TNN_9featureOnehot_CSLOG1_withValidation.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S4BFuDMZrEep"
      },
      "source": [
        "\n",
        "# **A Graph Neural Network as a Classifier for trees, using XRules dataset**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pZjPKR7Vad3q"
      },
      "source": [
        "# **Installing Dependencies**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7ZRRX8RQanA4"
      },
      "source": [
        "Installing torch_geometric library for GNN, and networkx library for checking if our custom graphs is created correctly.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n6BA7BP_XLWN",
        "outputId": "8141f6d6-4975-4de9-f79a-b3c9d6e53dfe"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting torch_geometric\n",
            "  Downloading torch_geometric-2.5.3-py3-none-any.whl (1.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from torch_geometric) (4.66.4)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from torch_geometric) (1.25.2)\n",
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            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->torch_geometric) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->torch_geometric) (2024.6.2)\n",
            "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->torch_geometric) (1.4.2)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->torch_geometric) (3.5.0)\n",
            "Installing collected packages: torch_geometric\n",
            "Successfully installed torch_geometric-2.5.3\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (3.3)\n"
          ]
        }
      ],
      "source": [
        "!pip install torch_geometric\n",
        "!pip install networkx"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2YGQXCwnbET6"
      },
      "source": [
        "# **Project Dataset File**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KzZ5jXNUbMfT"
      },
      "source": [
        "Using us1924.asc file from XRules real data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xogoiVl8cw7M"
      },
      "outputs": [],
      "source": [
        "# PROJECT_TRAIN_DATA='/content/drive/MyDrive/Graph-Neural-Network/Synth-Data/DS3.train.asc'\n",
        "# PROJECT_TEST_DATA='/content/drive/MyDrive/Graph-Neural-Network/Synth-Data/DS2.test.asc'\n",
        "PROJECT_TRAIN_DATA= '/content/drive/MyDrive/Graph-Neural-Network/Real-Data/cslog1/cslog1.asc'\n",
        "# PROJECT_TEST_DATA='/content/drive/MyDrive/Graph-Neural-Network/Real-Data/us2430/us2430.asc'"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aopdlKBRbyWz"
      },
      "source": [
        "Reading Data from PROJECT_DATA and storing the lines in trees list"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "zcZ5V2T9buKP"
      },
      "outputs": [],
      "source": [
        "train_file = open(PROJECT_TRAIN_DATA, 'r')\n",
        "train_trees = train_file.readlines()\n",
        "\n",
        "# test_file = open(PROJECT_TEST_DATA, 'r')\n",
        "# test_trees = test_file.readlines()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a6yDjeMAb4sW"
      },
      "source": [
        "# **Preprocessing Data and Creating Graph object for every Tree**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jE5Y205VpXMi",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3567c2e9-3838-4be4-db6c-2cf26a25f643"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-4-63af9e1b6255>:74: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
            "  embeddings = torch.tensor(final_nodes, dtype=torch.float)\n",
            "<ipython-input-4-63af9e1b6255>:81: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:274.)\n",
            "  edges = torch.tensor([rows, cols], dtype=torch.long)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[    0.],\n",
            "        [20349.],\n",
            "        [20354.],\n",
            "        [20368.]])\n",
            "tensor([[0, 1, 1],\n",
            "        [1, 2, 3]])\n",
            "8074\n"
          ]
        }
      ],
      "source": [
        "# importing necessary modules\n",
        "import numpy as np\n",
        "import torch\n",
        "import tensorflow as tf\n",
        "import torch_geometric.datasets as datasets\n",
        "import torch_geometric.data as data\n",
        "import torch_geometric.utils as utils\n",
        "from torch_geometric.data import Data\n",
        "import networkx as nx\n",
        "from torch_geometric.utils.convert import to_networkx\n",
        "import torch_geometric as tg\n",
        "\n",
        "train_dataset = []\n",
        "edu = 0\n",
        "\n",
        "\n",
        "\n",
        "for tree in train_trees:\n",
        "  # removing '\\n' from end of tree data\n",
        "  tree = tree.removesuffix('\\n')\n",
        "  # splitting each tree data by space\n",
        "  tree = tree.split(' ')\n",
        "  # the first entry is the tree label\n",
        "  tree_label = tree[0]\n",
        "\n",
        "  if tree_label == '1':\n",
        "    edu += 1\n",
        "  # the second entry is the tree id\n",
        "  tree_id = tree[1]\n",
        "  # the third entry is the tree sequence length\n",
        "  tree_len = tree[3]\n",
        "  # the rest is the tree sequence\n",
        "  tree_struct = tree[4:]\n",
        "\n",
        "  # a list for containing the nodes of each tree\n",
        "  nodes = []\n",
        "  # a stack for traversing the tree and getting the edges of graph\n",
        "  stack = []\n",
        "  # two lists for storing the edges in COO format\n",
        "  edges_row = []\n",
        "  edges_col = []\n",
        "  for s in tree_struct:\n",
        "    if s != '-1' and int(s) not in nodes:\n",
        "      nodes.append(int(s))\n",
        "\n",
        "  for s in tree_struct:\n",
        "    if s != '-1':\n",
        "      stack.append(int(s))\n",
        "      if len(stack) >= 2:\n",
        "        stack_len = len(stack)\n",
        "        edges_row.append(nodes.index(stack[stack_len - 2]))\n",
        "        edges_col.append(nodes.index(stack[stack_len - 1]))\n",
        "    else:\n",
        "      stack.pop()\n",
        "\n",
        "  node_array = []\n",
        "  for n in nodes:\n",
        "    temp = []\n",
        "    temp.append(n)\n",
        "    node_array.append(temp)\n",
        "  final_nodes = np.array(node_array)\n",
        "    # Assuming final_nodes is your existing tensor\n",
        "  final_nodes = torch.tensor(final_nodes, dtype=torch.float)\n",
        "\n",
        "  # Get the shape of the existing tensor\n",
        "  original_shape = final_nodes.shape\n",
        "\n",
        "  # Create a column vector of zeros with the same number of rows as final_nodes\n",
        "  zeros_column = torch.zeros(original_shape[0], 1)\n",
        "\n",
        "  # Concatenate the original tensor with the column of zeros along the second dimension (axis 1)\n",
        "  final_nodes_with_zeros = torch.cat([final_nodes, zeros_column], dim=1)\n",
        "  # embeddings = torch.tensor(final_nodes_with_zeros, dtype=torch.float)\n",
        "  embeddings = torch.tensor(final_nodes, dtype=torch.float)\n",
        "\n",
        "\n",
        "  y = torch.tensor([int(tree_label)])\n",
        "\n",
        "  rows = np.array(edges_row)\n",
        "  cols = np.array(edges_col)\n",
        "  edges = torch.tensor([rows, cols], dtype=torch.long)\n",
        "  undirected_edges = utils.to_undirected(edges)\n",
        "\n",
        "  # creating the DATA object based on embeddings and edges and adding it to the dataset list\n",
        "  train_dataset.append(Data(x=embeddings ,edge_index=edges, y=y))\n",
        "\n",
        "print(train_dataset[30]['x'])\n",
        "print(train_dataset[30]['edge_index'])\n",
        "# print(train_dataset[0].is_undirected())\n",
        "print(len(train_dataset))\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "calculating number of children of each node, normalization method 2"
      ],
      "metadata": {
        "id": "dZIFhP95jmld"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "aip6a40kDoxQ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5b3cea37-c4b0-4abe-8e34-da3e0615e2da"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "8074\n",
            "5\n",
            "[1. 0. 0. ... 0. 0. 0.]\n",
            "9061\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "import torch\n",
        "\n",
        "\n",
        "# Step 1: Extract unique features for both features\n",
        "unique_features1 = set()\n",
        "# unique_features2 = set()\n",
        "for graph in train_dataset:\n",
        "    for node in graph['x']:\n",
        "        unique_features1.add(node[0].item())  # Convert tensor to Python float\n",
        "        # unique_features2.add(node[1].item())  # Convert tensor to Python float\n",
        "\n",
        "# Step 2: Create dictionaries mapping features to integer indices for both features\n",
        "feature_to_index1 = {feature: i for i, feature in enumerate(unique_features1)}\n",
        "# feature_to_index2 = {feature: i for i, feature in enumerate(unique_features2)}\n",
        "\n",
        "# Step 3: Apply one-hot encoding for both features\n",
        "encoded_data = []\n",
        "for graph in train_dataset:\n",
        "    encoded_graph = []\n",
        "    for node in graph['x']:\n",
        "        # Create one-hot encoded vectors for both features\n",
        "        one_hot_vector1 = np.zeros(len(unique_features1))\n",
        "        # one_hot_vector2 = np.zeros(len(unique_features2))\n",
        "        feature_index1 = feature_to_index1[node[0].item()]  # Convert tensor to Python float\n",
        "        # feature_index2 = feature_to_index2[node[1].item()]  # Convert tensor to Python float\n",
        "        one_hot_vector1[feature_index1] = 1\n",
        "        # one_hot_vector2[feature_index2] = 1\n",
        "        # Concatenate one-hot vectors for both features\n",
        "        # encoded_node = np.concatenate([one_hot_vector1, one_hot_vector2])\n",
        "        # encoded_graph.append(encoded_node)\n",
        "        encoded_graph.append(one_hot_vector1)\n",
        "    encoded_data.append(encoded_graph)\n",
        "\n",
        "# Now, encoded_data contains your dataset with one-hot encoded features for both feature1 and feature2\n",
        "print(len(encoded_data))\n",
        "print(len(train_dataset[32].x))\n",
        "print(encoded_data[32][0])\n",
        "print(len(encoded_data[32][0]))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wW3EFeyimag0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ae22f3f4-ac35-4e0d-e1dc-9ea435bac7ea"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Data(x=[5, 1], edge_index=[2, 4], y=[1])\n",
            "tensor([[    0.],\n",
            "        [12811.],\n",
            "        [20351.],\n",
            "        [37409.],\n",
            "        [37411.]])\n",
            "tensor([[0, 1, 0, 3],\n",
            "        [1, 2, 3, 4]])\n",
            "tensor([1])\n",
            "<bound method BaseData.is_undirected of Data(x=[5, 1], edge_index=[2, 4], y=[1])>\n",
            "<class 'numpy.ndarray'>\n",
            "8074\n",
            "Data(x=[5, 9061], edge_index=[2, 4], y=[1])\n",
            "tensor([[1., 0., 0.,  ..., 0., 0., 0.],\n",
            "        [0., 0., 0.,  ..., 0., 0., 0.],\n",
            "        [0., 0., 0.,  ..., 0., 0., 0.],\n",
            "        [0., 0., 0.,  ..., 0., 0., 0.],\n",
            "        [0., 0., 0.,  ..., 0., 0., 0.]])\n",
            "tensor([[0, 1, 0, 3],\n",
            "        [1, 2, 3, 4]])\n",
            "tensor([1])\n",
            "<bound method BaseData.is_undirected of Data(x=[5, 9061], edge_index=[2, 4], y=[1])>\n"
          ]
        }
      ],
      "source": [
        "print(train_dataset[32])\n",
        "print(train_dataset[32].x)\n",
        "print(train_dataset[32].edge_index)\n",
        "print(train_dataset[32].y)\n",
        "print(train_dataset[32].is_undirected)\n",
        "\n",
        "final_train_dataset = []\n",
        "print(type(encoded_data[32][0]))\n",
        "for i in range(0, len(train_dataset)):\n",
        "  graph = train_dataset[i]\n",
        "  embeddings = []\n",
        "  for j in range(0, len(graph['x'])):\n",
        "    # Concatenate 492 zeros to the array\n",
        "    # num_zeros = 491\n",
        "    num_zeros = 0\n",
        "    zeros_to_concatenate = np.zeros(num_zeros)\n",
        "    concatenated_array = np.concatenate([encoded_data[i][j], zeros_to_concatenate])\n",
        "    embeddings.append(concatenated_array)\n",
        "  final_embeddings = torch.tensor(embeddings, dtype=torch.float)\n",
        "  final_train_dataset.append(Data(x=final_embeddings ,edge_index=graph.edge_index, y=graph.y))\n",
        "\n",
        "print(len(final_train_dataset))\n",
        "print(final_train_dataset[32])\n",
        "print(final_train_dataset[32].x)\n",
        "print(final_train_dataset[32].edge_index)\n",
        "print(final_train_dataset[32].y)\n",
        "print(final_train_dataset[32].is_undirected)\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "from torch_geometric.data import Data\n",
        "\n",
        "\n",
        "# Step 1: Compute the number of children for each node in each graph\n",
        "def compute_num_children(data):\n",
        "    num_nodes = data.x.size(0)\n",
        "    num_children = torch.zeros(num_nodes)\n",
        "    for edge in data.edge_index.T:\n",
        "        parent, child = edge\n",
        "        num_children[parent] += 1\n",
        "    return num_children\n",
        "\n",
        "# Step 2: Calculate the global sum of the number of children across all graphs\n",
        "global_sum = 0.0\n",
        "\n",
        "num_children_list = []\n",
        "\n",
        "for data in final_train_dataset:\n",
        "    num_children = compute_num_children(data)\n",
        "    num_children_list.append(num_children)\n",
        "    global_sum += num_children.sum().item()\n",
        "\n",
        "print(f\"Global sum of node children: {global_sum}\")\n",
        "\n",
        "\n",
        "# Step 3: Normalize the number of children and add as a node feature\n",
        "def normalize_and_add_feature(data, global_sum):\n",
        "    num_children = compute_num_children(data)\n",
        "    if global_sum > 0:  # Avoid division by zero\n",
        "        num_children = num_children / global_sum\n",
        "    else:\n",
        "        num_children = torch.zeros_like(num_children)  # All nodes have the same number of children\n",
        "    num_children = num_children.view(-1, 1)\n",
        "    data.x = torch.cat([data.x, num_children], dim=1)\n",
        "    return data\n",
        "\n",
        "# Apply normalization and add the feature to each graph in the dataset\n",
        "final_train_dataset = [normalize_and_add_feature(data, global_sum) for data in final_train_dataset]\n",
        "\n",
        "# Verify the updated node features for a sample graph\n",
        "print(final_train_dataset[30].x)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LDykseMGqKp3",
        "outputId": "797ebb55-71d2-43d3-eb14-1c30454120f5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Global sum of node children: 56789.0\n",
            "tensor([[1.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00, 0.0000e+00,\n",
            "         1.7609e-05],\n",
            "        [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00, 0.0000e+00,\n",
            "         3.5218e-05],\n",
            "        [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00, 0.0000e+00,\n",
            "         0.0000e+00],\n",
            "        [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00, 0.0000e+00,\n",
            "         0.0000e+00]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "calculating number of children of each node, normalization method 1"
      ],
      "metadata": {
        "id": "cNwNhOjmjiBM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "calculating number of children of each node, no normaliztion\n",
        "\n"
      ],
      "metadata": {
        "id": "LalggFbIjQin"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "from torch_geometric.data import Data\n",
        "from collections import deque\n",
        "\n",
        "# Define a function to compute the depth of each node\n",
        "def compute_node_depth(data):\n",
        "    num_nodes = data.x.size(0)\n",
        "    depth = -torch.ones(num_nodes)  # Initialize depths with -1\n",
        "    depth[0] = 0  # Assume node 0 is the root\n",
        "    queue = deque([0])\n",
        "\n",
        "    while queue:\n",
        "        node = queue.popleft()\n",
        "        current_depth = depth[node]\n",
        "        for neighbor in data.edge_index[1][data.edge_index[0] == node]:\n",
        "            if depth[neighbor] == -1:  # If the node is unvisited\n",
        "                depth[neighbor] = current_depth + 1\n",
        "                queue.append(neighbor)\n",
        "\n",
        "    return depth\n",
        "\n",
        "# Function to add depth as the third node feature\n",
        "def add_node_depth_feature(data):\n",
        "    depth = compute_node_depth(data)\n",
        "    depth = depth.view(-1, 1)\n",
        "    data.x = torch.cat([data.x, depth], dim=1)\n",
        "    return data\n",
        "\n",
        "# Apply the function to the dataset\n",
        "final_train_dataset = [add_node_depth_feature(data) for data in final_train_dataset]\n",
        "\n",
        "# Verify the updated node features for a sample graph\n",
        "print(final_train_dataset[30].x)\n"
      ],
      "metadata": {
        "id": "sI3ZNnibHXG-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e9dbf436-ba0a-43d8-981e-6000ea165905"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[1.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00, 1.7609e-05,\n",
            "         0.0000e+00],\n",
            "        [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00, 3.5218e-05,\n",
            "         1.0000e+00],\n",
            "        [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00, 0.0000e+00,\n",
            "         2.0000e+00],\n",
            "        [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00, 0.0000e+00,\n",
            "         2.0000e+00]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Function to add root indicator as the fourth node feature\n",
        "def add_root_indicator_feature(data):\n",
        "    num_nodes = data.x.size(0)\n",
        "    root_indicator = torch.zeros(num_nodes)\n",
        "    root_indicator[0] = 1  # Assume node 0 is the root\n",
        "    root_indicator = root_indicator.view(-1, 1)\n",
        "    data.x = torch.cat([data.x, root_indicator], dim=1)\n",
        "    return data\n",
        "\n",
        "# Apply the function to the dataset\n",
        "final_train_dataset = [add_root_indicator_feature(data) for data in final_train_dataset]\n",
        "\n",
        "# Verify the updated node features for a sample graph\n",
        "print(final_train_dataset[0].x)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lVpFB-YzsmO6",
        "outputId": "8a8f4195-1f1c-4c3b-e940-3c6ab2967d73"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[1.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 1.7609e-05, 0.0000e+00,\n",
            "         1.0000e+00],\n",
            "        [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 1.7609e-05, 1.0000e+00,\n",
            "         0.0000e+00],\n",
            "        [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 1.7609e-05, 2.0000e+00,\n",
            "         0.0000e+00],\n",
            "        [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00, 3.0000e+00,\n",
            "         0.0000e+00]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Function to add leaf indicator as the fifth node feature\n",
        "def add_leaf_indicator_feature(data):\n",
        "    num_nodes = data.x.size(0)\n",
        "    leaf_indicator = torch.ones(num_nodes)\n",
        "\n",
        "    for parent in data.edge_index[0]:\n",
        "        leaf_indicator[parent] = 0\n",
        "\n",
        "    leaf_indicator = leaf_indicator.view(-1, 1)\n",
        "    data.x = torch.cat([data.x, leaf_indicator], dim=1)\n",
        "    return data\n",
        "\n",
        "# Apply the function to the dataset\n",
        "final_train_dataset = [add_leaf_indicator_feature(data) for data in final_train_dataset]\n",
        "\n",
        "# Verify the updated node features for a sample graph\n",
        "print(final_train_dataset[0].x)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UzB3Ys61xQuX",
        "outputId": "f3d6f6a3-f10e-4862-ab8a-51a973659579"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[1., 0., 0.,  ..., 0., 1., 0.],\n",
            "        [0., 0., 0.,  ..., 1., 0., 0.],\n",
            "        [0., 0., 0.,  ..., 2., 0., 0.],\n",
            "        [0., 0., 0.,  ..., 3., 0., 1.]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Function to add the degree of each node as the sixth feature\n",
        "def add_degree_feature(data):\n",
        "    num_nodes = data.x.size(0)\n",
        "    degree = torch.zeros(num_nodes)\n",
        "\n",
        "    for node in data.edge_index[0]:\n",
        "        degree[node] += 1\n",
        "\n",
        "    degree = degree.view(-1, 1)\n",
        "    data.x = torch.cat([data.x, degree], dim=1)\n",
        "    return data\n",
        "\n",
        "# Apply the function to the dataset\n",
        "final_train_dataset = [add_degree_feature(data) for data in final_train_dataset]\n",
        "\n",
        "# Verify the updated node features for a sample graph\n",
        "print(final_train_dataset[30].x)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Jr4_YOBR4sUd",
        "outputId": "fd6df189-7a9d-4f42-c405-e0efa6c0ba32"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[1., 0., 0.,  ..., 1., 0., 1.],\n",
            "        [0., 0., 0.,  ..., 0., 0., 2.],\n",
            "        [0., 0., 0.,  ..., 0., 1., 0.],\n",
            "        [0., 0., 0.,  ..., 0., 1., 0.]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import networkx as nx\n",
        "from torch_geometric.utils import to_networkx\n",
        "\n",
        "# Function to add betweenness centrality as the seventh feature\n",
        "def add_betweenness_centrality_feature(data):\n",
        "    G = to_networkx(data, to_undirected=True)\n",
        "    betweenness = nx.betweenness_centrality(G)\n",
        "    betweenness_tensor = torch.tensor([betweenness[i] for i in range(len(betweenness))])\n",
        "\n",
        "    betweenness_tensor = betweenness_tensor.view(-1, 1)\n",
        "    data.x = torch.cat([data.x, betweenness_tensor], dim=1)\n",
        "    return data\n",
        "\n",
        "# Apply the function to the dataset\n",
        "final_train_dataset = [add_betweenness_centrality_feature(data) for data in final_train_dataset]\n",
        "\n",
        "# Verify the updated node features for a sample graph\n",
        "print(final_train_dataset[0].x)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jSlTh__YAgMy",
        "outputId": "3e78c648-1382-4f7d-f94d-695e6e46c49a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[1.0000, 0.0000, 0.0000,  ..., 0.0000, 1.0000, 0.0000],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 0.0000, 1.0000, 0.6667],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 0.0000, 1.0000, 0.6667],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 1.0000, 0.0000, 0.0000]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Function to compute the average path length for each node\n",
        "def compute_average_path_length(data):\n",
        "    G = to_networkx(data, to_undirected=True)\n",
        "    length = dict(nx.all_pairs_shortest_path_length(G))\n",
        "\n",
        "    avg_path_length = torch.zeros(data.x.size(0))\n",
        "    for node, paths in length.items():\n",
        "        avg_path_length[node] = sum(paths.values()) / (len(paths) - 1)\n",
        "\n",
        "    return avg_path_length\n",
        "\n",
        "# Function to add average path length as the eighth feature\n",
        "def add_avg_path_length_feature(data):\n",
        "    avg_path_length = compute_average_path_length(data)\n",
        "    avg_path_length = avg_path_length.view(-1, 1)\n",
        "    data.x = torch.cat([data.x, avg_path_length], dim=1)\n",
        "    return data\n",
        "\n",
        "# Apply the function to the dataset\n",
        "final_train_dataset = [add_avg_path_length_feature(data) for data in final_train_dataset]\n",
        "\n",
        "# Verify the updated node features for a sample graph\n",
        "print(final_train_dataset[0].x)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qvjv9DhXK51f",
        "outputId": "9761b422-9d2b-46fe-921e-9f32e07ebff3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[1.0000, 0.0000, 0.0000,  ..., 1.0000, 0.0000, 2.0000],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 1.0000, 0.6667, 1.3333],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 1.0000, 0.6667, 1.3333],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 2.0000]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "from torch_geometric.data import Data\n",
        "\n",
        "# Function to compute the subtree size (scope) of each node\n",
        "def compute_subtree_size(data):\n",
        "    num_nodes = data.x.size(0)\n",
        "    subtree_size = torch.ones(num_nodes)  # Initialize with 1 to count the node itself\n",
        "\n",
        "    # Create adjacency list\n",
        "    adjacency_list = [[] for _ in range(num_nodes)]\n",
        "    for edge in data.edge_index.T:\n",
        "        parent, child = edge\n",
        "        adjacency_list[parent.item()].append(child.item())\n",
        "\n",
        "    # Function to recursively calculate subtree size\n",
        "    def dfs(node):\n",
        "        size = 1\n",
        "        for child in adjacency_list[node]:\n",
        "            size += dfs(child)\n",
        "        subtree_size[node] = size\n",
        "        return size\n",
        "\n",
        "    # Assuming node 0 is the root\n",
        "    dfs(0)\n",
        "\n",
        "    return subtree_size\n",
        "\n",
        "# Function to add subtree size (scope) as the ninth node feature\n",
        "def add_subtree_size_feature(data):\n",
        "    subtree_size = compute_subtree_size(data)\n",
        "    subtree_size = subtree_size.view(-1, 1)\n",
        "    data.x = torch.cat([data.x, subtree_size], dim=1)\n",
        "    return data\n",
        "\n",
        "# Apply the function to the dataset\n",
        "# final_train_dataset = [add_subtree_size_feature(data) for data in final_train_dataset]\n",
        "\n",
        "# Verify the updated node features for a sample graph\n",
        "print(final_train_dataset[0].x)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "opO8C7syTxM5",
        "outputId": "526b1278-b863-4147-b51b-2724e7f8173a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tensor([[1.0000, 0.0000, 0.0000,  ..., 1.0000, 0.0000, 2.0000],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 1.0000, 0.6667, 1.3333],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 1.0000, 0.6667, 1.3333],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 2.0000]])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "08SZVdgqLD8T",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4defc69e-2ee2-4aa7-ae40-483f2b08aaa3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "9068\n",
            "tensor([[1.0000, 0.0000, 0.0000,  ..., 1.0000, 0.0000, 1.6667],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 2.0000, 1.0000, 1.0000],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 1.6667],\n",
            "        [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 1.6667]])\n"
          ]
        }
      ],
      "source": [
        "print(len(final_train_dataset[30]['x'][0]))\n",
        "print(final_train_dataset[30]['x'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eqyIyTCVGhD3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "outputId": "379f54da-1477-4842-eb11-461771f11d41"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import networkx as nx\n",
        "\n",
        "# importing matplotlib.pyplot\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "vis = to_networkx(final_train_dataset[30])\n",
        "\n",
        "\n",
        "\n",
        "nx.draw_networkx(vis)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "udKLfOYQkBXw"
      },
      "source": [
        "# **Training and Testing a GNN model**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0RRTv3YBj0HU"
      },
      "source": [
        "Breaking data to trainset (80% of data) and testset (20% of data), also breaking each set to batches with size=128\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1zkTOIjDkMSi"
      },
      "source": [
        "Creating a model: a Graph Convlotional Network with 3 layers"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-4BrTfLSk9PG"
      },
      "source": [
        "Training and testing data in 50 epochs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4ILMUiTx-SRz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e718701f-6c2e-447c-ffc1-e5d2d2580421"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 010, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 011, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7460\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7760\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7900\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7680\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 010, Valid Acc: 0.7700\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8080\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 010, Valid Acc: 0.7720\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7680\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7880\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7780\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8100\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 010, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 011, Valid Acc: 0.7860\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8080\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7640\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7740\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8100\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7780\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8080\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7880\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7840\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7640\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7840\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7880\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7540\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8080\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7780\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8100\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7720\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7640\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7720\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.6, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7760\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7260\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7860\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7600\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7880\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7640\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7900\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7700\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7700\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7680\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7640\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7880\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7740\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7680\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7880\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7680\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7840\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7780\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8080\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7860\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8100\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7740\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8120\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 010, Valid Acc: 0.7740\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7920\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7880\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7760\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8080\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7720\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8080\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8080\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7780\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7680\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7680\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7720\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7660\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7640\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7760\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.65, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7780\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7880\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7900\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7440\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7460\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7760\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7640\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7680\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7740\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8040\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7640\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.3, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7840\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7840\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7780\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7580\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7760\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7340\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8080\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7760\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7660\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7580\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7880\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7680\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7880\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7620\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0.5, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7900\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7240\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8100\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7740\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8000\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8140\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 010, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 011, Valid Acc: 0.7760\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.8080\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7940\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7800\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8020\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7780\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7760\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7820\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 64, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7740\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8140\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7980\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7840\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7740\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7760\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 3, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7720\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7880\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7800\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7700\n",
            "Early stopping!\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 000, Valid Acc: 0.8060\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 001, Valid Acc: 0.7960\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 002, Valid Acc: 0.7920\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 003, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 004, Valid Acc: 0.7860\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 005, Valid Acc: 0.7700\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 006, Valid Acc: 0.7680\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 007, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 008, Valid Acc: 0.7900\n",
            "Params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 128, 'learning_rate': 0.01, 'number_of_hops': 5, 'weight_decay': 0}, Epoch: 009, Valid Acc: 0.7820\n",
            "Early stopping!\n",
            "Best params: {'decay_factor': 0.55, 'dropout': 0, 'hidden_channels': 32, 'learning_rate': 0.01, 'number_of_hops': 4, 'weight_decay': 0}, Best Valid Acc: 0.8140\n",
            "Ensemble Test Acc: 0.8278\n"
          ]
        }
      ],
      "source": [
        "import torch\n",
        "from torch.nn import Linear, Dropout\n",
        "from torch_geometric.nn import global_mean_pool, MessagePassing\n",
        "from torch_geometric.utils import add_self_loops, degree\n",
        "import torch.nn.functional as F\n",
        "from torch_geometric.loader import DataLoader\n",
        "from sklearn.model_selection import ParameterGrid\n",
        "from torch.optim.lr_scheduler import StepLR\n",
        "\n",
        "# Assuming final_train_dataset is already defined\n",
        "train_loader = DataLoader(final_train_dataset[:6000], batch_size=128, shuffle=True)\n",
        "valid_loader = DataLoader(final_train_dataset[6000:6500], batch_size=128, shuffle=False)\n",
        "test_loader = DataLoader(final_train_dataset[6500:], batch_size=128, shuffle=False)\n",
        "\n",
        "class EnhancedCustomGCNConv(MessagePassing):\n",
        "    def __init__(self, in_channels, out_channels, decay_factor=0.5, number_of_hops=4):\n",
        "        super(EnhancedCustomGCNConv, self).__init__(aggr='add')\n",
        "        self.in_channels = in_channels\n",
        "        self.out_channels = out_channels\n",
        "        self.decay_factor = decay_factor\n",
        "        self.number_of_hops = number_of_hops\n",
        "        self.lin = Linear(in_channels, out_channels)\n",
        "\n",
        "    def forward(self, x, edge_index):\n",
        "        edge_index, _ = add_self_loops(edge_index, num_nodes=x.size(0))\n",
        "        x = self.lin(x)\n",
        "        row, col = edge_index\n",
        "        deg = degree(row, x.size(0), dtype=x.dtype)\n",
        "        deg_inv_sqrt = deg.pow(-0.5)\n",
        "        norm = deg_inv_sqrt[row] * deg_inv_sqrt[col]\n",
        "        x_final = torch.zeros_like(x)\n",
        "        x_degree = x\n",
        "        for hop in range(1, self.number_of_hops):\n",
        "            x_degree = self.propagate(edge_index, x=x_degree, norm=norm)\n",
        "            x_final += (self.decay_factor ** hop) * x_degree\n",
        "        return x_final\n",
        "\n",
        "    def message(self, x_j, norm):\n",
        "        return norm.view(-1, 1) * x_j\n",
        "\n",
        "    def update(self, aggr_out):\n",
        "        return aggr_out\n",
        "\n",
        "    def __repr__(self):\n",
        "        return f'{self.__class__.__name__}(in_channels={self.in_channels}, out_channels={self.out_channels}, decay_factor={self.decay_factor})'\n",
        "\n",
        "class GCN(torch.nn.Module):\n",
        "    def __init__(self, hidden_channels=64, decay_factor=0.6, dropout=0.5, number_of_hops=4):\n",
        "        super(GCN, self).__init__()\n",
        "        torch.manual_seed(12345)\n",
        "        self.conv1 = EnhancedCustomGCNConv(len(final_train_dataset[0]['x'][0]), hidden_channels, decay_factor, number_of_hops)\n",
        "        self.conv2 = EnhancedCustomGCNConv(hidden_channels, hidden_channels, decay_factor, number_of_hops)\n",
        "        self.conv3 = EnhancedCustomGCNConv(hidden_channels, hidden_channels, decay_factor, number_of_hops)\n",
        "        self.lin = Linear(hidden_channels, 2)\n",
        "        self.dropout = Dropout(p=dropout)\n",
        "\n",
        "    def forward(self, x, edge_index, batch):\n",
        "        x = self.conv1(x, edge_index)\n",
        "        x = x.relu()\n",
        "        x = self.dropout(x)\n",
        "        x = self.conv2(x, edge_index)\n",
        "        x = x.relu()\n",
        "        x = self.dropout(x)\n",
        "        x = self.conv3(x, edge_index)\n",
        "        x = x.relu()\n",
        "        x = global_mean_pool(x, batch)\n",
        "        x = self.lin(x)\n",
        "        return x\n",
        "\n",
        "def augment_data(dataset):\n",
        "    augmented_data = []\n",
        "    for data in dataset:\n",
        "        perturbed_data = data.clone()\n",
        "        perturbed_data.x += 0.01 * torch.randn_like(perturbed_data.x)\n",
        "        augmented_data.append(perturbed_data)\n",
        "    return augmented_data\n",
        "\n",
        "# Training and testing functions\n",
        "def train(model, optimizer, criterion):\n",
        "    model.train()\n",
        "    for data in train_loader:\n",
        "        optimizer.zero_grad()\n",
        "        out = model(data.x, data.edge_index, data.batch)\n",
        "        loss = criterion(out, data.y)\n",
        "        loss.backward()\n",
        "        optimizer.step()\n",
        "\n",
        "def test(model, loader):\n",
        "    model.eval()\n",
        "    correct = 0\n",
        "    for data in loader:\n",
        "        out = model(data.x, data.edge_index, data.batch)\n",
        "        pred = out.argmax(dim=1)\n",
        "        correct += int((pred == data.y).sum())\n",
        "    return correct / len(loader.dataset)\n",
        "\n",
        "param_grid = {\n",
        "    'hidden_channels': [32,64,128],\n",
        "    'number_of_hops': [3,4,5],\n",
        "    'decay_factor': [0.6, 0.65, 0.55],\n",
        "    'learning_rate': [0.01],\n",
        "    'weight_decay': [0],\n",
        "    'dropout': [0.3, 0.5, 0]\n",
        "}\n",
        "\n",
        "save_path = '/content/drive/MyDrive/Graph-Neural-Network/modelsParams/CSLOG1-1/threeLayerEnhancedCustomGCNConv-directed-64-withCycle-withoutDropOut-oneHotEncoded-batchSize128-decayFactor0.5-lr0.01.pth'\n",
        "\n",
        "best_valid_acc = 0\n",
        "patience = 10\n",
        "\n",
        "for params in ParameterGrid(param_grid):\n",
        "    model = GCN(hidden_channels=params['hidden_channels'], decay_factor=params['decay_factor'], dropout=params['dropout'], number_of_hops=params['number_of_hops'])\n",
        "    optimizer = torch.optim.Adam(model.parameters(), lr=params['learning_rate'], weight_decay=params['weight_decay'])\n",
        "    criterion = torch.nn.CrossEntropyLoss()\n",
        "\n",
        "    trigger_times = 0\n",
        "    for epoch in range(50):\n",
        "        train(model, optimizer, criterion)\n",
        "        valid_acc = test(model, valid_loader)\n",
        "\n",
        "        if valid_acc > best_valid_acc:\n",
        "            best_valid_acc = valid_acc\n",
        "            best_params = params\n",
        "            torch.save(model.state_dict(), save_path)\n",
        "            trigger_times = 0\n",
        "        else:\n",
        "            trigger_times += 1\n",
        "\n",
        "        print(f'Params: {params}, Epoch: {epoch:03d}, Valid Acc: {valid_acc:.4f}')\n",
        "\n",
        "        if trigger_times >= patience:\n",
        "            print('Early stopping!')\n",
        "            break\n",
        "\n",
        "print(f'Best params: {best_params}, Best Valid Acc: {best_valid_acc:.4f}')\n",
        "\n",
        "# Load best model and test\n",
        "best_model = GCN(hidden_channels=best_params['hidden_channels'], decay_factor=best_params['decay_factor'], dropout=best_params['dropout'], number_of_hops=best_params['number_of_hops'])\n",
        "best_model.load_state_dict(torch.load(save_path))\n",
        "\n",
        "def ensemble_test(models, loader):\n",
        "    for model in models:\n",
        "        model.eval()\n",
        "    correct = 0\n",
        "    for data in loader:\n",
        "        outputs = [model(data.x, data.edge_index, data.batch) for model in models]\n",
        "        out = torch.mean(torch.stack(outputs), dim=0)\n",
        "        pred = out.argmax(dim=1)\n",
        "        correct += int((pred == data.y).sum())\n",
        "    return correct / len(loader.dataset)\n",
        "\n",
        "# Create ensemble of best models\n",
        "models = [GCN(hidden_channels=best_params['hidden_channels'], decay_factor=best_params['decay_factor'], dropout=best_params['dropout'], number_of_hops=best_params['number_of_hops']) for _ in range(5)]\n",
        "for model in models:\n",
        "    model.load_state_dict(torch.load(save_path))\n",
        "\n",
        "ensemble_test_acc = ensemble_test(models, test_loader)\n",
        "print(f'Ensemble Test Acc: {ensemble_test_acc:.4f}')\n"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}