Tutorial 07 - Introduction to Graph Neural Networks.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1kYQluqhHtCD"
      },
      "source": [
        "# Tutorial 7 - Intro to GNNs"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YbwQBzTcHtCF"
      },
      "source": [
        "\n",
        "\n",
        "- You will implement and train a basic GNN  to do vertex classification on the Cora dataset.\n",
        "- You will implement  **your own** GraphSAGE (with mean/sum/max aggregation) message passing scheme as the core mechanism of your GNN.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Please visit [this github page](https://github.com/sw-gong/GNN-Tutorial/blob/master/GNN-tutorial-solution.ipynb) for the solutions."
      ],
      "metadata": {
        "id": "jWE0OZjLa7Mb"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q4423rvpHtCG"
      },
      "source": [
        "## Setting up working environment\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "background_save": true
        },
        "id": "_u2t8HyHHtCG"
      },
      "outputs": [],
      "source": [
        "!pip install torch torchvision\n",
        "!pip install torch-scatter torch-sparse torch-geometric"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Rm1Eog5QHtCH"
      },
      "source": [
        "## Pytorch Geometric Framework\n",
        "\n",
        "#### Generic Message Passing Scheme\n",
        "Generalizing the convolution operator to irregular domains is typically expressed as a *neighborhood aggregation* or *message passing* scheme.\n",
        "With $\\mathbf{x}^{(k-1)}_i \\in \\mathbb{R}^F$ denoting node features of node $i$ in layer $(k-1)$ and $\\mathbf{e}_{i,j} \\in \\mathbb{R}^D$ denoting (optional) edge features from node $i$ to node $j$, message passing graph neural networks can be described as\n",
        "\n",
        "$$\n",
        "  \\mathbf{x}_i^{(k)} = \\gamma^{(k)} \\left( \\mathbf{x}_i^{(k-1)}, \\square_{j \\in \\mathcal{N}(i)} \\, \\phi^{(k)}\\left(\\mathbf{x}_i^{(k-1)}, \\mathbf{x}_j^{(k-1)},\\mathbf{e}_{i,j}\\right) \\right)\n",
        "$$\n",
        "\n",
        "where $\\square$ denotes a differentiable, permutation invariant function, *e.g.*, sum, mean or max, and $\\gamma$ and $\\phi$ denote differentiable functions such as MLPs (Multi Layer Perceptrons).\n",
        "\n",
        "#### Graph data representations in PyG\n",
        "Given a *sparse* **Graph** $\\mathcal{G}=(\\mathbf{X}, (\\mathbf{I}, \\mathbf{E}))$ with **node features** $\\mathbf{X} \\in \\mathbb{R}^{|V| \\times F}$, **edge indices $\\mathbf{I} \\in \\{1, \\cdots, N\\}^{2 \\times |\\mathcal{E}|}$**, (optional) **edge features** $\\mathbf{E} \\in \\mathbb{R}^{|\\mathcal{E} \\times D|}$, it is described by an instance of class `torch_geometric.data.Data`, which holds the corresponding attributes.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Kv-G5MZ6HtCH"
      },
      "outputs": [],
      "source": [
        "import torch\n",
        "from torch_geometric.data import Data\n",
        "\n",
        "edge_index = torch.tensor([[1, 2, 3], [0, 0, 0]], dtype=torch.long)\n",
        "x = torch.tensor([[1], [1], [1]], dtype=torch.float)\n",
        "\n",
        "data = Data(edge_index=edge_index, x=x)\n",
        "data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Xu40n_WdHtCI"
      },
      "source": [
        "#### Abstract Message Passing Scheme in PyG\n",
        "\n",
        "PyTorch Geometric provides the `torch_geometric.nn.MessagePassing` base class, which helps in creating such kinds of message passing graph neural networks by automatically taking care of message propagation. The implementation is decoupled into **UPDATE**, **AGGREGATION**, **MESSAGE** functions as:\n",
        "$$\n",
        "    \\mathbf{x}_i^{(k)} = \\mathrm{UPDATE} \\left( \\mathbf{x}_i^{(k-1)},  \\mathrm{AGGR}_{j \\in \\mathcal{N}(i)} \\, \\mathrm{MESSAGE}^{(k)}\\left(\\mathbf{x}_i^{(k-1)}, \\mathbf{x}_j^{(k-1)},\\mathbf{e}_{i,j}\\right) \\right)    \n",
        "$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "buvcF_ffHtCJ"
      },
      "source": [
        "#### Implementing GraphSAGE\n",
        "\n",
        "The algorithm of GraphSAGE (*Inductive Representation Learning on Large Graphs (NIPS 2017)* embedding generation is described as:\n",
        "\n",
        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)\n",
        "\n",
        "\n",
        "You are required to implement this algortihm with **MEAN/SUM/MAX** AGGREGATE."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9sqyU941HtCJ"
      },
      "outputs": [],
      "source": [
        "import math\n",
        "import torch\n",
        "import torch.nn.functional as F\n",
        "from torch.nn import Parameter\n",
        "from torch_geometric.nn.conv import MessagePassing\n",
        "\n",
        "def uniform(size, tensor):\n",
        "    bound = 1.0 / math.sqrt(size)\n",
        "    if tensor is not None:\n",
        "        tensor.data.uniform_(-bound, bound)\n",
        "\n",
        "\n",
        "class SAGEConv(MessagePassing):\n",
        "    def __init__(self, in_channels, out_channels, aggr):\n",
        "        super(SAGEConv, self).__init__(aggr=aggr)\n",
        "\n",
        "        self.in_channels = in_channels\n",
        "        self.out_channels = out_channels\n",
        "\n",
        "        self.weight = Parameter(torch.Tensor(2 * in_channels, out_channels))\n",
        "\n",
        "        self.reset_parameters()\n",
        "\n",
        "    def reset_parameters(self):\n",
        "        uniform(self.weight.size(0), self.weight)\n",
        "\n",
        "    def forward(self, x, edge_index):\n",
        "\n",
        "        ########################################################################\n",
        "        #      START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)             #\n",
        "        ########################################################################\n",
        "        pass\n",
        "\n",
        "        ########################################################################\n",
        "        #                             END OF YOUR CODE                         #\n",
        "        ########################################################################\n",
        "\n",
        "\n",
        "\n",
        "    def message(self, x_j, edge_weight):\n",
        "\n",
        "        ########################################################################\n",
        "        #      START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)             #\n",
        "        ########################################################################\n",
        "        pass\n",
        "\n",
        "        ########################################################################\n",
        "        #                             END OF YOUR CODE                         #\n",
        "        ########################################################################\n",
        "\n",
        "\n",
        "\n",
        "    def update(self, aggr_out, x):\n",
        "\n",
        "        ########################################################################\n",
        "        #      START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)             #\n",
        "        ########################################################################\n",
        "        pass\n",
        "\n",
        "        ########################################################################\n",
        "        #                             END OF YOUR CODE                         #\n",
        "        ########################################################################\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f_lv1XPqHtCJ"
      },
      "source": [
        "## Vertex Classification\n",
        "\n",
        "The Cora dataset consists of 2708 scientific publications classified into one of seven classes. The citation network consists of 5429 links. Each publication in the dataset is described by a 0/1-valued word vector indicating the absence/presence of the corresponding word from the dictionary."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "NQTYIpBnHtCK"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "import os.path as osp\n",
        "import torch\n",
        "import torch.nn.functional as F\n",
        "from torch_geometric.datasets import Planetoid\n",
        "import torch_geometric.transforms as T\n",
        "\n",
        "path = osp.join(os.getcwd(), 'data', 'Cora')\n",
        "dataset = Planetoid(path, 'Cora')\n",
        "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "bbf_19-VHtCL"
      },
      "outputs": [],
      "source": [
        "class SAGENet(torch.nn.Module):\n",
        "    def __init__(self, dataset, aggr='mean'):\n",
        "        super(SAGENet, self).__init__()\n",
        "\n",
        "        ########################################################################\n",
        "        #      START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)             #\n",
        "        ########################################################################\n",
        "        pass\n",
        "\n",
        "\n",
        "        ########################################################################\n",
        "        #                             END OF YOUR CODE                         #\n",
        "        ########################################################################\n",
        "\n",
        "        self.reset_parameters()\n",
        "\n",
        "\n",
        "    def reset_parameters(self):\n",
        "        self.conv1.reset_parameters()\n",
        "        self.conv2.reset_parameters()\n",
        "\n",
        "    def forward(self, data):\n",
        "\n",
        "        ########################################################################\n",
        "        #      START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)             #\n",
        "        ########################################################################\n",
        "        pass\n",
        "\n",
        "        ########################################################################\n",
        "        #                             END OF YOUR CODE                         #\n",
        "        ########################################################################"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8QD5P-F5HtCL"
      },
      "source": [
        "# Train your network"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "UVUwPTJnHtCK"
      },
      "outputs": [],
      "source": [
        "import time\n",
        "\n",
        "from torch import tensor\n",
        "from torch.optim import Adam\n",
        "\n",
        "def run(dataset, model, runs, epochs, lr, weight_decay, early_stopping):\n",
        "\n",
        "    val_losses, accs, durations = [], [], []\n",
        "    for _ in range(runs):\n",
        "        data = dataset[0]\n",
        "        data = data.to(device)\n",
        "\n",
        "        model.to(device).reset_parameters()\n",
        "        optimizer = Adam(model.parameters(), lr=lr, weight_decay=weight_decay)\n",
        "\n",
        "        if torch.cuda.is_available():\n",
        "            torch.cuda.synchronize()\n",
        "\n",
        "        t_start = time.perf_counter()\n",
        "\n",
        "        best_val_loss = float('inf')\n",
        "        test_acc = 0\n",
        "        val_loss_history = []\n",
        "\n",
        "        for epoch in range(1, epochs + 1):\n",
        "            train(model, optimizer, data)\n",
        "            eval_info = evaluate(model, data)\n",
        "            eval_info['epoch'] = epoch\n",
        "\n",
        "            if eval_info['val_loss'] < best_val_loss:\n",
        "                best_val_loss = eval_info['val_loss']\n",
        "                test_acc = eval_info['test_acc']\n",
        "\n",
        "            val_loss_history.append(eval_info['val_loss'])\n",
        "            if early_stopping > 0 and epoch > epochs // 2:\n",
        "                tmp = tensor(val_loss_history[-(early_stopping + 1):-1])\n",
        "                if eval_info['val_loss'] > tmp.mean().item():\n",
        "                    break\n",
        "\n",
        "        if torch.cuda.is_available():\n",
        "            torch.cuda.synchronize()\n",
        "\n",
        "        t_end = time.perf_counter()\n",
        "\n",
        "        val_losses.append(best_val_loss)\n",
        "        accs.append(test_acc)\n",
        "        durations.append(t_end - t_start)\n",
        "\n",
        "    loss, acc, duration = tensor(val_losses), tensor(accs), tensor(durations)\n",
        "\n",
        "    print('Val Loss: {:.4f}, Test Accuracy: {:.3f} ± {:.3f}, Duration: {:.3f}'.\n",
        "          format(loss.mean().item(),\n",
        "                 acc.mean().item(),\n",
        "                 acc.std().item(),\n",
        "                 duration.mean().item()))\n",
        "\n",
        "\n",
        "def train(model, optimizer, data):\n",
        "    model.train()\n",
        "    optimizer.zero_grad()\n",
        "    out = model(data)\n",
        "    loss = F.nll_loss(out[data.train_mask], data.y[data.train_mask])\n",
        "    loss.backward()\n",
        "    optimizer.step()\n",
        "\n",
        "\n",
        "def evaluate(model, data):\n",
        "    model.eval()\n",
        "\n",
        "    with torch.no_grad():\n",
        "        logits = model(data)\n",
        "\n",
        "    outs = {}\n",
        "    for key in ['train', 'val', 'test']:\n",
        "        mask = data['{}_mask'.format(key)]\n",
        "        loss = F.nll_loss(logits[mask], data.y[mask]).item()\n",
        "        pred = logits[mask].max(1)[1]\n",
        "        acc = pred.eq(data.y[mask]).sum().item() / mask.sum().item()\n",
        "\n",
        "        outs['{}_loss'.format(key)] = loss\n",
        "        outs['{}_acc'.format(key)] = acc\n",
        "\n",
        "    return outs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9dWVNEQQkki3"
      },
      "outputs": [],
      "source": [
        "aggrs = ['mean', 'add', 'max']\n",
        "\n",
        "for aggr in aggrs:\n",
        "    print('GraphSAGE-{}'.format(aggr))\n",
        "    run(dataset, SAGENet(dataset, aggr), runs, epochs, lr, weight_decay,\n",
        "        early_stopping)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "PY1PBFlqa3wb"
      }
    }
  ],
  "metadata": {
    "colab": {
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    "kernelspec": {
      "display_name": "pyg",
      "language": "python",
      "name": "pyg"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.6.7"
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