ondisk_dataset_heterograph.ipynb

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  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "private_outputs": true,
      "provenance": [],
      "authorship_tag": "ABX9TyM1zJGR6lVdC9JfDbddFLpa"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# OnDiskDataset for Heterogeneous Graph\n",
        "\n",
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dmlc/dgl/blob/master/notebooks/stochastic_training/ondisk_dataset_heterograph.ipynb) [![GitHub](https://img.shields.io/badge/-View%20on%20GitHub-181717?logo=github&logoColor=ffffff)](https://github.com/dmlc/dgl/blob/master/notebooks/stochastic_training/ondisk_dataset_heterograph.ipynb)\n",
        "\n",
        "This tutorial shows how to create `OnDiskDataset` for heterogeneous graph that could be used in **GraphBolt** framework.\n",
        "\n",
        "By the end of this tutorial, you will be able to\n",
        "- organize graph structure data.\n",
        "- organize feature data.\n",
        "- organize training/validation/test set for specific tasks."
      ],
      "metadata": {
        "id": "FnFhPMaAfLtJ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Install DGL package"
      ],
      "metadata": {
        "id": "Wlb19DtWgtzq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Install required packages.\n",
        "import os\n",
        "import torch\n",
        "import numpy as np\n",
        "os.environ['TORCH'] = torch.__version__\n",
        "os.environ['DGLBACKEND'] = \"pytorch\"\n",
        "\n",
        "# Install the CPU version.\n",
        "device = torch.device(\"cpu\")\n",
        "!pip install --pre dgl -f https://data.dgl.ai/wheels-test/repo.html\n",
        "\n",
        "try:\n",
        "    import dgl\n",
        "    import dgl.graphbolt as gb\n",
        "    installed = True\n",
        "except ImportError as error:\n",
        "    installed = False\n",
        "    print(error)\n",
        "print(\"DGL installed!\" if installed else \"DGL not found!\")"
      ],
      "metadata": {
        "id": "UojlT9ZGgyr9"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}