Using Google Colab with R and tensorflow.ipynb

using-google-colab-with-r-and-tensorflow.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "V28",
      "authorship_tag": "ABX9TyMRFvdOHdFlv3/J5rbICLhq",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "ir",
      "display_name": "R"
    },
    "language_info": {
      "name": "R"
    },
    "accelerator": "TPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/thomvolker/52589e75795d6af73584bfcbe0022c5e/using-google-colab-with-r-and-tensorflow.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "First, we specify that we want to run `R` in `python`, which can be done by going to `Runtime > Change runtime type` and changing runtime type to `R`.\n",
        "\n",
        "Second, we can proceed as usual. The following code should get you started."
      ],
      "metadata": {
        "id": "jvT54p1qT-Q6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Load the required packages\n",
        "install.packages(\"tidyverse\")\n",
        "install.packages(\"keras\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Xrsb1lJHUlFe",
        "outputId": "77055e7c-2f26-4be6-db1c-2b84e8ae9d0b"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Installing package into ‘/usr/local/lib/R/site-library’\n",
            "(as ‘lib’ is unspecified)\n",
            "\n",
            "Installing package into ‘/usr/local/lib/R/site-library’\n",
            "(as ‘lib’ is unspecified)\n",
            "\n",
            "also installing the dependencies ‘RcppTOML’, ‘here’, ‘png’, ‘config’, ‘tfautograph’, ‘reticulate’, ‘tensorflow’, ‘tfruns’, ‘zeallot’\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "library(tidyverse)\n",
        "library(keras)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FOJttu3qVGIG",
        "outputId": "a2c6fac9-052a-4687-8513-cd64b43d7e6a"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "── \u001b[1mAttaching core tidyverse packages\u001b[22m ──────────────────────── tidyverse 2.0.0 ──\n",
            "\u001b[32m✔\u001b[39m \u001b[34mdplyr    \u001b[39m 1.1.4     \u001b[32m✔\u001b[39m \u001b[34mreadr    \u001b[39m 2.1.5\n",
            "\u001b[32m✔\u001b[39m \u001b[34mforcats  \u001b[39m 1.0.0     \u001b[32m✔\u001b[39m \u001b[34mstringr  \u001b[39m 1.5.1\n",
            "\u001b[32m✔\u001b[39m \u001b[34mggplot2  \u001b[39m 3.5.1     \u001b[32m✔\u001b[39m \u001b[34mtibble   \u001b[39m 3.2.1\n",
            "\u001b[32m✔\u001b[39m \u001b[34mlubridate\u001b[39m 1.9.4     \u001b[32m✔\u001b[39m \u001b[34mtidyr    \u001b[39m 1.3.1\n",
            "\u001b[32m✔\u001b[39m \u001b[34mpurrr    \u001b[39m 1.0.2     \n",
            "── \u001b[1mConflicts\u001b[22m ────────────────────────────────────────── tidyverse_conflicts() ──\n",
            "\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mfilter()\u001b[39m masks \u001b[34mstats\u001b[39m::filter()\n",
            "\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mlag()\u001b[39m    masks \u001b[34mstats\u001b[39m::lag()\n",
            "\u001b[36mℹ\u001b[39m Use the conflicted package (\u001b[3m\u001b[34m<http://conflicted.r-lib.org/>\u001b[39m\u001b[23m) to force all conflicts to become errors\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mnist <- dataset_mnist()"
      ],
      "metadata": {
        "id": "nPjXFpgYVpnM"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plot_img <- function(img, col = gray.colors(255, start = 1, end = 0), ...) {\n",
        "  image(t(img), asp = 1, ylim = c(1.1, -0.1), col = col, bty = \"n\", axes = FALSE, ...)\n",
        "}"
      ],
      "metadata": {
        "collapsed": true,
        "id": "qjVA8sCQV3E6"
      },
      "execution_count": 4,
      "outputs": []
    }
  ]
}