TFJS-collab-save-tensor.ipynb

TFJS-collab-save-tensor.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "TFJS-collab-save-tensor.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "javascript",
      "display_name": "Javascript"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/obenjiro/cd4b095c39af7ed78b12572560fbe0ac/notebook.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fsqcND6Klagn",
        "colab_type": "text"
      },
      "source": [
        "# Prep JS runtime for Google Colab"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bjNF3VjPjJHV",
        "colab_type": "text"
      },
      "source": [
        "Run cell (commands) below and then hit F5 (refresh the page) right after that"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZVkF16NwcMsZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!npm install -g npm@latest\n",
        "!npm cache verify\n",
        "!npm install -g --unsafe-perm ijavascript\n",
        "!ijsinstall --install=global\n",
        "!jupyter-kernelspec list"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r2UzIt5Gi6Em",
        "colab_type": "text"
      },
      "source": [
        "That's it! :) Now in the next cells you can write JavaScript"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MMyXtMptltc9",
        "colab_type": "text"
      },
      "source": [
        "# Example of usage"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qbVfsd0emCWY",
        "colab_type": "text"
      },
      "source": [
        "**Remember not to use `const` or `let`! Use `var` instead**\n",
        "\n",
        "This is how you can execute shell commands:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "skqAs_UHc8_P",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "var { spawn } = require('child_process');\n",
        "var sh = (cmd) => { \n",
        "    $$.async();\n",
        "    var sp = spawn(cmd, { cwd: process.cwd(), stdio: 'pipe', shell: true, encoding: 'utf-8' });\n",
        "    sp.stdout.on('data', data => console.log(data.toString()));\n",
        "    sp.stderr.on('data', data => console.error(data.toString()));\n",
        "    sp.on('close', () => $$.done());\n",
        "};\n",
        "var run_async = async (pf) => {\n",
        "  $$.async();\n",
        "  await pf();\n",
        "  $$.done();\n",
        "};\n",
        "sh('npm init -y');"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1oqifUNtdID-",
        "colab_type": "code",
        "outputId": "7a8d3f4b-7875-4d6b-fa63-332ffbb2364f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        }
      },
      "source": [
        "sh('node -v; npm -v');"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "v8.11.3\n",
            "\n",
            "\n",
            "6.13.7\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "28tLRTVq8xms",
        "colab_type": "code",
        "outputId": "9c323758-8a9c-45ce-b959-6017abc21544",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 680
        }
      },
      "source": [
        "sh('npm install @tensorflow/tfjs-node-gpu')"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "> @tensorflow/tfjs-node-gpu@1.5.2 install /content/node_modules/@tensorflow/tfjs-node-gpu\n",
            "> node scripts/install.js gpu download\n",
            "\n",
            "\n",
            "GPU-linux-1.5.2.tar.gz\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "* Downloading libtensorflow\n",
            "\n",
            "\n",
            "\n",
            "* Building TensorFlow Node.js bindings\n",
            "\n",
            "npm\n",
            " notice created a lockfile as package-lock.json. You should commit this file.\n",
            "\n",
            "npm\n",
            " \n",
            "WARN\n",
            " content@1.0.0 No description\n",
            "\n",
            "npm\n",
            " \n",
            "WARN\n",
            " content@1.0.0 No repository field.\n",
            "\n",
            "\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "+ @tensorflow/tfjs-node-gpu@1.5.2\n",
            "added 88 packages from 91 contributors and audited 153 packages in 32.336s\n",
            "\n",
            "\n",
            "1 package is looking for funding\n",
            "  run `npm fund` for details\n",
            "\n",
            "\n",
            "found 0 vulnerabilities\n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "psJPTwp79NXv",
        "colab_type": "code",
        "outputId": "d76be7bc-d6a2-41cd-c7f8-b0478e25515b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "var tf = require('@tensorflow/tfjs-node-gpu');\n",
        "console.log(tf.backend().isUsingGpuDevice);"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "node-pre-gyp info This Node instance does not support builds for N-API version 4\n",
            "node-pre-gyp info This Node instance does not support builds for N-API version 5\n",
            "node-pre-gyp info This Node instance does not support builds for N-API version 4\n",
            "node-pre-gyp info This Node instance does not support builds for N-API version 5\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "true\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "(node:292) Warning: N-API is an experimental feature and could change at any time.\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GcQiKW6sJFZX",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "3fb3c483-2e05-4263-d01f-3630162d253c"
      },
      "source": [
        "var tensorToSave = tf.tensor([[1, 2], [3, 4]]);\n",
        "tensorToSave.print()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tensor\n",
            "    [[1, 2],\n",
            "     [3, 4]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uEB7uGBFUeUY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "01fe7880-b15b-42ff-9f1f-dc9e395b8d7a"
      },
      "source": [
        "// saving tensor\n",
        "var fs = require('fs');\n",
        "fs.writeFileSync('saved-tensor.json', JSON.stringify(tensorToSave.arraySync()), 'utf-8');\n",
        "sh('ls -la saved-tensor.json');"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "-rw-r--r-- 1 root root 13 Feb 23 09:16 saved-tensor.json\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FX9NhyWsU1BM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "9904bc71-ae57-465a-daf2-eab3542910d5"
      },
      "source": [
        "// loading tensor\n",
        "var fs = require('fs');\n",
        "var str = fs.readFileSync('saved-tensor.json', 'utf-8');\n",
        "var tensorRestored = tf.tensor(JSON.parse(str));\n",
        "tensorRestored.print()"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tensor\n",
            "    [[1, 2],\n",
            "     [3, 4]]\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}