min-dalle-test/min_dalle.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/kuprel/min-dalle/blob/main/min_dalle.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3WL-G_f2_ld8"
      },
      "source": [
        "# min(DALL·E)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Zl_ZFisFApeh"
      },
      "source": [
        "### Install"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "cellView": "code",
        "id": "ix_xt4X1_6F4",
        "outputId": "f9cd1ba7-4681-471d-f4f5-129a581ca42e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting min-dalle==0.2.9\n",
            "  Downloading min-dalle-0.2.9.tar.gz (10 kB)\n",
            "Requirement already satisfied: torch>=1.10.0 in /usr/local/lib/python3.7/dist-packages (from min-dalle==0.2.9) (1.11.0+cu113)\n",
            "Requirement already satisfied: typing_extensions>=4.1.0 in /usr/local/lib/python3.7/dist-packages (from min-dalle==0.2.9) (4.1.1)\n",
            "Building wheels for collected packages: min-dalle\n",
            "  Building wheel for min-dalle (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for min-dalle: filename=min_dalle-0.2.9-py3-none-any.whl size=10790 sha256=95981af929f2d667a5279e988f51d4bbbc8a774ba8b3350aa99bc9812ab11cba\n",
            "  Stored in directory: /root/.cache/pip/wheels/f5/6a/2d/c0856f094be77d1a6a2d356dd9557ff6a7a6bc012856f83f03\n",
            "Successfully built min-dalle\n",
            "Installing collected packages: min-dalle\n",
            "  Attempting uninstall: min-dalle\n",
            "    Found existing installation: min-dalle 0.2.8\n",
            "    Uninstalling min-dalle-0.2.8:\n",
            "      Successfully uninstalled min-dalle-0.2.8\n",
            "Successfully installed min-dalle-0.2.9\n"
          ]
        }
      ],
      "source": [
        "! pip install min-dalle>=0.2.9"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kViq2dMbGDKt"
      },
      "source": [
        "### Load Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8W-L2ICFGFup",
        "outputId": "fad4b4c4-b66b-435e-aa81-af3e874ef7ce"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "initializing MinDalle\n",
            "intializing TextTokenizer\n",
            "initializing DalleBartEncoder\n",
            "initializing DalleBartDecoder\n",
            "initializing VQGanDetokenizer\n"
          ]
        }
      ],
      "source": [
        "from min_dalle import MinDalle\n",
        "\n",
        "model = MinDalle(is_mega=True, is_reusable=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c52TV1GbBNgS"
      },
      "source": [
        "### Generate Images"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 884
        },
        "id": "nQ0UG05dA4p2",
        "outputId": "c75050e2-d128-4d3d-817c-c3c9ccd61746"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "tokenizing text\n",
            "['Ġtrail']\n",
            "['Ġcam']\n",
            "['Ġfootage']\n",
            "['Ġof']\n",
            "['Ġgoll', 'um']\n",
            "['Ġeating']\n",
            "['Ġwatermelon']\n",
            "text tokens [0, 1737, 904, 8271, 111, 39831, 140, 7077, 16927, 2]\n",
            "encoding text tokens\n",
            "sampling image tokens\n",
            "detokenizing image\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=768x768 at 0x7F655DB42B10>"
            ],
            "image/png": "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
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CPU times: user 35.2 s, sys: 103 ms, total: 35.3 s\n",
            "Wall time: 34.9 s\n"
          ]
        }
      ],
      "source": [
        "%%time\n",
        "\n",
        "text = \"trail cam footage of gollum eating watermelon\" #@param {type:\"string\"}\n",
        "seed = 1 #@param {type:\"integer\"}\n",
        "grid_size = 3 #@param {type:\"integer\"}\n",
        "\n",
        "display(model.generate_image(text, seed, grid_size))"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "collapsed_sections": [
        "Zl_ZFisFApeh"
      ],
      "name": "min-dalle",
      "provenance": [],
      "include_colab_link": true
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}