min-dalle-test/min_dalle.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "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": 1,
      "metadata": {
        "cellView": "code",
        "id": "ix_xt4X1_6F4"
      },
      "outputs": [],
      "source": [
        "! pip install min-dalle\n",
        "! nvidia-smi"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kViq2dMbGDKt"
      },
      "source": [
        "### Load Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8W-L2ICFGFup",
        "outputId": "653d17b9-0252-45ec-81ef-bf1ad689daf5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "initializing MinDalle\n",
            "downloading tokenizer params\n",
            "intializing TextTokenizer\n",
            "downloading encoder params\n",
            "initializing DalleBartEncoder\n",
            "downloading decoder params\n",
            "initializing DalleBartDecoder\n",
            "downloading detokenizer params\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\n",
        "Note: a 3x3 grid will only work if you were allocated a P100 GPU"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "nQ0UG05dA4p2",
        "outputId": "cf32d35f-9c67-4377-9238-b2992d9e7d2b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "tokenizing text\n",
            "['Ġcourt']\n",
            "['Ġsketch']\n",
            "['Ġof']\n",
            "['Ġgodzilla']\n",
            "['Ġon']\n",
            "['Ġtrial']\n",
            "text tokens [0, 2634, 4189, 111, 14450, 133, 5167, 2]\n",
            "encoding text tokens\n",
            "sampling image tokens\n",
            "detokenizing image\n"
          ]
        },
        {
          "data": {
            "image/png": "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
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=768x768 at 0x7F4B8E8DA450>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 35.2 s, sys: 28.6 ms, total: 35.2 s\n",
            "Wall time: 35 s\n"
          ]
        }
      ],
      "source": [
        "%%time\n",
        "\n",
        "text = \"court sketch of godzilla on trial\" #@param {type:\"string\"}\n",
        "seed = 6 #@param {type:\"integer\"}\n",
        "grid_size = 2 #@param {type:\"integer\"}\n",
        "\n",
        "display(model.generate_image(text, seed, grid_size))"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "collapsed_sections": [
        "Zl_ZFisFApeh"
      ],
      "include_colab_link": true,
      "name": "min-dalle",
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}