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": null,
      "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": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8W-L2ICFGFup",
        "outputId": "73aa19d1-f2c6-4054-8d88-e882d21ce390"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "initializing MinDalle\n",
            "intializing TextTokenizer\n",
            "initializing DalleBartEncoder\n",
            "initializing DalleBartDecoder\n",
            "initializing VQGanDetokenizer\n"
          ]
        }
      ],
      "source": [
        "from PIL import Image\n",
        "from IPython.display import update_display\n",
        "import numpy\n",
        "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: reduce the grid size if you run out of GPU memory.  4x4 has been tested to work on T4 and P100 (with intermediate_image_count = None)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 801
        },
        "id": "nQ0UG05dA4p2",
        "outputId": "3266cc97-4c97-49c0-c15e-f89fa7373c46"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=750x750 at 0x7F982862A510>"
            ],
            "image/png": "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
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CPU times: user 34.4 s, sys: 897 ms, total: 35.3 s\n",
            "Wall time: 36.5 s\n"
          ]
        }
      ],
      "source": [
        "%%time\n",
        "\n",
        "text = \"Dali painting of WALL·E\" #@param {type:\"string\"}\n",
        "grid_size = 3 #@param {type:\"integer\"}\n",
        "seed = -1 #@param {type:\"integer\"}\n",
        "intermediate_image_count = 8 #@param [\"2\", \"4\", \"8\", \"16\", \"None\"] {type:\"raw\"}\n",
        "\n",
        "display_size = 750\n",
        "image_shape = (display_size, display_size, 3)\n",
        "zero_image = Image.fromarray(numpy.zeros(image_shape, dtype=numpy.uint8))\n",
        "display(zero_image, display_id=1)\n",
        "\n",
        "def handle_intermediate_image(row_index: int, image: Image.Image):\n",
        "    image = image.resize((display_size, display_size))\n",
        "    update_display(image, display_id=1)\n",
        "\n",
        "image = model.generate_image(\n",
        "    text,\n",
        "    seed,\n",
        "    grid_size,\n",
        "    intermediate_image_count,\n",
        "    handle_intermediate_image\n",
        ")"
      ]
    }
  ],
  "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
}