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": 4,
      "metadata": {
        "cellView": "code",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ix_xt4X1_6F4",
        "outputId": "9c4219ee-bf34-4d9f-b234-ed3fa2e98cef"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: min-dalle in /usr/local/lib/python3.7/dist-packages (0.2.10)\n",
            "Requirement already satisfied: torch>=1.10.0 in /usr/local/lib/python3.7/dist-packages (from min-dalle) (1.11.0+cu113)\n",
            "Requirement already satisfied: typing-extensions>=4.1.0 in /usr/local/lib/python3.7/dist-packages (from min-dalle) (4.1.1)\n",
            "Sun Jul  3 19:28:49 2022       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 460.32.03    Driver Version: 460.32.03    CUDA Version: 11.2     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla P100-PCIE...  Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   32C    P0    26W / 250W |      0MiB / 16280MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "! pip install min-dalle\n",
        "! nvidia-smi"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kViq2dMbGDKt"
      },
      "source": [
        "### Load Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8W-L2ICFGFup",
        "outputId": "5d3b2f09-f3c7-4759-dc7f-fcf7a6366e54"
      },
      "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 work if you were allocated a P100 or T4 GPU"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 972
        },
        "id": "nQ0UG05dA4p2",
        "outputId": "228430d8-9b29-46fc-85c6-b20b04f1d88d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "tokenizing text\n",
            "['Ġdali']\n",
            "['Ġpainting']\n",
            "['Ġof']\n",
            "['Ġwal', 'le']\n",
            "text tokens [0, 21853, 1545, 111, 563, 92, 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 0x7F086EC34C10>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 35 s, sys: 0 ns, total: 35 s\n",
            "Wall time: 34.7 s\n"
          ]
        }
      ],
      "source": [
        "%%time\n",
        "\n",
        "text = \"Dali painting of WALL·E\" #@param {type:\"string\"}\n",
        "grid_size = 2 #@param {type:\"integer\"}\n",
        "seed = -1 #@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
}