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": 2,
      "metadata": {
        "cellView": "code",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ix_xt4X1_6F4",
        "outputId": "36db2d18-c7d0-4603-e0dd-b289e7a99592"
      },
      "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\n",
            "  Downloading min-dalle-0.2.17.tar.gz (10 kB)\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",
            "Requirement already satisfied: numpy>=1.21 in /usr/local/lib/python3.7/dist-packages (from min-dalle) (1.21.6)\n",
            "Requirement already satisfied: pillow>=7.1 in /usr/local/lib/python3.7/dist-packages (from min-dalle) (7.1.2)\n",
            "Requirement already satisfied: requests>=2.23 in /usr/local/lib/python3.7/dist-packages (from min-dalle) (2.23.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.23->min-dalle) (2022.6.15)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.23->min-dalle) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.23->min-dalle) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.23->min-dalle) (1.24.3)\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-0.2.17-py3-none-any.whl size=10987 sha256=b1a239f5428d6ccc757f47094ce1e1986d3900a754cc7f3c0a362c4ffdba7162\n",
            "  Stored in directory: /root/.cache/pip/wheels/d4/8b/2d/14470dada5426179003743c4f0b8bfc9804c68c21a9275eb62\n",
            "Successfully built min-dalle\n",
            "Installing collected packages: min-dalle\n",
            "Successfully installed min-dalle-0.2.17\n",
            "Mon Jul  4 14:16:04 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   35C    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": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8W-L2ICFGFup",
        "outputId": "0afeaa09-c0df-4c2f-bdb2-19cebbd86281"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "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: reduce the grid size if you run out of GPU memory.  4x4 has been tested to work on T4 and P100"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "nQ0UG05dA4p2",
        "outputId": "7e711399-0b3f-48ee-808e-27a51509829b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "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"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=1024x1024 at 0x7F33C65140D0>"
            ],
            "image/png": "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
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CPU times: user 47.4 s, sys: 78.2 ms, total: 47.5 s\n",
            "Wall time: 48.1 s\n"
          ]
        }
      ],
      "source": [
        "%%time\n",
        "\n",
        "text = \"Dali painting of WALL·E\" #@param {type:\"string\"}\n",
        "grid_size = 4 #@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"
      ],
      "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
}