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": [
        "### Download models and install dependencies"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "cellView": "code",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ix_xt4X1_6F4",
        "outputId": "a1b44041-6887-4f4c-d535-9de9eca173ee"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Cloning into 'min-dalle'...\n",
            "remote: Enumerating objects: 420, done.\u001b[K\n",
            "remote: Counting objects: 100% (224/224), done.\u001b[K\n",
            "remote: Compressing objects: 100% (100/100), done.\u001b[K\n",
            "remote: Total 420 (delta 149), reused 179 (delta 121), pack-reused 196\u001b[K\n",
            "Receiving objects: 100% (420/420), 1.33 MiB | 14.81 MiB/s, done.\n",
            "Resolving deltas: 100% (245/245), done.\n",
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            "100   234  100   234    0     0   1800      0 --:--:-- --:--:-- --:--:--  1800\n",
            "100  290M  100  290M    0     0  93.1M      0  0:00:03  0:00:03 --:--:--  106M\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.7/dist-packages (1.11.0+cu113)\n",
            "Collecting flax==0.4.2\n",
            "  Downloading flax-0.4.2-py3-none-any.whl (186 kB)\n",
            "\u001b[K     |████████████████████████████████| 186 kB 5.3 MB/s \n",
            "\u001b[?25hCollecting wandb\n",
            "  Downloading wandb-0.12.20-py2.py3-none-any.whl (1.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.8 MB 60.0 MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.12 in /usr/local/lib/python3.7/dist-packages (from flax==0.4.2) (1.21.6)\n",
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            "Collecting optax\n",
            "  Downloading optax-0.1.2-py3-none-any.whl (140 kB)\n",
            "\u001b[K     |████████████████████████████████| 140 kB 71.2 MB/s \n",
            "\u001b[?25hRequirement already satisfied: matplotlib in /usr/local/lib/python3.7/dist-packages (from flax==0.4.2) (3.2.2)\n",
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            "Requirement already satisfied: scipy>=1.2.1 in /usr/local/lib/python3.7/dist-packages (from jax>=0.3->flax==0.4.2) (1.4.1)\n",
            "Requirement already satisfied: protobuf<4.0dev,>=3.12.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (3.17.3)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from wandb) (57.4.0)\n",
            "Collecting GitPython>=1.0.0\n",
            "  Downloading GitPython-3.1.27-py3-none-any.whl (181 kB)\n",
            "\u001b[K     |████████████████████████████████| 181 kB 66.4 MB/s \n",
            "\u001b[?25hRequirement already satisfied: six>=1.13.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (1.15.0)\n",
            "Collecting docker-pycreds>=0.4.0\n",
            "  Downloading docker_pycreds-0.4.0-py2.py3-none-any.whl (9.0 kB)\n",
            "Requirement already satisfied: psutil>=5.0.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (5.4.8)\n",
            "Collecting shortuuid>=0.5.0\n",
            "  Downloading shortuuid-1.0.9-py3-none-any.whl (9.4 kB)\n",
            "Collecting pathtools\n",
            "  Downloading pathtools-0.1.2.tar.gz (11 kB)\n",
            "Requirement already satisfied: requests<3,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (2.23.0)\n",
            "Requirement already satisfied: Click!=8.0.0,>=7.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (7.1.2)\n",
            "Collecting setproctitle\n",
            "  Downloading setproctitle-1.2.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (29 kB)\n",
            "Collecting sentry-sdk>=1.0.0\n",
            "  Downloading sentry_sdk-1.6.0-py2.py3-none-any.whl (145 kB)\n",
            "\u001b[K     |████████████████████████████████| 145 kB 68.4 MB/s \n",
            "\u001b[?25hRequirement already satisfied: PyYAML in /usr/local/lib/python3.7/dist-packages (from wandb) (3.13)\n",
            "Requirement already satisfied: promise<3,>=2.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (2.3)\n",
            "Collecting gitdb<5,>=4.0.1\n",
            "  Downloading gitdb-4.0.9-py3-none-any.whl (63 kB)\n",
            "\u001b[K     |████████████████████████████████| 63 kB 2.2 MB/s \n",
            "\u001b[?25hCollecting smmap<6,>=3.0.1\n",
            "  Downloading smmap-5.0.0-py3-none-any.whl (24 kB)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.0.0->wandb) (3.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.0.0->wandb) (2022.6.15)\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<3,>=2.0.0->wandb) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.0.0->wandb) (2.10)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib->flax==0.4.2) (0.11.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->flax==0.4.2) (1.4.3)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->flax==0.4.2) (2.8.2)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->flax==0.4.2) (3.0.9)\n",
            "Requirement already satisfied: jaxlib>=0.1.37 in /usr/local/lib/python3.7/dist-packages (from optax->flax==0.4.2) (0.3.7+cuda11.cudnn805)\n",
            "Collecting chex>=0.0.4\n",
            "  Downloading chex-0.1.3-py3-none-any.whl (72 kB)\n",
            "\u001b[K     |████████████████████████████████| 72 kB 691 kB/s \n",
            "\u001b[?25hRequirement already satisfied: toolz>=0.9.0 in /usr/local/lib/python3.7/dist-packages (from chex>=0.0.4->optax->flax==0.4.2) (0.11.2)\n",
            "Requirement already satisfied: dm-tree>=0.1.5 in /usr/local/lib/python3.7/dist-packages (from chex>=0.0.4->optax->flax==0.4.2) (0.1.7)\n",
            "Requirement already satisfied: flatbuffers<3.0,>=1.12 in /usr/local/lib/python3.7/dist-packages (from jaxlib>=0.1.37->optax->flax==0.4.2) (2.0)\n",
            "Building wheels for collected packages: pathtools\n",
            "  Building wheel for pathtools (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pathtools: filename=pathtools-0.1.2-py3-none-any.whl size=8806 sha256=7699646fac65684c2ccc2b48202e402265e5b09080ae1c581d247167f3668402\n",
            "  Stored in directory: /root/.cache/pip/wheels/3e/31/09/fa59cef12cdcfecc627b3d24273699f390e71828921b2cbba2\n",
            "Successfully built pathtools\n",
            "Installing collected packages: smmap, gitdb, chex, shortuuid, setproctitle, sentry-sdk, pathtools, optax, GitPython, docker-pycreds, wandb, flax\n",
            "Successfully installed GitPython-3.1.27 chex-0.1.3 docker-pycreds-0.4.0 flax-0.4.2 gitdb-4.0.9 optax-0.1.2 pathtools-0.1.2 sentry-sdk-1.6.0 setproctitle-1.2.3 shortuuid-1.0.9 smmap-5.0.0 wandb-0.12.20\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Downloading dataset artifact dalle-mini/dalle-mini/mini-1:v0\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Downloading large artifact mini-1:v0, 1673.43MB. 7 files... Done. 0:0:14.7\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Artifact downloaded to /content/min-dalle/pretrained/dalle_bart_mini\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Downloading dataset artifact dalle-mini/dalle-mini/mega-1-fp16:v14\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Downloading large artifact mega-1-fp16:v14, 4938.53MB. 7 files... Done. 0:0:53.4\n",
            "\u001b[34m\u001b[1mwandb\u001b[0m: Artifact downloaded to /content/min-dalle/pretrained/dalle_bart_mega\n"
          ]
        },
        {
          "data": {
            "text/plain": []
          },
          "execution_count": 1,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%%shell\n",
        "\n",
        "git clone https://github.com/kuprel/min-dalle\n",
        "mkdir -p /content/min-dalle/pretrained/vqgan/\n",
        "curl https://huggingface.co/dalle-mini/vqgan_imagenet_f16_16384/resolve/main/flax_model.msgpack -L --output /content/min-dalle/pretrained/vqgan/flax_model.msgpack\n",
        "pip install torch flax wandb\n",
        "wandb login --anonymously\n",
        "wandb artifact get --root=/content/min-dalle/pretrained/dalle_bart_mega dalle-mini/dalle-mini/mega-1-fp16:v14\n"
      ]
    },
    {
      "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": "a7008b7d-4c05-4860-e997-7b6e93062307"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "initializing MinDalleTorch\n",
            "reading files from pretrained/dalle_bart_mega\n",
            "converting params to torch\n",
            "initializing DalleBartEncoderTorch\n",
            "initializing DalleBartDecoderTorch\n",
            "initializing VQGanDetokenizer\n"
          ]
        }
      ],
      "source": [
        "import os\n",
        "os.chdir('/content/min-dalle')\n",
        "from min_dalle.min_dalle_torch import MinDalleTorch\n",
        "\n",
        "model = MinDalleTorch(is_mega=True, is_reusable=True)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c52TV1GbBNgS"
      },
      "source": [
        "### Generate an Image"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "nQ0UG05dA4p2",
        "outputId": "00d01630-a892-4018-d5b2-ee0ea2047b98"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "tokenizing text\n",
            "['Ġartificial']\n",
            "['Ġintelligence']\n",
            "text tokens [0, 6316, 7815, 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=256x256 at 0x7F0671709D10>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 7.4 s, sys: 8.11 ms, total: 7.41 s\n",
            "Wall time: 7.38 s\n"
          ]
        }
      ],
      "source": [
        "%%time\n",
        "\n",
        "text = \"artificial intelligence\" #@param {type:\"string\"}\n",
        "seed = 10 #@param {type:\"integer\"}\n",
        "\n",
        "image = model.generate_image(text, seed)\n",
        "display(image)"
      ]
    }
  ],
  "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
}