dreambooth_fine_tuning_demo_WITHOUT_INSTANCE_PROMPT.ipynb

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  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/karthiknadar1204/generative_deep_learning/blob/main/dreambooth_fine_tuning_demo_WITHOUT_INSTANCE_PROMPT.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "So-xAg-nSB3i",
        "outputId": "36226e5a-d657-4104-87eb-393c7a07c136"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cu117\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.3.0+cu121)\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (0.18.0+cu121)\n",
            "Requirement already satisfied: torchaudio in /usr/local/lib/python3.10/dist-packages (2.3.0+cu121)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch) (3.14.0)\n",
            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch) (4.12.1)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch) (1.12.1)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch) (3.3)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch) (3.1.4)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch) (2023.6.0)\n",
            "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch)\n",
            "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
            "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch)\n",
            "  Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
            "Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch)\n",
            "  Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n",
            "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch)\n",
            "  Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n",
            "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch)\n",
            "  Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
            "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch)\n",
            "  Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n",
            "Collecting nvidia-curand-cu12==10.3.2.106 (from torch)\n",
            "  Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n",
            "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch)\n",
            "  Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n",
            "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch)\n",
            "  Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n",
            "Collecting nvidia-nccl-cu12==2.20.5 (from torch)\n",
            "  Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)\n",
            "Collecting nvidia-nvtx-cu12==12.1.105 (from torch)\n",
            "  Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n",
            "Requirement already satisfied: triton==2.3.0 in /usr/local/lib/python3.10/dist-packages (from torch) (2.3.0)\n",
            "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch)\n",
            "  Downloading nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m59.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from torchvision) (1.25.2)\n",
            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision) (9.4.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch) (2.1.5)\n",
            "Requirement already satisfied: mpmath<1.4.0,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch) (1.3.0)\n",
            "Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12\n",
            "Successfully installed nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105\n",
            "Wed Jun  5 16:47:31 2024       \n",
            "+---------------------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |\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 T4                       Off | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   41C    P8              10W /  70W |      0MiB / 15360MiB |      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",
            "nvcc: NVIDIA (R) Cuda compiler driver\n",
            "Copyright (c) 2005-2023 NVIDIA Corporation\n",
            "Built on Tue_Aug_15_22:02:13_PDT_2023\n",
            "Cuda compilation tools, release 12.2, V12.2.140\n",
            "Build cuda_12.2.r12.2/compiler.33191640_0\n",
            "CUDA is available. GPU: Tesla T4\n"
          ]
        }
      ],
      "source": [
        "# Enable GPU in the notebook (Already done in Runtime settings)\n",
        "# Install PyTorch with CUDA support\n",
        "!pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu117\n",
        "\n",
        "# Check NVIDIA and CUDA installation\n",
        "!nvidia-smi\n",
        "!nvcc --version\n",
        "\n",
        "# Verify if PyTorch can access the GPU\n",
        "import torch\n",
        "\n",
        "if torch.cuda.is_available():\n",
        "    print(f\"CUDA is available. GPU: {torch.cuda.get_device_name(0)}\")\n",
        "else:\n",
        "    print(\"CUDA is not available.\")\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "zip_path = \"/content/ThankYou.zip\"\n",
        "\n",
        "extract_path = \"/content/unzipped_ThankYou_files\"\n",
        "\n",
        "!mkdir -p {extract_path}\n",
        "\n",
        "!unzip {zip_path} -d {extract_path}\n",
        "\n",
        "print(\"Files unzipped successfully!\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XPUMZL1xSDon",
        "outputId": "4dd139d0-e378-43a8-8cac-e4a5c8546798"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  /content/ThankYou.zip\n",
            "   creating: /content/unzipped_ThankYou_files/ThankYou/\n",
            "  inflating: /content/unzipped_ThankYou_files/__MACOSX/._ThankYou  \n",
            "  inflating: /content/unzipped_ThankYou_files/ThankYou/Thank_you_3.jpeg  \n",
            "  inflating: /content/unzipped_ThankYou_files/__MACOSX/ThankYou/._Thank_you_3.jpeg  \n",
            "  inflating: /content/unzipped_ThankYou_files/ThankYou/Thank_you_4.jpeg  \n",
            "  inflating: /content/unzipped_ThankYou_files/__MACOSX/ThankYou/._Thank_you_4.jpeg  \n",
            "  inflating: /content/unzipped_ThankYou_files/ThankYou/Thank_you_image_2.jpeg  \n",
            "  inflating: /content/unzipped_ThankYou_files/__MACOSX/ThankYou/._Thank_you_image_2.jpeg  \n",
            "  inflating: /content/unzipped_ThankYou_files/ThankYou/Screenshot 2024-06-05 at 9.17.47 PM.png  \n",
            "  inflating: /content/unzipped_ThankYou_files/__MACOSX/ThankYou/._Screenshot 2024-06-05 at 9.17.47 PM.png  \n",
            "  inflating: /content/unzipped_ThankYou_files/ThankYou/Thank_you_1.jpeg  \n",
            "  inflating: /content/unzipped_ThankYou_files/__MACOSX/ThankYou/._Thank_you_1.jpeg  \n",
            "Files unzipped successfully!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title GPU Check\n",
        "!nvidia-smi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2RvA18mdSDsZ",
        "outputId": "359c0d5f-5ecd-4159-85dc-98dbbad58c90"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Wed Jun  5 16:53:59 2024       \n",
            "+---------------------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |\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 T4                       Off | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   40C    P8               9W /  70W |      3MiB / 15360MiB |      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"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "!pip install -qq \"ipywidgets>=7,<8\"\n",
        "!git clone https://github.com/huggingface/diffusers\n",
        "%cd /content/diffusers\n",
        "!pip install ."
      ],
      "metadata": {
        "id": "G9Ps_2_JSD0H"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "%cd /content/diffusers/examples/dreambooth\n",
        "!pip install -r requirements.txt\n",
        "!pip install wandb\n",
        "!pip install bitsandbytes\n",
        "!pip install transformers gradio ftfy accelerate\n",
        "import gradio"
      ],
      "metadata": {
        "id": "bLBnfVWbSD5D"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install xformers"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p9nbqrLZSD95",
        "outputId": "fec2bda8-4516-4996-bf91-cdef79dd8372"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting xformers\n",
            "  Downloading xformers-0.0.26.post1-cp310-cp310-manylinux2014_x86_64.whl (222.7 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m222.7/222.7 MB\u001b[0m \u001b[31m6.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from xformers) (1.25.2)\n",
            "Requirement already satisfied: torch==2.3.0 in /usr/local/lib/python3.10/dist-packages (from xformers) (2.3.0+cu121)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (3.14.0)\n",
            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (4.12.1)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (1.12.1)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (3.3)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (3.1.4)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (2023.6.0)\n",
            "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (8.9.2.26)\n",
            "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (12.1.3.1)\n",
            "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (11.0.2.54)\n",
            "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (10.3.2.106)\n",
            "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (11.4.5.107)\n",
            "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (12.1.0.106)\n",
            "Requirement already satisfied: nvidia-nccl-cu12==2.20.5 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (2.20.5)\n",
            "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (12.1.105)\n",
            "Requirement already satisfied: triton==2.3.0 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->xformers) (2.3.0)\n",
            "Requirement already satisfied: nvidia-nvjitlink-cu12 in /usr/local/lib/python3.10/dist-packages (from nvidia-cusolver-cu12==11.4.5.107->torch==2.3.0->xformers) (12.5.40)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch==2.3.0->xformers) (2.1.5)\n",
            "Requirement already satisfied: mpmath<1.4.0,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch==2.3.0->xformers) (1.3.0)\n",
            "Installing collected packages: xformers\n",
            "Successfully installed xformers-0.0.26.post1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Utils for Dataset Preprocessing\n",
        "#@markdown * Resize and crop function\n",
        "#@markdown * Function to show images in a one row\n",
        "\n",
        "from PIL import Image\n",
        "import os\n",
        "import IPython.display as display\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def resize_and_crop_images(folder_path, target_size=512):\n",
        "    \"\"\"\n",
        "    Resize the images in a folder to have a smaller edge of the specified target size and display them.\n",
        "\n",
        "    Parameters:\n",
        "    - folder_path (str): Path to the folder containing the images.\n",
        "    - target_size (int): Desired size for the smaller edge (default is 512).\n",
        "    \"\"\"\n",
        "    # Iterate through all files in the folder\n",
        "    for filename in os.listdir(folder_path):\n",
        "        file_path = os.path.join(folder_path, filename)\n",
        "\n",
        "        # Check if the file is an image\n",
        "        if os.path.isfile(file_path) and filename.lower().endswith(('.png', '.jpg', '.jpeg', '.gif', '.bmp')):\n",
        "            # Open the image\n",
        "            image = Image.open(file_path)\n",
        "\n",
        "            # Get the original width and height\n",
        "            width, height = image.size\n",
        "\n",
        "            # Calculate the new size while maintaining the aspect ratio\n",
        "            if width <= height:\n",
        "                new_width = target_size\n",
        "                new_height = int(height * (target_size / width))\n",
        "            else:\n",
        "                new_width = int(width * (target_size / height))\n",
        "                new_height = target_size\n",
        "\n",
        "            # Resize the image\n",
        "            resized_image = image.resize((new_width, new_height))\n",
        "\n",
        "            left = (new_width - target_size) // 2\n",
        "            top = (new_height - target_size) // 2\n",
        "            right = (new_width + target_size) // 2\n",
        "            bottom = (new_height + target_size) // 2\n",
        "\n",
        "            # Perform the center crop\n",
        "            cropped_image = resized_image.crop((left, top, right, bottom))\n",
        "            cropped_image.save(file_path)\n",
        "\n",
        "def show_images_in_one_row(folder_path, target_size=256):\n",
        "    images = []\n",
        "\n",
        "    for filename in os.listdir(folder_path):\n",
        "        file_path = os.path.join(folder_path, filename)\n",
        "        if os.path.isfile(file_path) and filename.lower().endswith(('.png', '.jpg', '.jpeg', '.gif', '.bmp')):\n",
        "            img = Image.open(file_path)\n",
        "            img = img.resize((target_size, int(target_size * img.size[1] / img.size[0])))\n",
        "            images.append(img)\n",
        "\n",
        "    # Display images in one row\n",
        "    fig, axes = plt.subplots(1, len(images), figsize=(len(images) * 3, 3))\n",
        "    for ax, img in zip(axes, images):\n",
        "        ax.imshow(img)\n",
        "        ax.axis('off')\n",
        "    plt.show()"
      ],
      "metadata": {
        "id": "-7Ue5oeGSEB4"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Resize class images to 512x512 for diffusion model\n",
        "folder_path = '/content/unzipped_ThankYou_files/ThankYou' #@param {type:\"string\"}\n",
        "\n",
        "if len(os.listdir(folder_path)):\n",
        "  resize_and_crop_images(folder_path)\n",
        "  show_images_in_one_row(folder_path)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "lFD00IuiSEDY",
        "outputId": "94d950f7-dabe-472e-d1b0-c69a73426a24"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x300 with 5 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Create an output folder for saving the results and checkpoints\n",
        "\n",
        "if os.path.exists(\"/content/outputs\"):\n",
        "    print(\"Removing existing outputs folder\")\n",
        "    !rm -rf /content/outputs\n",
        "\n",
        "print(\"Creating new outputs folder\")\n",
        "!mkdir /content/outputs\n",
        "\n",
        "print('Output folder is created: /content/outputs')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VcV-_2bPSEEn",
        "outputId": "e0c5f6da-2b2d-4d8e-fbf4-4c1c1efdad38"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Creating new outputs folder\n",
            "Output folder is created: /content/outputs\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "\n",
        "# Directory where your 5 images are currently stored\n",
        "original_images_dir = '/content/unzipped_ThankYou_files'\n",
        "\n",
        "# Define paths for instance and class directories\n",
        "instance_data_dir = '/content/custom_dataset/instance_images'\n",
        "class_data_dir = '/content/custom_dataset/class_images'\n",
        "\n",
        "# Create instance and class directories\n",
        "os.makedirs(instance_data_dir, exist_ok=True)\n",
        "os.makedirs(class_data_dir, exist_ok=True)\n"
      ],
      "metadata": {
        "id": "Iipa5okySELX"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import shutil\n",
        "\n",
        "# Copy images to instance directory\n",
        "for file_name in os.listdir(original_images_dir):\n",
        "    full_file_name = os.path.join(original_images_dir, file_name)\n",
        "    if os.path.isfile(full_file_name):\n",
        "        shutil.copy(full_file_name, instance_data_dir)\n"
      ],
      "metadata": {
        "id": "Ajzv8QQISENl"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Copy images to class directory\n",
        "for file_name in os.listdir(original_images_dir):\n",
        "    full_file_name = os.path.join(original_images_dir, file_name)\n",
        "    if os.path.isfile(full_file_name):\n",
        "        shutil.copy(full_file_name, class_data_dir)\n"
      ],
      "metadata": {
        "id": "H1JyFym_SEQH"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/diffusers/examples/dreambooth\n",
        "\n",
        "!python train_dreambooth.py --pretrained_model_name_or_path 'CompVis/stable-diffusion-v1-4' \\\n",
        "                            --revision \"fp16\" \\\n",
        "                            --instance_data_dir '/content/custom_dataset/instance_images' \\\n",
        "                            --class_data_dir '/content/custom_dataset/class_images' \\\n",
        "                            --instance_prompt 'hand sign language for Thank You' \\\n",
        "                            --class_prompt 'hand sign language for Thank You' \\\n",
        "                            --with_prior_preservation \\\n",
        "                            --prior_loss_weight 1.0 \\\n",
        "                            --num_class_images 10 \\\n",
        "                            --output_dir '/content/outputs' \\\n",
        "                            --resolution 512 \\\n",
        "                            --train_text_encoder \\\n",
        "                            --train_batch_size 2 \\\n",
        "                            --sample_batch_size 2 \\\n",
        "                            --max_train_steps 400 \\\n",
        "                            --checkpointing_steps 200 \\\n",
        "                            --gradient_accumulation_steps 1 \\\n",
        "                            --gradient_checkpointing \\\n",
        "                            --learning_rate 1e-6 \\\n",
        "                            --lr_scheduler 'constant' \\\n",
        "                            --lr_warmup_steps=0 \\\n",
        "                            --use_8bit_adam \\\n",
        "                            --validation_prompt 'hand sign language for Thank You' \\\n",
        "                            --num_validation_images 4 \\\n",
        "                            --mixed_precision=\"fp16\" \\\n",
        "                            --enable_xformers_memory_efficient_attention \\\n",
        "                            --set_grads_to_none \\\n",
        "                            # --report_to 'wandb'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sTyCkx9YSETO",
        "outputId": "792445cc-f893-4c8b-e66e-8c541ad55069"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/diffusers/examples/dreambooth\n",
            "/usr/local/lib/python3.10/dist-packages/diffusers/models/transformers/transformer_2d.py:34: FutureWarning: `Transformer2DModelOutput` is deprecated and will be removed in version 1.0.0. Importing `Transformer2DModelOutput` from `diffusers.models.transformer_2d` is deprecated and this will be removed in a future version. Please use `from diffusers.models.modeling_outputs import Transformer2DModelOutput`, instead.\n",
            "  deprecate(\"Transformer2DModelOutput\", \"1.0.0\", deprecation_message)\n",
            "2024-06-05 17:00:12.278707: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
            "2024-06-05 17:00:12.278767: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
            "2024-06-05 17:00:12.376546: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
            "2024-06-05 17:00:12.572731: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
            "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
            "2024-06-05 17:00:14.113833: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "06/05/2024 17:00:16 - INFO - __main__ - Distributed environment: NO\n",
            "Num processes: 1\n",
            "Process index: 0\n",
            "Local process index: 0\n",
            "Device: cuda\n",
            "\n",
            "Mixed precision type: fp16\n",
            "\n",
            "model_index.json: 100% 543/543 [00:00<00:00, 3.15MB/s]\n",
            "/usr/local/lib/python3.10/dist-packages/diffusers/pipelines/pipeline_loading_utils.py:219: FutureWarning: You are loading the variant fp16 from CompVis/stable-diffusion-v1-4 via `revision='fp16'` even though you can load it via `variant=`fp16`. Loading model variants via `revision='fp16'` is deprecated and will be removed in diffusers v1. Please use `variant='fp16'` instead.\n",
            "  warnings.warn(\n",
            "vae/diffusion_pytorch_model.safetensors not found\n",
            "Fetching 14 files:   0% 0/14 [00:00<?, ?it/s]\n",
            "text_encoder/config.json: 100% 572/572 [00:00<00:00, 3.09MB/s]\n",
            "\n",
            "tokenizer/special_tokens_map.json: 100% 472/472 [00:00<00:00, 2.53MB/s]\n",
            "\n",
            "(…)kpoints/scheduler_config-checkpoint.json: 100% 209/209 [00:00<00:00, 1.42MB/s]\n",
            "\n",
            "pytorch_model.bin:   0% 0.00/246M [00:00<?, ?B/s]\u001b[A\n",
            "\n",
            "scheduler/scheduler_config.json: 100% 307/307 [00:00<00:00, 1.77MB/s]\n",
            "\n",
            "\n",
            "tokenizer/merges.txt:   0% 0.00/525k [00:00<?, ?B/s]\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "tokenizer/tokenizer_config.json: 100% 788/788 [00:00<00:00, 3.83MB/s]\n",
            "\n",
            "pytorch_model.bin:   9% 21.0M/246M [00:00<00:01, 147MB/s]\u001b[A\n",
            "\n",
            "\n",
            "unet/config.json: 100% 772/772 [00:00<00:00, 4.23MB/s]\n",
            "\n",
            "\n",
            "\n",
            "(…)ature_extractor/preprocessor_config.json: 100% 342/342 [00:00<00:00, 2.30MB/s]\n",
            "Fetching 14 files:   7% 1/14 [00:00<00:08,  1.46it/s]\n",
            "\n",
            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "\n",
            "diffusion_pytorch_model.bin:  95% 1.64G/1.72G [00:09<00:01, 68.8MB/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "diffusion_pytorch_model.bin:  96% 1.66G/1.72G [00:09<00:00, 81.3MB/s]\u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "diffusion_pytorch_model.bin:  98% 1.69G/1.72G [00:10<00:00, 105MB/s] \u001b[A\u001b[A\u001b[A\n",
            "\n",
            "\n",
            "diffusion_pytorch_model.bin: 100% 1.72G/1.72G [00:10<00:00, 167MB/s]\n",
            "Fetching 14 files: 100% 14/14 [00:11<00:00,  1.27it/s]\n",
            "{'requires_safety_checker', 'image_encoder'} was not found in config. Values will be initialized to default values.\n",
            "Loading pipeline components...:   0% 0/6 [00:00<?, ?it/s]Loaded tokenizer as CLIPTokenizer from `tokenizer` subfolder of CompVis/stable-diffusion-v1-4.\n",
            "Loading pipeline components...:  17% 1/6 [00:00<00:00,  8.08it/s]{'timestep_spacing', 'prediction_type'} was not found in config. Values will be initialized to default values.\n",
            "Loaded scheduler as PNDMScheduler from `scheduler` subfolder of CompVis/stable-diffusion-v1-4.\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/models/clip/feature_extraction_clip.py:28: FutureWarning: The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please use CLIPImageProcessor instead.\n",
            "  warnings.warn(\n",
            "Loaded feature_extractor as CLIPFeatureExtractor from `feature_extractor` subfolder of CompVis/stable-diffusion-v1-4.\n",
            "{'norm_num_groups', 'latents_mean', 'force_upcast', 'latents_std', 'scaling_factor'} was not found in config. Values will be initialized to default values.\n",
            "Loaded vae as AutoencoderKL from `vae` subfolder of CompVis/stable-diffusion-v1-4.\n",
            "Loading pipeline components...:  67% 4/6 [00:00<00:00,  9.25it/s]{'addition_embed_type', 'conv_out_kernel', 'dropout', 'class_embeddings_concat', 'attention_type', 'encoder_hid_dim_type', 'class_embed_type', 'dual_cross_attention', 'upcast_attention', 'resnet_time_scale_shift', 'use_linear_projection', 'resnet_skip_time_act', 'time_embedding_dim', 'projection_class_embeddings_input_dim', 'time_embedding_act_fn', 'addition_embed_type_num_heads', 'time_cond_proj_dim', 'mid_block_only_cross_attention', 'encoder_hid_dim', 'conv_in_kernel', 'only_cross_attention', 'resnet_out_scale_factor', 'num_class_embeds', 'num_attention_heads', 'reverse_transformer_layers_per_block', 'addition_time_embed_dim', 'timestep_post_act', 'cross_attention_norm', 'mid_block_type', 'transformer_layers_per_block', 'time_embedding_type'} was not found in config. Values will be initialized to default values.\n",
            "Loaded unet as UNet2DConditionModel from `unet` subfolder of CompVis/stable-diffusion-v1-4.\n",
            "Loading pipeline components...:  83% 5/6 [00:01<00:00,  2.02it/s]Loaded text_encoder as CLIPTextModel from `text_encoder` subfolder of CompVis/stable-diffusion-v1-4.\n",
            "Loading pipeline components...: 100% 6/6 [00:02<00:00,  2.60it/s]\n",
            "You have disabled the safety checker for <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> by passing `safety_checker=None`. Ensure that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered results in services or applications open to the public. Both the diffusers team and Hugging Face strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling it only for use-cases that involve analyzing network behavior or auditing its results. For more information, please have a look at https://github.com/huggingface/diffusers/pull/254 .\n",
            "06/05/2024 17:00:30 - INFO - __main__ - Number of class images to sample: 10.\n",
            "Generating class images:   0% 0/5 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torch/nn/modules/conv.py:456: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.)\n",
            "  return F.conv2d(input, weight, bias, self.stride,\n",
            "Generating class images: 100% 5/5 [01:10<00:00, 14.00s/it]\n",
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
            "  warnings.warn(\n",
            "You are using a model of type clip_text_model to instantiate a model of type . This is not supported for all configurations of models and can yield errors.\n",
            "scheduler/scheduler_config.json: 100% 313/313 [00:00<00:00, 1.86MB/s]\n",
            "{'timestep_spacing', 'rescale_betas_zero_snr', 'sample_max_value', 'dynamic_thresholding_ratio', 'clip_sample_range', 'prediction_type', 'thresholding', 'variance_type'} was not found in config. Values will be initialized to default values.\n",
            "/usr/local/lib/python3.10/dist-packages/diffusers/utils/hub_utils.py:337: FutureWarning: You are loading the variant fp16 from CompVis/stable-diffusion-v1-4 via `revision='fp16'`. This behavior is deprecated and will be removed in diffusers v1. One should use `variant='fp16'` instead. However, it appears that CompVis/stable-diffusion-v1-4 currently does not have a diffusion_pytorch_model.fp16.safetensors file in the 'main' branch of CompVis/stable-diffusion-v1-4. \n",
            " The Diffusers team and community would be very grateful if you could open an issue: https://github.com/huggingface/diffusers/issues/new with the title 'CompVis/stable-diffusion-v1-4 is missing diffusion_pytorch_model.fp16.safetensors' so that the correct variant file can be added.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/diffusers/utils/hub_utils.py:337: FutureWarning: You are loading the variant fp16 from CompVis/stable-diffusion-v1-4 via `revision='fp16'`. This behavior is deprecated and will be removed in diffusers v1. One should use `variant='fp16'` instead. However, it appears that CompVis/stable-diffusion-v1-4 currently does not have a diffusion_pytorch_model.fp16.bin file in the 'main' branch of CompVis/stable-diffusion-v1-4. \n",
            " The Diffusers team and community would be very grateful if you could open an issue: https://github.com/huggingface/diffusers/issues/new with the title 'CompVis/stable-diffusion-v1-4 is missing diffusion_pytorch_model.fp16.bin' so that the correct variant file can be added.\n",
            "  warnings.warn(\n",
            "{'norm_num_groups', 'latents_mean', 'force_upcast', 'latents_std', 'scaling_factor'} was not found in config. Values will be initialized to default values.\n",
            "{'addition_embed_type', 'conv_out_kernel', 'dropout', 'class_embeddings_concat', 'attention_type', 'encoder_hid_dim_type', 'class_embed_type', 'dual_cross_attention', 'upcast_attention', 'resnet_time_scale_shift', 'use_linear_projection', 'resnet_skip_time_act', 'time_embedding_dim', 'projection_class_embeddings_input_dim', 'time_embedding_act_fn', 'addition_embed_type_num_heads', 'time_cond_proj_dim', 'mid_block_only_cross_attention', 'encoder_hid_dim', 'conv_in_kernel', 'only_cross_attention', 'resnet_out_scale_factor', 'num_class_embeds', 'num_attention_heads', 'reverse_transformer_layers_per_block', 'addition_time_embed_dim', 'timestep_post_act', 'cross_attention_norm', 'mid_block_type', 'transformer_layers_per_block', 'time_embedding_type'} was not found in config. Values will be initialized to default values.\n",
            "06/05/2024 17:01:50 - INFO - __main__ - ***** Running training *****\n",
            "06/05/2024 17:01:50 - INFO - __main__ -   Num examples = 10\n",
            "06/05/2024 17:01:50 - INFO - __main__ -   Num batches each epoch = 5\n",
            "06/05/2024 17:01:50 - INFO - __main__ -   Num Epochs = 80\n",
            "06/05/2024 17:01:50 - INFO - __main__ -   Instantaneous batch size per device = 2\n",
            "06/05/2024 17:01:50 - INFO - __main__ -   Total train batch size (w. parallel, distributed & accumulation) = 2\n",
            "06/05/2024 17:01:50 - INFO - __main__ -   Gradient Accumulation steps = 1\n",
            "06/05/2024 17:01:50 - INFO - __main__ -   Total optimization steps = 400\n",
            "Steps:   0% 0/400 [00:00<?, ?it/s]Traceback (most recent call last):\n",
            "  File \"/content/diffusers/examples/dreambooth/train_dreambooth.py\", line 1443, in <module>\n",
            "    main(args)\n",
            "  File \"/content/diffusers/examples/dreambooth/train_dreambooth.py\", line 1224, in main\n",
            "    for step, batch in enumerate(train_dataloader):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/accelerate/data_loader.py\", line 454, in __iter__\n",
            "    current_batch = next(dataloader_iter)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 631, in __next__\n",
            "    data = self._next_data()\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py\", line 675, in _next_data\n",
            "    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/fetch.py\", line 51, in fetch\n",
            "    data = [self.dataset[idx] for idx in possibly_batched_index]\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/fetch.py\", line 51, in <listcomp>\n",
            "    data = [self.dataset[idx] for idx in possibly_batched_index]\n",
            "  File \"/content/diffusers/examples/dreambooth/train_dreambooth.py\", line 673, in __getitem__\n",
            "    instance_image = Image.open(self.instance_images_path[index % self.num_instance_images])\n",
            "ZeroDivisionError: integer division or modulo by zero\n",
            "Steps:   0% 0/400 [00:00<?, ?it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import locale\n",
        "locale.getpreferredencoding = lambda: \"UTF-8\"\n",
        "\n",
        "!accelerate config default"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8gWWl9_nSEW1",
        "outputId": "953d209f-3f14-4668-cc92-51925fa0987d"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "accelerate configuration saved at /root/.cache/huggingface/accelerate/default_config.yaml\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from huggingface_hub import notebook_login\n",
        "notebook_login()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145,
          "referenced_widgets": [
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          ]
        },
        "id": "MtJo-ye5SEZ0",
        "outputId": "979d241e-afac-4d21-c9a8-a96ddb6e97fe"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f4089dc0ea0c4fc592182c7f51e9c3c2"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from diffusers import DiffusionPipeline, UNet2DConditionModel, StableDiffusionPipeline\n",
        "from transformers import CLIPTextModel, CLIPTokenizer\n",
        "import os\n",
        "\n",
        "# Ensure the output directory exists\n",
        "output_dir = '/content/outputs'\n",
        "os.makedirs(output_dir, exist_ok=True)\n",
        "\n",
        "# Load the text encoder from the Hugging Face Hub\n",
        "text_encoder = CLIPTextModel.from_pretrained('CompVis/stable-diffusion-v1-4', subfolder='text_encoder', use_auth_token=True)\n",
        "\n",
        "# Save the text encoder model along with its configuration\n",
        "text_encoder_output_dir = os.path.join(output_dir, 'text_encoder')\n",
        "os.makedirs(text_encoder_output_dir, exist_ok=True)\n",
        "text_encoder.save_pretrained(text_encoder_output_dir, save_config=True)\n",
        "\n",
        "# Create the diffusion pipeline using the pre-trained model\n",
        "pipeline = DiffusionPipeline.from_pretrained(\"CompVis/stable-diffusion-v1-4\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428,
          "referenced_widgets": [
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        },
        "id": "uJrjNyy8SEdo",
        "outputId": "6ac80975-19da-4b08-c63e-a75aafb593a9"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py:3027: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py:2417: UserWarning: `save_config` is deprecated and will be removed in v5 of Transformers. Use `is_main_process` instead.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
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          "metadata": {}
        },
        {
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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          "metadata": {}
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          "metadata": {}
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          "output_type": "display_data",
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
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          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Demo with Gradio UI for Inference\n",
        "#@markdown The demo can be opened also in **other tab** on your browser or from another **computer** with given public url.\n",
        "#@markdown - **Prompt:** Prompt for generation\n",
        "#@markdown - **Negative Prompt:** Prevent generation from that prompt\n",
        "#@markdown - **Samples:** Number of images that will be generated\n",
        "#@markdown - **Guidance Scale:** It can be said as a coefficient for tune the power of the prompt on the generated images.\n",
        "#@markdown - **Inference Steps:** How many iteration steps while denoising? If the generated images are noisy, try to increase this parameter.\n",
        "#@markdown - **Height and Width:** Highly recommended 512\n",
        "#@markdown - **RUN!**\n",
        "\n",
        "import gradio as gr\n",
        "\n",
        "def inference(prompt, num_samples, negative_prompt, guidance_scale, num_inference_steps, height, width):\n",
        "    all_images = []\n",
        "    images = pipeline(\n",
        "        prompt,\n",
        "        height=height,\n",
        "        width=width,\n",
        "        negative_prompt=negative_prompt,\n",
        "        num_images_per_prompt=num_samples,\n",
        "        num_inference_steps=num_inference_steps,\n",
        "        guidance_scale=guidance_scale\n",
        "    ).images\n",
        "    all_images.extend(images)\n",
        "    return all_images\n",
        "\n",
        "with gr.Blocks() as demo:\n",
        "    gr.HTML(\"<h2 style=\\\"font-size: 2em; font-weight: bold\\\" align=\\\"center\\\">Stable Diffusion Dreambooth - Run Concept</h2>\")\n",
        "    with gr.Row():\n",
        "        with gr.Column():\n",
        "            prompt = gr.Textbox(label=\"Prompt\")\n",
        "            negative_prompt = gr.Textbox(label=\"Negative Prompt\")\n",
        "            samples = gr.Slider(label=\"Samples\", value=1, maximum=12)\n",
        "            guidance_scale = gr.Slider(label=\"Guidance Scale\", value=7.5, maximum=30)\n",
        "            num_inference_steps = gr.Slider(label=\"Inference Steps\", value=50, maximum=500)\n",
        "            height = gr.Slider(label=\"Height\", value=512)\n",
        "            width = gr.Slider(label=\"Width\", value=512)\n",
        "            run = gr.Button(value=\"Run\")\n",
        "        with gr.Column():\n",
        "            gallery = gr.Gallery(show_label=False)\n",
        "\n",
        "    run.click(inference, inputs=[prompt, samples, negative_prompt, guidance_scale, num_inference_steps, height, width], outputs=gallery)\n",
        "    gr.Examples([[\"a photo of sks dog riding a bicycle\", 1, \"\", 7.5, 150, 512, 512]], [prompt, samples, negative_prompt, guidance_scale, num_inference_steps, height, width], gallery, inference, cache_examples=False)\n",
        "\n",
        "demo.launch(debug=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 680,
          "referenced_widgets": [
            "e4d26f2dfb4b416f9a95a5a2edfc6c65",
            "19f43b3da1394456b1b7682abb465964",
            "29240e65836e4bb7901d350ca0dace86",
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            "e1695088ccde46efb40edd30b293065c",
            "d7076cce25f64069ba72634e3fc4a6d1"
          ]
        },
        "id": "hibBx4arSEfv",
        "outputId": "8bcb4a45-976c-4255-9656-63f306ad8901"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
            "\n",
            "Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n",
            "Running on public URL: https://7d3da8c557c878ff52.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<div><iframe src=\"https://7d3da8c557c878ff52.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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          "data": {
            "text/plain": [
              "  0%|          | 0/50 [00:00<?, ?it/s]"
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            "application/vnd.jupyter.widget-view+json": {
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    {
      "cell_type": "code",
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      "metadata": {
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      "outputs": []
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    {
      "cell_type": "code",
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    {
      "cell_type": "code",
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}