“DreamBooth_Stable_Diffusion_(NovelAILeaks_Ver_)”的副本.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/toppac/ACbook/blob/master/%E2%80%9CDreamBooth_Stable_Diffusion_(NovelAILeaks_Ver_)%E2%80%9D%E7%9A%84%E5%89%AF%E6%9C%AC.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "XU7NuMAA2drw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8871f4c6-9f4f-4469-aa9e-2bf48b738096"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Tesla T4, 15109 MiB, 15109 MiB\n"
          ]
        }
      ],
      "source": [
        "#@title Check type of GPU and VRAM available.\n",
        "!nvidia-smi --query-gpu=name,memory.total,memory.free --format=csv,noheader"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "aLWXPZqjsZVV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0fe83e41-8a13-4b2a-eccc-290951a0c089",
        "cellView": "form"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Install done.\n"
          ]
        }
      ],
      "source": [
        "#@title Install Requirements\n",
        "from IPython.display import clear_output\n",
        "def cprint(msg):\n",
        "  clear_output()\n",
        "  print(msg)\n",
        "\n",
        "\n",
        "# !curl -LO https://github.com/huggingface/diffusers/raw/main/examples/dreambooth/train_dreambooth.py\n",
        "# use memory-optim version\n",
        "!curl -Lo train_dreambooth.py https://github.com/CCRcmcpe/diffusers/raw/main/examples/dreambooth/train_dreambooth.py\n",
        "!pip install -U pip\n",
        "\n",
        "%pip install wandb\n",
        "%pip install -qq git+https://github.com/CCRcmcpe/diffusers\n",
        "%pip install -q -U --pre triton\n",
        "%pip install -q accelerate==0.12.0 transformers ftfy bitsandbytes gradio\n",
        "%pip install omegaconf einops pytorch_lightning \n",
        "\n",
        "#@title ### Install xformers from precompiled wheel.\n",
        "from subprocess import getoutput\n",
        "from IPython.display import HTML\n",
        "from IPython.display import clear_output\n",
        "import time\n",
        "\n",
        "s = getoutput('nvidia-smi')\n",
        "if 'T4' in s:\n",
        "  gpu = 'T4'\n",
        "elif 'P100' in s:\n",
        "  gpu = 'P100'\n",
        "elif 'V100' in s:\n",
        "  gpu = 'V100'\n",
        "elif 'A100' in s:\n",
        "  gpu = 'A100'\n",
        "\n",
        "while True:\n",
        "    try: \n",
        "        gpu=='T4'or gpu=='P100'or gpu=='V100'or gpu=='A100'\n",
        "        break\n",
        "    except:\n",
        "        pass\n",
        "    print('[1;31mit seems that your GPU is not supported at the moment')\n",
        "    time.sleep(5)\n",
        "\n",
        "if (gpu=='T4'):\n",
        "  %pip install https://github.com/TheLastBen/fast-stable-diffusion/raw/main/precompiled/T4/xformers-0.0.13.dev0-py3-none-any.whl\n",
        "  \n",
        "elif (gpu=='P100'):\n",
        "  %pip install https://github.com/TheLastBen/fast-stable-diffusion/raw/main/precompiled/P100/xformers-0.0.13.dev0-py3-none-any.whl\n",
        "\n",
        "elif (gpu=='V100'):\n",
        "  %pip install https://github.com/TheLastBen/fast-stable-diffusion/raw/main/precompiled/V100/xformers-0.0.13.dev0-py3-none-any.whl\n",
        "\n",
        "elif (gpu=='A100'):\n",
        "  %pip install https://github.com/TheLastBen/fast-stable-diffusion/raw/main/precompiled/A100/xformers-0.0.13.dev0-py3-none-any.whl  \n",
        "\n",
        "cprint(\"Install done.\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Login to wandb to watch training process (Optional)\n",
        "WANDB_KEY = \"\" #@param {type:\"string\"}\n",
        "if WANDB_KEY != \"\":\n",
        "  !wandb login $WANDB_KEY"
      ],
      "metadata": {
        "cellView": "form",
        "id": "-pGMYCm_C0_E"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Download `animefull` model and traindata (example, for nahida)\n",
        "\n",
        "#@markdown Path of model\n",
        "URL = \"https://pub-2fdef7a2969f43289c42ac5ae3412fd4.r2.dev/animefull-pruned.tar\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown Path of the initial model folder.\n",
        "SRC_PATH = \"/content/animefull-pruned\" #@param {type:\"string\"}\n",
        "!mkdir -p $SRC_PATH\n",
        "\n",
        "%cd $SRC_PATH\n",
        "!apt install -y -qq aria2 > /dev/null\n",
        "!aria2c --summary-interval=5 -x 6 --allow-overwrite=true -o data.tar $URL\n",
        "!echo \"Decompressing..\"\n",
        "!tar xf data.tar \n",
        "!echo \"Done\"\n",
        "\n",
        "#@markdown Path of the convert output (as train model input).\n",
        "MODEL_NAME = \"/content/animefull\" #@param {type:\"string\"}\n",
        "\n",
        "%cd /content\n",
        "!curl -Lo convert.py https://github.com/CCRcmcpe/diffusers/raw/main/scripts/convert_original_stable_diffusion_to_diffusers.py\n",
        "!curl -Lo /content/animevae.pt https://pub-2fdef7a2969f43289c42ac5ae3412fd4.r2.dev/animevae.pt\n",
        "!python convert.py --checkpoint_path $SRC_PATH/model.ckpt --original_config_file $SRC_PATH/config.yaml --vae_path animevae.pt --dump_path $MODEL_NAME --scheduler_type ddim\n",
        "\n",
        "\n",
        "download_example_traindata = True #@param {type:\"boolean\"}\n",
        "if download_example_traindata:\n",
        "  !mkdir -p nahida\n",
        "  !curl -L https://pub-2fdef7a2969f43289c42ac5ae3412fd4.r2.dev/train-nahida.tar | tar x -C nahida\n",
        "  !rm -fr nahida/._train*\n"
      ],
      "metadata": {
        "id": "VYQ9Mt1pizKN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "be401880-daa5-40fd-b692-122220161c69"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/animefull-pruned\n",
            "\n",
            "WARNING: apt does not have a stable CLI interface. Use with caution in scripts.\n",
            "\n",
            "\n",
            "10/24 11:24:42 [\u001b[1;32mNOTICE\u001b[0m] Downloading 1 item(s)\n",
            " *** Download Progress Summary as of Mon Oct 24 11:24:48 2022 *** \n",
            "=\n",
            "[#136042 687MiB/3.9GiB(16%) CN:5 DL:124MiB ETA:27s]\n",
            "FILE: /content/animefull-pruned/data.tar\n",
            "-\n",
            "\n",
            " *** Download Progress Summary as of Mon Oct 24 11:24:54 2022 *** \n",
            "=\n",
            "[#136042 1.5GiB/3.9GiB(39%) CN:5 DL:152MiB ETA:16s]\n",
            "FILE: /content/animefull-pruned/data.tar\n",
            "-\n",
            "\n",
            " *** Download Progress Summary as of Mon Oct 24 11:25:00 2022 *** \n",
            "=\n",
            "[#136042 2.3GiB/3.9GiB(60%) CN:5 DL:147MiB ETA:10s]\n",
            "FILE: /content/animefull-pruned/data.tar\n",
            "-\n",
            "\n",
            " *** Download Progress Summary as of Mon Oct 24 11:25:06 2022 *** \n",
            "=\n",
            "[#136042 3.2GiB/3.9GiB(82%) CN:5 DL:146MiB ETA:4s]\n",
            "FILE: /content/animefull-pruned/data.tar\n",
            "-\n",
            "\n",
            " *** Download Progress Summary as of Mon Oct 24 11:25:11 2022 *** \n",
            "=\n",
            "[#136042 3.9GiB/3.9GiB(98%) CN:2 DL:136MiB]\n",
            "FILE: /content/animefull-pruned/data.tar\n",
            "-\n",
            "\n",
            "\u001b[0m\n",
            "10/24 11:25:14 [\u001b[1;32mNOTICE\u001b[0m] Download complete: /content/animefull-pruned/data.tar\n",
            "\n",
            "Download Results:\n",
            "gid   |stat|avg speed  |path/URI\n",
            "======+====+===========+=======================================================\n",
            "136042|\u001b[1;32mOK\u001b[0m  |   127MiB/s|/content/animefull-pruned/data.tar\n",
            "\n",
            "Status Legend:\n",
            "(OK):download completed.\n",
            "Decompressing..\n",
            "Done\n",
            "/content\n",
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            "  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\n",
            "100 30096  100 30096    0     0  78375      0 --:--:-- --:--:-- --:--:-- 78375\n",
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            "100  784M  100  784M    0     0  29.0M      0  0:00:26  0:00:26 --:--:-- 34.1M\n",
            "Downloading: 100% 4.52k/4.52k [00:00<00:00, 4.77MB/s]\n",
            "Downloading: 100% 1.71G/1.71G [01:13<00:00, 23.4MB/s]\n",
            "Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPTextModel: ['vision_model.encoder.layers.21.self_attn.out_proj.weight', 'vision_model.encoder.layers.15.self_attn.q_proj.bias', 'vision_model.encoder.layers.9.self_attn.out_proj.weight', 'vision_model.encoder.layers.18.self_attn.q_proj.bias', 'vision_model.encoder.layers.22.layer_norm1.bias', 'vision_model.encoder.layers.9.mlp.fc2.bias', 'vision_model.encoder.layers.9.layer_norm1.weight', 'vision_model.encoder.layers.20.self_attn.out_proj.bias', 'vision_model.encoder.layers.19.self_attn.v_proj.weight', 'vision_model.encoder.layers.5.layer_norm1.weight', 'vision_model.post_layernorm.weight', 'vision_model.encoder.layers.6.self_attn.q_proj.weight', 'vision_model.encoder.layers.12.layer_norm1.weight', 'vision_model.encoder.layers.12.self_attn.v_proj.bias', 'vision_model.encoder.layers.17.self_attn.out_proj.weight', 'vision_model.encoder.layers.11.self_attn.out_proj.weight', 'vision_model.encoder.layers.11.layer_norm1.weight', 'vision_model.encoder.layers.13.layer_norm2.bias', 'vision_model.encoder.layers.14.self_attn.v_proj.weight', 'vision_model.encoder.layers.2.self_attn.out_proj.weight', 'vision_model.encoder.layers.1.mlp.fc2.weight', 'vision_model.encoder.layers.7.self_attn.out_proj.weight', 'vision_model.encoder.layers.21.mlp.fc2.weight', 'vision_model.embeddings.position_embedding.weight', 'vision_model.encoder.layers.11.self_attn.q_proj.weight', 'vision_model.encoder.layers.10.mlp.fc1.weight', 'vision_model.encoder.layers.10.layer_norm1.weight', 'vision_model.encoder.layers.5.layer_norm2.bias', 'vision_model.encoder.layers.17.self_attn.v_proj.bias', 'vision_model.encoder.layers.2.mlp.fc1.weight', 'vision_model.encoder.layers.2.self_attn.q_proj.weight', 'vision_model.encoder.layers.6.self_attn.out_proj.weight', 'vision_model.encoder.layers.11.layer_norm2.weight', 'vision_model.encoder.layers.22.mlp.fc2.weight', 'vision_model.encoder.layers.9.self_attn.q_proj.bias', 'vision_model.encoder.layers.7.self_attn.v_proj.bias', 'vision_model.encoder.layers.18.layer_norm1.bias', 'vision_model.encoder.layers.11.self_attn.q_proj.bias', 'vision_model.encoder.layers.3.layer_norm1.weight', 'vision_model.encoder.layers.21.layer_norm1.weight', 'vision_model.encoder.layers.11.self_attn.v_proj.bias', 'vision_model.encoder.layers.22.layer_norm2.weight', 'vision_model.encoder.layers.3.self_attn.k_proj.weight', 'vision_model.encoder.layers.19.self_attn.out_proj.bias', 'vision_model.encoder.layers.10.self_attn.q_proj.bias', 'vision_model.encoder.layers.1.self_attn.v_proj.bias', 'vision_model.encoder.layers.18.self_attn.q_proj.weight', 'vision_model.encoder.layers.12.self_attn.v_proj.weight', 'vision_model.encoder.layers.7.self_attn.q_proj.weight', 'vision_model.encoder.layers.1.mlp.fc2.bias', 'vision_model.encoder.layers.11.self_attn.v_proj.weight', 'vision_model.encoder.layers.23.layer_norm1.weight', 'vision_model.encoder.layers.8.layer_norm2.weight', 'vision_model.encoder.layers.22.self_attn.k_proj.weight', 'visual_projection.weight', 'vision_model.encoder.layers.1.layer_norm2.bias', 'vision_model.encoder.layers.15.self_attn.out_proj.bias', 'vision_model.encoder.layers.20.self_attn.q_proj.bias', 'vision_model.encoder.layers.4.self_attn.q_proj.weight', 'vision_model.post_layernorm.bias', 'vision_model.encoder.layers.21.self_attn.v_proj.weight', 'vision_model.encoder.layers.21.mlp.fc1.bias', 'vision_model.encoder.layers.14.self_attn.q_proj.weight', 'vision_model.encoder.layers.13.self_attn.v_proj.bias', 'vision_model.encoder.layers.18.layer_norm2.weight', 'vision_model.encoder.layers.8.mlp.fc1.bias', 'vision_model.encoder.layers.2.self_attn.v_proj.bias', 'vision_model.encoder.layers.2.layer_norm1.bias', 'vision_model.encoder.layers.17.layer_norm1.weight', 'vision_model.encoder.layers.18.layer_norm2.bias', 'vision_model.encoder.layers.22.self_attn.out_proj.bias', 'vision_model.encoder.layers.5.self_attn.q_proj.weight', 'vision_model.encoder.layers.23.layer_norm1.bias', 'vision_model.encoder.layers.23.self_attn.k_proj.weight', 'vision_model.encoder.layers.15.mlp.fc1.bias', 'vision_model.encoder.layers.13.self_attn.v_proj.weight', 'vision_model.encoder.layers.23.self_attn.out_proj.weight', 'vision_model.encoder.layers.23.self_attn.k_proj.bias', 'vision_model.encoder.layers.16.layer_norm2.bias', 'vision_model.encoder.layers.2.layer_norm1.weight', 'vision_model.encoder.layers.0.self_attn.out_proj.weight', 'vision_model.encoder.layers.20.self_attn.k_proj.bias', 'vision_model.encoder.layers.6.self_attn.v_proj.bias', 'vision_model.encoder.layers.12.mlp.fc1.bias', 'vision_model.encoder.layers.19.mlp.fc2.weight', 'vision_model.encoder.layers.6.self_attn.q_proj.bias', 'vision_model.encoder.layers.18.self_attn.k_proj.bias', 'vision_model.encoder.layers.14.layer_norm1.weight', 'vision_model.encoder.layers.15.self_attn.k_proj.bias', 'vision_model.encoder.layers.12.self_attn.k_proj.bias', 'vision_model.encoder.layers.1.self_attn.q_proj.weight', 'vision_model.encoder.layers.3.self_attn.out_proj.weight', 'vision_model.encoder.layers.7.layer_norm2.bias', 'vision_model.encoder.layers.6.layer_norm1.weight', 'vision_model.encoder.layers.14.self_attn.k_proj.weight', 'vision_model.encoder.layers.8.self_attn.q_proj.bias', 'vision_model.encoder.layers.1.self_attn.out_proj.bias', 'vision_model.encoder.layers.21.self_attn.k_proj.bias', 'vision_model.encoder.layers.16.self_attn.k_proj.bias', 'vision_model.encoder.layers.15.layer_norm1.weight', 'vision_model.encoder.layers.13.self_attn.out_proj.weight', 'vision_model.encoder.layers.3.layer_norm2.weight', 'vision_model.encoder.layers.16.layer_norm1.weight', 'vision_model.encoder.layers.5.layer_norm1.bias', 'vision_model.encoder.layers.23.mlp.fc2.bias', 'vision_model.encoder.layers.2.layer_norm2.bias', 'vision_model.encoder.layers.5.self_attn.out_proj.weight', 'vision_model.encoder.layers.4.layer_norm2.bias', 'vision_model.encoder.layers.12.mlp.fc2.weight', 'vision_model.encoder.layers.17.layer_norm2.bias', 'vision_model.encoder.layers.14.mlp.fc2.bias', 'vision_model.encoder.layers.21.self_attn.q_proj.bias', 'vision_model.encoder.layers.21.self_attn.v_proj.bias', 'vision_model.encoder.layers.21.layer_norm1.bias', 'vision_model.encoder.layers.6.layer_norm2.bias', 'vision_model.encoder.layers.10.layer_norm2.weight', 'vision_model.encoder.layers.2.self_attn.k_proj.weight', 'vision_model.encoder.layers.2.self_attn.k_proj.bias', 'vision_model.encoder.layers.11.mlp.fc1.bias', 'vision_model.encoder.layers.10.self_attn.q_proj.weight', 'vision_model.encoder.layers.12.layer_norm2.bias', 'vision_model.encoder.layers.15.self_attn.out_proj.weight', 'vision_model.encoder.layers.16.self_attn.q_proj.weight', 'vision_model.embeddings.patch_embedding.weight', 'vision_model.encoder.layers.9.layer_norm1.bias', 'vision_model.encoder.layers.22.mlp.fc2.bias', 'vision_model.encoder.layers.9.mlp.fc1.bias', 'vision_model.encoder.layers.10.mlp.fc1.bias', 'vision_model.encoder.layers.9.layer_norm2.bias', 'vision_model.encoder.layers.20.layer_norm2.weight', 'vision_model.encoder.layers.18.self_attn.v_proj.bias', 'vision_model.encoder.layers.22.layer_norm1.weight', 'vision_model.encoder.layers.5.mlp.fc1.bias', 'vision_model.encoder.layers.16.self_attn.v_proj.bias', 'vision_model.encoder.layers.10.layer_norm1.bias', 'vision_model.encoder.layers.14.self_attn.out_proj.bias', 'vision_model.encoder.layers.11.mlp.fc1.weight', 'vision_model.encoder.layers.6.self_attn.out_proj.bias', 'vision_model.encoder.layers.18.self_attn.v_proj.weight', 'vision_model.encoder.layers.0.layer_norm1.bias', 'vision_model.encoder.layers.10.layer_norm2.bias', 'vision_model.encoder.layers.4.layer_norm1.weight', 'logit_scale', 'vision_model.encoder.layers.11.self_attn.out_proj.bias', 'vision_model.encoder.layers.12.mlp.fc1.weight', 'vision_model.encoder.layers.1.layer_norm2.weight', 'vision_model.encoder.layers.1.mlp.fc1.bias', 'vision_model.encoder.layers.7.self_attn.k_proj.bias', 'vision_model.encoder.layers.19.self_attn.out_proj.weight', 'vision_model.encoder.layers.7.self_attn.v_proj.weight', 'vision_model.encoder.layers.2.mlp.fc2.bias', 'vision_model.encoder.layers.18.mlp.fc2.bias', 'vision_model.encoder.layers.17.self_attn.k_proj.bias', 'vision_model.encoder.layers.2.self_attn.out_proj.bias', 'vision_model.encoder.layers.14.self_attn.q_proj.bias', 'vision_model.encoder.layers.12.self_attn.q_proj.bias', 'vision_model.encoder.layers.5.self_attn.v_proj.bias', 'vision_model.encoder.layers.16.layer_norm2.weight', 'vision_model.encoder.layers.3.mlp.fc2.bias', 'vision_model.encoder.layers.15.self_attn.k_proj.weight', 'vision_model.encoder.layers.0.mlp.fc1.bias', 'vision_model.encoder.layers.9.self_attn.k_proj.bias', 'vision_model.encoder.layers.3.self_attn.v_proj.weight', 'vision_model.encoder.layers.7.self_attn.k_proj.weight', 'vision_model.encoder.layers.16.mlp.fc2.weight', 'vision_model.encoder.layers.4.mlp.fc2.bias', 'vision_model.encoder.layers.23.mlp.fc1.weight', 'vision_model.encoder.layers.17.mlp.fc1.weight', 'vision_model.encoder.layers.17.self_attn.out_proj.bias', 'vision_model.encoder.layers.15.mlp.fc2.weight', 'vision_model.encoder.layers.23.self_attn.q_proj.weight', 'vision_model.encoder.layers.17.self_attn.q_proj.weight', 'vision_model.encoder.layers.2.self_attn.v_proj.weight', 'vision_model.encoder.layers.16.mlp.fc1.bias', 'vision_model.encoder.layers.4.mlp.fc1.weight', 'vision_model.encoder.layers.1.self_attn.out_proj.weight', 'vision_model.encoder.layers.17.self_attn.q_proj.bias', 'vision_model.encoder.layers.22.self_attn.q_proj.weight', 'vision_model.encoder.layers.6.mlp.fc1.bias', 'vision_model.encoder.layers.20.mlp.fc2.bias', 'vision_model.encoder.layers.18.self_attn.out_proj.bias', 'vision_model.encoder.layers.17.mlp.fc2.weight', 'vision_model.encoder.layers.21.self_attn.out_proj.bias', 'vision_model.encoder.layers.3.layer_norm1.bias', 'vision_model.encoder.layers.9.self_attn.v_proj.weight', 'vision_model.encoder.layers.12.self_attn.q_proj.weight', 'vision_model.encoder.layers.5.mlp.fc2.weight', 'vision_model.encoder.layers.15.mlp.fc1.weight', 'vision_model.encoder.layers.12.self_attn.k_proj.weight', 'vision_model.encoder.layers.12.layer_norm2.weight', 'vision_model.encoder.layers.7.mlp.fc2.bias', 'vision_model.encoder.layers.8.self_attn.out_proj.weight', 'vision_model.encoder.layers.23.self_attn.q_proj.bias', 'vision_model.encoder.layers.17.mlp.fc2.bias', 'vision_model.encoder.layers.5.self_attn.q_proj.bias', 'vision_model.encoder.layers.20.self_attn.q_proj.weight', 'vision_model.encoder.layers.0.self_attn.q_proj.bias', 'vision_model.encoder.layers.15.mlp.fc2.bias', 'vision_model.encoder.layers.3.self_attn.k_proj.bias', 'vision_model.encoder.layers.16.mlp.fc2.bias', 'vision_model.pre_layrnorm.weight', 'vision_model.encoder.layers.5.self_attn.v_proj.weight', 'vision_model.encoder.layers.11.self_attn.k_proj.weight', 'vision_model.encoder.layers.4.self_attn.v_proj.weight', 'vision_model.encoder.layers.23.self_attn.v_proj.weight', 'vision_model.encoder.layers.20.layer_norm1.bias', 'text_projection.weight', 'vision_model.encoder.layers.20.layer_norm2.bias', 'vision_model.encoder.layers.0.layer_norm1.weight', 'vision_model.encoder.layers.13.self_attn.q_proj.weight', 'vision_model.encoder.layers.7.layer_norm1.weight', 'vision_model.encoder.layers.0.mlp.fc2.bias', 'vision_model.encoder.layers.20.layer_norm1.weight', 'vision_model.encoder.layers.10.self_attn.out_proj.bias', 'vision_model.encoder.layers.4.self_attn.k_proj.weight', 'vision_model.encoder.layers.0.mlp.fc2.weight', 'vision_model.encoder.layers.4.self_attn.q_proj.bias', 'vision_model.encoder.layers.17.self_attn.v_proj.weight', 'vision_model.encoder.layers.10.self_attn.out_proj.weight', 'vision_model.encoder.layers.1.layer_norm1.weight', 'vision_model.encoder.layers.8.self_attn.q_proj.weight', 'vision_model.encoder.layers.13.layer_norm1.bias', 'vision_model.encoder.layers.6.mlp.fc1.weight', 'vision_model.encoder.layers.7.mlp.fc1.bias', 'vision_model.encoder.layers.11.self_attn.k_proj.bias', 'vision_model.encoder.layers.0.self_attn.v_proj.bias', 'vision_model.encoder.layers.0.self_attn.k_proj.bias', 'vision_model.encoder.layers.12.self_attn.out_proj.bias', 'vision_model.encoder.layers.0.self_attn.v_proj.weight', 'vision_model.encoder.layers.6.self_attn.k_proj.weight', 'vision_model.encoder.layers.3.mlp.fc1.bias', 'vision_model.encoder.layers.22.layer_norm2.bias', 'vision_model.encoder.layers.19.mlp.fc1.weight', 'vision_model.encoder.layers.8.layer_norm1.bias', 'vision_model.encoder.layers.4.layer_norm2.weight', 'vision_model.encoder.layers.9.self_attn.v_proj.bias', 'vision_model.encoder.layers.10.self_attn.k_proj.bias', 'vision_model.embeddings.position_ids', 'vision_model.encoder.layers.1.self_attn.k_proj.weight', 'vision_model.encoder.layers.7.layer_norm2.weight', 'vision_model.encoder.layers.8.layer_norm1.weight', 'vision_model.encoder.layers.5.self_attn.k_proj.bias', 'vision_model.encoder.layers.23.self_attn.v_proj.bias', 'vision_model.encoder.layers.11.layer_norm1.bias', 'vision_model.encoder.layers.0.self_attn.q_proj.weight', 'vision_model.encoder.layers.16.self_attn.v_proj.weight', 'vision_model.encoder.layers.0.layer_norm2.weight', 'vision_model.encoder.layers.13.self_attn.k_proj.bias', 'vision_model.encoder.layers.17.layer_norm1.bias', 'vision_model.encoder.layers.23.mlp.fc1.bias', 'vision_model.encoder.layers.9.mlp.fc1.weight', 'vision_model.encoder.layers.3.layer_norm2.bias', 'vision_model.encoder.layers.4.layer_norm1.bias', 'vision_model.encoder.layers.14.mlp.fc1.weight', 'vision_model.encoder.layers.8.mlp.fc1.weight', 'vision_model.encoder.layers.17.layer_norm2.weight', 'vision_model.encoder.layers.16.layer_norm1.bias', 'vision_model.encoder.layers.18.mlp.fc1.weight', 'vision_model.encoder.layers.4.self_attn.k_proj.bias', 'vision_model.encoder.layers.22.mlp.fc1.weight', 'vision_model.encoder.layers.2.self_attn.q_proj.bias', 'vision_model.encoder.layers.7.mlp.fc1.weight', 'vision_model.encoder.layers.15.layer_norm2.bias', 'vision_model.encoder.layers.7.self_attn.q_proj.bias', 'vision_model.encoder.layers.13.layer_norm1.weight', 'vision_model.encoder.layers.2.mlp.fc2.weight', 'vision_model.encoder.layers.20.self_attn.v_proj.bias', 'vision_model.encoder.layers.16.mlp.fc1.weight', 'vision_model.encoder.layers.9.self_attn.k_proj.weight', 'vision_model.encoder.layers.0.self_attn.k_proj.weight', 'vision_model.encoder.layers.12.mlp.fc2.bias', 'vision_model.encoder.layers.20.self_attn.k_proj.weight', 'vision_model.encoder.layers.21.mlp.fc2.bias', 'vision_model.encoder.layers.10.self_attn.v_proj.bias', 'vision_model.encoder.layers.16.self_attn.out_proj.weight', 'vision_model.encoder.layers.20.mlp.fc2.weight', 'vision_model.encoder.layers.6.mlp.fc2.bias', 'vision_model.encoder.layers.17.mlp.fc1.bias', 'vision_model.encoder.layers.9.self_attn.out_proj.bias', 'vision_model.encoder.layers.3.self_attn.v_proj.bias', 'vision_model.encoder.layers.9.mlp.fc2.weight', 'vision_model.encoder.layers.19.mlp.fc1.bias', 'vision_model.encoder.layers.3.self_attn.out_proj.bias', 'vision_model.encoder.layers.15.self_attn.v_proj.bias', 'vision_model.encoder.layers.2.mlp.fc1.bias', 'vision_model.encoder.layers.20.mlp.fc1.weight', 'vision_model.encoder.layers.23.self_attn.out_proj.bias', 'vision_model.encoder.layers.13.layer_norm2.weight', 'vision_model.encoder.layers.15.self_attn.q_proj.weight', 'vision_model.encoder.layers.23.layer_norm2.weight', 'vision_model.encoder.layers.21.layer_norm2.weight', 'vision_model.encoder.layers.3.mlp.fc1.weight', 'vision_model.encoder.layers.22.self_attn.v_proj.bias', 'vision_model.encoder.layers.2.layer_norm2.weight', 'vision_model.encoder.layers.1.self_attn.q_proj.bias', 'vision_model.encoder.layers.12.self_attn.out_proj.weight', 'vision_model.encoder.layers.4.mlp.fc2.weight', 'vision_model.encoder.layers.11.mlp.fc2.bias', 'vision_model.embeddings.class_embedding', 'vision_model.encoder.layers.6.self_attn.v_proj.weight', 'vision_model.encoder.layers.15.layer_norm2.weight', 'vision_model.encoder.layers.14.self_attn.v_proj.bias', 'vision_model.encoder.layers.22.mlp.fc1.bias', 'vision_model.encoder.layers.4.mlp.fc1.bias', 'vision_model.encoder.layers.15.layer_norm1.bias', 'vision_model.encoder.layers.21.self_attn.k_proj.weight', 'vision_model.encoder.layers.23.mlp.fc2.weight', 'vision_model.encoder.layers.20.self_attn.v_proj.weight', 'vision_model.encoder.layers.7.mlp.fc2.weight', 'vision_model.encoder.layers.1.layer_norm1.bias', 'vision_model.encoder.layers.18.self_attn.k_proj.weight', 'vision_model.encoder.layers.13.mlp.fc2.weight', 'vision_model.encoder.layers.3.self_attn.q_proj.bias', 'vision_model.encoder.layers.20.mlp.fc1.bias', 'vision_model.encoder.layers.18.layer_norm1.weight', 'vision_model.encoder.layers.15.self_attn.v_proj.weight', 'vision_model.encoder.layers.3.self_attn.q_proj.weight', 'vision_model.encoder.layers.19.self_attn.v_proj.bias', 'vision_model.encoder.layers.14.self_attn.out_proj.weight', 'vision_model.encoder.layers.16.self_attn.k_proj.weight', 'vision_model.encoder.layers.13.mlp.fc2.bias', 'vision_model.encoder.layers.10.mlp.fc2.bias', 'vision_model.encoder.layers.14.mlp.fc1.bias', 'vision_model.encoder.layers.21.mlp.fc1.weight', 'vision_model.encoder.layers.14.layer_norm1.bias', 'vision_model.encoder.layers.8.self_attn.v_proj.weight', 'vision_model.encoder.layers.19.layer_norm1.bias', 'vision_model.encoder.layers.5.mlp.fc1.weight', 'vision_model.encoder.layers.19.self_attn.k_proj.bias', 'vision_model.encoder.layers.14.layer_norm2.weight', 'vision_model.encoder.layers.8.self_attn.k_proj.weight', 'vision_model.encoder.layers.0.self_attn.out_proj.bias', 'vision_model.encoder.layers.12.layer_norm1.bias', 'vision_model.encoder.layers.4.self_attn.out_proj.weight', 'vision_model.encoder.layers.10.self_attn.v_proj.weight', 'vision_model.encoder.layers.6.layer_norm1.bias', 'vision_model.encoder.layers.19.self_attn.q_proj.weight', 'vision_model.encoder.layers.21.layer_norm2.bias', 'vision_model.encoder.layers.1.self_attn.v_proj.weight', 'vision_model.encoder.layers.19.layer_norm1.weight', 'vision_model.encoder.layers.13.self_attn.k_proj.weight', 'vision_model.encoder.layers.19.self_attn.q_proj.bias', 'vision_model.encoder.layers.9.self_attn.q_proj.weight', 'vision_model.encoder.layers.13.self_attn.out_proj.bias', 'vision_model.encoder.layers.9.layer_norm2.weight', 'vision_model.encoder.layers.6.layer_norm2.weight', 'vision_model.encoder.layers.23.layer_norm2.bias', 'vision_model.encoder.layers.8.self_attn.v_proj.bias', 'vision_model.encoder.layers.8.layer_norm2.bias', 'vision_model.encoder.layers.0.layer_norm2.bias', 'vision_model.encoder.layers.19.layer_norm2.bias', 'vision_model.encoder.layers.8.mlp.fc2.weight', 'vision_model.encoder.layers.16.self_attn.out_proj.bias', 'vision_model.encoder.layers.8.mlp.fc2.bias', 'vision_model.encoder.layers.4.self_attn.out_proj.bias', 'vision_model.encoder.layers.21.self_attn.q_proj.weight', 'vision_model.encoder.layers.22.self_attn.q_proj.bias', 'vision_model.encoder.layers.13.self_attn.q_proj.bias', 'vision_model.encoder.layers.14.self_attn.k_proj.bias', 'vision_model.encoder.layers.5.self_attn.out_proj.bias', 'vision_model.encoder.layers.0.mlp.fc1.weight', 'vision_model.encoder.layers.20.self_attn.out_proj.weight', 'vision_model.encoder.layers.10.mlp.fc2.weight', 'vision_model.encoder.layers.1.self_attn.k_proj.bias', 'vision_model.encoder.layers.14.mlp.fc2.weight', 'vision_model.encoder.layers.7.layer_norm1.bias', 'vision_model.encoder.layers.19.self_attn.k_proj.weight', 'vision_model.encoder.layers.19.mlp.fc2.bias', 'vision_model.encoder.layers.13.mlp.fc1.bias', 'vision_model.encoder.layers.11.layer_norm2.bias', 'vision_model.encoder.layers.5.mlp.fc2.bias', 'vision_model.encoder.layers.5.layer_norm2.weight', 'vision_model.encoder.layers.4.self_attn.v_proj.bias', 'vision_model.encoder.layers.19.layer_norm2.weight', 'vision_model.encoder.layers.17.self_attn.k_proj.weight', 'vision_model.pre_layrnorm.bias', 'vision_model.encoder.layers.6.self_attn.k_proj.bias', 'vision_model.encoder.layers.5.self_attn.k_proj.weight', 'vision_model.encoder.layers.14.layer_norm2.bias', 'vision_model.encoder.layers.3.mlp.fc2.weight', 'vision_model.encoder.layers.10.self_attn.k_proj.weight', 'vision_model.encoder.layers.1.mlp.fc1.weight', 'vision_model.encoder.layers.13.mlp.fc1.weight', 'vision_model.encoder.layers.16.self_attn.q_proj.bias', 'vision_model.encoder.layers.18.mlp.fc2.weight', 'vision_model.encoder.layers.18.self_attn.out_proj.weight', 'vision_model.encoder.layers.22.self_attn.out_proj.weight', 'vision_model.encoder.layers.11.mlp.fc2.weight', 'vision_model.encoder.layers.8.self_attn.out_proj.bias', 'vision_model.encoder.layers.6.mlp.fc2.weight', 'vision_model.encoder.layers.7.self_attn.out_proj.bias', 'vision_model.encoder.layers.18.mlp.fc1.bias', 'vision_model.encoder.layers.22.self_attn.v_proj.weight', 'vision_model.encoder.layers.8.self_attn.k_proj.bias', 'vision_model.encoder.layers.22.self_attn.k_proj.bias']\n",
            "- This IS expected if you are initializing CLIPTextModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing CLIPTextModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
            "Downloading: 100% 961k/961k [00:00<00:00, 2.57MB/s]\n",
            "Downloading: 100% 525k/525k [00:00<00:00, 1.68MB/s]\n",
            "Downloading: 100% 389/389 [00:00<00:00, 460kB/s]\n",
            "Downloading: 100% 905/905 [00:00<00:00, 853kB/s]\n",
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            "  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            " 16 46.1M   16 7940k    0     0  10.1M      0  0:00:04 --:--:--  0:00:04 10.1Mtar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            " 78 46.1M   78 36.4M    0     0  21.0M      0  0:00:02  0:00:01  0:00:01 21.0Mtar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.quarantine'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:kMDLabel_xhnxuj5ify5wt3dw4ylvmicpgq'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.macl'\n",
            "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
            "100 46.1M  100 46.1M    0     0  23.6M      0  0:00:01  0:00:01 --:--:-- 23.5M\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Rxg0y5MBudmd",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3bc6687c-769f-4df4-d4a3-3cbda1e58bef"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[*] Weights will be saved at /content/remote/nahida-dreambooth-2\n"
          ]
        }
      ],
      "source": [
        "#@title Settings\n",
        "\n",
        "#@markdown Path for images of the concept for training.\n",
        "INSTANCE_PROMPT = \"nahida\" #@param {type:\"string\"}\n",
        "INSTANCE_DIR = \"/content/nahida\" #@param {type:\"string\"}\n",
        "!mkdir -p $INSTANCE_DIR\n",
        "\n",
        "#@markdown A general name for class like dog for dog images.\n",
        "CLASS_PROMPT = \"masterpiece, looking at viewer, see_through_raincoat,white hair, cat paws , long hair, hair ornament, hair flower, (loli:1.4), white_flower,white_socks ,parted lips, blurry,shirt, Cat_ears,loose coat,((Blue pick dye)),wet_queen_dress,fairy-tale\" #@param {type:\"string\"}\n",
        "CLASS_DIR = \"/content/nahida_autogen\" #@param {type:\"string\"}\n",
        "\n",
        "\n",
        "#@markdown If model weights should be saved directly in google drive (takes around 4-5 GB).\n",
        "save_to_gdrive = False #@param {type:\"boolean\"}\n",
        "if save_to_gdrive:\n",
        "    from google.colab import drive\n",
        "    drive.mount('/content/drive')\n",
        "\n",
        "#@markdown Enter the directory name to save model at.\n",
        "\n",
        "OUTPUT_DIR = \"remote/nahida-dreambooth-2\" #@param {type:\"string\"}\n",
        "if save_to_gdrive:\n",
        "    OUTPUT_DIR = \"/content/drive/MyDrive/\" + OUTPUT_DIR\n",
        "else:\n",
        "    OUTPUT_DIR = \"/content/\" + OUTPUT_DIR\n",
        "\n",
        "print(f\"[*] Weights will be saved at {OUTPUT_DIR}\")\n",
        "\n",
        "!mkdir -p $OUTPUT_DIR"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qn5ILIyDJIcX"
      },
      "source": [
        "## Start Training\n",
        "\n",
        "Use the table below to choose the best flags based on your memory and speed requirements. Tested on Tesla T4 GPU.\n",
        "\n",
        "\n",
        "| `fp16` | `train_batch_size` | `gradient_accumulation_steps` | `gradient_checkpointing` | `use_8bit_adam` | GB VRAM usage | Speed (it/s) |\n",
        "| ---- | ------------------ | ----------------------------- | ----------------------- | --------------- | ---------- | ------------ |\n",
        "| fp16 | 1                  | 1                             | TRUE                    | TRUE            | 9.92       | 0.93         |\n",
        "| no   | 1                  | 1                             | TRUE                    | TRUE            | 10.08      | 0.42         |\n",
        "| fp16 | 2                  | 1                             | TRUE                    | TRUE            | 10.4       | 0.66         |\n",
        "| fp16 | 1                  | 1                             | FALSE                   | TRUE            | 11.17      | 1.14         |\n",
        "| no   | 1                  | 1                             | FALSE                   | TRUE            | 11.17      | 0.49         |\n",
        "| fp16 | 1                  | 2                             | TRUE                    | TRUE            | 11.56      | 1            |\n",
        "| fp16 | 2                  | 1                             | FALSE                   | TRUE            | 13.67      | 0.82         |\n",
        "| fp16 | 1                  | 2                             | FALSE                   | TRUE            | 13.7       | 0.83          |\n",
        "| fp16 | 1                  | 1                             | TRUE                    | FALSE           | 15.79      | 0.77         |\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-ioxxvHoicPs"
      },
      "source": [
        "Add `--gradient_checkpointing` flag for around 9.92 GB VRAM usage.\n",
        "\n",
        "remove `--use_8bit_adam` flag for full precision. Requires 15.79 GB with `--gradient_checkpointing` else 17.8 GB."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jjcSXTp-u-Eg",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ad59cd9e-cee2-4712-8b80-a4884215f5fe"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n",
            "The following values were not passed to `accelerate launch` and had defaults used instead:\n",
            "\t`--num_processes` was set to a value of `1`\n",
            "\t`--num_machines` was set to a value of `1`\n",
            "\t`--mixed_precision` was set to a value of `'no'`\n",
            "\t`--num_cpu_threads_per_process` was set to `1` to improve out-of-box performance\n",
            "To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`.\n",
            "Generating class images: 100% 7/7 [03:43<00:00, 31.99s/it]\n",
            "\n",
            "===================================BUG REPORT===================================\n",
            "Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues\n",
            "For effortless bug reporting copy-paste your error into this form: https://docs.google.com/forms/d/e/1FAIpQLScPB8emS3Thkp66nvqwmjTEgxp8Y9ufuWTzFyr9kJ5AoI47dQ/viewform?usp=sf_link\n",
            "================================================================================\n",
            "/usr/local/lib/python3.7/dist-packages/bitsandbytes/cuda_setup/paths.py:106: UserWarning: /usr/lib64-nvidia did not contain libcudart.so as expected! Searching further paths...\n",
            "  f'{candidate_env_vars[\"LD_LIBRARY_PATH\"]} did not contain '\n",
            "/usr/local/lib/python3.7/dist-packages/bitsandbytes/cuda_setup/paths.py:28: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('\"172.28.0.3\",\"jupyterArgs\"'), PosixPath('\"/usr/local/bin/dap_multiplexer\",\"enableLsp\"'), PosixPath('true}'), PosixPath('{\"kernelManagerProxyPort\"'), PosixPath('6000,\"kernelManagerProxyHost\"'), PosixPath('[\"--ip=172.28.0.2\"],\"debugAdapterMultiplexerPath\"')}\n",
            "  \"WARNING: The following directories listed in your path were found to \"\n",
            "/usr/local/lib/python3.7/dist-packages/bitsandbytes/cuda_setup/paths.py:28: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//ipykernel.pylab.backend_inline'), PosixPath('module')}\n",
            "  \"WARNING: The following directories listed in your path were found to \"\n",
            "/usr/local/lib/python3.7/dist-packages/bitsandbytes/cuda_setup/paths.py:28: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/env/python')}\n",
            "  \"WARNING: The following directories listed in your path were found to \"\n",
            "CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching /usr/local/cuda/lib64...\n",
            "CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so\n",
            "CUDA SETUP: Highest compute capability among GPUs detected: 7.5\n",
            "CUDA SETUP: Detected CUDA version 112\n",
            "CUDA SETUP: Loading binary /usr/local/lib/python3.7/dist-packages/bitsandbytes/libbitsandbytes_cuda112.so...\n",
            "Caching latents: 100% 29/29 [00:10<00:00,  2.65it/s]\n",
            "Steps:  10% 500/5000 [09:28<1:22:39,  1.10s/it, loss=0.357, lr=4.92e-6][*] Weights saved at /content/remote/nahida-dreambooth-2/500\n",
            "Steps:  20% 1000/5000 [19:03<1:13:39,  1.10s/it, loss=0.356, lr=4.6e-6][*] Weights saved at /content/remote/nahida-dreambooth-2/1000\n",
            "Steps:  30% 1500/5000 [28:37<1:04:17,  1.10s/it, loss=0.353, lr=4.06e-6][*] Weights saved at /content/remote/nahida-dreambooth-2/1500\n",
            "Steps:  40% 2000/5000 [38:10<55:13,  1.10s/it, loss=0.354, lr=3.36e-6][*] Weights saved at /content/remote/nahida-dreambooth-2/2000\n",
            "Steps:  50% 2500/5000 [47:43<46:02,  1.11s/it, loss=0.349, lr=2.58e-6][*] Weights saved at /content/remote/nahida-dreambooth-2/2500\n",
            "Steps:  60% 3000/5000 [57:16<36:46,  1.10s/it, loss=0.344, lr=1.79e-6][*] Weights saved at /content/remote/nahida-dreambooth-2/3000\n",
            "Steps:  70% 3500/5000 [1:06:49<27:30,  1.10s/it, loss=0.338, lr=1.07e-6]Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/serialization.py\", line 379, in save\n",
            "    _save(obj, opened_zipfile, pickle_module, pickle_protocol)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/serialization.py\", line 604, in _save\n",
            "    zip_file.write_record(name, storage.data_ptr(), num_bytes)\n",
            "OSError: [Errno 28] No space left on device\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"train_dreambooth.py\", line 750, in <module>\n",
            "    main()\n",
            "  File \"train_dreambooth.py\", line 734, in main\n",
            "    save_weights(global_step)\n",
            "  File \"train_dreambooth.py\", line 639, in save_weights\n",
            "    pipeline.save_pretrained(save_dir)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/diffusers/pipeline_utils.py\", line 181, in save_pretrained\n",
            "    save_method(os.path.join(save_directory, pipeline_component_name))\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/transformers/modeling_utils.py\", line 1621, in save_pretrained\n",
            "    save_function(shard, os.path.join(save_directory, shard_file))\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/serialization.py\", line 380, in save\n",
            "    return\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/serialization.py\", line 259, in __exit__\n",
            "    self.file_like.write_end_of_file()\n",
            "RuntimeError: [enforce fail at inline_container.cc:319] . unexpected pos 248690560 vs 248690448\n",
            "terminate called after throwing an instance of 'c10::Error'\n",
            "  what():  [enforce fail at inline_container.cc:319] . unexpected pos 248690560 vs 248690448\n",
            "frame #0: c10::ThrowEnforceNotMet(char const*, int, char const*, std::string const&, void const*) + 0x55 (0x7f56efc330c5 in /usr/local/lib/python3.7/dist-packages/torch/lib/libc10.so)\n",
            "frame #1: <unknown function> + 0x3441f8c (0x7f571b7f4f8c in /usr/local/lib/python3.7/dist-packages/torch/lib/libtorch_cpu.so)\n",
            "frame #2: mz_zip_writer_add_mem_ex_v2 + 0x5b1 (0x7f571b7ef361 in /usr/local/lib/python3.7/dist-packages/torch/lib/libtorch_cpu.so)\n",
            "frame #3: caffe2::serialize::PyTorchStreamWriter::writeRecord(std::string const&, void const*, unsigned long, bool) + 0xb9 (0x7f571b7f6549 in /usr/local/lib/python3.7/dist-packages/torch/lib/libtorch_cpu.so)\n",
            "frame #4: caffe2::serialize::PyTorchStreamWriter::writeEndOfFile() + 0x2c3 (0x7f571b7f6a13 in /usr/local/lib/python3.7/dist-packages/torch/lib/libtorch_cpu.so)\n",
            "frame #5: caffe2::serialize::PyTorchStreamWriter::~PyTorchStreamWriter() + 0x125 (0x7f571b7f6c85 in /usr/local/lib/python3.7/dist-packages/torch/lib/libtorch_cpu.so)\n",
            "frame #6: <unknown function> + 0x709aa5 (0x7f5741ae2aa5 in /usr/local/lib/python3.7/dist-packages/torch/lib/libtorch_python.so)\n",
            "frame #7: <unknown function> + 0x37a33f (0x7f574175333f in /usr/local/lib/python3.7/dist-packages/torch/lib/libtorch_python.so)\n",
            "frame #8: <unknown function> + 0x37b25f (0x7f574175425f in /usr/local/lib/python3.7/dist-packages/torch/lib/libtorch_python.so)\n",
            "frame #9: /usr/bin/python3() [0x5a2cdc]\n",
            "frame #10: /usr/bin/python3() [0x520fa8]\n",
            "frame #11: /usr/bin/python3() [0x520fbc]\n",
            "frame #12: /usr/bin/python3() [0x520fbc]\n",
            "frame #13: /usr/bin/python3() [0x520fbc]\n",
            "frame #14: /usr/bin/python3() [0x520fbc]\n",
            "frame #15: /usr/bin/python3() [0x520fbc]\n",
            "frame #16: /usr/bin/python3() [0x565691]\n",
            "frame #17: PyDict_SetItemString + 0x50 (0x565df0 in /usr/bin/python3)\n",
            "frame #18: PyImport_Cleanup + 0x7a (0x62fc9a in /usr/bin/python3)\n",
            "frame #19: Py_FinalizeEx + 0x64 (0x609f84 in /usr/bin/python3)\n",
            "frame #20: /usr/bin/python3() [0x64d9c9]\n",
            "frame #21: _Py_UnixMain + 0x2e (0x64dd2e in /usr/bin/python3)\n",
            "frame #22: __libc_start_main + 0xe7 (0x7f575f553c87 in /lib/x86_64-linux-gnu/libc.so.6)\n",
            "frame #23: _start + 0x2a (0x5b636a in /usr/bin/python3)\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/bin/accelerate\", line 8, in <module>\n",
            "    sys.exit(main())\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/accelerate/commands/accelerate_cli.py\", line 43, in main\n",
            "    args.func(args)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/accelerate/commands/launch.py\", line 837, in launch_command\n",
            "    simple_launcher(args)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/accelerate/commands/launch.py\", line 354, in simple_launcher\n",
            "    raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd)\n",
            "subprocess.CalledProcessError: Command '['/usr/bin/python3', 'train_dreambooth.py', '--mixed_precision=fp16', '--pretrained_model_name_or_path=/content/animefull', '--pretrained_vae_name_or_path=/content/animefull/vae', '--instance_data_dir=/content/nahida', '--class_data_dir==/content/nahida_autogen', '--output_dir=/content/remote/nahida-dreambooth-2', '--with_prior_preservation', '--prior_loss_weight=1.0', '--instance_prompt=nahida', '--class_prompt=masterpiece, looking at viewer, see_through_raincoat,white hair, cat paws , long hair, hair ornament, hair flower, (loli:1.4), white_flower,white_socks ,parted lips, blurry,shirt, Cat_ears,loose coat,((Blue pick dye)),wet_queen_dress,fairy-tale', '--seed=1337', '--resolution=512', '--train_batch_size=1', '--gradient_accumulation_steps=1', '--learning_rate=5e-6', '--lr_scheduler=cosine_with_restarts', '--lr_warmup_steps=100', '--num_class_images=25', '--sample_batch_size=4', '--max_train_steps=5000', '--save_interval=500', '--gradient_checkpointing', '--use_8bit_adam']' died with <Signals.SIGABRT: 6>.\n"
          ]
        }
      ],
      "source": [
        "%cd /content\n",
        "!mkdir -p $OUTPUT_DIR\n",
        "!accelerate launch train_dreambooth.py \\\n",
        "  --mixed_precision=\"fp16\" \\\n",
        "  --pretrained_model_name_or_path=$MODEL_NAME \\\n",
        "  --pretrained_vae_name_or_path=$MODEL_NAME/vae \\\n",
        "  --instance_data_dir=$INSTANCE_DIR \\\n",
        "  --class_data_dir==$CLASS_DIR \\\n",
        "  --output_dir=$OUTPUT_DIR \\\n",
        "  --with_prior_preservation --prior_loss_weight=1.0 \\\n",
        "  --instance_prompt=\"{INSTANCE_PROMPT}\" \\\n",
        "  --class_prompt=\"{CLASS_PROMPT}\" \\\n",
        "  --seed=1337 \\\n",
        "  --resolution=512 \\\n",
        "  --train_batch_size=1 \\\n",
        "  --gradient_accumulation_steps=1 \\\n",
        "  --learning_rate=5e-6 \\\n",
        "  --lr_scheduler=\"cosine_with_restarts\" \\\n",
        "  --lr_warmup_steps=100 \\\n",
        "  --num_class_images=25 \\\n",
        "  --sample_batch_size=4 \\\n",
        "  --max_train_steps=5000 \\\n",
        "  --save_interval=500 \\\n",
        "  --gradient_checkpointing \\\n",
        "  --use_8bit_adam\n",
        "\n",
        "# disabled: --not_cache_latents "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5V8wgU0HN-Kq"
      },
      "source": [
        "## Convert weights to ckpt to use in web UIs like AUTOMATIC1111."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "89Az5NUxOWdy",
        "outputId": "63362182-e124-4ebf-c60b-dbc08667b54e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            "  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\n",
            "100  8871  100  8871    0     0  17125      0 --:--:-- --:--:-- --:--:-- 17125\n",
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            "100 87516  100 87516    0     0   178k      0 --:--:-- --:--:-- --:--:--  178k\n",
            "Traceback (most recent call last):\n",
            "  File \"back_convert.py\", line 215, in <module>\n",
            "    unet_state_dict = torch.load(unet_path, map_location=\"cpu\")\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/serialization.py\", line 699, in load\n",
            "    with _open_file_like(f, 'rb') as opened_file:\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/serialization.py\", line 230, in _open_file_like\n",
            "    return _open_file(name_or_buffer, mode)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/torch/serialization.py\", line 211, in __init__\n",
            "    super(_open_file, self).__init__(open(name, mode))\n",
            "FileNotFoundError: [Errno 2] No such file or directory: '/content/remote/nahida-dreambooth-2/checkpoint_last/unet/diffusion_pytorch_model.bin'\n",
            "[*] Converted ckpt saved at /content/remote/nahida-dreambooth-2/model.ckpt\n"
          ]
        }
      ],
      "source": [
        "!curl -Lo back_convert.py https://github.com/huggingface/diffusers/raw/main/scripts/convert_diffusers_to_original_stable_diffusion.py\n",
        "!curl -Lo back_convert_alt.py https://pub-2fdef7a2969f43289c42ac5ae3412fd4.r2.dev/back_convert.py\n",
        "\n",
        "#@markdown Run conversion.\n",
        "ckpt_path = OUTPUT_DIR + \"/model.ckpt\"\n",
        "src_ckpt_path = SRC_PATH + \"/model.ckpt\"\n",
        "use_checkpoint = 'checkpoint_last' #@param {type:\"string\"}\n",
        "use_alt_method = False  #@param {type:\"boolean\"}\n",
        "\n",
        "if use_alt_method:\n",
        "  !python back_convert_alt.py --model_path '{OUTPUT_DIR}/checkpoint_last' --src_path $src_ckpt_path  --checkpoint_path $ckpt_path \n",
        "else:\n",
        "  !python back_convert.py --model_path '{OUTPUT_DIR}/checkpoint_last' --checkpoint_path $ckpt_path \n",
        "\n",
        "print(f\"[*] Converted ckpt saved at {ckpt_path}\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ToNG4fd_dTbF"
      },
      "source": [
        "## Inference"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gW15FjffdTID",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "outputId": "6ac92812-3429-4845-deb0-bba2495c0a46"
      },
      "outputs": [
        {
          "output_type": "error",
          "ename": "OSError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mHFValidationError\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/diffusers/configuration_utils.py\u001b[0m in \u001b[0;36mget_config_dict\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m    233\u001b[0m                     \u001b[0msubfolder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubfolder\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 234\u001b[0;31m                     \u001b[0mrevision\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrevision\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    235\u001b[0m                 )\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/huggingface_hub/file_download.py\u001b[0m in \u001b[0;36mhf_hub_download\u001b[0;34m(repo_id, filename, subfolder, repo_type, revision, library_name, library_version, cache_dir, user_agent, force_download, force_filename, proxies, etag_timeout, resume_download, use_auth_token, local_files_only, legacy_cache_layout)\u001b[0m\n\u001b[1;32m   1021\u001b[0m     storage_folder = os.path.join(\n\u001b[0;32m-> 1022\u001b[0;31m         \u001b[0mcache_dir\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrepo_folder_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepo_id\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrepo_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrepo_type\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrepo_type\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1023\u001b[0m     )\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/huggingface_hub/utils/_validators.py\u001b[0m in \u001b[0;36m_inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     91\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0marg_name\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"repo_id\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 92\u001b[0;31m                 \u001b[0mvalidate_repo_id\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg_value\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     93\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/huggingface_hub/utils/_validators.py\u001b[0m in \u001b[0;36mvalidate_repo_id\u001b[0;34m(repo_id)\u001b[0m\n\u001b[1;32m    136\u001b[0m         raise HFValidationError(\n\u001b[0;32m--> 137\u001b[0;31m             \u001b[0;34m\"Repo id must be in the form 'repo_name' or 'namespace/repo_name':\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    138\u001b[0m             \u001b[0;34mf\" '{repo_id}'. Use `repo_type` argument if needed.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mHFValidationError\u001b[0m: Repo id must be in the form 'repo_name' or 'namespace/repo_name': '/content/remote/nahida-dreambooth-2/checkpoint_last'. Use `repo_type` argument if needed.",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-12-82ea01640155>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0mmodel_path\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mOUTPUT_DIR\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0muse_checkpoint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0mpipe\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mStableDiffusionPipeline\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_pretrained\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch_dtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfloat16\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"cuda\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     12\u001b[0m \u001b[0mg_cuda\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/diffusers/pipeline_utils.py\u001b[0m in \u001b[0;36mfrom_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m    373\u001b[0m                 \u001b[0mlocal_files_only\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlocal_files_only\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    374\u001b[0m                 \u001b[0muse_auth_token\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0muse_auth_token\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 375\u001b[0;31m                 \u001b[0mrevision\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrevision\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    376\u001b[0m             )\n\u001b[1;32m    377\u001b[0m             \u001b[0;31m# make sure we only download sub-folders and `diffusers` filenames\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/diffusers/configuration_utils.py\u001b[0m in \u001b[0;36mget_config_dict\u001b[0;34m(cls, pretrained_model_name_or_path, **kwargs)\u001b[0m\n\u001b[1;32m    259\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    260\u001b[0m                 raise EnvironmentError(\n\u001b[0;32m--> 261\u001b[0;31m                     \u001b[0;34mf\"We couldn't connect to '{HUGGINGFACE_CO_RESOLVE_ENDPOINT}' to load this model, couldn't find it\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    262\u001b[0m                     \u001b[0;34mf\" in the cached files and it looks like {pretrained_model_name_or_path} is not the path to a\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    263\u001b[0m                     \u001b[0;34mf\" directory containing a {cls.config_name} file.\\nCheckout your internet connection or see how to\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mOSError\u001b[0m: We couldn't connect to 'https://huggingface.co' to load this model, couldn't find it in the cached files and it looks like /content/remote/nahida-dreambooth-2/checkpoint_last is not the path to a directory containing a model_index.json file.\nCheckout your internet connection or see how to run the library in offline mode at 'https://huggingface.co/docs/diffusers/installation#offline-mode'."
          ]
        }
      ],
      "source": [
        "import torch\n",
        "import os\n",
        "from torch import autocast\n",
        "from diffusers import StableDiffusionPipeline\n",
        "from IPython.display import display\n",
        "\n",
        "#@markdown Run Gradio UI for generating images.\n",
        "use_checkpoint = 'checkpoint_last' #@param {type:\"string\"}\n",
        "model_path = os.path.join(OUTPUT_DIR, use_checkpoint)\n",
        "\n",
        "pipe = StableDiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float16).to(\"cuda\")\n",
        "g_cuda = None\n",
        "\n",
        "\n",
        "import gradio as gr\n",
        "\n",
        "def inference(prompt, negative_prompt, num_samples, height=512, width=512, num_inference_steps=50, guidance_scale=7.5):\n",
        "    with torch.autocast(\"cuda\"), torch.inference_mode():\n",
        "        return pipe(\n",
        "                prompt, height=int(height), width=int(width),\n",
        "                negative_prompt=negative_prompt,\n",
        "                num_images_per_prompt=int(num_samples),\n",
        "                num_inference_steps=int(num_inference_steps), guidance_scale=guidance_scale,\n",
        "                generator=g_cuda\n",
        "            ).images\n",
        "\n",
        "with gr.Blocks() as demo:\n",
        "    with gr.Row():\n",
        "        with gr.Column():\n",
        "            prompt = gr.Textbox(label=\"Prompt\", value=\"photo of sks guy, digital painting\")\n",
        "            negative_prompt = gr.Textbox(label=\"Negative Prompt\", value=\"\")\n",
        "            run = gr.Button(value=\"Generate\")\n",
        "            with gr.Row():\n",
        "                num_samples = gr.Number(label=\"Number of Samples\", value=4)\n",
        "                guidance_scale = gr.Number(label=\"Guidance Scale\", value=7.5)\n",
        "            with gr.Row():\n",
        "                height = gr.Number(label=\"Height\", value=512)\n",
        "                width = gr.Number(label=\"Width\", value=512)\n",
        "            num_inference_steps = gr.Slider(label=\"Steps\", value=50)\n",
        "        with gr.Column():\n",
        "            gallery = gr.Gallery()\n",
        "\n",
        "    run.click(inference, inputs=[prompt, negative_prompt, num_samples, height, width, num_inference_steps, guidance_scale], outputs=gallery)\n",
        "\n",
        "demo.launch(debug=True)"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [
        "ToNG4fd_dTbF"
      ],
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3.10.7 64-bit",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "name": "python",
      "version": "3.10.7"
    },
    "vscode": {
      "interpreter": {
        "hash": "e7370f93d1d0cde622a1f8e1c04877d8463912d04d973331ad4851f04de6915a"
      }
    },
    "accelerator": "GPU",
    "gpuClass": "standard"
  },
  "nbformat": 4,
  "nbformat_minor": 0
}