Stable_Diffusion.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x9QrInhoCqNL",
        "outputId": "21a45915-6a23-47fa-9793-d1f18c1006b5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: huggingface_hub in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (0.14.1)\n",
            "Requirement already satisfied: filelock in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from huggingface_hub) (3.12.0)\n",
            "Requirement already satisfied: fsspec in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from huggingface_hub) (2023.5.0)\n",
            "Requirement already satisfied: requests in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from huggingface_hub) (2.28.2)\n",
            "Requirement already satisfied: tqdm>=4.42.1 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from huggingface_hub) (4.65.0)\n",
            "Requirement already satisfied: pyyaml>=5.1 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from huggingface_hub) (6.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from huggingface_hub) (4.5.0)\n",
            "Requirement already satisfied: packaging>=20.9 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from huggingface_hub) (23.1)\n",
            "Requirement already satisfied: colorama in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from tqdm>=4.42.1->huggingface_hub) (0.4.6)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from requests->huggingface_hub) (3.1.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from requests->huggingface_hub) (3.4)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from requests->huggingface_hub) (1.26.15)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from requests->huggingface_hub) (2022.12.7)\n"
          ]
        }
      ],
      "source": [
        "!pip install --upgrade huggingface_hub"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145,
          "referenced_widgets": [
            "50cf9445fa504839b10c4be8e854d6d6",
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            "a60966679ecd4468971a6171e0c552cd",
            "c66111fb15a64823bda71e81570845f8",
            "ae1626bb8cb742789d9c8c334b03a331",
            "f7791ad458194a0cbd7e6b1fa61cd72d",
            "a395b098816e42978815678ff8f4b4f9",
            "f7a1344e0f9c48f7907a2e196794a745",
            "892dcc1c83f54416892ffc5899e32ff9",
            "8e9625f91a0d42218d9bb49809b9669e",
            "7600126882e744b3bc8d61780942cf49",
            "f0f08e1e47d640cb865b0f1a5b5b5fe2",
            "a15e7f51f7c8478b9d21c9d802ab5f89",
            "ae6828cde99841bb897a7a3bc6eecdc5",
            "ab73e1c5933a440ba502039d90f86fc5",
            "fd97514be3c0499e896fcdc96750d7a2",
            "6d6367cf011f4788a330ef98bd8e493c",
            "f127a2a384184f7096f3f5cfbbc29835",
            "14daa93667c64bee82eea393c2a217a2",
            "aa04c3a409ec4c2faa5518bb1d7b9857"
          ]
        },
        "id": "k0czjH6YDLwX",
        "outputId": "d723a4f6-55b2-4b64-8593-3bf810b35211"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "6ca9958af9cc47da9fefa4aa24a4feb4",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from huggingface_hub import notebook_login\n",
        "notebook_login()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jHPrtVWlDQEZ",
        "outputId": "7e9994be-d538-4a62-ad03-81a33c5c0833"
      },
      "outputs": [],
      "source": [
        "!pip install -qq -U diffusers transformers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mBoo-l_sE1wo",
        "outputId": "191bc2de-5092-43a5-f733-e35f3bffd909"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: accelerate in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (0.19.0)\n",
            "Requirement already satisfied: numpy>=1.17 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from accelerate) (1.23.5)\n",
            "Requirement already satisfied: packaging>=20.0 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from accelerate) (23.1)\n",
            "Requirement already satisfied: psutil in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from accelerate) (5.9.5)\n",
            "Requirement already satisfied: pyyaml in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from accelerate) (6.0)\n",
            "Requirement already satisfied: torch>=1.6.0 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from accelerate) (2.0.1)\n",
            "Requirement already satisfied: filelock in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from torch>=1.6.0->accelerate) (3.12.0)\n",
            "Requirement already satisfied: typing-extensions in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from torch>=1.6.0->accelerate) (4.5.0)\n",
            "Requirement already satisfied: sympy in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from torch>=1.6.0->accelerate) (1.12)\n",
            "Requirement already satisfied: networkx in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from torch>=1.6.0->accelerate) (3.1)\n",
            "Requirement already satisfied: jinja2 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from torch>=1.6.0->accelerate) (3.1.2)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from jinja2->torch>=1.6.0->accelerate) (2.1.2)\n",
            "Requirement already satisfied: mpmath>=0.19 in c:\\users\\navami\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from sympy->torch>=1.6.0->accelerate) (1.3.0)\n"
          ]
        }
      ],
      "source": [
        "!pip install --upgrade accelerate"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4ZasbayfEGwF",
        "outputId": "40f4952a-f1af-4eb7-d24b-4b356b110fd3"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "`text_config_dict` is provided which will be used to initialize `CLIPTextConfig`. The value `text_config[\"id2label\"]` will be overriden.\n"
          ]
        },
        {
          "ename": "AssertionError",
          "evalue": "Torch not compiled with CUDA enabled",
          "output_type": "error",
          "traceback": [
            "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[1;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
            "Cell \u001b[1;32mIn[16], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mdiffusers\u001b[39;00m \u001b[39mimport\u001b[39;00m StableDiffusionPipeline\n\u001b[1;32m----> 2\u001b[0m pipe \u001b[39m=\u001b[39m StableDiffusionPipeline\u001b[39m.\u001b[39;49mfrom_pretrained(\u001b[39m'\u001b[39;49m\u001b[39mSG161222/Realistic_Vision_V1.4\u001b[39;49m\u001b[39m'\u001b[39;49m)\u001b[39m.\u001b[39;49mto(\u001b[39m'\u001b[39;49m\u001b[39mcuda\u001b[39;49m\u001b[39m'\u001b[39;49m)\n",
            "File \u001b[1;32mc:\\Users\\NAVAMI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\diffusers\\pipelines\\pipeline_utils.py:670\u001b[0m, in \u001b[0;36mDiffusionPipeline.to\u001b[1;34m(self, torch_device, torch_dtype, silence_dtype_warnings)\u001b[0m\n\u001b[0;32m    666\u001b[0m     logger\u001b[39m.\u001b[39mwarning(\n\u001b[0;32m    667\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mThe module \u001b[39m\u001b[39m'\u001b[39m\u001b[39m{\u001b[39;00mmodule\u001b[39m.\u001b[39m\u001b[39m__class__\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__name__\u001b[39m\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m has been loaded in 8bit and moving it to \u001b[39m\u001b[39m{\u001b[39;00mtorch_dtype\u001b[39m}\u001b[39;00m\u001b[39m via `.to()` is not yet supported. Module is still on \u001b[39m\u001b[39m{\u001b[39;00mmodule\u001b[39m.\u001b[39mdevice\u001b[39m}\u001b[39;00m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m    668\u001b[0m     )\n\u001b[0;32m    669\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m--> 670\u001b[0m     module\u001b[39m.\u001b[39;49mto(torch_device, torch_dtype)\n\u001b[0;32m    672\u001b[0m \u001b[39mif\u001b[39;00m (\n\u001b[0;32m    673\u001b[0m     module\u001b[39m.\u001b[39mdtype \u001b[39m==\u001b[39m torch\u001b[39m.\u001b[39mfloat16\n\u001b[0;32m    674\u001b[0m     \u001b[39mand\u001b[39;00m \u001b[39mstr\u001b[39m(torch_device) \u001b[39min\u001b[39;00m [\u001b[39m\"\u001b[39m\u001b[39mcpu\u001b[39m\u001b[39m\"\u001b[39m]\n\u001b[0;32m    675\u001b[0m     \u001b[39mand\u001b[39;00m \u001b[39mnot\u001b[39;00m silence_dtype_warnings\n\u001b[0;32m    676\u001b[0m     \u001b[39mand\u001b[39;00m \u001b[39mnot\u001b[39;00m is_offloaded\n\u001b[0;32m    677\u001b[0m ):\n\u001b[0;32m    678\u001b[0m     logger\u001b[39m.\u001b[39mwarning(\n\u001b[0;32m    679\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39mPipelines loaded with `torch_dtype=torch.float16` cannot run with `cpu` device. It\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m    680\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39m is not recommended to move them to `cpu` as running them will fail. Please make\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    683\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39m `torch_dtype=torch.float16` argument, or use another device for inference.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m    684\u001b[0m     )\n",
            "File \u001b[1;32mc:\\Users\\NAVAMI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\transformers\\modeling_utils.py:1878\u001b[0m, in \u001b[0;36mPreTrainedModel.to\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1873\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[0;32m   1874\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39m`.to` is not supported for `8-bit` models. Please use the model as it is, since the\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m   1875\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39m model has already been set to the correct devices and casted to the correct `dtype`.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m   1876\u001b[0m     )\n\u001b[0;32m   1877\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m-> 1878\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39msuper\u001b[39;49m()\u001b[39m.\u001b[39;49mto(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
            "File \u001b[1;32mc:\\Users\\NAVAMI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1145\u001b[0m, in \u001b[0;36mModule.to\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1141\u001b[0m         \u001b[39mreturn\u001b[39;00m t\u001b[39m.\u001b[39mto(device, dtype \u001b[39mif\u001b[39;00m t\u001b[39m.\u001b[39mis_floating_point() \u001b[39mor\u001b[39;00m t\u001b[39m.\u001b[39mis_complex() \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m,\n\u001b[0;32m   1142\u001b[0m                     non_blocking, memory_format\u001b[39m=\u001b[39mconvert_to_format)\n\u001b[0;32m   1143\u001b[0m     \u001b[39mreturn\u001b[39;00m t\u001b[39m.\u001b[39mto(device, dtype \u001b[39mif\u001b[39;00m t\u001b[39m.\u001b[39mis_floating_point() \u001b[39mor\u001b[39;00m t\u001b[39m.\u001b[39mis_complex() \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m, non_blocking)\n\u001b[1;32m-> 1145\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_apply(convert)\n",
            "File \u001b[1;32mc:\\Users\\NAVAMI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\nn\\modules\\module.py:797\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn)\u001b[0m\n\u001b[0;32m    795\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_apply\u001b[39m(\u001b[39mself\u001b[39m, fn):\n\u001b[0;32m    796\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mchildren():\n\u001b[1;32m--> 797\u001b[0m         module\u001b[39m.\u001b[39;49m_apply(fn)\n\u001b[0;32m    799\u001b[0m     \u001b[39mdef\u001b[39;00m \u001b[39mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[0;32m    800\u001b[0m         \u001b[39mif\u001b[39;00m torch\u001b[39m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[0;32m    801\u001b[0m             \u001b[39m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[0;32m    802\u001b[0m             \u001b[39m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    807\u001b[0m             \u001b[39m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[0;32m    808\u001b[0m             \u001b[39m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n",
            "File \u001b[1;32mc:\\Users\\NAVAMI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\nn\\modules\\module.py:797\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn)\u001b[0m\n\u001b[0;32m    795\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_apply\u001b[39m(\u001b[39mself\u001b[39m, fn):\n\u001b[0;32m    796\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mchildren():\n\u001b[1;32m--> 797\u001b[0m         module\u001b[39m.\u001b[39;49m_apply(fn)\n\u001b[0;32m    799\u001b[0m     \u001b[39mdef\u001b[39;00m \u001b[39mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[0;32m    800\u001b[0m         \u001b[39mif\u001b[39;00m torch\u001b[39m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[0;32m    801\u001b[0m             \u001b[39m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[0;32m    802\u001b[0m             \u001b[39m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    807\u001b[0m             \u001b[39m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[0;32m    808\u001b[0m             \u001b[39m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n",
            "    \u001b[1;31m[... skipping similar frames: Module._apply at line 797 (1 times)]\u001b[0m\n",
            "File \u001b[1;32mc:\\Users\\NAVAMI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\nn\\modules\\module.py:797\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn)\u001b[0m\n\u001b[0;32m    795\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_apply\u001b[39m(\u001b[39mself\u001b[39m, fn):\n\u001b[0;32m    796\u001b[0m     \u001b[39mfor\u001b[39;00m module \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mchildren():\n\u001b[1;32m--> 797\u001b[0m         module\u001b[39m.\u001b[39;49m_apply(fn)\n\u001b[0;32m    799\u001b[0m     \u001b[39mdef\u001b[39;00m \u001b[39mcompute_should_use_set_data\u001b[39m(tensor, tensor_applied):\n\u001b[0;32m    800\u001b[0m         \u001b[39mif\u001b[39;00m torch\u001b[39m.\u001b[39m_has_compatible_shallow_copy_type(tensor, tensor_applied):\n\u001b[0;32m    801\u001b[0m             \u001b[39m# If the new tensor has compatible tensor type as the existing tensor,\u001b[39;00m\n\u001b[0;32m    802\u001b[0m             \u001b[39m# the current behavior is to change the tensor in-place using `.data =`,\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    807\u001b[0m             \u001b[39m# global flag to let the user control whether they want the future\u001b[39;00m\n\u001b[0;32m    808\u001b[0m             \u001b[39m# behavior of overwriting the existing tensor or not.\u001b[39;00m\n",
            "File \u001b[1;32mc:\\Users\\NAVAMI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\nn\\modules\\module.py:820\u001b[0m, in \u001b[0;36mModule._apply\u001b[1;34m(self, fn)\u001b[0m\n\u001b[0;32m    816\u001b[0m \u001b[39m# Tensors stored in modules are graph leaves, and we don't want to\u001b[39;00m\n\u001b[0;32m    817\u001b[0m \u001b[39m# track autograd history of `param_applied`, so we have to use\u001b[39;00m\n\u001b[0;32m    818\u001b[0m \u001b[39m# `with torch.no_grad():`\u001b[39;00m\n\u001b[0;32m    819\u001b[0m \u001b[39mwith\u001b[39;00m torch\u001b[39m.\u001b[39mno_grad():\n\u001b[1;32m--> 820\u001b[0m     param_applied \u001b[39m=\u001b[39m fn(param)\n\u001b[0;32m    821\u001b[0m should_use_set_data \u001b[39m=\u001b[39m compute_should_use_set_data(param, param_applied)\n\u001b[0;32m    822\u001b[0m \u001b[39mif\u001b[39;00m should_use_set_data:\n",
            "File \u001b[1;32mc:\\Users\\NAVAMI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1143\u001b[0m, in \u001b[0;36mModule.to.<locals>.convert\u001b[1;34m(t)\u001b[0m\n\u001b[0;32m   1140\u001b[0m \u001b[39mif\u001b[39;00m convert_to_format \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39mand\u001b[39;00m t\u001b[39m.\u001b[39mdim() \u001b[39min\u001b[39;00m (\u001b[39m4\u001b[39m, \u001b[39m5\u001b[39m):\n\u001b[0;32m   1141\u001b[0m     \u001b[39mreturn\u001b[39;00m t\u001b[39m.\u001b[39mto(device, dtype \u001b[39mif\u001b[39;00m t\u001b[39m.\u001b[39mis_floating_point() \u001b[39mor\u001b[39;00m t\u001b[39m.\u001b[39mis_complex() \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m,\n\u001b[0;32m   1142\u001b[0m                 non_blocking, memory_format\u001b[39m=\u001b[39mconvert_to_format)\n\u001b[1;32m-> 1143\u001b[0m \u001b[39mreturn\u001b[39;00m t\u001b[39m.\u001b[39;49mto(device, dtype \u001b[39mif\u001b[39;49;00m t\u001b[39m.\u001b[39;49mis_floating_point() \u001b[39mor\u001b[39;49;00m t\u001b[39m.\u001b[39;49mis_complex() \u001b[39melse\u001b[39;49;00m \u001b[39mNone\u001b[39;49;00m, non_blocking)\n",
            "File \u001b[1;32mc:\\Users\\NAVAMI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\torch\\cuda\\__init__.py:239\u001b[0m, in \u001b[0;36m_lazy_init\u001b[1;34m()\u001b[0m\n\u001b[0;32m    235\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mRuntimeError\u001b[39;00m(\n\u001b[0;32m    236\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39mCannot re-initialize CUDA in forked subprocess. To use CUDA with \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m    237\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39mmultiprocessing, you must use the \u001b[39m\u001b[39m'\u001b[39m\u001b[39mspawn\u001b[39m\u001b[39m'\u001b[39m\u001b[39m start method\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m    238\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mhasattr\u001b[39m(torch\u001b[39m.\u001b[39m_C, \u001b[39m'\u001b[39m\u001b[39m_cuda_getDeviceCount\u001b[39m\u001b[39m'\u001b[39m):\n\u001b[1;32m--> 239\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mAssertionError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mTorch not compiled with CUDA enabled\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m    240\u001b[0m \u001b[39mif\u001b[39;00m _cudart \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m    241\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mAssertionError\u001b[39;00m(\n\u001b[0;32m    242\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39mlibcudart functions unavailable. It looks like you have a broken build?\u001b[39m\u001b[39m\"\u001b[39m)\n",
            "\u001b[1;31mAssertionError\u001b[0m: Torch not compiled with CUDA enabled"
          ]
        }
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      "source": [
        "from diffusers import StableDiffusionPipeline\n",
        "pipe = StableDiffusionPipeline.from_pretrained('SG161222/Realistic_Vision_V1.4').to('cuda')"
      ]
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        "outputId": "bfd787e2-64f1-4313-832f-8daf6dd8151a"
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        {
          "ename": "NameError",
          "evalue": "name 'pipe' is not defined",
          "output_type": "error",
          "traceback": [
            "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "Cell \u001b[1;32mIn[15], line 7\u001b[0m\n\u001b[0;32m      4\u001b[0m prompt \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39ma cartoon of an indian student\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m      6\u001b[0m \u001b[39m# Pass the prompt in the pipeline\u001b[39;00m\n\u001b[1;32m----> 7\u001b[0m pipe(prompt)\u001b[39m.\u001b[39mimages[\u001b[39m0\u001b[39m]\n",
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        "torch.cuda.empty_cache()\n",
        "# Initialize a prompt\n",
        "prompt = \"a cartoon of an indian student\"\n",
        "\n",
        "# Pass the prompt in the pipeline\n",
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