latent_blending.ipynb

{
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      "metadata": {
        "id": "t9DPiP5BgqfF"
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      "source": [
        "# Instructions\n",
        "### 0) [optional]: change the model type in the cell below, and BYO-ckpt.\n",
        "### 1) hit the white play button below \n",
        "### 2) grab yourself a coffee 🍹 (10min wait) \n",
        "### 3) scroll all the way to bottom of output and open link \"Running on public URL: https://xxxxxxxxx.gradio.live\" \n",
        "### 4) there are many parameters, read here what they mean: https://github.com/lunarring/latentblending/blob/main/parameters.md\n",
        "👇 (start here, move cursor below finger and play button will appear)"
      ]
    },
    {
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      "execution_count": null,
      "metadata": {
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          "height": 1000,
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        "id": "jgZQj-tE6GWW",
        "outputId": "04e7e6f8-4569-462b-83e8-05eb26159e73"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Installing collected packages: sentencepiece, protobuf, ftfy, huggingface-hub, open-clip-torch\n",
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            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
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            "  Created wheel for antlr4-python3-runtime: filename=antlr4_python3_runtime-4.9.3-py3-none-any.whl size=144575 sha256=4c3089a5fd2660cf8938916989dc92d95679df79fa60107c725ce9d597b5561c\n",
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        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "pydevd_plugins"
                ]
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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Collecting uc-micro-py\n",
            "  Downloading uc_micro_py-1.0.1-py3-none-any.whl (6.2 kB)\n",
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            "Building wheels for collected packages: ffmpy, python-multipart\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpy: filename=ffmpy-0.3.0-py3-none-any.whl size=4711 sha256=e6f285734c2d220275fd83d619b53eff12a63a51db2207d308d8e4aaeb0aefd1\n",
            "  Stored in directory: /root/.cache/pip/wheels/ff/5b/59/913b443e7369dc04b61f607a746b6f7d83fb65e2e19fcc958d\n",
            "  Building wheel for python-multipart (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for python-multipart: filename=python_multipart-0.0.5-py3-none-any.whl size=31678 sha256=a1da63cd4efc2c72da5c43f3d5f62f57ad40c86b3898ea9c392a508753533fca\n",
            "  Stored in directory: /root/.cache/pip/wheels/9e/fc/1c/cf980e6413d3ee8e70cd8f39e2366b0f487e3e221aeb452eb0\n",
            "Successfully built ffmpy python-multipart\n",
            "Installing collected packages: rfc3986, pydub, ffmpy, websockets, uc-micro-py, sniffio, python-multipart, pycryptodome, orjson, mdurl, h11, uvicorn, markdown-it-py, linkify-it-py, anyio, starlette, mdit-py-plugins, httpcore, httpx, fastapi, gradio\n",
            "Successfully installed anyio-3.6.2 fastapi-0.89.1 ffmpy-0.3.0 gradio-3.16.1 h11-0.14.0 httpcore-0.16.3 httpx-0.23.3 linkify-it-py-1.0.3 markdown-it-py-2.1.0 mdit-py-plugins-0.3.3 mdurl-0.1.2 orjson-3.8.5 pycryptodome-3.16.0 pydub-0.25.1 python-multipart-0.0.5 rfc3986-1.5.0 sniffio-1.3.0 starlette-0.22.0 uc-micro-py-1.0.1 uvicorn-0.20.0 websockets-10.4\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting pytorch_lightning\n",
            "  Downloading pytorch_lightning-1.8.6-py3-none-any.whl (800 kB)\n",
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            "\u001b[?25hCollecting torchmetrics>=0.7.0\n",
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            "\u001b[?25hCollecting lightning-utilities!=0.4.0,>=0.3.0\n",
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            "  Downloading tensorboardX-2.5.1-py2.py3-none-any.whl (125 kB)\n",
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            "Collecting protobuf<=3.20.1,>=3.8.0\n",
            "  Downloading protobuf-3.20.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.0 MB)\n",
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            "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests->fsspec[http]>2021.06.0->pytorch_lightning) (4.0.0)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->fsspec[http]>2021.06.0->pytorch_lightning) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->fsspec[http]>2021.06.0->pytorch_lightning) (2022.12.7)\n",
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            "Installing collected packages: protobuf, torchmetrics, tensorboardX, lightning-utilities, pytorch_lightning\n",
            "  Attempting uninstall: protobuf\n",
            "    Found existing installation: protobuf 3.20.3\n",
            "    Uninstalling protobuf-3.20.3:\n",
            "      Successfully uninstalled protobuf-3.20.3\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "tensorflow 2.9.2 requires protobuf<3.20,>=3.9.2, but you have protobuf 3.20.1 which is incompatible.\n",
            "tensorboard 2.9.1 requires protobuf<3.20,>=3.9.2, but you have protobuf 3.20.1 which is incompatible.\n",
            "googleapis-common-protos 1.57.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-translate 3.8.4 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-language 2.6.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-firestore 2.7.3 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-datastore 2.11.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-bigquery 3.4.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-cloud-bigquery-storage 2.17.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\n",
            "google-api-core 2.11.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 3.20.1 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed lightning-utilities-0.5.0 protobuf-3.20.1 pytorch_lightning-1.8.6 tensorboardX-2.5.1 torchmetrics-0.11.0\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting transformers\n",
            "  Downloading transformers-4.25.1-py3-none-any.whl (5.8 MB)\n",
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            "\u001b[?25hCollecting tokenizers!=0.11.3,<0.14,>=0.11.1\n",
            "  Downloading tokenizers-0.13.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.6 MB)\n",
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            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2022.12.7)\n",
            "Installing collected packages: tokenizers, transformers\n",
            "Successfully installed tokenizers-0.13.2 transformers-4.25.1\n",
            "Cloning into 'latentblending'...\n",
            "remote: Enumerating objects: 530, done.\u001b[K\n",
            "remote: Counting objects: 100% (50/50), done.\u001b[K\n",
            "remote: Compressing objects: 100% (37/37), done.\u001b[K\n",
            "remote: Total 530 (delta 24), reused 29 (delta 13), pack-reused 480\u001b[K\n",
            "Receiving objects: 100% (530/530), 8.36 MiB | 6.82 MiB/s, done.\n",
            "Resolving deltas: 100% (301/301), done.\n",
            "Already up to date.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/pytorch_lightning/utilities/distributed.py:258: LightningDeprecationWarning: `pytorch_lightning.utilities.distributed.rank_zero_only` has been deprecated in v1.8.1 and will be removed in v1.10.0. You can import it from `pytorch_lightning.utilities` instead.\n",
            "  rank_zero_deprecation(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2023-01-15 16:09:49--  https://huggingface.co/stabilityai/stable-diffusion-2-1-base/resolve/main/v2-1_512-ema-pruned.ckpt\n",
            "Resolving huggingface.co (huggingface.co)... 54.235.118.239, 3.231.67.228, 2600:1f18:147f:e850:e203:c458:10cd:fc3c, ...\n",
            "Connecting to huggingface.co (huggingface.co)|54.235.118.239|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://cdn-lfs.huggingface.co/repos/24/cb/24cbc2f7542236eb613b4f16b6802d7c2bef443e86cf9d076719733866e66c3a/88ecb782561455673c4b78d05093494b9c539fc6bfc08f3a9a4a0dd7b0b10f36?response-content-disposition=attachment%3B%20filename%3D%22v2-1_512-ema-pruned.ckpt%22&Expires=1674051670&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL3JlcG9zLzI0L2NiLzI0Y2JjMmY3NTQyMjM2ZWI2MTNiNGYxNmI2ODAyZDdjMmJlZjQ0M2U4NmNmOWQwNzY3MTk3MzM4NjZlNjZjM2EvODhlY2I3ODI1NjE0NTU2NzNjNGI3OGQwNTA5MzQ5NGI5YzUzOWZjNmJmYzA4ZjNhOWE0YTBkZDdiMGIxMGYzNj9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPWF0dGFjaG1lbnQlM0IlMjBmaWxlbmFtZSUzRCUyMnYyLTFfNTEyLWVtYS1wcnVuZWQuY2twdCUyMiIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY3NDA1MTY3MH19fV19&Signature=kJC8WBl81~MjK7xt5NvRbmwoUiAw5bvjbeFBCgrGaEkKtZs9ufJDDcTdTH9N7DHR8IviAK14FAfn9XouLcmaGYMhclnLkdWbNPavOMF9gNmqjWvaTeUfslV9XHr~D8rb4Mn~ppw5B2P~3OkzKTEBVtuMXyH-71I38wwxbfCk4WQiHmRlpxAPA9Uq-R8erBTtK26FkJJCYpivHhdPZvoVhsMquvflplZYn-x1-LPxfdD5W-Hf8SvGi6N0iX-r6GnHfjUBzKK09znQ0nv73KRnus1fg-ayl3u20TKPJ~MufcItn8GmJJxVTFOR-2V8oVf29e~OQmYxPnfMXWYfs3lw0A__&Key-Pair-Id=KVTP0A1DKRTAX [following]\n",
            "--2023-01-15 16:09:50--  https://cdn-lfs.huggingface.co/repos/24/cb/24cbc2f7542236eb613b4f16b6802d7c2bef443e86cf9d076719733866e66c3a/88ecb782561455673c4b78d05093494b9c539fc6bfc08f3a9a4a0dd7b0b10f36?response-content-disposition=attachment%3B%20filename%3D%22v2-1_512-ema-pruned.ckpt%22&Expires=1674051670&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL3JlcG9zLzI0L2NiLzI0Y2JjMmY3NTQyMjM2ZWI2MTNiNGYxNmI2ODAyZDdjMmJlZjQ0M2U4NmNmOWQwNzY3MTk3MzM4NjZlNjZjM2EvODhlY2I3ODI1NjE0NTU2NzNjNGI3OGQwNTA5MzQ5NGI5YzUzOWZjNmJmYzA4ZjNhOWE0YTBkZDdiMGIxMGYzNj9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPWF0dGFjaG1lbnQlM0IlMjBmaWxlbmFtZSUzRCUyMnYyLTFfNTEyLWVtYS1wcnVuZWQuY2twdCUyMiIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY3NDA1MTY3MH19fV19&Signature=kJC8WBl81~MjK7xt5NvRbmwoUiAw5bvjbeFBCgrGaEkKtZs9ufJDDcTdTH9N7DHR8IviAK14FAfn9XouLcmaGYMhclnLkdWbNPavOMF9gNmqjWvaTeUfslV9XHr~D8rb4Mn~ppw5B2P~3OkzKTEBVtuMXyH-71I38wwxbfCk4WQiHmRlpxAPA9Uq-R8erBTtK26FkJJCYpivHhdPZvoVhsMquvflplZYn-x1-LPxfdD5W-Hf8SvGi6N0iX-r6GnHfjUBzKK09znQ0nv73KRnus1fg-ayl3u20TKPJ~MufcItn8GmJJxVTFOR-2V8oVf29e~OQmYxPnfMXWYfs3lw0A__&Key-Pair-Id=KVTP0A1DKRTAX\n",
            "Resolving cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)... 13.227.254.33, 13.227.254.123, 13.227.254.52, ...\n",
            "Connecting to cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)|13.227.254.33|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 5214865159 (4.9G) [binary/octet-stream]\n",
            "Saving to: ‘v2-1_512-ema-pruned.ckpt’\n",
            "\n",
            "v2-1_512-ema-pruned 100%[===================>]   4.86G   184MB/s    in 30s     \n",
            "\n",
            "2023-01-15 16:10:20 (166 MB/s) - ‘v2-1_512-ema-pruned.ckpt’ saved [5214865159/5214865159]\n",
            "\n",
            "--2023-01-15 16:10:20--  http://v2-1_512-ema-pruned.ckpt/\n",
            "Resolving v2-1_512-ema-pruned.ckpt (v2-1_512-ema-pruned.ckpt)... failed: Name or service not known.\n",
            "wget: unable to resolve host address ‘v2-1_512-ema-pruned.ckpt’\n",
            "FINISHED --2023-01-15 16:10:20--\n",
            "Total wall clock time: 31s\n",
            "Downloaded: 1 files, 4.9G in 30s (166 MB/s)\n",
            "LatentDiffusion: Running in eps-prediction mode\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.\n",
            "Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.\n",
            "DiffusionWrapper has 865.91 M params.\n",
            "making attention of type 'vanilla-xformers' with 512 in_channels\n",
            "building MemoryEfficientAttnBlock with 512 in_channels...\n",
            "Working with z of shape (1, 4, 32, 32) = 4096 dimensions.\n",
            "making attention of type 'vanilla-xformers' with 512 in_channels\n",
            "building MemoryEfficientAttnBlock with 512 in_channels...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/3.94G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "341059598bb54246ad013a06228104a4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n",
            "Running on public URL: https://3e25df32-cc36-4745.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spaces\n",
            "STARTING DIFFUSION!\n",
            "autosetup_branching: num_inference_steps: 20 list_nmb_branches: [2, 3, 5, 9] list_injection_idx: [0, 5, 11, 17]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "computing transition:   0%|          | 0/21 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "65415aaafdac4b48b69ad524a6cd6450"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Latent Blending pass finished. Resulted in 9 images\n",
            "MovieSaver initialized. fps=30 crf=24 pix_fmt=yuv420p codec=libx264 preset=fast\n"
          ]
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a658eabcd03b4f28913e51f0f6aba716"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Initialization done. Movie shape: (512, 512, 3)\n",
            "Movie saved, 10s playtime, watch here: \n",
            "movie_230115_161425.mp4\n",
            "DONE SAVING MOVIE! SENDING BACK...\n",
            "Keyboard interruption in main thread... closing server.\n",
            "Killing tunnel 127.0.0.1:7860 <> https://3e25df32-cc36-4745.gradio.live\n"
          ]
        }
      ],
      "source": [
        "!pip install wget\n",
        "import wget\n",
        "import os\n",
        "\n",
        "import requests\n",
        "model = 'v2-1_512-ema-pruned' #@param [\"v2-1_512-ema-pruned\", \"v2-1_768-ema-pruned\", \"v1.5\"]\n",
        "#@markdown Optionally, specify your own checkpoint below. Make sure to select the correct model above.\n",
        "url_ckpt = \"\" #@param {type:\"string\"}\n",
        "\n",
        "if len(url_ckpt) < 1:\n",
        "  if model == \"v2-1_512-ema-pruned\":\n",
        "    url_ckpt = \"https://huggingface.co/stabilityai/stable-diffusion-2-1-base/resolve/main/v2-1_512-ema-pruned.ckpt\"\n",
        "    fp_config = 'latentblending/configs/v2-inference.yaml'\n",
        "  elif model == \"v2-1_768-ema-pruned\":\n",
        "    url_ckpt = \"https://huggingface.co/stabilityai/stable-diffusion-2-1/resolve/main/v2-1_768-ema-pruned.ckpt\"\n",
        "    fp_config = 'latentblending/configs/v2-inference-v.yaml'\n",
        "\n",
        "# Check that the supplied URLs exist.\n",
        "response = requests.head(url_ckpt)\n",
        "if response.status_code != 200 and response.status_code != 302:\n",
        "  raise ValueError(f\"url_ckpt could not be downloaded: {url_ckpt} gives {response.status_code}\")\n",
        "fp_ckpt = 'model.ckpt'\n",
        "wget.download(url_ckpt, fp_ckpt)\n",
        "assert os.path.isfile(fp_ckpt), \"model download has failed.\"\n",
        "\n",
        "\n",
        "if model == \"v2-1_512-ema-pruned\":\n",
        "  fp_config = 'latentblending/configs/v2-inference.yaml'\n",
        "elif model == \"v2-1_768-ema-pruned\":\n",
        "  fp_config = 'latentblending/configs/v2-inference-v.yaml'\n",
        "elif model == 'v1.5':\n",
        "  fp_config = 'latentblending/configs/v1-inference.yaml'\n",
        "\n",
        "print(f\"url_ckpt: {url_ckpt} fp_config {fp_config}\")\n",
        "\n",
        "\n",
        "# installs\n",
        "!pip install open-clip-torch\n",
        "!pip install omegaconf\n",
        "!pip install fastcore -U\n",
        "!pip install Pillow\n",
        "!pip install ffmpeg-python\n",
        "!pip install einops\n",
        "!pip install gradio\n",
        "\n",
        "import os, sys\n",
        "from subprocess import getoutput\n",
        "\n",
        "# Xformers\n",
        "os.system(\"pip install --extra-index-url https://download.pytorch.org/whl/cu113 torch torchvision==0.13.1+cu113\")\n",
        "os.system(\"pip install triton==2.0.0.dev20220701\")\n",
        "gpu_info = getoutput('nvidia-smi')\n",
        "if(\"A10G\" in gpu_info):\n",
        "    os.system(f\"pip install -q https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.15/xformers-0.0.15.dev0+4c06c79.d20221205-cp38-cp38-linux_x86_64.whl\")\n",
        "elif(\"T4\" in gpu_info):\n",
        "    os.system(f\"pip install -q https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.15/xformers-0.0.15.dev0+1515f77.d20221130-cp38-cp38-linux_x86_64.whl\")\n",
        "\n",
        "!pip install pytorch_lightning\n",
        "!pip install transformers\n",
        "\n",
        "# Get Latent Blending from git / pull \n",
        "!git clone https://github.com/lunarring/latentblending\n",
        "!cd latentblending; git pull; cd ..\n",
        "sys.path.append(\"/content/latentblending\")\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "# Imports\n",
        "import torch\n",
        "import numpy as np\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "import warnings\n",
        "import torch\n",
        "from tqdm.auto import tqdm\n",
        "from PIL import Image\n",
        "import torch\n",
        "from typing import Callable, List, Optional, Union\n",
        "from latent_blending import LatentBlending, add_frames_linear_interp, get_time, yml_save, LatentBlending, compare_dicts\n",
        "from stable_diffusion_holder import StableDiffusionHolder\n",
        "from gradio_ui import BlendingFrontend\n",
        "import gradio as gr\n",
        "\n",
        "torch.set_grad_enabled(False)\n",
        "torch.backends.cudnn.benchmark = False\n",
        "\n",
        "\n",
        "#%% First let us spawn a stable diffusion holder\n",
        "device = \"cuda\" \n",
        "\n",
        "\n",
        "sdh = StableDiffusionHolder(fp_ckpt, fp_config, device) \n",
        "\n",
        "from latent_blending import get_time, yml_save, LatentBlending, add_frames_linear_interp, compare_dicts\n",
        "from gradio_ui import BlendingFrontend\n",
        "\n",
        "import gradio as gr\n",
        "\n",
        "if __name__ == \"__main__\":    \n",
        "    \n",
        "    self = BlendingFrontend(sdh) # Yes this is possible in python and yes it is an awesome trick\n",
        "    \n",
        "    with gr.Blocks() as demo:\n",
        "        with gr.Row():\n",
        "            prompt1 = gr.Textbox(label=\"prompt 1\")\n",
        "            prompt2 = gr.Textbox(label=\"prompt 2\")\n",
        "            negative_prompt = gr.Textbox(label=\"negative prompt\")          \n",
        "            \n",
        "        with gr.Row():\n",
        "            nmb_branches_final = gr.Slider(5, 125, self.nmb_branches_final, step=4, label='nmb trans images', interactive=True) \n",
        "            height = gr.Slider(256, 2048, self.height, step=128, label='height', interactive=True)\n",
        "            width = gr.Slider(256, 2048, self.width, step=128, label='width', interactive=True) \n",
        "            \n",
        "        with gr.Row():\n",
        "            num_inference_steps = gr.Slider(5, 100, self.num_inference_steps, step=1, label='num_inference_steps', interactive=True)\n",
        "            branch1_influence = gr.Slider(0.0, 1.0, self.branch1_influence, step=0.01, label='branch1_influence', interactive=True) \n",
        "            guidance_scale = gr.Slider(1, 25, self.guidance_scale, step=0.1, label='guidance_scale', interactive=True) \n",
        "    \n",
        "        with gr.Row():\n",
        "            depth_strength = gr.Slider(0.01, 0.99, self.depth_strength, step=0.01, label='depth_strength', interactive=True) \n",
        "            duration = gr.Slider(0.1, 30, self.duration, step=0.1, label='video duration', interactive=True) \n",
        "            guidance_scale_mid_damper = gr.Slider(0.01, 2.0, self.guidance_scale_mid_damper, step=0.01, label='guidance_scale_mid_damper', interactive=True) \n",
        "            \n",
        "        with gr.Row():\n",
        "            seed1 = gr.Number(42, label=\"seed 1\", interactive=True)\n",
        "            b_newseed1 = gr.Button(\"randomize seed 1\", variant='secondary')\n",
        "            seed2 = gr.Number(420, label=\"seed 2\", interactive=True)\n",
        "            b_newseed2 = gr.Button(\"randomize seed 2\", variant='secondary')\n",
        "        with gr.Row():\n",
        "            b_compute_transition = gr.Button('compute transition', variant='primary')\n",
        "        \n",
        "        with gr.Row():\n",
        "            img1 = gr.Image(label=\"1/5\")\n",
        "            img2 = gr.Image(label=\"2/5\")\n",
        "            img3 = gr.Image(label=\"3/5\")\n",
        "            img4 = gr.Image(label=\"4/5\")\n",
        "            img5 = gr.Image(label=\"5/5\")\n",
        "        \n",
        "        with gr.Row():\n",
        "            vid_transition = gr.Video()\n",
        "        \n",
        "        # Bind the on-change methods\n",
        "        depth_strength.change(fn=self.change_depth_strength, inputs=depth_strength)\n",
        "        num_inference_steps.change(fn=self.change_num_inference_steps, inputs=num_inference_steps)\n",
        "        nmb_branches_final.change(fn=self.change_nmb_branches_final, inputs=nmb_branches_final)\n",
        "        \n",
        "        guidance_scale.change(fn=self.change_guidance_scale, inputs=guidance_scale)\n",
        "        guidance_scale_mid_damper.change(fn=self.change_guidance_scale_mid_damper, inputs=guidance_scale_mid_damper)\n",
        "        \n",
        "        height.change(fn=self.change_height, inputs=height)\n",
        "        width.change(fn=self.change_width, inputs=width)\n",
        "        negative_prompt.change(fn=self.change_negative_prompt, inputs=negative_prompt)\n",
        "        seed1.change(fn=self.change_seed1, inputs=seed1)\n",
        "        seed2.change(fn=self.change_seed2, inputs=seed2)\n",
        "        duration.change(fn=self.change_duration, inputs=duration)\n",
        "        branch1_influence.change(fn=self.change_branch1_influence, inputs=branch1_influence)\n",
        "    \n",
        "        b_newseed1.click(self.randomize_seed1, outputs=seed1)\n",
        "        b_newseed2.click(self.randomize_seed2, outputs=seed2)\n",
        "        b_compute_transition.click(self.compute_transition, \n",
        "                                   inputs=[prompt1, prompt2],\n",
        "                                   outputs=[img1, img2, img3, img4, img5, vid_transition])\n",
        "        \n",
        "    demo.launch(share=self.share, inbrowser=True, inline=False, debug=True)\n"
      ]
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