Upload sd_token_similarity_calculator.ipynb

Google Colab Notebooks/sd_token_similarity_calculator.ipynb

@@ -539,6 +539,113 @@
         "id": "hyK423TQCRup"
       }
     },
+    {
+      "cell_type": "code",
+      "source": [
+        "# @title Process the raw vocab into json + .safetensor pair\n",
+        "\n",
+        "# NOTE : although they have 1x768 dimension , these are not text_encodings , but token vectors\n",
+        "import json\n",
+        "import pandas as pd\n",
+        "import os\n",
+        "import shelve\n",
+        "import torch\n",
+        "from safetensors.torch import save_file , load_file\n",
+        "import json\n",
+        "\n",
+        "home_directory = '/content/'\n",
+        "using_Kaggle = os.environ.get('KAGGLE_URL_BASE','')\n",
+        "if using_Kaggle : home_directory = '/kaggle/working/'\n",
+        "%cd {home_directory}\n",
+        "#-------#\n",
+        "\n",
+        "# Load the data if not already loaded\n",
+        "try:\n",
+        "    loaded\n",
+        "except:\n",
+        "    %cd {home_directory}\n",
+        "    !git clone https://huggingface.co/datasets/codeShare/text-to-image-prompts\n",
+        "    loaded = True\n",
+        "#--------#\n",
+        "\n",
+        "# User input\n",
+        "target = home_directory + 'text-to-image-prompts/vocab/'\n",
+        "root_output_folder = home_directory + 'output/'\n",
+        "output_folder = root_output_folder  + 'vocab/'\n",
+        "root_filename = 'vocab'\n",
+        "NUM_FILES = 1\n",
+        "#--------#\n",
+        "\n",
+        "# Setup environment\n",
+        "def my_mkdirs(folder):\n",
+        "    if os.path.exists(folder)==False:\n",
+        "        os.makedirs(folder)\n",
+        "#--------#\n",
+        "output_folder_text = output_folder + 'text/'\n",
+        "output_folder_text = output_folder + 'text/'\n",
+        "output_folder_token_vectors = output_folder + 'token_vectors/'\n",
+        "target_raw = target + 'raw/'\n",
+        "%cd {home_directory}\n",
+        "my_mkdirs(output_folder)\n",
+        "my_mkdirs(output_folder_text)\n",
+        "my_mkdirs(output_folder_token_vectors)\n",
+        "#-------#\n",
+        "\n",
+        "%cd {target_raw}\n",
+        "tokens = torch.load(f'{root_filename}.pt' , weights_only=True)\n",
+        "tokens = model.clone().detach()\n",
+        "\n",
+        "\n",
+        "%cd {target_raw}\n",
+        "with open(f'{root_filename}.json', 'r') as f:\n",
+        "    data = json.load(f)\n",
+        "_df = pd.DataFrame({'count': data})['count']\n",
+        "#reverse key and value in the dict\n",
+        "vocab = {\n",
+        "    value : key for key, value in _df.items()\n",
+        "}\n",
+        "#------#\n",
+        "\n",
+        "\n",
+        "tensors = {}\n",
+        "for key in vocab:\n",
+        "  name = vocab[key]\n",
+        "  token = tokens[int(key)]\n",
+        "  tensors[key] = token\n",
+        "#-----#\n",
+        "\n",
+        "%cd {output_folder_token_vectors}\n",
+        "save_file(tensors, \"vocab.safetensors\")\n",
+        "\n",
+        "%cd {output_folder_text}\n",
+        "with open('vocab.json', 'w') as f:\n",
+        "    json.dump(vocab, f)\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "H3JRx5rhWIEo",
+        "outputId": "df7f400b-1f0a-4c1e-c6c9-4c3db0491545",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "execution_count": 26,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "/content\n",
+            "/content\n",
+            "/content/text-to-image-prompts/vocab/raw\n",
+            "/content/text-to-image-prompts/vocab/raw\n",
+            "/content/output/vocab/token_vectors\n",
+            "/content/output/vocab/text\n"
+          ]
+        }
+      ]
+    },
     {
       "cell_type": "code",
       "source": [
@@ -743,10 +850,28 @@
         "!zip -r {zip_dest} {root_output_folder}"
       ],
       "metadata": {
-        "id": "V4YCpmWlkPMG"
+        "id": "V4YCpmWlkPMG",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "9eafe028-a982-4b67-adf3-0633cbbe81f7"
       },
-      "execution_count": null,
-      "outputs": []
+      "execution_count": 27,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "/content\n",
+            "  adding: content/output/ (stored 0%)\n",
+            "  adding: content/output/vocab/ (stored 0%)\n",
+            "  adding: content/output/vocab/text/ (stored 0%)\n",
+            "  adding: content/output/vocab/text/vocab.json (deflated 71%)\n",
+            "  adding: content/output/vocab/token_vectors/ (stored 0%)\n",
+            "  adding: content/output/vocab/token_vectors/vocab.safetensors (deflated 9%)\n"
+          ]
+        }
+      ]
     },
     {
       "cell_type": "code",