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Google Colab Notebooks/sd_token_similarity_calculator.ipynb

@@ -251,10 +251,32 @@
         "\n"
       ],
       "metadata": {
-        "id": "rUXQ73IbonHY"
+        "id": "rUXQ73IbonHY",
+        "outputId": "18df4768-39a6-4ca9-8c5a-47317001e907",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
       },
-      "execution_count": null,
-      "outputs": []
+      "execution_count": 1,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "/content\n",
+            "/content\n",
+            "Cloning into 'text-to-image-prompts'...\n",
+            "remote: Enumerating objects: 6051, done.\u001b[K\n",
+            "remote: Counting objects: 100% (4169/4169), done.\u001b[K\n",
+            "remote: Compressing objects: 100% (2335/2335), done.\u001b[K\n",
+            "remote: Total 6051 (delta 2075), reused 3837 (delta 1821), pack-reused 1882 (from 1)\u001b[K\n",
+            "Receiving objects: 100% (6051/6051), 37.71 MiB | 6.04 MiB/s, done.\n",
+            "Resolving deltas: 100% (2075/2075), done.\n",
+            "Updating files: 100% (3079/3079), done.\n",
+            "Filtering content: 100% (776/776), 2.23 GiB | 38.41 MiB/s, done.\n"
+          ]
+        }
+      ]
     },
     {
       "cell_type": "code",
@@ -2857,8 +2879,104 @@
         "\n"
       ],
       "metadata": {
-        "id": "JR0wl2ecj6RJ",
-        "cellView": "form"
+        "id": "JR0wl2ecj6RJ"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# @title Create random suffix pairings\n",
+        "import random\n",
+        "import json\n",
+        "import pandas as pd\n",
+        "import os\n",
+        "import shelve\n",
+        "import torch\n",
+        "from safetensors.torch import save_file\n",
+        "\n",
+        "\n",
+        "def my_mkdirs(folder):\n",
+        "  if os.path.exists(folder)==False:\n",
+        "    os.makedirs(folder)\n",
+        "\n",
+        "\n",
+        "output_folder = '/content/output/prefix_suffix_pairs/'\n",
+        "my_mkdirs(output_folder)\n",
+        "\n",
+        "_prompts = {}\n",
+        "_text_encodings = {}\n",
+        "nA = 0\n",
+        "\n",
+        "try: loaded3\n",
+        "except:\n",
+        "  loaded3 = True\n",
+        "  if True:\n",
+        "    tmp = '/content/text-to-image-prompts/vocab/text_encodings/prefix/'\n",
+        "    for item in ['common','average','rare','weird','exotic'] :\n",
+        "      url =  tmp  + item\n",
+        "      prefix, text_encodings, PREFIX_NUM_VOCAB_ITEMS = append_from_url(_prompts , _text_encodings, nA , url , '')\n",
+        "  #------#\n",
+        "\n",
+        "  if True :\n",
+        "    tmp = '/content/text-to-image-prompts/vocab/text_encodings/suffix/'\n",
+        "    for item in ['common','average','rare','weird','exotic'] :\n",
+        "      url =  tmp  + item\n",
+        "      suffix , text_encodings, SUFFIX_NUM_VOCAB_ITEMS = append_from_url(_prompts , _text_encodings, nA , url , '')\n",
+        "  #------#\n",
+        "\n",
+        "  if False :\n",
+        "    url = '/content/text-to-image-prompts/vocab/text_encodings/emoji/'\n",
+        "    prompts , emojis_text_encodings, NUM_VOCAB_ITEMS = append_from_url(_prompts , _text_encodings, nA , url , '')\n",
+        "  #------#\n",
+        "#--------#\n",
+        "\n",
+        "if False:\n",
+        "  item3 = '#uc# '\n",
+        "  while (item3.find('#uc#')>-1 or (not item3.isalpha())) :\n",
+        "    item3 = prompts[f'{random.randint(0,NUM_VOCAB_ITEMS)}']\n",
+        "    item3 = item3.replace('</w>', '')\n",
+        "  #------#\n",
+        "\n",
+        "  item4 = '#uc# '\n",
+        "  while (item4.find('#uc#')>-1 or (not item4.isalpha())) :\n",
+        "    item4 = prompts[f'{random.randint(0,NUM_VOCAB_ITEMS)}']\n",
+        "    item4 = item4.replace('</w>', '')\n",
+        "  #------#\n",
+        "#------#\n",
+        "\n",
+        "\n",
+        "output = ''\n",
+        "%cd {output_folder}\n",
+        "with open('prefix_suffix_pairs' + '.txt', 'w') as f:\n",
+        "  for iter in range (200000):\n",
+        "    item = '#uc# '\n",
+        "    while (not item.isalpha()) :\n",
+        "      item = prefix[f'{random.randint(0,PREFIX_NUM_VOCAB_ITEMS)}']\n",
+        "      item = item.replace('</w>', '')\n",
+        "\n",
+        "    item2 = '#uc# '\n",
+        "    while (item2.find('#uc#')>-1 or (not item2.isalpha())) :\n",
+        "      item2 = suffix[f'{random.randint(0,SUFFIX_NUM_VOCAB_ITEMS)}']\n",
+        "      item2 = item2.replace('</w>', '')\n",
+        "\n",
+        "    item3 = '#uc# '\n",
+        "    while (item3.find('#uc#')>-1 or (not item3.isalpha())) :\n",
+        "      item3 = suffix[f'{random.randint(0,SUFFIX_NUM_VOCAB_ITEMS)}']\n",
+        "      item3 = item3.replace('</w>', '')\n",
+        "    #------#\n",
+        "\n",
+        "    #------#\n",
+        "    output = output + item + '-' +  item2 + ' ' +  item3\n",
+        "    # + ' ' +  item4\n",
+        "    output = output + ' \\n'\n",
+        "  #---------#\n",
+        "  f.write(str(output))"
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "64c0zJDDChN7"
       },
       "execution_count": null,
       "outputs": []