test_use.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_14808\\1546184754.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'./USE_questions.txt'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mencoding\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'utf-8'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m     \u001b[0mquestions\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreadlines\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[0membed\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mhub\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"https://tfhub.dev/google/universal-sentence-encoder-multilingual-large/3\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      8\u001b[0m \u001b[0membedded_vectors\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0membed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mquestions\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\module_v2.py\u001b[0m in \u001b[0;36mload\u001b[1;34m(handle, tags, options)\u001b[0m\n\u001b[0;32m     90\u001b[0m   \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     91\u001b[0m     \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Expected a string, got %s\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mhandle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 92\u001b[1;33m   \u001b[0mmodule_path\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mresolve\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     93\u001b[0m   is_hub_module_v1 = tf.io.gfile.exists(\n\u001b[0;32m     94\u001b[0m       native_module.get_module_proto_path(module_path))\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\module_v2.py\u001b[0m in \u001b[0;36mresolve\u001b[1;34m(handle)\u001b[0m\n\u001b[0;32m     45\u001b[0m     \u001b[0mA\u001b[0m \u001b[0mstring\u001b[0m \u001b[0mrepresenting\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mModule\u001b[0m \u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     46\u001b[0m   \"\"\"\n\u001b[1;32m---> 47\u001b[1;33m   \u001b[1;32mreturn\u001b[0m \u001b[0mregistry\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresolver\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     48\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     49\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\registry.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m     49\u001b[0m     \u001b[1;32mfor\u001b[0m \u001b[0mimpl\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mreversed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_impls\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     50\u001b[0m       \u001b[1;32mif\u001b[0m \u001b[0mimpl\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_supported\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 51\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mimpl\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     52\u001b[0m       \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     53\u001b[0m         \u001b[0mfails\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimpl\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\compressed_module_resolver.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, handle)\u001b[0m\n\u001b[0;32m     66\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     67\u001b[0m     return resolver.atomic_download(handle, download, module_dir,\n\u001b[1;32m---> 68\u001b[1;33m                                     self._lock_file_timeout_sec())\n\u001b[0m\u001b[0;32m     69\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     70\u001b[0m   \u001b[1;32mdef\u001b[0m \u001b[0m_lock_file_timeout_sec\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\resolver.py\u001b[0m in \u001b[0;36matomic_download\u001b[1;34m(handle, download_fn, module_dir, lock_file_timeout_sec)\u001b[0m\n\u001b[0;32m    406\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    407\u001b[0m       \u001b[1;31m# Wait for lock file to disappear.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 408\u001b[1;33m       \u001b[0m_wait_for_lock_to_disappear\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlock_file\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlock_file_timeout_sec\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    409\u001b[0m       \u001b[1;31m# At this point we either deleted a lock or a lock got removed by the\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    410\u001b[0m       \u001b[1;31m# owner or another process. Perform one more iteration of the while-loop,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\resolver.py\u001b[0m in \u001b[0;36m_wait_for_lock_to_disappear\u001b[1;34m(handle, lock_file, lock_file_timeout_sec)\u001b[0m\n\u001b[0;32m    331\u001b[0m       \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    332\u001b[0m     \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 333\u001b[1;33m       \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    334\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    335\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "import tensorflow_hub as hub\n",
    "import tensorflow_text\n",
    "import numpy as np\n",
    "\n",
    "with open('./USE_questions.txt', encoding='utf-8') as f:\n",
    "    questions = f.readlines()\n",
    "embed = hub.load(\"https://tfhub.dev/google/universal-sentence-encoder-multilingual-large/3\")\n",
    "embedded_vectors = embed(questions)\n",
    "\n",
    "def metric(u, v):\n",
    "    return np.clip(np.dot(u, v) / (np.linalg.norm(u) * np.linalg.norm(v)), -1, 1)\n",
    "\n",
    "def __new__(cls, q):\n",
    "    q_embed = cls.embed(q)\n",
    "    q_cosine = np.array([cls.metric(e1, q_embed[0]) for e1 in cls.embedded_vectors])\n",
    "    return cls.questions[q_cosine.argmax()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_14808\\3589629240.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[0mjapanese_sentences\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;34m\"犬\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"子犬はいいです\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"私は犬と一緒にビーチを散歩するのが好きです\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 10\u001b[1;33m \u001b[0membed\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mhub\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"https://tfhub.dev/google/universal-sentence-encoder-multilingual-large/3\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     11\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m \u001b[1;31m# Compute embeddings.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\module_v2.py\u001b[0m in \u001b[0;36mload\u001b[1;34m(handle, tags, options)\u001b[0m\n\u001b[0;32m     90\u001b[0m   \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     91\u001b[0m     \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Expected a string, got %s\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mhandle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 92\u001b[1;33m   \u001b[0mmodule_path\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mresolve\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     93\u001b[0m   is_hub_module_v1 = tf.io.gfile.exists(\n\u001b[0;32m     94\u001b[0m       native_module.get_module_proto_path(module_path))\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\module_v2.py\u001b[0m in \u001b[0;36mresolve\u001b[1;34m(handle)\u001b[0m\n\u001b[0;32m     45\u001b[0m     \u001b[0mA\u001b[0m \u001b[0mstring\u001b[0m \u001b[0mrepresenting\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mModule\u001b[0m \u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     46\u001b[0m   \"\"\"\n\u001b[1;32m---> 47\u001b[1;33m   \u001b[1;32mreturn\u001b[0m \u001b[0mregistry\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresolver\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     48\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     49\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\registry.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m     49\u001b[0m     \u001b[1;32mfor\u001b[0m \u001b[0mimpl\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mreversed\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_impls\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     50\u001b[0m       \u001b[1;32mif\u001b[0m \u001b[0mimpl\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_supported\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 51\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mimpl\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     52\u001b[0m       \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     53\u001b[0m         \u001b[0mfails\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimpl\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\compressed_module_resolver.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, handle)\u001b[0m\n\u001b[0;32m     66\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     67\u001b[0m     return resolver.atomic_download(handle, download, module_dir,\n\u001b[1;32m---> 68\u001b[1;33m                                     self._lock_file_timeout_sec())\n\u001b[0m\u001b[0;32m     69\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     70\u001b[0m   \u001b[1;32mdef\u001b[0m \u001b[0m_lock_file_timeout_sec\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\resolver.py\u001b[0m in \u001b[0;36matomic_download\u001b[1;34m(handle, download_fn, module_dir, lock_file_timeout_sec)\u001b[0m\n\u001b[0;32m    406\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    407\u001b[0m       \u001b[1;31m# Wait for lock file to disappear.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 408\u001b[1;33m       \u001b[0m_wait_for_lock_to_disappear\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlock_file\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlock_file_timeout_sec\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    409\u001b[0m       \u001b[1;31m# At this point we either deleted a lock or a lock got removed by the\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    410\u001b[0m       \u001b[1;31m# owner or another process. Perform one more iteration of the while-loop,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\Coding\\lincall-ai\\.venv\\lib\\site-packages\\tensorflow_hub\\resolver.py\u001b[0m in \u001b[0;36m_wait_for_lock_to_disappear\u001b[1;34m(handle, lock_file, lock_file_timeout_sec)\u001b[0m\n\u001b[0;32m    331\u001b[0m       \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    332\u001b[0m     \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 333\u001b[1;33m       \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    334\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    335\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "import tensorflow_hub as hub\n",
    "import numpy as np\n",
    "import tensorflow_text\n",
    "\n",
    "# Some texts of different lengths.\n",
    "english_sentences = [\"dog\", \"Puppies are nice.\", \"I enjoy taking long walks along the beach with my dog.\"]\n",
    "italian_sentences = [\"cane\", \"I cuccioli sono carini.\", \"Mi piace fare lunghe passeggiate lungo la spiaggia con il mio cane.\"]\n",
    "japanese_sentences = [\"犬\", \"子犬はいいです\", \"私は犬と一緒にビーチを散歩するのが好きです\"]\n",
    "\n",
    "embed = hub.load(\"https://tfhub.dev/google/universal-sentence-encoder-multilingual-large/3\")\n",
    "\n",
    "# Compute embeddings.\n",
    "en_result = embed(english_sentences)\n",
    "it_result = embed(italian_sentences)\n",
    "ja_result = embed(japanese_sentences)\n",
    "\n",
    "# Compute similarity matrix. Higher score indicates greater similarity.\n",
    "similarity_matrix_it = np.inner(en_result, it_result)\n",
    "similarity_matrix_ja = np.inner(en_result, ja_result)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Please fix your imports. Module tensorflow.python.training.tracking.data_structures has been moved to tensorflow.python.trackable.data_structures. The old module will be deleted in version 2.11.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Please fix your imports. Module tensorflow.python.training.tracking.data_structures has been moved to tensorflow.python.trackable.data_structures. The old module will be deleted in version 2.11.\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "import tensorflow_hub as hub\n",
    "\n",
    "embed = hub.KerasLayer('USE_model')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Some texts of different lengths.\n",
    "english_sentences = [\"dog\", \"Puppies are nice.\", \"I enjoy taking long walks along the beach with my dog.\"]\n",
    "italian_sentences = [\"cane\", \"I cuccioli sono carini.\", \"Mi piace fare lunghe passeggiate lungo la spiaggia con il mio cane.\"]\n",
    "japanese_sentences = [\"犬\", \"子犬はいいです\", \"私は犬と一緒にビーチを散歩するのが好きです\"]\n",
    "\n",
    "# Compute embeddings.\n",
    "en_result = embed(english_sentences)\n",
    "it_result = embed(italian_sentences)\n",
    "ja_result = embed(japanese_sentences)\n",
    "\n",
    "# Compute similarity matrix. Higher score indicates greater similarity.\n",
    "similarity_matrix_it = np.inner(en_result, it_result)\n",
    "similarity_matrix_ja = np.inner(en_result, ja_result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.9696459 , 0.27347845, 0.25536817],\n",
       "       [0.3772605 , 0.8931675 , 0.28806683],\n",
       "       [0.24611367, 0.23792985, 0.9352151 ]], dtype=float32)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "similarity_matrix_it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow_hub as hub\n",
    "import tensorflow_text\n",
    "import numpy as np\n",
    "from json import JSONEncoder\n",
    "\n",
    "class USE:\n",
    "    with open('./USE_questions.txt', encoding='utf-8') as f:\n",
    "        questions = f.readlines()\n",
    "    with open('./USE_answers.txt', encoding='utf-8') as f:\n",
    "        answers = f.readlines()\n",
    "    embed = hub.KerasLayer('USE_model')\n",
    "    embedded_vectors = embed(questions)\n",
    "    encoder = JSONEncoder()\n",
    "\n",
    "    def metric(u, v):\n",
    "        return np.clip(np.dot(u, v) / (np.linalg.norm(u) * np.linalg.norm(v)), -1, 1)\n",
    "\n",
    "    def __new__(cls, q):\n",
    "        q_embed = cls.embed(q)\n",
    "        q_cosine = np.array([cls.metric(e1, q_embed[0]) for e1 in cls.embedded_vectors])\n",
    "        print(q_cosine.max())\n",
    "        if q_cosine.max() < 0.4:\n",
    "            return ''\n",
    "        return cls.questions[q_cosine.argmax()] + '|' + cls.answers[q_cosine.argmax()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.2615303099155426\n"
     ]
    }
   ],
   "source": [
    "USE('아니 숟가락 왜 안 넣어주시냐구요')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7.9 ('.venv': venv)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "4c45a5d2cedf03315b605f781a38921e17d7dbdeb292664a5e6f38421aada0de"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}