{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2023-10-05T07:20:29.202015200Z",
     "start_time": "2023-10-05T07:20:29.190080700Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "0\n",
      "<torch.cuda.device object at 0x0000028DAB1DB580>\n",
      "1\n",
      "NVIDIA GeForce RTX 3090\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "\n",
    "print(torch.cuda.is_available())     # Returns a bool indicating if CUDA is currently available.\n",
    "print(torch.cuda.current_device())   # Returns the index of a currently selected device.\n",
    "print(torch.cuda.device(0))          # Context-manager that changes the selected device.\n",
    "print(torch.cuda.device_count())     # Returns the number of GPUs available.\n",
    "print(torch.cuda.get_device_name(0)) # Gets the name of a device."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2023-10-05 10:37:05,350 SequenceTagger predicts: Dictionary with 20 tags: <unk>, O, S-ORG, S-MISC, B-PER, E-PER, S-PER, S-LOC, B-MISC, E-MISC, B-ORG, E-ORG, I-ORG, I-PER, B-LOC, I-LOC, E-LOC, I-MISC, <START>, <STOP>\n",
      "non_holiday_pred [{'entity_group': 'PER', 'word': 'George Washington', 'start': 0, 'end': 17, 'score': 0.9970293045043945}, {'entity_group': 'LOC', 'word': 'Washington', 'start': 28, 'end': 38, 'score': 0.9996309280395508}]\n"
     ]
    }
   ],
   "source": [
    "from handler import EndpointHandler\n",
    "\n",
    "# init handler\n",
    "my_handler = EndpointHandler(path=\".\")\n",
    "\n",
    "# prepare sample payload\n",
    "non_holiday_payload = {\"inputs\": \"George Washington ging naar Washington\"}\n",
    "\n",
    "\n",
    "# test the handler\n",
    "non_holiday_pred=my_handler(non_holiday_payload)\n",
    "\n",
    "\n",
    "# show results\n",
    "print(\"non_holiday_pred\", non_holiday_pred)\n",
    "\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-05T07:37:05.789680900Z",
     "start_time": "2023-10-05T07:37:03.091564500Z"
    }
   },
   "id": "a12c4a4792afc707"
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [],
   "source": [
    "from typing import Any, Dict, List\n",
    "import os\n",
    "from flair.data import Sentence\n",
    "from flair.models import SequenceTagger"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-05T07:36:53.389033800Z",
     "start_time": "2023-10-05T07:36:53.382053200Z"
    }
   },
   "id": "f411919d7d047065"
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2023-10-05 10:36:58,072 SequenceTagger predicts: Dictionary with 20 tags: <unk>, O, S-ORG, S-MISC, B-PER, E-PER, S-PER, S-LOC, B-MISC, E-MISC, B-ORG, E-ORG, I-ORG, I-PER, B-LOC, I-LOC, E-LOC, I-MISC, <START>, <STOP>\n"
     ]
    }
   ],
   "source": [
    "tagger = SequenceTagger.load('pytorch_model.bin')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-05T07:36:59.846440300Z",
     "start_time": "2023-10-05T07:36:54.140093700Z"
    }
   },
   "id": "8f497b3807de2e1"
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "'0.12.2'"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import flair\n",
    "flair.__version__"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-10-05T07:36:37.788428800Z",
     "start_time": "2023-10-05T07:36:37.754490Z"
    }
   },
   "id": "df243c485fd370b"
  }
 ],
 "metadata": {
  "kernelspec": {
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  "language_info": {
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