pororo_question_generation_retry.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "pororo question generation_retry.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "TPU",
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "48472096df294be78a38a1c02e6552a9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_3bfe8827604c474c95e8415f17714947",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_3556fd0799c04387a81ba53edbae5fe1",
              "IPY_MODEL_388593c5ffcc413496fb536539c92de7",
              "IPY_MODEL_7f2d4a04b9d744918d92097679d1f9c2"
            ]
          }
        },
        "3bfe8827604c474c95e8415f17714947": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "3556fd0799c04387a81ba53edbae5fe1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_7e40ac058a1047f8a8caf5a73d11c543",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_15c9dd333a2d48869a28cc4bc6e02f86"
          }
        },
        "388593c5ffcc413496fb536539c92de7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_a46ad3128c6041608014491a4d6ff057",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 1110,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1110,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_664aee7a762444b181ac45be7787f855"
          }
        },
        "7f2d4a04b9d744918d92097679d1f9c2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_c0518a969ff14d6bb922f6f222797c6c",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 1.08k/1.08k [00:00&lt;00:00, 23.1kB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_c7db1bf8a96f4ae8b096446928b610d9"
          }
        },
        "7e40ac058a1047f8a8caf5a73d11c543": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "15c9dd333a2d48869a28cc4bc6e02f86": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "a46ad3128c6041608014491a4d6ff057": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "664aee7a762444b181ac45be7787f855": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "c0518a969ff14d6bb922f6f222797c6c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "c7db1bf8a96f4ae8b096446928b610d9": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "2ed1e82ee671485ca81b88df625408ae": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_0470f28313df4cd98050a41f17709c77",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_2eb16b601cfa48f295436c97cf27cdf6",
              "IPY_MODEL_16d27128b68146c4a7a565ae6baa93be",
              "IPY_MODEL_41b733067ea0484686bb1471ded32785"
            ]
          }
        },
        "0470f28313df4cd98050a41f17709c77": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "2eb16b601cfa48f295436c97cf27cdf6": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_84262bb5085349ec8bd20703b7d6c069",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_fb538a6564e34986bc5b1e05d9b02c0c"
          }
        },
        "16d27128b68146c4a7a565ae6baa93be": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_89d7026807354a50a28560381c7698c1",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 2,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 2,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_94956b3f819e47a7b8f3ce5c957e61ff"
          }
        },
        "41b733067ea0484686bb1471ded32785": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_224d9185a7314835b281feb9121e0e97",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 2.00/2.00 [00:00&lt;00:00, 52.9B/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_6ac4e083d3514acc96d438c3502fcdf0"
          }
        },
        "84262bb5085349ec8bd20703b7d6c069": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "fb538a6564e34986bc5b1e05d9b02c0c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "89d7026807354a50a28560381c7698c1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "94956b3f819e47a7b8f3ce5c957e61ff": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "224d9185a7314835b281feb9121e0e97": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "6ac4e083d3514acc96d438c3502fcdf0": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "869f9ee624e64b35a1167cc810c5b2ec": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_4ca3d670f99f43428b8043a039860cb1",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_1f75b1a67df34c4a8066521e5ca0c122",
              "IPY_MODEL_e9d1e96d3fbe4d189b01f315dcba8ca1",
              "IPY_MODEL_988cb1a36ca947108a351eb250eba730"
            ]
          }
        },
        "4ca3d670f99f43428b8043a039860cb1": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "1f75b1a67df34c4a8066521e5ca0c122": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_5923068b7b56447480f041243545b1ca",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_83cfa92d5c66406b9d69decd3d39ce49"
          }
        },
        "e9d1e96d3fbe4d189b01f315dcba8ca1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_7f82a10c4a71473a878f00e284bb0c01",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 85,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 85,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_9f7303733a8b416a9077f291a7794bd5"
          }
        },
        "988cb1a36ca947108a351eb250eba730": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_354f9be7847a4e31bd0b1aad15529151",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 85.0/85.0 [00:00&lt;00:00, 2.23kB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_af980b10d75d48eeb313e6a6078b71b7"
          }
        },
        "5923068b7b56447480f041243545b1ca": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "83cfa92d5c66406b9d69decd3d39ce49": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "7f82a10c4a71473a878f00e284bb0c01": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "9f7303733a8b416a9077f291a7794bd5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "354f9be7847a4e31bd0b1aad15529151": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "af980b10d75d48eeb313e6a6078b71b7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "0ca1732ed62549688088ec401c0fcdf3": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_32656efdd4f84708b8af8edca1eb1f1e",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_1447d43d171b4d7885976416dcf0e2f9",
              "IPY_MODEL_dae568dfb43a4ecc81f386427c4dca5d",
              "IPY_MODEL_54cd7f71c285411f874db3cafa8c62a7"
            ]
          }
        },
        "32656efdd4f84708b8af8edca1eb1f1e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "1447d43d171b4d7885976416dcf0e2f9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_61fdce810d9b409a87cb4cf5eb70288c",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_df1807c7e58c42328e28bf767a055f60"
          }
        },
        "dae568dfb43a4ecc81f386427c4dca5d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_faaddc1c7da846c2bcf6d89cd1fbb938",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 109,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 109,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_69a1b8f499e44f65b5e973dae2483453"
          }
        },
        "54cd7f71c285411f874db3cafa8c62a7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_15fc314c75834084a24588b351758696",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 109/109 [00:00&lt;00:00, 2.67kB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_303423cb24f745d28e9af6b62c370715"
          }
        },
        "61fdce810d9b409a87cb4cf5eb70288c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "df1807c7e58c42328e28bf767a055f60": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "faaddc1c7da846c2bcf6d89cd1fbb938": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "69a1b8f499e44f65b5e973dae2483453": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "15fc314c75834084a24588b351758696": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "303423cb24f745d28e9af6b62c370715": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "95998bb3e1b5468e95412e26705b2da3": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_ecdfa8c7187f4085975ea33d2629546a",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_684ffc9a80fb4c25be6f25b4b4e1756c",
              "IPY_MODEL_7ac7fd4a5e9248628aff4068b51311df",
              "IPY_MODEL_eb83ef6e255943ce9e4232e53d3f3f2d"
            ]
          }
        },
        "ecdfa8c7187f4085975ea33d2629546a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "684ffc9a80fb4c25be6f25b4b4e1756c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_2b00af78a0d941fca5703fa2e05c8df9",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_0974c2b8e4a949f1a4218b583bb8e59c"
          }
        },
        "7ac7fd4a5e9248628aff4068b51311df": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_b448361522c843e1b0ddb4de02009d20",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 682149,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 682149,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_9864890111504d23bf56435785be75a5"
          }
        },
        "eb83ef6e255943ce9e4232e53d3f3f2d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_6494ad4a234847168de927eba2327bb5",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 666k/666k [00:00&lt;00:00, 1.47MB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_4698d436356146bcb8fd7a92a39520bc"
          }
        },
        "2b00af78a0d941fca5703fa2e05c8df9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "0974c2b8e4a949f1a4218b583bb8e59c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "b448361522c843e1b0ddb4de02009d20": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "9864890111504d23bf56435785be75a5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "6494ad4a234847168de927eba2327bb5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "4698d436356146bcb8fd7a92a39520bc": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/threegenie/pororo_tutorial/blob/main/pororo_question_generation_retry.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3Pwq2mg_WWy9"
      },
      "source": [
        "### Conda 가상환경 구축 및 필요한 library 설치"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ola625d912Z3",
        "outputId": "d52a423b-be79-46e5-adb2-d17f219d6fd4"
      },
      "source": [
        "!which python # should return /usr/local/bin/python"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/usr/local/bin/python\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7OMngvK_2CN9",
        "outputId": "7b1bc968-f09a-4100-c2da-0e025e88e7f3"
      },
      "source": [
        "!python --version"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python 3.7.12\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r-5QGokd2Ku8",
        "outputId": "0b85062b-77b2-4830-d08d-b7937738c9a4"
      },
      "source": [
        "!echo $PYTHONPATH # /env/python"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/env/python\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hsrBG_wf2SOq",
        "outputId": "233c5036-8a6b-4abc-96cd-b28d63650b09"
      },
      "source": [
        "%env PYTHONPATH="
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "env: PYTHONPATH=\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sojURo5kHLlX",
        "outputId": "7fcb17ab-b1d7-471d-cffb-e9c694fdc46e"
      },
      "source": [
        "################################################################################\n",
        "# INSTALL CONDA ON GOOGLE COLAB\n",
        "################################################################################\n",
        "! wget https://repo.anaconda.com/miniconda/Miniconda3-py37_4.9.2-Linux-x86_64.sh\n",
        "! chmod +x Miniconda3-py37_4.9.2-Linux-x86_64.sh\n",
        "! bash ./Miniconda3-py37_4.9.2-Linux-x86_64.sh -b -f -p /usr/local\n",
        "import sys\n",
        "sys.path.append('/usr/local/lib/python3.7/site-packages/')"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2021-10-01 00:55:07--  https://repo.anaconda.com/miniconda/Miniconda3-py37_4.9.2-Linux-x86_64.sh\n",
            "Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.131.3, 104.16.130.3, 2606:4700::6810:8303, ...\n",
            "Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.131.3|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 90040905 (86M) [application/x-sh]\n",
            "Saving to: ‘Miniconda3-py37_4.9.2-Linux-x86_64.sh’\n",
            "\n",
            "Miniconda3-py37_4.9 100%[===================>]  85.87M  58.8MB/s    in 1.5s    \n",
            "\n",
            "2021-10-01 00:55:09 (58.8 MB/s) - ‘Miniconda3-py37_4.9.2-Linux-x86_64.sh’ saved [90040905/90040905]\n",
            "\n",
            "PREFIX=/usr/local\n",
            "Unpacking payload ...\n",
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\bdone\n",
            "Solving environment: - \b\b\\ \b\b| \b\bdone\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local\n",
            "\n",
            "  added / updated specs:\n",
            "    - _libgcc_mutex==0.1=main\n",
            "    - brotlipy==0.7.0=py37h27cfd23_1003\n",
            "    - ca-certificates==2020.10.14=0\n",
            "    - certifi==2020.6.20=pyhd3eb1b0_3\n",
            "    - cffi==1.14.3=py37h261ae71_2\n",
            "    - chardet==3.0.4=py37h06a4308_1003\n",
            "    - conda-package-handling==1.7.2=py37h03888b9_0\n",
            "    - conda==4.9.2=py37h06a4308_0\n",
            "    - cryptography==3.2.1=py37h3c74f83_1\n",
            "    - idna==2.10=py_0\n",
            "    - ld_impl_linux-64==2.33.1=h53a641e_7\n",
            "    - libedit==3.1.20191231=h14c3975_1\n",
            "    - libffi==3.3=he6710b0_2\n",
            "    - libgcc-ng==9.1.0=hdf63c60_0\n",
            "    - libstdcxx-ng==9.1.0=hdf63c60_0\n",
            "    - ncurses==6.2=he6710b0_1\n",
            "    - openssl==1.1.1h=h7b6447c_0\n",
            "    - pip==20.2.4=py37h06a4308_0\n",
            "    - pycosat==0.6.3=py37h27cfd23_0\n",
            "    - pycparser==2.20=py_2\n",
            "    - pyopenssl==19.1.0=pyhd3eb1b0_1\n",
            "    - pysocks==1.7.1=py37_1\n",
            "    - python==3.7.9=h7579374_0\n",
            "    - readline==8.0=h7b6447c_0\n",
            "    - requests==2.24.0=py_0\n",
            "    - ruamel_yaml==0.15.87=py37h7b6447c_1\n",
            "    - setuptools==50.3.1=py37h06a4308_1\n",
            "    - six==1.15.0=py37h06a4308_0\n",
            "    - sqlite==3.33.0=h62c20be_0\n",
            "    - tk==8.6.10=hbc83047_0\n",
            "    - tqdm==4.51.0=pyhd3eb1b0_0\n",
            "    - urllib3==1.25.11=py_0\n",
            "    - wheel==0.35.1=pyhd3eb1b0_0\n",
            "    - xz==5.2.5=h7b6447c_0\n",
            "    - yaml==0.2.5=h7b6447c_0\n",
            "    - zlib==1.2.11=h7b6447c_3\n",
            "\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  _libgcc_mutex      pkgs/main/linux-64::_libgcc_mutex-0.1-main\n",
            "  brotlipy           pkgs/main/linux-64::brotlipy-0.7.0-py37h27cfd23_1003\n",
            "  ca-certificates    pkgs/main/linux-64::ca-certificates-2020.10.14-0\n",
            "  certifi            pkgs/main/noarch::certifi-2020.6.20-pyhd3eb1b0_3\n",
            "  cffi               pkgs/main/linux-64::cffi-1.14.3-py37h261ae71_2\n",
            "  chardet            pkgs/main/linux-64::chardet-3.0.4-py37h06a4308_1003\n",
            "  conda              pkgs/main/linux-64::conda-4.9.2-py37h06a4308_0\n",
            "  conda-package-han~ pkgs/main/linux-64::conda-package-handling-1.7.2-py37h03888b9_0\n",
            "  cryptography       pkgs/main/linux-64::cryptography-3.2.1-py37h3c74f83_1\n",
            "  idna               pkgs/main/noarch::idna-2.10-py_0\n",
            "  ld_impl_linux-64   pkgs/main/linux-64::ld_impl_linux-64-2.33.1-h53a641e_7\n",
            "  libedit            pkgs/main/linux-64::libedit-3.1.20191231-h14c3975_1\n",
            "  libffi             pkgs/main/linux-64::libffi-3.3-he6710b0_2\n",
            "  libgcc-ng          pkgs/main/linux-64::libgcc-ng-9.1.0-hdf63c60_0\n",
            "  libstdcxx-ng       pkgs/main/linux-64::libstdcxx-ng-9.1.0-hdf63c60_0\n",
            "  ncurses            pkgs/main/linux-64::ncurses-6.2-he6710b0_1\n",
            "  openssl            pkgs/main/linux-64::openssl-1.1.1h-h7b6447c_0\n",
            "  pip                pkgs/main/linux-64::pip-20.2.4-py37h06a4308_0\n",
            "  pycosat            pkgs/main/linux-64::pycosat-0.6.3-py37h27cfd23_0\n",
            "  pycparser          pkgs/main/noarch::pycparser-2.20-py_2\n",
            "  pyopenssl          pkgs/main/noarch::pyopenssl-19.1.0-pyhd3eb1b0_1\n",
            "  pysocks            pkgs/main/linux-64::pysocks-1.7.1-py37_1\n",
            "  python             pkgs/main/linux-64::python-3.7.9-h7579374_0\n",
            "  readline           pkgs/main/linux-64::readline-8.0-h7b6447c_0\n",
            "  requests           pkgs/main/noarch::requests-2.24.0-py_0\n",
            "  ruamel_yaml        pkgs/main/linux-64::ruamel_yaml-0.15.87-py37h7b6447c_1\n",
            "  setuptools         pkgs/main/linux-64::setuptools-50.3.1-py37h06a4308_1\n",
            "  six                pkgs/main/linux-64::six-1.15.0-py37h06a4308_0\n",
            "  sqlite             pkgs/main/linux-64::sqlite-3.33.0-h62c20be_0\n",
            "  tk                 pkgs/main/linux-64::tk-8.6.10-hbc83047_0\n",
            "  tqdm               pkgs/main/noarch::tqdm-4.51.0-pyhd3eb1b0_0\n",
            "  urllib3            pkgs/main/noarch::urllib3-1.25.11-py_0\n",
            "  wheel              pkgs/main/noarch::wheel-0.35.1-pyhd3eb1b0_0\n",
            "  xz                 pkgs/main/linux-64::xz-5.2.5-h7b6447c_0\n",
            "  yaml               pkgs/main/linux-64::yaml-0.2.5-h7b6447c_0\n",
            "  zlib               pkgs/main/linux-64::zlib-1.2.11-h7b6447c_3\n",
            "\n",
            "\n",
            "Preparing transaction: - \b\b\\ \b\b| \b\b/ \b\bdone\n",
            "Executing transaction: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "installation finished.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oSjWLGu32dNZ",
        "outputId": "8b288f27-14d9-47d6-908d-b02f353e90ff"
      },
      "source": [
        "!which conda  # should return /usr/local/bin/conda"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/usr/local/bin/conda\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_mlp26HZ3Kjk",
        "outputId": "39da4666-411d-44fd-a274-907e8edb7009"
      },
      "source": [
        "!conda --version"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "conda 4.9.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "awtMrtbm3SjV",
        "outputId": "7bced13a-b389-4862-db90-7256a36d4541"
      },
      "source": [
        "!python --version"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python 3.7.9\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k1gU87_H4UJp",
        "outputId": "ec2a191c-e348-438b-ecbb-b5f852f4c4db"
      },
      "source": [
        "# 구글 코랩이 설치된 폴더 안의 파일, 패키지 리스트\n",
        "\n",
        "!ls /usr/local/lib/python3.7/dist-packages"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "absl\n",
            "absl_py-0.12.0.dist-info\n",
            "alabaster\n",
            "alabaster-0.7.12.dist-info\n",
            "albumentations\n",
            "albumentations-0.1.12.dist-info\n",
            "altair\n",
            "altair-4.1.0.dist-info\n",
            "apiclient\n",
            "appdirs-1.4.4.dist-info\n",
            "appdirs.py\n",
            "apt\n",
            "apt_inst.cpython-37m-x86_64-linux-gnu.so\n",
            "apt_inst.pyi\n",
            "apt_pkg.cpython-37m-x86_64-linux-gnu.so\n",
            "apt_pkg.pyi\n",
            "aptsources\n",
            "argcomplete\n",
            "argcomplete-1.12.3.dist-info\n",
            "argon2\n",
            "argon2_cffi-21.1.0.dist-info\n",
            "arviz\n",
            "arviz-0.11.2.dist-info\n",
            "astor\n",
            "astor-0.8.1.dist-info\n",
            "astropy\n",
            "astropy-4.3.1.dist-info\n",
            "astunparse\n",
            "astunparse-1.6.3.dist-info\n",
            "atari_py\n",
            "atari_py-0.2.9.dist-info\n",
            "atari_py.libs\n",
            "atomicwrites\n",
            "atomicwrites-1.4.0.dist-info\n",
            "attr\n",
            "attrs-21.2.0.dist-info\n",
            "audioread\n",
            "audioread-2.1.9.dist-info\n",
            "autograd\n",
            "autograd-1.3.dist-info\n",
            "babel\n",
            "Babel-2.9.1.dist-info\n",
            "backcall\n",
            "backcall-0.2.0.dist-info\n",
            "beautifulsoup4-4.6.3.dist-info\n",
            "bin\n",
            "bleach\n",
            "bleach-4.1.0.dist-info\n",
            "blis\n",
            "blis-0.4.1.dist-info\n",
            "bokeh\n",
            "bokeh-2.3.3.dist-info\n",
            "bottleneck\n",
            "Bottleneck-1.3.2.dist-info\n",
            "branca\n",
            "branca-0.4.2.dist-info\n",
            "bs4\n",
            "bs4-0.0.1.dist-info\n",
            "bson\n",
            "cachecontrol\n",
            "CacheControl-0.12.6.dist-info\n",
            "cached_property-1.5.2.dist-info\n",
            "cached_property.py\n",
            "cachetools\n",
            "cachetools-4.2.2.dist-info\n",
            "caffe2\n",
            "catalogue-1.0.0.dist-info\n",
            "catalogue.py\n",
            "certifi\n",
            "certifi-2021.5.30.dist-info\n",
            "cffi\n",
            "cffi-1.14.6.dist-info\n",
            "_cffi_backend.cpython-37m-x86_64-linux-gnu.so\n",
            "cffi.libs\n",
            "cftime\n",
            "cftime-1.5.0.dist-info\n",
            "chardet\n",
            "chardet-3.0.4.dist-info\n",
            "charset_normalizer\n",
            "charset_normalizer-2.0.6.dist-info\n",
            "chess\n",
            "clang\n",
            "clang-5.0.dist-info\n",
            "click\n",
            "click-7.1.2.dist-info\n",
            "client\n",
            "cloudpickle\n",
            "cloudpickle-1.3.0.dist-info\n",
            "cmake\n",
            "cmake-3.12.0.dist-info\n",
            "cmdstanpy\n",
            "cmdstanpy-0.9.5.dist-info\n",
            "colab\n",
            "colorcet\n",
            "colorcet-2.0.6.dist-info\n",
            "colorlover\n",
            "colorlover-0.3.0.dist-info\n",
            "community\n",
            "community-1.0.0b1.dist-info\n",
            "contextlib2-0.5.5.dist-info\n",
            "contextlib2.py\n",
            "convertdate\n",
            "convertdate-2.3.2.dist-info\n",
            "coverage\n",
            "coverage-3.7.1.dist-info\n",
            "coveralls\n",
            "coveralls-0.5.dist-info\n",
            "crcmod\n",
            "crcmod-1.7.dist-info\n",
            "cufflinks\n",
            "cufflinks-0.17.3.dist-info\n",
            "cv2\n",
            "_cvxcore.cpython-37m-x86_64-linux-gnu.so\n",
            "cvxopt\n",
            "cvxopt-1.2.7.dist-info\n",
            "cvxopt.libs\n",
            "cvxpy\n",
            "cvxpy-1.0.31.dist-info\n",
            "cycler-0.10.0.dist-info\n",
            "cycler.py\n",
            "cymem\n",
            "cymem-2.0.5.dist-info\n",
            "Cython\n",
            "Cython-0.29.24.dist-info\n",
            "cython.py\n",
            "daft-0.0.4.dist-info\n",
            "daft.py\n",
            "dask\n",
            "dask-2.12.0.dist-info\n",
            "datascience\n",
            "datascience-0.10.6.dist-info\n",
            "dateutil\n",
            "debugpy\n",
            "debugpy-1.0.0.dist-info\n",
            "decorator-4.4.2.dist-info\n",
            "decorator.py\n",
            "defusedxml\n",
            "defusedxml-0.7.1.dist-info\n",
            "descartes\n",
            "descartes-1.1.0.dist-info\n",
            "dill\n",
            "dill-0.3.4.dist-info\n",
            "distributed\n",
            "distributed-1.25.3.dist-info\n",
            "_distutils_hack\n",
            "distutils-precedence.pth\n",
            "dlib-19.18.0.dist-info\n",
            "dlib.cpython-37m-x86_64-linux-gnu.so\n",
            "dm_tree-0.1.6.dist-info\n",
            "docopt-0.6.2.dist-info\n",
            "docopt.py\n",
            "docs\n",
            "docutils\n",
            "docutils-0.17.1.dist-info\n",
            "dopamine\n",
            "dopamine_rl-1.0.5.dist-info\n",
            "dot_parser.py\n",
            "earthengine_api-0.1.283.dist-info\n",
            "easydict\n",
            "easydict-1.9.dist-info\n",
            "ecos\n",
            "ecos-2.0.7.post1.dist-info\n",
            "_ecos.cpython-37m-x86_64-linux-gnu.so\n",
            "editdistance\n",
            "editdistance-0.5.3.dist-info\n",
            "ee\n",
            "en_core_web_sm\n",
            "en_core_web_sm-2.2.5.dist-info\n",
            "entrypoints-0.3.dist-info\n",
            "entrypoints.py\n",
            "ephem\n",
            "ephem-4.0.0.2.dist-info\n",
            "erfa\n",
            "et_xmlfile\n",
            "et_xmlfile-1.1.0.dist-info\n",
            "examples\n",
            "fa2\n",
            "fa2-0.3.5.dist-info\n",
            "fastai\n",
            "fastai-1.0.61.dist-info\n",
            "fastdtw\n",
            "fastdtw-0.3.4.dist-info\n",
            "fastprogress\n",
            "fastprogress-1.0.0.dist-info\n",
            "fastrlock\n",
            "fastrlock-0.6.dist-info\n",
            "fbprophet\n",
            "fbprophet-0.7.1-py3.7.egg-info\n",
            "feather\n",
            "feather_format-0.4.1.dist-info\n",
            "filelock-3.0.12.dist-info\n",
            "filelock.py\n",
            "firebase_admin\n",
            "firebase_admin-4.4.0.dist-info\n",
            "fix_yahoo_finance\n",
            "fix_yahoo_finance-0.0.22.dist-info\n",
            "flask\n",
            "Flask-1.1.4.dist-info\n",
            "flatbuffers\n",
            "flatbuffers-1.12.dist-info\n",
            "folium\n",
            "folium-0.8.3.dist-info\n",
            "future\n",
            "future-0.16.0.dist-info\n",
            "gast\n",
            "gast-0.4.0.dist-info\n",
            "GDAL-2.2.2.dist-info\n",
            "gdalconst.py\n",
            "gdalnumeric.py\n",
            "gdal.py\n",
            "gdown\n",
            "gdown-3.6.4.dist-info\n",
            "gensim\n",
            "gensim-3.6.0.dist-info\n",
            "geographiclib\n",
            "geographiclib-1.52.dist-info\n",
            "geopy\n",
            "geopy-1.17.0.dist-info\n",
            "gin\n",
            "gin_config-0.4.0.dist-info\n",
            "github2pypi\n",
            "glob2\n",
            "glob2-0.7.dist-info\n",
            "gnm.py\n",
            "google\n",
            "google-2.0.3.dist-info\n",
            "googleapiclient\n",
            "google_api_core-1.26.3.dist-info\n",
            "google_api_core-1.26.3-py3.9-nspkg.pth\n",
            "google_api_python_client-1.12.8.dist-info\n",
            "googleapis_common_protos-1.53.0.dist-info\n",
            "googleapis_common_protos-1.53.0-py3.9-nspkg.pth\n",
            "google_auth-1.35.0.dist-info\n",
            "google_auth-1.35.0-py3.9-nspkg.pth\n",
            "google_auth_httplib2-0.0.4.dist-info\n",
            "google_auth_httplib2.py\n",
            "google_auth_oauthlib\n",
            "google_auth_oauthlib-0.4.6.dist-info\n",
            "google_cloud_bigquery-1.21.0.dist-info\n",
            "google_cloud_bigquery-1.21.0-py3.6-nspkg.pth\n",
            "google_cloud_bigquery_storage-1.1.0.dist-info\n",
            "google_cloud_bigquery_storage-1.1.0-py3.8-nspkg.pth\n",
            "google_cloud_core-1.0.3.dist-info\n",
            "google_cloud_core-1.0.3-py3.6-nspkg.pth\n",
            "google_cloud_datastore-1.8.0.dist-info\n",
            "google_cloud_datastore-1.8.0-py3.6-nspkg.pth\n",
            "google_cloud_firestore-1.7.0.dist-info\n",
            "google_cloud_firestore-1.7.0-py3.8-nspkg.pth\n",
            "google_cloud_language-1.2.0.dist-info\n",
            "google_cloud_language-1.2.0-py3.6-nspkg.pth\n",
            "google_cloud_storage-1.18.1.dist-info\n",
            "google_cloud_storage-1.18.1-py3.7-nspkg.pth\n",
            "google_cloud_translate-1.5.0.dist-info\n",
            "google_cloud_translate-1.5.0-py3.6-nspkg.pth\n",
            "google_colab-1.0.0.dist-info\n",
            "google_colab-1.0.0-py3.7-nspkg.pth\n",
            "google_drive_downloader\n",
            "googledrivedownloader-0.4.dist-info\n",
            "google_pasta-0.2.0.dist-info\n",
            "google_resumable_media-0.4.1.dist-info\n",
            "google_resumable_media-0.4.1-py3.6-nspkg.pth\n",
            "googlesearch\n",
            "graphviz\n",
            "graphviz-0.10.1.dist-info\n",
            "greenlet\n",
            "greenlet-1.1.1.dist-info\n",
            "gridfs\n",
            "grpc\n",
            "grpcio-1.40.0.dist-info\n",
            "gspread\n",
            "gspread-3.0.1.dist-info\n",
            "gspread_dataframe-3.0.8.dist-info\n",
            "gspread_dataframe.py\n",
            "gym\n",
            "gym-0.17.3.dist-info\n",
            "h5py\n",
            "h5py-3.1.0.dist-info\n",
            "h5py.libs\n",
            "HeapDict-1.0.1.dist-info\n",
            "heapdict.py\n",
            "helper\n",
            "hijri_converter\n",
            "hijri_converter-2.2.1.dist-info\n",
            "holidays\n",
            "holidays-0.10.5.2.dist-info\n",
            "holoviews\n",
            "holoviews-1.14.6.dist-info\n",
            "html5lib\n",
            "html5lib-1.0.1.dist-info\n",
            "httpimport-0.5.18.dist-info\n",
            "httpimport.py\n",
            "httplib2\n",
            "httplib2-0.17.4.dist-info\n",
            "httplib2shim\n",
            "httplib2shim-0.0.3.dist-info\n",
            "humanize\n",
            "humanize-0.5.1.dist-info\n",
            "hyperopt\n",
            "hyperopt-0.1.2.dist-info\n",
            "ideep4py\n",
            "ideep4py-2.0.0.post3.dist-info\n",
            "idna\n",
            "idna-2.10.dist-info\n",
            "imageio\n",
            "imageio-2.4.1.dist-info\n",
            "imagesize-1.2.0.dist-info\n",
            "imagesize.py\n",
            "imbalanced_learn-0.4.3.dist-info\n",
            "imblearn\n",
            "imblearn-0.0.dist-info\n",
            "imgaug\n",
            "imgaug-0.2.9.dist-info\n",
            "importlib_metadata\n",
            "importlib_metadata-4.8.1.dist-info\n",
            "importlib_resources\n",
            "importlib_resources-5.2.2.dist-info\n",
            "imutils\n",
            "imutils-0.5.4.dist-info\n",
            "inflect-2.1.0.dist-info\n",
            "inflect.py\n",
            "iniconfig\n",
            "iniconfig-1.1.1.dist-info\n",
            "intel_openmp-2021.3.0.dist-info\n",
            "intervaltree\n",
            "intervaltree-2.1.0.dist-info\n",
            "ipykernel\n",
            "ipykernel-4.10.1.dist-info\n",
            "ipykernel_launcher.py\n",
            "IPython\n",
            "ipython-5.5.0.dist-info\n",
            "ipython_genutils\n",
            "ipython_genutils-0.2.0.dist-info\n",
            "ipython_sql-0.3.9.dist-info\n",
            "ipywidgets\n",
            "ipywidgets-7.6.5.dist-info\n",
            "isympy.py\n",
            "itsdangerous\n",
            "itsdangerous-1.1.0.dist-info\n",
            "jax\n",
            "jax-0.2.21.dist-info\n",
            "jaxlib\n",
            "jaxlib-0.1.71+cuda111.dist-info\n",
            "jdcal-1.4.1.dist-info\n",
            "jdcal.py\n",
            "jedi\n",
            "jedi-0.18.0.dist-info\n",
            "jieba\n",
            "jieba-0.42.1.dist-info\n",
            "jinja2\n",
            "Jinja2-2.11.3.dist-info\n",
            "joblib\n",
            "joblib-1.0.1.dist-info\n",
            "jpeg4py\n",
            "jpeg4py-0.1.4.dist-info\n",
            "jsonschema\n",
            "jsonschema-2.6.0.dist-info\n",
            "jupyter-1.0.0.dist-info\n",
            "jupyter_client\n",
            "jupyter_client-5.3.5.dist-info\n",
            "jupyter_console\n",
            "jupyter_console-5.2.0.dist-info\n",
            "jupyter_core\n",
            "jupyter_core-4.8.1.dist-info\n",
            "jupyterlab_pygments\n",
            "jupyterlab_pygments-0.1.2.dist-info\n",
            "jupyterlab_widgets\n",
            "jupyterlab_widgets-1.0.2.dist-info\n",
            "jupyter.py\n",
            "kaggle\n",
            "kaggle-1.5.12.dist-info\n",
            "kapre\n",
            "kapre-0.3.5.dist-info\n",
            "keras\n",
            "keras-2.6.0.dist-info\n",
            "keras_preprocessing\n",
            "Keras_Preprocessing-1.1.2.dist-info\n",
            "keras_vis-0.4.1.dist-info\n",
            "kiwisolver-1.3.2.dist-info\n",
            "kiwisolver.cpython-37m-x86_64-linux-gnu.so\n",
            "korean_lunar_calendar\n",
            "korean_lunar_calendar-0.2.1.dist-info\n",
            "libfuturize\n",
            "libpasteurize\n",
            "librosa\n",
            "librosa-0.8.1.dist-info\n",
            "lightgbm\n",
            "lightgbm-2.2.3.dist-info\n",
            "llvmlite\n",
            "llvmlite-0.34.0.dist-info\n",
            "lmdb\n",
            "lmdb-0.99.dist-info\n",
            "lunarcalendar\n",
            "LunarCalendar-0.0.9.dist-info\n",
            "lxml\n",
            "lxml-4.2.6.dist-info\n",
            "markdown\n",
            "Markdown-3.3.4.dist-info\n",
            "markupsafe\n",
            "MarkupSafe-2.0.1.dist-info\n",
            "matplotlib\n",
            "matplotlib-3.2.2.dist-info\n",
            "matplotlib-3.2.2-py3.7-nspkg.pth\n",
            "matplotlib_inline\n",
            "matplotlib_inline-0.1.3.dist-info\n",
            "matplotlib.libs\n",
            "matplotlib_venn\n",
            "matplotlib_venn-0.11.6.dist-info\n",
            "Misc\n",
            "missingno\n",
            "missingno-0.5.0.dist-info\n",
            "mistune-0.8.4.dist-info\n",
            "mistune.py\n",
            "mizani\n",
            "mizani-0.6.0.dist-info\n",
            "mkl-2019.0.dist-info\n",
            "mlxtend\n",
            "mlxtend-0.14.0.dist-info\n",
            "more_itertools\n",
            "more_itertools-8.10.0.dist-info\n",
            "moviepy\n",
            "moviepy-0.2.3.5.dist-info\n",
            "mpl_toolkits\n",
            "mpmath\n",
            "mpmath-1.2.1.dist-info\n",
            "msgpack\n",
            "msgpack-1.0.2.dist-info\n",
            "multiprocess\n",
            "_multiprocess\n",
            "multiprocess-0.70.12.2.dist-info\n",
            "multitasking\n",
            "multitasking-0.0.9.dist-info\n",
            "murmurhash\n",
            "murmurhash-1.0.5.dist-info\n",
            "music21\n",
            "music21-5.5.0.dist-info\n",
            "natsort\n",
            "natsort-5.5.0.dist-info\n",
            "nbclient\n",
            "nbclient-0.5.4.dist-info\n",
            "nbconvert\n",
            "nbconvert-5.6.1.dist-info\n",
            "nbformat\n",
            "nbformat-5.1.3.dist-info\n",
            "nest_asyncio-1.5.1.dist-info\n",
            "nest_asyncio.py\n",
            "netCDF4\n",
            "netCDF4-1.5.7.dist-info\n",
            "netCDF4.libs\n",
            "networkx\n",
            "networkx-2.6.3.dist-info\n",
            "nibabel\n",
            "nibabel-3.0.2.dist-info\n",
            "nisext\n",
            "nltk\n",
            "nltk-3.2.5.dist-info\n",
            "notebook\n",
            "notebook-5.3.1.dist-info\n",
            "numba\n",
            "numba-0.51.2.dist-info\n",
            "numbergen\n",
            "numexpr\n",
            "numexpr-2.7.3.dist-info\n",
            "numpy\n",
            "numpy-1.19.5.dist-info\n",
            "numpy.libs\n",
            "nvidia_ml_py3-7.352.0.dist-info\n",
            "nvidia_smi.py\n",
            "oauth2client\n",
            "oauth2client-4.1.3.dist-info\n",
            "oauthlib\n",
            "oauthlib-3.1.1.dist-info\n",
            "ogr.py\n",
            "okgrade\n",
            "okgrade-0.4.3.dist-info\n",
            "opencv_contrib_python-4.1.2.30.dist-info\n",
            "opencv_python-4.1.2.30.dist-info\n",
            "OpenGL\n",
            "openpyxl\n",
            "openpyxl-2.5.9.dist-info\n",
            "opt_einsum\n",
            "opt_einsum-3.3.0.dist-info\n",
            "osgeo\n",
            "osqp\n",
            "osqp-0.6.2.post0.dist-info\n",
            "osqppurepy\n",
            "osr.py\n",
            "packaging\n",
            "packaging-21.0.dist-info\n",
            "palettable\n",
            "palettable-3.3.0.dist-info\n",
            "pandas\n",
            "pandas-1.1.5.dist-info\n",
            "pandas_datareader\n",
            "pandas_datareader-0.9.0.dist-info\n",
            "pandas_gbq\n",
            "pandas_gbq-0.13.3.dist-info\n",
            "pandas_profiling\n",
            "pandas_profiling-1.4.1.dist-info\n",
            "pandocfilters-1.5.0.dist-info\n",
            "pandocfilters.py\n",
            "panel\n",
            "panel-0.12.1.dist-info\n",
            "param\n",
            "param-1.11.1.dist-info\n",
            "parso\n",
            "parso-0.8.2.dist-info\n",
            "past\n",
            "pasta\n",
            "pathlib-1.0.1.dist-info\n",
            "pathlib.py\n",
            "patsy\n",
            "patsy-0.5.1.dist-info\n",
            "pep517\n",
            "pep517-0.11.0.dist-info\n",
            "pexpect\n",
            "pexpect-4.8.0.dist-info\n",
            "pickleshare-0.7.5.dist-info\n",
            "pickleshare.py\n",
            "PIL\n",
            "Pillow-7.1.2.dist-info\n",
            "Pillow.libs\n",
            "pip\n",
            "pip-21.1.3.dist-info\n",
            "piptools\n",
            "pip_tools-6.2.0.dist-info\n",
            "pkg_resources\n",
            "plac-1.1.3.dist-info\n",
            "plac_core.py\n",
            "plac_ext.py\n",
            "plac.py\n",
            "plac_tk.py\n",
            "plotly\n",
            "plotly-4.4.1.dist-info\n",
            "_plotly_future_\n",
            "_plotly_utils\n",
            "plotlywidget\n",
            "plotnine\n",
            "plotnine-0.6.0.dist-info\n",
            "pluggy\n",
            "pluggy-0.7.1.dist-info\n",
            "pooch\n",
            "pooch-1.5.1.dist-info\n",
            "portpicker-1.3.9.dist-info\n",
            "portpicker.py\n",
            "prefetch_generator\n",
            "prefetch_generator-1.0.1.dist-info\n",
            "preshed\n",
            "preshed-3.0.5.dist-info\n",
            "prettytable\n",
            "prettytable-2.2.0.dist-info\n",
            "progressbar\n",
            "progressbar2-3.38.0.dist-info\n",
            "prometheus_client\n",
            "prometheus_client-0.11.0.dist-info\n",
            "promise\n",
            "promise-2.3.dist-info\n",
            "prompt_toolkit\n",
            "prompt_toolkit-1.0.18.dist-info\n",
            "protobuf-3.17.3.dist-info\n",
            "protobuf-3.17.3-py3.7-nspkg.pth\n",
            "psutil\n",
            "psutil-5.4.8.dist-info\n",
            "psycopg2\n",
            "psycopg2-2.7.6.1.dist-info\n",
            "ptyprocess\n",
            "ptyprocess-0.7.0.dist-info\n",
            "pvectorc.cpython-37m-x86_64-linux-gnu.so\n",
            "py\n",
            "py-1.10.0.dist-info\n",
            "pyarrow\n",
            "pyarrow-3.0.0.dist-info\n",
            "pyasn1\n",
            "pyasn1-0.4.8.dist-info\n",
            "pyasn1_modules\n",
            "pyasn1_modules-0.2.8.dist-info\n",
            "__pycache__\n",
            "pycocotools\n",
            "pycocotools-2.0.2.dist-info\n",
            "pycparser\n",
            "pycparser-2.20.dist-info\n",
            "pyct\n",
            "pyct-0.4.8.dist-info\n",
            "pydata_google_auth\n",
            "pydata_google_auth-1.2.0.dist-info\n",
            "pydot-1.3.0.dist-info\n",
            "pydot_ng\n",
            "pydot_ng-2.0.0.dist-info\n",
            "pydotplus\n",
            "pydotplus-2.0.2.dist-info\n",
            "pydot.py\n",
            "pydrive\n",
            "PyDrive-1.3.1.dist-info\n",
            "pyemd\n",
            "pyemd-0.5.1.dist-info\n",
            "pyerfa-2.0.0.dist-info\n",
            "pyglet\n",
            "pyglet-1.5.0.dist-info\n",
            "pygments\n",
            "Pygments-2.6.1.dist-info\n",
            "pylab.py\n",
            "pymc3\n",
            "pymc3-3.11.4.dist-info\n",
            "pymeeus\n",
            "PyMeeus-0.5.11.dist-info\n",
            "pymongo\n",
            "pymongo-3.12.0.dist-info\n",
            "pymystem3\n",
            "pymystem3-0.2.0.dist-info\n",
            "pynvml.py\n",
            "PyOpenGL-3.1.5.dist-info\n",
            "pyparsing-2.4.7.dist-info\n",
            "pyparsing.py\n",
            "pyrsistent\n",
            "pyrsistent-0.18.0.dist-info\n",
            "_pyrsistent_version.py\n",
            "pysndfile\n",
            "pysndfile-1.3.8.dist-info\n",
            "PySocks-1.7.1.dist-info\n",
            "pystan\n",
            "pystan-2.19.1.1.dist-info\n",
            "_pytest\n",
            "pytest-3.6.4.dist-info\n",
            "pytest.py\n",
            "python_apt-0.0.0.egg-info\n",
            "python_chess-0.23.11.dist-info\n",
            "python_dateutil-2.8.2.dist-info\n",
            "python_louvain-0.15.dist-info\n",
            "python_slugify-5.0.2.dist-info\n",
            "python_utils\n",
            "python_utils-2.5.6.dist-info\n",
            "pytz\n",
            "pytz-2018.9.dist-info\n",
            "pyviz_comms\n",
            "pyviz_comms-2.1.0.dist-info\n",
            "PyWavelets-1.1.1.dist-info\n",
            "pywt\n",
            "pyximport\n",
            "PyYAML-3.13.dist-info\n",
            "pyzmq-22.3.0.dist-info\n",
            "pyzmq.libs\n",
            "qdldl-0.1.5.post0.dist-info\n",
            "qdldl.cpython-37m-x86_64-linux-gnu.so\n",
            "qtconsole\n",
            "qtconsole-5.1.1.dist-info\n",
            "qtpy\n",
            "QtPy-1.11.2.dist-info\n",
            "regex\n",
            "regex-2019.12.20.dist-info\n",
            "requests\n",
            "requests-2.23.0.dist-info\n",
            "requests_oauthlib\n",
            "requests_oauthlib-1.3.0.dist-info\n",
            "resampy\n",
            "resampy-0.2.2.dist-info\n",
            "retrying-1.3.3.dist-info\n",
            "retrying.py\n",
            "_rinterface_cffi_abi.py\n",
            "_rinterface_cffi_api.abi3.so\n",
            "rpy2\n",
            "rpy2-3.4.5.dist-info\n",
            "rsa\n",
            "rsa-4.7.2.dist-info\n",
            "samples\n",
            "scikit_image-0.16.2.dist-info\n",
            "scikit_learn-0.22.2.post1.dist-info\n",
            "scipy\n",
            "scipy-1.4.1.dist-info\n",
            "scs\n",
            "scs-2.1.4.dist-info\n",
            "_scs_direct.cpython-37m-x86_64-linux-gnu.so\n",
            "_scs_indirect.cpython-37m-x86_64-linux-gnu.so\n",
            "_scs_python.cpython-37m-x86_64-linux-gnu.so\n",
            "seaborn\n",
            "seaborn-0.11.2.dist-info\n",
            "semver-2.13.0.dist-info\n",
            "semver.py\n",
            "send2trash\n",
            "Send2Trash-1.8.0.dist-info\n",
            "setuptools\n",
            "setuptools-57.4.0.dist-info\n",
            "setuptools_git\n",
            "setuptools_git-1.2.dist-info\n",
            "shapely\n",
            "Shapely-1.7.1.dist-info\n",
            "simplegeneric-0.8.1.dist-info\n",
            "simplegeneric.py\n",
            "six-1.15.0.dist-info\n",
            "six.py\n",
            "skimage\n",
            "sklearn\n",
            "sklearn-0.0.dist-info\n",
            "sklearn_pandas\n",
            "sklearn_pandas-1.8.0.dist-info\n",
            "slugify\n",
            "smart_open\n",
            "smart_open-5.2.1.dist-info\n",
            "snowballstemmer\n",
            "snowballstemmer-2.1.0.dist-info\n",
            "sockshandler.py\n",
            "socks.py\n",
            "sortedcontainers\n",
            "sortedcontainers-2.4.0.dist-info\n",
            "SoundFile-0.10.3.post1.dist-info\n",
            "_soundfile.py\n",
            "soundfile.py\n",
            "spacy\n",
            "spacy-2.2.4.dist-info\n",
            "sphinx\n",
            "Sphinx-1.8.5.dist-info\n",
            "sphinxcontrib\n",
            "sphinxcontrib_serializinghtml-1.1.5.dist-info\n",
            "sphinxcontrib_serializinghtml-1.1.5-py3.9-nspkg.pth\n",
            "sphinxcontrib_websupport-1.2.4.dist-info\n",
            "sphinxcontrib_websupport-1.2.4-py3.8-nspkg.pth\n",
            "sql\n",
            "sqlalchemy\n",
            "SQLAlchemy-1.4.25.dist-info\n",
            "sqlparse\n",
            "sqlparse-0.4.2.dist-info\n",
            "srsly\n",
            "srsly-1.0.5.dist-info\n",
            "statsmodels\n",
            "statsmodels-0.10.2.dist-info\n",
            "sympy\n",
            "sympy-1.7.1.dist-info\n",
            "tables\n",
            "tables-3.4.4.dist-info\n",
            "tabulate-0.8.9.dist-info\n",
            "tabulate.py\n",
            "tblib\n",
            "tblib-1.7.0.dist-info\n",
            "tensorboard\n",
            "tensorboard-2.6.0.dist-info\n",
            "tensorboard_data_server\n",
            "tensorboard_data_server-0.6.1.dist-info\n",
            "tensorboard_plugin_wit\n",
            "tensorboard_plugin_wit-1.8.0.dist-info\n",
            "tensorflow\n",
            "tensorflow-2.6.0.dist-info\n",
            "tensorflow_datasets\n",
            "tensorflow_datasets-4.0.1.dist-info\n",
            "tensorflow_estimator\n",
            "tensorflow_estimator-2.6.0.dist-info\n",
            "tensorflow_gcs_config\n",
            "tensorflow_gcs_config-2.6.0.dist-info\n",
            "tensorflow_hub\n",
            "tensorflow_hub-0.12.0.dist-info\n",
            "tensorflow_metadata\n",
            "tensorflow_metadata-1.2.0.dist-info\n",
            "tensorflow_probability\n",
            "tensorflow_probability-0.13.0.dist-info\n",
            "termcolor-1.1.0.dist-info\n",
            "termcolor.py\n",
            "terminado\n",
            "terminado-0.12.1.dist-info\n",
            "testpath\n",
            "testpath-0.5.0.dist-info\n",
            "tests\n",
            "textblob\n",
            "textblob-0.15.3.dist-info\n",
            "text_unidecode\n",
            "text_unidecode-1.3.dist-info\n",
            "theano\n",
            "Theano_PyMC-1.1.2.dist-info\n",
            "thinc\n",
            "thinc-7.4.0.dist-info\n",
            "tifffile\n",
            "tifffile-2021.8.30.dist-info\n",
            "tlz\n",
            "toml\n",
            "toml-0.10.2.dist-info\n",
            "tomli\n",
            "tomli-1.2.1.dist-info\n",
            "toolz\n",
            "toolz-0.11.1.dist-info\n",
            "torch\n",
            "torch-1.9.0+cu102.dist-info\n",
            "torchsummary\n",
            "torchsummary-1.5.1.dist-info\n",
            "torchtext\n",
            "torchtext-0.10.0.dist-info\n",
            "torchvision\n",
            "torchvision-0.10.0+cu102.dist-info\n",
            "torchvision.libs\n",
            "tornado\n",
            "tornado-5.1.1.dist-info\n",
            "tqdm\n",
            "tqdm-4.62.3.dist-info\n",
            "traitlets\n",
            "traitlets-5.1.0.dist-info\n",
            "tree\n",
            "tweepy\n",
            "tweepy-3.10.0.dist-info\n",
            "typeguard\n",
            "typeguard-2.7.1.dist-info\n",
            "typing_extensions-3.7.4.3.dist-info\n",
            "typing_extensions.py\n",
            "tzlocal\n",
            "tzlocal-1.5.1.dist-info\n",
            "uritemplate\n",
            "uritemplate-3.0.1.dist-info\n",
            "urllib3\n",
            "urllib3-1.24.3.dist-info\n",
            "vega_datasets\n",
            "vega_datasets-0.9.0.dist-info\n",
            "vis\n",
            "wasabi\n",
            "wasabi-0.8.2.dist-info\n",
            "wcwidth\n",
            "wcwidth-0.2.5.dist-info\n",
            "webencodings\n",
            "webencodings-0.5.1.dist-info\n",
            "werkzeug\n",
            "Werkzeug-1.0.1.dist-info\n",
            "wheel\n",
            "wheel-0.37.0.dist-info\n",
            "widgetsnbextension\n",
            "widgetsnbextension-3.5.1.dist-info\n",
            "wordcloud\n",
            "wordcloud-1.5.0.dist-info\n",
            "wrapt\n",
            "wrapt-1.12.1.dist-info\n",
            "xarray\n",
            "xarray-0.18.2.dist-info\n",
            "xgboost\n",
            "xgboost-0.90.dist-info\n",
            "xlrd\n",
            "xlrd-1.1.0.dist-info\n",
            "xlwt\n",
            "xlwt-1.3.0.dist-info\n",
            "yaml\n",
            "yellowbrick\n",
            "yellowbrick-0.9.1.dist-info\n",
            "zict\n",
            "zict-2.0.0.dist-info\n",
            "zipp-3.5.0.dist-info\n",
            "zipp.py\n",
            "zmq\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d0BUiXEH80Cx",
        "outputId": "5ca6b47d-53cc-4dbc-f2bd-95b067cb0093"
      },
      "source": [
        "!ls"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Miniconda3-py37_4.9.2-Linux-x86_64.sh  sample_data\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "viA700jR9Ufc"
      },
      "source": [
        "# requirements.txt 생성\n",
        "p = \"\"\"\n",
        "torch==1.6.0\n",
        "pillow>=4.1.1\n",
        "transformers>=4.0.0\n",
        "sentence_transformers>=0.4.1.2\n",
        "nltk>=3.5\n",
        "word2word\n",
        "torchvision==0.7.0\n",
        "fairseq>=0.10.2\n",
        "python-mecab-ko==1.0.9\n",
        "kollocate\n",
        "koparadigm\n",
        "g2pk\n",
        "wget\n",
        "joblib\n",
        "lxml\n",
        "g2p_en\n",
        "whoosh\n",
        "marisa-trie\n",
        "kss\n",
        "pandas\n",
        "scipy\n",
        "ipykernel\n",
        "\"\"\"\n",
        "\n",
        "c = \"\"\"text_file = open(\"requirements.txt\", \"w+\");text_file.write(p);text_file.close()\"\"\" \n",
        "\n",
        "exec(c)"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6eA46QRo92nm",
        "outputId": "95e5cf64-b1f7-4127-c22d-72783d3fff12"
      },
      "source": [
        "# 가상환경 만들기\n",
        "\n",
        "!conda create -n pororo python==3.7"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\bdone\n",
            "Solving environment: | \b\bfailed with repodata from current_repodata.json, will retry with next repodata source.\n",
            "Collecting package metadata (repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
            "Solving environment: - \b\b\\ \b\b| \b\b/ \b\bdone\n",
            "\n",
            "\n",
            "==> WARNING: A newer version of conda exists. <==\n",
            "  current version: 4.9.2\n",
            "  latest version: 4.10.3\n",
            "\n",
            "Please update conda by running\n",
            "\n",
            "    $ conda update -n base -c defaults conda\n",
            "\n",
            "\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local/envs/pororo\n",
            "\n",
            "  added / updated specs:\n",
            "    - python==3.7\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    _openmp_mutex-4.5          |            1_gnu          22 KB\n",
            "    ca-certificates-2021.7.5   |       h06a4308_1         113 KB\n",
            "    certifi-2021.5.30          |   py37h06a4308_0         139 KB\n",
            "    libedit-3.1.20210714       |       h7f8727e_0         165 KB\n",
            "    libffi-3.2.1               |    hf484d3e_1007          48 KB\n",
            "    libgcc-ng-9.3.0            |      h5101ec6_17         4.8 MB\n",
            "    libgomp-9.3.0              |      h5101ec6_17         311 KB\n",
            "    libstdcxx-ng-9.3.0         |      hd4cf53a_17         3.1 MB\n",
            "    openssl-1.0.2u             |       h7b6447c_0         2.2 MB\n",
            "    pip-21.2.2                 |   py37h06a4308_0         1.8 MB\n",
            "    python-3.7.0               |       h6e4f718_3        27.2 MB\n",
            "    readline-7.0               |       h7b6447c_5         324 KB\n",
            "    setuptools-58.0.4          |   py37h06a4308_0         775 KB\n",
            "    tk-8.6.11                  |       h1ccaba5_0         3.0 MB\n",
            "    wheel-0.37.0               |     pyhd3eb1b0_1          33 KB\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:        44.0 MB\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  _libgcc_mutex      pkgs/main/linux-64::_libgcc_mutex-0.1-main\n",
            "  _openmp_mutex      pkgs/main/linux-64::_openmp_mutex-4.5-1_gnu\n",
            "  ca-certificates    pkgs/main/linux-64::ca-certificates-2021.7.5-h06a4308_1\n",
            "  certifi            pkgs/main/linux-64::certifi-2021.5.30-py37h06a4308_0\n",
            "  libedit            pkgs/main/linux-64::libedit-3.1.20210714-h7f8727e_0\n",
            "  libffi             pkgs/main/linux-64::libffi-3.2.1-hf484d3e_1007\n",
            "  libgcc-ng          pkgs/main/linux-64::libgcc-ng-9.3.0-h5101ec6_17\n",
            "  libgomp            pkgs/main/linux-64::libgomp-9.3.0-h5101ec6_17\n",
            "  libstdcxx-ng       pkgs/main/linux-64::libstdcxx-ng-9.3.0-hd4cf53a_17\n",
            "  ncurses            pkgs/main/linux-64::ncurses-6.2-he6710b0_1\n",
            "  openssl            pkgs/main/linux-64::openssl-1.0.2u-h7b6447c_0\n",
            "  pip                pkgs/main/linux-64::pip-21.2.2-py37h06a4308_0\n",
            "  python             pkgs/main/linux-64::python-3.7.0-h6e4f718_3\n",
            "  readline           pkgs/main/linux-64::readline-7.0-h7b6447c_5\n",
            "  setuptools         pkgs/main/linux-64::setuptools-58.0.4-py37h06a4308_0\n",
            "  sqlite             pkgs/main/linux-64::sqlite-3.33.0-h62c20be_0\n",
            "  tk                 pkgs/main/linux-64::tk-8.6.11-h1ccaba5_0\n",
            "  wheel              pkgs/main/noarch::wheel-0.37.0-pyhd3eb1b0_1\n",
            "  xz                 pkgs/main/linux-64::xz-5.2.5-h7b6447c_0\n",
            "  zlib               pkgs/main/linux-64::zlib-1.2.11-h7b6447c_3\n",
            "\n",
            "\n",
            "Proceed ([y]/n)? ㅛ\n",
            "Invalid choice: ㅛ\n",
            "Proceed ([y]/n)? ㅛ\n",
            "Invalid choice: ㅛ\n",
            "Proceed ([y]/n)? y\n",
            "\n",
            "\n",
            "Downloading and Extracting Packages\n",
            "_openmp_mutex-4.5    | 22 KB     | : 100% 1.0/1 [00:00<00:00,  5.44it/s]               \n",
            "openssl-1.0.2u       | 2.2 MB    | : 100% 1.0/1 [00:00<00:00,  2.85it/s]\n",
            "tk-8.6.11            | 3.0 MB    | : 100% 1.0/1 [00:00<00:00,  3.07it/s]\n",
            "libedit-3.1.20210714 | 165 KB    | : 100% 1.0/1 [00:00<00:00,  9.99it/s]\n",
            "ca-certificates-2021 | 113 KB    | : 100% 1.0/1 [00:00<00:00, 11.05it/s]\n",
            "pip-21.2.2           | 1.8 MB    | : 100% 1.0/1 [00:00<00:00,  3.30it/s]               \n",
            "readline-7.0         | 324 KB    | : 100% 1.0/1 [00:00<00:00,  9.86it/s]\n",
            "libgcc-ng-9.3.0      | 4.8 MB    | : 100% 1.0/1 [00:00<00:00,  2.63it/s]\n",
            "setuptools-58.0.4    | 775 KB    | : 100% 1.0/1 [00:00<00:00,  7.05it/s]\n",
            "libgomp-9.3.0        | 311 KB    | : 100% 1.0/1 [00:00<00:00,  9.83it/s]\n",
            "libffi-3.2.1         | 48 KB     | : 100% 1.0/1 [00:00<00:00, 10.87it/s]\n",
            "certifi-2021.5.30    | 139 KB    | : 100% 1.0/1 [00:00<00:00, 10.55it/s]\n",
            "libstdcxx-ng-9.3.0   | 3.1 MB    | : 100% 1.0/1 [00:00<00:00,  3.77it/s]\n",
            "python-3.7.0         | 27.2 MB   | : 100% 1.0/1 [00:01<00:00,  1.33s/it]              \n",
            "wheel-0.37.0         | 33 KB     | : 100% 1.0/1 [00:00<00:00,  8.83it/s]\n",
            "Preparing transaction: \\ \b\b| \b\b/ \b\b- \b\bdone\n",
            "Verifying transaction: | \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n",
            "Executing transaction: \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\bdone\n",
            "#\n",
            "# To activate this environment, use\n",
            "#\n",
            "#     $ conda activate pororo\n",
            "#\n",
            "# To deactivate an active environment, use\n",
            "#\n",
            "#     $ conda deactivate\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J46Qhj9sDjv_",
        "outputId": "5d242566-265b-4f96-867c-5fc15b04c4a6"
      },
      "source": [
        "# 혹시 conda init 하라는 알림이 뜰 경우\n",
        "!conda init"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "no change     /usr/local/condabin/conda\n",
            "no change     /usr/local/bin/conda\n",
            "no change     /usr/local/bin/conda-env\n",
            "no change     /usr/local/bin/activate\n",
            "no change     /usr/local/bin/deactivate\n",
            "no change     /usr/local/etc/profile.d/conda.sh\n",
            "no change     /usr/local/etc/fish/conf.d/conda.fish\n",
            "no change     /usr/local/shell/condabin/Conda.psm1\n",
            "no change     /usr/local/shell/condabin/conda-hook.ps1\n",
            "no change     /usr/local/lib/python3.7/site-packages/xontrib/conda.xsh\n",
            "no change     /usr/local/etc/profile.d/conda.csh\n",
            "modified      /root/.bashrc\n",
            "\n",
            "==> For changes to take effect, close and re-open your current shell. <==\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TxRYAoSZJH_a",
        "outputId": "d8cd117c-379e-495d-ab8c-806de10b9e88"
      },
      "source": [
        "# 먼저 가상환경 실행시키고 가상환경 확인\n",
        "!source activate pororo && conda env list"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "# conda environments:\n",
            "#\n",
            "base                     /usr/local\n",
            "pororo                *  /usr/local/envs/pororo\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OT5CY5GdQzLY"
      },
      "source": [
        "> Requirements.txt 설치"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hso_feEt9Q27",
        "outputId": "7afa899e-1b3d-4fc6-e5ac-c4f7ace6114d"
      },
      "source": [
        "!conda install --channel conda-forge --file requirements.txt --yes"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\bdone\n",
            "Solving environment: / \b\bfailed with initial frozen solve. Retrying with flexible solve.\n",
            "Collecting package metadata (repodata.json): \\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\b/ \b\b- \b\b\\ \b\b| \b\bdone\n",
            "Solving environment: - \b\bfailed with initial frozen solve. Retrying with flexible solve.\n",
            "\n",
            "PackagesNotFoundError: The following packages are not available from current channels:\n",
            "\n",
            "  - word2word\n",
            "  - sentence_transformers[version='>=0.4.1.2']\n",
            "  - kss\n",
            "  - kollocate\n",
            "  - torch==1.6.0\n",
            "  - python-mecab-ko==1.0.9\n",
            "  - torchvision==0.7.0\n",
            "  - koparadigm\n",
            "  - g2pk\n",
            "  - g2p_en\n",
            "\n",
            "Current channels:\n",
            "\n",
            "  - https://conda.anaconda.org/conda-forge/linux-64\n",
            "  - https://conda.anaconda.org/conda-forge/noarch\n",
            "  - https://repo.anaconda.com/pkgs/main/linux-64\n",
            "  - https://repo.anaconda.com/pkgs/main/noarch\n",
            "  - https://repo.anaconda.com/pkgs/r/linux-64\n",
            "  - https://repo.anaconda.com/pkgs/r/noarch\n",
            "\n",
            "To search for alternate channels that may provide the conda package you're\n",
            "looking for, navigate to\n",
            "\n",
            "    https://anaconda.org\n",
            "\n",
            "and use the search bar at the top of the page.\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "B2SUQQeZWxFP",
        "outputId": "bda2fc1b-205f-4513-c1ae-96d946bb62cc"
      },
      "source": [
        "!pip install pororo"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pororo\n",
            "  Downloading pororo-0.4.2-py3-none-any.whl (256 kB)\n",
            "\u001b[K     |████████████████████████████████| 256 kB 1.7 MB/s \n",
            "\u001b[?25hCollecting nltk>=3.5\n",
            "  Downloading nltk-3.6.3-py3-none-any.whl (1.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.5 MB 27.5 MB/s \n",
            "\u001b[?25hCollecting word2word\n",
            "  Downloading word2word-1.0.0-py3-none-any.whl (31 kB)\n",
            "Collecting marisa-trie\n",
            "  Downloading marisa_trie-0.7.7-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.2 MB 17.4 MB/s \n",
            "\u001b[?25hCollecting joblib\n",
            "  Downloading joblib-1.0.1-py3-none-any.whl (303 kB)\n",
            "\u001b[K     |████████████████████████████████| 303 kB 53.1 MB/s \n",
            "\u001b[?25hCollecting transformers>=4.0.0\n",
            "  Downloading transformers-4.11.2-py3-none-any.whl (2.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 2.9 MB 45.3 MB/s \n",
            "\u001b[?25hCollecting kss\n",
            "  Downloading kss-3.2.0.tar.gz (42.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 42.4 MB 56 kB/s \n",
            "\u001b[?25hCollecting torch==1.6.0\n",
            "  Downloading torch-1.6.0-cp37-cp37m-manylinux1_x86_64.whl (748.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 748.8 MB 16 kB/s \n",
            "\u001b[?25hCollecting whoosh\n",
            "  Downloading Whoosh-2.7.4-py2.py3-none-any.whl (468 kB)\n",
            "\u001b[K     |████████████████████████████████| 468 kB 32.0 MB/s \n",
            "\u001b[?25hCollecting sentence-transformers>=0.4.1.2\n",
            "  Downloading sentence-transformers-2.0.0.tar.gz (85 kB)\n",
            "\u001b[K     |████████████████████████████████| 85 kB 3.0 MB/s \n",
            "\u001b[?25hCollecting g2p-en\n",
            "  Downloading g2p_en-2.1.0-py3-none-any.whl (3.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.1 MB 21.5 MB/s \n",
            "\u001b[?25hCollecting fairseq>=0.10.2\n",
            "  Downloading fairseq-0.10.2-cp37-cp37m-manylinux1_x86_64.whl (1.7 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.7 MB 23.7 MB/s \n",
            "\u001b[?25hCollecting wget\n",
            "  Downloading wget-3.2.zip (10 kB)\n",
            "Collecting torchvision==0.7.0\n",
            "  Downloading torchvision-0.7.0-cp37-cp37m-manylinux1_x86_64.whl (5.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 5.9 MB 17.2 MB/s \n",
            "\u001b[?25hCollecting lxml\n",
            "  Downloading lxml-4.6.3-cp37-cp37m-manylinux2014_x86_64.whl (6.3 MB)\n",
            "\u001b[K     |████████████████████████████████| 6.3 MB 11.4 MB/s \n",
            "\u001b[?25hCollecting pillow>=4.1.1\n",
            "  Downloading Pillow-8.3.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.0 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.0 MB 33.0 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tqdm in /usr/local/lib/python3.7/site-packages (from nltk>=3.5->pororo) (4.51.0)\n",
            "Collecting regex\n",
            "  Downloading regex-2021.9.30-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (747 kB)\n",
            "\u001b[K     |████████████████████████████████| 747 kB 49.0 MB/s \n",
            "\u001b[?25hCollecting click\n",
            "  Downloading click-8.0.1-py3-none-any.whl (97 kB)\n",
            "\u001b[K     |████████████████████████████████| 97 kB 6.0 MB/s \n",
            "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.7/site-packages (from word2word->pororo) (2.24.0)\n",
            "Collecting numpy\n",
            "  Downloading numpy-1.21.2-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (15.7 MB)\n",
            "\u001b[K     |████████████████████████████████| 15.7 MB 182 kB/s \n",
            "\u001b[?25hRequirement already satisfied: setuptools in /usr/local/lib/python3.7/site-packages (from marisa-trie->pororo) (50.3.1.post20201107)\n",
            "Collecting tokenizers<0.11,>=0.10.1\n",
            "  Downloading tokenizers-0.10.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.3 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.3 MB 49.9 MB/s \n",
            "\u001b[?25hCollecting pyyaml>=5.1\n",
            "  Downloading PyYAML-5.4.1-cp37-cp37m-manylinux1_x86_64.whl (636 kB)\n",
            "\u001b[K     |████████████████████████████████| 636 kB 46.6 MB/s \n",
            "\u001b[?25hCollecting filelock\n",
            "  Downloading filelock-3.2.0-py2.py3-none-any.whl (10 kB)\n",
            "Collecting importlib-metadata; python_version < \"3.8\"\n",
            "  Downloading importlib_metadata-4.8.1-py3-none-any.whl (17 kB)\n",
            "Collecting huggingface-hub>=0.0.17\n",
            "  Downloading huggingface_hub-0.0.17-py3-none-any.whl (52 kB)\n",
            "\u001b[K     |████████████████████████████████| 52 kB 1.1 MB/s \n",
            "\u001b[?25hCollecting packaging>=20.0\n",
            "  Downloading packaging-21.0-py3-none-any.whl (40 kB)\n",
            "\u001b[K     |████████████████████████████████| 40 kB 3.5 MB/s \n",
            "\u001b[?25hCollecting sacremoses\n",
            "  Downloading sacremoses-0.0.46-py3-none-any.whl (895 kB)\n",
            "\u001b[K     |████████████████████████████████| 895 kB 56.0 MB/s \n",
            "\u001b[?25hCollecting emoji\n",
            "  Downloading emoji-1.5.0.tar.gz (185 kB)\n",
            "\u001b[K     |████████████████████████████████| 185 kB 52.5 MB/s \n",
            "\u001b[?25hCollecting future\n",
            "  Downloading future-0.18.2.tar.gz (829 kB)\n",
            "\u001b[K     |████████████████████████████████| 829 kB 57.5 MB/s \n",
            "\u001b[?25hCollecting scikit-learn\n",
            "  Downloading scikit_learn-1.0-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (23.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 23.1 MB 1.2 MB/s \n",
            "\u001b[?25hCollecting scipy\n",
            "  Downloading scipy-1.7.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (28.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 28.5 MB 45 kB/s \n",
            "\u001b[?25hCollecting sentencepiece\n",
            "  Downloading sentencepiece-0.1.96-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.2 MB 41.6 MB/s \n",
            "\u001b[?25hCollecting distance>=0.1.3\n",
            "  Downloading Distance-0.1.3.tar.gz (180 kB)\n",
            "\u001b[K     |████████████████████████████████| 180 kB 69.7 MB/s \n",
            "\u001b[?25hCollecting inflect>=0.3.1\n",
            "  Downloading inflect-5.3.0-py3-none-any.whl (32 kB)\n",
            "Collecting sacrebleu>=1.4.12\n",
            "  Downloading sacrebleu-2.0.0-py3-none-any.whl (90 kB)\n",
            "\u001b[K     |████████████████████████████████| 90 kB 8.5 MB/s \n",
            "\u001b[?25hCollecting dataclasses\n",
            "  Downloading dataclasses-0.6-py3-none-any.whl (14 kB)\n",
            "Requirement already satisfied: cffi in /usr/local/lib/python3.7/site-packages (from fairseq>=0.10.2->pororo) (1.14.3)\n",
            "Collecting cython\n",
            "  Downloading Cython-0.29.24-cp37-cp37m-manylinux1_x86_64.whl (2.0 MB)\n",
            "\u001b[K     |████████████████████████████████| 2.0 MB 36.6 MB/s \n",
            "\u001b[?25hCollecting hydra-core\n",
            "  Downloading hydra_core-1.1.1-py3-none-any.whl (145 kB)\n",
            "\u001b[K     |████████████████████████████████| 145 kB 60.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/site-packages (from requests->word2word->pororo) (1.25.11)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/site-packages (from requests->word2word->pororo) (2020.6.20)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/site-packages (from requests->word2word->pororo) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/site-packages (from requests->word2word->pororo) (2.10)\n",
            "Collecting typing-extensions>=3.6.4; python_version < \"3.8\"\n",
            "  Downloading typing_extensions-3.10.0.2-py3-none-any.whl (26 kB)\n",
            "Collecting zipp>=0.5\n",
            "  Downloading zipp-3.6.0-py3-none-any.whl (5.3 kB)\n",
            "Collecting pyparsing>=2.0.2\n",
            "  Downloading pyparsing-2.4.7-py2.py3-none-any.whl (67 kB)\n",
            "\u001b[K     |████████████████████████████████| 67 kB 5.5 MB/s \n",
            "\u001b[?25hRequirement already satisfied: six in /usr/local/lib/python3.7/site-packages (from sacremoses->transformers>=4.0.0->pororo) (1.15.0)\n",
            "Collecting threadpoolctl>=2.0.0\n",
            "  Downloading threadpoolctl-2.2.0-py3-none-any.whl (12 kB)\n",
            "Collecting colorama\n",
            "  Downloading colorama-0.4.4-py2.py3-none-any.whl (16 kB)\n",
            "Collecting tabulate>=0.8.9\n",
            "  Downloading tabulate-0.8.9-py3-none-any.whl (25 kB)\n",
            "Collecting portalocker\n",
            "  Downloading portalocker-2.3.2-py2.py3-none-any.whl (15 kB)\n",
            "Requirement already satisfied: pycparser in /usr/local/lib/python3.7/site-packages (from cffi->fairseq>=0.10.2->pororo) (2.20)\n",
            "Collecting antlr4-python3-runtime==4.8\n",
            "  Downloading antlr4-python3-runtime-4.8.tar.gz (112 kB)\n",
            "\u001b[K     |████████████████████████████████| 112 kB 54.9 MB/s \n",
            "\u001b[?25hCollecting omegaconf==2.1.*\n",
            "  Downloading omegaconf-2.1.1-py3-none-any.whl (74 kB)\n",
            "\u001b[K     |████████████████████████████████| 74 kB 3.1 MB/s \n",
            "\u001b[?25hCollecting importlib-resources; python_version < \"3.9\"\n",
            "  Downloading importlib_resources-5.2.2-py3-none-any.whl (27 kB)\n",
            "Building wheels for collected packages: kss, sentence-transformers, wget, emoji, future, distance, antlr4-python3-runtime\n",
            "  Building wheel for kss (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for kss: filename=kss-3.2.0-py3-none-any.whl size=42447980 sha256=457cad402b296e5965ea1c1990cb55dd9038e371599888e6350d397d2b8577c3\n",
            "  Stored in directory: /root/.cache/pip/wheels/a1/47/9c/a5f83b5ab6096e3c4a33643fc553b26098c23e72b6539b86f4\n",
            "  Building wheel for sentence-transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sentence-transformers: filename=sentence_transformers-2.0.0-py3-none-any.whl size=126710 sha256=26e2f53e057f3b2af0ff9fe91ee12deec2c7d8e5ec4b461e52acf350fd148362\n",
            "  Stored in directory: /root/.cache/pip/wheels/d1/c1/0f/faafd427f705c4b012274ba60d9a91d75830306811e1355293\n",
            "  Building wheel for wget (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for wget: filename=wget-3.2-py3-none-any.whl size=9681 sha256=29250d213c0543229407fbf285a1235b426427289cc8237776cd7daad4e5ad23\n",
            "  Stored in directory: /root/.cache/pip/wheels/a1/b6/7c/0e63e34eb06634181c63adacca38b79ff8f35c37e3c13e3c02\n",
            "  Building wheel for emoji (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for emoji: filename=emoji-1.5.0-py3-none-any.whl size=187441 sha256=5c13a67fbf99dff9d74562e5ce162b0d54f2859d18288320a99f2339b56ad61c\n",
            "  Stored in directory: /root/.cache/pip/wheels/db/b5/f6/b39abf14e94b3d6640613bbe630a66c10ccf7a12882d064fb5\n",
            "  Building wheel for future (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for future: filename=future-0.18.2-py3-none-any.whl size=491059 sha256=8e89fa127507b32d4b9ef705adf3ec56cc010b670c09d08cd94f196ad7817b11\n",
            "  Stored in directory: /root/.cache/pip/wheels/56/b0/fe/4410d17b32f1f0c3cf54cdfb2bc04d7b4b8f4ae377e2229ba0\n",
            "  Building wheel for distance (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for distance: filename=Distance-0.1.3-py3-none-any.whl size=16261 sha256=da2982238a80f4d06768d498538073000874ddc04d5f38399bf89a8099cb6152\n",
            "  Stored in directory: /root/.cache/pip/wheels/b2/10/1b/96fca621a1be378e2fe104cfb0d160bb6cdf3d04a3d35266cc\n",
            "  Building wheel for antlr4-python3-runtime (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for antlr4-python3-runtime: filename=antlr4_python3_runtime-4.8-py3-none-any.whl size=141229 sha256=6ade9ce06af9b4f5940dca00dc5742959376b1820b99449e88e8c65281713413\n",
            "  Stored in directory: /root/.cache/pip/wheels/ca/33/b7/336836125fc9bb4ceaa4376d8abca10ca8bc84ddc824baea6c\n",
            "Successfully built kss sentence-transformers wget emoji future distance antlr4-python3-runtime\n",
            "Installing collected packages: joblib, regex, typing-extensions, zipp, importlib-metadata, click, nltk, numpy, wget, word2word, marisa-trie, tokenizers, pyyaml, filelock, pyparsing, packaging, huggingface-hub, sacremoses, transformers, emoji, kss, future, torch, whoosh, pillow, torchvision, threadpoolctl, scipy, scikit-learn, sentencepiece, sentence-transformers, distance, inflect, g2p-en, colorama, tabulate, portalocker, sacrebleu, dataclasses, cython, antlr4-python3-runtime, omegaconf, importlib-resources, hydra-core, fairseq, lxml, pororo\n",
            "Successfully installed antlr4-python3-runtime-4.8 click-8.0.1 colorama-0.4.4 cython-0.29.24 dataclasses-0.6 distance-0.1.3 emoji-1.5.0 fairseq-0.10.2 filelock-3.2.0 future-0.18.2 g2p-en-2.1.0 huggingface-hub-0.0.17 hydra-core-1.1.1 importlib-metadata-4.8.1 importlib-resources-5.2.2 inflect-5.3.0 joblib-1.0.1 kss-3.2.0 lxml-4.6.3 marisa-trie-0.7.7 nltk-3.6.3 numpy-1.21.2 omegaconf-2.1.1 packaging-21.0 pillow-8.3.2 pororo-0.4.2 portalocker-2.3.2 pyparsing-2.4.7 pyyaml-5.4.1 regex-2021.9.30 sacrebleu-2.0.0 sacremoses-0.0.46 scikit-learn-1.0 scipy-1.7.1 sentence-transformers-2.0.0 sentencepiece-0.1.96 tabulate-0.8.9 threadpoolctl-2.2.0 tokenizers-0.10.3 torch-1.6.0 torchvision-0.7.0 transformers-4.11.2 typing-extensions-3.10.0.2 wget-3.2 whoosh-2.7.4 word2word-1.0.0 zipp-3.6.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "pyparsing"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hQSlJI3zY4M2"
      },
      "source": [
        "## 뽀로로를 돌려보자 !!!!!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mhl-RtrJWyY1"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import sys, os\n",
        "import torch"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fcL6OGFlW2yC",
        "outputId": "3c5e7c16-a13d-4fa5-b3e3-5e1a7e3f709c"
      },
      "source": [
        "from pororo import Pororo"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[Korean Sentence Splitter]: Initializing Kss...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        },
        "id": "U5RT3q9QXJTE",
        "outputId": "2d62c42b-aa83-4bc8-94c2-8fbd6e78c86a"
      },
      "source": [
        "Pororo.available_tasks()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "\"Available tasks are ['mrc', 'rc', 'qa', 'question_answering', 'machine_reading_comprehension', 'reading_comprehension', 'sentiment', 'sentiment_analysis', 'nli', 'natural_language_inference', 'inference', 'fill', 'fill_in_blank', 'fib', 'para', 'pi', 'cse', 'contextual_subword_embedding', 'similarity', 'sts', 'semantic_textual_similarity', 'sentence_similarity', 'sentvec', 'sentence_embedding', 'sentence_vector', 'se', 'inflection', 'morphological_inflection', 'g2p', 'grapheme_to_phoneme', 'grapheme_to_phoneme_conversion', 'w2v', 'wordvec', 'word2vec', 'word_vector', 'word_embedding', 'tokenize', 'tokenise', 'tokenization', 'tokenisation', 'tok', 'segmentation', 'seg', 'mt', 'machine_translation', 'translation', 'pos', 'tag', 'pos_tagging', 'tagging', 'const', 'constituency', 'constituency_parsing', 'cp', 'pg', 'collocation', 'collocate', 'col', 'word_translation', 'wt', 'summarization', 'summarisation', 'text_summarization', 'text_summarisation', 'summary', 'gec', 'review', 'review_scoring', 'lemmatization', 'lemmatisation', 'lemma', 'ner', 'named_entity_recognition', 'entity_recognition', 'zero-topic', 'dp', 'dep_parse', 'caption', 'captioning', 'asr', 'speech_recognition', 'st', 'speech_translation', 'tts', 'text_to_speech', 'speech_synthesis', 'ocr', 'srl', 'semantic_role_labeling', 'p2g', 'aes', 'essay', 'qg', 'question_generation', 'age_suitability', 'wsd']\""
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B-q_ILhJY7Jz"
      },
      "source": [
        "> Question Genreration "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286,
          "referenced_widgets": [
            "48472096df294be78a38a1c02e6552a9",
            "3bfe8827604c474c95e8415f17714947",
            "3556fd0799c04387a81ba53edbae5fe1",
            "388593c5ffcc413496fb536539c92de7",
            "7f2d4a04b9d744918d92097679d1f9c2",
            "7e40ac058a1047f8a8caf5a73d11c543",
            "15c9dd333a2d48869a28cc4bc6e02f86",
            "a46ad3128c6041608014491a4d6ff057",
            "664aee7a762444b181ac45be7787f855",
            "c0518a969ff14d6bb922f6f222797c6c",
            "c7db1bf8a96f4ae8b096446928b610d9",
            "2ed1e82ee671485ca81b88df625408ae",
            "0470f28313df4cd98050a41f17709c77",
            "2eb16b601cfa48f295436c97cf27cdf6",
            "16d27128b68146c4a7a565ae6baa93be",
            "41b733067ea0484686bb1471ded32785",
            "84262bb5085349ec8bd20703b7d6c069",
            "fb538a6564e34986bc5b1e05d9b02c0c",
            "89d7026807354a50a28560381c7698c1",
            "94956b3f819e47a7b8f3ce5c957e61ff",
            "224d9185a7314835b281feb9121e0e97",
            "6ac4e083d3514acc96d438c3502fcdf0",
            "869f9ee624e64b35a1167cc810c5b2ec",
            "4ca3d670f99f43428b8043a039860cb1",
            "1f75b1a67df34c4a8066521e5ca0c122",
            "e9d1e96d3fbe4d189b01f315dcba8ca1",
            "988cb1a36ca947108a351eb250eba730",
            "5923068b7b56447480f041243545b1ca",
            "83cfa92d5c66406b9d69decd3d39ce49",
            "7f82a10c4a71473a878f00e284bb0c01",
            "9f7303733a8b416a9077f291a7794bd5",
            "354f9be7847a4e31bd0b1aad15529151",
            "af980b10d75d48eeb313e6a6078b71b7",
            "0ca1732ed62549688088ec401c0fcdf3",
            "32656efdd4f84708b8af8edca1eb1f1e",
            "1447d43d171b4d7885976416dcf0e2f9",
            "dae568dfb43a4ecc81f386427c4dca5d",
            "54cd7f71c285411f874db3cafa8c62a7",
            "61fdce810d9b409a87cb4cf5eb70288c",
            "df1807c7e58c42328e28bf767a055f60",
            "faaddc1c7da846c2bcf6d89cd1fbb938",
            "69a1b8f499e44f65b5e973dae2483453",
            "15fc314c75834084a24588b351758696",
            "303423cb24f745d28e9af6b62c370715",
            "95998bb3e1b5468e95412e26705b2da3",
            "ecdfa8c7187f4085975ea33d2629546a",
            "684ffc9a80fb4c25be6f25b4b4e1756c",
            "7ac7fd4a5e9248628aff4068b51311df",
            "eb83ef6e255943ce9e4232e53d3f3f2d",
            "2b00af78a0d941fca5703fa2e05c8df9",
            "0974c2b8e4a949f1a4218b583bb8e59c",
            "b448361522c843e1b0ddb4de02009d20",
            "9864890111504d23bf56435785be75a5",
            "6494ad4a234847168de927eba2327bb5",
            "4698d436356146bcb8fd7a92a39520bc"
          ]
        },
        "id": "l7x07VfnXLP7",
        "outputId": "234ff767-32fb-4680-b805-da8bc3405b28"
      },
      "source": [
        "qg = Pororo(task=\"question_generation\", lang=\"ko\")"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "48472096df294be78a38a1c02e6552a9",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/1.08k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "2ed1e82ee671485ca81b88df625408ae",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/2.00 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "869f9ee624e64b35a1167cc810c5b2ec",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/85.0 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "0ca1732ed62549688088ec401c0fcdf3",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/109 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "95998bb3e1b5468e95412e26705b2da3",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/666k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. \n",
            "The tokenizer class you load from this checkpoint is 'BartTokenizer'. \n",
            "The class this function is called from is 'PreTrainedTokenizerFast'.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v934BHhAXljZ",
        "outputId": "7fc8de54-97d5-4276-ff12-af87c3ec8bab"
      },
      "source": [
        "qg(\n",
        "    \"카카오톡\",\n",
        "    \"카카오톡은 스마트폰의 데이터 통신 기능을 이용하여, 문자 과금 없이 사람들과 메시지를 주고받을 수 있는 애플리케이션이다. 스마트폰 대중화 이 후 기존 인스턴트 메신저 앱의 번거로운 친구 추가 절차 없이, 스마트폰 주소록의 전 화번호만으로 손쉽게 메시지를 주고받을 수 있는 것이 특징이다.\",\n",
        "    n_wrong=3\n",
        ")"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/site-packages/transformers/tokenization_utils_base.py:2227: UserWarning: `max_length` is ignored when `padding`=`True`.\n",
            "  warnings.warn(\"`max_length` is ignored when `padding`=`True`.\")\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('스마트폰의 데이터 통신 기능을 이용하여, 문자 과금 없이 사람들과 메시지를 주고받을 수 있는 애플리케이션 이름은?',\n",
              " ['텔레그램', '챗온', '디스코드'])"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "q7ToKtYlYEjV",
        "outputId": "db208e9a-4e6e-462e-bfd9-e1824f85b90a"
      },
      "source": [
        "qg(\n",
        "    [\"토트넘\", \"손흥민\", \"인스타그램\"],\n",
        "    \"‘2020년 더 베스트 국제축구연맹(FIFA) 풋볼 어워드’에서 FIFA 푸스카스를 수상한 잉글랜드 프로축구 1부리그 프리미어리 그(EPL) 소속 토트넘 홋스퍼 FC의 손흥민이 기쁜 마음을 드러냈다. 푸스카스는 1년간 전 세계 축구경기에 서 나온 골 중 가장 멋진 골을 뽑는다. 손흥민은 스위스 취리히 소재 FIFA 본부에서 온라인으로 열린 ‘2020년 더 베스트 FIFA 풋볼 어워드’ 시 상식에서 푸스카스를 받았다. 손흥민의 이번 수상은 한국 선수로는  최초이자 아시아에서는 2016년 모하메 드 파이즈 수브리(말레이시아)에 이어 두 번째다. 상을 받은 손흥민은 이날 오전 인스타그램에 “아주 특별한 밤이었다. 저를 지지해주고 제게 투표해 주어서 감사하다”며 셀 프 카메라가 담긴 사진 한 장을 게시했 다. 공개된 사진 속 손흥민은 환한 미소와 엄지를 들어 보이고 있 다. 여기에 손흥민은 이 순간을 절대 잊 지 않겠다고 덧붙였다.  앞서 손흥민은 지난해 12월8일 번리 FC와 가진 EPL 경기에서 환상적인 골을 터뜨 렸다. 당시 손흥민은 토트넘 진영에서 얀 베르통언(벨기에)의 패 스를 받고 공을 잡고 약 70ｍ를 혼자 내달리며 무려 번리 선수 6명을 따돌린 뒤 페널티 지역에서 오른발  슈팅으로 골망을 흔들었다. 이후 이 골은 EPL ‘12월의 골’을 시작으로 영국 공영방송 BBC의 ‘올해의 골’, 영국 스포츠 매체 디 애슬레틱의 ‘올해의  골’에 이어 EPL 사무국이 선정하는 2019∼20시즌 ‘올해의 골’ 등으로 선정되며 최고의 골로 인정받은 바 있다.\",\n",
        "    n_wrong=2\n",
        ")"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/site-packages/transformers/tokenization_utils_base.py:2227: UserWarning: `max_length` is ignored when `padding`=`True`.\n",
            "  warnings.warn(\"`max_length` is ignored when `padding`=`True`.\")\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(\"손흥민은 2020년 더 베스트 국제축구연맹(FIFA) 풋볼 어워드'에서 FIFA 푸스카스를 수상한 잉글랜드 프로축구 1부리그 프리미어리 그(EPL) 소속 팀은 어디야?\",\n",
              "  ['이즐링턴', '웸블리']),\n",
              " ('누가 ‘2020년 더 베스트 국제축구연맹(FIFA) 풋볼 어워드’에서 FIFA 푸스카스를 수상했어?', ['지동원', '구자철']),\n",
              " ('손흥민은 셀프 카메라가 담긴 사진 한 장을 어디에 올렸어?', ['트위터', '페이스북'])]"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KMx5vOCEYF6l",
        "outputId": "46e54f84-6540-4f1f-cce2-bbd24cd38ead"
      },
      "source": [
        "qg(\"포즈(pose·자세분석) API\",\n",
        "   \"카카오 인공지능(AI) 연구개발 자회사 카카오브레인이 AI 솔루션을 첫 상품화했다. 카카오는 카카오브레인 '포즈(pose·자세분석) API'를 유료 공개한다고 24일 밝혔다. 카카오브레인이 AI 기술을 유료 API를 공개하는 것은 처음이다. 공개하자마자 외부 문의가 쇄도한다. 포즈는 AI 비전(VISION, 영상·화면분석) 분야 중 하나다. 카카오브레인 포즈 API는 이미지나 영상을 분석해 사람 자세를 추출하는 기능을 제공한다.\",n_wrong=3)"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/site-packages/transformers/tokenization_utils_base.py:2227: UserWarning: `max_length` is ignored when `padding`=`True`.\n",
            "  warnings.warn(\"`max_length` is ignored when `padding`=`True`.\")\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('카카오브레인이 처음 공개하는 AI 기술은 무엇인가?', [])"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DKF3WDr6YeK1"
      },
      "source": [
        "와아아ㅏ아아ㅏ 가상환경에서는 된다!!!!!!!!!!!!!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jbwRftA2YouU",
        "outputId": "fa266cf8-fc0f-4db1-8175-cabc8acade5a"
      },
      "source": [
        "qg('농협카드 전화번호는 어떻게 되나요?',\n",
        "   '카드사별 전화번호는 아래 지식을 참고하시기 바랍니다. [링크] 789. 카드사별 전화번호',n_wrong=3)"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/site-packages/transformers/tokenization_utils_base.py:2227: UserWarning: `max_length` is ignored when `padding`=`True`.\n",
            "  warnings.warn(\"`max_length` is ignored when `padding`=`True`.\")\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('카드사별 전화번호는 뭐야?', [])"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gOB08rBGaUw7",
        "outputId": "e0c76270-ad60-4f6f-9ac4-2a5c1aecfcc0"
      },
      "source": [
        "qg('5월1일 근로자의 날은 ATM 수수료가 휴일기준으로 적용되나요?','임시공휴일, 근로자의날(5/1) ATM 수수료는 평일이면 평일기준, 휴일이면 휴일기준으로 해당일에 따라 달리 적용됩니다.',n_wrong=3)"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/site-packages/transformers/tokenization_utils_base.py:2227: UserWarning: `max_length` is ignored when `padding`=`True`.\n",
            "  warnings.warn(\"`max_length` is ignored when `padding`=`True`.\")\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('ATM 수수료는 언제 나와?', [])"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dYti7QQzfUMq"
      },
      "source": [
        "df = pd.read_csv('test.csv')"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "g8MM3Znqgt_O",
        "outputId": "95445c94-5b2a-47ce-d304-cdfb2d15f965"
      },
      "source": [
        "df"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>answer</th>\n",
              "      <th>question</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>내 오피스텔 얼마야?</td>\n",
              "      <td>하나은행의 365일 24시간 이용 가능한 자산관리서비스예요. 자산 분석을 통해 금융...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>대출 가입</td>\n",
              "      <td>금리 및 한도는 대출 신청을 통해 확인이 가능해요. 하나원큐 대출 상품가입에서 원하...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        answer                                           question\n",
              "0  내 오피스텔 얼마야?  하나은행의 365일 24시간 이용 가능한 자산관리서비스예요. 자산 분석을 통해 금융...\n",
              "1        대출 가입  금리 및 한도는 대출 신청을 통해 확인이 가능해요. 하나원큐 대출 상품가입에서 원하..."
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eo7M-Mk_hHQ6"
      },
      "source": [
        "df['qg_question'] = None"
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wSwzTmg6gu8Z",
        "outputId": "c60e5632-badd-4254-e2e8-b00d18dcf8c4"
      },
      "source": [
        "for i in range(len(df)):\n",
        "  df['qg_question'][i] = qg(df['answer'][i],df['question'][i])"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/site-packages/transformers/tokenization_utils_base.py:2227: UserWarning: `max_length` is ignored when `padding`=`True`.\n",
            "  warnings.warn(\"`max_length` is ignored when `padding`=`True`.\")\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "QkfrPNdahPOs",
        "outputId": "d10c69f5-81e6-4322-8929-6df278831678"
      },
      "source": [
        "df"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>answer</th>\n",
              "      <th>question</th>\n",
              "      <th>qg_question</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>내 오피스텔 얼마야?</td>\n",
              "      <td>하나은행의 365일 24시간 이용 가능한 자산관리서비스예요. 자산 분석을 통해 금융...</td>\n",
              "      <td>하나은행 자산관리서비스는 어떻게 이용 가능해?</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>대출 가입</td>\n",
              "      <td>금리 및 한도는 대출 신청을 통해 확인이 가능해요. 하나원큐 대출 상품가입에서 원하...</td>\n",
              "      <td>금리 및 한도는 무엇을 통해 확인할 수 있어?</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        answer  ...                qg_question\n",
              "0  내 오피스텔 얼마야?  ...  하나은행 자산관리서비스는 어떻게 이용 가능해?\n",
              "1        대출 가입  ...  금리 및 한도는 무엇을 통해 확인할 수 있어?\n",
              "\n",
              "[2 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    }
  ]
}