Himani/Milestone3/BERT_passage.ipynb

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      "source": [
        "import pandas as pd\n",
        "import numpy as np \n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "import json"
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        "!pip install transformers==4.27.4\n",
        "!pip install wandb\n",
        "!pip install datasets\n",
        "!pip install bert_score\n",
        "!pip install evaluate\n",
        "!pip install accelerate\n",
        "!pip install gradio --upgrade\n",
        "!pip install --upgrade torch\n",
        "!pip install sentencepiece"
      ],
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            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers==4.27.4)\n",
            "  Downloading tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n",
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            "Installing collected packages: tokenizers, huggingface-hub, transformers\n",
            "Successfully installed huggingface-hub-0.14.1 tokenizers-0.13.3 transformers-4.27.4\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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            "  Downloading torch-2.0.1-cp310-cp310-manylinux1_x86_64.whl (619.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m619.9/619.9 MB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch) (3.12.0)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch) (4.5.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch) (1.11.1)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch) (3.1)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch) (3.1.2)\n",
            "Collecting nvidia-cuda-nvrtc-cu11==11.7.99 (from torch)\n",
            "  Downloading nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl (21.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.0/21.0 MB\u001b[0m \u001b[31m48.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting nvidia-cuda-runtime-cu11==11.7.99 (from torch)\n",
            "  Downloading nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl (849 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m849.3/849.3 kB\u001b[0m \u001b[31m50.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting nvidia-cuda-cupti-cu11==11.7.101 (from torch)\n",
            "  Downloading nvidia_cuda_cupti_cu11-11.7.101-py3-none-manylinux1_x86_64.whl (11.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m11.8/11.8 MB\u001b[0m \u001b[31m66.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting nvidia-cudnn-cu11==8.5.0.96 (from torch)\n",
            "  Downloading nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl (557.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m557.1/557.1 MB\u001b[0m \u001b[31m2.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting nvidia-cublas-cu11==11.10.3.66 (from torch)\n",
            "  Downloading nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl (317.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m317.1/317.1 MB\u001b[0m \u001b[31m2.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting nvidia-cufft-cu11==10.9.0.58 (from torch)\n",
            "  Downloading nvidia_cufft_cu11-10.9.0.58-py3-none-manylinux1_x86_64.whl (168.4 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m168.4/168.4 MB\u001b[0m \u001b[31m5.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting nvidia-curand-cu11==10.2.10.91 (from torch)\n",
            "  Downloading nvidia_curand_cu11-10.2.10.91-py3-none-manylinux1_x86_64.whl (54.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m54.6/54.6 MB\u001b[0m \u001b[31m9.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting nvidia-cusolver-cu11==11.4.0.1 (from torch)\n",
            "  Downloading nvidia_cusolver_cu11-11.4.0.1-2-py3-none-manylinux1_x86_64.whl (102.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m102.6/102.6 MB\u001b[0m \u001b[31m8.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting nvidia-cusparse-cu11==11.7.4.91 (from torch)\n",
            "  Downloading nvidia_cusparse_cu11-11.7.4.91-py3-none-manylinux1_x86_64.whl (173.2 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m173.2/173.2 MB\u001b[0m \u001b[31m6.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting nvidia-nccl-cu11==2.14.3 (from torch)\n",
            "  Downloading nvidia_nccl_cu11-2.14.3-py3-none-manylinux1_x86_64.whl (177.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m177.1/177.1 MB\u001b[0m \u001b[31m7.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting nvidia-nvtx-cu11==11.7.91 (from torch)\n",
            "  Downloading nvidia_nvtx_cu11-11.7.91-py3-none-manylinux1_x86_64.whl (98 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m98.6/98.6 kB\u001b[0m \u001b[31m11.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch) (2.0.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch) (67.7.2)\n",
            "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch) (0.40.0)\n",
            "Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch) (3.25.2)\n",
            "Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch) (16.0.3)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch) (2.1.2)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch) (1.3.0)\n",
            "Installing collected packages: nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, nvidia-cusolver-cu11, nvidia-cudnn-cu11, torch\n",
            "  Attempting uninstall: torch\n",
            "    Found existing installation: torch 2.0.0+cu118\n",
            "    Uninstalling torch-2.0.0+cu118:\n",
            "      Successfully uninstalled torch-2.0.0+cu118\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torchaudio 2.0.1+cu118 requires torch==2.0.0, but you have torch 2.0.1 which is incompatible.\n",
            "torchdata 0.6.0 requires torch==2.0.0, but you have torch 2.0.1 which is incompatible.\n",
            "torchtext 0.15.1 requires torch==2.0.0, but you have torch 2.0.1 which is incompatible.\n",
            "torchvision 0.15.1+cu118 requires torch==2.0.0, but you have torch 2.0.1 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 torch-2.0.1\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting sentencepiece\n",
            "  Downloading sentencepiece-0.1.99-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m22.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: sentencepiece\n",
            "Successfully installed sentencepiece-0.1.99\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#text preprocessing\n",
        "def parse_spoiler_for_correct_spoiler_positions(df):\n",
        "    spoiler = []        \n",
        "    for sp in df['spoilerPositions']:\n",
        "        if len(sp) <=1:\n",
        "          df['spoilerPositions'] = [[[4, 37],[4, 222]]]  # this data is manually checked and assigned because it was throwing error\n",
        "        else:\n",
        "          start,end = sp[0],sp[1]\n",
        "          spoiler.append(df['targetParagraphs'][start[0]][start[1]:end[1]])\n",
        "        \n",
        "    return spoiler"
      ],
      "metadata": {
        "id": "R3IUDIjfvwAw"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#text preprocessing\n",
        "def find_token_positions(x):    \n",
        "    token_position = []\n",
        "    for position in x['spoilerPositions']:\n",
        "        if len(position) <2:\n",
        "          print(\"format of data is not right for uuid\", x['uuid'])\n",
        "        else:\n",
        "          index = 0\n",
        "          start,end = position\n",
        "          \n",
        "          for idx,element in enumerate([x['targetTitle']] + x['targetParagraphs']):\n",
        "              if idx==start[0]+1:\n",
        "                  # because character is starting at given index +1\n",
        "                  end_index = index + end[1]\n",
        "                  start_index = index+start[1]\n",
        "                  token_position.append([start_index,end_index])\n",
        "                  break\n",
        "              if idx==0:\n",
        "                  index+=len(element)+3\n",
        "              else:\n",
        "                  index+=len(element)+1\n",
        "        \n",
        "    return token_position"
      ],
      "metadata": {
        "id": "9-9PF2lGvlIu"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#formatting dataframe columns accroding to requirements\n",
        "def formatted_df(df):\n",
        "  \n",
        "  df['spoilerParsed'] = df.apply(parse_spoiler_for_correct_spoiler_positions,1)\n",
        "  df['combinedParagraphs'] = df['targetParagraphs'].apply(lambda x:\" \".join(x),1)\n",
        "  df.combinedParagraphs = df.targetTitle + \" - \" + df.combinedParagraphs\n",
        "  df['tokenPosition'] = df.apply(find_token_positions,1) \n",
        "  df['tags'] = df.tags.apply(lambda x:x[0],1)\n",
        "  df['postText'] = df.postText.apply(lambda x:x[0],1)\n",
        "  df['label'] = df['tags'].map({\"phrase\":0,\"passage\":1,\"multi\":2})\n",
        "  return df\n",
        "    "
      ],
      "metadata": {
        "id": "6vVDe5elwMvb"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data_path = './train.jsonl'\n",
        "df = pd.read_json(data_path, lines=True)\n",
        "df_valid = pd.read_json(\"./validation.jsonl\", lines=True)\n",
        "formatted_df(df)\n",
        "formatted_df(df_valid)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "bgDrve7fv8Gg",
        "outputId": "1a611ae9-a8fb-423e-dabc-4940213f41d6"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                     uuid                           postId  \\\n",
              "0    6dc7ddef-4e8e-4a6b-9296-526377518071  800048986762423_885081814925806   \n",
              "1    435b24de-56f6-4d4e-9c38-54b8e0630aac                           4jp20e   \n",
              "2    8091ba93-6376-473a-9117-01d6cf0507e4               857559227384160256   \n",
              "3    8b713277-0e5b-4873-a216-b650f21f3b4c               389091583213453312   \n",
              "4    a2f91b65-c36c-481f-92b1-2fc77d6411fc               744740593046274048   \n",
              "..                                    ...                              ...   \n",
              "795  1189d343-42eb-47e7-8395-ff978a683875               428006164904034305   \n",
              "796  7912282b-137b-4098-875d-8ad9f19354a8               806153730206892032   \n",
              "797  1fdf71e8-ec14-4c3b-a7c5-ca678c6f8ccb               847331053991813120   \n",
              "798  17f6b540-cf8d-4ddf-8321-1c9ce2315d71               788056531304583168   \n",
              "799  89dcad77-d8ad-4705-8676-717b26fda2ad               388308677494444032   \n",
              "\n",
              "                                              postText postPlatform  \\\n",
              "0    Five Nights at Freddy’s Sequel Delayed for Wei...     Facebook   \n",
              "1    Why Arizona Sheriff Joe Arpaio’s fate could ha...       reddit   \n",
              "2    Here’s how much you should be tipping your hai...      Twitter   \n",
              "3           \"Harry Potter\" alums reunite for new movie      Twitter   \n",
              "4    A man swallowed a microSD card and you won't b...      Twitter   \n",
              "..                                                 ...          ...   \n",
              "795  This is what happens when you leave a hotel cl...      Twitter   \n",
              "796  This Texas GOP elector announces that he won't...      Twitter   \n",
              "797  This beauty queen cured her acne with one diet...      Twitter   \n",
              "798            WikiLeaks' Julian Assange Reported Dead      Twitter   \n",
              "799  Original \"Law &amp; Order: SVU\" cast member le...      Twitter   \n",
              "\n",
              "                                      targetParagraphs  \\\n",
              "0    [Five Nights at Freddy’s creator Scott Cawthon...   \n",
              "1    [© REUTERS/Laura Segall Maricopa County Sherif...   \n",
              "2    [Here’s how much you should be tipping your ha...   \n",
              "3    [The mythology of punk music's evolution can b...   \n",
              "4    [PetaPixel is one of my favorite blogs. The wr...   \n",
              "..                                                 ...   \n",
              "795  [Instead of encountering a mound of dirty towe...   \n",
              "796  [A Republican elector in Texas says he will no...   \n",
              "797  [Her inspirational journey is encouraging othe...   \n",
              "798  [On 16 October 2016, WikiLeaks posted a series...   \n",
              "799  [Richard Belzer is leaving \"Law & Order: SVU.\"...   \n",
              "\n",
              "                                           targetTitle  \\\n",
              "0    Five Nights at Freddy’s Sequel Delayed for Wei...   \n",
              "1    Why Arizona Sheriff Joe Arpaio’s fate could ha...   \n",
              "2    Here’s how much you should be tipping your hai...   \n",
              "3    Alan Rickman & Rupert Grint On 'CBGB,' Reuniti...   \n",
              "4    Man swallowed a microSD card and you won't bel...   \n",
              "..                                                 ...   \n",
              "795  This Is What Happens When You Leave A Hotel Cl...   \n",
              "796  Texas GOP elector announces he won't vote for ...   \n",
              "797  UK beauty queen cured her severe acne with one...   \n",
              "798  WikiLeaks’ Julian Assange Isn’t Dead, Just Off...   \n",
              "799  Richard Belzer Leaving 'Law & Order: SVU': Mun...   \n",
              "\n",
              "                                     targetDescription  \\\n",
              "0    Five Nights at Freddy's creator Scott Cawthon ...   \n",
              "1    <p>A single word — \"intentionally\" — could tra...   \n",
              "2    Remembering how much you’re supposed to tip an...   \n",
              "3    The mythology of punk music's evolution can be...   \n",
              "4    PetaPixel is one of my favorite blogs. The wri...   \n",
              "..                                                 ...   \n",
              "795  Instead of encountering a mound of dirty towel...   \n",
              "796  The Electoral College vote for president on De...   \n",
              "797  A beauty pageant contestant has taken to Insta...   \n",
              "798  A series of mysterious tweets from WikiLeaks l...   \n",
              "799  Richard Belzer is leaving \"Law & Order: SVU.\" ...   \n",
              "\n",
              "                                        targetKeywords  \\\n",
              "0                                                 None   \n",
              "1                                                 None   \n",
              "2                                                        \n",
              "3    Alan Rickman,Hilly Kristal,new rupert grint mo...   \n",
              "4                                                 None   \n",
              "..                                                 ...   \n",
              "795  givebackfilms,give back films,video,random act...   \n",
              "796  donald trump, texas, electoral college, faithl...   \n",
              "797  acne, Skincare, beauty, Beauty pageant, Dermat...   \n",
              "798       dead man's switch, julian assange, wikileaks   \n",
              "799  TV Canada,richard belzer leaving law and order...   \n",
              "\n",
              "                                           targetMedia  \\\n",
              "0    [https://gamerant.com/wp-content/uploads/five-...   \n",
              "1    [https://archive.is/0eGBT/bbf6d79b366fc7e75b8b...   \n",
              "2                                                 None   \n",
              "3    [http://s.m.huffpost.com/assets/Logo_Huffingto...   \n",
              "4    [https://cdn0.vox-cdn.com/uploads/chorus_image...   \n",
              "..                                                 ...   \n",
              "795  [http://s.m.huffpost.com/assets/Logo_Huffingto...   \n",
              "796                                               None   \n",
              "797                                               None   \n",
              "798  [http://static.snopes.com/app/themes/snopes-th...   \n",
              "799  [http://s.m.huffpost.com/assets/Logo_Huffingto...   \n",
              "\n",
              "                                             targetUrl  \\\n",
              "0    https://gamerant.com/five-nights-at-freddys-se...   \n",
              "1                             https://archive.is/0eGBT   \n",
              "2                                                 None   \n",
              "3                               http://huff.to/1ccNwKJ   \n",
              "4    http://www.theverge.com/circuitbreaker/2016/6/...   \n",
              "..                                                 ...   \n",
              "795                             http://huff.to/1ebARdm   \n",
              "796                                               None   \n",
              "797                                               None   \n",
              "798                             http://trib.al/leR8lNw   \n",
              "799                             http://huff.to/19m7Itl   \n",
              "\n",
              "                                            provenance  \\\n",
              "0    {'source': 'anonymized', 'humanSpoiler': 'They...   \n",
              "1    {'source': 'anonymized', 'humanSpoiler': '\"Int...   \n",
              "2    {'source': 'anonymized', 'humanSpoiler': None,...   \n",
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              "..                                            ...      ...   \n",
              "795                          [[[3, 0], [3, 150]]]  passage   \n",
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              "797   [[[2, 144], [2, 158]], [[6, 56], [6, 124]]]    multi   \n",
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              "      <td>[Julian Assange’s internet link has been inten...</td>\n",
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              "      <td>Richard Belzer Leaving 'Law &amp; Order: SVU': Mun...</td>\n",
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              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f2c5b5c2-d89c-47a1-9bd4-39440dcaea35 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f2c5b5c2-d89c-47a1-9bd4-39440dcaea35');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import evaluate\n",
        "bleu = evaluate.load(\"bleu\",n=4)\n",
        "squad_metric = evaluate.load(\"squad\")\n",
        "meteor = evaluate.load(\"meteor\")"
      ],
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        "outputId": "3f08e934-c5ae-43e2-f1ad-eb46e3a9bf15"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
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          "metadata": {}
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        {
          "output_type": "stream",
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          "text": [
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n",
            "[nltk_data] Downloading package omw-1.4 to /root/nltk_data...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# **PASSAGE Generation Task!**\n",
        "from tqdm.auto import tqdm\n",
        "from transformers import AutoTokenizer, AutoModelForSequenceClassification\n",
        "import torch\n",
        "import nltk\n",
        "from nltk import sent_tokenize\n",
        "from itertools import chain\n",
        "\n",
        "nltk.download('punkt')\n",
        "bleu = evaluate.load(\"bleu\")\n",
        "squad_metric = evaluate.load(\"squad\")\n",
        "df_para = df_valid[df_valid.tags==\"passage\"][[\"uuid\",\"targetTitle\",\"postText\",\"targetParagraphs\",\"spoiler\",\"tokenPosition\"]].reset_index(drop=True)\n",
        "df_para[\"targetParagraphsWithTitle\"] = df_para.apply(lambda x: [x['targetTitle']] + x['targetParagraphs'] if x['targetTitle']!=x['postText'] else x['targetParagraphs'],1)\n",
        "df_para[\"answers\"] = df_para.apply(lambda x: {'text':x['spoiler'], \"answer_start\":[x['tokenPosition'][0][0]]},1)\n",
        "df_para[\"sents\"] = df_para.targetParagraphsWithTitle.apply(lambda x: list(chain.from_iterable([sent_tokenize(y) for y in x])),1)\n",
        "name = \"cross-encoder/ms-marco-TinyBERT-L-2-v2\"\n",
        "# name = \"cross-encoder/stsb-TinyBERT-L-4\"\n",
        "#name = \"cross-encoder/ms-marco-MiniLM-L-12-v2\"\n",
        "\n",
        "model = AutoModelForSequenceClassification.from_pretrained(name)\n",
        "tokenizer = AutoTokenizer.from_pretrained(name)\n",
        "\n",
        "best_paras = []\n",
        "model.eval()\n",
        "\n",
        "for ind, row in tqdm(df_para.iterrows(), total=len(df_para)):\n",
        "    paras = row['targetParagraphs']\n",
        "    query = [row['postText']]*len(paras)\n",
        "    features = tokenizer(query,paras,  padding=True, truncation=True, return_tensors=\"pt\")\n",
        "    \n",
        "    with torch.no_grad():\n",
        "        scores = [x.item() for x in model(**features).logits]\n",
        "    scores = list(zip(scores,paras))\n",
        "    scores.sort(reverse=True)\n",
        "    best_paras.append([x[1] for x in scores[:5]])\n",
        "best_sents = []\n",
        "\n",
        "for i in tqdm(range(len(best_paras))):\n",
        "    candidates = []\n",
        "    for p in best_paras[i][:1]:\n",
        "        candidates+=sent_tokenize(p)\n",
        "        \n",
        "    query  = [df_para.iloc[i][\"postText\"]]*len(candidates)\n",
        "    features = tokenizer(query, candidates,  padding=True, truncation=True, return_tensors=\"pt\")\n",
        "    \n",
        "\n",
        "    with torch.no_grad():\n",
        "        scores = [x.item() for x in model(**features).logits]\n",
        "    scores = list(zip(scores, candidates))\n",
        "    scores.sort(reverse=True)\n",
        "    best_sents.append(scores[0][1])\n",
        "theoretical_texts_squad = [{\"id\": ex[\"uuid\"], \"answers\": ex[\"answers\"]} for ind,ex in df_para.iterrows()]\n",
        "\n",
        "theoretical_texts = [i['answers']['text'][0] for ind,i in df_para.iterrows()] \n",
        "predictions = [sent for i,sent in enumerate(best_sents)]\n",
        "\n",
        "dataframe = pd.DataFrame({'actual_spoiler': theoretical_texts , 'gen_spoiler': predictions })\n"
      ],
      "metadata": {
        "colab": {
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          "height": 276,
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        "id": "EqGnwvHyvXPr",
        "outputId": "f3c88380-ef8c-4f56-a492-6eb61a328fd7"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n"
          ]
        },
        {
          "output_type": "display_data",
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        {
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    {
      "cell_type": "code",
      "source": [
        "predictions_squad = [{\"id\":df_para.iloc[i][\"uuid\"],\"prediction_text\":sent} for i,sent in enumerate(best_sents)]"
      ],
      "metadata": {
        "id": "ZOXH_JGP3a7G"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataframe\n"
      ],
      "metadata": {
        "id": "V81gS9sbwl_6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
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        "outputId": "2228bc3c-95c0-4544-9304-abc5ade2827f"
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      "execution_count": 9,
      "outputs": [
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              "                                        actual_spoiler  \\\n",
              "0    some of the plot elements are so disturbing th...   \n",
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              "..                                                 ...   \n",
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              "318  China is too quick to rebalance its services s...   \n",
              "319  the plant the dog was chewing on was deadly wa...   \n",
              "320  The video below shows the stunned cleaner init...   \n",
              "321  Julian Assange’s internet link has been intent...   \n",
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              "                                           gen_spoiler  \n",
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              "1                            He pooped a microSD card!  \n",
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              "3    After all, the feelings about the lack of a po...  \n",
              "4    Well, it couldn't have been any faker -- just ...  \n",
              "..                                                 ...  \n",
              "317  It became clearer and clearer that people had ...  \n",
              "318  Last week, the US House of Representatives hel...  \n",
              "319                   An hour later, the dog was dead.  \n",
              "320  Kyle and Josh from GiveBackFilms, a YouTube ch...  \n",
              "321  On 16 October 2016, WikiLeaks posted a series ...  \n",
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            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bleu.compute(predictions=best_sents, references=theoretical_texts)\n"
      ],
      "metadata": {
        "id": "85menAiFwovT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "76a9cef7-aa07-461b-d0e6-ca02b94ef10b"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'bleu': 0.13220037347064073,\n",
              " 'precisions': [0.22979678638941398,\n",
              "  0.11987226725620241,\n",
              "  0.10741687979539642,\n",
              "  0.10322752734062417],\n",
              " 'brevity_penalty': 1.0,\n",
              " 'length_ratio': 1.1297383876134544,\n",
              " 'translation_length': 8464,\n",
              " 'reference_length': 7492}"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "squad_metric.compute(predictions=predictions_squad, references=theoretical_texts_squad)\n"
      ],
      "metadata": {
        "id": "Q_Kev8GOwrMZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e2642a9b-596b-49c3-92cb-acfd26d9cb7d"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'exact_match': 4.658385093167702, 'f1': 20.633288343525965}"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "meteor.compute(predictions=best_sents, references=theoretical_texts)"
      ],
      "metadata": {
        "id": "WlOHHHRdwwDb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "53d27487-909d-4af3-e776-14c6632dab2d"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'meteor': 0.23401157283527552}"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    }
  ]
}