PARROT.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z8V22C8x2nt_"
      },
      "source": [
        "# **How to Paraphrase text in Python with PARROT**\n",
        "\n",
        "Chanin Nantasenamat\n",
        "\n",
        "[*Coding Professor YouTube channel*](https://www.youtube.com/channel/UCJzlfIoF8nmWqJIv_iWQVRw)\n",
        "\n",
        "[*Data Professor YouTube channel*](http://youtube.com/dataprofessor)\n",
        "\n",
        "<a href=\"https://github.com/PrithivirajDamodaran/Parrot\"><img width=\"150\" src=\"https://github.com/PrithivirajDamodaran/Parrot/raw/main/images/Logo.png\"></a>\n",
        "\n",
        "---\n",
        "\n",
        "🔴 **Support my work:**\n",
        "[![Buy me a coffee](https://img.shields.io/badge/Buy%20me%20a%20coffee--yellow.svg?logo=buy-me-a-coffee&logoColor=orange&style=social)](https://www.buymeacoffee.com/dataprofessor)\n",
        "\n",
        "🟠 **Learn Data Science for FREE:**\n",
        "[![YouTube](https://img.shields.io/youtube/channel/subscribers/UCV8e2g4IWQqK71bbzGDEI4Q?style=social)](http://youtube.com/dataprofessor)\n",
        "[![Medium](https://img.shields.io/badge/Medium-12100E?style=for-the-badge&logo=medium&logoColor=white&style=social)](https://medium.com/@chanin.nantasenamat)\n",
        "[![GitHub](https://img.shields.io/badge/GitHub-100000?style=for-the-badge&style=social&logo=github&logoColor=white)](https://github.com/dataprofessor/)\n",
        "[![Newsletter](https://img.shields.io/badge/Newsletter-3A8EED?style=for-the-badge&style=social&logoColor=white)](http://newsletter.dataprofessor.org/)\n",
        "[![DataProfessor](https://img.shields.io/badge/Data-Professor-3A8EED?style=for-the-badge&style=social&logoColor=white)](http://dataprofessor.org/)\n",
        "\n",
        "🟢 **Learn Python and R for FREE:**\n",
        "[![Python](https://img.shields.io/badge/Python-3776AB?style=for-the-badge&style=social&logo=python&logoColor=white)](https://www.youtube.com/playlist?list=PL2WsO1N8GK8vMMPQaux9PZaAXBGV7absc)\n",
        "[![R](https://img.shields.io/badge/R-276DC3?style=for-the-badge&style=social&logo=r&logoColor=white)](https://www.youtube.com/playlist?list=PL2WsO1N8GK8v9xaNwbR1tiGH9lO4epcjg)\n",
        "\n",
        "🔵 **Connect with me:**\n",
        "[![Follow](https://img.shields.io/twitter/follow/thedataprof?style=social)](https://www.twitter.com/thedataprof)\n",
        "[![LinkedIn](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&style=social&logo=linkedin&logoColor=white)](https://www.linkedin.com/company/dataprofessor/)\n",
        "[![Facebook](https://img.shields.io/badge/Facebook-1877F2?style=for-the-badge&style=social&logo=facebook&logoColor=white)](http://facebook.com/dataprofessor/)\n",
        "[![Instagram](https://img.shields.io/badge/Instagram-E4405F?style=for-the-badge&style=social&logo=instagram&logoColor=white)](https://www.instagram.com/data.professor/)\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JeObOANOHSZ8",
        "outputId": "e90df321-a5bd-4207-8a2a-03af1f65a54f"
      },
      "source": [
        "! pip install git+https://github.com/PrithivirajDamodaran/Parrot.git"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting git+https://github.com/PrithivirajDamodaran/Parrot.git\n",
            "  Cloning https://github.com/PrithivirajDamodaran/Parrot.git to /tmp/pip-req-build-nf5gujqq\n",
            "  Running command git clone -q https://github.com/PrithivirajDamodaran/Parrot.git /tmp/pip-req-build-nf5gujqq\n",
            "Collecting transformers\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/b0/9e/5b80becd952d5f7250eaf8fc64b957077b12ccfe73e9c03d37146ab29712/transformers-4.6.0-py3-none-any.whl (2.3MB)\n",
            "\u001b[K     |████████████████████████████████| 2.3MB 3.9MB/s \n",
            "\u001b[?25hCollecting sentencepiece\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/f5/99/e0808cb947ba10f575839c43e8fafc9cc44e4a7a2c8f79c60db48220a577/sentencepiece-0.1.95-cp37-cp37m-manylinux2014_x86_64.whl (1.2MB)\n",
            "\u001b[K     |████████████████████████████████| 1.2MB 33.4MB/s \n",
            "\u001b[?25hCollecting python-Levenshtein\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/2a/dc/97f2b63ef0fa1fd78dcb7195aca577804f6b2b51e712516cc0e902a9a201/python-Levenshtein-0.12.2.tar.gz (50kB)\n",
            "\u001b[K     |████████████████████████████████| 51kB 3.8MB/s \n",
            "\u001b[?25hCollecting sentence-transformers\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/14/9d/abacb6f7bb63df39285c55bb51b6403a7fd93ac2aea48b01f6215175446c/sentence-transformers-1.1.1.tar.gz (81kB)\n",
            "\u001b[K     |████████████████████████████████| 81kB 6.6MB/s \n",
            "\u001b[?25hCollecting fuzzywuzzy\n",
            "  Downloading https://files.pythonhosted.org/packages/43/ff/74f23998ad2f93b945c0309f825be92e04e0348e062026998b5eefef4c33/fuzzywuzzy-0.18.0-py2.py3-none-any.whl\n",
            "Requirement already satisfied: importlib-metadata; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from transformers->parrot==1.0) (4.0.1)\n",
            "Collecting huggingface-hub==0.0.8\n",
            "  Downloading https://files.pythonhosted.org/packages/a1/88/7b1e45720ecf59c6c6737ff332f41c955963090a18e72acbcbeac6b25e86/huggingface_hub-0.0.8-py3-none-any.whl\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from transformers->parrot==1.0) (2.23.0)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers->parrot==1.0) (2019.12.20)\n",
            "Collecting sacremoses\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/75/ee/67241dc87f266093c533a2d4d3d69438e57d7a90abb216fa076e7d475d4a/sacremoses-0.0.45-py3-none-any.whl (895kB)\n",
            "\u001b[K     |████████████████████████████████| 901kB 42.7MB/s \n",
            "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.7/dist-packages (from transformers->parrot==1.0) (4.41.1)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from transformers->parrot==1.0) (1.19.5)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from transformers->parrot==1.0) (3.0.12)\n",
            "Collecting tokenizers<0.11,>=0.10.1\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/ae/04/5b870f26a858552025a62f1649c20d29d2672c02ff3c3fb4c688ca46467a/tokenizers-0.10.2-cp37-cp37m-manylinux2010_x86_64.whl (3.3MB)\n",
            "\u001b[K     |████████████████████████████████| 3.3MB 32.1MB/s \n",
            "\u001b[?25hRequirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from transformers->parrot==1.0) (20.9)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from python-Levenshtein->parrot==1.0) (56.1.0)\n",
            "Requirement already satisfied: torch>=1.6.0 in /usr/local/lib/python3.7/dist-packages (from sentence-transformers->parrot==1.0) (1.8.1+cu101)\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.7/dist-packages (from sentence-transformers->parrot==1.0) (0.9.1+cu101)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.7/dist-packages (from sentence-transformers->parrot==1.0) (0.22.2.post1)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.7/dist-packages (from sentence-transformers->parrot==1.0) (1.4.1)\n",
            "Requirement already satisfied: nltk in /usr/local/lib/python3.7/dist-packages (from sentence-transformers->parrot==1.0) (3.2.5)\n",
            "Requirement already satisfied: typing-extensions>=3.6.4; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from importlib-metadata; python_version < \"3.8\"->transformers->parrot==1.0) (3.7.4.3)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata; python_version < \"3.8\"->transformers->parrot==1.0) (3.4.1)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->transformers->parrot==1.0) (3.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->transformers->parrot==1.0) (2020.12.5)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->transformers->parrot==1.0) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->transformers->parrot==1.0) (2.10)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers->parrot==1.0) (1.15.0)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers->parrot==1.0) (8.0.0)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers->parrot==1.0) (1.0.1)\n",
            "Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->transformers->parrot==1.0) (2.4.7)\n",
            "Requirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.7/dist-packages (from torchvision->sentence-transformers->parrot==1.0) (7.1.2)\n",
            "Building wheels for collected packages: parrot, python-Levenshtein, sentence-transformers\n",
            "  Building wheel for parrot (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for parrot: filename=parrot-1.0-cp37-none-any.whl size=8685 sha256=49e66a013d09f3213c96db0188d324b04acfc5c3ece9920dc0dec8007427fb50\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-m8n3lmxg/wheels/96/16/2c/b241910909ea2fc05552298ed25a2b1383f369c672f8aee255\n",
            "  Building wheel for python-Levenshtein (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for python-Levenshtein: filename=python_Levenshtein-0.12.2-cp37-cp37m-linux_x86_64.whl size=149809 sha256=97e431b7ab8563d408aa57c55ca439e0872fba820aafdf1c451a64bd355c47bb\n",
            "  Stored in directory: /root/.cache/pip/wheels/b3/26/73/4b48503bac73f01cf18e52cd250947049a7f339e940c5df8fc\n",
            "  Building wheel for sentence-transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sentence-transformers: filename=sentence_transformers-1.1.1-cp37-none-any.whl size=123338 sha256=aec9dad048bd548d6b80eeafa24fc1ed919676dd12e71f8646d1015261dd35f0\n",
            "  Stored in directory: /root/.cache/pip/wheels/5e/89/29/45e45adc162b50f97f71801e8b07947c9cfe2b3ae7dbf37896\n",
            "Successfully built parrot python-Levenshtein sentence-transformers\n",
            "Installing collected packages: huggingface-hub, sacremoses, tokenizers, transformers, sentencepiece, python-Levenshtein, sentence-transformers, fuzzywuzzy, parrot\n",
            "Successfully installed fuzzywuzzy-0.18.0 huggingface-hub-0.0.8 parrot-1.0 python-Levenshtein-0.12.2 sacremoses-0.0.45 sentence-transformers-1.1.1 sentencepiece-0.1.95 tokenizers-0.10.2 transformers-4.6.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "82aBk31THVG1"
      },
      "source": [
        "# Import libraries\n",
        "from parrot import Parrot\n",
        "import torch\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M8jkvnL2HlY4"
      },
      "source": [
        "# For reproducibility\n",
        "def random_state(seed):\n",
        "  torch.manual_seed(seed)\n",
        "  if torch.cuda.is_available():\n",
        "    torch.cuda.manual_seed_all(seed)\n",
        "\n",
        "random_state(1234)"
      ],
      "execution_count": 3,
      "outputs": []
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        "#Init models (make sure you init ONLY once if you integrate this to your code)\n",
        "parrot = Parrot(model_tag=\"prithivida/parrot_paraphraser_on_T5\", use_gpu=False)"
      ],
      "execution_count": 4,
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    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g_7ZwlzNHoSC"
      },
      "source": [
        "phrases = [\"What's the most delicious papayas?\"]"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hpfkoa3qHt5M",
        "outputId": "d42434c8-15f2-4bbc-ec2b-be66dc3823f4"
      },
      "source": [
        "for phrase in phrases:\n",
        "  print(\"-\"*100)\n",
        "  print(\"Input_phrase: \", phrase)\n",
        "  print(\"-\"*100)\n",
        "  para_phrases = parrot.augment(input_phrase=phrase)\n",
        "  for para_phrase in para_phrases:\n",
        "   print(para_phrase)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "----------------------------------------------------------------------------------------------------\n",
            "Input_phrase:  What's the most delicious papayas?\n",
            "----------------------------------------------------------------------------------------------------\n",
            "(\"what's the best papaya to eat?\", 29)\n",
            "('which are the best papayas?', 27)\n",
            "('what is your most delicious papaya?', 19)\n",
            "('list the most delicious papayas?', 16)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MOZC5jaMH2L-"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}