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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cYH27blqekE-"
      },
      "source": [
        "SPARSE RETRIEVAL"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C2NM0WlxeL3z",
        "colab": {
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        "!pip install -U beir"
      ],
      "execution_count": 1,
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        {
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          "name": "stdout",
          "text": [
            "Collecting beir\n",
            "  Downloading beir-0.2.3.tar.gz (52 kB)\n",
            "\u001b[K     |████████████████████████████████| 52 kB 1.2 MB/s \n",
            "\u001b[?25hCollecting sentence-transformers\n",
            "  Downloading sentence-transformers-2.1.0.tar.gz (78 kB)\n",
            "\u001b[K     |████████████████████████████████| 78 kB 6.7 MB/s \n",
            "\u001b[?25hCollecting pytrec_eval\n",
            "  Downloading pytrec_eval-0.5.tar.gz (15 kB)\n",
            "Collecting faiss_cpu\n",
            "  Downloading faiss_cpu-1.7.1.post2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (8.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 8.4 MB 43.1 MB/s \n",
            "\u001b[?25hCollecting elasticsearch\n",
            "  Downloading elasticsearch-7.15.1-py2.py3-none-any.whl (378 kB)\n",
            "\u001b[K     |████████████████████████████████| 378 kB 47.3 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tensorflow>=2.2.0 in /usr/local/lib/python3.7/dist-packages (from beir) (2.6.0)\n",
            "Collecting tensorflow-text\n",
            "  Downloading tensorflow_text-2.6.0-cp37-cp37m-manylinux1_x86_64.whl (4.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 4.4 MB 35.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tensorflow-hub in /usr/local/lib/python3.7/dist-packages (from beir) (0.12.0)\n",
            "Requirement already satisfied: keras~=2.6 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (2.6.0)\n",
            "Requirement already satisfied: astunparse~=1.6.3 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (1.6.3)\n",
            "Requirement already satisfied: flatbuffers~=1.12.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (1.12)\n",
            "Requirement already satisfied: tensorboard~=2.6 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (2.6.0)\n",
            "Requirement already satisfied: grpcio<2.0,>=1.37.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (1.41.0)\n",
            "Requirement already satisfied: termcolor~=1.1.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (1.1.0)\n",
            "Requirement already satisfied: h5py~=3.1.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (3.1.0)\n",
            "Requirement already satisfied: absl-py~=0.10 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (0.12.0)\n",
            "Requirement already satisfied: wheel~=0.35 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (0.37.0)\n",
            "Requirement already satisfied: typing-extensions~=3.7.4 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (3.7.4.3)\n",
            "Requirement already satisfied: tensorflow-estimator~=2.6 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (2.6.0)\n",
            "Requirement already satisfied: wrapt~=1.12.1 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (1.12.1)\n",
            "Requirement already satisfied: gast==0.4.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (0.4.0)\n",
            "Requirement already satisfied: opt-einsum~=3.3.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (3.3.0)\n",
            "Requirement already satisfied: six~=1.15.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (1.15.0)\n",
            "Requirement already satisfied: numpy~=1.19.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (1.19.5)\n",
            "Requirement already satisfied: clang~=5.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (5.0)\n",
            "Requirement already satisfied: protobuf>=3.9.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (3.17.3)\n",
            "Requirement already satisfied: google-pasta~=0.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (0.2.0)\n",
            "Requirement already satisfied: keras-preprocessing~=1.1.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.2.0->beir) (1.1.2)\n",
            "Requirement already satisfied: cached-property in /usr/local/lib/python3.7/dist-packages (from h5py~=3.1.0->tensorflow>=2.2.0->beir) (1.5.2)\n",
            "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.6->tensorflow>=2.2.0->beir) (1.8.0)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.6->tensorflow>=2.2.0->beir) (3.3.4)\n",
            "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.6->tensorflow>=2.2.0->beir) (1.0.1)\n",
            "Requirement already satisfied: google-auth<2,>=1.6.3 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.6->tensorflow>=2.2.0->beir) (1.35.0)\n",
            "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.6->tensorflow>=2.2.0->beir) (0.4.6)\n",
            "Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.6->tensorflow>=2.2.0->beir) (2.23.0)\n",
            "Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.6->tensorflow>=2.2.0->beir) (57.4.0)\n",
            "Requirement already satisfied: tensorboard-data-server<0.7.0,>=0.6.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.6->tensorflow>=2.2.0->beir) (0.6.1)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.7/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.6->tensorflow>=2.2.0->beir) (0.2.8)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.7/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.6->tensorflow>=2.2.0->beir) (4.7.2)\n",
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            "Installing collected packages: pyyaml, tokenizers, sacremoses, huggingface-hub, transformers, sentencepiece, tensorflow-text, sentence-transformers, pytrec-eval, faiss-cpu, elasticsearch, beir\n",
            "  Attempting uninstall: pyyaml\n",
            "    Found existing installation: PyYAML 3.13\n",
            "    Uninstalling PyYAML-3.13:\n",
            "      Successfully uninstalled PyYAML-3.13\n",
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-ypLvwb8euUd",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3d40f290-28ac-4706-c089-fc322486b5bb"
      },
      "source": [
        "import pathlib, os\n",
        "import time\n",
        "import pandas as pd\n",
        "from tqdm.notebook import tqdm\n",
        "from tqdm.autonotebook import trange\n",
        "from beir import util, LoggingHandler\n",
        "from beir.retrieval import models\n",
        "from beir.datasets.data_loader import GenericDataLoader\n",
        "from beir.retrieval.evaluation import EvaluateRetrieval\n",
        "from beir.retrieval.search.sparse import SparseSearch"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:5: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
            "  \"\"\"\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lx8P_Kv_h0km"
      },
      "source": [
        "def load(dataset):\n",
        "  hostname = 'localhost'\n",
        "  index_name = dataset\n",
        "  url = 'https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/{}.zip'.format(dataset)\n",
        "  out_dir = os.path.join(os.getcwd(), 'datasets')\n",
        "  data_path = util.download_and_unzip(url, out_dir)\n",
        "  return GenericDataLoader(data_path).load(split='test') # 'test', 'train', 'dev'"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DJemldWFh9ZH"
      },
      "source": [
        "def retrieve(corpus, queries, qrels, model_name, batch_size):\n",
        "  sparse_model = SparseSearch(models.SPARTA(model_name), batch_size=batch_size)\n",
        "  retriever_sp = EvaluateRetrieval(sparse_model)\n",
        "  results_sp = retriever_sp.retrieve(corpus, queries)\n",
        "  return retriever_sp.evaluate(qrels, results_sp, retriever_sp.k_values)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZmzKisVDiO0M"
      },
      "source": [
        "def evaluate(corpus, queries, qrels, model_name, batch_size):\n",
        "  ndcg, _map, recall, precision = retrieve(corpus, queries, qrels, model_name, batch_size)\n",
        "  c_map = 'MAP@10'\n",
        "  c_map_h = 'MAP@100'\n",
        "  c_map_t = 'MAP@1000'\n",
        "  c_ndcg = 'NDCG@10'\n",
        "  c_ndcg_h = 'NDCG@100'\n",
        "  c_ndcg_t = 'NDCG@1000'\n",
        "  c_pre = 'P@10'\n",
        "  c_pre_h = 'P@100'\n",
        "  c_pre_t = 'P@1000'\n",
        "  c_rec = 'Recall@10'\n",
        "  c_rec_h = 'Recall@100'\n",
        "  c_rec_t = 'Recall@1000'\n",
        "  eval_dict = {\n",
        "      c_map: [_map[c_map]], \n",
        "      c_map_h: [_map[c_map_h]],\n",
        "      c_map_t: [_map[c_map_t]],\n",
        "      c_ndcg: [ndcg[c_ndcg]], \n",
        "      c_ndcg_h: [ndcg[c_ndcg_h]],\n",
        "      c_ndcg_t: [ndcg[c_ndcg_t]],\n",
        "      c_pre: [precision[c_pre]], \n",
        "      c_pre_h: [precision[c_pre_h]],\n",
        "      c_pre_t: [precision[c_pre_t]],\n",
        "      c_rec: [recall[c_rec]],\n",
        "      c_rec_h: [recall[c_rec_h]],\n",
        "      c_rec_t: [recall[c_rec_t]]}\n",
        "  eval_df = pd.DataFrame(data=eval_dict)\n",
        "  eval_df.index = [model_name]\n",
        "  return eval_df"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_l9ru98yCRdr",
        "colab": {
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          "height": 145,
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        },
        "outputId": "174fdf0e-36a2-4b62-d455-4d85f50cc235"
      },
      "source": [
        "model_db = 'BeIR/sparta-msmarco-distilbert-base-v1'\n",
        "ag_corpus, ag_queries, ag_qrels = load('arguana')\n",
        "fq_corpus, fq_queries, fq_qrels = load('fiqa')"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "dcd1e95c5906416dbe9fe2a00e566632",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "/content/datasets/arguana.zip:   0%|          | 0.00/3.60M [00:00<?, ?iB/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "bb534aad219640a6a18bf48c133e6bd6",
              "version_minor": 0,
              "version_major": 2
            },
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              "  0%|          | 0/8674 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "372b0802e1db4c2883af8fd7e3729a72",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "/content/datasets/fiqa.zip:   0%|          | 0.00/17.1M [00:00<?, ?iB/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "2fbf1a291bd649eabd164bf905933789",
              "version_minor": 0,
              "version_major": 2
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        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VWzLV_VmXrTC"
      },
      "source": [
        "**TOUCHÉ** - [Homepage](https://webis.de/events/touche-20/) - [Paper](https://www.researchgate.net/publication/344371868_Overview_of_Touche_2020_Argument_Retrieval)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PRyckU4MXsC9"
      },
      "source": [
        "# tc_corpus, tc_queries, tc_qrels = load('webis-touche2020')\n",
        "# evaluate(tc_corpus, tc_queries, tc_qrels, model_db, 128)"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c_U2yfTIXsyP"
      },
      "source": [
        "**ARGUANA** - [Homepage](http://argumentation.bplaced.net/arguana/data) - [Paper](https://aclanthology.org/P18-1023.pdf)"
      ]
    },
    {
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      "source": [
        "**FIQA** - [Homepage](https://sites.google.com/view/fiqa/home) - [Paper](https://www.researchgate.net/publication/324629350_WWW'18_Open_Challenge_Financial_Opinion_Mining_and_Question_Answering)"
      ]
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              "                                         MAP@10  ...  Recall@1000\n",
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      "source": [
        "end of fun."
      ]
    }
  ]
}