Upload prepraring.ipynb

prepraring.ipynb

@@ -0,0 +1,430 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "501d0d55-8d15-463d-95cb-1f70d72de7fb",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--2023-12-30 12:56:11--  https://raw.githubusercontent.com/askplatypus/wikidata-simplequestions/master/annotated_wd_data_train_answerable.txt\n",
+      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
+      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
+      "HTTP request sent, awaiting response... 200 OK\n",
+      "Length: 1193868 (1,1M) [text/plain]\n",
+      "Saving to: ‘annotated_wd_data_train_answerable.txt’\n",
+      "\n",
+      "annotated_wd_data_t 100%[===================>]   1,14M  6,45MB/s    in 0,2s    \n",
+      "\n",
+      "2023-12-30 12:56:11 (6,45 MB/s) - ‘annotated_wd_data_train_answerable.txt’ saved [1193868/1193868]\n",
+      "\n",
+      "--2023-12-30 12:56:11--  https://raw.githubusercontent.com/askplatypus/wikidata-simplequestions/master/annotated_wd_data_valid_answerable.txt\n",
+      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.110.133, 185.199.111.133, ...\n",
+      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.\n",
+      "HTTP request sent, awaiting response... 200 OK\n",
+      "Length: 173187 (169K) [text/plain]\n",
+      "Saving to: ‘annotated_wd_data_valid_answerable.txt’\n",
+      "\n",
+      "annotated_wd_data_v 100%[===================>] 169,13K  --.-KB/s    in 0,09s   \n",
+      "\n",
+      "2023-12-30 12:56:12 (1,86 MB/s) - ‘annotated_wd_data_valid_answerable.txt’ saved [173187/173187]\n",
+      "\n",
+      "--2023-12-30 12:56:12--  https://raw.githubusercontent.com/askplatypus/wikidata-simplequestions/master/annotated_wd_data_test_answerable.txt\n",
+      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.108.133, 185.199.110.133, ...\n",
+      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.\n",
+      "HTTP request sent, awaiting response... 200 OK\n",
+      "Length: 345052 (337K) [text/plain]\n",
+      "Saving to: ‘annotated_wd_data_test_answerable.txt’\n",
+      "\n",
+      "annotated_wd_data_t 100%[===================>] 336,96K  --.-KB/s    in 0,1s    \n",
+      "\n",
+      "2023-12-30 12:56:12 (2,70 MB/s) - ‘annotated_wd_data_test_answerable.txt’ saved [345052/345052]\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "!wget -nc https://raw.githubusercontent.com/askplatypus/wikidata-simplequestions/master/annotated_wd_data_train_answerable.txt\n",
+    "!wget -nc https://raw.githubusercontent.com/askplatypus/wikidata-simplequestions/master/annotated_wd_data_valid_answerable.txt\n",
+    "!wget -nc https://raw.githubusercontent.com/askplatypus/wikidata-simplequestions/master/annotated_wd_data_test_answerable.txt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "73af4417-0637-4848-9d35-e734a685ebc4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/salnikov/.cache/pypoetry/virtualenvs/kgqa-signatures-J3ZJKtLx-py3.10/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import datasets \n",
+    "import numpy as np\n",
+    "import random\n",
+    "import logging\n",
+    "\n",
+    "np.random.seed(8)\n",
+    "random.seed(8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "6ffea0dd-3d28-416c-b7c3-c8dd73d5e304",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DatasetDict({\n",
+       "    train: Dataset({\n",
+       "        features: ['subject', 'property', 'object', 'question'],\n",
+       "        num_rows: 19481\n",
+       "    })\n",
+       "    valid: Dataset({\n",
+       "        features: ['subject', 'property', 'object', 'question'],\n",
+       "        num_rows: 2821\n",
+       "    })\n",
+       "    test: Dataset({\n",
+       "        features: ['subject', 'property', 'object', 'question'],\n",
+       "        num_rows: 5622\n",
+       "    })\n",
+       "})"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataset = datasets.DatasetDict()\n",
+    "for split, data_path in [\n",
+    "    (\"train\", \"annotated_wd_data_train_answerable.txt\"),\n",
+    "    (\"valid\", \"annotated_wd_data_valid_answerable.txt\"),\n",
+    "    (\"test\", \"annotated_wd_data_test_answerable.txt\"),\n",
+    "]:\n",
+    "    df = pd.read_csv(data_path, names=['subject', 'property', 'object', 'question'], sep='\\t')\n",
+    "    dataset[split] = datasets.Dataset.from_pandas(df)\n",
+    "\n",
+    "dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f7e71241",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import os.path\n",
+    "import pickle\n",
+    "import warnings\n",
+    "\n",
+    "from joblib import register_store_backend, numpy_pickle\n",
+    "from joblib._store_backends import FileSystemStoreBackend, CacheWarning\n",
+    "\n",
+    "\n",
+    "class FileSystemStoreBackendNoNumpy(FileSystemStoreBackend):\n",
+    "    NAME = \"no_numpy\"\n",
+    "\n",
+    "    def load_item(self, path, verbose=1, msg=None):\n",
+    "        \"\"\"Load an item from the store given its path as a list of\n",
+    "           strings.\"\"\"\n",
+    "        full_path = os.path.join(self.location, *path)\n",
+    "\n",
+    "        if verbose > 1:\n",
+    "            if verbose < 10:\n",
+    "                print('{0}...'.format(msg))\n",
+    "            else:\n",
+    "                print('{0} from {1}'.format(msg, full_path))\n",
+    "\n",
+    "        mmap_mode = (None if not hasattr(self, 'mmap_mode')\n",
+    "                     else self.mmap_mode)\n",
+    "\n",
+    "        filename = os.path.join(full_path, 'output.pkl')\n",
+    "        if not self._item_exists(filename):\n",
+    "            raise KeyError(\"Non-existing item (may have been \"\n",
+    "                           \"cleared).\\nFile %s does not exist\" % filename)\n",
+    "\n",
+    "        # file-like object cannot be used when mmap_mode is set\n",
+    "        if mmap_mode is None:\n",
+    "            with self._open_item(filename, \"rb\") as f:\n",
+    "                item = pickle.load(f)\n",
+    "        else:\n",
+    "            item = numpy_pickle.load(filename, mmap_mode=mmap_mode)\n",
+    "        return item\n",
+    "\n",
+    "    def dump_item(self, path, item, verbose=1):\n",
+    "        \"\"\"Dump an item in the store at the path given as a list of\n",
+    "           strings.\"\"\"\n",
+    "        try:\n",
+    "            item_path = os.path.join(self.location, *path)\n",
+    "            if not self._item_exists(item_path):\n",
+    "                self.create_location(item_path)\n",
+    "            filename = os.path.join(item_path, 'output.pkl')\n",
+    "            if verbose > 10:\n",
+    "                print('Persisting in %s' % item_path)\n",
+    "\n",
+    "            def write_func(to_write, dest_filename):\n",
+    "                mmap_mode = (None if not hasattr(self, 'mmap_mode')\n",
+    "                             else self.mmap_mode)\n",
+    "                with self._open_item(dest_filename, \"wb\") as f:\n",
+    "                    try:\n",
+    "                        if mmap_mode is None:\n",
+    "                            pickle.dump(to_write, f)\n",
+    "                        else:\n",
+    "                            numpy_pickle.dump(to_write, f, compress=self.compress)\n",
+    "                    except pickle.PicklingError as e:\n",
+    "                        # TODO(1.5) turn into error\n",
+    "                        warnings.warn(\n",
+    "                            \"Unable to cache to disk: failed to pickle \"\n",
+    "                            \"output. In version 1.5 this will raise an \"\n",
+    "                            f\"exception. Exception: {e}.\",\n",
+    "                            FutureWarning\n",
+    "                        )\n",
+    "\n",
+    "            self._concurrency_safe_write(item, filename, write_func)\n",
+    "        except Exception as e:  # noqa: E722\n",
+    "            warnings.warn(\n",
+    "                \"Unable to cache to disk. Possibly a race condition in the \"\n",
+    "                f\"creation of the directory. Exception: {e}.\",\n",
+    "                CacheWarning\n",
+    "            )\n",
+    "\n",
+    "\n",
+    "register_store_backend(FileSystemStoreBackendNoNumpy.NAME, FileSystemStoreBackendNoNumpy)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "41eb3bbd-19bb-4c0d-892c-35478eabc00b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import time\n",
+    "from http.client import RemoteDisconnected\n",
+    "\n",
+    "import requests\n",
+    "from joblib import Memory\n",
+    "from urllib3.exceptions import ProtocolError\n",
+    "\n",
+    "\n",
+    "SPARQL_API_URL = \"http://127.0.0.1:7001\"\n",
+    "CACHE_DIRECTORY = \"wikidata/cache\"\n",
+    "\n",
+    "logger = logging.getLogger()\n",
+    "memory = Memory(CACHE_DIRECTORY, verbose=0, backend=FileSystemStoreBackendNoNumpy.NAME)\n",
+    "\n",
+    "\n",
+    "def execute_wiki_request_with_delays(api_url, params, headers):\n",
+    "    response = requests.get(\n",
+    "        api_url,\n",
+    "        params=params,\n",
+    "        headers=headers,\n",
+    "    )\n",
+    "    to_sleep = 0.2\n",
+    "    while response.status_code == 429:\n",
+    "        logger.warning(\n",
+    "            {\n",
+    "                \"msg\": f\"Request to wikidata endpoint failed. Retry.\",\n",
+    "                \"params\": params,\n",
+    "                \"endpoint\": api_url,\n",
+    "                \"response\": {\n",
+    "                    \"status_code\": response.status_code,\n",
+    "                    \"headers\": dict(response.headers),\n",
+    "                },\n",
+    "                \"retry_after\": to_sleep,\n",
+    "            }\n",
+    "        )\n",
+    "        if \"retry-after\" in response.headers:\n",
+    "            to_sleep += int(response.headers[\"retry-after\"])\n",
+    "        to_sleep += 0.5\n",
+    "        time.sleep(to_sleep)\n",
+    "        response = requests.get(\n",
+    "            api_url,\n",
+    "            params=params,\n",
+    "            headers=headers,\n",
+    "        )\n",
+    "\n",
+    "    return response\n",
+    "\n",
+    "\n",
+    "@memory.cache(ignore=['api_url'])\n",
+    "def execute_sparql_request(request: str, api_url: str = SPARQL_API_URL):\n",
+    "    params = {\"format\": \"json\", \"query\": request}\n",
+    "    headers = {\n",
+    "        \"Accept\": \"application/sparql-results+json\",\n",
+    "        \"User-Agent\": \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.102 Safari/537.36\",\n",
+    "    }\n",
+    "    logger.info(\n",
+    "        {\n",
+    "            \"msg\": \"Send request to Wikidata\",\n",
+    "            \"params\": params,\n",
+    "            \"endpoint\": api_url,\n",
+    "            \"request\": request\n",
+    "        }\n",
+    "    )\n",
+    "    try:\n",
+    "        response = execute_wiki_request_with_delays(api_url, params, headers)\n",
+    "    except (ProtocolError, RemoteDisconnected, requests.exceptions.ConnectionError) as e:\n",
+    "        logger.error(\n",
+    "            {\n",
+    "                \"msg\": str(e),\n",
+    "                \"request\": request,\n",
+    "                \"endpoint\": api_url,\n",
+    "            }\n",
+    "        )\n",
+    "        return None\n",
+    "\n",
+    "    try:\n",
+    "        response = response.json()[\"results\"][\"bindings\"]\n",
+    "        logger.debug(\n",
+    "            {\n",
+    "                \"msg\": \"Received response from Wikidata\",\n",
+    "                \"params\": params,\n",
+    "                \"endpoint\": api_url,\n",
+    "                \"request\": request,\n",
+    "                \"response\": response\n",
+    "            }\n",
+    "        )\n",
+    "        return response\n",
+    "    except Exception as e:\n",
+    "        logger.error(\n",
+    "            {\n",
+    "                \"msg\": str(e),\n",
+    "                \"params\": params,\n",
+    "                \"endpoint\": api_url,\n",
+    "                \"response\": {\n",
+    "                    \"status_code\": response.status_code,\n",
+    "                    \"headers\": dict(response.headers),\n",
+    "                },\n",
+    "            }\n",
+    "        )\n",
+    "        raise e\n",
+    "\n",
+    "def get_label(entity_id):\n",
+    "    query = \"\"\"\n",
+    "    PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> \n",
+    "    PREFIX wd: <http://www.wikidata.org/entity/> \n",
+    "    SELECT DISTINCT ?label\n",
+    "    WHERE {\n",
+    "        wd:<ENTITY> rdfs:label ?label\n",
+    "    } \n",
+    "    \"\"\".replace(\n",
+    "        \"<ENTITY>\", entity_id\n",
+    "    )\n",
+    "    \n",
+    "    for lbl_obj in execute_sparql_request(query):\n",
+    "        if lbl_obj['label']['xml:lang'] == 'en':\n",
+    "            return lbl_obj['label']['value']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "2568fa09",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Map:   0%|          | 0/19481 [00:00<?, ? examples/s]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Map: 100%|██████████| 19481/19481 [01:44<00:00, 185.89 examples/s]\n",
+      "Map: 100%|██████████| 2821/2821 [00:08<00:00, 334.13 examples/s]\n",
+      "Map: 100%|██████████| 5622/5622 [00:15<00:00, 352.59 examples/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "dataset = dataset.map(\n",
+    "    lambda record: {'object_label': get_label(record['object'])}\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "222d50c1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Creating parquet from Arrow format: 100%|██████████| 20/20 [00:00<00:00, 474.06ba/s]\n",
+      "Uploading the dataset shards: 100%|██████████| 1/1 [00:02<00:00,  2.07s/it]\n",
+      "Creating parquet from Arrow format: 100%|██████████| 3/3 [00:00<00:00, 921.29ba/s]\n",
+      "Uploading the dataset shards: 100%|██████████| 1/1 [00:01<00:00,  1.63s/it]\n",
+      "Creating parquet from Arrow format: 100%|██████████| 6/6 [00:00<00:00, 1000.75ba/s]\n",
+      "Uploading the dataset shards: 100%|██████████| 1/1 [00:01<00:00,  1.73s/it]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "CommitInfo(commit_url='https://huggingface.co/datasets/s-nlp/sqwd/commit/680b8199969fc0389fc96feb4f3b8be15b2674d0', commit_message='Upload dataset', commit_description='', oid='680b8199969fc0389fc96feb4f3b8be15b2674d0', pr_url=None, pr_revision=None, pr_num=None)"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataset.push_to_hub('s-nlp/sqwd', 'answerable', set_default=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2652ed4d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}