{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "36b5fea9-940a-4f92-9cd9-7c8ce4d0f59b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from collections import Counter\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.feature_extraction.text import TfidfTransformer\n",
    "from sklearn.decomposition import TruncatedSVD\n",
    "from tqdm.notebook import tqdm\n",
    "from openTSNE import TSNE\n",
    "import datashader as ds\n",
    "import colorcet as cc\n",
    "\n",
    "from dask.distributed import Client, LocalCluster\n",
    "import dask.dataframe as dd\n",
    "import dask_ml.feature_extraction.text\n",
    "import dask.bag as db\n",
    "\n",
    "from transformers import AutoTokenizer\n",
    "from huggingface_hub import notebook_login, HfApi, hf_hub_download, Repository\n",
    "from datasets import load_dataset\n",
    "from datasets.utils.py_utils import convert_file_size_to_int"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6acce76a-5b79-4ee0-ad92-08b819d268e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "tokenizer = AutoTokenizer.from_pretrained(\"bigscience/bloom\")\n",
    "vocab = tokenizer.vocab\n",
    "reverse_vocab = {v:k for k,v in vocab.items()}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b8811f08-4b4c-4e13-86b6-43ee6a4e6e07",
   "metadata": {},
   "outputs": [],
   "source": [
    "def batch_tokenize(batch):\n",
    "    return {'tokenized': [' '.join(e.tokens) for e in tokenizer(batch['text']).encodings]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "23af3f6c-34bb-4011-863d-d8bea08192a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "dset_name = \"bigscience-catalogue-lm-data/roots_fr_uncorpus\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "52054ce2-7f33-49c5-a5a9-fe91548b8fae",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using custom data configuration bigscience-catalogue-lm-data--cleaned_lm_fr_uncorpus-df68e40301b12c79\n",
      "Reusing dataset parquet (/media/ssd/BIGSCIENCE/cache/bigscience-catalogue-lm-data___parquet/bigscience-catalogue-lm-data--cleaned_lm_fr_uncorpus-df68e40301b12c79/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec)\n"
     ]
    }
   ],
   "source": [
    "dset = load_dataset(dset_name, split=\"train\", cache_dir=\"/media/ssd/BIGSCIENCE/cache\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bd31288f-82f1-4752-aeb1-d1ec6cc6e00c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dataset({\n",
       "    features: ['text', 'meta'],\n",
       "    num_rows: 145876\n",
       "})"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f59e42a7-0cc0-4425-b4e8-40446a1d187f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "32ed568f9c304dc8a03249663aeb2de4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#0:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "172d9a3a899a46169867ef587bacceba",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#2:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "02bfa09885c5473e9fa467679bf00ea3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#1:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6b15ca26b3bd483fba54c7684c63466f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#3:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d463c281d07d48079b60a4b2c202b6e7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#4:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "baacdf95f2b14f9aa5fd950cc22f3fd6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#5:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7d98de76aa6e4a6ca49fad9a4c898720",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#6:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6fc210f8cefb4a2d9534eade64dea7c8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#7:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c5b3b6b5847f404896a9e0a00579a593",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#8:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a68ee61bdde34c0b955754a4c0b02ed0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#9:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "50e0a782643a4770a253057faac8b928",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#10:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "22375f9686304fa48dcc7adc372d513f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#11:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "14acdaaec87d4259bca8a14bff647e66",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#12:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9df96cb4fa6d442892c2f1f444939009",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#13:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "372c7f490ab34986a301b782e5e9c453",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#14:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8414313d13804cebbba18453cb4cc07c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#15:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b1eb560e02d74c908f33470f3dd858e3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#16:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d20e5dfb74fb4141a6155fcb72ff82e5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#17:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ef6e9200e5e74be6ae13ae4f7f6f1a44",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#18:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dd7daf7591a242ceba21b2390a3e25d9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#20:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "25472bd1f3ac4054b545e0e8df158838",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#19:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "41a3ad4470bf444f82a25e9dea48079b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#21:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c0d9c4c2aa5c4feead3ef7b644c1d953",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#22:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "67706a9796264b788781ac56146dccb1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#24:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2257fb580e264d60a61ee1a2c7c12bc0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#23:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8ed19032e8f24931b9cad7ea22cc5b9f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#25:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "852b2ebafaa2479a84ed7057124aa8a8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#26:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6efde215a93f46148559eab4897690a6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "#27:   0%|          | 0/82 [00:00<?, ?ba/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 10.8 s, sys: 2.33 s, total: 13.2 s\n",
      "Wall time: 4min 11s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "dset = dset.map(batch_tokenize, batched=True, batch_size=64, num_proc=28)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "387dbba2-e07f-4cf8-a520-42872eafd46f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sharding into 43 files.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "161c38ceeb304985a08affeef501a6a3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/43 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 30 s, sys: 2.43 s, total: 32.4 s\n",
      "Wall time: 32.2 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['tokenized-013.parquet',\n",
       " 'tokenized-037.parquet',\n",
       " 'tokenized-024.parquet',\n",
       " 'tokenized-032.parquet',\n",
       " 'tokenized-027.parquet',\n",
       " 'tokenized-007.parquet',\n",
       " 'tokenized-028.parquet',\n",
       " 'tokenized-005.parquet',\n",
       " 'tokenized-029.parquet',\n",
       " 'tokenized-010.parquet',\n",
       " 'tokenized-004.parquet',\n",
       " 'tokenized-003.parquet',\n",
       " 'tokenized-016.parquet',\n",
       " 'tokenized-040.parquet',\n",
       " 'tokenized-031.parquet',\n",
       " 'tokenized-012.parquet',\n",
       " 'tokenized-030.parquet',\n",
       " 'tokenized-041.parquet',\n",
       " 'tokenized-017.parquet',\n",
       " 'tokenized-034.parquet',\n",
       " 'tokenized-020.parquet',\n",
       " 'tokenized-026.parquet',\n",
       " 'tokenized-015.parquet',\n",
       " 'tokenized-014.parquet',\n",
       " 'tokenized-011.parquet',\n",
       " 'tokenized-022.parquet',\n",
       " 'tokenized-009.parquet',\n",
       " 'tokenized-036.parquet',\n",
       " 'tokenized-025.parquet',\n",
       " 'tokenized-018.parquet',\n",
       " 'tokenized-039.parquet',\n",
       " 'tokenized-042.parquet',\n",
       " 'tokenized-001.parquet',\n",
       " 'tokenized-021.parquet',\n",
       " 'tokenized-023.parquet',\n",
       " 'tokenized-006.parquet',\n",
       " 'tokenized-000.parquet',\n",
       " 'tokenized-033.parquet',\n",
       " 'tokenized-035.parquet',\n",
       " 'tokenized-008.parquet',\n",
       " 'tokenized-038.parquet',\n",
       " 'tokenized-002.parquet',\n",
       " 'tokenized-019.parquet']"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "max_shard_size = convert_file_size_to_int('300MB')\n",
    "dataset_nbytes = dset.data.nbytes\n",
    "num_shards = int(dataset_nbytes / max_shard_size) + 1\n",
    "num_shards = max(num_shards, 1)\n",
    "print(f\"Sharding into {num_shards} files.\")\n",
    "os.makedirs(f\"{dset_name}/tokenized\", exist_ok=True)\n",
    "for shard_index in tqdm(range(num_shards)):\n",
    "    shard = dset.shard(num_shards=num_shards, index=shard_index, contiguous=True)\n",
    "    shard.to_parquet(f\"{dset_name}/tokenized/tokenized-{shard_index:03d}.parquet\")\n",
    "os.listdir(f'{dset_name}/tokenized/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "187941f9-5243-45b4-b187-284307d7ca7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
       "    <div style=\"margin-left: 48px;\">\n",
       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-e038e83a-221b-11ed-a525-40b0760fea7a</p>\n",
       "        <table style=\"width: 100%; text-align: left;\">\n",
       "\n",
       "        <tr>\n",
       "        \n",
       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
       "        \n",
       "        </tr>\n",
       "\n",
       "        \n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\"></td>\n",
       "            </tr>\n",
       "        \n",
       "\n",
       "        </table>\n",
       "\n",
       "        \n",
       "            <details>\n",
       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
       "    </div>\n",
       "    <div style=\"margin-left: 48px;\">\n",
       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">45d34c47</p>\n",
       "        <table style=\"width: 100%; text-align: left;\">\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Workers:</strong> 7\n",
       "                </td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Total threads:</strong> 28\n",
       "                </td>\n",
       "                <td style=\"text-align: left;\">\n",
       "                    <strong>Total memory:</strong> 62.60 GiB\n",
       "                </td>\n",
       "            </tr>\n",
       "            \n",
       "            <tr>\n",
       "    <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
       "    <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
       "</tr>\n",
       "\n",
       "            \n",
       "        </table>\n",
       "\n",
       "        <details>\n",
       "            <summary style=\"margin-bottom: 20px;\">\n",
       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
       "            </summary>\n",
       "\n",
       "            <div style=\"\">\n",
       "    <div>\n",
       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
       "        <div style=\"margin-left: 48px;\">\n",
       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-b9de7467-0242-4807-ad9d-9241afa2c2a1</p>\n",
       "            <table style=\"width: 100%; text-align: left;\">\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Comm:</strong> tcp://127.0.0.1:34657\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Workers:</strong> 7\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Total threads:</strong> 28\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Started:</strong> Just now\n",
       "                    </td>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Total memory:</strong> 62.60 GiB\n",
       "                    </td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "\n",
       "    <details style=\"margin-left: 48px;\">\n",
       "        <summary style=\"margin-bottom: 20px;\">\n",
       "            <h3 style=\"display: inline;\">Workers</h3>\n",
       "        </summary>\n",
       "\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:37977\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:44675/status\" target=\"_blank\">http://127.0.0.1:44675/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 8.94 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:35529\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /media/ssd/BIGSCIENCE/dask-worker-space/worker-f4t43chg\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:34541\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:44713/status\" target=\"_blank\">http://127.0.0.1:44713/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 8.94 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:36837\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /media/ssd/BIGSCIENCE/dask-worker-space/worker-d7xhhp6y\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:41035\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:41835/status\" target=\"_blank\">http://127.0.0.1:41835/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 8.94 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:37267\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /media/ssd/BIGSCIENCE/dask-worker-space/worker-r1hlyoa0\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:43453\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:39007/status\" target=\"_blank\">http://127.0.0.1:39007/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 8.94 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:35059\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /media/ssd/BIGSCIENCE/dask-worker-space/worker-5u2rmzie\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 4</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:43103\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:45759/status\" target=\"_blank\">http://127.0.0.1:45759/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 8.94 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:37227\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /media/ssd/BIGSCIENCE/dask-worker-space/worker-r1c7349j\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 5</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:35613\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:34293/status\" target=\"_blank\">http://127.0.0.1:34293/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 8.94 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:37127\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /media/ssd/BIGSCIENCE/dask-worker-space/worker-6f6k7cqw\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "        <div style=\"margin-bottom: 20px;\">\n",
       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
       "            <div style=\"margin-left: 48px;\">\n",
       "            <details>\n",
       "                <summary>\n",
       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 6</h4>\n",
       "                </summary>\n",
       "                <table style=\"width: 100%; text-align: left;\">\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Comm: </strong> tcp://127.0.0.1:39423\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:39111/status\" target=\"_blank\">http://127.0.0.1:39111/status</a>\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Memory: </strong> 8.94 GiB\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Nanny: </strong> tcp://127.0.0.1:38503\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\"></td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
       "                            <strong>Local directory: </strong> /media/ssd/BIGSCIENCE/dask-worker-space/worker-ba89br89\n",
       "                        </td>\n",
       "                    </tr>\n",
       "\n",
       "                    \n",
       "\n",
       "                    \n",
       "\n",
       "                </table>\n",
       "            </details>\n",
       "            </div>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "    </details>\n",
       "</div>\n",
       "\n",
       "        </details>\n",
       "    </div>\n",
       "</div>\n",
       "            </details>\n",
       "        \n",
       "\n",
       "    </div>\n",
       "</div>"
      ],
      "text/plain": [
       "<Client: 'tcp://127.0.0.1:34657' processes=7 threads=28, memory=62.60 GiB>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client = Client()\n",
    "client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dd26792f-ad76-4928-b94b-70f7d9dad6eb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.utils_perf - WARNING - full garbage collections took 27% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 28% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 27% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 28% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 28% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 28% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 29% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 29% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 29% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 29% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 29% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 30% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 32% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 29% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 28% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 28% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 27% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 29% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 30% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 30% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 30% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 30% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 30% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 30% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 30% CPU time recently (threshold: 10%)\n",
      "distributed.utils_perf - WARNING - full garbage collections took 31% CPU time recently (threshold: 10%)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 9.24 s, sys: 742 ms, total: 9.98 s\n",
      "Wall time: 23 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df = dd.read_parquet(f'{dset_name}/tokenized/')\n",
    "vect = dask_ml.feature_extraction.text.CountVectorizer(tokenizer=str.split,\n",
    "                                                       token_pattern=None,\n",
    "                                                       vocabulary=vocab)\n",
    "tokenized_bag = df['tokenized'].to_bag()\n",
    "X = vect.transform(tokenized_bag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8811759e-f44d-48ed-b1f6-86befa2cd8a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.utils_perf - WARNING - full garbage collections took 21% CPU time recently (threshold: 10%)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 39.8 s, sys: 5.9 s, total: 45.7 s\n",
      "Wall time: 2min 39s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "counts = X.compute()\n",
    "client.shutdown()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a4a8bff0-68c2-4f63-9330-bcab28e2cd02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<145876x250680 sparse matrix of type '<class 'numpy.int64'>'\n",
       "\twith 43446986 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "acb19280-e554-4d92-8706-f843a299217c",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(',', 34814464),\n",
       " ('.', 21948181),\n",
       " (')', 4949061),\n",
       " (';', 2740524),\n",
       " ('ant', 1231074),\n",
       " ('1', 1134577),\n",
       " ('),', 1117959),\n",
       " ('le', 1042373),\n",
       " ('e', 996400),\n",
       " ('ation', 976949),\n",
       " ('2', 965098),\n",
       " ('/', 901092),\n",
       " ('b', 810668),\n",
       " ('a', 801115),\n",
       " ('s', 752845),\n",
       " ('ent', 749895),\n",
       " ('3', 714091),\n",
       " ('c', 675251),\n",
       " ('er', 653847),\n",
       " ('ement', 650192),\n",
       " (':', 646632),\n",
       " ('ie', 639917),\n",
       " ('la', 623993),\n",
       " ('4', 607453),\n",
       " ('ations', 604552),\n",
       " ('es', 563981),\n",
       " ('m', 559806),\n",
       " ('d', 554653),\n",
       " ('i', 544907),\n",
       " ('les', 541236),\n",
       " ('is', 514949),\n",
       " (').', 501087),\n",
       " ('5', 494491),\n",
       " ('isation', 488711),\n",
       " ('en', 487799),\n",
       " ('\"', 473312),\n",
       " ('un', 462088),\n",
       " ('6', 418736),\n",
       " ('aient', 409955),\n",
       " ('f', 409463),\n",
       " ('g', 399877),\n",
       " ('ait', 391162),\n",
       " ('r', 387126),\n",
       " ('ants', 384791),\n",
       " ('>>', 376997),\n",
       " ('us', 366909),\n",
       " ('ique', 359072),\n",
       " ('n', 343549),\n",
       " ('de', 342141),\n",
       " ('7', 339226),\n",
       " ('-', 338144),\n",
       " ('aux', 336640),\n",
       " ('v', 330524),\n",
       " ('ements', 303551),\n",
       " (\"l'\", 302513),\n",
       " ('il', 302115),\n",
       " ('ies', 300399),\n",
       " ('it', 299106),\n",
       " ('al', 298741),\n",
       " ('ale', 296358),\n",
       " ('if', 294240),\n",
       " ('8', 292746),\n",
       " ('era', 290015),\n",
       " ('p', 285288),\n",
       " ('par', 282921),\n",
       " ('ur', 280345),\n",
       " ('t', 279981),\n",
       " ('ante', 278659),\n",
       " (']', 274980),\n",
       " ('an', 273027),\n",
       " ('u', 272306),\n",
       " ('iques', 270463),\n",
       " ('in', 269539),\n",
       " ('9', 263244),\n",
       " ('aire', 262021),\n",
       " ('et', 261216),\n",
       " ('age', 261030),\n",
       " ('h', 255820),\n",
       " ('l', 255274),\n",
       " ('10', 255160),\n",
       " ('au', 255134),\n",
       " ('ateur', 253419),\n",
       " ('on', 251010),\n",
       " ('ues', 250799),\n",
       " ('ir', 244181),\n",
       " ('voir', 235858),\n",
       " ('at', 231829),\n",
       " ('ales', 228747),\n",
       " ('con', 217926),\n",
       " ('iser', 215583),\n",
       " ('ont', 212434),\n",
       " ('ires', 211954),\n",
       " ('antes', 205935),\n",
       " ('erait', 205901),\n",
       " ('ons', 203324),\n",
       " ('ateurs', 197845),\n",
       " ('ue', 197308),\n",
       " ('mr', 196911),\n",
       " ('des', 195245),\n",
       " ('12', 193578)]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "freq = counts.sum(axis=0).A1\n",
    "frequencies = Counter({reverse_vocab[i]:freq[i] for i in freq.nonzero()[0]})\n",
    "frequencies.most_common(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9c8b98af-097f-4bf1-9bb1-2f0a130751ca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 994 ms, sys: 116 ms, total: 1.11 s\n",
      "Wall time: 1.06 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "tfidf = tfidf_transformer.fit_transform(counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c6a122c2-bce7-413c-b488-2faaa2296d4f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3min 37s, sys: 1min, total: 4min 38s\n",
      "Wall time: 1min 7s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "svd = TruncatedSVD(n_components=160)\n",
    "X = svd.fit_transform(tfidf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "df3fd243-87d9-4b25-bcc3-cbf3f779630d",
   "metadata": {},
   "outputs": [],
   "source": [
    "tsne = TSNE(\n",
    "    perplexity=30,\n",
    "    metric=\"cosine\",\n",
    "    n_jobs=28,\n",
    "    random_state=42,\n",
    "    verbose=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "498ae603-f853-41bd-a75e-7854c1464e7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------------------------------------\n",
      "TSNE(metric='cosine', n_jobs=28, random_state=42, verbose=True)\n",
      "--------------------------------------------------------------------------------\n",
      "===> Finding 90 nearest neighbors using Annoy approximate search using cosine distance...\n",
      "   --> Time elapsed: 31.83 seconds\n",
      "===> Calculating affinity matrix...\n",
      "   --> Time elapsed: 1.01 seconds\n",
      "===> Calculating PCA-based initialization...\n",
      "   --> Time elapsed: 0.62 seconds\n",
      "===> Running optimization with exaggeration=12.00, lr=12156.33 for 250 iterations...\n",
      "Iteration   50, KL divergence 8.0172, 50 iterations in 3.3109 sec\n",
      "Iteration  100, KL divergence 7.6925, 50 iterations in 3.2977 sec\n",
      "Iteration  150, KL divergence 7.5762, 50 iterations in 3.3080 sec\n",
      "Iteration  200, KL divergence 7.5796, 50 iterations in 3.3637 sec\n",
      "Iteration  250, KL divergence 7.5440, 50 iterations in 3.3075 sec\n",
      "   --> Time elapsed: 16.59 seconds\n",
      "===> Running optimization with exaggeration=1.00, lr=12156.33 for 500 iterations...\n",
      "Iteration   50, KL divergence 5.4392, 50 iterations in 3.0292 sec\n",
      "Iteration  100, KL divergence 4.9245, 50 iterations in 3.0565 sec\n",
      "Iteration  150, KL divergence 4.6700, 50 iterations in 3.6400 sec\n",
      "Iteration  200, KL divergence 4.5170, 50 iterations in 4.5099 sec\n",
      "Iteration  250, KL divergence 4.4161, 50 iterations in 5.1544 sec\n",
      "Iteration  300, KL divergence 4.3463, 50 iterations in 5.7396 sec\n",
      "Iteration  350, KL divergence 4.2947, 50 iterations in 7.1917 sec\n",
      "Iteration  400, KL divergence 4.2536, 50 iterations in 7.5439 sec\n",
      "Iteration  450, KL divergence 4.2217, 50 iterations in 8.4501 sec\n",
      "Iteration  500, KL divergence 4.1947, 50 iterations in 8.8987 sec\n",
      "   --> Time elapsed: 57.21 seconds\n",
      "CPU times: user 22min 46s, sys: 12.8 s, total: 22min 59s\n",
      "Wall time: 1min 52s\n"
     ]
    }
   ],
   "source": [
    "%%time \n",
    "tsne_embedding = tsne.fit(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "97915b89-2844-4ada-ae28-82377ccb21a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data=tsne_embedding, columns=['x','y'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "4fe427bd-6326-4442-ab32-b47990439c47",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 44.5 ms, sys: 16 µs, total: 44.5 ms\n",
      "Wall time: 40.2 ms\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/html": [
       "<img style=\"margin: auto; border:1px solid\" src='data:image/png;base64,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'/>"
      ],
      "text/plain": [
       "<xarray.Image (y: 600, x: 600)>\n",
       "array([[4278190080, 4278190080, 4278190080, ..., 4278190080, 4278190080,\n",
       "        4278190080],\n",
       "       [4278190080, 4278190080, 4278190080, ..., 4278190080, 4278190080,\n",
       "        4278190080],\n",
       "       [4278190080, 4278190080, 4278190080, ..., 4278190080, 4278190080,\n",
       "        4278190080],\n",
       "       ...,\n",
       "       [4278190080, 4278190080, 4278190080, ..., 4278190080, 4278190080,\n",
       "        4278190080],\n",
       "       [4278190080, 4278190080, 4278190080, ..., 4278190080, 4278190080,\n",
       "        4278190080],\n",
       "       [4278190080, 4278190080, 4278190080, ..., 4278190080, 4278190080,\n",
       "        4278190080]], dtype=uint32)\n",
       "Coordinates:\n",
       "  * x        (x) float64 -71.24 -71.0 -70.75 -70.5 ... 75.77 76.01 76.26 76.51\n",
       "  * y        (y) float64 -65.28 -65.06 -64.83 -64.6 ... 69.14 69.36 69.59 69.81"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "agg = ds.Canvas(plot_height=600, plot_width=600).points(df, 'x', 'y')\n",
    "img = ds.tf.shade(agg, cmap=cc.fire, how='eq_hist')\n",
    "ds.tf.set_background(img, \"black\")"
   ]
  }
 ],
 "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": "3.8.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}