{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import selfies as sf\n",
    "from tokenizers import Tokenizer\n",
    "from tokenizers.models import WordLevel\n",
    "from tokenizers.pre_tokenizers import Split\n",
    "from tokenizers.processors import TemplateProcessing\n",
    "from tokenizers.trainers import WordLevelTrainer\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"./train.txt\") as f:\n",
    "    smiles = [line.strip() for line in f]\n",
    "\n",
    "selfies = []\n",
    "for smile in tqdm(smiles):\n",
    "    try:\n",
    "        selfies.append(sf.encoder(smile))\n",
    "    except:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tokenizer = Tokenizer(WordLevel(unk_token=\"<UNK>\"))\n",
    "\n",
    "tokenizer.pre_tokenizer = Split(\n",
    "    pattern=\"]\", \n",
    "    behavior=\"merged_with_previous\"\n",
    ")\n",
    "\n",
    "trainer = WordLevelTrainer(\n",
    "    special_tokens=[\"<CLS>\", \"<EOS>\", \"<PAD>\", \"<UNK>\"]\n",
    ")\n",
    "\n",
    "tokenizer.train_from_iterator(selfies, trainer=trainer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tokenizer.post_processor = TemplateProcessing(\n",
    "    single=\"<CLS> $A <EOS>\",\n",
    "    special_tokens=[\n",
    "        (\"<CLS>\", tokenizer.token_to_id(\"<CLS>\")),\n",
    "        (\"<EOS>\", tokenizer.token_to_id(\"<EOS>\")),\n",
    "    ],\n",
    ")\n",
    "\n",
    "tokenizer.enable_padding(\n",
    "    direction=\"right\",\n",
    "    pad_id=tokenizer.token_to_id(\"<PAD>\"),\n",
    "    pad_token=\"<PAD>\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tokenizer.save(\"./tokenizer.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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