Upload milk_dialog_dataset.ipynb

milk_dialog_dataset.ipynb

@@ -0,0 +1,786 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1bcd4735-038a-4364-90ed-6e58d8fa2dac",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import re\n",
+    "import pandas as pd\n",
+    "from datasets import Dataset\n",
+    "from huggingface_hub import login"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a23cc23d-90d6-431f-8057-67dbac509de2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# add the credential helper so we can use\n",
+    "# the library to push data to the hub later\n",
+    "\n",
+    "!git config --global credential.helper cache\n",
+    "\n",
+    "# login to the hub\n",
+    "\n",
+    "login(\n",
+    "    '',\n",
+    "    add_to_git_credential=True\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a28d0034-ce6b-4a76-ab52-6050c0c74bfc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('bad.rpy', 'r') as f:\n",
+    "    rpy_text = f.read()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "95397968-6caf-41b9-a27f-c806ac0a1993",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lines = re.findall(r\"^\\s{4}.*$\", rpy_text, re.MULTILINE) # Find all lines starting with 4 empty spaces"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4558c31b-1b1d-4bfb-a76a-b36a09edaab3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "non_latin_lines = [line for line in lines if re.search(r\"[^\\x00-\\x7F]\", line)] # Get all lines containing non-latin characters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4c6d06de-aa42-4d52-bc82-8f469100769c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "latin_lines = [line for line in lines if line not in non_latin_lines] # Get only the lines containing latin characters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ef9eb581-b849-4c5a-bbdd-ecf27445a819",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filtered_lines = [re.sub(r\"\\[(.*?)\\]|\\{(.*?)\\}\", \"\", line) for line in latin_lines] # Remove all text between square or curly braces including them"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "35cc3cac-d76e-4aa3-b954-178ca8c82fdd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filtered_lines = [line for line in filtered_lines if \"game/bad.rpy\" not in line] # Remove all lines containing game related information"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e5928733-bfb8-4ce0-afd6-fdd0a7fce2bf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filtered_lines = [line.replace(\"'[cname]'\", \"me\") for line in filtered_lines] # Replace '[cname]' with \"me\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f216353e-e74f-4ed1-9d5c-cf9715a887d5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Removes a bunch of rpy specific tags, read the line because I'm too lazy to list them all and yes it is a big ass line\n",
+    "filtered_lines = [line.replace(\"    ei \", \"\").replace(\"    n \", \"\").replace(\"    gg \", \"\").replace(\"    new \", \"\").replace(\"\\n    # ei \", \"\").replace(\"\\\\\", \"\").replace(\"\\n    # n \", \"\") for line in filtered_lines]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c879273e-8c8e-4659-bae9-73d288773a24",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filtered_lines = [re.sub(r\"\\s+\", \" \", line) for line in filtered_lines] # Remove all extra space"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "68e07452-4afb-43ab-b033-7258aec5c341",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filtered_lines = [line.replace('\"', '') for line in filtered_lines] # Remove \""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "649c6760-fe86-425f-9bd9-93c8baab9589",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filtered_lines = [line.lstrip() for line in filtered_lines] # Remove spaces from the start of the lines"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d16d37a5-3e86-4774-83b5-ade50af416a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filtered_lines = [line for line in filtered_lines if line != \"...\"] # remove non textual lines"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a9b3f0ee-a6f7-412b-b68b-7c117c516b9f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filtered_lines = [line for line in filtered_lines if filtered_lines.count(line) == 1] # Remove repeated lines"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5665cb09-241a-4a2c-8b9c-892aedd8536d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filtered_lines = [line.lstrip('(').rstrip(')') for line in filtered_lines] # Remove parenthesis from the begining or end of a line"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "841d3d7c-736b-4d47-911f-25018c84abb3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(f'Number of lines: {len(filtered_lines)}\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "86fde09a-698c-4cd8-ac41-4b688f80d729",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a dataframe from the input and output columns\n",
+    "df = pd.DataFrame({'response': filtered_lines})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9b0dff6a-afe5-412f-aaf0-c6fc467d4675",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset = Dataset.from_pandas(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "12d35230-4859-4185-a03b-0b68b561d01f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(dataset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "df7282e2-67a5-462b-a870-2824fd575a2c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "split = dataset.train_test_split(test_size=0.1)\n",
+    "train = split['train']\n",
+    "test = split['test']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "765fd5be-39e2-4206-8bd1-5a210ecf2f4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(split)\n",
+    "print(train)\n",
+    "print(test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "154673b0-bc62-4873-814d-ac1af88514cc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "repository = \"alexandreteles/milk\"\n",
+    "\n",
+    "train.push_to_hub(\n",
+    "    repo_id=repository,\n",
+    "    split=\"train\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4b719b32-836d-4014-832c-75ecd4cd4d72",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test.push_to_hub(\n",
+    "    repo_id=repository,\n",
+    "    split=\"test\"\n",
+    ")"
+   ]
+  }
+ ],
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+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
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