notebooks/tutorials/1. Generating data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import checklist\n",
    "from checklist.editor import Editor\n",
    "from checklist.perturb import Perturb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we create any tests, it's worth taking a tour of CheckList's abstractions for manipulating text data and coming up with examples. In this tutorial, we'll look at creating examples from scratch."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating examples from scratch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Templates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we'll create an editor:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "editor = Editor()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The editor allows us to fill in templates with lists of 'fill-ins', and doing cartesian products. For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['This is a good movie.',\n",
       " 'This is a great movie.',\n",
       " 'This is a awesome movie.',\n",
       " 'This is a excellent movie.']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = editor.template('This is a {adj} movie.', adj=['good', 'great', 'awesome', 'excellent'])\n",
    "ret.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`editor.template` returns a Munch (a glorified dict which allows us to call `ret.data` instead of `ret['data']`). \n",
    "If you set any of the arguments `labels`, `meta`, or `save`, additional fields will exist in `ret`. Here is an example, notice how `ret.labels` now has a label for each example in `ret.data`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 1, 1, 1]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = editor.template('This is a {adj} movie.', adj=['good', 'great', 'awesome', 'excellent'], labels=1,\n",
    "                      meta=True, save=True)\n",
    "ret.labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setting `meta=True` gives us the fill in values for each example in `ret.data`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is a good movie. {'adj': 'good'}\n",
      "This is a great movie. {'adj': 'great'}\n"
     ]
    }
   ],
   "source": [
    "print(ret.data[0], ret.meta[0])\n",
    "print(ret.data[1], ret.meta[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice we had a bug before: 'This is a excellent movie' is not gramatically correct.  \n",
    "You can set an option in the template to use the right article before a fill-in:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['This is a good movie.',\n",
       " 'This is a great movie.',\n",
       " 'This is an awesome movie.',\n",
       " 'This is an excellent movie.']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = editor.template('This is {a:adj} movie.', adj=['good', 'great', 'awesome', 'excellent'])\n",
    "ret.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, the first argument does not need to be a single string. It can be a list, a tuple, or a dict. The same is true of the `labels` parameter:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'question': 'Is this a good movie?', 'context': 'This is a good movie.'}\n",
      "Yes, this is good.\n",
      "\n",
      "{'question': 'Is this a great movie?', 'context': 'This is a great movie.'}\n",
      "Yes, this is great.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ret = editor.template({'question': 'Is this a {adj} movie?',\n",
    "                       'context': 'This is a {adj} movie.' },\n",
    "                      labels='Yes, this is {adj}.',\n",
    "                      adj=['good', 'great', 'awesome', 'excellent'])\n",
    "print(ret.data[0])\n",
    "print(ret.labels[0])\n",
    "print()\n",
    "print(ret.data[1])\n",
    "print(ret.labels[1])\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lexicons"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The editor has built-in lexicons, which you can use in templates without having to specify the fill-in values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['male', 'female', 'first_name', 'first_pronoun', 'last_name', 'country', 'nationality', 'city', 'religion', 'religion_adj', 'sexual_adj']\n"
     ]
    }
   ],
   "source": [
    "print(list(editor.lexicons.keys()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Michael is not friends with Jennifer',\n",
       " 'Michael is not friends with Jessica',\n",
       " 'Michael is not friends with Ashley',\n",
       " 'Michael is not friends with Sarah']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = editor.template('{male} is not friends with {female}')\n",
    "ret.data[0:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also use different versions of the same tag in a template by adding an integer to the end, e.g.:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Michael is not friends with Michael',\n",
       " 'Michael is not friends with Christopher',\n",
       " 'Michael is not friends with Matthew',\n",
       " 'Michael is not friends with David']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = editor.template('{male1} is not friends with {male2}')\n",
    "ret.data[0:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you set `remove_duplicates` to True, you will never get two fill-ins with the same value within an example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Michael is not friends with Christopher',\n",
       " 'Michael is not friends with Matthew',\n",
       " 'Michael is not friends with David',\n",
       " 'Michael is not friends with James']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = editor.template('{male1} is not friends with {male2}', remove_duplicates=True)\n",
    "ret.data[0:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also use different versions for tags that are not in the lexicons:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['good is not the same as bad',\n",
       " 'good is not the same as great',\n",
       " 'bad is not the same as good',\n",
       " 'bad is not the same as great']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = editor.template('{adj1} is not the same as {adj2}', adj=['good', 'bad', 'great'], remove_duplicates=True)\n",
    "ret.data[0:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, you can also add tags to the lexicons and reuse them later:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "editor.add_lexicon('adj', ['good', 'bad', 'great', 'terrible'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['good is not the same as bad',\n",
       " 'good is not the same as great',\n",
       " 'good is not the same as terrible',\n",
       " 'bad is not the same as good']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = editor.template('{adj} is not the same as {adj2}', remove_duplicates=True)\n",
    "ret.data[:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Masked Language Model Suggestion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use a masked language model to fill-in templates directly by using the special tag `{mask}`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['This is a good idea.',\n",
       " 'This is a good sign.',\n",
       " 'This is a good thing.',\n",
       " 'This is a good example.',\n",
       " 'This is a good start.']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = editor.template('This is {a:adj} {mask}.', remove_duplicates=True)\n",
    "ret.data[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also add multiple masks to a single example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['This is a good history lesson.',\n",
       " 'This is a good chess move.',\n",
       " 'This is a good news story.',\n",
       " 'This is a good programming language.',\n",
       " 'This is a good data set.']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret = editor.template('This is {a:adj} {mask} {mask}.', remove_duplicates=True)\n",
    "ret.data[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Of course, sometimes you want to filter out some of the language model suggestions. You can use `editor.suggest` to just get the suggested words or tuples:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['idea', 'sign', 'thing', 'example', 'start']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "editor.suggest('This is {a:adj} {mask}.')[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('history', 'lesson'),\n",
       " ('chess', 'move'),\n",
       " ('news', 'story'),\n",
       " ('programming', 'language'),\n",
       " ('data', 'set')]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "editor.suggest('This is {a:adj} {mask} {mask}.')[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, you can use a very handy visualization to select suggestions from a list.\n",
    "In the example below, we select only positive adjectives.  \n",
    "(We use a gif here for the notebook to work in preview mode)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# from IPython.display import HTML, Image\n",
    "# with open('visual_suggest.gif','rb') as f:\n",
    "#     display(Image(data=f.read(), format='png'))\n",
    "editor.visual_suggest('This is {a:mask} movie.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# editor.selected_suggestions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Wordnet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also ask for context-specific suggestions based on wordnet categories (synonyms, antonyms, hypernyms, hyponyms):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['spicy', 'raging']"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "editor.synonyms('My drink is hot.', 'hot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# spicy does not fit here\n",
    "editor.synonyms('It is hot outside.', 'hot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['cold']"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "editor.antonyms('My drink is hot.', 'hot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['cold']"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "editor.antonyms('It is hot outside.', 'hot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['animal', 'creature', 'food', 'beast', 'meat', 'mammal', 'person', 'organism']"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "editor.hypernyms('My dog eats other animals.', 'dog')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['dog', 'pet', 'bird', 'prey', 'baby']"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "editor.hyponyms('My animal eats other animals.', 'animal')[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['cat', 'animal', 'monkey', 'pet', 'elephant']"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Hyponyms of hypernym\n",
    "editor.related_words('My dog eats other animals.', 'dog')[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "checklist",
   "language": "python",
   "name": "checklist"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}