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@cs224
Last active September 12, 2022 05:41
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Pandas: easier way to sample interpolated time series data at given times (e.g. every full day)
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Author: cs224\n",
"\n",
"Last updated: 2022-09-12\n",
"\n",
"Python implementation: CPython\n",
"Python version : 3.8.12\n",
"IPython version : 8.2.0\n",
"\n",
"numpy : 1.23.1\n",
"pandas: 1.4.2\n",
"\n"
]
}
],
"source": [
"%load_ext watermark\n",
"%watermark -a 'cs224' -u -d -v -p numpy,pandas"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import numpy as np, pandas as pd, matplotlib.pyplot as plt, seaborn as sns\n",
"\n",
"pd.set_option('display.max_columns', 500)\n",
"pd.set_option('display.width', 1000)\n",
"# pd.set_option('display.float_format', lambda x: '%.2f' % x)\n",
"np.set_printoptions(edgeitems=10)\n",
"np.set_printoptions(linewidth=1000)\n",
"np.set_printoptions(suppress=True)\n",
"np.core.arrayprint._line_width = 180\n",
"\n",
"SEED = 42\n",
"np.random.seed(SEED)\n",
"\n",
"sns.set()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"text/html": [
"<style>.container { width:70% !important; }</style>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from IPython.display import display, HTML\n",
"display(HTML(\"<style>.container { width:70% !important; }</style>\"))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Sample Data at Regular Times"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The function `generate_interpolated_time_series` implements two different methods for generating samples at regular time intervals via `pd.merge` and via `pd.concat`:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def generate_interpolated_time_series(df_in, freq='T', method='reindex', start=None):\n",
" if start is None:\n",
" start = df_in.index[0].floor(freq)\n",
" end = df_in.index[-1]\n",
" \n",
" if method == 'reindex':\n",
" idx = pd.date_range(start=start, end=end, freq=freq)\n",
" ldf = df_in.reindex(df_in.index.union(idx)).interpolate().bfill()\n",
" ldf = ldf[~ldf.index.isin(df_in.index.difference(idx))]\n",
" else: \n",
" df_sampling = pd.DataFrame(index=pd.date_range(start, end, freq=freq))\n",
"\n",
" ldf = None\n",
" if method=='merge':\n",
" ldf = pd.merge(df_in, df_sampling, left_index=True, right_index=True, how='outer')\n",
" elif method=='concat':\n",
" ldf = pd.concat([df_in, df_sampling], axis=1)\n",
" else:\n",
" raise Exception('Method unknown: ' + method)\n",
"\n",
" row = ldf.iloc[0,:]\n",
" ldf.iloc[0,np.arange(len(row))[pd.isnull(row)]] = df_in.bfill().iloc[0,np.arange(len(row))[pd.isnull(row)]]\n",
" ldf = ldf.interpolate()\n",
"\n",
" ldf = ldf.loc[df_sampling.index,:]\n",
" \n",
" return ldf"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Generate Sample Data"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"63072000000.0"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"two_years_in_millis = 1000.0 * 60.0 * 60.0 * 24 * 365 * 2\n",
"two_years_in_millis"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 2253890010, 5950318585, 5992124617, 6120997885, 7395928407, 9019323606, 10232596331, 11511833222, 12283350500, 13498510183, 13667599921, 13920098395, 16931627608, 18171550593, 19114748744, 19831932064, 21478181249, 21505186044, 21609326044, 21717122356, 22367939125, 25826776337, 27684640889, 28389719467, 29190929843, 29992748275, 31498038644, 32514809293, 32860315778, 33309023619, 34428312921, 38855133183, 40586384939, 41092960003, 44667062782, 44922131914, 46298420295, 47343692632, 49663944717, 49871670585, 51275693469, 51426888379, 52327453966, 54103059476, 55118152455, 56223726525, 57514167376, 58958184286, 59814544355, 60874137634, 62785489853, 63064136635])"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# roughly every 2 weeks; year has 52 weeks\n",
"rs = np.random.RandomState(seed=42)\n",
"schedule_millis = np.sort(rs.randint(low=0, high=two_years_in_millis, size=(52,)))\n",
"random_values = rs.randint(low=5, high=500, size=(52,)) * .10\n",
"schedule_millis"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([21.9, 25.6, 19.4, 30. , 21.7, 21.2, 24.1, 34.2, 37.1, 5.7, 28.4, 41.4, 22.1, 25.6, 19.2, 38.4, 49.7, 4.5, 16.1, 1.9, 30.5, 6.9, 34.9, 33.1, 1.3, 34.8, 13.3, 49.6, 14. , 47.6, 6.7, 14.3, 8.5, 39.6, 16.7, 42.3, 29.3, 38.3, 26.5, 49.4, 23.5, 4.5, 3.2, 13.9, 20.5, 33.2, 27.2, 42.2, 3.7, 5.2, 41.1, 6.6])"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"random_values"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"import time, datetime"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1662961270015"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"curr_time = round(time.time()*1000)\n",
"curr_time"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1662879679947"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"now_millis = 1662879679947\n",
"now_millis"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([1665133569957, 1668829998532, 1668871804564, 1669000677832, 1670275608354, 1671899003553, 1673112276278, 1674391513169, 1675163030447, 1676378190130, 1676547279868, 1676799778342, 1679811307555, 1681051230540, 1681994428691, 1682711612011, 1684357861196, 1684384865991, 1684489005991, 1684596802303, 1685247619072, 1688706456284, 1690564320836, 1691269399414, 1692070609790, 1692872428222, 1694377718591, 1695394489240, 1695739995725, 1696188703566, 1697307992868, 1701734813130, 1703466064886, 1703972639950, 1707546742729, 1707801811861, 1709178100242, 1710223372579, 1712543624664, 1712751350532, 1714155373416, 1714306568326, 1715207133913, 1716982739423, 1717997832402, 1719103406472, 1720393847323, 1721837864233, 1722694224302, 1723753817581, 1725665169800, 1725943816582], dtype=int64)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"schedule_millis = schedule_millis + now_millis\n",
"schedule_millis"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>values</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2022-10-07 11:06:09.957</th>\n",
" <td>21.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-11-19 04:53:18.532</th>\n",
" <td>47.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-11-19 16:30:04.564</th>\n",
" <td>66.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-11-21 04:17:57.832</th>\n",
" <td>96.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-12-05 22:26:48.354</th>\n",
" <td>118.6</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" values\n",
"2022-10-07 11:06:09.957 21.9\n",
"2022-11-19 04:53:18.532 47.5\n",
"2022-11-19 16:30:04.564 66.9\n",
"2022-11-21 04:17:57.832 96.9\n",
"2022-12-05 22:26:48.354 118.6"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lds = pd.Series(schedule_millis).apply(lambda t: pd.to_datetime(datetime.datetime.fromtimestamp(t/1000.0)))\n",
"ldf = pd.DataFrame(random_values, index=lds.values, columns=['values'])\n",
"ldf = ldf.cumsum()\n",
"ldf.head()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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ffqxjSZevqdv0rGupadmoFB6fpVfnUykYDhw4wMmTJ/nlL3/JuHHjuO++++jRoweVlZUsXLiQo0ePOp9KSdRUjfoeWGoeNiqFx6X0mspzaiTu6UbNbt++fZw7d47c3Fw6dOhAZWUltbW1dOnShdraWjIyMnjooYe44YYbmDFjBg0NDVRUVNC5c2fg/D0m4vE4aWlp1NTU0KZNmyQfkdR6NfbatWvXxOVJ09LSOHXqFLNnz6a4uJjbb7+dnj17UlFRwaxZs6ioqEjcw+XcuXNEo1GiUS+UIjUl25SCzUal8LjcXp1PpZbT2Gu3bt244oorqK+vJxaLceTIEZYsWUJhYSGzZ8/mzJkz/Pa3v6WysjJxH2Hw9VVqbjYqBZuNSuFxub2m6pzqN/mbUWVlJY8//jgffPAB3bt3p6amhmeeeSZx3zM4f+mI6upqjhw5wowZMwCIRqMfe2JeeAm1VHliSi3tf/W6aNEievToAZzvcubMmdxyyy0AHDx4kKlTp3L11Vdz9913U19fD0Bamv+sSk3JNqVgs1EpPJqqV+dTqfl9Wq8ffvghR48eJSMjg+eee45+/foxfvx4Bg4cyPTp04Hznyf5+io1DxuVgs1GpfBoql5TdU71FKRmcvDgQWbNmkVWVhYbNmygsLCQvLw8nnrqqf/32P/85z+kpaUlnrQX8h5pUvP7pF4b7/ECkJOTk/jA89y5c+Tl5XHTTTfx/vvvA+dbtVepadmmFGw2KoWHvUrhcSm95ubm0rdvXwBefPFF2rRpw759+5gyZQpt27YF/DxJai42KgWbjUrhYa+Xz03+ZlJVVcVtt93GE088AUB+fj6jRo2ibdu2nD17FoDGOyVs376dvLw8MjMzeeWVV7jrrrvYtGlT0tYupZpL6bVRQ0MDaWlpRKNRTpw4wdChQ5OxZCkl2KYUbDYqhYe9SuFxsV7PnDkDnL836apVqxgzZgwbN27k2WefBWDNmjVJW7eUKmxUCjYblcLDXi+f1xtpInv27GHv3r306NGD66+/nmuvvZauXbuSk5NDQ0MD0WiUkpISTp8+TWZmJgCRSASArVu3UldXx+TJkyktLeXRRx9l2LBhyTwcqVX7PL0CnDlzhtOnT1NWVkZhYSHp6el8+ctfTuKRSK2LbUrBZqNSeNirFB6fpdfGbysNGzaMfv36MXLkSCZMmEA0GmXx4sVkZWUl+Wik1sdGpWCzUSk87LXpucl/mRoaGli0aBFr1qxh6NChvPvuu0yfPp0777yTLl260NDQkHjs7t27GTFiROLP8Xic6upqtm7dykcffURBQQEPPvhgMg5DSgmX0yvARx99xM9//nO2bNnC3XffzQ9+8IOWPgSpVbJNKdhsVAoPe5XC43J6zc7O5oUXXiA9PT3xs5EjR7bo+qXWzkalYLNRKTzstfm4yX+Zjh07xj//+U/Wrl1Lz549+eMf/8jq1as5e/Ys06ZNIxqNUl9fD8Dhw4eZOHFi4v+tra0lJyeHadOmMXr0aLKzs5N1GFJKuJxea2pqyM3NZdKkSSxYsCBxJpmky2ebUrDZqBQe9iqFx+V+npSRkZH4xpOkpmejUrDZqBQe9tp8/Bv5HI4fP05dXR0Au3bt4sCBA/Ts2ZP6+nq+8Y1vMHLkSHbs2MFbb70FQCwW4/Dhw9TV1dG/f382btxI3759WbZsGQDjxo1zg19qJk3V6/LlywG4+eab/cBTagK2KQWbjUrhYa9SeDRVry+++CKAH3RKTcxGpWCzUSk87LVl+E3+z+DQoUPMnz+feDwOwMyZM7nmmmvIzs7m73//O4MGDQLgjjvuYM+ePWzbto0hQ4bQtm1bNm7cSFVVFffeey8HDx5k/vz5jB07NolHI7Vu9ioFk21KwWajUnjYqxQe9ioFm41KwWajUnjYa8vy1IdLtHbtWqZMmUKfPn1YtGgR7du356WXXuLgwYMMHjyYN954I/HY3Nxcrr/+evbu3Zu4l8Thw4cpKytj4MCBvPPOOz4xpWZkr1Iw2aYUbDYqhYe9SuFhr1Kw2agUbDYqhYe9tjw3+S9RaWkpDz74IHPnzqVr1648+eSTFBUV0alTJ7761a9y9OhRXnvttcTjBw4cyHvvvUd1dTUAI0eOZNOmTUyfPj1ZhyClDHuVgsk2pWCzUSk87FUKD3uVgs1GpWCzUSk87LXlebn+SzRx4kTS09MBqKmpoV27dnTo0IGzZ88yePBg9u3bx9KlS7nmmmvo3bs3O3fuZPjw4XTo0AGAAQMGJHH1UmqxVymYbFMKNhuVwsNepfCwVynYbFQKNhuVwsNeW56b/Jeoa9euAMTjcdq0acP+/fs5d+4c1113HVlZWUyZMoUjR47wyCOPkJGRQWlpKYWFhWRkZCR55VLqsVcpmGxTCjYblcLDXqXwsFcp2GxUCjYblcLDXluem/yfUSQSAeD9998nLy+PrKwsAK644goWLVrE0aNH2bVrF6NGjUrmMiVhr1JQ2aYUbDYqhYe9SuFhr1Kw2agUbDYqhYe9thw3+T+j+vp6YrEY27ZtY/DgwQCsXr2aoqIiZs6cSX5+Pt26dUvyKiWBvUpBZZtSsNmoFB72KoWHvUrBZqNSsNmoFB722nLc5P+MYrEYdXV1HDt2jO7du/Od73yHsrIyCgsLyc/PT/byJF3AXqVgsk0p2GxUCg97lcLDXqVgs1Ep2GxUCg97bTlu8n8OBw4cYPPmzezevZupU6dSUFCQ7CVJ+gT2KgWTbUrBZqNSeNirFB72KgWbjUrBZqNSeNhry4jE4/F4shcRNrW1taxatYrvfve7ZGRkJHs5ki7CXqVgsk0p2GxUCg97lcLDXqVgs1Ep2GxUCg97bRlu8kuSJEmSJEmSJEmSFBLRZC9AkiRJkiRJkiRJkiRdGjf5JUmSJEmSJEmSJEkKCTf5JUmSJEmSJEmSJEkKCTf5JUmSJEmSJEmSJEkKCTf5JUmSJEmSJEmSJEkKCTf5JUmSJEmSJEmSJEkKCTf5JUmSJEmSJEmSJEkKCTf5JUmSJEmSJEmSJEkKCTf5JUmSJEmSJEmSJEkKif8DYeZWA6OsdzIAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 2560x640 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(32, 8), dpi=80, facecolor='w', edgecolor='k')\n",
"ax = plt.subplot(1, 1, 1)\n",
"ldf.plot(ax=ax)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Apply to Sample Data"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Timestamp('2022-10-07 00:00:00')"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"start = ldf.index[0].replace(second=0,microsecond=0,nanosecond=0,minute=0,hour=0)\n",
"start"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_sampled_1 = generate_interpolated_time_series(ldf, freq='D', method='merge', start=start)\n",
"df_sampled_2 = generate_interpolated_time_series(ldf, freq='D', method='concat', start=start)\n",
"df_sampled_3 = generate_interpolated_time_series(ldf, freq='D', method='reindex')\n",
"all([df_sampled_1.equals(df_sampled_2),df_sampled_1.equals(df_sampled_3)])"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>values</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2022-10-07</th>\n",
" <td>21.900000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-10-08</th>\n",
" <td>22.481818</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-10-09</th>\n",
" <td>23.063636</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-10-10</th>\n",
" <td>23.645455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-10-11</th>\n",
" <td>24.227273</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" values\n",
"2022-10-07 21.900000\n",
"2022-10-08 22.481818\n",
"2022-10-09 23.063636\n",
"2022-10-10 23.645455\n",
"2022-10-11 24.227273"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_sampled_1.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In the following graph you can see that the sampled data overlays the ground truth data nicely as the orange nicely covers the blue."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 2560x640 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(32, 8), dpi=80, facecolor='w', edgecolor='k')\n",
"ax = plt.subplot(1, 1, 1)\n",
"ldf.plot(ax=ax)\n",
"df_sampled_1.plot(ax=ax)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Rolling Windows"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sometimes you want to know summary data for rolling windows like \"a month\" (30 days) or \"a year\" (365 days). With the `pandas.rolling` function that is nicely doable:"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 2560x640 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(32, 8), dpi=80, facecolor='w', edgecolor='k')\n",
"ax = plt.subplot(1, 1, 1)\n",
"df_sampled_1['values'].diff().fillna(0.0).rolling(window=30).sum().to_frame().plot(ax=ax)"
]
},
{
"cell_type": "code",
"execution_count": null,
"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": "3.8.12"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": true,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}
@cs224
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cs224 commented Sep 11, 2022

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