From af207ffca7ec04d215bbb5f86a0fc413fde10290 Mon Sep 17 00:00:00 2001 From: cheng Date: Tue, 28 Nov 2023 21:39:30 +0000 Subject: [PATCH] update notebook --- notebooks/news_recommendation_byom.ipynb | 135 +++++++++++++----- src/learn_to_pick/pytorch/feature_embedder.py | 4 +- src/learn_to_pick/pytorch/policy.py | 6 +- 3 files changed, 106 insertions(+), 39 deletions(-) diff --git a/notebooks/news_recommendation_byom.ipynb b/notebooks/news_recommendation_byom.ipynb index b74f4ca..6f8c45e 100644 --- a/notebooks/news_recommendation_byom.ipynb +++ b/notebooks/news_recommendation_byom.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 37, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -21,17 +21,104 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n", + "To disable this warning, you can either:\n", + "\t- Avoid using `tokenizers` before the fork if possible\n", + "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Processing /home/chetan/dev/learn_to_pick\n", + " Preparing metadata (setup.py) ... \u001b[?25ldone\n", + "\u001b[?25hRequirement already satisfied: numpy>=1.24.4 in /anaconda/envs/learn_to_pick/lib/python3.10/site-packages (from learn-to-pick==0.0.3) (1.26.1)\n", + "Requirement already satisfied: pandas>=2.0.3 in /anaconda/envs/learn_to_pick/lib/python3.10/site-packages (from learn-to-pick==0.0.3) (2.1.1)\n", + "Requirement already satisfied: vowpal-wabbit-next==0.7.0 in /anaconda/envs/learn_to_pick/lib/python3.10/site-packages (from learn-to-pick==0.0.3) (0.7.0)\n", + "Requirement already satisfied: sentence-transformers>=2.2.2 in 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sha256=bee6266df7b0bde64de2e58bff8c435340c315aa8fa9cfa3c84751c22a26fab1\n", + " Stored in directory: /tmp/pip-ephem-wheel-cache-zigo2ps9/wheels/18/bf/25/d8dda8a9a6b5284eaed510a4708ef9b22b9894a5e94b329ea2\n", + "Successfully built learn-to-pick\n", + "Installing collected packages: learn-to-pick\n", + " Attempting uninstall: learn-to-pick\n", + " Found existing installation: learn-to-pick 0.0.3\n", + " Uninstalling learn-to-pick-0.0.3:\n", + " Successfully uninstalled learn-to-pick-0.0.3\n", + "Successfully installed learn-to-pick-0.0.3\n" + ] + } + ], "source": [ - "# ! pip install ../\n", + "! pip install ../\n", "# ! pip install matplotlib" ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -62,7 +149,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -82,7 +169,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -126,17 +213,7 @@ }, { "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [], - "source": [ - "from learn_to_pick import PyTorchFeatureEmbedder\n", - "fe = PyTorchFeatureEmbedder() #auto_embed=True" - ] - }, - { - "cell_type": "code", - "execution_count": 43, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -150,17 +227,15 @@ "source": [ "from learn_to_pick import PyTorchPolicy\n", "\n", - "picker = learn_to_pick.PickBest.create(\n", - " metrics_step=100, metrics_window_size=100, selection_scorer=CustomSelectionScorer())\n", "pytorch_picker = learn_to_pick.PickBest.create(\n", - " metrics_step=100, metrics_window_size=100, policy=PyTorchPolicy(feature_embedder=fe), selection_scorer=CustomSelectionScorer())\n", + " metrics_step=100, metrics_window_size=100, policy=PyTorchPolicy(), selection_scorer=CustomSelectionScorer())\n", "random_picker = learn_to_pick.PickBest.create(\n", " metrics_step=100, metrics_window_size=100, policy=learn_to_pick.PickBestRandomPolicy(), selection_scorer=CustomSelectionScorer())" ] }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -169,11 +244,6 @@ "for i in range(2500):\n", " user = choose_user(users)\n", " time_of_day = choose_time_of_day(times_of_day)\n", - " picker.run(\n", - " article = learn_to_pick.ToSelectFrom(articles),\n", - " user = learn_to_pick.BasedOn(user),\n", - " time_of_day = learn_to_pick.BasedOn(time_of_day),\n", - " )\n", "\n", " random_picker.run(\n", " article = learn_to_pick.ToSelectFrom(articles),\n", @@ -197,21 +267,20 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "The final average score for the default policy, calculated over a rolling window, is: 0.97\n", - "The final average score for the default policy, calculated over a rolling window, is: 0.81\n", - "The final average score for the random policy, calculated over a rolling window, is: 0.55\n" + "The final average score for the default policy, calculated over a rolling window, is: 0.93\n", + "The final average score for the random policy, calculated over a rolling window, is: 0.53\n" ] }, { "data": { - "image/png": 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", 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PDHoRHtkJnUdbv8+N3kX9fb5jHjx1TE2qGvUBxagWTv84Ad5tCb88qiZIDrglXe0bGVEUdfmeFty8LfpPtWjRIiZMmMC2bdvYsWMHDz74II0aNeL+++/nlVdeYfv27fTo0QOA3bt3s2/fPn766SeCg4M5fPgwGRkZLFiwAIDAwECys7MZMmQIvXv3Zvv27SQnJ/PAAw8wdepUFi5caL7u2rVr8fPzY80adeg6KyuLAQMG0KBBA3755RdCQ0PZtWsXxlJ/rGJjY1mxYgW//fYbFy9eZOTIkbz55pu8/vrrVnjihLCh48VTNJHX/PedYb+n1D/OsWthyRh4cD14XnkzryorzIU/nlVvO9IKln5PqqtqkvarUwcd77Tt9TLi4e/XYM9iQFEbzvWarO6d4+lv22tXlX9DuO83WPe6utvx9i/g7Da4c6Hlxca5F2Hju7D1M3UZt04PXcbAoBfAN8Qm4f+Hpx90Hat+pMXB3u9h73dqofCuRepHYFPodDd0GuUwK4pqXzJSmANvaDRH9nw8uPtU+fCIiAg++OADdDodrVq1Yv/+/XzwwQdMnDiRIUOGsGDBAnMysmDBAgYMGEDTpk0B8PLyIj8/n9DQUPP5Fi1aRF5eHl999RU+Pmocc+bMYdiwYbz11luEhKj/GXx8fPjiiy/M0zOff/45KSkpbN++ncDAQACaN29eJlaj0cjChQvx9fUFYMyYMaxdu1aSEeH4ThQv6S1vWkKvh9vnqUP0abHwy1S4c1HN36lv/hAunVb3h+n/dM3OZU3egeqKnr//T/1oe6ttCjcLstXnYMuHJW8O29+hFtLWbWz969WUi5u6BLrxNbD8QbWW6LP+MOx/0GFE5Y8vKlBrNTa8pSYkAM0Gq3UwIW1tGnqFApuqo38DnoPTm9Wk5OAKNUlZ95r60aS/mpi0vcWi1y9rk2kaDfXq1QtdqT96vXv35vjx4xgMBiZOnMh3331HXl4eBQUFLF68mPvvv7/C8x0+fJhOnTqZExGAvn37YjQaOXr0qPm+Dh06lKkT2bNnD126dDEnIuWJjIw0JyIAYWFhJCcnW/TzCmF3+VlwJka9faUaCZ96MHKROp1y6Ge1F0VNXDylrqAB9cXIWstTraXXZLWHx6XTaiGpNRkNsOtr+LArbHhTTUQiouCBtWpfD0dMREprEa1O2zTuCwVZ6vTGr4+pI13lURS1RuOTKFj1nJqIBLeFe3+EMT9pm4iUptdDk34w/BN1Gmf4XDUJATi5EVZMgndawNFVmoVY+0ZG3LzVEQqtrm0lw4YNw8PDg+XLl+Pu7k5hYSEjRlQhQ6+C0skKqKMslXFzcyvztU6nKzONI4RDOvWPWkAa0Fhd1nslDburq13+eFrt0BneFRpFVe+aq56Hojz1j32726p3Dlty94EBz8LKabDhbbVw18O38sdVJnad+twlHVC/rhsJ0a+ooy9a18tYwi8cxv6ijnJsfAd2LoSz29Vpm/otS447v0v9eU9vVr/2CYZrX4DO99p/qwFLeNRR61Y6j1anbvYuUVdZpZ2E0A6aheXAz1g16XSaDjVZ4vIC0X///ZcWLVrg4qJ2Gxw3bhwLFizA3d2du+66q0zS4O7ujsFgKPP4Nm3asHDhQrKzs80Jx+bNm9Hr9eZC1fJ07NiRL774grS0tApHR4RwOqWnaCp7Qew5UV3ieeBHWHofTPoHfIIsu97xNXB0Jehd4YZ3HPdFuOtYdZ+ctFjYMkddaVNdyUfUFTLH/1S/9vSH/s+oz6ezbkzn4qomFo37wE8PQvJB+Hwg3Py+Omqy9lXY/4N6rKsX9JmqTn9ZI6mzp4BGMOBp6P8UJB9WV5lpRKZpNHTmzBmmTZvG0aNH+e677/joo4947LGSnTwfeOAB/v77b1atWvWfKZrIyEj27dvH0aNHSU1NpbCwkHvuuQdPT0/GjRvHgQMHWLduHY888ghjxowx14uUZ/To0YSGhjJ8+HA2b95MXFwcP/74IzExMTb72YWwOUUpKV6tyjJWnU6tEQhqqe6s++MEddqhqory1Z4lAFGTILi15THbi4sbDH5JvR0zB7KqMeWalQK/PQGf9lETEb2r2kDs0T3qi7OzJiKlNRukTts0GQCF2bD8Ifiwc0ki0mm0ukLm2hedLxEpTafTfEpJkhENjR07ltzcXHr27MmUKVN47LHHePDBB83fb9GiBX369KF169ZERZUdMp44cSKtWrWie/fu1K9fn82bN+Pt7c3q1atJS0ujR48ejBgxgsGDBzNnzpwK43B3d+fPP/8kODiYG2+8kQ4dOvDmm2+aR2iEcEppcWpdhN6tZH68Mh6+art0N2+IW2/Z5nIxc9Rr1glRp0EcXdvh6nRUQZY6HVFVhblqO/MPu8CO+Wpn29Y3w5RtcMObapFsbeIbAmOWqytidHowFkFkP3hwA9w2V9PRhNpEpygOuOD4MhkZGfj7+5Oeno6fX9lld3l5eZw8eZImTZrg6ek8ffkHDhxI586dmT179hWPURSFFi1a8PDDDzNtmkZtpGvIWf99RC3w71xY9ayaiIz71bLH7vsBfpoI6OCeZWphY0UunVV3mi3MUVfndBxZ7bDtKm6D2v9D7wZTt6mrL67EaFSbpq19VW1vDxDWWa21Kd2/pTZL2Ku2sY/s57hTcA6motfv0mRkxEGlpKQwZ84cEhMTGT9+vNbhCOF8KlrSW5mOI6H7BECBnx5Qk42K/PmCmog06gMdbNy7w5qaDlCXoBoL4e8Klumf3gJfDFYTtPSz4NcQbvscJq67ehIRUNu4N+kviYgN1L4C1loiODiYoKAgPv/8c+rWrat1OEI4l8JcOLVJvd38uuqdY+gsiN+ltgpfOk7dz6S8nhyx69QlwToXuNGBi1avJHqm2vTtwDJ1t9zS+8NciIU1M+DIb+rX7nXgmifURm4O3FpcOB9JRjRiat9+JU4weyaE4zq9GYpy1b1AgttU7xyuHmoDtM/6qy29/3wRbny77DFFBSVFqz0nQuh/t3FweGGdoP0INRn56xW1P0ZOmlpHsm1eSSfRruPUBlp1grWOWNRCMk0jhKh9zBvjDa7ZSEXdxnD75+rtbZ/B/mVlv7/1U3WvFZ/6MLAGy2O1du2Lat1I7FpY+ZRanPrvJ2oi0vw6mLwFhs2WRETYjCQjQojax1Qv0qKaUzSltRyi7ukC6kZjKcXdjDPi1aZhoDb38gqo+bW0EtgEuhfXpm2fB3mXILiduork3mXVH10SoopqTTIi0xqOSf5dhN1dPK2OVuhc1P4Q1jDweXUFRWG2uhtrQTb8+ZK6LLZhT7XfhLPr/4y6l06dEHXX10n/qDvBCmEHTl8zYuqFUVBQUKW25sK+cnLUTbIubycvhM2YRkUielpvtMLFVd1bZW4/SDkCX98GZ7cCOrjpXetvCa+FOvXh0d3qdE1t+HmEU3H6ZMTV1RVvb29SUlJwc3NDL/+JHIKiKOTk5JCcnExAQIA0UBP2Y64XqcaS3orUCYY7F8DCm4sTEaD7/WVXnzi72tA1VTglp09GdDodYWFhnDx5ktOnT2sdjrhMQEAAoaGhWochrhZFBXByg3rb2skIqHuVRL+s7sXiFagWfgohaszpkxFQ25m3aNGCgoICrUMRpbi5ucmIiLCvs/+qdRw+9SG0o22u0ecRtQV4UKva1/pcCI3UimQEQK/XS7txIa52pbuu2mrKVqeD9nfY5txCXKWkwEIIUXscr0ELeCGEZiQZEULUDhnxkHwQ0EHTQVpHI4SwgCQjQojawbSKpkE38KmnbSxCCItIMiKEqB1OrFE/yxSNEE5HkhEhhPMzFEHsevW2JCNCOB1JRoQQzu/8DshPB6+60KCr1tEIISwkyYgQwvmZlvQ2uxb00ttGCGcjyYgQwvkdl3oRIZyZJCNCCOeWlQIJe9TbzQZrGooQonokGRFCOLfYv9XPoR3BN0TbWIQQ1SLJiBDCucmSXiGcniQjQgjnZTSUNDtrcZ22sQghqk2SESGE80rYA7lp4OEHDXtoHY0QopokGRFCOC/TxnhNB4CLm7axCCGqTZIRIYTzMvUXaS5TNEI4M0lGhBDOKSdN7bwK0FyW9ArhzCQZEUI4p7h1oBihfhvwb6h1NEKIGpBkRAjhnMyraGRJrxDOTpIRIYTzUZRS9SKSjAjh7CQZEULYTlGBbc6buB+yksDNBxr1ts01hBB2I8mIEMI2EvbBmxHw3d1QkGPdc5tGRZr0B1cP655bCGF3kowIIWxj+xdQlAdHV8I3d0BeuvXObaoXkVU0QtQKkowIIayvKB8OrVBvu7jDmS2w8GZ1h92aysuAs/+qt6VeRIhaQZIRIYT1Hf9THQnxDYcJa8CnPiTugwVD4dLZmp375AYwFkG95hDYxDrxCiE0Va1k5OOPPyYyMhJPT0+ioqLYtm1bhcfPnj2bVq1a4eXlRUREBE888QR5eXnVClgI4QT2/aB+7nAHhHeG8avAPwIunID5QyH1ePXPLatohKh1LE5GlixZwrRp05g5cya7du2iU6dODBkyhOTk5HKPX7x4Mc899xwzZ87k8OHDfPnllyxZsoTnn3++xsELIRxQ7iU4tkq93XGU+jmoOdy/GoJaQsY5mD8E4vdYfm5FKVUvIsmIELWFxcnI+++/z8SJExk/fjxt27Zl7ty5eHt7M3/+/HKP37JlC3379uXuu+8mMjKS66+/ntGjR1c6miKEcFKHfgZDAQS3hZD2Jff7N1BHSMI6Q84FtYbk1GbLzp1yFNLPgqsnRF5j1bCFENqxKBkpKChg586dREeXvCPR6/VER0cTExNT7mP69OnDzp07zclHXFwcv//+OzfeeOMVr5Ofn09GRkaZDyGEk9i/VP3c4U7Q6cp+z6cejPsVGl8DBZnwze1wbHXVz22aomncF9y8rBOvEEJzFiUjqampGAwGQkJCytwfEhJCYmJiuY+5++67efXVV7nmmmtwc3OjWbNmDBw4sMJpmlmzZuHv72/+iIiIsCRMIYRW0s/BqX/U2x3uLP8YTz+4dxm0vEFd+vv93bBvadXOL/UiQtRKNl9Ns379et544w0++eQTdu3axU8//cTKlSv5v//7vys+Zvr06aSnp5s/zp6tYfW9EMI+9i9TPzfuCwEVvIlw84JRX6s1JcYi+GkibJtX8bkLsuF08bROi+usE68QwiG4WnJwUFAQLi4uJCUllbk/KSmJ0NDQch/z0ksvMWbMGB544AEAOnToQHZ2Ng8++CAvvPACev1/8yEPDw88PKSrohBOx7SKpuPIyo91cYPhc8HTH7Z9Dr8/BXmXoN9T/53eATi1Sa1FCWikLusVQtQaFo2MuLu7061bN9auXWu+z2g0snbtWnr3Ln9/iJycnP8kHC4uLgAoimJpvEIIR5V4AJIPqk3O2t5atcfo9XDD2zDgWfXrv1+DP19UV81crvQUTXnJihDCaVk0MgIwbdo0xo0bR/fu3enZsyezZ88mOzub8ePHAzB27FgaNGjArFmzABg2bBjvv/8+Xbp0ISoqihMnTvDSSy8xbNgwc1IihKgF9hePirS4HrzqVv1xOh0Meh48A2D1dIiZo46Q3Pw/cCn1J+r4GvVzc5miEaK2sTgZGTVqFCkpKcyYMYPExEQ6d+7MqlWrzEWtZ86cKTMS8uKLL6LT6XjxxRc5f/489evXZ9iwYbz++uvW+ymEENoyGkuKUE29RSzV+2F1yuaXqbD7G7WD6x1fqhvhXYiFiydB7wZN+lkvbiGEQ9ApTjBXkpGRgb+/P+np6fj5+WkdjhDicic3wqJhajLx5DFw86z+uQ7/CsvuV+tDmg6EUd/CnsXwx9MQ2Q/u+81qYQshbKuqr9+yN40QouZMhattb61ZIgLQZhjcsxTcfCBuPXx1a8mme7KKRohaSZIRIbSmKGrxp6FI60iqpzBP7boK1Z+iuVzTgTDuF7WO5PyOkiW90l9EiFpJkhEhtHZwOcztq64icUbHV0N+Bvg1hEZ9rHfeht1h/B9Qp7htgG+42mJeCFHrSDIihNbi1qmfd38N+VnaxlId5h16R6hLda0ppC1MWA2tboLrXpElvULUUpKMCKG1xAPq54KskukOZ5GTVrK3jLWmaC5XNxJGL65aIzUhhFOSZEQILRmKIPlQyde7v9Euluo49DMYC9XdeUNkCkUIUT2SjAihpbRYdbM4V0/Q6eHMFkg9oXVUVWdJ+3chhLgCSUaE0FLifvVzaMeSzqJ7nGR05NIZNXlCB+1HaB2NEMKJSTIihJbMyUh76HKvenvPd86xzHd/ccfVyGvAv4G2sQghnJokI0JoKam4eDWkPbQcCt71ICsRYtdW/DitKUqpKRobFa4KIa4akowIoaXS0zSu7tDxLvXr3V9rF1NVJO6HlCPg4gFtb9E6GiGEk5NkRAitZCVDVhKgK1mJYpqqOfoHZKdqFlql9i1RP7caqu5HI4QQNSDJiBBaMY2K1GsG7j7q7ZC2EN4VjEUlL/iOxmiAAz+qt2WKRghhBZKMCKGV0vUipXUdo37e9bVam+FoTv0DmQnqvjHNZeM6IUTNSTIihFZMnVdDL0tG2t+h9h1JOQznd9k/rsqYClfb3abWuQghRA1JMiKEVkoXr5bm6Q9tb1VvO1oha2EuHPpFvS2NzoQQViLJiBBaKMyD1GPq7cunaaCkkPXAj1CQY7+4KnP0DyjIBP9GENFL62iEELWEJCNCaCHlMCgG8AoEv/D/fr/xNRDQGPIz4PCv9o/vSkyNzjreaf0deoUQVy35ayKEFkrXi+h0//2+Xl8yOuIoUzXZF+D4n+rtDjJFI4SwHklGhNCCeSVNhysf0/luQKeuXkmLs0tYFTq0XF1yHNoRgltrHY0QohaRZEQILZiLVytIRvwbQrNr1dt7Fts+psrsM03RyKiIEMK6JBkRwt4U5crLei9n3jxvsdpsTCsXT8HZf5EdeoUQtiDJiBD2ln4W8tNB7wZBrSo+tvVN4FUXMs5D3Dr7xFceU+Fq0wHgF6ZdHEKIWkmSESHszTRFU7915U3DXD1KikV3f2PbuK6k9A69UrgqhLABSUaEsLeqTtGYmKZqjqyEnDTbxFSRhD1qTxRXT2gzzP7XF0LUepKMCGFvifvUzxUVr5YW1hHCOoGhoGSEwp5MhautbgRPP/tfXwhR60kyIoS9XWmDvIp0Kd48b7edN88zFMGBZeptWUUjhLARSUaEsKe8DHVlClR9ZATUzfNcPNREJmGvTUIr18kNkJWkdoptNth+1xVCXFUkGRHCnpIOqp/9GoB3YNUf5x0IbW5Wb9uzkNW0ikZ26BVC2JAkI0LYU3WmaExMhaz7f1B3z7W1gpySfXE6jrL99YQQVy1JRoSwJ0uLV0trMgD8IyAvXV1ZY2tHf4eCLHXDvoietr+eEOKqJcmIEPZk6bLe0vQuxfvVYJ/N80wrdzqOLH8zPyGEsBJJRoSwF0MRJB9Sb1e0QV5FOt+jfo7bABdPWyeu8mSnwom/1NvS6EwIYWOSjAhhL2mxUJQHbj4Q2KR656jbWJ2uQYG931k1vDIOLgfFAGGdoX5L211HCCGQZEQI+zG1gQ9pq065VJe558i3YDTWPK7y7FuifpbCVSGEHUgyIoS9mJORatSLlNbmZvDwh/Qzah8Qa0s8AOe2g06v9jcRQggbk2RECHsxLeutzkqa0ty8oMMI9ba1e44cXA4LblBvN48G3xDrnl8IIcohyYgQ9pJopWQESnqOHP4Vci/W/HyFefDbNFh6H+RnQEQvGPZhzc8rhBBVIMmIEPaQlQJZiYAOgtvW/HzhXdTpHkM+7F9Ws3NdiIUvo2HHl+rX10yD+1aCX1jN4xRCiCqQZEQIe0gqrhcJbAoedWp+Pp2uZHSkJlM1+5fBZ/3VehbvILj3R4ieCS6uNY9RCCGqSJIRIeyhJs3OrqTDSNC7QcKekuLYqirMhV8egR8nqF1WI/vBpE1qnYgQQtiZJCNC2IMpWbBGvYiJTz1ofaN625LRkZSjMO9a2PUVoIMBz8LYn2VaRgihGUlGhLAH8wZ5VkxGoKTnyL4lUJRf+fF7FsPnA9VOsD7BMHYFDHq+Zn1PhBCihiQZEcLWCvPU0Qiw7sgIQLNrwTdcXVFz9PcrH1eQDcsnw4rJUJijdnGdtAmaDrRuPEIIUQ2SjAhhaylH1NbqXnXBL9y65y6zed4VpmqSDsHng2DvYrWR2aAXYcxy6SEihHAYkowIYWvmKZr2ttn91pSMnFgL6edK7lcUtS5k3iBIPQq+YTDuVxjwtEzLCCEciiQjQtiauXi1o23OX68ZNL4GUGBP8eZ5+Znw04PqipmiPHWVzKRNEHmNbWIQQogakGRECFuzxbLey5l6juz5BhL2qkWq+38AnQtEvwx3LwWfINtdXwghakCSESFsSVFss6z3cm1vAXdfuHhKrQ+5cAL8GsD43+GaJ0Av/9WFEI5L/kIJYUvpZyE/XW1OFtTKdtdx94H2t6u3FQO0HKpOyzTqZbtrCiGElUjPZyFsyTRFU78VuLrb9lr9n4LMBHW5b9Qk2xTLCiGEDUgyIoQt2WOKxiSgEdyz1PbXEUIIK5NpGiFsybRBXogNi1eFEMLJSTIihC2ZR0YkGRFCiCuRZEQIW8nLUFe3gPX3pBFCiFpEkhEhbCX5kPrZN1zdYVcIIUS5qpWMfPzxx0RGRuLp6UlUVBTbtm2r8PhLly4xZcoUwsLC8PDwoGXLlvz+ewWbeglRG9izeFUIIZyYxatplixZwrRp05g7dy5RUVHMnj2bIUOGcPToUYKDg/9zfEFBAddddx3BwcEsW7aMBg0acPr0aQICAqwRvxCOS+pFhBCiSixORt5//30mTpzI+PHjAZg7dy4rV65k/vz5PPfcc/85fv78+aSlpbFlyxbc3NwAiIyMrFnUQjiDRFlJI4QQVWHRNE1BQQE7d+4kOjq65AR6PdHR0cTExJT7mF9++YXevXszZcoUQkJCaN++PW+88QYGg+GK18nPzycjI6PMhxBOxWiA5MPqbVttkCeEELWERclIamoqBoOBkJCQMveHhISQmJhY7mPi4uJYtmwZBoOB33//nZdeeon33nuP11577YrXmTVrFv7+/uaPiIgIS8IUQnsXYqEoF9y8IbCJ1tEIIYRDs/lqGqPRSHBwMJ9//jndunVj1KhRvPDCC8ydO/eKj5k+fTrp6enmj7Nnz9o6TCGsK3Gf+jmkHehdtI1FCCEcnEU1I0FBQbi4uJCUlFTm/qSkJEJDQ8t9TFhYGG5ubri4lPxBbtOmDYmJiRQUFODu/t/9Ojw8PPDw8LAkNCEcS1LxnjRSLyKEEJWyaGTE3d2dbt26sXbtWvN9RqORtWvX0rt373If07dvX06cOIHRaDTfd+zYMcLCwspNRISoFUwb5MlKGiGEqJTF0zTTpk1j3rx5LFq0iMOHDzN58mSys7PNq2vGjh3L9OnTzcdPnjyZtLQ0HnvsMY4dO8bKlSt54403mDJlivV+CiEcjXlZrxSvCiFEZSxe2jtq1ChSUlKYMWMGiYmJdO7cmVWrVpmLWs+cOYNeX5LjREREsHr1ap544gk6duxIgwYNeOyxx3j22Wet91MI4UiyUiArEdBBcFutoxFCCIenUxRF0TqIymRkZODv7096ejp+fn5ahyNExWL/hq9vg8Cm8OhuraMRQgjNVPX1W/amEcLazPUi0gZeCCGqQpIRIazNvJJGkhEhhKgKSUaEsDbZIE8IISwiyYgQ1lSYB6nH1NuyrFcIIapEkhEhrCnlCBiLwDMA/BpoHY0QQjgFSUaEsKakUsWrOp22sQghhJOQZEQIa5KVNEIIYTFJRoSwJileFUIIi0kyIoS1KAokFScjskEeRqPC5hOppGUXaB2K2Y5TaaRk5msdRq13NDGTo4mZWochnIjF7eCFEFeQfhby0kHvCvVbaR2NpooMRp79cT8/7jpH/5b1+er+nlqHxLaTaYz8LIZGgd788Vg/fDzkz58tHE3M5OaP/qHQoHBzxzCeHdqaiEBvrcMSDk5GRoSwFlO9SP3W4OqhbSwayis0MPnbXfy46xwAm46nOMRoxPLdajxn0nJ4848jGkdTOymKwoyfD1BoUHcZ+W1fAoPf28Cs3w+TnluocXTCkUkyIoS1mDuvXr1TNFn5RYxfsJ01h5Jwd9UT5u+JUYFVBxM1javIYGTVgZIYvv73NFtOpGoYUe30674Etp5Mw8NVzxdju9O3eT0KDEY+2xjHwHfWsWjLKQoNRq3DFA5IkhEhrCVxn/r5Km12djG7gHvm/UtM3AV83F1YOL4H9/dtAsDKffGaxhYTd4GLOYXU83FndM8IAJ5eto+s/CJN46pNsvKLeH3lIQCmDGpOdNsQvpkQxfz7utM8uA4XcwqZ+ctBhszeyJpDSTjBHq3CjiQZEcJaruJlvYnpeYz8LIa959Kp6+3G4om96NMsiBs6hAKw9WQayZl5msW3cl8CAEPbh/LiTW1pWNeL85dyeeP3w5rFVNt8tPY4SRn5NAr05sH+TQHQ6XRc2zqEVY/14/+Gt6eejztxKdlM/GoHd8/byoHz6RpHLRyFJCNCWEN+Jlw8qd6+yjbIO5WazYi5WzienEWonyc/PNSbThEBADSs603niAAUhTLTJPZUaDCap4lu6hiGj4crb4/oCMDirWf453iKJnHVJieSM/lyk/r7P3NYWzzdXMp839VFz5hejVn39EAmD2yGu6uemLgLDJuziSd/2EtCeq4WYYtSjEZtR6okGRE2dyQxg+k/7eeT9SdYfzRZ03fINpN0UP3sGw4+9ar8sIIiI38eTGTmzweccink4YQMRsyN4dzFXBrX82bppN60CPEtc8zNHcMAtZhRC1tiL3App5CgOu5ENVH/bfo0C2Jc78YAPLtsH5l5UlxZXYqi8PIvhygyKgxuHczgNiFXPNbP041nh7bm7ycHcGvncBQFftx1jkHvrue9P4+SbcVps/wiAwfOp/PDjrO8+ushPl53ggz5dy7Xt1tPM27BNvIKDZrFIGvbhE2dvpDNvV9sJTWrbK+JoDoetAnzpW24H23D1I8mQT64ujhpfmxudlZ5vYiiKByMz2DZznP8sjfe3IfjnxOprHqsP+6uzvEc7DydxvgF28nIK6J1qC9fTehJsK/nf467oUMYr608zPZTaSRl5BHi999jbMlUr3JD+zBc9CUt+p+9oTXrjqZwJi2H11ce5s07Oto1rtrijwOJbDqRirurnhnD2lbpMQ3revO/u7owvm8TXvvtEDtOX+Sjv0/w3bazPHV9S+7sHlHm36oyadkFHE7I4FB8hvo5IYMTyVkUXfZu/8tNJ3k8ugWjezbCzVn/1ljZJ+tP8PaqowCs2H2eu3o20iQOSUaEzaRm5TN2/jZSswpoFeJLq1BfDiVkEJeSRWpWPv8cz+ef4yUrGjxc9bQO9aVNmJ85SWkd5kcdZ+gHkVh5s7OUzHx+3nOeZTvPcaTUKEh9Xw8KDUbiUrL5ctNJJg9sZutoa2zjsRQe+nonuYUGujWuy/xxPfD3div32AYBXnRtFMCuM5f4Y38C9xUXtdpDQZGR1QeTALixQ1iZ73m7u/LunZ0Y9XkM328/y9D2oQxsFWy32GqDnIIiXvtNLVqd1L8pjev5WPT4zhEBLJ3Um1UHEnlz1RFOX8jhuZ/2s3DLKZ6/sQ39W9Yvc7zRqHA6LadM0nEoPoPEjPJHW/293Ggb5kerUF/+OZ5CbEo2M34+qJ7/hjYMbhOM7irdQ0pRFN5cdYTPNsQBMHVQc0b1iNAsHif4Ky+cUXZ+Efcv3M7pCzk0rOvF1w+UvGvOLTBwNCnT/E7mUIL6hyWnwMDec+nsPVe2qK1xPW/ahvnRJsyPDg386dciyPFGUJLKL17NLzKw9nAyy3aeY8OxFAzF79TcXfVc1zaEEV0b0q9FED/viefJpXv56O/jDO8STpi/l71/gir7fX8Cj32/m0KDQv+W9Zl7b1e83Sv+U3JTx3B2nbnESjsnI5tjU0nPLSSojgc9mwT+5/s9mwRyX59IFmw+xXM/7mf1E/3x9yo/qRL/9fG6E8Sn59EgwIvJA5tX6xw6nY4bOoQxuE0IX8Wc4qO/T3AkMZOx87cxoGV9otuGcDRR/VtxJDGTnILypxJK/51oW/yGJszf05xsFBqMfL/tDB/8dZy4lGwe+GoHvZvW44Wb2tC+gX+1nwNnZDAqvLhiP99tOwvACze2YWJx0bFWdIoTrK/KyMjA39+f9PR0/Pz8tA5HVKLQYOSBRTvYcCyFut5u/Di5D03r16nwMUajwpm0HPM7HVOCkpD+33c8j0e34PHolrYK33JGA7zRAIpyYeoOlHrN2XsunWU7z/Lr3oQyzZ66NArgjq4NGdYxvMxIgqIo3Dk3hh2nL3JzxzDm3N1Vi5+kUku2n2H6T/sxKnBThzA+GNW5StNKCem59J71NwD/Th9MqL99pmqeXrqXpTvPMbZ3Y169tfxRq9wCAzf8byOnLuQwoltD3r2zk11ic3YnU7MZ8sFGtY/ImG4MaRdqlfNeyingw7Un+PrfU+bmaaWVN4LaKtQXX8+qJZEZeYV8si6W+ZtPUlBkRKeD27s05Okhrez2e6mlgiIjTyzZw8r9Ceh1MOv2DozqYbupmaq+fksyIqxKURSeWrqPH3edw9NNz3cTe9GlUd1qn6/0XPD2U2n8eSiJut5ubHluMF7uLpWfwB5SjsHHPTC6evFZ3w0s25VAbEq2+dth/p7c1qUBd3RrSLMKkrKD8ekM+2gTRgUWT4yiT7Mge0RfZZ9vjOWN39XOpaN7RvDa8A4WzeuP+HQLO05fZMbNbbn/GtuPjhQUGen+2hoy8opY8mAvoppeubB4x6k07vwsBkWB+fd159rWVy7CFOr/8/sWbGfDsRT6t6zPovE9rD7dcSo1m4/+PkFKVr5aX2bl2rKzaTm8s/oov+xVa4o83fQ82K8pDw1oVmu3CsgpKGLSN7vYeCwFNxcd/7ury3+mL61NkhGhiXdWH+HjdbG46HV8PqZbhZX1ljIYFQa+u46zabm8Nrw99/ZqbLVzV1deoYH9qxfQY8eT7DY257aCVwH1D9vQdqHc0a0hfZoFVflFe8bPB/gq5jQtguvw+2P9HKLITlEU3ll9lE/WxwLw0ICmPDe0tcUvPgs2n+SVXw/RvXFdlk3uY4tQy1h3JJnxC7cT7OtBzPTBlf4bvL7yEPP+OUmwrwdrnhhwxRoYAX8eTOTBr3fi5qJj9eP9Kx35dGS7z1zk9ZWH2XH6IqDWcD11fUtGdLOsiNbRpecUcv+i7ew8fREvNxc+H9uNfi3qV/7AGqrq67f2f+lErfF1zCk+Xqe+YL0+vL1VExEAF72O8X3Ud9TzN52s/rr4U5vgo26wZoa6sV017Tx9kag31rL93w0AHDY2omdkIG/d0YHtL0Qz+64u9GtR36I/aE9e14pAH3eOJ2exaMupasdmLUajwosrDpgTkWeGtmL6DW2q9S74hvZh6HSw4/RFu/SVMC0lvrFDWJX+DZ68vhVN6/uQnJnPK78etHV4VpOWXcDoz/9l2pI95F6hnsKa8goNvFpctDqxX1OnTkQAujSqy9JJvfn0nq40rudNSmY+z/64n5s+/KfW9KBJzsxj1Ocx7Dx9ET9PV755IMouiYglJBkRVrHqQAIzflH/gD8R3dJmy8NG9ojA19OVuNRs/j6SXL2T7P4GLpyAzf+DD7vAtnlgsKz/gKIovPLrQdJzC+nirm7ANiT6On6Y1JtRPRpVef76cv7ebjw7VN3xd/Zfx0m+wioBeyg0GHl8yR6+3XoGnQ5ev609D1ezSBEg1N+T7o3VKbvf99u2AVp+kYE/D5U0OqsKTzcX3r2zE3od/LT7PH9qvJ9OVRiNCo8v2UNM3AV+2n2eMV9utfmGdJ+sj+XcxVzC/D2Zem31fx8ciamI9s8n+vPiTW3w83TlSGImY77cxn0LtnEsyfl6AJmcTcth5NwYjiRmUt/Xgx8m9aZb4+pPnduKJCOixradTOPR7/egKDC6ZyMeHWy7P1B1PFy5uzjRmfdPXPVOcm6H+tkrEHIuwO9Pwad94OgqqOKs5YZjKew7l46nm56e3uqcc72m3aoXz2Xu7BZB54gAsvKLNGtXnltg4MGvdvDL3nhc9To+vKsL90TVfFrspuL5aVvvVbPpeCqZeUWE+HnQzYKapa6N6ppXFTy//AAXswsqeYS25qw7wcZjKXi66fHzdGXH6Yvc9fm/Ntsl+cyFHOZuUEfJXrypbaWrqJyNh6sLD/RryoanBzG+bySueh3rj6YwdPZGnl++3yF2n7bE8aRMRszdwqniVY1LH+pN61DHLHWQZMSBbI27wOcbY8kpcJ7Nu44lZfLAou0UFBmJbhPC/93azubr9u8r/iOx9WQa+89ZOM2SexEuHFdvPxwDN74L3vUg9Rh8Nwq+ugUS9lV4CkVR+OjvEwBM7OqHS1bxO+iQqjV8qoxer+PVW9uh08GKPfFsjbtglfNWVVZ+EePmb2PdUfVFbt647gzrFG6Vc9/QQZ2q2XXmEucv2W6qZmWpKRq9hfP+T0S3pHlwHVKz8nnZgadr/jmewgd/HQPgteEdWPJQb4LqeHA4IYM7527h3MUcq1/z1d8OUlBkpG/zetzYwTqrZxxRXR93Zg5rx5ppAxjSLkQtKt96hkHvrueDNceIt+HvrrXsPXuJkZ/FkJSRT4vgOiyb1IfIIMv6wNiTJCMOIC4li4lf7WDU5//yxu9HeOWXQ1qHVCUJ6bmMm7+NjLwiujYK4KPRXezS/yPM38s89P7FJgtHR87vUj/XjQTfUOg5ER7dDX0fAxd3OLkRPusPKx6GjPLfvcfEXmDn6Yu4u+q5v3mWemdgU/DwLff46ujYMIDRxSNAM385SJGdtl0vKDLy0Nc72HYqDV9PV76eEMUgKzYCC/HzpEek2u/jj/22aQ+fX2RgzSG10dlN1Vgp4Onmwnt3dsJFr+PnPfGsOqBNG/uKJKTn8ph5NDKCEd0a0ibMj2WTetMgwEtdpvxpDCeSrTe98PeRJP46nIyrXscrt9j+TYcjaBLkw2djurPkwV50bOhPVn4R/1t7nL5v/c29X2xlxe7zdqnTsdSW2FTunvcvF3MK6RQRwA8P9Xb4ZcuSjGgoLbuAl385yPUfqFtqu+h16HSwZMdZ1h2tZj2EnaTnFnLf/O0kpOfRrL4PX47rYdeltg9cow6lr9yXYNm7lPM71c8Nupfc5+kP170KU3dA+zsABfZ8qxa5rnsD8rPKnOLDv9WRlbt6RFA3Q22jXFHn1ep6+vpWBHi7cSQxk6//PW3181/OaFR4etleNp+4gLe7C99MiDInDtZk671q/jmWSmZ+EaF+nnSt5rLyThEBTBqg/o69sPwAF7IcZ3i+0GBkyre7SMsuoF24HzOHtTN/LzLIhx8n96F5cB0SM/K4c24M+85dqvE18woNvPKr+ibp/mua0DzYeom3M4hqWo8VD/flw9FdiGoSiKLAphOpPL5kDz1e/4tnlu1l28k0HGFx6p8HE7lvwXayCwz0aVaPbx+Ioq6Pu9ZhVUqSEQ3kFxn4bEMsA95Zx8Itp8wbTK1+vJ95tchzP+6zeSFadeUVGpj41Q6OJmUS7OvBovt72v2XvUNDf6KaBFJkVCxbdWKqF2nY/b/fq9sYRsyHB9ZCRBQU5sCGt9SkZNdXYDSw/VQa/8al4eaiY9KAZqU6r1p/X5O6Pu48PUQtZn3/z2M2n69+c9URft6j1oh8em8388671ja0fSg6Hew5e4mzadafSli5v/pTNKU9OrgFrUJ8uZBdYC7OdgSzfj/CrjOX8PV05ZN7uv5nh9xQ/+Kdkxv6czGnkLvnbSUmtmZTffM2xnH6Qg4hfh48OrhFjc7lrPR6Hbd0CmfJQ73555lBPB7dgohAL7Lyi/hhxzlGfhbDgHfW87+/jtvk97oqftx5jsnf7qKgyMj1bUOYf18P59hOA0lG7EpRFH7bF8/g9zYw648jZOYV0TbMj8UPRPHlfT1oHuzL00Na0STIh6SMfP7vN8ebrjEYFab9sIdtJ9Oo4+HKwvE9aVjXW5NYJvZT37ku3naGrKrs9qkocL44GWlQTjJi0rA73L8a7lykTudkJcIvj8Bn/fl75RIARnRrSHiAFySakhHrj4wA3NWjER0a+JOZX8Rbq47Y5BqgbiD2+UZ1yuutOzoyoKXtlv0F+3oSVdya/Q8rT4HkFZaaoqniKpor8XBVV9e46HWs3JdgrkPR0u/7E5i/+SQA793Z6Yp7wQT6uPPtxF70blpPrQFasI2/ip8XS527mMPH69UaqedvbOM0L262FBHozePRLdnw1CCWPNiLkd0b4uPuwpm0HD746xj93l7HqM9iWLrjbNX+NlnBgs0neXLpXgxGhTu6Niw3UXVkkozYyc7TF7nj0y1MXbybcxdzCfHz4J0RHfn1kWvo07yk06aXuwvv3tkRnQ6W7TzH2sPV+wNiC4qi8H+/HeL3/Ym4uahNzdqGa1eZfW3rYJoG+ZCZV8QP289W/oCLp9TVM3q3/+wh8x86HbQbDlO2wfWvq1M5SQd4NuU5Fri/zSMdDFCUD6m2m6YBtbfKK7eqw/DLdp5jZ3FjJmv6dW+8OfF9Zmgr7ujW0OrXuNxNHdWC2JVWXuK78VgKWflFhPt70sUKIzsdGvozpXjjwpd+PkCqhtM1cSlZPLNMLa5+aEBTrq+k/XodD1cWjO/BdW1D1Fqgb3ayfPc5i6/72m+HySs0EtUkkFusVMhcW+j1OqKa1uPtEZ3Y/mI0H4zqxDXNg9DpYOvJNJ5eto8er/3FtCV72HIitfq9kSqgKAqz/zpmnkYb3zeSd0Z0dLz9uyrhXNE6obNpOUxZvIs7Pt3CrjOX8HJz4Ynolqx7auAVt8nu1jiQB4rbZU//aT+XchxjeeHcDXEsLJ4SeW9k5zJJlBb0ep25rfj8zSfNm9BdkaleJLQDuFWxmMvVA/pMhUf3sMbvdgoVFwbp9xC+eDAsHQ/GIvAMAH/bvYB3bVSXkd3V88/4+UDlP6cFtsSm8uQPewEY17sxkwfYZ8fgoe1C0evUin9rDmlba4qmtKnXtqB1qC9p2QW8tOKAJnUBuQUGHv52F1n5RfRsEsjT17eq0uM83Vz49J6u3N61AQajwhNL9lo0rbnxWAqrDibiotfx6q3tr4qi1erydnflti4N+eaBKDY/ey1PD2lF0yAfcgsN/LT7PHd/sZV+b6/j3dVHOZmaXfkJq8BoVHjl10PM/kutY5t2XUtm3NzWar/79iTjbTaSnlvIx+tOsHDzKQoM6mZMI7tF8OT1LQn2q/yF8MnrW7H2SDJxKdm88ushPhjV2fZBV+CnXefM0wQv3tTGYd4h3dG1Ie/9eZRzF3NZfTCx4n0WKqoXqcTBSy5MTB5BE31ffm39F3Xi/oCjK9VvhnZQR1Js6NmhrVl1IJGD8Rks3naGMVZohX8oPoOHvtpJgcHIjR1CmTHMfisk6vt60KtpPbbEXuD3/Qk8ZIUkKK/QYJ6KqOkUTWnurnreG9mJW+ds5o8Dify6L8Guv/+KovDCiv0cScwkqI4HcyxctebqoufdEZ3w83Rj4ZZTzPxFbdb3yLXNK/z3zi8y8HJxrcy43pG0Cr26ilZrIjzAiymDmvPwwGbsOnOJH3ed49e98Zy/lMucdSeYs+4EjQK9cXWp2f+3/EKjeYn8y8Pa2nVHbGuTkRErKzQYWbj5JAPfWcfnG+MoMBi5pnkQKx/px1sjOlYpEYGy3SCXa9wNcsOxFPPw8APXNOGBftpuNV2al7uLeY+aLyprglaVepErmFPcV6R9h27UGfs93Pc7hHVWvxl5jcXns1S9Oh48Wfxu+N3VR0mrYTOucxdzuG/BNjKL32m/P7Kz3ffhMCWOK620xHf90RSyCww0CPCis5WLb9uF+/PItWrh5oyfD5Ccab/OuEu2n+WnXefR6+Cj0V2q/DekNL1ex8xhbXk8Wv0Z3l9zjNdWHq5w2mD+plPEpWYTVMeDx6+7OotWa0qn09GtcV3euE3dIuKj0V0Y2Ko+eh2cScshLiW7Rh/nL+Xiotfx/shOTp2IgIyMWI2iKKw5lMSbfxwhrngIrnlwHV64sQ0DW9Wv1jvOro3q8mD/ZszdEMvzyw/QIzLQ7qtW9p9LZ/I3OykyKtzSKZznb2xj1+tXxZjejflsQxy7zlxi5+mL5bc6LiooaWZm4cjIsaRM/jigJoNTBxV3l43sCxPXqc3SglrWJPwquyeqEd9vP8vhhAzeXnWEN++o3gqei9kFjJu/jeTMfFqF+DJvbHdNCt2Gtg9lxs8H2HcunTMXcmhUr2aF0Kak5qaOYTYZ4Xl4UDP+PKSOTr2w/ACfj+lm85GkA+fTzSt5nhrSit7NrrzzcGV0Oh2PR7fEz9ONV387xJebTpKeW8ibt3f4z0hLQnouHxUvYZ9+Q2v8qrm9gSjh6ebCsE7hDOsUTnJmHqdSrTM9GRHoRZi/l1XOpSVJRqwgNiWLF5bv59+4NADq+bjzxHUtuatHRI2LiB6PbsHaw0kcT85i5i8H+XB0F2uEXCWnL2QzfuE2corXq79zZ0eHnIsM9vXk1s7hLN15ji83xdGtcTlt2ZP2gyEfvOqqDcosYBoVGdoutOxQtV4Pwa1rErpFXF30/N+t7RgxN4YlO85yV89GFo8A5BUaeOCrHcSmZBPm78nC+3vg76XNC01QHQ96N6vH5hMXWLk/gckDqz9Vk1doMBd722pLdDcXPe/e2Ylb5mxizaEkfthxllE9bLMHE6i7rE7+dicFRUYGtw5mUn/r1PPcf00T/L3ceObHfSzbeY7MvEL+d1eXMgnpaysPk1NgoHvjutzetYFVritKBPt6Euzr2E3I7E2maazg1V8P8W9cGh6ueh4e2Iz1Tw/k3l6NrVLNbJqucdHr+GVvvM26Vl7uWFImIz+LITWrgDZhfnw2phsero67TGxCP3WIctWBxPILIs+Zmp11s6i+Iy4li9+K91FxhE3BukcGcnvXBigKzPz5gEXV+UUGI498t9u8c+ei+3tq/o7qpg6mVTU126tm/dFkcoqnaDo19LdGaOVqE+bHY8V9Np79cT8PLNrOieSsSh5lOUVReHLpXs6m5dKwrhfvj+xs1TcCd3RryKf3dMXdRc/qg0lMWLTdvAR1y4lUVu5LQK+DV+ywvYMQIMmIVZy+oE7LfDamG88MbV3tHVuvpHQ3yBdX2L4b5OV7Giwa38PqP5O1tQ71o1+LIIwK5j4MZVSzXuTjdbEYFRjcOpj2DWz3ImeJ525oja+HK3vPpbNkRxWWNKO+uM345SBrDiXh7qrny/t60DJE+4LEIe1CcNHrOHA+g1M1WGFg6uZ6s42maEqbNKAZ4/tG4qLX8dfhZIbM3siMn637//KzjXH8dTgJdxc9n97TDX9v6///u75dKAvH98DH3YXNJy5wzxdbScnMZ2bxtNC9vRrTLtwxfudF7SfJSA0pikJCulrM1qx+HZtdx17dIE17GlwqtadBdQrmtGAqrP1h+9n/dq+txkqaMxdyWLHnPACPOFDXyWBfTx6/Tq1TeXvVkSot/f7o7xMs3noGnQ4+vKuzTdq8V0e9Oh70Ka6DqG4ha26BgbWH1e0TrLmK5kpcXfTMHNaO1Y/3J7pNMAajwlcxpxn4znrmboglr7Bme5X8G3eBd1ar/Wtm3tKWDjYc6enTPIhvJ/YiwNuNvWcvce176zmenEU9H3eevK5qy4eFsAZJRmooLbuA/CJ16W6IDV+0PVxdeG9kSTfI32ywBbuz7mlg0r9FEK1CfMkuMPD9tjMl38hJgzR123MalFNPcgWfbjiBwajQr0WQ1Vdn1NS43o1pFeLLxZxC3v3zaIXHLtl+hvfXqLu7vnpLO4a2t/0LtiVMm9lVt8PpuqPJ5BYaiAj0ooMdR6+aB9fhi3E9WPxAFG3D/MjML+LNP44Q/f4GftkbX61+JMmZeTzy3W4MRoXbujTg7p62q0kx6RwRwNKHehPi50FmnjpV8+zQ1jYZjRHiSiQZqaH4S+qoSFAdD9xdbft0tm9QqhvkigNW3avEmfc0MNHpdObakYVbTlFo2unWtFNvYFPwrtqIwPlLuSzbqXardMS9OFxd9ObOrN9uPcOB8+nlHvf3kSSeX662rJ8yqBljekfaK8QqG9IuFBe9jkMJGdVqBmVKYm7qEK5JfUOf5kH8+sg1vDOiIyF+Hpy7mMuj3+3m9k+3sPN0WpXPU2Qw8uh3u0nJzKdlSB1ev81+TcZahPiybFIfekYGcmvncEbYoQuvEKVJMlJD8elqw5nwAPsUApq6QV7MKeTFFfut0g1y/qaSPQ1GdHO+PQ1Ku7VzOEF1PEhIz+N307B/NepFPtsQS6FBoVfTQIeZ0rhcr6b1uKVTOIqitiq/vJh195mLPPztLvO/61NV7Nppb3V93Olb3M33dwunanIKilh7RF1Fc7MdpmiuxEWv487uEax7aiBPRLfE292F3WcuccenMUz5dhdnLlS+jPO9Ncf4Ny4NH3cXPr23G97u9n0zEBHozQ+TevO/u7o45Ko5UbtJMlJDCcXd78L97VNXYeoG6arXsfpgEr/srf50jaIofLDmGK8W70tyf98mvH2H8+1pUJqHqwvjeqtN0Ob9E6cmaxbWiyRn5PF98V43j17reKMipb1wUxt8il/4ftxVsu9IXEoW9y/cTl6hkYGt6jPr9g4OvSri5uKpmt8snKr5+0gyeYVGGtfzpp2G+ySZeLu78lh0C9Y/NZBR3SPQ6dRamOj3N/D6ykOk55S/E/dfh5L4dL06lfjWiI42rT8TwhE576uOgzAVr9pziWTpbpAzfzlYrW6Qpj0N/rdWbWz05HUteenmNrXiHdE9vRrj6abnwPkMtsZdKNmTpoojI59vjKOgyEi3xnVr1GTKHkL8PM3TSG/+cYT03EKSM/MYO38bF3MK6djQn4/v7oqbgyeY17cLwVWv43BCBrEpVV8qaxpJuamD7VfRWCLYz5O3RnTk90f70a9FEAUGI/P+OcmAd9exYPPJkilE1P2rpv2wB4D7+kRyc0fH2GpBCHty7L9QTsC0L0B4gH1XnDw8qBntwv24lFPIC8st27yryGDkqWV7zZvevXJLOx4Z3MKh/pjXRKCPO3d0Vee8f1m3CXLTwMUdQivfWfdCVj7fblWLXyvbu8NRjO/bhGb1fbiQXcDrKw8xfsF2zl3MJbKeN/Pv64GPE9T+BHiXmqqp4uhIdn4Rfx9RV9HYqtFZTbUJ8+Or+3uyYHwPWgTX4VJOIa/8eojrP9jI6oOJ5BUamPztTjLyiugcEeCQHY6FsAdJRmrINDJir5oRE1M3SDcXHWsOJZmXoFYmr9DApG928dOu87jodXwwqhPj+kTaNlgNmHbzzYrbpt4R2lHdgbcSX2w6SW6hgY4N/RnQsr4tQ7Qad1c9r96qJlo/7DjHwfgMguq4s+j+ngTVqfxndhSmZblVXeJrmqKJdJApmivR6XQMahXMH4/14/Xb2hNUx52Tqdk89PVOBryzjgPnM6jr7cbH93S1eRG8EI5KfvNryFQzEmanmpHSSneDnPnzQZIyKp6uycovYvyC7WozJVc9n93bjdu61M6q+Wb16xDdJpguerWVe1XqRS7lFPBV8WjR1EHOMSpi0rd5kHmJrLe7C/Pv60Hjej4aR2WZIW1DcXPRcSQxkxPJmZUeb15FY4dGZ9bg6qLnnqjGrHtqIFMGNcPDVU9SRj46Hcy+qwsN7PyGRghHIslIDRiMCknFy2vtPTJiMmlAMzo08Ccjr4jnf7ry6pq07ALunvcvMXEXqOPhyqLxPYluG2LnaO1rwjVN6axXiwKzgjpXevz8zafILjDQOtSX65zwuXnl1naM7tmIRff3pGPDAK3DsZi/txvXFE/VrNxX8S7VWflFrDta3Oisg3PVWPh6uvH0kNb8/dRAJvZrwgcjOzvNKJwQtiLJSA0kZ+ZhMCq46nWaDYe7uqira9xd9Kw9ksyPu/47XZOQnsvIz2LYdy6dut5uLJ4Y5fCFmdbQq5EP7fWnAPgxKbTCYzPyCllQ3Eb+kWuds34mqI4Hs27v4LBLkavipo5V26tm7eEk8ouMNA3yoU2Y9m3tq6NBgBcv3NSW4V1kIzohJBmpgfjiKZpQf09cNFyF0jLEl8evU6drXvn1IAnFvU8ATqVmM+LTGE4kZxHm78nSSb2d8l1zdeiSDuJGERcUXz7aXUR+0ZXbdH+15RSZeUU0D67DDe0rTlyE7VzXNgQ3Fx3HkrI4nnTlqRpnm6IRQlRMkpEaMHVfDdd451OAB/s1pVNEAJl5RTz3ozpdcyg+gxFzYzh/KZcmQT4sndSb5sHO+S6yWoqbnR3RtyA1u4Cf95T/bjs7v4gvN6mjIlMHNa8Vy5udlb+XG/1bqFMWVypkzcwrZP2xFMA+e9EIIWxPkpEaMI1AhNl5WW95XF30vHdnR9xd9Ww4lsKrvx3irs9jSM3Kp02YHz881JuGdb21DtO+ipuduTfuAcCX/5wst6bmm39PczGnkMh63pp28RQq86qaKyzxXXs4mYIiI83q+9DKAXYeFkLUnCQjNWAaGbFnw7OKNA/25cni3VwXbD5FRl4R3RvX5fsHe1Hf13mWeFpN8chI2x7X4u3uwtGkTP45nlrmkNwCA/P+iQPg4UHNnbr7bG0R3TYEdxc9x5OzOFbOVI1pxOSmjtrsRSOEsD75y1sD8Ro1PKvIA/2a0rVRAAADWtbn6wlR+Htdhbtv5qRBmppk+DTpycjuEYDaR6S077adITWrgIZ1vbhNCgkdgp+nG/1bqqtqLm8Pn5lXyIajxVM0DtroTAhhOUlGasDc8MxBRkZA3bDr6wlRLBzfgy/GdcfL3Tk3vKsxUwv4wGbgHcj9fZug18HGYykcTVTfbecVGvhso7r0d/LAZg7fMv1qUjJVE19mau2vw0kUGIw0D65DyxDZv0WI2kL++taAI9WMlObj4crAVsFX94vrZZvjNarnzZB26iqZLzepIybLdp4jKSOfMH9P2TLdwUS3CcHdVU9sSjZHS03VmFfRONheNEKImqnWq9XHH39MZGQknp6eREVFsW3btio97vvvv0en0zF8+PDqXNah5BUaSM0qABxrZEQUK64XKb053gP9mgKwYnc88ZdyzbukPtS/KR6uV+kIkoPy9XQzNwIzJSDpuYVsPKbW/MgqGiFqF4uTkSVLljBt2jRmzpzJrl276NSpE0OGDCE5ObnCx506dYqnnnqKfv36VTtYR5JYPEXj6aYnwPsqrMlwZIpSMk3TsJv57m6N69KlUQAFBiPjF2zn/KVcgup4cFfPRhoFKipyc6lVNYqi8NchdYqmZUgdWsoqGiFqFYuTkffff5+JEycyfvx42rZty9y5c/H29mb+/PlXfIzBYOCee+7hlVdeoWnTpjUK2FHEp5uKV71kuNjRpMVB7kVw8YCQDmW+NbF4dMQ09P9Q/6Z4usmoiCMaXDxVE5eazeGEzJJVNE7W/l0IUTmLkpGCggJ27txJdHR0yQn0eqKjo4mJibni41599VWCg4OZMGFCla6Tn59PRkZGmQ9Hk+BADc/EZUz1ImEdwdW9zLeubxtCw7rqv1mgjzv39JJREUdVx8OVQa3UqZrvtp3hn+OmRmfSIVeI2saiZCQ1NRWDwUBISNlNxEJCQkhMLH9jq02bNvHll18yb968Kl9n1qxZ+Pv7mz8iIiIsCdMuzMWrGuzWKypRTr2IiauLniei1V4sT1zXEm93V3tGJixk2qvmm62nKTQotA71vbq6CAtxlbDpcovMzEzGjBnDvHnzCAoKqvLjpk+fTnp6uvnj7NmzNoyyes6bGp7Jtt+O57KVNJe7o1tDDr86lDG9GtsxKFEdg1sH4+Gqx7S6V3qLCFE7WfS2MCgoCBcXF5KSksrcn5SURGjof4dOY2NjOXXqFMOGDTPfZzQa1Qu7unL06FGaNWv2n8d5eHjg4eHYHUNNIyMNHGxZ71WvMA8S96u3G3S74mFXbf8VJ+Pj4cqgVsGsOqiOvN4oq2iEqJUsGhlxd3enW7durF271nyf0Whk7dq19O7d+z/Ht27dmv3797Nnzx7zxy233MKgQYPYs2ePQ06/VFWCg7WCF8US94OxELzrQd1IraMRVnBrZ3Wqpl24H83qS6MzIWojiyfMp02bxrhx4+jevTs9e/Zk9uzZZGdnM378eADGjh1LgwYNmDVrFp6enrRv377M4wMCAgD+c7+zKVlNIyMjDqV0vYiscqoVhrYPZc7dXejYIEDrUIQQNmJxMjJq1ChSUlKYMWMGiYmJdO7cmVWrVpmLWs+cOYNeX7s7f2bmFZKZVwTIyIjDqaReRDgfnU7HzR1lOa8QtVm1lhJMnTqVqVOnlvu99evXV/jYhQsXVueSDsW0J42/lxs+HrIaw6GYR0auXC8ihBDCsdTuIQwbMe3WK8t6HUx2Klw8pd6WZEQIIZyGJCPVYN6tV5b1OhZTC/h6LcArQNNQhBBCVJ0kI9UgIyMOSupFhBDCKUkyUg3xl2RkxCFJvYgQQjglSUaqIUGW9Toeo7HUTr0yMiKEEM5EkpFqMNWMyLJeB5IWC3np4OoJIc7dw0YIIa42koxYSFEUc82I7NjrQMw79XYCFzdtYxFCCGERSUYslJZdQH6Rur9OiL9j759zValgp14hhBCOTZIRC5mmaOr7euDhKputOQzzShopXhVCCGcjyYiFSqZopHjVYRTmQtIB9baMjAghhNORZMRCUrzqgBL2gbEIfOpDQCOtoxFCCGEhSUYsZG54Jst6HYfs1CuEEE5NkhELxRePjDSQhmeOQ+pFhBDCqUkyYqEEcyt4SUYchqykEUIIpybJiIXMNSMyTeMYslLg0hlABw26ah2NEEKIapBkxAIGo0JiRvG+NDIy4hhMoyJBLcHTX9tYhBBCVIskIxZIzszDYFRw1euo7ysNzxyC7EcjhBBOT5IRC5h26w3x88RFL6s2HMI52alXCCGcnSQjFpDdeh2M0Qjnd6m3ZWRECCGcliQjFoiXlTSO5cIJyE8HVy8Ibqd1NEIIIapJkhELmKZpwqXHiGMwFa+GdwYXV01DEUIIUX2SjFhApmkcjNSLCCFErSDJiAVkXxoHYxoZkXoRIYRwapKMWKCkZkRGRjRXmAtJB9XbMjIihBBOTZKRKsovMpCaVQDIvjQOIWFv8U69weAfoXU0QgghakCSkSpKLJ6i8XTTE+DtpnE0omRzPNmpVwghnJ0kI1VkXknj74VOXvy0d16KV4UQoraQZKSKzPUispLGMZyTNvBCCFFbSDJSRaZlvbKSxgFkJUN68U694bJTrxBCODvpFFVF8enS8KxKFAUyEyHpACTug8T96kd2CnS8CwY8Cz71anYNU71I/Vbg6VfzmIUQQmhKkpEqSiiepgmXZb0lDEVw4XhxwrEPEg+ot3NSyz9+22ew93vo/xREPQSu1dz52FwvIlM0QghRG0gyUkWmAtawq3VkJC9d7ethGulI3A/Jh8GQ/99jdS4Q1BJC20NoB/XDaIC1r6iPW/MSbP8Col+GdrdZvhrGvJJGileFEKI2kGSkiuLTr7KREUWBE3/BrkWQsA8unS7/OHffkqQjpPhzcBtwKydpa3Yt7P0O1v6fer5l4+HfT2HI6xDRs2pxGY0Qv1u9LSMjQghRK0gyUgVZ+UVk5hUBV8nISOJ++PNFiFtf9n7/iJKEI7SDmoQERIK+inXQehfocq86GrLlI9j8Pzi3Db68Tr0v+mWoG1nxOVKPQX4GuHlDcFvLfzYhhBAOR5KRKjDVi/h5ulLHoxY/ZRkJsO412P0toICLO/SYCK2GqkmId6B1ruPuAwOfg67jSq53cDkcWQlRk6Dfk+AVUP5jTfUiYZ1lp14hhKgl5K95FZw3Fa/W1lGRguySkYrCHPW+qo5U1IRfGNz6sZqAmEZitnwIu7+BgdOh+3hwuazbrdSLCCFErSN9RqqgZLfeWlYvYjSoL/wfdYP1s9REpGEPmLAG7lxo20SktNAOMGYF3L0UglpBbhr88TR80huO/K7Wr5jIShohhKh1ZGSkChJq48hI3Ab48wW1PgQgoHH1V7dYg04HLa9Xi1x3LYJ1b6jLhr8fDZH94PrX1BU6SYfU46XzqhBC1BqSjFRBrWp4lnJMXVp7bJX6tYd/zft+WJOLK/SYAB3uhE3vQ8wncOof+HwgNOkHigHqhIJfA60jFUIIYSWSjFRBSSt4J56myU5Vp2J2LFBf0PWu0H2CdTqi2oKnnzpS0/1+WPsq7F8KJzeq35OdeoUQolaRZKQKzA3PnHFfmsI82Pop/PO+uiQWoNVNcN2rENRc29iqIqAR3PEFRE1Wp5XOxEDLoVpHJYQQwookGamEoijmHXsbONM0jaLAgR/hr1eKN5UDwjrB9a+r0x3OpmE3GP8H5FwAnyCtoxFCCGFFkoxU4mJOIflFRgBC/B2gpqIqkg7BL1Ph/E71a78GMHgGdBhZ9QZljkink0RECCFqIUlGKmEaFQmq44GHq4vG0VRBWhx8dYu6S657Hbjmceg1Bdy9tY5MCCGEKJckI5WINy/rdYLi1awU+OYONREJ7Qj3LAPfEK2jEkIIISrkxGP29mFqeBbu6MWr+VmweKQ6MhLQWBIRIYQQTkOSkUqYdusNc+SREUMhLL0P4neBdz249ydJRIQQQjgNSUYqkXDJwUdGFAV+fQxOrFF3sr37B+dYsiuEEEIUk2SkEqaaEYcdGfn7NdjzLehc1P1kpE26EEIIJyPJSCVKNslzwJGR7V/AP++qt4f9D1oO0TYeIYQQohokGamAwaiQmKEmIw7X8Ozwr7DyKfX2oBeg6xht4xFCCCGqSZKRCqRk5mMwKrjqddT3daCGZ6djYNkEQIFu46H/01pHJIQQQlSbJCMVOF9cLxLi54mL3kE2Zks+At+NAkO+usfMTe/JpnFCCCGcmiQjFXC43XrTz6tNzfLSISIKRnwJeifoCiuEEEJUQJKRCpiX9TpCvUjuJfh2BGScg6CWMPp7cHOAuIQQQogakmSkAg7T8KwwD76/B5IPgW8Y3PsjeAdqG5MQQghhJdVKRj7++GMiIyPx9PQkKiqKbdu2XfHYefPm0a9fP+rWrUvdunWJjo6u8HhHYt6XRstlvUYjLH8ITm8CDz+1zXtAI+3iEUIIIazM4mRkyZIlTJs2jZkzZ7Jr1y46derEkCFDSE5OLvf49evXM3r0aNatW0dMTAwRERFcf/31nD9/vsbB21pJjxGNRkYUBVZPh0MrwMUd7voWQttrE4sQQghhIzpFURRLHhAVFUWPHj2YM2cOAEajkYiICB555BGee+65Sh9vMBioW7cuc+bMYezYsVW6ZkZGBv7+/qSnp+Pn52dJuDXS/bW/SM3K57dHrqF9A3+7Xdds02z4a6Z6e8R8aH+H/WMQQgghqqmqr98WjYwUFBSwc+dOoqOjS06g1xMdHU1MTEyVzpGTk0NhYSGBgVeuecjPzycjI6PMh73lFxlIzcoHNCpg3ft9SSIyZJYkIkIIIWoti5KR1NRUDAYDISFld4QNCQkhMTGxSud49tlnCQ8PL5PQXG7WrFn4+/ubPyIiIiwJ0yoSi6doPFz11PV2s+/FT/wFP09Rb/eeCr0ftu/1hRBCCDuy62qaN998k++//57ly5fj6XnlOozp06eTnp5u/jh79qwdo1TFl1rWq7NnU7H43bBkLBiLoMOdcN3/2e/aQgghhAZcLTk4KCgIFxcXkpKSytyflJREaGhohY999913efPNN/nrr7/o2LFjhcd6eHjg4aFt+3VTw7PwqizrzUyCY6tAMdTsokYDbHgLCrOhyQC49RPQy+prIYQQtZtFyYi7uzvdunVj7dq1DB8+HFALWNeuXcvUqVOv+Li3336b119/ndWrV9O9u3NscW/Rbr0rJkPsWutdPLQDjPoGXN2td04hhBDCQVmUjABMmzaNcePG0b17d3r27Mns2bPJzs5m/PjxAIwdO5YGDRowa9YsAN566y1mzJjB4sWLiYyMNNeW1KlThzp16ljxR7Gu8+YeI5WMjORnwsmN6u2WN9S8PbtvKPR/Bjztt2pICCGE0JLFycioUaNISUlhxowZJCYm0rlzZ1atWmUuaj1z5gz6UlMLn376KQUFBYwYMaLMeWbOnMnLL79cs+htKOGSqftqJSMjJzeCsRDqNoG7v7dDZEIIIUTtYnEyAjB16tQrTsusX7++zNenTp2qziU0Z5qmqXRZ74m/1M/Nr7w6SAghhBBXJtWRVxBflWkaRZFkRAghhKghSUbKkZVfREZeEVDJNE3qcbh0Rm3V3qSfnaITQgghahdJRsphqhfx9XSljkcFM1mmUZHGfcDdxw6RCSGEELWPJCPliDfVi1S2rFemaIQQQogak2SkHKaRkQobnhXkwKlN6u3m19khKiGEEKJ2kmSkHKaRkQrrRU5vBkM++DWE+q3sFJkQQghR+0gyUo4qraQxT9EMBnvuXSOEEELUMpKMlMO0L02FreCPr1E/t5ApGiGEEKImJBkpR8KlShqepcVBWizoXaFJfztGJoQQQtQ+koxcRlEU4ivbsfdE8aZ4EVHg6W+nyIQQQojaSZKRy1zMKSSv0AhA6JVqRmRJrxBCCGE1koxcxlS8GlTHHQ/XcnbgLcov2aVXkhEhhBCixiQZuUylG+SdiYHCHKgTAqEd7BiZEEIIUTtJMnKZkpU0V5iiMa2iaR4tS3qFEEIIK5Bk5DLnL1WyrNdUvNp8sJ0iEkIIIWo3SUYuU7Kst5yRkfRzkHIYdHpoOsjOkQkhhBC1kyQjl0kwL+stZ2TEtIqmQXfwDrRjVEIIIUTtJcnIZeKLR0bKnaaRJb1CCCGE1UkyUorBqJCYcYVpGkMhxG1Qb0syIoQQQliNJCOlpGTmYzAquOh1BPteloyc3Qb5GeBdD8K7aBOgEEIIUQtJMlKKqQ18iK8HLvrLlu2apmiaXQt6edqEEEIIa5FX1VIq3CBP6kWEEEIIm5BkpBRTK/iwy5ORzCRI3Kfebib9RYQQQghrkmSkFPNuvZd3X40tbnQW1hnq1LdvUEIIIUQtJ8lIKQnmZb2XJSMyRSOEEELYjCQjpZTb8MxogNi/1dstrtMgKiGEEKJ2k2SklPPlFbCe3wW5F8HDX+28KoQQQgirkmSkWH6RgdSsfOCyaRrzkt6B4OJq/8CEEEKIWk6SkWJJ6Woi4uGqJ9DHveQbJ9aon5vLFI0QQghhC5KMFIsvVS+i0xU3PMu+oE7TADSXJb1CCCGELUgyUsxUvFpmiiZuHaBAcDvwC9cmMCGEEKKWk2SkWLm79R4vnqJpIUt6hRBCCFuRZKSYqfuqebdeo7Gk2Zn0FxFCCCFsRpKRYgnply3rTdwH2SngXgciemkYmRBCCFG7STJSzLwvjalmxLSKpskAcHW/wqOEEEIIUVOSjBQrmaYpHhk5YZqikVU0QgghhC1JMgJk5xeRkVcEFI+M5F6Cs9vUb0q9iBBCCGFTkoxQsqzX19MVX083iFsPigGCWkLdxtoGJ4QQQtRykoxQsqw33LSsV3bpFUIIIexGkhFKFa8GeIKiSL2IEEIIYUeSjADx6aUaniUfgsx4cPWExn01jkwIIYSo/SQZARJMK2n8PUumaCL7gZtXBY8SQgghhDVIMsJlDc+kXkQIIYSwK0lGKKkZaeBTBKdj1DslGRFCCCHs4qpPRhRFIb54aW+TzF1gLIS6kVCvmbaBCSGEEFeJqz4ZuZRTSF6hEYB6Cf+odzaPBp1Ow6iEEEKIq8dVn4yYRkWCfNxwjZN6ESGEEMLeJBkpbnjW3TcNLp0BF3d1JY0QQggh7OKqT0ZMreAHuuxV72jUGzzqaBiREEIIcXW56pMR88hI4U71DpmiEUIIIezqqk9GEtJz8aCAyKw96h0trtM0HiGEEOJqc9UnI/GXcumlP4yrMR/8GkD91lqHJIQQQlxVJBm5lMdA/R71i+aDZUmvEEIIYWdXdTJiMCokZeTRX79PvaO5TNEIIYQQ9nZVJyOpWfmEKYk00yeg6Fyg6QCtQxJCCCGuOld1MnL+Ui4DikdFdBFR4OmvcURCCCHE1adaycjHH39MZGQknp6eREVFsW3btgqPX7p0Ka1bt8bT05MOHTrw+++/VytYa0u4lMcAfXF/kRaypFcIIYTQgsXJyJIlS5g2bRozZ85k165ddOrUiSFDhpCcnFzu8Vu2bGH06NFMmDCB3bt3M3z4cIYPH86BAwdqHHxNJV1Mp4/+oPqF9BcRQgghNKFTFEWx5AFRUVH06NGDOXPmAGA0GomIiOCRRx7hueee+8/xo0aNIjs7m99++818X69evejcuTNz586t0jUzMjLw9/cnPT0dPz8/S8Kt0NffLmLM8UfJcgukzvRY0F/Vs1ZCCCGEVVX19duiV9+CggJ27txJdHTJKIJeryc6OpqYmJhyHxMTE1PmeIAhQ4Zc8XiA/Px8MjIyynzYQmjKJgASg/pKIiKEEEJoxKJX4NTUVAwGAyEhIWXuDwkJITExsdzHJCYmWnQ8wKxZs/D39zd/REREWBJmlbXI3ApAdqNBNjm/EEIIISrnkMMB06dPJz093fxx9uxZ619EUYjvOJW99W4ksMP11j+/EEIIIarE1ZKDg4KCcHFxISkpqcz9SUlJhIaGlvuY0NBQi44H8PDwwMPDw5LQLKfT0efWB4EHbXsdIYQQQlTIopERd3d3unXrxtq1a833GY1G1q5dS+/evct9TO/evcscD7BmzZorHi+EEEKIq4tFIyMA06ZNY9y4cXTv3p2ePXsye/ZssrOzGT9+PABjx46lQYMGzJo1C4DHHnuMAQMG8N5773HTTTfx/fffs2PHDj7//HPr/iRCCCGEcEoWJyOjRo0iJSWFGTNmkJiYSOfOnVm1apW5SPXMmTPoS61M6dOnD4sXL+bFF1/k+eefp0WLFqxYsYL27dtb76cQQgghhNOyuM+IFmzVZ0QIIYQQtmOTPiNCCCGEENYmyYgQQgghNCXJiBBCCCE0JcmIEEIIITQlyYgQQgghNCXJiBBCCCE0JcmIEEIIITQlyYgQQgghNCXJiBBCCCE0ZXE7eC2YmsRmZGRoHIkQQgghqsr0ul1Zs3enSEYyMzMBiIiI0DgSIYQQQlgqMzMTf3//K37fKfamMRqNxMfH4+vri06ns9p5MzIyiIiI4OzZs7LnjQ3J82w/8lzbhzzP9iHPs33Y8nlWFIXMzEzCw8PLbKJ7OacYGdHr9TRs2NBm5/fz85NfdDuQ59l+5Lm2D3me7UOeZ/uw1fNc0YiIiRSwCiGEEEJTkowIIYQQQlNXdTLi4eHBzJkz8fDw0DqUWk2eZ/uR59o+5Hm2D3me7cMRnmenKGAVQgghRO11VY+MCCGEEEJ7kowIIYQQQlOSjAghhBBCU5KMCCGEEEJTV3Uy8vHHHxMZGYmnpydRUVFs27ZN65BqlZdffhmdTlfmo3Xr1lqH5fQ2btzIsGHDCA8PR6fTsWLFijLfVxSFGTNmEBYWhpeXF9HR0Rw/flybYJ1cZc/1fffd95/f8aFDh2oTrJOaNWsWPXr0wNfXl+DgYIYPH87Ro0fLHJOXl8eUKVOoV68ederU4Y477iApKUmjiJ1TVZ7ngQMH/uf3edKkSXaJ76pNRpYsWcK0adOYOXMmu3btolOnTgwZMoTk5GStQ6tV2rVrR0JCgvlj06ZNWofk9LKzs+nUqRMff/xxud9/++23+fDDD5k7dy5bt27Fx8eHIUOGkJeXZ+dInV9lzzXA0KFDy/yOf/fdd3aM0Plt2LCBKVOm8O+//7JmzRoKCwu5/vrryc7ONh/zxBNP8Ouvv7J06VI2bNhAfHw8t99+u4ZRO5+qPM8AEydOLPP7/Pbbb9snQOUq1bNnT2XKlCnmrw0GgxIeHq7MmjVLw6hql5kzZyqdOnXSOoxaDVCWL19u/tpoNCqhoaHKO++8Y77v0qVLioeHh/Ldd99pEGHtcflzrSiKMm7cOOXWW2/VJJ7aKjk5WQGUDRs2KIqi/v66ubkpS5cuNR9z+PBhBVBiYmK0CtPpXf48K4qiDBgwQHnsscc0ieeqHBkpKChg586dREdHm+/T6/VER0cTExOjYWS1z/HjxwkPD6dp06bcc889nDlzRuuQarWTJ0+SmJhY5nfb39+fqKgo+d22kfXr1xMcHEyrVq2YPHkyFy5c0Dokp5aeng5AYGAgADt37qSwsLDM73Tr1q1p1KiR/E7XwOXPs8m3335LUFAQ7du3Z/r06eTk5NglHqfYKM/aUlNTMRgMhISElLk/JCSEI0eOaBRV7RMVFcXChQtp1aoVCQkJvPLKK/Tr148DBw7g6+urdXi1UmJiIkC5v9um7wnrGTp0KLfffjtNmjQhNjaW559/nhtuuIGYmBhcXFy0Ds/pGI1GHn/8cfr27Uv79u0B9Xfa3d2dgICAMsfK73T1lfc8A9x99900btyY8PBw9u3bx7PPPsvRo0f56aefbB7TVZmMCPu44YYbzLc7duxIVFQUjRs35ocffmDChAkaRiaEddx1113m2x06dKBjx440a9aM9evXM3jwYA0jc05TpkzhwIEDUltmY1d6nh988EHz7Q4dOhAWFsbgwYOJjY2lWbNmNo3pqpymCQoKwsXF5T/V2ElJSYSGhmoUVe0XEBBAy5YtOXHihNah1Fqm31/53dZG06ZNCQoKkt/xapg6dSq//fYb69ato2HDhub7Q0NDKSgo4NKlS2WOl9/p6rnS81yeqKgoALv8Pl+VyYi7uzvdunVj7dq15vuMRiNr166ld+/eGkZWu2VlZREbG0tYWJjWodRaTZo0ITQ0tMzvdkZGBlu3bpXfbTs4d+4cFy5ckN9xCyiKwtSpU1m+fDl///03TZo0KfP9bt264ebmVuZ3+ujRo5w5c0Z+py1Q2fNcnj179gDY5ff5qp2mmTZtGuPGjaN79+707NmT2bNnk52dzfjx47UOrdZ46qmnGDZsGI0bNyY+Pp6ZM2fi4uLC6NGjtQ7NqWVlZZV5p3Ly5En27NlDYGAgjRo14vHHH+e1116jRYsWNGnShJdeeonw8HCGDx+uXdBOqqLnOjAwkFdeeYU77riD0NBQYmNjeeaZZ2jevDlDhgzRMGrnMmXKFBYvXszPP/+Mr6+vuQ7E398fLy8v/P39mTBhAtOmTSMwMBA/Pz8eeeQRevfuTa9evTSO3nlU9jzHxsayePFibrzxRurVq8e+fft44okn6N+/Px07drR9gJqs4XEQH330kdKoUSPF3d1d6dmzp/Lvv/9qHVKtMmrUKCUsLExxd3dXGjRooIwaNUo5ceKE1mE5vXXr1inAfz7GjRunKIq6vPell15SQkJCFA8PD2Xw4MHK0aNHtQ3aSVX0XOfk5CjXX3+9Ur9+fcXNzU1p3LixMnHiRCUxMVHrsJ1Kec8voCxYsMB8TG5urvLwww8rdevWVby9vZXbbrtNSUhI0C5oJ1TZ83zmzBmlf//+SmBgoOLh4aE0b95cefrpp5X09HS7xKcrDlIIIYQQQhNXZc2IEEIIIRyHJCNCCCGE0JQkI0IIIYTQlCQjQgghhNCUJCNCCCGE0JQkI0IIIYTQlCQjQgghhNCUJCNCCCGE0JQkI0IIIYTQlCQjQgghhNCUJCNCCCGE0JQkI0IIIYTQ1P8DDRkN2WT01rEAAAAASUVORK5CYII=", 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" ] @@ -222,14 +291,12 @@ ], "source": [ "from matplotlib import pyplot as plt\n", - "picker.metrics.to_pandas()['score'].plot(label=\"vw\")\n", "random_picker.metrics.to_pandas()['score'].plot(label=\"random\")\n", "pytorch_picker.metrics.to_pandas()['score'].plot(label=\"pytorch\")\n", "\n", "plt.legend()\n", "\n", "print(f\"The final average score for the default policy, calculated over a rolling window, is: {pytorch_picker.metrics.to_pandas()['score'].iloc[-1]}\")\n", - "print(f\"The final average score for the default policy, calculated over a rolling window, is: {picker.metrics.to_pandas()['score'].iloc[-1]}\")\n", "print(f\"The final average score for the random policy, calculated over a rolling window, is: {random_picker.metrics.to_pandas()['score'].iloc[-1]}\")\n" ] } diff --git a/src/learn_to_pick/pytorch/feature_embedder.py b/src/learn_to_pick/pytorch/feature_embedder.py index ed39fcd..7014c92 100644 --- a/src/learn_to_pick/pytorch/feature_embedder.py +++ b/src/learn_to_pick/pytorch/feature_embedder.py @@ -39,13 +39,13 @@ def format( if len(context_featurized.dense) > 0: raise NotImplementedError( - "pytorch policy doesn't support context with dense feature" + "pytorch policy doesn't support context with dense features" ) for action_featurized in actions_featurized: if len(action_featurized.dense) > 0: raise NotImplementedError( - "pytorch policy doesn't support action with dense feature" + "pytorch policy doesn't support action with dense features" ) context_sparse = self.encode( diff --git a/src/learn_to_pick/pytorch/policy.py b/src/learn_to_pick/pytorch/policy.py index 606df93..6848e47 100644 --- a/src/learn_to_pick/pytorch/policy.py +++ b/src/learn_to_pick/pytorch/policy.py @@ -4,7 +4,7 @@ from learn_to_pick.pytorch.feature_embedder import PyTorchFeatureEmbedder import torch import os -from typing import Any, Optional, PathLike, TypeVar, Union +from typing import Any, Optional, TypeVar, Union TEvent = TypeVar("TEvent", bound=base.Event) @@ -55,7 +55,7 @@ def learn(self, event: TEvent) -> None: def log(self, event): pass - def save(self, path: Optional[Union[str, PathLike]]) -> None: + def save(self, path: Optional[Union[str, os.PathLike]]) -> None: state = { "workspace_state_dict": self.workspace.state_dict(), "optimizer_state_dict": self.workspace.optim.state_dict(), @@ -69,7 +69,7 @@ def save(self, path: Optional[Union[str, PathLike]]) -> None: os.makedirs(dir, exist_ok=True) torch.save(state, path) - def load(self, path: Optional[Union[str, PathLike]]) -> None: + def load(self, path: Optional[Union[str, os.PathLike]]) -> None: import parameterfree if os.path.exists(path):