From dfb2b75f8221b89f105f020196030c2c90a00e53 Mon Sep 17 00:00:00 2001 From: Stefan Schneider Date: Wed, 12 Jan 2022 16:11:26 +0100 Subject: [PATCH] finalize demo, update readme, remove old tutorial --- README.md | 34 +- examples/demo.ipynb | 1663 ++++++++++++------ examples/tutorial.ipynb | 3587 --------------------------------------- setup.py | 3 +- 4 files changed, 1124 insertions(+), 4163 deletions(-) delete mode 100644 examples/tutorial.ipynb diff --git a/README.md b/README.md index d3e2c14..2df8afc 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ [![CI](https://github.com/stefanbschneider/mobile-env/actions/workflows/python-package.yml/badge.svg)](https://github.com/stefanbschneider/mobile-env/actions/workflows/python-package.yml) [![PyPI](https://github.com/stefanbschneider/mobile-env/actions/workflows/python-publish.yml/badge.svg)](https://github.com/stefanbschneider/mobile-env/actions/workflows/python-publish.yml) [![Documentation](https://readthedocs.org/projects/mobile-env/badge/?version=latest)](https://mobile-env.readthedocs.io/en/latest/?badge=latest) -[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/stefanbschneider/mobile-env/blob/master/examples/tutorial.ipynb) +[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/stefanbschneider/mobile-env/blob/master/examples/demo.ipynb) # mobile-env: An Open Environment for Autonomous Coordination in Mobile Networks @@ -19,15 +19,16 @@ To maximize the QoE of single UEs, the UE intends to connect to as many BSs as p However, BSs multiplex resources among connected UEs (e.g. schedule physical resource blocks) and, therefore, UEs compete for limited resources (conflicting goals). To maximize QoE globally, the policy must recognize that (1) the data rate of any connection is governed by the channel (e.g. SNR) between UE and BS and (2) QoE of single UEs not necessarily grows linearly with increasing data rate. - -**[Try mobile-env on Google Colab: ![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/stefanbschneider/mobile-env/blob/master/examples/tutorial.ipynb)** -


Base station icon by Clea Doltz from the Noun Project

+**[Try mobile-env: ![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/stefanbschneider/mobile-env/blob/master/examples/demo.ipynb)** + +Documentation and API: [ReadTheDocs](https://mobile-env.readthedocs.io/en/latest/) + ## Installation @@ -107,14 +108,9 @@ env = gym.make('mobile-small-central-v0', config=config) # ... ``` -## Documentation -Read the [documentation online](https://mobile-env.readthedocs.io/en/latest/index.html). +## About `mobile-env` -## DeepCoMP -mobile-env builds on [DeepCoMP](https://github.com/CN-UPB/DeepCoMP) and makes its simulation accessible via an OpenAI Gym interface that is independent of any specific reinforcement learning framework. - -## Citing If you use mobile-env in your work, please cite with: @@ -129,10 +125,22 @@ If you use mobile-env in your work, please cite with: } ``` -mobile-env is based on [DeepCoMP](https://github.com/CN-UPB/DeepCoMP), -providing the underlying environment as open, stand-alone platform to be used by others. -mobile-env is inspired by [highway-env](https://github.com/eleurent/highway-env), which focuses on autonomous driving. +mobile-env is based on [DeepCoMP](https://github.com/CN-UPB/DeepCoMP), providing the underlying environment as open, stand-alone platform to be used by others. + List of repositories, publications, or preprints using `mobile-env` (please open a pull request to add missing entries): * [DeepCoMP](https://github.com/CN-UPB/DeepCoMP) + + + +## Contributing + +Development: [@stefanbschneider](https://github.com/stefanbschneider) and [@stwerner97](https://github.com/stwerner97/) + + +We happy if you find `mobile-env` useful. If you have feedback or want to report bugs, feel free to [open an issue](https://github.com/stefanbschneider/mobile-env/issues/new). + +We also welcome contributions: Whether you implement a new channel model, fix a bug, or just make a minor addition elsewhere, feel free to open a pull request! + + diff --git a/examples/demo.ipynb b/examples/demo.ipynb index 1260a43..4b7d40b 100644 --- a/examples/demo.ipynb +++ b/examples/demo.ipynb @@ -16,6 +16,7 @@ "* `mobile-env` is written in pure Python and can be installed easily via [PyPI](https://pypi.org/project/mobile-env/)\n", "* It allows simulating various scenarios with moving users in a cellular network with multiple base stations\n", "* `mobile-env` implements the [OpenAI Gym](https://gym.openai.com/) interface such that it can be used with all common frameworks for reinforcement learning\n", + "* `mobile-env` is not restricted to reinforcement learning approaches but can also be used with conventional control approaches or dummy benchmark algorithms\n", "* It supports both centralized, single-agent control and distributed, multi-agent control\n", "* It can be configured easily (e.g., adjusting number and movement of users, properties of cells, etc.)\n", "* It is also easy to extend `mobile-env`, e.g., implementing different observations, actions, or reward\n", @@ -28,7 +29,7 @@ "\n", "This demonstration consists of the following steps:\n", "\n", - "1. Installation and usage of `mobile-env` with a dummy actions\n", + "1. Installation and usage of `mobile-env` with dummy actions\n", "2. Configuration of `mobile-env` and adjustment of the observation space (optional)\n", "3. Training a single-agent reinforcement learning approach with [`stable-baselines3`](https://github.com/DLR-RM/stable-baselines3)\n", "4. Training a multi-agent reinforcement learning approach with [Ray RLlib](https://docs.ray.io/en/latest/rllib.html)\n", @@ -41,7 +42,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 15, "metadata": { "collapsed": false, "jupyter": { @@ -64,13 +65,13 @@ "Requirement already satisfied: shapely==1.8.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from mobile-env) (1.8.0)\n", "Requirement already satisfied: svgpath2mpl==1.0.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from mobile-env) (1.0.0)\n", "Requirement already satisfied: pyparsing>=2.2.1 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (2.4.7)\n", - "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (1.3.1)\n", - "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (4.28.1)\n", "Requirement already satisfied: setuptools-scm>=4 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (6.3.2)\n", - "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (2.8.1)\n", - "Requirement already satisfied: pillow>=6.2.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (8.4.0)\n", + "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (1.3.1)\n", "Requirement already satisfied: cycler>=0.10 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (0.10.0)\n", "Requirement already satisfied: packaging>=20.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (21.3)\n", + "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (2.8.1)\n", + "Requirement already satisfied: pillow>=6.2.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (8.4.0)\n", + "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib==3.5.0->mobile-env) (4.28.1)\n", "Requirement already satisfied: cloudpickle<1.7.0,>=1.2.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from gym>=0.19.0->mobile-env) (1.6.0)\n", "Requirement already satisfied: six in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from cycler>=0.10->matplotlib==3.5.0->mobile-env) (1.15.0)\n", "Requirement already satisfied: tomli>=1.0.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from setuptools-scm>=4->matplotlib==3.5.0->mobile-env) (1.2.2)\n", @@ -80,7 +81,7 @@ ], "source": [ "# installation via PyPI\n", - "!pip install mobile-env" + "!pip install -U mobile-env" ] }, { @@ -96,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 16, "metadata": { "collapsed": false, "jupyter": { @@ -111,8 +112,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "pygame 2.1.0 (SDL 2.0.16, Python 3.8.2)\n", - "Hello from the pygame community. https://www.pygame.org/contribute.html\n", "\n", "Small environment with 5 users and 3 cells.\n" ] @@ -148,14 +147,14 @@ "\n", "To measure QoE, `mobile-env` defaults to a logarithmic utility function of the users' data rate, where -20 indicates bad QoE and +20 indicates good QoE. This can be easily configured and changed.\n", "\n", - "![Utility plot](../docs/images/utility.png)\n", + "![Utility plot](https://raw.githubusercontent.com/stefanbschneider/mobile-env/main/docs/images/utility.png)\n", "\n", "To get started, we will use random dummy actions." ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 17, "metadata": { "collapsed": false, "jupyter": { @@ -168,7 +167,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -212,7 +211,9 @@ "Again, the line color indicates the QoE that's achieved via the connection.\n", "Note that users can connect to multiple cells simultaneously using coordinated multipoint (CoMP).\n", "\n", - "Before training a reinforcement learning agent to properly control cell selection, we will look at some configuration options of `mobile-env` next.\n", + "Here, with random action, users sometimes connect to cells but are oftentimes also completely disconnected from any cells, leading to bad QoE (red circles).\n", + "\n", + "Before training a reinforcement learning agent to properly control cell selection, we will look at some configuration options of `mobile-env` next. If you are in a hurry, feel free to skip this step.\n", "\n", "\n", "\n", @@ -229,7 +230,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 18, "metadata": { "collapsed": false, "jupyter": { @@ -263,7 +264,7 @@ " 'utility_params': {'lower': -20, 'upper': 20, 'coeffs': (10, 0, 10)}}" ] }, - "execution_count": 3, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -278,7 +279,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 19, "metadata": { "collapsed": false, "jupyter": { @@ -291,7 +292,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -317,7 +318,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 20, "metadata": { "collapsed": false, "jupyter": { @@ -330,7 +331,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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7e3vatGlDSRLEREZGsnnzZpKTk4tdp6LQ6XTY29vz3//+l7feeosuXbrg4uKCq6srLVu2xMHBgR49evD1119z8eJFXFxcOHHiRK6XvbOzM8uXL+fTTz+lVatWNGvWjJo1a+Ll5cWIESOIjo7GaDTm6lehUDBlyhR27NjBF198gbOzM1WrVsXNzY1FixZx9OhRWrZsSXp6OgEBAVy8eJFdu3ZRq1YtXF1dC72m2NhY2rRpw1tvvcW8efPw8fGhdu3apKWl0b17d6pUqUJgYCCfffYZiYmJKBQK9u3bZ94D4uDgQJ8+ffjxxx/ZsmULQ4YMoX79+kRGRrJr1y7ziys4OBiVSkXNmjWpUaMGERER7N69m3r16mEwGOjYsWOJF24tgdXdsYxIKfnzzz9RKBR07969whbxDAYDycnJuLq6FmjnXbVqFevWreObb74p9aKtVqvl9OnT1K1bt8A2VqxYwUcffcTatWupX79+qfrJD6PRaFY6D+PLYUnu3bvH4cOH6d279yPnny+l5MSJE2YTzfPPP4+bm1up2zty5Ahr1qzhv//9L56enoWWVavVREREEBwcnOsZ0Ol0fPnll/j4+PDkk0+W+PnQ6/Vs27aNy5cv4+HhwZQpUyy2XmI0GlmzZg3JyclMnTq13J5dqx97OZJz+laQ21V5cObMGZ577jk++OADevXqlW8Zk8mE0WhEpVKVq1z37t3jyJEjDBgwABcXl1znshefhBAl9rS4du0a+/fvZ+jQoSUaHWf3+zA+l8LkyXbxe9iylJRs2Y1Go9kcU5ZrMJlMGAwGbGxsSt1OduiJbFNKSdvJfi5NJhNKpbLEz2Zx2i7NM18SrH7s5cjDUhp+fn4MGjSImjVrFlgmp/2wPKlevTrVq1fP91xGRgazZs2iTp06vPzyyyVq19PTk3r16uHo6FgquQ4cOIBWq6VXr14PXZmW95e8PMmW3VLyKxQKbG1tyyxTWUbYQohi7+iuTG0XF6tir6RIKYmNjUVKia+vbx7FVKVKlUIXPSsLQgjc3NzyjOSLg4+PT4lH6jnJXuyyYuWfhtUUU0mRUjJ58mTUajUrV658ZEd7OZ+vih41P8y+S4vRaOTcuXPUqVOnVC/D0pDty6/X6yukP0vz4G7VRwl7e/sSLfbnxGqKKSMPvvwqSkmMHj2ajIyMR0Yp5ceDsqelpREVFUW1atWwtbUlLi6OEydO0LFjR4srskfxvhkMBs6dO0dQUFCFKXa9Xs/vv//+SPrlK5VKXFxcCvT8quz07NmT7t27W7zdMo3YhRB3gVTACBiklK2EEJ7Ar0AN4C4wWkqZWFg7lX3ELqXk8OHD6PV6Onfu/Mh7aDxMLly4wIEDBxg1ahQ+Pj5s2bKFV199lZ9//jnXZqN/KtlRNB0dHR+6ndZK5aawEbslNFQ3KWWzHB28BuyWUtYBdmf9/8ij1+vLbaqqVquJjY19ZKeTJaF27doMGTIEDw8PADp16sSPP/5Y4VuuKytCiBKFarZiJT8sMWJvJaWMy3HsGtBVShkphAgA9kop6xXWTmUcsWs0Gm7cuEFwcDBOTk7Fcp1LSEggPDycevXqlWjV/5NPPmH9+vWsX7++TIuFVopHZXOFLIzscM85v6d2dnZlkjk7lERZ28luy2g0mt1qs10PjUYjBoPB7L2SHe5BqVSiUqnM/wNlcnssi9w5+wfMG+xyXkd2JjP429slO8NXdrnsLGE2NjYVOpsvTxu7BHYJISTwrZRyCeAnpcze7xsF+JWxjzKTnJxMamoqAQEBxV6ETEhI4ODBgzg6OlK7du1iPXh3797l+PHjBAYGlkixt2nTBiHEQ9l6XFkJCwsjNDSUVq1alUugrd27dyOlpFevXqSkpHDu3DmaNWtWYXbt4qLRaGjXrh1SSpydnQkLC+PQoUNUq1YtV7kDBw7g6elJw4YNOXXqFC1atCjwmY2IiKBr167s27ePKlWqlEk+nU7HV199hVqtJjAwkKeeegqVSsWZM2fYu3cvaWlpTJgwAY1Gw2effUa3bt0YN24c9+/f5/vvv0cIwahRo2jUqFGFKvfk5GS++uorYmNj+fDDD0lOTmbOnDk0adKE7t27m4OchYeHs27dOmJiYjAYDMyZM4eNGzeSkJBA1apV6dOnDz///DNarZb69eszcuTICruGQskZw6KkP0DVrN++wDmgM5D0QJnEAupOBU4CJ6tVqybLk3379sklS5bItLS0YtfR6/UyNjZWZmRkFLuORqORsbGx0mAwFKu8yWSSaWlpMjk5WZpMpmL3U1mx5LV8+OGHskWLFjIqKsoict28edP8WZpMJnno0CF56NAhaTKZ5O7du2VISIg8cOBAgW2sW7dOvvbaazI9Pb3M8pSExYsXS39/f7l582Z57do1OW3aNDl79mx58+ZN2bt3b/nzzz/L9u3byyZNmsjq1avLAQMGyG7dusnOnTvLESNGyGeffVaeO3dOdu7cWY4aNUpOmDBBvvPOO9LGxkZOmjRJ3rx5s0zyhYWFyf/85z8yMTFRTps2TcbGxkoppczIyJC3b9+WH374oTx48KDU6XRy+/btcvny5VJKKZcuXSoPHDggT506Jb/66itpNBrLfK9KgsFgkDExMfKVV16RarVaRkREyFmzZslLly7J9PT0XM+wyWSSv/zyi9y4caM0mUwyISFB7t+/X77xxhtSq9VKjUYjIyMj5Zw5cyr0ewyclAXo5jLNG6SU4Vm/Y4DfgTZAdJYJhqzfMQXUXSKlbCWlbFXe5ocmTZrQu3dv7O3ti11HpVLh7e1dotGivb093t7eJXJN3LNnD1u3bn0s7Ov79+9n8+bNeWKClIbx48fzySefFLnlvDhs2rSJYcOGcevWLSBzSt2+fXvat2+PEIKWLVvy+eef06RJkwLbCA8P58aNGxgMhnzP6/V6fvrpJ3bv3l1meXMSGhpKly5d6NOnD3Xr1qVatWrcvXsXtVrN8ePHCQsLIykpic8++4yIiAgCAgJo2rQpJ0+eJCkpifXr13Pw4EHOnTvH7Nmz2bt3L87OztjZ2TF37lxzgK/S4uXlhYeHB0uXLiU0NJS0tDTzubCwMNLT03FycjIH0comPj4eHx8f3NzcSE9PL5MMJcFgMJCUlERGRgYODg7mWYKLiwvt2rXjwIEDrFq1KledtLQ0zp8/b35eUlNTuX79Oj4+PmbTy4YNG+jWrVuFXUdRlFqxCyGchBAu2X8DvYGLwCZgYlaxicDGsgqZEykl4eHh3L9/v9ibT9zd3alevXql8QW/cuUKf/zxB0ajkYYNG9KiRYvHwtMmJCTEYtdSrVo1OnfuXOSLVWZtdy/sWWjbti2zZ8/OFY0xp23dzc2N7t27FxpYavr06axYsaJAU41er2f16tXs2rWrUHlLSvv27dm+fTuffvopW7du5eDBg9y8eZNly5aZywQEBFC9enXs7Ox44403cHR0xNHRkV9++YW33nrLvCu4bt26ueLUWGIwYWdnx7Rp0xgzZoy5fZllw+/QoQMtW7bkxo0beUaUQUFB3L59m8jISDw9PSvMDBMXF8f69es5e/as+bmRUmJvb8/w4cPp06ePeQCQff7OnTt4eHjg7u6OXq/Hx8eHUaNGERERQWJiIqtWrcLFxYUePXpUyDUUh7LY2P2A37M+EBWwUkq5QwhxAlgjhJgC3ANGl13M3Jw4cQKdTkdgYGC5PBBarZbExER8fHzKxTth+fLl7Nu3jzZt2hQaEuBRo6CwAuVJZGQkr7zyCpMmTSowZk5wcHCZR6YqlarQZ8HBwYFly5YVGCdcSsnt27fN8hT3ue3fvz/9+/fn8OHDnDhxApPJRGBgIBcvXqRHjx7UqlWL1NRUHBwc6NWrFy4uLkycOJFz584xb9487t27R7Vq1ejZsye2trZ06NCBmjVr0r17d/73v//x0ksvlSiy5YMYjUbWr19PWFgYY8aM4datW3h4eHD9+nVOnTqFo6Mjo0eP5vbt22zbtg2tVku9evXo3bs3P/74I0ajkbFjx5a6/5Li7+/P5MmTSU1N5YcffiAuLo41a9bQp08fli9fjtFoZPjw4Wi1Wg4fPkzXrl2Jioqid+/eqFQqoqOjWbFiBQaDgb59+6LX680x19etW8fo0aMrhUfTI7fzVEpJUlISJpOp3N70ly9fZu/evYwYMQI/P8uv/YaHh5OQkEBISEiJZhFqtZqjR49Sv379Mi96PUoYjUZiY2NxdXXNEzcmIiKCl19+maeffprevXs/JAmLxmQyMX78eBQKBcuXL38sZmhWHi6P1c5TIYTZB7q8qFatGt27d8fd3b1c2q9atWquNFzFRafTcffuXfz8/P5Rij0sLIzBgwczdepUZs6cmetcQEAAK1asqNQui5D53M6aNatI90qj0cjly5epWbMmzs7OFSihlceJR06xVwTOzs4WjSsOf4clKIsCcnd3Z/z48RZ3/8tv1laZFKXJZEKr1ZpTkeXEUn7olvh8CiN7wbao/g0GAydOnMDf39+q2K2UGqtirwBiY2N5++23GTVqVJlWzoUQJfLsKQopJYmJiZw/f55z586RlpaGs7MzzZo1o3Hjxnh4eORSdMVJ7lEeZOfcLC/vKSklJ0+eRKPRPJSMN0ajkfnz5+Pq6srMmTMZNmyYValbKRNWxV4BZGRkEBoaSmJioSFzKhSj0cixY8dYsmQJjo6OtGrVisDAQJKSkvj111/54YcfmDp1Ku3atTOvA0RHR7Nx40Z69+5N7dq1K0xWlUpVpgW+4pCenk56evpDCfMrpSQyMhKNRmPuv7CE0eWBUqm0iJvqw+BRlt3Z2blcXuKP3OLpo4jMsZ26olwusxVFjRo18oxApZTs2rWLL774glmzZqFWq/nzzz9JTU3FxcWFnj174uLiwieffMKMGTPo06ePObHv9evXqVWrVrns0Lx//z6nTp2id+/ehe7CvXz5Mnfv3qVXr14WmTnk2tjxEDIcyaxsQEIIpJSsW7eOa9euVVj/CoUCV1fXRzJColKpxNnZuVLmki0OXbt2pUuXLqWq+1gtnj6KCCHKnDGmpJw9e5a4uDiCgoJyKXYpJTdv3uTnn3/mpZdeYseOHRgMBkaPHk3VqlUJDQ1l06ZNKJVKZs2axY8//kjdunWpWbMmjo6ONGvWrNxk3r17N4sWLaJx48aFzgjWrFnDzp07ad++vUUW0h92vJgHswFVpPuflccT64g9CyklFy5cID09nbZt26JQKFi3bh03btzgxRdfLNA/WavVEhcXh5+fX4XanYsiJSWFjIwMvLy8ciktKSUff/wx9vb26HQ6dDodw4YN47fffuPWrVvUrVuXIUOG8Pvvv5t3DKrVal566aVyn20kJiYSGhpK/fr1C30RRkVFkZCQQL169SrNpjMrViqa8g7bW65IKTl37hwajcbi7W7fvp0tW7aY7ZoxMTFERUWZ/79y5QonT54s1H73xx9/MHDgQC5fvpzn3K1bt1iyZAlRUVEVbgN0dXXF29s7z0hUr9dz4cIFmjVrxvHjxxk+fDiLFi3C3d2dgQMH4ujoyKeffspTTz3FiRMnaNiwIZcuXSpwK70l8fDwoEmTJkXObvz9/Uu8B+BRISMjgyVLlhAdHQ1kDhyyn32NRkNKSgpqtTpXHYPBQFpa2kNPA2gwGEhPT0er1ZplMRqN5vULg8GAyWRCrVajVqsfqrwmk4n09HSzHCaTibS0NNLS0szRGnPKn5aWhlqtNsufXS67nezrqyxUelNMtmL39/cvUQqpnA9NftNsKSWrVq1Cr9fTr18/FAoFXbt2NdtZAV555RUMBkOh/TZq1IgpU6bk65d+6tQp3nnnHb788ku++eabQt3dKorY2FgyMjLQ6/W4ubkRFRVl3vTz+eefM2LECOzt7QkLC8Pb2xuDwYBGo0Gv1xc4aykNRX0+/1S0Wi1Lliyhc+fO+Pn58eGHHxIbG8tXX33F7NmzuXHjBpMmTWLChAnmOocOHWLWrFmcOHEi312PSUlJhIeH07Bhw1zHLXnfTSYT69at486dO5hMJp5++mkCAgKIjY1l48aNJCYmUrduXTp37sySJUuIi4vjww8/tOgzVRJSUlL4+uuviYiIYMGCBSQlJfHyyy/TsmVLunXrZjY5RkZGsmHDBiIjI9Fqtbz66qts2bKF+Ph4vLy8GDhwIMuXL0er1VKjRg3GjRtXKZ7nSj9iF0IwZMgQvL29S1Tvr7/+YurUqcTGxhbY7oIFC/jkk0/MC2YqlSpXbGg7OzucnJwK/aBq1qzJv//973zlGzBgAGvWrKFr167lvqmquGQv0GX/VigUGI1G7OzszD8mkwmFQoFOp0Or1ZaLDTo2NpapU6daPGjWo46zszO//fYbNWrUADJ3G9++fZv9+/dz+/ZtLl26xJkzZ3juuecYNmwYrVu3Zt68edy+fZtZs2bRtm1bmjdvTvPmzfn4448ZMmQIPXr0YPLkycycOZMDBw7Qrl07tm3bZlG5L126xBtvvEG/fv3YtGkTkydPxmQy4evrS6tWrTh37hyLFi1CCEGvXr3Yvn37Q82x6urqyjPPPMPOnTu5ffs2BoOBw4cPExwcnGvQERgYyJQpU0hMTCQtLQ0fHx/at29PQkICCxYsID4+npkzZxIUFMQ777zDhQsXHto15aTSj9izs9yXlPT0dOLj4wucHgkhyiVcQE6cnJzo2LEjHTt2LLBMfHw83377LYMGDaJx48blKg+At7c3Li4umEwm7t+/jxAChUKBi4sL//rXv4BM90J/f3+uXr2Kn58fzs7OFo9/YTQaiY+PL1Vkv6SkJObOnUvHjh0ZPny4xWS6fPmyOZqiJfcLlASFQmFW6tlotVqio6PRarXExMRw9+5dFAoFt27dwtvbm8mTJ3Pt2jU++ugj6tevz4wZM/jzzz+JiIjgypUrPPPMM3Tq1Ik+ffpw5MgRDAZDgXF1SkvVqlVp3LgxL730ElevXjXvjBZCEB8fT2JiIunp6ebnLS4u7qGYYlJTU0lKSkKlUuHk5ERCQgI6nQ6FQkGvXr2YM2cOLi4unD592lwnLCyMn3/+mY0bNyKEICUlhfj4eNRqtfk5/uabb2jcuHGhEUIrkko/Yi+IbBexgiLUDRw4kF9//TVXRL/KSEJCAhs3buTq1asV0p+NjQ3NmjXj2LFjBAUF8fPPP/P888/j6urK4sWLcXd35/nnn2fJkiX06NGDjIwMmjZtavGFYX9/f3799VcGDRpU4rrp6els3LiREydOWFSm8PBwrl279lBHkvlRvXp1Ro0alSu5Rv/+/enVqxcnTpww2+OzbcN3797N5f7XtGlTWrZsSf/+/Tl79iz/+c9/LP55enp68uyzz/LSSy8hhKBPnz7o9XpOnTpFSEgIgwYN4ubNm6Snp5vvb05bdkVx6dIlfvnlFzZs2GDOmGQwGDh06BDDhg3LNQjLzly1c+dObGxsaNKkCaGhodja2jJq1ChSU1O5dOkSI0aMQKfT8fHHH1ea8NuVfsReEMnJyUyfPp2+ffsyceLEPOcVCkWlCLSUlpbGhQsXaNiwYb5hYYODg9m6dWuFZu4ZPHgwr7/+OhMnTuTw4cNs376d8PBwrly5wsGDB7l79y6Ojo60bduWlStXmmOcWJIHXfxKgr+/P4cOHbJ4xqnOnTvTvn37PIHGHiZNmjQxK+k2bdqg0+lo06YN0dHRGI1GBgwYQK1atWjXrh3vvfcenTt3JikpiVq1atGkSRP0ej3+/v7Y2dnRs2dP/vrrL6pXr14uduC7d+9y6tQpevToQb9+/Xj33Xdp27YtP/30EykpKXz66adERUWxfPlyunfvznvvvcfrr7+Or6+vxWUpiHbt2tGuXTtiYmL44IMP6NGjBwcOHADg4sWLaLVaevbsiVqt5oMPPmDWrFmkpqby+eef4+Xlxc2bN/nmm28wGAzMmjWL5s2bExgYiJOTE4sXL2by5MkVMvMuikfW3TElJYXXXnuNHj16MGLEiHKSrOwcOnSIqVOnsnjxYnr27Fmiunq9nvDwcHx9fS2qbKSUHD58mC+//JInn3wSBwcHPvnkEzQaDTY2NsyZM4f09HR+/fVXnn/+edq1a2cRRZCcnExycjJVq1atdB4tUkqz9wNkmtGcnZ0rfCFMo9Hw5ptvMmvWrDzp78rCunXrWL16NS4uLvzwww8Wa9fKw6Mwd8dHVrFb2qsiO162RqMhJCTEYqP9lJQUjh49SuvWrUu8gHrhwgWeeuop3nnnHYYNG2YRebIxmUxcvHiRPXv2EBoayo0bN8yJexs3bkxAQAC9evWyaC7Kjz76iI0bN7J58+YSL4aXF1JKYmNj2bJlC/v37zevyahUKtq3b8+QIUPw9fWtsNlfamoqo0aN4rPPPqNu3boWa9fqhfT48UjvPC3ogSyPh/PatWskJyfToEEDi7Xp6upa6jjhVatWZfr06TRv3txi8mSjUCho3LgxNjY2/Pe//8Xb25tVq1bx1FNPcefOHZ577jlq1apl0fvcq1cvi0QtvHHjBqGhoXTq1KlMtmIpJWfOnGHhwoU0aNCAadOmmZ83hULBX3/9xezZs5k1a5bFZi1F4ezszPr16y3uBmhV5v8sKv2I3WAw8Nxzz/Hqq69adATzIFJKNBoNJpOpSBfHxwWTycSCBQuIiIggLCyMw4cPm/2nq1Spwpw5cypFNpgHefvtt9m1axfbtm0rkxvp5cuXeeONN5g4cSKJiYns27fPrFB1Oh1PPPEEAQEBLFu2jNdee43mzZv/I54LK48Gj/SIHTAr3PJECFFui2bZLlGurq5ldqMzmUwkJCTg4OBQ5sXDiIgIfv31VxwcHJg0aRJKpZJ27dqxZs0aNBoNTz31FIGBgWXqozyYOnUqQ4cOLdOCs0aj4bvvvmP06NHcvHmT8PBw/v3vf5uTqyQnJ7N69WoSEhIYNWoUS5cuZdGiReW+ocZkMhEZGVnunjnZexms/M3DuCfu7u7lktCn0it2pVLJL7/8Uik8XEpLWFgYo0aNYubMmfl68JSE1NRURo8eTY8ePXjjjTfK1FZkZCQ6nQ43NzcOHTrEvXv3sLOzIyMjg6ioKCIjIy2i2E0mEwaDAZVKZZHPsbQZqLKRUprNbtWqVWPHjh1MnTqVpUuXmkMr+/v78/zzz/P+++/TvHlzDAYDZ8+epW3btmWWvzBSUlLo3r07gwcPLrf481YqDx07dqRDhw4Wb7fSm2IeB5KTk1myZAm9evUqc3RErVbL999/T8OGDcuUtAMyzVxJSUlotVqOHz9O06ZNcXFx4ebNm8THx9OrVy+LbNQ5fvw47777Lh9++GGl2MCRHU4iLCwMjUZDgwYNOHr0KLGxsXTq1MmcV1ehUFCnTh3Onj1LQEAAKpWKyZMnl+uoTqvV8tlnn/HUU0/9o9IfWik5ZQoCJoT4QQgRI4S4mOOYpxDiDyHEjazfHlnHhRDiMyHETSHEeSFEC8tdxqOLm5sbr7zyikVC3trb2/P888+XWalDpudHdjyYtWvXcuXKFXx9fenQoQODBg2y2O5LJycnqlSpUqJYPzkxGAzcvn2blJQUi8gDmbMVHx8fQkNDCQ4OxmAwMHDgQNatW8fGjRupW7cu169fx9/fn7i4OLy9vYmLi7NY/wVhb2/P//3f/1mVupUyUZx58U9A3weOvQbsllLWAXZn/Q/QD6iT9TMV+LqsAkopSU5OrtDoiEajEZ1OV2l2kZU3V69epX///ly8eDHfvKJlJSQkhCVLlpQ661JERAQjRoxg5cqVFpPJ3d2d5ORkfH19iYqKIjAwkMjISLp168YTTzxBTEwMVapUISkpCTc3N1JSUkoV2qKkmEwmEhMTK1WkQCuPHkUqdinlfiDhgcNDgJ+z/v4ZGJrj+DKZyVHAXQhRpj39RqORUaNGcfHixaILW4jbt2+zYsUKEhIevGzLkB0m1BJmsLK2ZTQazTtPL168aN6ebkmyg4iV1oTh5eXFrFmz6Nq1q8VkatasGTdv3qRTp07s2rWLQYMGcffuXWrUqEHNmjW5ffs2Y8eO5c8//6RFixacO3fOoj79BZGSkkLHjh25detWufZj5fGmtCtZflLKyKy/o4DsaFpVgdAc5cKyjpUaIQRt2rSp0OiIrq6uVK9evdwCQf3444/MmDEjT1zt0pCRkcHs2bP5+uvSTY5u3bpFYGAgo0ePpnfv3ly6dKnMMlkaJycnJk2aRP369S3SnhCCOnXqYDAYkFJiZ2fH5s2bmTFjBmvWrGH58uVMnjyZXbt2YTQacXBwIDU1tVyzR2VjY2PDE088UWqzlRUrYAGvGCmlFEKUeLgohJhKprmm0K3TSqWS999/v/QClgI/P79yjfyYnV/T0m2WBm9vb5588kkCAgLw9vYul7yXN2/e5IcffuC5556jevXqFm+/NLi6ujJ58mQ+/fRTZsyYwZkzZzhw4AAnT55EpVJx6NAhDAYDw4YN48cff2TSpEkWj02TH05OTixZsqTc+7HyeFMsrxghRA1gi5SyUdb/14CuUsrILFPLXillPSHEt1l/r3qwXGHtV1avGKPRSEpKCteuXSMmJgZHR0fq16+Pn58fKpWq1NPybMVuiTjnlmwrG5PJhMlkQqlUcu/ePbRaLXXr1i21q+LBgwd59dVXWbx4Ma1a5buIb0ZKyf79+0lOTmbAgAEWjykjpcRoNKJQKJBSsnv3br777jumT5/O6tWr0ev1GI1GbGxsePrpp/n00095+umnzclYyhspJTqdDltb20faxddK+VMeG5Q2AROBj7J+b8xx/HkhxGqgLZBclFIvDtkvn4raPJDt7rZs2TIOHDiAv78/VapUIS0tje+++44qVarwzDPPEBISUiqZHlTCZYnjUR5JME6cOMG9e/cYMmQIly5dIjk5mdq1a5da0bRr147t27cXe8S7evVqwsPD6du3r8UVu16vZ9OmTVStWpX27dvTs2dPqlWrxvnz5zlx4gT29vYoFAr0ej3Xr19n3rx51KpVq8KUbHp6OmPGjOHTTz+lTp06pW6nqAGbdXPS401x3B1XAUeAekKIMCHEFDIVei8hxA2gZ9b/ANuA28BN4DtgRlkFNBqNPP/889y+fbusTRULKSXR0dG89tprpKenM2vWLDp06ICdnR1BQUFMnz6dNm3a8N5777Fv3z6LeM6kp6fz8ssvs27dOgtcQdlxcXHB09PTnC5w4MCBZVKwKpUKV1fXYrfxzjvv8NVXX5VLcnAhBB4eHuZdqwqFguDgYI4cOcKkSZNITU0lOTnZHNI4MDCwQiNRKhQKatWqVWTe16JITEykS5cujBo1ioEDBzJnzhwGDhxI165drVmr/gEUOWKXUo4r4FSPfMpKYGZZhXqgTaKiotBqtZZstkA0Gg0LFy6kXr161KxZk6+++oqQkBBCQkKIjIzkm2++oXnz5kyYMIEvvviCatWqUbNmzTKNgEwmE+Hh4cTHx5dJdrVazXfffUerVq144oknSlzfaDSSkZFB/fr1CQkJAShSuWabDlQqlUXiypR3ZisbGxt69Pj70ZVScurUKS5fvkxMTAwBAQEYjUYOHz5MVFQUJ0+epFOnThU2wnV0dOSzzz6zSDvPP/889erVY8yYMWzfvp3Zs2ezZ8+ecvP2slJ5eCRCCqxatarCglGdPHmSpKQkevXqxbJly3jzzTeJiIjgzJkzaDQaWrdubU45NnjwYH766Sf++9//lml06eLiwvLly8s83Ver1fz2228YjUZat27NrVu3CAgIKHYsinv37vHXX38xcOBA/P39i1VHo9Gwdu1a6tevX+R2+6tXr3Ljxg369OmDra0tBoOBP/74g6pVqz60HakGg4FVq1Zx9uxZnn32WWrXro1er8fW1pbdu3ezbNky2rRp89BS5ZUWe3t7hg8fziuvvEJSUhJdunRhzpw5eV5QK1euJCwsDCcnpwpN9mIl89mrW7duoakzS0ulV+xCiDJPS4uLyWTijz/+oH///mzfvp0JEyZw8OBBTp06RfPmzYmPj+fs2bPMmzePefPmMXPmTHbs2EFCQkKZRpllySaUE09PT9avX4+joyNpaWns3buXtm3b0qJF8TYAu7m5Ubt27RIFQ1OpVAQHBxfr+tevX8+GDRto1aoVJpMJe3t7PvzwQzp06PDQFLtCoaBDhw5otVq0Wq05XZutrS2DBw+mQ4cOFWqKMRqNnDp1igYNGpRJ0ep0Ol5//XV+++03li9fztatW/n000/zxLvp1q0bMTExbNu2jaFDh1rgCqwUl4iICP78889/pmI3Go288cYbTJ8+vdxd5dLT07lz5w6DBg0iKiqKgIAAfv75Z8aNG8eyZcvo2LEjer2eu3fv0qBBA+7du4e9vT2pqanlYj6IiIjg008/5amnniqW4lMoFObAUdkjtvzS8RWEl5dXiTcB2dra0qlTp3zPGY1GIiMjcXd3x9nZmWeeeYYhQ4ag0+nYunUrvXv3ZsmSJRWyo7MglEolY8eOZezYsSxatAidTkdwcDDDhw8vFxt/UaSlpTFt2jRWrFhRprwAaWlp7Nu3j+DgYDZt2sT169cxGo2kpaXleiYCAgJwcHDA3d29TIHVrJQco9FYbia+Sq/YpZScO3cuV3Le8sJgMKDX61EoFOYbbmtrS2JiIklJSdy4cYOaNWsSHx+Po6MjGRkZKBSKcgt3kJKSwrFjx+jevTvBwcFcvXqV+vXrmxNVSCnRarXY2NjkMVUplcpytVUXh+joaIYNG8akSZOYOXMmvr6++Pr6otVq6d27N4GBgeW2ESfbrREy70VxvkAxMTHMmTMHZ2fnhxaH3tHRkffff7/YprCC8PT0LDDZt9Uj5vGn0jvKKpVK1qxZQ8OGDcu9LycnJ3x8fEhPT8fGxgaDwWBWok899RSDBg3i2LFjtGzZkjt37uDr64tOpyu3jSt169Zl69at9OzZk/j4eE6cOJFrgTVbca5evTpXvejoaNauXUtkZOk9TaWUhIWFERMTg8Fg4OrVq/m2l+1Hn597nZubG5MnT86zkGtvb0+dOnXKfXflnj172L59e7E3b6WmpvLzzz9z+PDhh6b8bGxs6N+/f5l3WgshzAndH/yxKvbHn0qv2IUQuLi4VIid09bWlvbt23P48GHatWvHpk2bmD59Og4ODuzfv5+4uDimTJnCrVu30Ov12NnZ4eDgUG7hDhQKhXn0WLVqVcaNG5drumxnZ0fjxo3zTKFPnTrFtGnTOHLkSKn7NhqN7N27lxMnTqDT6di+fTv5bSL79ddfeeGFF0hPT89zzsnJienTp+e7FT8yMpKbN28Wy100LS2NhISEEu+u9fT0LFFuVVdXV2bOnEn37t1L1I8VK5WNSq/YjUYj8+bNIzw8vEL66969O+fPnyckJASNRsPWrVuxtbVl48aNHD9+HFtbW1atWsWIESNYvXo1o0ePRqlUotPpLB4mICcqlQp3d/dcJgIPDw8WLFiQJ4Rv27ZtWblyJTY2Nvzvf/8jNTU13zZNJhM//fQTa9euNY+6TQYj2tgENPcj6FC/ETGh4SxfvpxBgwbRrl27PG1kK92S+vPPnz+f6dOnFyua5OHDh9m8eXOJsgoJIWjZsiXt27cvtreRm5vbQx/Nmkwm4uLiyj2DkpXHm0qv2KWU/PHHH8TExFRIf/7+/jz33HN89913DBw4kPbt27Nu3TqCgoI4fvw4KSkpvPTSS2zfvp2aNWvSuXNnduzYwc6dO0vVX/b2fUu+FLy8vOjTpw9hYWFs3Lgx39F0dt9//PEHe/fuBSAjJY2LHy/lz24T2BIygGM9JnPj1UWc/XUTQYFB+Wb0efrpp/n5559L7MHx5JNP8uKLLxbL46lRo0a0b9/e/FIrzPxTFubMmVNhHlgFkZaWxtChQytsQ56Vx5NKv3iqVCpZu3ZtueQFzA8hhHlDyrp162jTpg2JiYnUq1cPW1tbDhw4gJeXF7Vq1eLpp5/GxsaG4ODgUo30pJQcPHiQ9PR0evfubXFz06RJkxg9enSBpiKlUslXX32VuQCs1bFxzrt89/NPdNQ74oCC87p0DECPK24kHT2Lb5c2ea6ztDK3bt262GWzk05IkyT1xj0Sz1/FpDfgVC0Aj+YNUdrbWmSkXRkSd9va2tK/f3/z2o4VK6Xh4T/JRSCEKJGd1BIolUo6d+5McHAwb731Fra2tuzbt4969eqRkJDA22+/TYsWLcyKoCw+2HZ2dhZzezIajYSHh+Pm5oabmxsODg6FLlAKIcyuhlG7j2BY8xeN9LbokdTCFgcUHCOV+Ohorn+xHM+WjbBxKd8Ih9evX+err77i+eefz5WYQ5+u4dCXP3Hvp9+xuR5GqkmPwceNBt070mbeyzjVCHzoZpSikFKiT05FHRqJUZeBrbsrjkEBKGxtzLLb29vzn//85yFLauVR55EwxaSlpVVoBiXIVHq3bt3CYDDQpEkTMjIy8PHxMQe0slQfbdq0oWvXrhZRSomJiYwePZpvv/22RPWklIRt+gtS01Hytxwx6NEisZeCyJ0H0cWV/1b0xMREzp8/n8u9VZpM3PhpHSv/O49fr5xAY9SzXyZxNOY+G39dw4mZczGka0hPT+f48ePlEnq4rEijiag/D3PoyTlsazOSDW1GsK3rk5x++SM0EdGFmpWklObELxqNplj9ZWdiyv7uJCYmkpCQUOB6i5XHi0qv2LMzKFV0AgitVsuyZcu4c+eO2VRSp04d80LerVu3Smzjzc82XNbsQjlxdnZm2rRp9OzZs2QVpcSg1pAtlgQMSOrhQBC2RKPHqMvAmJG5oJecnMzNmzfLJX1bq1at2LJlC82bNzcf00bHc/+n32mdYYcjCtQYUSDojhv3pY7YQ6eJ2n2YlJQUTp8+XSG5SUuClJLYw6c5Ovl1Irbt47A2jt0ykXXhVzn39XKOPftfMhJTCn2evvzyS2rWrMno0aPZunVrkesy8fHxhISEMHnyZG7dukW9evUYP348o0ePLo9LtFLJqPSKXQhB06ZNK3x3Ynh4OKdOnSI9PR0HBwdiYmLMcbLv3LnDmTNnStxmREQEv//+O4mJieUgceY0ftKkScUOIWBGCFzr1iDKxsRl1FwgnTOks5UEUjASjD1O1ati45Jp9z137hwbNmwol01jSqUSR0fHXJ4s2ph4Es9ezZpLCCQgABUCExJDShpxR87i6+PDuHHjqFGjhsXlKgtGjY4bX69EEx6DCUkyBvywwQQYTSaidh9hwYTn+PjjjwtU1rNmzeKVV15h586djBs3jmHDhhXap4eHBxMmTECtVmM0GgkMDKRXr14FLqRbebyo9DZ2pVLJRx99VHRBCxMYGMiSJUu4c+cOGo2GOnXq4OXlRb9+/XjhhRdo2rRpofUzMjLQ6/U4OjqaR+Mmk8mcju1hIKUkISEBGxubXNvKhRBUG9mX2l+vIuBO3ne9UCmpPnYA9j6eAFy6dIkNGzYwcuRIvLy88u0nW+lbwoVQSolEkoIRDUaMSPRIbqDBM/sRlhKFUvlQwxMUhD4tnchdh8ieEjmhRI9EAEYkpowMNIfPQftGBbbxxRdfkJKSwooVK0hNTS1yYKFSqXJ5MQ0dOpSePXty6tSpXOU+//xzrl69WmkyW1mxDJV+xP6wsLOzo23btpw/fx6NRkN0dDQpKSn06NGDHj164O3tXajCOnHiBGvWrMkVbjgwMJCRI0fi6elpMTmllOj1+mKZRXQ6HU8//TTvvfdennNO1arQ6rM3caxeBaH629NF6ehAtVF9qT/7X+bjffv2Zc6cOQWGLJBSMmvWLF588cUSvcSywwA86BNv7+uFS6M63EOHJzYkYSQEB2LQ0woXVC5OeLV5OEHEioM0GDFlmbEMSOIxEIIjzihJw4hA0Kd7T15/7TVMJhMXL140j6yzwyI3btyYQ4cO0bdvXy5evMinn35aeJ9SYjAYMJlM6HQ6PvnkE7Zs2ZJnP8iMGTOYO3euNbLjY0alH7GbTCYOHDhAixYtHsrDZ2try/jx47GxseHtt99myJAhxdoKHxQUlCdGeXlkO9LpdEyfPp2QkBBeeeUV4uLiuHLlCq1atcojp0qlYsiQIQQEBORpRygVVOnXhR5//sS91VtJvnwTpYM9gUN64tetLSrnv2ceNWvWpGbNmgXKJIQwp5IryfWaTCa2bduGu7t7rsBiDn7e1Jk4jPQrtzDp/t64U4vM6/Nq24SAXk9UWq8YlZMDLvVrknDiArYIGuPIQVLwRoU/tgilEo9m9VEolWRkZHD8+HH8/PxwcnJCo9HQtm1bbt++ze+//46Uko4dOxbpZpqenk5kZCT+/v789NNPDBgwgNDQ0DzrL0qlskKjV1qpGB4Jxf7aa6/x+eefF5kvszxxcHBAoVAUe8GwWrVqhSbpLgyDwcCBAwfw9vamcePGhZYVQlClShXztHvnzp18+OGHrF27Nk90QJVKxZQpUwpuS6nApXZ1Gr4xPdNsUMoXkRCCsWPHFnhep9MRGhpK1apV87x8nJ2d84QNFkoFtZ4ZhT4ljTvLNpJ+NwxpNGHr5Y7PEy2J6t6IV995i7fffrtIU8ytW7e4ceMGXbp0KfdYNdnYODtRc9Jwki9cx6TNoDYO1Obvvh2D/Kk+doA5RPXQoUPNgxgbGxvmzp3Ld999R79+/QAIDg4usk9nZ2eLJOyw8mhS6RW7QqHggw8+oG7dug+l/2y3sZs3b+Lo6FghykBKSWJiYr67IHU6HTqdDmdnZxQKBXZ2drz//vvm871796Zq1aplWkAUQoCFRr9GoxGDwYCt7d+biE6fPs3UqVP55JNPco0glUplgWGDbZydaPTmDKqN6kfCqYsYdXqcgwPxbtuM5WtWc/PmzQK34V+9epXt27czceJEUlJSiIqKKrb7bLZJQ0qJjY1NgS+6bLdclUqV5xkRSgW1Jw1Hcz+S20t/QxeflLkmYGuDU42qtPz0P7gEB2WWFSKXqU6v13P+/HkMBoPZhNavXz8GDBhQLPmt/DN5JBT7wwzK1LJlS7Zs2YKzszPPPfdchUxbVSoVgwcPzleJ/Pjjj6xdu5bVq1fn2eIvpcTb27vEMdUtRXYKw2rVqpm9Wi5fvszJkycZPny4eTRdu3ZtXnzxxXwjdhY2QxAKBW4NauFaP3PEqtVquXnvLiNHjmTcuHEFhgM4f/48v/zyC/3798doNGI0GnPZ/qWUnD59mvT0dDp27Jgntkx2SAt/f3969OiRb5x2rVbLpEmTaNy4MW+//Xae61E62NN07iyChvcmfPNfGNLUONeqRtCwXjgE+CAKiGejUqnw9PSkW7dudO7cGYB69eoVeI+sWIFHQLE/bIYMGVLhfQohCtzeHh0dzf379/OMTg8dOoROp6Nbt26ltjXrdDoSEhLw9vYuVZKJ06dPk5CQwNixY83K0cPDg+rVq+dSuj4+PkyePLlUMsLfyjImJoa//vqL/v37FzpDGTRoEJ06dcLHx4fw8PB8k0V/++23REZG0q5duzznqlSpws6dOzlx4gTt2rXLN7yFUqmkQ4cOBAcHo9Pp2LFjB7Vq1TKb0oQQCFsbvNs0wat142KbuoQQ1KpVi5iYGLOnUUWZkKw8uhSp2IUQPwADgRgpZaOsY+8AzwKxWcX+I6XclnXudWAKYARekFKWLjpWJUetVnP06FHq1atXoZlnQkJC6NChQ5m/3FJKc9x5Ozs7IDPn6Z9//smQIUPyvSaj0YharcbBwSHfF88TTzxBRkZGrllNYGAggYGBRcpjMplQq9WEhYWxbNkypk6dWqQ5KSAggGHDhuXrcpmTnKEVqlevnq9r33/+8x90Ol2eF5oQgmbNmvHaa68RFxdX4AK+ra0tL7/8MkCRiddLYurS6/VcvHiRY8eOceHCBQB69uzJwIEDi1Xfyj+T4ozYfwK+AJY9cPwTKeXCnAeEECHAWKAhUAX4UwhRV0pZ6ngAUkq2b9+OjY0NPXv2rDSeDxkZGdy7dw8/P79yUewmk4mMjAxsbW1zmQZGjhzJiBEj8tyHB5NZFIVWq2XNmjW5kulWrVqVHj16FKgoo6Oj2bRpE7169aJWrVp5zpfFh1ytVrN69WrS0tLYv38/Q4cOLVKx29ra5uvhU1KEEMV6iRS3Lzs7O4vN9BwcHJgxYwbVq1fnxx9/xGQy8ddff1mkbSuPL0UqdinlfiFEjWK2NwRYLaXUAXeEEDeBNkCpMz4YjUYWLFhAUFBQybfKlyNubm6MHz++3CICHj58mLlz57Jo0SIaNfp740p+LpOlednZ2NjQpEmTXL7oTk5OhdpvXV1dadq0aZEj5NJga2tLkyZNCAgIYPLkyeWWlaogHgzzUBZKWl9KSVRUFEqlEh8fn1z1NRoNbdq04c6dO+aIj126dGH48OEl7qMsMlp5tCiLVnpeCPEv4CTwspQyEagKHM1RJizrWKlRKBS88MIL+WbheZgIIcwmjPLA3d2d6tWrEx4eTo0aNSwexlWlUpXYfdTZ2Zn27dtbVI5sbG1tadOmTYHnTSYT9+7dw8nJCV9fX4v3n538uUmTJqV2Uy0tJpOJffv24eDgwODBg3Ods7Gx4aWXXuKXX35h5MiRCCHyJFYpDteuXeO5554jPT2dadOmMXny5GInILHy6FHaT/ZroBbQDIgEPi5pA0KIqUKIk0KIk7GxsQWWUygUDBs2jJo1a+YZZWRkZJCYmFjhkR8rgkaNGvHCCy8wZ84cdu3a9bDFsRjZycmvXLlSol2pGo2GKVOmsGDBgnKRy2g0kpKSUqyMTpZGoVDQtWtXOnTokOecXq9n8eLFXL9+nXnz5vHGG2+wfv36EvfxzTffoFAo6NevH++++641Q9NjTqkUu5QyWkpplFKagO/INLcAhANBOYoGZh3Lr40lUspWUspW+WXmKQ6bN2+mf//+3Llzp1T1S0psbCzXr18vkQ/0nTt3CAsLK1V8mKCgIF599dVCR7LFkaE8sg0Vl6SkJK5cuWJWJCaTiRs3bpQ4Q5CdnR0vvPBCuUUndHNzY8yYMbliwFcUQgj8/f3x8fFBSsm1a9dQq9VApo39xIkT3L59m9u3b/Prr79y69atUvVTu3ZtevXqlevYypUr+fzzz63BwR4zSmWKEUIESCmzU9YPAy5m/b0JWCmEWETm4mkd4HiZpSyA2rVr07dv3wrLrnT58mVu3LhBUFBQsbxSTCYTR48excnJKd8F1mzFn56ejl6vz7MQ6+7uzlNPPVUqWaWU6GITSDhzGUNqOnZeHni0CMHG1blC7au3bt3i+PHj+Pv74+HhgUKhYMCAASWWQaVSMXTo0PIRkkzlWhm21uv1eg4ePMjgwYNxdHTEaDSyZ88e80zizz//LLUSvnfvHgcPHsx1rFu3bjRq1Ij9+/eXWXYrlYfiuDuuAroC3kKIMOBtoKsQohmZobvvAs8BSCkvCSHWAJcBAzCzLB4xRdG0adMCoyxKKYmOjsbW1jbfoFuxsbGcOXOGtm3bFunNIaXkzJkzGI1GBg8eXGzbukKhoE+fPoUqjI8++oiLFy+i1WoZMmRIrs0tpcVkMBK+dS+XP1pCwtnLxOvUKFycqNOmBc3fm4VXm6boDQYOHTpEYGAgderUKXOfBRESEkJgYKA5mqQQotiumlJK1Gq1uc4/YcHP1taWQYMGmZ9JvV7Phx9+SHx8PJDpL7948eIStzt58mSeeeYZVqxYwauvvmp26wwICMDBwaFSvNSsWI7ieMWMy+fw0kLKfwB8UBahLIFWq+Xpp5+mQYMGLFq0KM/5tLQ0IiIi0Gq1xXLTi4mJISMjA29v72IvOgkhcHd3R6vVYjKZ8v3yzJw5k+TkZDIyMqhRowYZGRlcuHCBoKCgUi0SSimJO3qGE9PfRhMZy320XEaDV4oG2z8Pog2Nosvmb7EJ9CUyMjJPXBZLU1R6vsKQUrJt2zbs7OwYNGhQnnM6na7cF7ErGiFErs/d3t7enGw8Z5mS0rhxY44ePWqu/094Sf6TeSx2nur1ekJDQ/Hx8ckVPOmpp57C398/3zrVq1cnJCSE0NBQfH19833Qc9qle/bsiZQyV7niuMidO3eOl19+mQ8++CCPR0l2EpGcJCcnc/LkSYDSKXajkVvf/4Y2Kg6J5DoanFDghhI7FKTeuMe91Vto9OYMRo4cWalHakIIGjVqlK+Mer2e6dOnU7VqVd577z3z/S/qM7GkW2NJKG2/Dyrh0q6VWJX5P4tK7+8kpSQuLq7QqIqpqans3LmTGzdumI+pVCqefPJJevToUWC9xYsX87///S9P/O9s4uPjmTp1Kjt27EClUuUJAqXRaJg9ezYrVqwosA83NzeaNm1a7BjsLi4ujBkzJpfvekkwZeiJ3nscpEQCqRhxREEEGdxBCyYT0X8dBSmxtbUttWLPyMggJiamXL0rhBA0aNCAunXr5lFKCoWCkJCQPIud586dY9euXQU+L1qtlpdeeollyx7cb1e+REREsHHjxjLnYzUajSxcuLDoglb+0VT6EXv2dLxPnz4FJnZwdXVl0KBBeHh4FLtdIQT//e9/MZlMBZpWspMAZ3soPIjJZCIpKYm0tLQC+wkODuaTTz7JdSwtLY0vv/ySTp065XFxUygUJVoMNhgMZGRkYG9vn3kdEpCZLyoFUAVbnFGiw4SBzNGeNGV6yeQ3fsu+pmvXrnHjxg0MBgNVq1alSZMm+Pj4mDdkhYaGsnPnTgYPHlyskAGWRqVS8corr+Q5npSUxDfffIOLi0u+7oM5kzxn/3/69GmcnZ2pX78+kJkW8bvvvqNhw4Y88cQTVKlSJVcbGo2G1atXExUVxQsvvFCszVRGo9Fskisp2etFGRkZSClp0KABWq0We3v7Erdl5Z9BpVfsQgjatGlTqB1cpVKVWLkIIcxf5ILw9fVl9erVBSp+Jycnli5dWuIpbnp6Ops3by5Q+ZSEixcvcvLkSUaNGoWbmxsKWxu82zXjfmgUQkJTnDhDOnYoMmOAKxT4PNE8TzTB7OxFW7ZsYfXq1bi6utKoUSNsbGz4888/+fbbb+natSsTJ07E1dUVf39/OnfuXC67UAsjO4yuUqnM93OpU6cO0dHRXLp0Kd976+joyPfff58rXeGtW7fw9PQ0Pw+RkZFs2rSJ1NRU6tSpk69i37dvH9evX2fKlCnFUuxBQUGMHj26yGfFZDKZU9XlbHf48OGcPXvW/DnNnj2b+fPnW80rVvLlkVDsRSng8uy7sJABRZ0vCB8fHzZt2mSRKH2+vr7Ur1/fvIAoVEr8x/Xn7tY9iHQtDijpwN/5TZ2qBVDjybwhgfV6PV9//TUXL15k5syZREZGcvbsWQwGA3Xq1GH48OHs2rWLN954g7lz5+Lp6Vlqc1FZuH37Ni+99BKzZ88278A0GAycPXsWX19fAgMD2bx5c4HK9sHPTKlUMmTIkFwviWbNmrFr1y7s7Ozy/Yzc3d1ZvHgxBoOhwFlifHw8165do0WLFtjb2xfbxq3X6zl69Cg+Pj65rsFgMDB//nzCw8NZvnw5p06dyrPmY8VKNpXexv44olAo8PT0tIhir1KlCh07djRPy4UQuHdohvvzY3BtUAuFbaZbm9LRHs/WjWmz5D3c6ufOwCOl5M8//+Ts2bOMHz+e5cuXc+7cObp3786gQYNIS0vjiy++oFWrVvj5+fHNN988tJ2LNjY2eHt75/LmSUtL44UXXuC7775DoVDg5eVVbDOFEAJ7e/tcoXpVKhXe3t64uLjk++JWKBS4ubnh5eVV4Gxux44dTJ06lbt375bo+mxtbRk8eHAec1zVqlX58ssvWbNmjTk1oVWpWymISj9iN5lMnD17lvr165e7a96D3L17l+Tk5AI9MyorXj4+DPjwdTTPRxO9/wT6pFTs/bzx69oGW0+3PAohKSmJlStXMmPGDH766Se6detGw4YN2bhxI+np6XTv3p2uXbuycOFCpk+fzueff86tW7fKZSYVHh7O+vXrGTlyZL7RFIOCgvj+++9zHXN2duajjz7KYzJ5mPTs2RM/P78Sx50RQuDt7Z3neLVq1di9ezevvfYakyZNIiAgoFDFnp6ebg5D7OLiglqtRqvVolKpzHsKrDy+PBIj9kuXLpGamlrh/d68eZPz589bLBaNlJKTJ09y4sSJErutlSQ0QPa03zHQnxrjBlJn+jgcu7QgIiUx3/r379/H3t6e+Ph43NzcCAkJ4d133yUgIIBGjRqxcuVKbt++TZ8+fTh48CBdunThwIED5RKm4ObNm3z//fcFhhzIvracSk2lUtG5c+eHEg6gIPz8/OjZs2e+g5HShHkIDAykSpUqfPTRR8yZM6fI0forr7xCzZo1mTJlCgkJCYwYMYKaNWvSqVOnXN5jVh5PKr1iF0IwdOjQfEcx5U3Hjh0ZNmxYqbIJ5YeUkkWLFrFw4cISe0fExsby+++/U1jAtPzIVoLnzp1jz549+ZpQbty4QbVq1cwZgnbv3k2fPn04cuQIq1evZtiwYWzevJkGDRpw69Yt6tWrV+JYL8WlXbt2bN26ldatW5dL+5WBXbt2MWnSJKKjo4tdp1q1akRGRpKWlkZQUFCR5d98802mTp2KWq0mOjqaQ4cOsX37djIyMjhz5kxZxLfyCFDpTTFCiAKz1pQ3+dlptVotycnJeHt752uekVKSkpKC0WjEw8Mj18hKCME777wDUOKQqdneIKVxlwNo1aoVDRs2zPclle1lotVqsbGxQafT4ePtxe2b18gwZI4qTSYTQgiklCiVynKLqGlnZ/dQ3CcrEoPBgFarLdGI/aeffmLw4MEkJSXl+xn+8MMPnD9/3vz/+PHj8fX15cqVK0Dm81a3bt08z/Rnn33GtWvXKjxUsZXypdIr9vzQarVcu3aNGjVqlClrz4NIKdHr9ahUqgIV78aNG1mwYAGrVq0qMMbK66+/Tnx8PMuXL8/1JRRCULduXYxGI3q9vtCs9w/i6+trjsddGtzc3Aq8V8HBwezfv5+OHTty7tw5evbsySfz32ZS75oofFtw8uRJOnToQFRUFP7+/ty+fTvf9HIlJTuxdEnuQ0FcvnyZHTt2MG7cOItkVQIICwsjLCyMZs2aWdRnvH///vTt27dYL/eMjAwWLFiAj48P69ato127djRv3jxPuYkTJ+Z6URiNRv78809MJpN5UPD++++bE3pkM3PmTJKSklizZo1lLs5KpaDSm2LyIyUlhcOHDxMWFmbRdu/fv8/w4cPZvn17gWUaNWrEmDFjCvXf7tWrFwMHDixwwfXrr79m0qRJJCQkcO/evWLFABdCoFAoysUTombNmqSkpFCrVi1zyNhnn3mGpIRYtm/dRL06wfTs2ZN169bRpUsXDh06RIcOHcosy5o1axg9enSJzUv5ceTIEebNm2dRE9GNGzc4cOBAgRvUSkt2JMn87p/JZCI0NNScN1Wv1/PZZ5+xf/9+5syZwxNPPMGIESPy1FMqlahUKvPP77//zv379/H390dKycKFC4mNjeWZZ56hf//+ueo9So4BVorHIzli9/LyYvTo0SU20eh0OkJDQ6latWq+roZ2dnYEBQUVOgto2LAhDRs2LPC8EIJhw4YVKocQAoPBQGRkJPv27WPgwIEWGQGXFk9PT/r378+6dev417/+xfLly5n89ER+OxDGnXvhdO/Vj4ULFtC5c2dzTJ4GDRqUuV8PDw8CAwMtsoYxfPhwWrVqZdFIla1btyYkJKTCvEji4uJ46623sLGx4c0338Te3h57e3u2bt3KRx99xMaNG4mPj0en0zF//vxC2xo7dixjx441/9+wYUOmTZtW3pdgpZLwSI7YlUolXl5euXyPC0Ov13PixAk2bdrEsGHDOHToUL7l/Pz8+Oqrr3jiiScwmUwl3gJuNBrR6XRF2k6joqKIjIzE19eX/v375wlUdubMGRYvXlxhnkBKpdIc63zHjh1MmzaN8xcuYVTYU8PfmYN7djBs2BCklBw+fJgXXnjBIqaJPn368Pnnn1sknr6HhwdNmza1qEuss7Mzfn5+5ZbX9kEyMjK4e/cu9evXNw9alEolrVq1Yu3atRw+fJh58+bRp0+fCpHHyqPLIzliL4hsF7IH3eH0ej0XLlzA09OTF198scARd846UVFRZu+Mxo0bF8seevnyZU6ePMnw4cMLHfUPHjyYRo0a4e7unm8Ex+PHj7N8+XJGjBhRYQvHDg4OTJw4kffff59z586xadMmGjVpgSbqPNdv3OTs0T9JzrBn7ty5pfIXz++zsW6wyU1AQADr16/HxsYmj3lECIGjoyMTJkx4SNJZeZR4JEfsBXH06FHGjx+fx87q4ODA6NGj6d+/P5MnTy7W4pqjoyN2dnacOXOm0MiSOfHw8KBGjRpFziRat27NmDFjCiw3YcIENm/ebLFFwOKgVqtxc3Pjiy++wMXFBVdXV44dO8b+U7cIqenL9SsXmDzpKapUqVIqhRwaGsr48ePZt2+fxWU3Go1cuHCBiIgIi7ddkWTvgrXavK2UlUqv2E0mEwcOHCiWWaKgeBxCCJydnYttuoFML5IhQ4YwYMCAYtuAAwMD6datW5lDBTg6OuLv71+hX/CLFy+yZcsW0tLS2LFjB+3atcs0QSjtqFXdj5iIu1w7d8QcYbA0lNfib2pqKs899xxff/21xdu2YuVR5JEwxUREROSyOxZE27ZtWbFihcWUh6ura6YSkxKDRotRl4HCxgalvR1CWXollZ39J9uDobjs27ePhIQEBg8ebHGlX69ePTw8PMw7Y5OTkxk5ciTnzp3j4PUE7kUms3njbzRv140qQcGFtpWcnMytW7do0KCB+SUXFBTE8uXLy0WxOzk58e677xZr405lJ/vZsLW1LfFeBytWsqn0T072ztOc7oUFbcm2tEuglJKMpBSufbGcPzqOY0u9vmxrOpjzb39G+t2wUo9c4+LiGDlyZKEJOvJj7dq1fP/998U2DT1IWload+7cybe+u7s7derU4dKlS8THx+Po6Mi5c+e4ePEiKWlq1HoV9+/cJOLGcQwGfaHXHhUVxbFjx0hOTjYfK093TRsbG3r16mXR2DUGg4G7d+9WeCiL9PR0RowYwa1btyq0XyuPF5V+xJ5fTsvw8HDmzp3LlClTaNu2bbn1rU9O5fSLH3J75Wb26+NJwkBIrCPpH4UTe/Ak7X+aj1ONqiVWVra2ttStW7fAxCEF8dZbb5GRkVEik1JOrl+/zrFjxxg7dmyB4WZnzJhB//79uXjxIiqVimnTpuHh4YFCF49L9BacbO4QExlOlaAaBfZTs2ZNnnjiCbOHUGVbJM0eFScmJqLT6XB0dMTT0zPX7CktLY3t27fTunVrWrVqVWGyKRQKateuXerPOJsbN26Y9wc0aNCApKQkIiMjzXH2rTzeFKnYhRBBwDLAj8z8PEuklIuFEJ7Ar0AN4C4wWkqZKDK/xYuB/oAamCSlPG1JoXU6HZGRkeU+mor64zD3Vm0hQa8hFSNdceMAKVQz2RF78DS3fviNxm//G6EqmVnEzc0t3wTbRVFYDlSj0UhycnKhawn16tUzh6PNj+zIgikpKRw7doxOnTqZ47PrtGqEczgi8RL3Ik6j96+CrW3+SaRVKhUffvghCoWCX375pUjFnpaWxtmzZ2nQoEGxE3dIKUlNTUWpVBYr0UV2nfT0dPbs2cO2bdtISUnB1tYWrVZLUFAQw4cPp0WLFtja2uLs7MyAAQOKndLQUjg6OrJ48eIyt/Pll18SFRXF3r17mTdvHgsXLiQhIQGlUmnewWrl8aU4I3YD8LKU8rQQwgU4JYT4A5gE7JZSfiSEeA14DXgV6AfUyfppC3yd9dtiBAcHs27dunL1L5ZScnfVFkwZepxRYkJylFSi0WNEgsnEvdVbafjacyhUZY+rXhr0ej03b97Ez8+PmJgYnn76aV577TWGDBmSb3knJ6diK8HU1FTu3buHl5cXOp2Otb+tp4a3gg5e9nhorxET2Yyq1YILXKx+5plnip1cIj09ncuXL+Pr61tsxa7X63n22WcJDAxk4cKFRfYjpSQ2NpZ58+ZhNBoZOXIkrq6uqNVqXFxcuHv3Ll999RVNmjRh5syZODg4PFLxUwwGQy7z2Pz58zEajTRp0oSUlBTCw8O5fPky/fv35/79+2bFbjAYMBgM5jAXViqO0ppUi0ORmlFKGQlEZv2dKoS4AlQFhgBds4r9DOwlU7EPAZbJzKfsqBDCXQgRkNWORRBClHmqWhTSaCIjOXNGYIugO+7Eo0ePRJWVLVSfko5JrwcejmJXq9Xs27ePFi1aUKNGDfr27UutWrUs0na9evUYNmwYq1atQghBrVq18PPxRqDELeYMSVFn0PlVzXejkhCi0CTiD+Lj48OTTz6Zx+RWEEajkejoaFq3bk2NGjWKVSctLY3333+fwMBAGjVqxG+//UZGRgZubm7ExsYSEBDAM888w6pVq1iyZAkzZsywWFTPimDZsmW5goCNGDGC9evXo9Pp8PPzM5s0H1yQ/frrr7l8+TLnzp3j5s2bZZbj5s2bVKlSxSIbxSIiIrCzs7NI+sULFy7QuHHjMrcDmWHEGzRoUObF7dTUVIKDC3dEKC0lGvIKIWoAzYFjgF8OZR1FpqkGMpV+aI5qYVnHSqXYpZSEhobi7+9f7so8J0KpwKlaAAhAwknSSMZAU5ywyVLsjoH+KOzKLpNarWb+/Pm0adOGAQMGFLues7Mzw4cPx9nZGUdHR95+++0S9avX61Gr1Tg7O+fxstHr9ebRnEqlMucPlal2KBIu46a9RkJMUwKCapfZhq5QKIo9k4DMnKPbt2+nffv2PPHEE0WWl1KyZcsWHB0dadSoEcuXL+eZZ57B39/fHIztwoULLF26lOnTp/P1119z4cIFmjdvXuHrAxqNhnfeeYeZM2eWaMYwefLkXP+///77fPHFFyxcuJCGDRtib2/P8OHDiYyMzLV57t///jdxcXEsXryY9957r8zyf/zxxwwdOtQiA4zffvsNHx8funTpUua2XnjhBT755BOLfJ5z5szhvffeK7Nb8/3791m5cmWZ5cmPYr9yhBDOwDpgtpQyJee5rNF5iVxEhBBThRAnhRAnCwsCZTQaGT9+PBcuXChJ82VGCEHwxGGoHB0RCLrgymA8qY4dAoGwURE8aRhKCyj2jIwMTp8+XeIRk1KpxNfXt9Sjoxs3brBq1SoSEhJyHffy8qJ27dpcunSJSZMm5R6ZOFVBeDXCQ5WMOuJcnhAKUko0Gg0ZGRmlkqk4ODg40LNnT0JCQopVXq/X88cff9CrVy9WrVrFnDlzuH37Nu+++y6fffYZ7777Lh4eHvTp04cNGzbQrVs3tm3bVm7yF4bBYOD06dPmIGClpX379nz66afY2Njg7u7O2rVrGTNmDF9//TW9e/fOVTY/B4XSYkk3zfx24JYWS6ShzCY7h21ZUSgUFrvvecjpOljQD2AD7AReynHsGhCQ9XcAcC3r72+BcfmVK+inZcuWsiAMBoP84osvZFRUVIFlyguDRisvzvta/urUVK6grvlnpU2IPDzx/6QuIUmaTKYy92MymWRaWprU6XRSr9fLW7duyeTk5DK3mf1TEPHx8fLYsWNSrVaXrN2U+9J47C0Zt+99GXb3Rq4+UlJS5LBhw+TChQvLJH9ONBqN/OOPP2RoaGip6oeHh8uxY8fKbdu2yenTp8tjx47Jf/3rX3L9+vXy9ddflxs2bJBPPvmkvHr1qhw3bpzcs2ePfOaZZ6TRaJRS/n0vjSaj1BsNxbq3pcVkMsnU1FRpMBgs3nZB/RmNRqlWq0t9PTnvh0ajkQZD2e5Rdj2dTiczMjLK3I7JZJLp6ekWkSm7LaPRWOK2crZhMpmkwWAw3/fSyAaclAXo1OJ4xQhgKXBFSpnTlWMTMBH4KOv3xhzHnxdCrCZz0TRZlsG+rlQqmTlzZmmrlwmlvR31X3war3bNuP3TetLvRmDr7kKNJwcR0LsjNm4uFnlzCyHMpoikpCR27txJq1atypRF6Ntvv+Xu3bvMnTu3QBOWp6cnbdq0KbGs0ikAPBvjGn2ChIjTZPgHmUceKpWKxo0bW9R2GB0dzUsvvcS0adOYMWNGiesnJCTg4OBASkoKPj4+3L17l5CQEPbt3cuVq1dxcHAgKSmJsLAwbG1tsbOzIz093ZxcJF6bxN7Q4/xx/zBqvZaqzn4MDO5CK7/G2Kssax7M3iVdUWzZsoU333wTIQQLFy6kZ8+eJW4jO/qko6MjISEhnD9/Hnd3d6Kioti+fXuJcya8+uqr7N69m1mzZvHNN9/g6upK165dee2110rUTkREBEOHDiUwMJBbt25ha2tLlSpVqFatGl988UWx29FoNLzxxhtcvHiR9PR0UlNTqVatGrGxsXz++efF/g5Nnz6d8+fPs23bNp599lmMRiNhYWE8//zzLFy4EMgMJ/LKK6+U6DrzozhzpieACUB3IcTZrJ/+ZCr0XkKIG0DPrP8BtgG3gZvAd0DJv4mVCKW9Hf7d2tH+p/n02P0znTd8RfXR/bF1dy0X+6uLiwuDBg3Czs6O999/v9TxT1JTU0lOTi6XvKQIJcKvLUpbJ7wM14mJuG/ux8HBgXfffbfI0MUlISAggO+++46RI0eWuK5er+f69eskJibi6upKfHw8QUFBXLx8iZC6Kly9dCSp1EQlx5EuM1DrNKSo07C3t0ehUBCvTeKj49+x+Mwyzsde48yJU/y24lfeOvw5K65uRme0rMnJZDIRFRVVYR4qCxYsoEOHDjRv3tysXEpK48aNeffdd3n22Wf56quvOHLkCH369OHy5cslzrR15coVVq1axZkzZ/j444+xtbWlWrVqpfoefPfdd1y8eJEJEybQs2dPUlJSaNWqFXfu3ClRO1FRUfz4449cv36dK1eucOnSJdq1a0dMTAxpaWnFbqdLly7me3L//n169erFlStXiI2NJS0tjdmzZ7NixQrCw8NLeql5KI5XzEGgIA2Wx/Uha4pgsSG2zMr+olKpHupGFyEEKBUYjUbi4uK4ceMGarUaHx8f6tati6OjY7Hd+wpDqVQSGBjItWvX2LRpE/379y9VNMWXXnoJKHkKvuIghCBNuHM73pMa9qFoI0+hCwiyaJahnNja2pZ6I5perycxMRG9Xo+dnR2JiYk4OzvTtElDlGlnaOJrQ1L0CVJDBFNXvQ9xKYRv+gaTUcPiY2uJzojkSORZJBKjxkDyxWikSaI16lhxZTMtfUNo5ps3Nn32i07qDRgz9ChslChUNqAo/BlJSUmhU6dObN682aI7aQujZcuWpKWlERlZuol19erVkVLyyiuv0K5dO6pVq8bgwYNZu3ZtidqRUvLLL79Qr149IiMjOX/+PDt37uS3334rlVznz59HSsmPP/7Ijh07+OKLL2jQoEGJk3m7uLjQoEEDTp48icFgwM/Pj+nTp7N06dIStdOsWTPz361bt2bUqFFs2LAByNz5PWjQIF588UWL7M+p9CEFjEYjTz75pDl348NCSsn169d54403mDVrFhs3buTgwYO88sorjBw5kqVLl1p0w1Tnzp3Zvn07TZo0KVX97Mw45fUyjI6O4eANPck6W7wMN4iNvGeR2UFqaiqHDh0q0UioMBwcHBg3bhwjR47kr7/+YsyYMcyfP5/OnbsRJ+rx2bLD9G8axCsNquF/LQbfxoGcPXiCay4pzNv/M3+FHkUikUYTSWcjcK3ng9JOhZSZyn3n3UP5XrchXcOdXzbyV++n2dKgH9uaDuHC3M9Ju1N4KApbW1sGDRpUoeaYkydPcvbs2VLXv3fvHqNGjcLDw4M1a9Zw9uxZtm3bxtWrV0vcltFoxN/fH4VCQdOmTZk3b16p5WratCl9+vRh8ODBGAwGFi5cyMmTJ0lJSSm6cg4SExM5e/Ysb775JoGBgcTExPDVV1+VWi6AEydOsH79erNTSFJSEhs3bqRmzZoWCdVd6RW7EAIPD48KdXV8ECklBw8e5O2336Zhw4bMmDGDRo0a4e3tTePGjRk5ciShoaG88cYbBaZ50+l0JCUlFTtxh42NDV5eXnk2YWWnTktMTCy27NHR0URHR5da8e7YsYNXX3011xciKCiIUWPG41ezCa7KVDKiz6LRaJBSYjKZ+Pzzz/nyyy9L3OfJkyeZOnUqZ86cKZWsD5Idx3z48OGkpKQQGxvLiBEjuHrlKrv/PIKDsyfLt90kPcHIR5M60ipOy1OtOvJe18lMq9YLO2Xm/TdlGFGHJZNwKpyUK7HoYtIBiNMmYnrgGg1qDRfe/Zzj095i1769rAi7yLFrl7j4/jccmfh/pN0OLfC+ODo6smjRogpL6P3qq69y9OhRzp07V2rb7sWLF9Hr9Xh7e/PBBx/g4uLCtm3bqFGjRom8WoQQzJ8/n48//pjWrVvz8ssvYzAYzFnPSsqzzz5LZGQk27dvp2nTpri7u7Nv374SbzwLDAxkxowZrF+/Hk9PTxo3bsyxY8fw8/Mr0Qt469at1K5dmzfffBMbGxt27NhBUFAQvr6+uLq68sUXX/DUU0+V6lofRJSLDbaEtGrVSp48eTLfcznleximGCkld+7c4bXXXuNf//oXV65c4fz587Rq1Qpvb28uXbrE/fv3GT9+PKdPn0aj0fDmm2/mca86fvw4Z86cYfz48WV6IyclJTFw4EB69uzJO++8U2R5k8nEhAkTEEKwbNmyXKYZk8mEXq/n4MGDREREMG7cOFQqFdJkwqjWoldrEArBz6tWsXnHNn76+We8vb1z3RvUkRgufsvP267gVG8IY8eNR0rJ7NmzUSgULFq0CIVCQWJiIsuXL6dv376Fpq9LTk7m+PHjtGnTxuKJyiMjI3n//fepX78+dnZ2HD58GK1WS1paGk+O7MWB3VsI9FEyc0I3jK7NSFRV55VzXxKtiTc/h/oUHfFH7+Pfuw5CCAbW7Mrrbaaa+xFCELX7CPsGTyNNnc5OkuiBG3tJoSduOChU1J89iWYfvozC9uFvgHrw+1+a71hROqSkbRbUnqXaeVhtFVfXFrc9IcQpKWW+gYweiSBgDxODwcBPP/1E//79uXHjBnFxccydO5eTJ08SFRVFv379cHBw4JNPPmHatGksXbqUs2fP0r59+1ztVK9eHRsbmzLboR0dHZk2bRp169bN9/yDL0IhBOPHj8/X/n/z5k0OHz7M/v37iYiIyEySbDAStuFPbn23hoTTl0ChoE6nlnw+7SU83dxz1RdCIB18MXk0YcveVbhcy2DosOHY29uzYMECcxnI9Gz54Ycf8PPzIzY2FgcHB5o1a5ZHJjc3N3r16lWme5QfQggCAgKYP38+Fy9e5N133yU1NZXU1FTs7OzYf+wqTz8/Fz+HOGwU13DVn8FVFU9v/9qsuJOAKUtMG1c7/HrUQgB2woZW8e7c+GolJr0B1/o18e3UmrurtmBUa1FjwgEFdihQARlIHEySe2u20/A/07Dzcs8jZ7bPffv27QsM1Gbp+1IZ2iiP9iwpV2W8T4VR6RX7wyY9PZ3r16/TvXt3du/ezdy5c/n4449xdXXFz8+PpUuX0qNHD8aNG8f69evp1asXf/31Vx7F7ufnV+Jojvlha2vLU089VeD5/fv38/333/Phhx8SGBjIiRMnWLVqFXPnzs3zYLm4uFC1alXmzp2LSqXCzs6OBdNmc3DVekanO3GQZBIxUHNTBG0On0X5zTsEDeudux2hxKZqe755cwSaDIiLvEdgzXp5Nl7Url2bzZs34+rqyoQJE/Dy8irx4lNZEUIQFhbG2rVradiwISkpKSxfvpz//ve/nDp1Chtbe6o26EtidC3UicdwN91jiIORy85OnElLx0RWaj+VEge1pMP6MJJPL2ZDdBQakxEfDw8atG2FNiZzw5c9CrSY0CMxwt+hKJJTMRawgUutVvPmm2+yYsWKClHsVh5PKr2N3Wg08s477xAaGlp04XIgNDQUR0dHwsLCqFOnDhcvXsTJyYmAgAAOHjzIyJEjzbay6OhoatSowb1790qUBNuSGAwGdDqduf/sBNv5yRMQEECvXr0IDAzE39+f9NuhBP51AZt0LQJohytdcee+1KKOjefqJz+hi829S1UIgXD0x7d2ewLdTegiT5GakkJUVFSuIEcqlYrAwEBcXFyYP38+b7zxRq52tm/fzoIFC8q847IoUlNT2bdvH5GRkaSkpNCiRQs2bNhAaGhoZlwchQKfwBDsqw8lRtESV+HEf4KqMDXAn9qOLlRx9KaVdwgjj9hTf0cE+sh49pkS0WBEm5hM5I4DJJ7NXOh3RIEPNmwnkQBscMj6utn7e6O0z3/HobOzM0uWLHkskoZYeXhUesWevXAZHx//UPpXq9XY29ubY6rExcURFBTEhQsXSExMJDk5GVtbW3Q6nXlrdkZGBiaTCaPRWD5+5Dm4ceMGy5cvJz09czGve/furFq1yqwY2rVrx+rVq6lVqxZSSnMMmAeRUhKz9zjGe1Fm31Y7BHfQ4osNCiDhxEWSr9zCaDQ+kCJPIHxbobRzxdt0i5W/LKVXr15s2LAhXxtu/fr1qVWrVq6R/7lz5/jrr7/KNRQBQHx8PLdu3SI1NZX+/fvj5eXFqFGj0Gg0/P7774SFhWVuEnL1wK9OD9I9BqCgBmO9vVlatzbL2wzhvaCRBB6IRBizXBqBGPRkxtXIiq6hEAgE7XFhOF60wBkFAqFUUmP8IGxc8o+No1QqadWqVYV6xVh5/Kj0il2pVPLbb789tOQAAQEBJCcnU7VqVe7evUvr1q05ePAgQ4cOZezYsRgMBtzc3MxJiOPj4/H29ubcuXOsW7cOnU5XrvLt2bOHhQsXEhcXB2Qqzpxujtn/nzt3ji1btjBlyhSz/ftB9GlqpPHvkf1VNMSjpwXOCMCky8Co0bJ+/Xqeeuopjh8/jlqtzuzL0R+8muCkSKOupwZHRwd+//33Yr/YZs2axa+//moRV6/CqFWrFlOnTqVhw4Zcv36devXqkZycTN++fZk4cSLu7u5A5n1TqVT4Vq2Lc63hxKnaoclQYZt4HO25laTeuGducxCeNMGRY6SixQQmiXOtaqicM+MMKTKjCyFUSqoM6EydaWMR1oTVVsqRSm9jF0KYv2wPAx8fH5ycnLCzs0OtVhMVFcXYsWNJSkri2LFjdOvWjSlTprBp0yZatmzJoUOHaN68OY6Ojri5uZV73soxY8bQrVu3Il2kFi9ezJ9//smwYcMKtPU7Bvpz2slAVHoGh0jhDjrsEZwgjXa44ODljp23B542elxdXdm9ezfe3t5Zo28F+LZCGX+O5oEGFi94n6BaDYu9YOTg4FBgoKZffvmF69ev8+abb5Y5aFLdunWZP38+ycnJrF27ltjYWHx8fBg9enS+XjhCCJyc3bCr1Ymk2GrExh3BaDiLEJkjdSOSNIxoMKEEBAKEoMa4gfh0bMntn9aTeuMeKmdHqo8dQNCQntj5ehZ4X4xGI3fu3KFq1aoWDVxl5Z9FpVfsUkpSUlJwcnIq18QaBWFnZ8fAgQPZsmULTz31FF999RUzZ85k9+7d/Pbbb4waNYodO3aYt6qvXLmSiRMnEhwcTP369ct9JdzNza1YboEvvPACY8aMoUePHvneRyEE/j3a0z+kBe1OXEAi6ZTzPAK/bu1wC6lNd4dGtGnThvDwcAICAv4u5OAL3k1xjTiALzG4u3ewwBVCZGQkd+/etei6xd69e/H39+eZZ54hNja2yH0SKpUNXv61ULv6EZ3shWOdU6RfzdypmYaRdEy0xxV7FNh6uuPbtQ1+Xdvi37MD0mg0j9CLeh7S09MZM2YMK1asqLCdp1YePyq9KSY7282lS5ceSv8KhYJ+/frh4eHB7t27efXVV4mJieH06dPUrFmTlStX0qxZMwYNGsSmTZuYPXs2gYGBFgkvkJOEhAQ2bNiQJ8RucWnevDl9+/bFxsYmX7kSExO5GxtF43kv4ly7OgqlKtuAgMLGBs/WjWny7r9ROmSGLHVxcaF+/fq5QgYLhRLh2xZh44KH4RbxkXfN57I3LpVmzeGll15i6dKlRbqKarVarl69al5vKAgpJTExMQQHB3Pjxg3++OMP1Gp1kXJkbnZypnq73tSe+i8UtjYoEdTDkRY4440NCEFA7w74dGhhfgYUWeEwivM82Nvb8+9//7vMKfnUajWffvop69evJz4+noULF7Jo0SLWrFlTpnatPBpUesUuhKB9+/YVnnsyJyqVihdffBEPDw8OHDjAgQMHCAkJoV69eoSHhxMTE8Pvv//O888/z+jRo8slxvLFixd54403cmXJsSTXr19nz549OLdsSLcd39P43X9TZWA3qg7tSctP/0OXjV/h2qBW0crJ3gt8W+KiUqOPPoNGowEyvYvGjx/P3r17SyybSqXC1ta2yL4TEhL466+/igyiJITA09PTnMAlNja22EGmhBAoVSrqTR1H049exrVRHVAqQICjvyO1J3ai+YI5pd58ZGtry6RJkwrNb1scMjIy+Pnnn/nhhx+IiYlh7ty5dO7c2ZwwxcrjTaXfeVqZ0Ov1nDp1irfeeovU1FRCQ0Np3rw5AQEBvPvuu/j7+5dolC6l5MKFC2g0Glq3bl2oPT7bn75u3bolyjYkpTSP8j09C7btqtVqc1hbpVKZObLOejZECdcJpCYWefk7UtV6Ev1HUK1WCOHh4bz22mtMnTrVIhlxAO7cucOSJUt49tlnCQ4ORq/XExcXh6enZ6EvVyklcXFxrFq1ivT0dPPegAfXHu7fv8/Nmzfp0KFDvrMFaTKRdjec+ItXSQw9R4B/LN71PFB4NkZ4twcbj4e6wW7BggXs27ePBQsW0LRpUzp16kSLFi1yLZ7fv38fjUaDSqWyWFILK8XHxcWl1Kn/Humdp5WNbdu20bNnTw4fPsyVK1fo0aMHx44d4/bt2/j7+5e4vaioKNLS0mjVKt/Px4yTkxPNmzcvcftSSl588UUAfvrppwIVjaOjY26zishcBCwV9t7g0xyn0D3ERZ9CW7UmgYGB/PLLLxZVdLGxsRw4cIAhQ4YQHByMjY1Nbpt/AQgh8Pb25vnnn8917EESEhK4f/8+rVu3zj+3q0KBS3AQzjUD8dd1JCH8PKlpJ3BNOgvq++DdEVzrgyheZFK9Xo/JZCrW7KQk+Pj48MEHH3Dy5EmOHTuW69yxY8e4desWN27cKFUsdiulJz4+ntTUVF5//XWLt13pFbvJZGLPnj20bt0aV1fXhyrLvXv32LlzJ56enrRo0QIbGxuuXLlCREQEy5Yto23btiVe4O3WrRtSyjyjdUvFyBFCMHTo0DK3U+J+vVugiD2Lj/oOMWG3qFYrBKHIHBFKKUsVX+PBOi1btmTbtm0lmsHkbKsoGRo3bkyDBg2KXFjN3L9gj3/N1iQnBBITdQR3zU3sorYi028jvJ9A2nrlew05WbhwIVeuXGHJkiXY2dmV6fPSaDScOXOG0NBQli5dyvXr13FwcMjT5qhRo0hKSmLVqlWMGzeu1P1ZKTnlmfP0kVDsb775Jp9//nmRo9ry5tixY1y7do2ePXsipSQ+Pp5GjRpx9OhRDh8+TFRUVImi8gkhsLHJ3xZ7/vx5vvzyS1599dUyJQYWQjB8+PBS1y8IvV5PcnIy7u7ueV5mmTFkfDL92jP2o0zaBlf2g60LeLcAtzqgLF7MnMTERA4dOkSbNm3ymEqUSmW5vuyzQx8Xh+wXhbtXFXTO/UmMuIx92klcki+h0ISDV3uEa4NCrzswMBC1Ws0ff/xBx44dyxRSQKVS8corr5gTXfTo0aPCszNZeXhUesWuUCj43//+R7169R62KPTs2ZMVK1aQlpZGREQE3t7e2Nra8t577+Hm5maRWDDZqNVqIiIizBucTCYTOp0OOzu7cveNLw73799n586dDB48OM/LTEoJRh3CmI5UKrh0+Sp7T9+nmr8bw7tfxyagHdsvGAmNiOHpp58u8OUGmSESUlNTKyyjUFkRQmBv74h/zZaZo/fIo3hor2MXtQOZfjvTPGPnAwiQejDqABMobHnqqScxGIxs3LixzK6dNjY2pTLdWXk8eCQUe6dOnYouWAH4+fkxYMAA1q5dS0xMDE888QQ9e/akYcOGFu+rbdu2rF+/3qz0wsPD2blzJ3369ClWHJFs10KFQlGmKX1GRgY3b96katWqufzl/fz86NixY8HeSomXIPECAggO9KB+DS++/u00kTFJVFMd58Sf1zhxS8OECRMKVew+Pj6MGTOmyJeZlJIDBw6gVCrp0KHDQ48KKoTAzdMPR5d+JETUQJV8FI+Uq6AJB892CDsvZPI5TKk3kdIINp4oPZqhcm/OsGHDKsXL28qjS6VX7JURk8lEYGAgjRo1KlXauuKgUChy2XZdXFyoXbt2sbfcf/LJJ9y+fZtFixaVyf0yO2hWhw4daNq0qfm4s7NzIdmdJMSdBmnMdC10tSc2UY1Wb8TDzQGkkdkTOmOoOb5I3/TskAhFYTKZ+OKLL7C1taV9+/YPXbFDpuy2tnb4VmtCWkog0RFHcdNeJfHSBrw9XRDo2bj7MrdDE7kdmsCHL/fHs3oSCp8elUJ+K48uVsVeShwcHHBycrKYi5hGoyE2NpaAgIB8R7Du7u507dq12O3Z2Nhw+/ZtwsPDCQ4OLrVc7u7ujBgxAmdnZ1JSUtBoNCgUClxcXApe4JMm0GemCZRSkqbRs3rXZfo/UQtnh8xrc7YzIdzd8tTPznsZFxfHCy+8UOzFaIVCwfz588s8QykIk8lEWloadnZ2JX5RKhQKXNy8sHfsRUp0IG5yJ7YqPUIoGdW3MTfuxrFx9xXcXVSQchFcQsDRGt3RSukp8lsjhAgClgF+ZIbHWCKlXCyEeAd4FsjOBfcfKeW2rDqvA1MAI/CClHJnaQU0Go0sWbKE4cOHW9SGXVZq1qxpzsRjCbZv387cuXNZsWKFRUw7EydOxM3NzbxBqDhkR6TMmThcCEFqairLli3j7NmzCCEwGo24ubnRt29funfvjr29PQqF4u+XnFCAyhF08UgJ6/66yskrkTjYqajm74qvhxNC5ZRZLh+yPY1KssdCCEHNmjWLXb6kqNVqfv31Vxo1apQn1n5xyB69e/kGITVAlgldSsm+E3fp2KpGpvnFpIXY3ciqIxEq60KnldJRnOGQAXhZSnlaCOECnBJC/JF17hMp5cKchYUQIcBYoCFQBfhTCFFXSmksjYBSSpYvX56vV8TDIjg4mL/++ovLly/TvXt3GjTIm6W+pDRr1oypU6cWyw+7OLi6uppT3RWX+/fvs2/fPvr27Yuvry9SSjZs2MDq1avp1q0bs2bNIiMjA5VKhVqtZtOmTWzevJlmzZrRrl27HF5LAryaQXo4QhgZ0yuE4d3qoRACBzsVoMg8XwDvvPMOJpMpX9mL4wZaHukU7ezsaNGiRbFMbxkZGRw8eJCaNWvmfdlII0IazXsE0tQZRMakMKxXyN9ltBFg1EKWYpdSsn79emrVqsWJEycICgqib9++FrkuK48nRX7rpZSRQGTW36lCiCtAYaEEhwCrpZQ64I4Q4ibQBjhSGgGVSiUrV64s1eaf8qJ169a0bt3aom0GBwczY8aMUtVNT0/nzp071KpVyxwRMHOEWLIE4I6Ojvj7+2Nvb4+Ukm3btvHzzz/z9NNPc/PmTT777DOcnZ3RarXY2dnRr18/wsLC+PXXX/PeD8/GkHoHkXgJB7tshQ6gAM8m4J7/yzA7pn1BhIaG8vbbb/Pcc8/Rrl27fMtkZGTw5ptvUqdOHaZOnZpvmZJiY2NDy5Yti1U2KSmJ//u//2PEiBF5N58o7UDlCoZkADRaPcFBnri7ZK81KMGzPdi456q2fft2AP744w86dOhgVexWCqVES+9CiBpAcyB7+9rzQojzQogfhBDZTrdVgZzpjsIo/EVQVJ9Ur169XOKvlBQpJWq1utK53h06dIixY8dy7ty5MrXj6+tLnz59cHNzIy4ujhUrVtC4cWO+/fZbjEYjr776Kq+88gpvvfUW48eP5/fff8fHx4d+/fpx/Phxs4ueEAJh4wzVB0NQf3CsArbu4BQI1QZCtYEIG8dSjaYNBgNJSUkFZloymUzExcURExNTZDCwsnDw4EHmz59PWlpannOenp588803TJw4MW9FlTO41IesdCa+Xs48ObgZSmXmV9GocOLIZQ2pabmDkoWFhbF79258fX2tHjNWiqTYT4gQwhlYB8yWUqYAXwO1gGZkjug/LknHQoipQoiTQoiTsbGxRVfIQXYmoIpOP6fRaPj11185deqUxdq0xLU0a9aMt956y2K+/lJK/vzzT0JCQvDy8qJZs2YMHDiQRYsW8eabb/Laa69x+PBh+vTpw8qVK+nbt695g1YuVE7g1wEaTIdGs6H+c+DbFlSljzNes2ZN1q5dW2C8maioKEaOHEm7du2YNWtWvtem1+vNG3fyIyEhgZUrVxIdHV1gmbNnz7J169Z81zBUKhWtWrUqwGyjyByRO9UFkXPCLEDlhtGrBzfvxZgzSWVkZLBr1y7atWtHly5dmDdvXolnYlb+eRRLsQshbMhU6iuklOsBpJTRUkqjlNIEfEemuQUgHMi5pB+YdSwXUsolUspWUspWPj4+JRL6zp07jBgxgj179pSoXllRqVTUq1fPoi6O9+/fZ+TIkezatavUbfj6+jJ69GiLJT82GAycPHmS1q1bc/HiRYYOHcpXX31F586dadWqFSNGjODatWscOnSIqlWrcvXqVby9vYmOjs5j3xZCZIbzVdpm/i5jOOPszEYFteHi4sKwYcNo2bJlviNbtVrNlClT+Prrrwvs4/r168ybN6/QGdCUKVPYsGFDiQM4CSFA6QgBAyFgMLg2Buf64NUJgsZj61GfUaNGmT9LvV7P7t276dOnD7169aJr164PNfGMlUeD4njFCGApcEVKuSjH8YAs+zvAMOBi1t+bgJVCiEVkLp7WAY5bUmgbGxt8fX1zBa2qCGxtbS0e9jT7Woob7yQ5OZmkpCQCAwPLLRpfRkYGcXFxuLq6kpaWhoeHB8nJyTg4OLBjxw58fHzo1q0bUVFRBAUFERMTg5OTE6mpqeUiT0lwcXHh//7v/wo8r1Ao8PHxKTQ5SbNmzVi7di3Vq1cvsExhGZ+KIlO524NLA6RzfTKdzf5+4T3YbkJCAtevXycsLIyzZ8+We15YK48+xXGZeAKYAFwQQpzNOvYfYJwQohmZT+Vd4DkAKeUlIcQa4DKZHjUzS+sRA5k20zNnztCgQQOzIg8MDOS7777Lt7zRaEStVuPg4PBQMi6VlICAAJYsWVLs8kuXLmXVqlVs2bKl3LyEVCqVeZHU3t6e9PR0bGxsUKlUNGnShPr163Pt2jXatWtHWFgY7u7u3Llzp8JftIUhpSQ9PR0pJc7OzmalaW9vz8KFCwuta29vn6+nk8FgwGAwYGtrazE7d6ZcBc9ghBAcPHiQ33//HYBFixYxYMCAIttNSUnhtddeo379zBnA22+/jb29PYGBgYW++Kw8HhT5dEopD0ophZSyiZSyWdbPNinlBCll46zjg3OM3pFSfiClrCWlrCel3F5WIS9fvpxrNGie4uczHb9y5QoDBgxg3759Ze22QijsWvKjR48ezJw5s1yDX9na2tKmTRsuXrxIo0aNOHLkCE8//TQXL16kdu3aeHh4oFAoaNy4MadOnSIkJIS4uDj8/Pwq1Y7JKVOmMHz4cAwGg/lYSe93Ts6cOcOSJUuIj4+3pJiFolKpeO6553jxxRfNP4MGDSqynhCCa9eusWvXLpKSklizZg3e3t5s2bKlAqS28rCp9Mvr2WFnvb29i1Xe3d2d9u3bW8wfvKLR6/WcP3++QOXRtGlTJk2aVK6JjoUQdOnShaNHj9K6dWuOHj1KTEwMAwYM4JtvvuHUqVM888wzLFmyhJYtW3L27Fnq1auXr0uqRqMhOjq60MXK8qJZs2ZFJjApCe7u7gQFBVXo4qXJZOLIkSPs37+f/fv3s2/fPvPovTBcXFxyuUS+8MILNG/ePM+A4MSJE+zZs8ccbM7K40Glt1Vk59csLoGBgcyfPz/fc3q9nvj4eDw9PSuVZ4FGo2Hx4sW0bNmSunXrMmHCBKZNm8b06dMrVI74+HjOnz9Py5YtqV69Or1792br1q0899xzHD16lKtXrxIdHc327dtp1qyZWZmvWrWKjz76KN9QCJcvX+b48eOMHTvWYou7xUEIYfEEBnXq1KFOnToWbbMobG1t+d///md+MRqNRj7//PMSt7Nz506aNGmSZ6aSkZFhVeqPIZV+xG5Jzpw5Q//+/Tl06FCp6kspMRqNZXazNBgMZGRkmD1IdDodf/31F+fPn8fX15d3332Xfv36lamP0pCcnMzt27dRq9UIIRg3bhzVq1fnxx9/pFu3bly4cIHOnTvTsGFDbt++jbOzMytWrOA///lPgREna9WqRbdu3axxwAugqGdKo9HQvXt3mjVrRrNmzWjZsiUxMTFFtpuens7Bgwe5d+8eX3/9NdeuXWPp0qV5/P+feOIJ+vbtWyn2iVixHP+onKcRERGsWLGC0aNH5+vxoNFoOHHiBA0aNOD/2zv38Kiqq+H/1szkSkICMSFAwBDCXUggiNy+UkAuokgRKCD4UmxrXxC/Vktbo3x8WLH6tjxq9UWw1BuVolYsIGj7cpECYpE7JEjCXQiBhIQwISGZ237/mJMxkITMkNsw7N/znCdz9jlnn7UmZ9bsWXvttaoLwbx69Spr166lc+fOdcp1/frrr7Njxw6WLVtGREQESimsVishISE3zHaolEI5nYjZ3CC+bKfTid1uv2Zy0GazsXfvXrZu3crHH3+MUspTiefXv/41qamptGnTxq9867cSZWVlrF27lo4dO1a7slUpRX5+/jWGPzQ0tNaQR5fLRX5+fpV8O8HBwVVSLVdUUGrsX4i3OxUVlJ5++umbuv5GNU9vqxF7mzZt+NWvflVjGNu3337L7NmzPcu3r6ci0dW5c+dqXH16+PBhZs+ezbFjx2qUIzY2lvbt23uMp4gQFRVVo1F3lpWTu3EHO6bPZcPgqWweOZNjb31MWX6hT4myasNsNnsSelUQHBxMYmIie/fuZdq0aZw+fZqWLVvyve99j2PHjtG6dWu/M+o2m4358+fz3nvvNbUotWIymYiKiqoxokhEiIuLIz4+3rN5E8duMplo1arVNdfFx8fXnD9fE1D4vY+9MWnfvj2LFy+uMalXSEgI5eXl/Pa3vyU5ObnalZ5Wq5UTJ07ccDn75MmTmTx5slcG0VpUxKtPz+fyis9Iu2LGhovNXKbflh30Wj+CfkueIyQupsGMq8vlYv369ZSVlbF9+3aSk5O5evUq58+fZ/fu3Tz00EMkJCTU+f42m419+/aRkJBA27Y3nYHCI/Pp06f9KvyyJoKDgxk5cqTX5zudTj788EMefvjhBpRKc6tzW43YayMsLIwhQ4YQFxdX4zkDBgzgl7/8ZY1RN/369WPNmjX07Nmzxj6qC7fLzc1l9erVVRb5lB4+Qchf/oecK0UoFMcp4zhllDps5Kz9gqPLPkI5Gy61QkFBAcuXLycjI4MRI0bQtWtXxo0bR3l5Obt27eIf//hHvdzHZrNx6NAhzp49W+e+QkJCWLZsGXPnzq0HydwopTxbbVy8eJGjR496HQnkTfhlhS/e6XTeVPFuze2FNuw+kpSUxIwZM2qMIzeZTDdVl3T79u3MmzePU6dOedqUUpxZ8SnNrzoQhMs4OY+NZNwuG+V0cur9tThKSmvo9TucTie5ubk+J8YKDQ1l9OjRDB06lKysLEJCQsjKyqJFixaMGzeu3qJEwsPDmTJlik9zFzabjXPnzlVZiVmR2bI+F6iVlZWxevVqMjMzaz03MzOTf/3rX/UWbaKUYsWKFXTp0oXu3bvX25epJnDxe1eMy+Vi+/bt9O7d26ewx1uNkSNHVgmnUy4XpWfPe0aJ+dg5QRmXcOBE0Zpgys7n4ywrh6gbvzclJSWsWbPGkzvdWyIjI0lPT0cpxZdffsm2bduIiIhg0qRJ9ZpK2WQy+Rw5k5uby/r16xkzZgyJiYk+XauUAqXAh8VKJpPJqy/stLQ0unXrVmvZP1947bXXmDBhAsOGDbvhL0qNBm4Bww7uD3C3bt0C2rBHRUWRmpp6TZuYTKiWzfmKYo5ylW6EMZNWbMVKJ0IxIQRFRWL2IiY/PDyc4cOHe73Q63ry8/PZuHEjTz31FECjZ9asjri4OIYPH06rVq1QSvH5559jNpsZOXJkjcY67/wFzuw7RPD+Y5Tn5hPcIop240cQ1aMTpqDqC3scP34cl8vF2LFjvfoSiIiIaJDwzgMHDlBeXk7Pnj3rFJWlCXz83rCLCOPHj/e7vC92u52zZ88SGxvbYDHaIkLnqWMZ9uF6/s/VMoIRTAiDiMSEICah/Q/HYImofZLQYrHUyW1y5swZ7rzzzgZNZeArYWFhnglsp9PJ8uXLCQ4OZsSIEdUaYJfdwZG3/8apRe+QVXyRcoeDZFM4sUv+StcnZ9L1yR9hCgmucm1GRgZ2u53k5OQmiwAaO3Ysp06dori42Kdyh5rbE/+yltVwM5WAGoPi4mI+//xzBgwY0CCjp5KSEr799lvapfWg12NTOfrmh7jK3D7bIExgMhE7sDftZ46n8HIRLVq0aLBsj4AnLW+F39jlcjVoWgNfMZlMvPLKKzeciCzcm0n+q+9julRMS0wUIux0XWZYvpD54ptEdrqTdhNGVbnu3nvvRSnVpGGd2dnZHv++TturqQ2/N+z+SvPmzXnggQd8zsftLdu2bWPu3Lm8/fbb9H7+F0SndOXEO6u4cuIslmbh3DllDEkzxpN1KY9dH29iypQpDfqBb9euHR06dOAPf/gDzZo1Y8KECbRv377B7ucrInLD/EBKKU4uX035xSIEMAMHKaUDIQjgKC7h+Fsfk/DgcCT4u9QIIuIXq2bLysqYPn064F7Nq9HciIAx7BWhaHUt5OAtFoulQQ1bamoq6enpJCcnY4kIJ2nGQyROG4vLZsdksWAKCgKT0CG6GcHBwQ0esy0iTJo0yZMpsbq8MPWFtwWrXS4XIuLVhKZyuSg6mOWeMAXuIIhhRLGfEpy4w8OKMrJx2myYghtOt5vl3LlzzJ8/H3C7ZcaNG9fEEmn8mYAx7JmZmRw5coQxY8bcEgtTaiM+Pp5p06Z91yBgDg6uMlHasmXLRllNWPGF2ZBuMaUUjiulFO7JoOxCAZZmYbTo052w1nFVDLzD4fCsJ3j66adr/TIXEUyhbtnLcHGCMopxEoR4sqGbg4MRw51VUVfVX1IRz5kzx1N6MDk5uYml0fg7AWPYLRYLwcFVJ75uNTIzMyksLGTgwIFVfOYFBQXYbDbi4+NveT2vR7lc5BzIZOuzi+CrDMqKiikKho49e5Dy1KO0n3RflaiVyMhIrxfriMlEwthh5G35miCHIgIz4ZhpRRAWBEwm2owd6v4lBOzcuZPz58/z8MMPN+ivE2958803KSgoQClFjx49vMrJXpnS0lIefvhh4uLimDVrlo6qCXACxrB36dLFp2LOly9fJjs7m+7du/vVSr6CggIuXLiAy+WqYtgXLFjAyZMnWbVqVcBl4yvNyeOTGU/x90NfM5oWCPC57RLf31OG/f+eI7hlNK1HDfZ8oVksFhYuXAjU7K65nnYTRnH6o8+5uGMfd6prY8wjO91Jx0cnIma3W6dPnz6UlpY26IS0L0RGRrJgwQIKCwtZvXq1z9c7HA62b9/OJ598Qo8ePepfQI1fETCG3dcRbF5eHrt376Zt27ZeG/bCwkKsVivt2rWr9gN/vW9YKUVOTg4Wi8Xrn/QDBw5EKVVteOe4ceMoKCjwu9DPuqKU4syqfxLzTQ6dcEfatCGY7oRjAmyFlzm27ENaDbkbc5jbIN/ML5awNnEMePclMl98k5x1X1CefwlLRDjxIwfR/Vc/Ifquzp5+fS2w3lBUPFPJycmekngLFiy4qb66devGjBkzmDRpEi+++CJms5k1a9Zw8uTJJimEomk4btuUAh06dGDq1Kk+1Q09ePAgGzdurLGY8IkTJ1i7di2lpe4l/i6Xi23btrFz506v72GxWAgKCqrWcN17771MnjzZb0aR9YZSXNiyExwOj7/bVMn3jVLkbd2Fo7Sshg68Q0SI6Nieu//7/zNi+0pG7VrFqJ1/Y8A7LxHTrxdi8j/3VllZGUOHDmXq1Kl89dVX/PSnP+XkyZM+95Obm8vzzz/Po48+ysqVKz2T4HfddRf9+vXzy5Bizc0TWEM/H7BYLD6HB/bp04cuXbrU6AZxOByUl5d7VmWaTCaGDx/e4CNsu91OUZE7lv2WHc0rRTmKEpxcwUkZLkpwUowJB4ogl0JR9xTFIoI5LITmnRLrLnM94E5tAEj1v0JcLhcRERG0b9+e+Ph4pkyZUmMh9xvxwQcfsHnzZoqKipg9e7bnOenYsSMxMTEcOHCgrqpo/IhaR+wiEioiX4vIARHJFJHnjPYOIrJTRI6JyIciEmy0hxj7x4zjiQ2sQ6PRvHlzWrduXWN4XefOnZk4caIn7rkil3bLli0bdLJz+/bt3Hfffezbt6/B7tGgiHDHwN4UWFyYEPKwcx4bTuAiDkrERWz/VCx+tCCqLiilcNkd5H+1j4yFSzjw/17l1PtrKS8oqjZ75P79+1m6dCkFBQU899xzWK1Wn+85b948NmzYwK5du/jNb34TeL/6NNfgzfCuHBimlLoiIkHAdhH5HHgKeEUp9YGILAV+DCwx/l5SSiWLyBTgv4DJDSS/X9FYMfTXk5iYyEMPPUSbNm0a/d71gYhgHtiLiJAwRjksHhdMopHFMigqko4//SHmsPqfMFZKceHChWorCzUUdusVDsx7lewP15Fx8RyxykLb8OZEdU+m73/Pd7uFjOcoLCyMN954g6VLl9K3b1/uuecenn/+eZ/vaTabtTG/jah1xK7cXDF2g4xNAcOAj43294AfGK/HGfsYx4dLoMXm+RkdOnTgmWeeqbZAhVKK1157jddff71eqy3VNyv+uY5VMXaa9e7qyX0jFgvNuyaR+tJc2o4Z0mDlADds2MC///3veu+7OlwOJ9mLV3DsTx9Skl9AgbKTSSnO0jIKd2ewa9YCyvMLPecrpUhMTCQlJYU33njDkwVUo7kRXjlkRcQM7AGSgcXAcaBIKeUwTjkLVFiVtsAZAKWUQ0QuAzHAxXqUW+MlFdkJK6J0qjOOZWVlOJ1OwsPDG8R4KqX47LPPuHLlCpMmTarWlfWjmTMZNXo0ad16ULBjH1dzLmCJaEbs4DSa3dlwNVXNZjNDhw5ttPDRsryLnFqxFmWz0wwTnQgli++Selm/Oc7pjz6n039OxWQxU1ZWxogRIwA4ffo0R48eZfjw4TWWd9RowEvDrpRyAqkiEg38Heha1xuLyGPAY4Bf5RxpKCrKtUVERDRqKJ2I8Pvf/97zujpeeuklMjMzWb58ebWJvWpL1+BNCoBPP/2U/Px8HnrooWoNe8eOHT05UNo+MLTW/uoLESEhIaFB71EZ2yUrxdmn3Pemqm7OsnL2//oPtB4xkOZdkjwyXrhwgZUrV5KWlsbWrVt55JFHGk1mza2HT+GOSqki4AtgABAtIhVfDAlAjvE6B2gHYByPAgqq6etPSqm+Sqm+/hIz3JDY7Xa2bNnS6NEHIkJISAghISE1GsmKkLeafLAff/wxP/nJTygqKqr2uNPpJD09nZdffrlGd8/vfvc7li5d6lXUTsUXSCB68MRsRizu97kMF6cpJxc7l3F4zglvF++J1w8LC2Pbtm0MHjyYIUOGYDKZOHjwYJPIrrl1qPVTJiKxgF0pVSQiYcAI3BOiXwATgQ+AGcAa45K1xv5XxvHNyp+du41EUFAQY8aM8atUtxVMnDjxhsedTid2u/2G5zgcjhoXuYhIo01M+juhcS2JHdiHC5vdPv0WWIjA7AnkDIqKJO3VZ2nW3j0RbjKZSE5OZsmSJcTFxfHBBx8wfPjwJpJec6vgjSumNfCe4Wc3AR8ppdaJyGHgAxFZCOwD3jLOfwv4i4gcAwqBKQ0g9y2HyWTyaTGUPzF58mR++MMf1jiCNpvNtbp7morz589z8eJFunbt6hcx/sEtoug0+2EK9x6GIivdqJSwzmSi9ejBxA25+5prRIS77roLpRRz5szxuZ6u5vaj1iddKXUQqJIxSCl1AuhXTXsZMKlepNP4BbW5RfzZbZKdnU12djZJSUl+YdhFhIQHh+FasoCjb6zg4r8PoBxOwtu1JmH8vfRI/5nHDVPdtf76Pmv8i6Z/0jWaBuTuu++mZ8+e9VpYuq6YgoK4c/IY4of158rpHFw2O6GxLWmWmIApyKKNt6bOaMPuZxw/fpzLly+TkpKiF5TUA2FhYX45ryEihMbFEBLb0rOv0dQX2lnnZ5w6dYpvvvnGk29GU5WK8MtAmJNvLPeKUgqHw4HD4dDP1m2ANux+xuDBgxk/frxf+IP9lf3797N27doas2xqqrJ3715PEruXX35ZG/cARxt2PyMkJMTrFaAul4vi4mKfDJxSiqtXr1JSUuLViNflcmG1WmsNd6zAZrNRXFzsteFwOBxYrVaf8oGbTCZMJpN2X/jAX/7yF9q2bcusWbP44x//6PX/U3NrooeFtzDFxcV89NFHpKSk0K9flQClGtm4cSOlpaVMnDixVj9+YWEhn3zyCf369SM1NbXWvvfs2UNmZiaTJ08mMjKy1vOPHz/Oli1bGDt2rNdJzHr16kWvXr28OlfzHQkJCVWekz//+c9kZWVx6NAhcnJyarjSe+x2OxZL/UwAOxwOd4K4ephrstls9ZZzvr76slqtDRYCrQ37LUxkZCTTpk3z2W0zYsQIlFJexUO3aNGC6dOne133My0tjZSUFK+jUJKSkmjXrp1PuVr0SP3myMrKYt26dde8f5MmTSIvL48333yTJ598ss73WLx4Mffffz+JiYl17uvTTz8lJiaGgQMH1rmv9PR0XnzxxTr3AzB//nx+/vOf1znS6uzZs3z22Wf1ItP1aMN+C2MymQgPD6/9xEqIiE8PpNls9ukewcHBPo1mgoKC/KJYdKAzZ84cHn/8cXbs2MELL7zgec+joqKw2+2EhYURExNT5/s0a9aM6OjoeukrIiKC5s2b10tfoaGh9VYXISwsjJYtW9Y52qqkpKTBBiniD5EFffv2Vbt3725qMTSa25Ly8nKys7Pp2bNnnfs6cuQICQkJnmIzdeHMmTOEhIQQFxdX57727t1L796968WQ7t+/n549e9bZRVRSUsLp06fp3r37TV0vInuUUn2rO6ZH7BrNbUxOTg5vv/22p9rXzfh8Dx06xJo1axAR+vbty4YNGyguLsZisfDEE0/4PLJdtWoVWVlZDBs2jI0bNyIipKWlMXr0aJ/6KSoqYvHixYgITqeT9evXYzKZSEpKYurUqV73o5TyVJ+qCLNdv349LpeL6dOn06FDB6/6WbFiBTk5OcyZM4f333+fixfdmcytVisbNmwA4J577mHkyJE+6Vmj0E29paWlKY1G0/g8+OCDqnfv3qpXr15q6tSpN9XHli1b1C9+8Qs1f/58FR0drSwWi5o/f76KiopSBQUFPvWVn5+vBg0apMxms/rRj36kunXrpqZOnaqeeOIJn+Vas2aNCg8PV0uWLFFDhw5VMTEx6sknn1RjxozxqZ+TJ0+q6Ohodffdd6t27dopQP3sZz9TCQkJatOmTV73M3fuXNW8eXN18eJFlZKSoubNm6ciIiLUokWLVFRUlLr//vvV+PHjldVq9ao/YLeqwabqcEeN5jbm0qVLzJ49m5kzZ1JYWFj7BdUwZMgQXnjhBaxWK8HBwQwaNIgHHnjAZ9+4UorNmzdz/PhxXC4X7777Lk899dRNu3XeffddysvL2bBhA1arlVmzZtGjRw+fi6pER0eTlpbGrl27OHPmDDExMTz++OM+By08+uijHldQSkoKkyZN8tRmSEpK4p133mHTpk31Ep2kDbtGc5tTWlrK1atXaz+xBmw2G8888wx//etfWblyJWazmeLiYlq3bu1zX4sXLyYlJQWTyURoaGidCrSHhYUxcuRIRo0axZ49ezh48CBxcXE+R7Pk5+ezY8cOnn32Wdq2bcvVq1c5fPjwTctV0WdeXp6nyIvT6fR8MdZHeKf2sWs0tzGDBw8mPT0dwPPXV1avXs3ixYuZMGEChw8f5tChQyxdupSMjAyf+1q3bh1nzpzhnnvuIT09nSVLlpCYmEjv3lUSzNbKvHnzGDRoEM2aNQPgiy++wOVy+ZyKIioqiu7du/P6669TUlKC0+nkrbfeori42Kd+vvzyS+x2O++8847nPdq7dy8/+MEPyMzMpE+fPjzyyCMkJSX51G916KgYjeY25urVqxw7dgwRoVOnTjdV+7WoqIgzZ85UaTebzXTu3Nlnl4Xdbic7O5tWrVqRm5sLQExMjNcL2Cqw2WxkZ2dXMeSRkZE+x9nn5uZ6Jjsr06FDB69dRSdPnuTKlSvXtIkI8fHxHj3vuOMOr3/p3CgqRht2jUajuQW5kWHXPnaNRqMJMLSPXaPR+DXl5eWsW7fumsRliYmJ9O/fvwml8m+0YddoNH6NyWSibdu2fPXVVyxatIhFixZhtVo5cuQIJSUl15zbpk0b8vLycDgchISE0KNHj9syt5A27BqNxq8JCgqif//+WK1WQkND2bNnDxcuXCA7O5uMjAxKS0tJTU2lvLyc8PBwMjIyGDVqFAcOHCA7O7vesjreStTqYxeRUBH5WkQOiEimiDxntL8rIidFZL+xpRrtIiKvicgxETkoIn0aWAeNRnMbUTngY+HChQwdOpTp06fTpk0b9uzZQ6dOnejSpQszZ868bctLejN5Wg4MU0qlAKnAaBGpcG79SimVamz7jbb7gE7G9hiwpH5F1mg0GjexsbGMGTOG8ePHA5CcnMyFCxewWCxs3br1tq0UVasrxshJUBF8GWRsN4qRHAcsN677t4hEi0hrpVRunaXVaDS3Lb1792bZsmXEx8djs9m4cuUKiYmJlJeX06pVKxYuXEhMTAwnTpzAbrdz77333rYjdq987CJiBvYAycBipdROEZkFvCAi84FNwNNKqXKgLVB5tcJZo00bdo1Gc9PExsYybNiwGo9XRMl06tSpsUTyW7yKY1dKOZVSqUAC0E9E7gLSga7A3UBL4De+3FhEHhOR3SKyOz8/3zepNRqNRlMjPi1QUkoVAV8Ao5VSuUb2yHLgHaCimGIO0K7SZQlG2/V9/Ukp1Vcp1bciw5lGo9Fo6o43UTGxIhJtvA4DRgBHRKS10SbAD4CKjD9rgf8womP6A5e1f12j0WgaD2987K2B9ww/uwn4SCm1TkQ2i0gsIMB+4D+N8z8DxgDHgFJgZr1LrdFoNJoa8SYq5iBQJWemUqraWQwjGubxuoum0Wg0mptBJwHTaDSaAEMbdo1GowkwtGHXaDSaAEMbdo1GowkwtGHXaDSaAEMbdo1GowkwtGHXaDSaAEMbdo1GowkwtGHXaDSaAEMqVyNpMiFEioGsppajEbgDuNjUQjQCWs/AQuvpn9yplKo2g6K/1DzNUkr1bWohGhoR2a31DBy0noFFIOmpXTEajUYTYGjDrtFoNAGGvxj2PzW1AI2E1jOw0HoGFgGjp19Mnmo0Go2m/vCXEbtGo9Fo6glt2DUajSbAaHLDLiKjRSRLRI6JyNNNLU9dEJG3RSRPRDIqtbUUkQ0ictT428JoFxF5zdD7oIj0aTrJfUNE2onIFyJyWEQyReTnRntA6SoioSLytYgcMPR8zmjvICI7DX0+FJFgoz3E2D9mHE9sUgV8QETMIrJPRNYZ+wGnI4CInBKRQyKyX0R2G20B9dxCExt2o47qYuA+oDswVUS6N6VMdeRdYPR1bU8Dm5RSnYBNxj64de5kbI8BSxpJxvrAAfxSKdUd6A88bvzfAk3XcmCYUioFSAVGGwXa/wt4RSmVDFwCfmyc/2PgktH+inHercLPgW8q7QeijhUMVUqlVopZD7TnFpRSTbYBA4B/VtpPB9KbUqZ60CkRyKi0nwW0Nl63xr0YC+BNYGp1591qG7AGGBHIugLhwF7gHtyrEy1Gu+cZBv4JDDBeW4zzpKll90K3BNwGbRiwDneB+oDSsZKup4A7rmsLuOe2qV0xbYEzlfbPGm2BRCulVK7x+jzQyngdELobP8V7AzsJQF0NF8V+IA/YABwHipRSDuOUyrp49DSOXwZiGlXgm+NV4NeAy9iPIfB0rEAB/yMie0TkMaMt4J5bf0kpcFuglFIiEjDxpSISAawCfqGUsoqI51ig6KqUcgKpIhIN/B3o2rQS1S8i8gCQp5TaIyLfb2JxGoPBSqkcEYkDNojIkcoHA+W5beoRew7QrtJ+gtEWSFwQkdYAxt88o/2W1l1EgnAb9RVKqU+M5oDUFUApVQR8gdstES0iFYOiyrp49DSORwEFjSupzwwCHhSRU8AHuN0xfySwdPSglMox/ubh/qLuRwA+t01t2HcBnYwZ+GBgCrC2iWWqb9YCM4zXM3D7oyva/8OYee8PXK70c9CvEffQ/C3gG6XUy5UOBZSuIhJrjNQRkTDc8wjf4DbwE43TrtezQv+JwGZlOGf9FaVUulIqQSmViPvzt1kpNY0A0rECEWkmIpEVr4GRQAYB9twCTTt5ajwPY4Bs3L7LZ5tanjrqshLIBey4/XE/xu1/3AQcBTYCLY1zBXdE0HHgENC3qeX3Qc/BuH2VB4H9xjYm0HQFegH7DD0zgPlGexLwNXAM+BsQYrSHGvvHjONJTa2Dj/p+H1gXqDoaOh0wtswKexNoz61SSqcU0Gg0mkCjqV0xGo1Go6lntGHXaDSaAEMbdo1GowkwtGHXaDSaAEMbdo1GowkwtGHXaDSaAEMbdo1Gowkw/hf41+op1WeH1gAAAABJRU5ErkJggg==\n", 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" ] @@ -347,7 +348,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 21, "metadata": { "collapsed": false, "jupyter": { @@ -360,7 +361,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -395,7 +396,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 22, "metadata": { "collapsed": false, "jupyter": { @@ -408,7 +409,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -495,7 +496,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 23, "metadata": { "collapsed": false, "jupyter": { @@ -512,7 +513,7 @@ "['connections', 'snrs', 'utility']" ] }, - "execution_count": 9, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -533,7 +534,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 24, "metadata": { "collapsed": false, "jupyter": { @@ -549,7 +550,7 @@ "output_type": "stream", "text": [ "Raw observations: [ 0. 0. 0.3470676 1. -1. 0.\n", - " 0. 1. 0.2665389 -1. 0. 0.\n", + " 1. 1. 0.2665389 -0.08450864 0. 0.\n", " 0.38201445 1. -1. ]\n", "\n", "Observations for user 1:\n", @@ -558,9 +559,9 @@ "Current utility: -1.0\n", "\n", "Observations for user 2:\n", - "Current connections to the 2 cells: [0. 0.]\n", + "Current connections to the 2 cells: [0. 1.]\n", "SNR to the 2 cells: [1. 0.2665389]\n", - "Current utility: -1.0\n", + "Current utility: -0.08450863510370255\n", "\n", "Observations for user 3:\n", "Current connections to the 2 cells: [0. 0.]\n", @@ -597,7 +598,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 25, "metadata": { "collapsed": false, "jupyter": { @@ -650,7 +651,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 26, "metadata": { "collapsed": false, "jupyter": { @@ -665,7 +666,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "New, raw observations: [0.0, 0.0, 0, 0.39157578, 1.0, -1.0, 0.0, 1.0, 1, 0.08438771, 1.0, -0.14720577, 1.0, 0.0, 1, 1.0, 0.021902867, 0.65321183]\n", + "New, raw observations: [0.0, 0.0, 0, 0.39157578, 1.0, -1.0, 0.0, 0.0, 0, 0.08438771, 1.0, -1.0, 1.0, 0.0, 1, 1.0, 0.021902867, 0.65321183]\n", "\n", "Observations for user 1:\n", "Current connections to the 2 cells: [0.0, 0.0]\n", @@ -674,10 +675,10 @@ "Current utility: -1.0\n", "\n", "Observations for user 2:\n", - "Current connections to the 2 cells: [0.0, 1.0]\n", - "NEW: Any connection?: 1\n", + "Current connections to the 2 cells: [0.0, 0.0]\n", + "NEW: Any connection?: 0\n", "SNR to the 2 cells: [0.08438771, 1.0]\n", - "Current utility: -0.14720577001571655\n", + "Current utility: -1.0\n", "\n", "Observations for user 3:\n", "Current connections to the 2 cells: [1.0, 0.0]\n", @@ -726,7 +727,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 27, "metadata": { "collapsed": false, "jupyter": { @@ -742,25 +743,25 @@ "output_type": "stream", "text": [ "Requirement already satisfied: stable-baselines3 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (1.3.0)\n", - "Requirement already satisfied: numpy in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from stable-baselines3) (1.21.4)\n", + "Requirement already satisfied: gym<0.20,>=0.17 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from stable-baselines3) (0.19.0)\n", + "Requirement already satisfied: torch>=1.8.1 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from stable-baselines3) (1.10.0)\n", "Requirement already satisfied: pandas in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from stable-baselines3) (1.2.3)\n", "Requirement already satisfied: cloudpickle in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from stable-baselines3) (1.6.0)\n", - "Requirement already satisfied: torch>=1.8.1 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from stable-baselines3) (1.10.0)\n", "Requirement already satisfied: matplotlib in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from stable-baselines3) (3.5.0)\n", - "Requirement already satisfied: gym<0.20,>=0.17 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from stable-baselines3) (0.19.0)\n", + "Requirement already satisfied: numpy in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from stable-baselines3) (1.21.4)\n", "Requirement already satisfied: typing-extensions in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from torch>=1.8.1->stable-baselines3) (4.0.0)\n", - "Requirement already satisfied: pillow>=6.2.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (8.4.0)\n", "Requirement already satisfied: setuptools-scm>=4 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (6.3.2)\n", - "Requirement already satisfied: pyparsing>=2.2.1 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (2.4.7)\n", "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (2.8.1)\n", + "Requirement already satisfied: cycler>=0.10 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (0.10.0)\n", + "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (1.3.1)\n", + "Requirement already satisfied: pyparsing>=2.2.1 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (2.4.7)\n", "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (4.28.1)\n", + "Requirement already satisfied: pillow>=6.2.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (8.4.0)\n", "Requirement already satisfied: packaging>=20.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (21.3)\n", - "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (1.3.1)\n", - "Requirement already satisfied: cycler>=0.10 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from matplotlib->stable-baselines3) (0.10.0)\n", "Requirement already satisfied: pytz>=2017.3 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from pandas->stable-baselines3) (2021.1)\n", "Requirement already satisfied: six in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from cycler>=0.10->matplotlib->stable-baselines3) (1.15.0)\n", - "Requirement already satisfied: tomli>=1.0.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from setuptools-scm>=4->matplotlib->stable-baselines3) (1.2.2)\n", - "Requirement already satisfied: setuptools in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from setuptools-scm>=4->matplotlib->stable-baselines3) (46.1.3)\n" + "Requirement already satisfied: setuptools in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from setuptools-scm>=4->matplotlib->stable-baselines3) (46.1.3)\n", + "Requirement already satisfied: tomli>=1.0.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from setuptools-scm>=4->matplotlib->stable-baselines3) (1.2.2)\n" ] } ], @@ -778,7 +779,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 28, "metadata": { "collapsed": false, "jupyter": { @@ -796,320 +797,320 @@ "Using cpu device\n", "Wrapping the env with a `Monitor` wrapper\n", "Wrapping the env in a DummyVecEnv.\n", - "Logging to results_sb\\PPO_1\n", + "Logging to results_sb\\PPO_2\n", "---------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -5.47 |\n", + "| ep_rew_mean | -5.52 |\n", "| time/ | |\n", - "| fps | 168 |\n", + "| fps | 137 |\n", "| iterations | 1 |\n", - "| time_elapsed | 12 |\n", + "| time_elapsed | 14 |\n", "| total_timesteps | 2048 |\n", "---------------------------------\n", + "----------------------------------------\n", + "| rollout/ | |\n", + "| ep_len_mean | 10 |\n", + "| ep_rew_mean | -5.93 |\n", + "| time/ | |\n", + "| fps | 145 |\n", + "| iterations | 2 |\n", + "| time_elapsed | 28 |\n", + "| total_timesteps | 4096 |\n", + "| train/ | |\n", + "| approx_kl | 0.00966817 |\n", + "| clip_fraction | 0.0976 |\n", + "| clip_range | 0.2 |\n", + "| entropy_loss | -3.29 |\n", + "| explained_variance | -0.14 |\n", + "| learning_rate | 0.0003 |\n", + "| loss | 1.18 |\n", + "| n_updates | 10 |\n", + "| policy_gradient_loss | -0.0146 |\n", + "| value_loss | 2.37 |\n", + "----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -5.83 |\n", + "| ep_rew_mean | -5.08 |\n", "| time/ | |\n", - "| fps | 187 |\n", - "| iterations | 2 |\n", - "| time_elapsed | 21 |\n", - "| total_timesteps | 4096 |\n", - "| train/ | |\n", - "| approx_kl | 0.011307748 |\n", - "| clip_fraction | 0.119 |\n", - "| clip_range | 0.2 |\n", - "| entropy_loss | -3.29 |\n", - "| explained_variance | -0.0886 |\n", - "| learning_rate | 0.0003 |\n", - "| loss | 0.845 |\n", - "| n_updates | 10 |\n", - "| policy_gradient_loss | -0.015 |\n", - "| value_loss | 2.43 |\n", - "-----------------------------------------\n", - "-----------------------------------------\n", - "| rollout/ | |\n", - "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -5.18 |\n", - "| time/ | |\n", - "| fps | 197 |\n", + "| fps | 146 |\n", "| iterations | 3 |\n", - "| time_elapsed | 31 |\n", + "| time_elapsed | 41 |\n", "| total_timesteps | 6144 |\n", "| train/ | |\n", - "| approx_kl | 0.010906098 |\n", - "| clip_fraction | 0.0975 |\n", + "| approx_kl | 0.012774698 |\n", + "| clip_fraction | 0.143 |\n", "| clip_range | 0.2 |\n", "| entropy_loss | -3.27 |\n", - "| explained_variance | 0.283 |\n", + "| explained_variance | 0.306 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 1.11 |\n", + "| loss | 1.14 |\n", "| n_updates | 20 |\n", - "| policy_gradient_loss | -0.0166 |\n", - "| value_loss | 2.71 |\n", + "| policy_gradient_loss | -0.0218 |\n", + "| value_loss | 2.57 |\n", "-----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -5.6 |\n", + "| ep_rew_mean | -5.38 |\n", "| time/ | |\n", - "| fps | 201 |\n", + "| fps | 149 |\n", "| iterations | 4 |\n", - "| time_elapsed | 40 |\n", + "| time_elapsed | 54 |\n", "| total_timesteps | 8192 |\n", "| train/ | |\n", - "| approx_kl | 0.012331916 |\n", - "| clip_fraction | 0.132 |\n", + "| approx_kl | 0.011263395 |\n", + "| clip_fraction | 0.114 |\n", "| clip_range | 0.2 |\n", "| entropy_loss | -3.25 |\n", - "| explained_variance | 0.327 |\n", + "| explained_variance | 0.351 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 1.3 |\n", + "| loss | 1.09 |\n", "| n_updates | 30 |\n", - "| policy_gradient_loss | -0.0193 |\n", - "| value_loss | 2.51 |\n", + "| policy_gradient_loss | -0.0183 |\n", + "| value_loss | 2.54 |\n", "-----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -5.09 |\n", + "| ep_rew_mean | -4.74 |\n", "| time/ | |\n", - "| fps | 202 |\n", + "| fps | 149 |\n", "| iterations | 5 |\n", - "| time_elapsed | 50 |\n", + "| time_elapsed | 68 |\n", "| total_timesteps | 10240 |\n", "| train/ | |\n", - "| approx_kl | 0.014774322 |\n", - "| clip_fraction | 0.156 |\n", + "| approx_kl | 0.012882629 |\n", + "| clip_fraction | 0.146 |\n", "| clip_range | 0.2 |\n", "| entropy_loss | -3.2 |\n", - "| explained_variance | 0.348 |\n", + "| explained_variance | 0.335 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 1.38 |\n", + "| loss | 1.05 |\n", "| n_updates | 40 |\n", - "| policy_gradient_loss | -0.0223 |\n", - "| value_loss | 2.62 |\n", + "| policy_gradient_loss | -0.0197 |\n", + "| value_loss | 2.66 |\n", "-----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -4.83 |\n", + "| ep_rew_mean | -4.72 |\n", "| time/ | |\n", - "| fps | 203 |\n", + "| fps | 151 |\n", "| iterations | 6 |\n", - "| time_elapsed | 60 |\n", + "| time_elapsed | 81 |\n", "| total_timesteps | 12288 |\n", "| train/ | |\n", - "| approx_kl | 0.013777858 |\n", - "| clip_fraction | 0.16 |\n", - "| clip_range | 0.2 |\n", - "| entropy_loss | -3.14 |\n", - "| explained_variance | 0.434 |\n", - "| learning_rate | 0.0003 |\n", - "| loss | 1.04 |\n", - "| n_updates | 50 |\n", - "| policy_gradient_loss | -0.0227 |\n", - "| value_loss | 2.2 |\n", - "-----------------------------------------\n", - "-----------------------------------------\n", - "| rollout/ | |\n", - "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -4.67 |\n", - "| time/ | |\n", - "| fps | 205 |\n", - "| iterations | 7 |\n", - "| time_elapsed | 69 |\n", - "| total_timesteps | 14336 |\n", - "| train/ | |\n", - "| approx_kl | 0.012769257 |\n", + "| approx_kl | 0.012676832 |\n", "| clip_fraction | 0.166 |\n", "| clip_range | 0.2 |\n", - "| entropy_loss | -3.08 |\n", - "| explained_variance | 0.434 |\n", + "| entropy_loss | -3.16 |\n", + "| explained_variance | 0.427 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 1.19 |\n", - "| n_updates | 60 |\n", - "| policy_gradient_loss | -0.0197 |\n", - "| value_loss | 2.09 |\n", + "| loss | 0.891 |\n", + "| n_updates | 50 |\n", + "| policy_gradient_loss | -0.0221 |\n", + "| value_loss | 2.07 |\n", "-----------------------------------------\n", + "----------------------------------------\n", + "| rollout/ | |\n", + "| ep_len_mean | 10 |\n", + "| ep_rew_mean | -4.59 |\n", + "| time/ | |\n", + "| fps | 159 |\n", + "| iterations | 7 |\n", + "| time_elapsed | 90 |\n", + "| total_timesteps | 14336 |\n", + "| train/ | |\n", + "| approx_kl | 0.01478526 |\n", + "| clip_fraction | 0.167 |\n", + "| clip_range | 0.2 |\n", + "| entropy_loss | -3.1 |\n", + "| explained_variance | 0.41 |\n", + "| learning_rate | 0.0003 |\n", + "| loss | 0.996 |\n", + "| n_updates | 60 |\n", + "| policy_gradient_loss | -0.0233 |\n", + "| value_loss | 2.28 |\n", + "----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -4.16 |\n", + "| ep_rew_mean | -4.15 |\n", "| time/ | |\n", - "| fps | 206 |\n", + "| fps | 165 |\n", "| iterations | 8 |\n", - "| time_elapsed | 79 |\n", + "| time_elapsed | 99 |\n", "| total_timesteps | 16384 |\n", "| train/ | |\n", - "| approx_kl | 0.012809217 |\n", - "| clip_fraction | 0.147 |\n", + "| approx_kl | 0.010950519 |\n", + "| clip_fraction | 0.135 |\n", "| clip_range | 0.2 |\n", - "| entropy_loss | -3.02 |\n", - "| explained_variance | 0.42 |\n", + "| entropy_loss | -3.03 |\n", + "| explained_variance | 0.413 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 0.857 |\n", + "| loss | 0.832 |\n", "| n_updates | 70 |\n", - "| policy_gradient_loss | -0.0186 |\n", - "| value_loss | 2.09 |\n", + "| policy_gradient_loss | -0.0172 |\n", + "| value_loss | 2.03 |\n", "-----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -4.15 |\n", + "| ep_rew_mean | -4.13 |\n", "| time/ | |\n", - "| fps | 206 |\n", + "| fps | 168 |\n", "| iterations | 9 |\n", - "| time_elapsed | 89 |\n", + "| time_elapsed | 109 |\n", "| total_timesteps | 18432 |\n", "| train/ | |\n", - "| approx_kl | 0.014097567 |\n", - "| clip_fraction | 0.149 |\n", + "| approx_kl | 0.013974641 |\n", + "| clip_fraction | 0.182 |\n", "| clip_range | 0.2 |\n", "| entropy_loss | -2.95 |\n", - "| explained_variance | 0.473 |\n", + "| explained_variance | 0.461 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 0.967 |\n", + "| loss | 0.911 |\n", "| n_updates | 80 |\n", - "| policy_gradient_loss | -0.0178 |\n", - "| value_loss | 1.87 |\n", + "| policy_gradient_loss | -0.0215 |\n", + "| value_loss | 1.85 |\n", "-----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -4.18 |\n", + "| ep_rew_mean | -4.08 |\n", "| time/ | |\n", - "| fps | 206 |\n", + "| fps | 166 |\n", "| iterations | 10 |\n", - "| time_elapsed | 99 |\n", + "| time_elapsed | 123 |\n", "| total_timesteps | 20480 |\n", "| train/ | |\n", - "| approx_kl | 0.013525041 |\n", - "| clip_fraction | 0.143 |\n", + "| approx_kl | 0.013551852 |\n", + "| clip_fraction | 0.174 |\n", "| clip_range | 0.2 |\n", - "| entropy_loss | -2.87 |\n", - "| explained_variance | 0.498 |\n", + "| entropy_loss | -2.86 |\n", + "| explained_variance | 0.489 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 0.716 |\n", + "| loss | 0.745 |\n", "| n_updates | 90 |\n", - "| policy_gradient_loss | -0.0184 |\n", - "| value_loss | 1.58 |\n", + "| policy_gradient_loss | -0.0212 |\n", + "| value_loss | 1.51 |\n", "-----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -3.8 |\n", + "| ep_rew_mean | -3.96 |\n", "| time/ | |\n", - "| fps | 205 |\n", + "| fps | 167 |\n", "| iterations | 11 |\n", - "| time_elapsed | 109 |\n", + "| time_elapsed | 134 |\n", "| total_timesteps | 22528 |\n", "| train/ | |\n", - "| approx_kl | 0.011971119 |\n", - "| clip_fraction | 0.147 |\n", + "| approx_kl | 0.012691457 |\n", + "| clip_fraction | 0.156 |\n", "| clip_range | 0.2 |\n", - "| entropy_loss | -2.8 |\n", - "| explained_variance | 0.503 |\n", + "| entropy_loss | -2.78 |\n", + "| explained_variance | 0.485 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 1.13 |\n", + "| loss | 0.94 |\n", "| n_updates | 100 |\n", - "| policy_gradient_loss | -0.0191 |\n", - "| value_loss | 1.75 |\n", + "| policy_gradient_loss | -0.018 |\n", + "| value_loss | 1.82 |\n", "-----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -4.04 |\n", + "| ep_rew_mean | -3.94 |\n", "| time/ | |\n", - "| fps | 205 |\n", + "| fps | 168 |\n", "| iterations | 12 |\n", - "| time_elapsed | 119 |\n", + "| time_elapsed | 145 |\n", "| total_timesteps | 24576 |\n", "| train/ | |\n", - "| approx_kl | 0.011888548 |\n", - "| clip_fraction | 0.153 |\n", + "| approx_kl | 0.013166713 |\n", + "| clip_fraction | 0.171 |\n", "| clip_range | 0.2 |\n", - "| entropy_loss | -2.71 |\n", - "| explained_variance | 0.508 |\n", + "| entropy_loss | -2.69 |\n", + "| explained_variance | 0.492 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 0.697 |\n", + "| loss | 0.76 |\n", "| n_updates | 110 |\n", - "| policy_gradient_loss | -0.0171 |\n", - "| value_loss | 1.42 |\n", + "| policy_gradient_loss | -0.0186 |\n", + "| value_loss | 1.46 |\n", "-----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -3.2 |\n", + "| ep_rew_mean | -3.24 |\n", "| time/ | |\n", - "| fps | 206 |\n", + "| fps | 168 |\n", "| iterations | 13 |\n", - "| time_elapsed | 128 |\n", + "| time_elapsed | 157 |\n", "| total_timesteps | 26624 |\n", "| train/ | |\n", - "| approx_kl | 0.011168966 |\n", - "| clip_fraction | 0.16 |\n", + "| approx_kl | 0.011980441 |\n", + "| clip_fraction | 0.137 |\n", "| clip_range | 0.2 |\n", - "| entropy_loss | -2.66 |\n", - "| explained_variance | 0.513 |\n", + "| entropy_loss | -2.63 |\n", + "| explained_variance | 0.507 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 0.735 |\n", + "| loss | 0.765 |\n", "| n_updates | 120 |\n", - "| policy_gradient_loss | -0.0208 |\n", - "| value_loss | 1.55 |\n", + "| policy_gradient_loss | -0.0173 |\n", + "| value_loss | 1.49 |\n", "-----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -3.76 |\n", + "| ep_rew_mean | -3.71 |\n", "| time/ | |\n", - "| fps | 206 |\n", + "| fps | 171 |\n", "| iterations | 14 |\n", - "| time_elapsed | 138 |\n", + "| time_elapsed | 167 |\n", "| total_timesteps | 28672 |\n", "| train/ | |\n", - "| approx_kl | 0.013959848 |\n", - "| clip_fraction | 0.174 |\n", + "| approx_kl | 0.012702217 |\n", + "| clip_fraction | 0.129 |\n", "| clip_range | 0.2 |\n", - "| entropy_loss | -2.6 |\n", - "| explained_variance | 0.503 |\n", + "| entropy_loss | -2.53 |\n", + "| explained_variance | 0.502 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 0.876 |\n", + "| loss | 0.628 |\n", "| n_updates | 130 |\n", - "| policy_gradient_loss | -0.0216 |\n", - "| value_loss | 1.6 |\n", + "| policy_gradient_loss | -0.0151 |\n", + "| value_loss | 1.58 |\n", "-----------------------------------------\n", "-----------------------------------------\n", "| rollout/ | |\n", "| ep_len_mean | 10 |\n", - "| ep_rew_mean | -3.54 |\n", + "| ep_rew_mean | -3.6 |\n", "| time/ | |\n", - "| fps | 207 |\n", + "| fps | 172 |\n", "| iterations | 15 |\n", - "| time_elapsed | 148 |\n", + "| time_elapsed | 177 |\n", "| total_timesteps | 30720 |\n", "| train/ | |\n", - "| approx_kl | 0.010908822 |\n", - "| clip_fraction | 0.133 |\n", + "| approx_kl | 0.010899981 |\n", + "| clip_fraction | 0.122 |\n", "| clip_range | 0.2 |\n", - "| entropy_loss | -2.52 |\n", - "| explained_variance | 0.548 |\n", + "| entropy_loss | -2.48 |\n", + "| explained_variance | 0.549 |\n", "| learning_rate | 0.0003 |\n", - "| loss | 1.02 |\n", + "| loss | 0.816 |\n", "| n_updates | 140 |\n", - "| policy_gradient_loss | -0.0144 |\n", - "| value_loss | 1.54 |\n", + "| policy_gradient_loss | -0.0165 |\n", + "| value_loss | 1.47 |\n", "-----------------------------------------\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 14, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -1141,7 +1142,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 29, "metadata": { "collapsed": false, "jupyter": { @@ -1157,29 +1158,29 @@ "output_type": "stream", "text": [ "Requirement already satisfied: tensorboard in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (2.7.0)\n", - "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from tensorboard) (1.8.0)\n", + "Requirement already satisfied: absl-py>=0.4 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from tensorboard) (1.0.0)\n", "Requirement already satisfied: google-auth<3,>=1.6.3 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from tensorboard) (2.3.3)\n", - "Requirement already satisfied: werkzeug>=0.11.15 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from tensorboard) (2.0.2)\n", - "Requirement already satisfied: grpcio>=1.24.3 in c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages (from tensorboard) (1.42.0)\n", - 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"execution_count": 18, + "execution_count": 39, "metadata": { "collapsed": false, "jupyter": { @@ -1208,7 +1209,7 @@ { "data": { "text/plain": [ - "Reusing TensorBoard on port 6006 (pid 19344), started 22:35:08 ago. (Use '!kill 19344' to kill it.)" + "Reusing TensorBoard on port 6006 (pid 6156), started 0:20:37 ago. (Use '!kill 6156' to kill it.)" ] }, "metadata": {}, @@ -1218,11 +1219,11 @@ "data": { "text/html": [ "\n", - " \n", " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%tensorboard --logdir ray_results" - ] - }, - { - "cell_type": "markdown", - "id": "a6c32f8b-eefd-4c30-808d-6bfb4bbbee35", - "metadata": {}, - "source": [ - "To visualize the final multi-agent policy, load the latest model checkpoint:" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "bfc933bc-4983-49ba-a7f4-8032886bd045", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2021-11-24 12:41:23,766\tINFO ppo.py:166 -- In multi-agent mode, policies will be optimized sequentially by the multi-GPU optimizer. Consider setting simple_optimizer=True if this doesn't work for you.\n", - "2021-11-24 12:41:23,766\tINFO trainer.py:770 -- Current log_level is WARN. For more information, set 'log_level': 'INFO' / 'DEBUG' or use the -v and -vv flags.\n" - ] - }, - { - "ename": "RayActorError", - "evalue": "The actor died because of an error raised in its creation task, \u001b[36mray::RolloutWorker.__init__()\u001b[39m (pid=18304, ip=127.0.0.1)\n File \"python\\ray\\_raylet.pyx\", line 565, in ray._raylet.execute_task\n File \"python\\ray\\_raylet.pyx\", line 569, in ray._raylet.execute_task\n File \"python\\ray\\_raylet.pyx\", line 519, in ray._raylet.execute_task.function_executor\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\_private\\function_manager.py\", line 576, in actor_method_executor\n return method(__ray_actor, *args, **kwargs)\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\util\\tracing\\tracing_helper.py\", line 451, in _resume_span\n return method(self, *_args, **_kwargs)\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\evaluation\\rollout_worker.py\", line 584, in __init__\n self._build_policy_map(\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\util\\tracing\\tracing_helper.py\", line 451, in _resume_span\n return method(self, *_args, **_kwargs)\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\evaluation\\rollout_worker.py\", line 1384, in _build_policy_map\n self.policy_map.create_policy(name, orig_cls, obs_space, act_space,\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\policy\\policy_map.py\", line 123, in create_policy\n sess = self.session_creator()\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\evaluation\\worker_set.py\", line 323, in session_creator\n return tf1.Session(\nAttributeError: 'NoneType' object has no attribute 'Session'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mRayActorError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_1344/335420695.py\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mcheckpoint\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0manalysis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_last_checkpoint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mmodel\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mppo\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPPOTrainer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0menv\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'mobile-small-ma-v0'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 3\u001b[0m \u001b[0mmodel\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrestore\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcheckpoint\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\agents\\trainer_template.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, config, env, logger_creator)\u001b[0m\n\u001b[0;32m 135\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 136\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0menv\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlogger_creator\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 137\u001b[1;33m \u001b[0mTrainer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0menv\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlogger_creator\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 138\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 139\u001b[0m \u001b[1;33m@\u001b[0m\u001b[0moverride\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbase\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\agents\\trainer.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, config, env, logger_creator)\u001b[0m\n\u001b[0;32m 621\u001b[0m \u001b[0mlogger_creator\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdefault_logger_creator\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 622\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 623\u001b[1;33m \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlogger_creator\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 624\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 625\u001b[0m \u001b[1;33m@\u001b[0m\u001b[0mclassmethod\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\tune\\trainable.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, config, logger_creator)\u001b[0m\n\u001b[0;32m 105\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 106\u001b[0m \u001b[0mstart_time\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 107\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msetup\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcopy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdeepcopy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 108\u001b[0m \u001b[0msetup_time\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0mstart_time\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 109\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0msetup_time\u001b[0m \u001b[1;33m>\u001b[0m \u001b[0mSETUP_TIME_THRESHOLD\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\agents\\trainer_template.py\u001b[0m in \u001b[0;36msetup\u001b[1;34m(self, config)\u001b[0m\n\u001b[0;32m 145\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_override_all_subkeys_if_type_changes\u001b[0m \u001b[1;33m+=\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 146\u001b[0m \u001b[0moverride_all_subkeys_if_type_changes\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 147\u001b[1;33m \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msetup\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 148\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 149\u001b[0m def _init(self, config: TrainerConfigDict,\n", - "\u001b[1;32mc:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\agents\\trainer.py\u001b[0m in \u001b[0;36msetup\u001b[1;34m(self, config)\u001b[0m\n\u001b[0;32m 774\u001b[0m \u001b[0mlogging\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetLogger\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"ray.rllib\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msetLevel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"log_level\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 775\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 776\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_init\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0menv_creator\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 777\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 778\u001b[0m \u001b[1;31m# Evaluation setup.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\agents\\trainer_template.py\u001b[0m in \u001b[0;36m_init\u001b[1;34m(self, config, env_creator)\u001b[0m\n\u001b[0;32m 169\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 170\u001b[0m \u001b[1;31m# Creating all workers (excluding evaluation workers).\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 171\u001b[1;33m self.workers = self._make_workers(\n\u001b[0m\u001b[0;32m 172\u001b[0m \u001b[0menv_creator\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0menv_creator\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 173\u001b[0m \u001b[0mvalidate_env\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mvalidate_env\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\agents\\trainer.py\u001b[0m in \u001b[0;36m_make_workers\u001b[1;34m(self, env_creator, validate_env, policy_class, config, num_workers)\u001b[0m\n\u001b[0;32m 856\u001b[0m \u001b[0mWorkerSet\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mThe\u001b[0m \u001b[0mcreated\u001b[0m \u001b[0mWorkerSet\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 857\u001b[0m \"\"\"\n\u001b[1;32m--> 858\u001b[1;33m return WorkerSet(\n\u001b[0m\u001b[0;32m 859\u001b[0m \u001b[0menv_creator\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0menv_creator\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 860\u001b[0m \u001b[0mvalidate_env\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mvalidate_env\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\evaluation\\worker_set.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, env_creator, validate_env, policy_class, trainer_config, num_workers, logdir, _setup)\u001b[0m\n\u001b[0;32m 85\u001b[0m (not trainer_config.get(\"observation_space\") or\n\u001b[0;32m 86\u001b[0m not trainer_config.get(\"action_space\")):\n\u001b[1;32m---> 87\u001b[1;33m remote_spaces = ray.get(self.remote_workers(\n\u001b[0m\u001b[0;32m 88\u001b[0m \u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mforeach_policy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremote\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 89\u001b[0m lambda p, pid: (pid, p.observation_space, p.action_space)))\n", - "\u001b[1;32mc:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\_private\\client_mode_hook.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 103\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[1;34m\"init\"\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mis_client_mode_enabled_by_default\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 104\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 105\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 106\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 107\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\worker.py\u001b[0m in \u001b[0;36mget\u001b[1;34m(object_refs, timeout)\u001b[0m\n\u001b[0;32m 1625\u001b[0m \u001b[1;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mas_instanceof_cause\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1626\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1627\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1628\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1629\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mis_individual_id\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mRayActorError\u001b[0m: The actor died because of an error raised in its creation task, \u001b[36mray::RolloutWorker.__init__()\u001b[39m (pid=18304, ip=127.0.0.1)\n File \"python\\ray\\_raylet.pyx\", line 565, in ray._raylet.execute_task\n File \"python\\ray\\_raylet.pyx\", line 569, in ray._raylet.execute_task\n File \"python\\ray\\_raylet.pyx\", line 519, in ray._raylet.execute_task.function_executor\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\_private\\function_manager.py\", line 576, in actor_method_executor\n return method(__ray_actor, *args, **kwargs)\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\util\\tracing\\tracing_helper.py\", line 451, in _resume_span\n return method(self, *_args, **_kwargs)\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\evaluation\\rollout_worker.py\", line 584, in __init__\n self._build_policy_map(\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\util\\tracing\\tracing_helper.py\", line 451, in _resume_span\n return method(self, *_args, **_kwargs)\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\evaluation\\rollout_worker.py\", line 1384, in _build_policy_map\n self.policy_map.create_policy(name, orig_cls, obs_space, act_space,\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\policy\\policy_map.py\", line 123, in create_policy\n sess = self.session_creator()\n File \"c:\\users\\stefan\\git-repos\\work\\mobile-env\\venv\\lib\\site-packages\\ray\\rllib\\evaluation\\worker_set.py\", line 323, in session_creator\n return tf1.Session(\nAttributeError: 'NoneType' object has no attribute 'Session'" - ] - } - ], - "source": [ - "checkpoint = analysis.get_last_checkpoint()\n", - "model = ppo.PPOTrainer(config=config, env='mobile-small-ma-v0')\n", - "model.restore(checkpoint)" - ] - }, - { - "cell_type": "markdown", - "id": "62cff06a-46bb-4634-98fb-9386ef30dca2", - "metadata": {}, - "source": [ - "Mobile-Env provides a render() function to visualize the simulation.\n", - "In Google Colaboratory the better-looking 'human' mode is unavailable (only available locally). Still, we can visualize the final policy as RGB images:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a0954673-504d-4d1a-91d0-9834f4673754", - "metadata": {}, - "outputs": [], - "source": [ - "import time\n", - "import pylab as pl\n", - "import matplotlib.pyplot as plt\n", - "from IPython import display\n", - "%matplotlib inline\n", - "\n", - "env = register('mobile-small-ma-v0')\n", - "done = {'__all__': False}\n", - "obs = env.reset()\n", - "\n", - "while not done['__all__']:\n", - " # gather action from each actor (for each UE)\n", - " action = {}\n", - " for agent_id, agent_obs in obs.items():\n", - " policy_id = config['multiagent']['policy_mapping_fn'](agent_id)\n", - " action[agent_id] = model.compute_action(agent_obs, policy_id=policy_id)\n", - " \n", - " # perform step on simulation environment \n", - " obs, reward, done, info = env.step(action)\n", - "\n", - " # display environment as RGB\n", - " plt.imshow(env.env.render(mode='rgb_array'))\n", - " display.display(plt.gcf())\n", - " display.clear_output(wait=True)\n", - " time.sleep(0.025)" - ] - }, - { - "cell_type": "markdown", - "id": "10ab9204-6fe7-4bdc-a1fd-8448ba352107", - "metadata": {}, - "source": [ - "# Central Environment with Stable-Baselines3" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5f634160-6737-4a8a-9848-d31ea202d79f", - "metadata": {}, - "outputs": [], - "source": [ - "!pip install stable-baselines3" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ee2d6df8-b020-4e85-80fe-7c9572fb9fe5", - "metadata": {}, - "outputs": [], - "source": [ - "from stable_baselines3 import PPO\n", - "from stable_baselines3.ppo import MlpPolicy" - ] - }, - { - "cell_type": "markdown", - "id": "349c7adf-d971-442b-a5b9-a82b40eca351", - "metadata": {}, - "source": [ - "The decision making policy can also be trained on scenarios that simulate centralized control over user equipments, i.e., one single agent decides what connections should be established for each UE and is given global information. The centralized setting wraps the observations, rewards and actions of the multi-agent setting. Now, observations are single (concatenated) vectors that jointly represent up-to-date information on all UEs. The reward is the average utility of active UEs. Similarly, actions are vectors of discrete decisions.\n", - "\n", - "Use *stable-baselines3*'s PPO agent on the (small) centralized control environment and train it for 500,000 steps:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "490a6382-a5c2-40cf-9f24-431c4a3e796c", - "metadata": {}, - "outputs": [], - "source": [ - "# create the small central simulation\n", - "env = gym.make(\"mobile-small-central-v0\")\n", - "\n", - "# train PPO agent on environment\n", - "model = PPO(MlpPolicy, env, verbose=1, tensorboard_log='ppo_central_tensorboard')\n", - "model.learn(total_timesteps=50000)" - ] - }, - { - "cell_type": "markdown", - "id": "dfcd0c7e-1725-4d5e-8e3d-29560eff0e39", - "metadata": {}, - "source": [ - "Visualize the training results with Tensorboard:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e544681c-938e-45eb-9481-5d8084c9028c", - "metadata": {}, - "outputs": [], - "source": [ - "%tensorboard --logdir ppo_central_tensorboard" - ] - }, - { - "cell_type": "markdown", - "id": "3db72f60-2297-4a70-bc5c-04fc07622895", - "metadata": {}, - "source": [ - "Visualize what the central agent has learned. Note that the RGB visualization on Google Colaboratory does not render the environment as clearly as the 'human' mode, which is unavailable in virtual environments." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "22f251ed-a1ef-4647-abc1-9457cbd4d72a", - "metadata": {}, - "outputs": [], - "source": [ - "import time\n", - "import pylab as pl\n", - "import matplotlib.pyplot as plt\n", - "from IPython import display\n", - "%matplotlib inline\n", - "\n", - "env = gym.make('mobile-small-central-v0')\n", - "done = False\n", - "obs = env.reset()\n", - "\n", - "while not done:\n", - " action, _ = model.predict(obs)\n", - "\n", - " # perform step on simulation environment \n", - " obs, reward, done, info = env.step(action)\n", - "\n", - " # display environment as RGB\n", - " plt.imshow(env.render(mode='rgb_array'))\n", - " display.display(plt.gcf())\n", - " display.clear_output(wait=True)\n", - " time.sleep(0.025)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6f1297e5-b221-49d7-ba51-361b860e22b4", - "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": "3.8.2" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/setup.py b/setup.py index f7049e7..ec267a5 100644 --- a/setup.py +++ b/setup.py @@ -19,8 +19,7 @@ setup( name="mobile-env", - # always use higher version in dev than what's on PyPI - version="0.3.0", + version="1.0.0", author="Stefan Schneider, Stefan Werner", description="mobile-env: An Open Environment for Autonomous Coordination in Wireless Mobile Networks", long_description=long_description,