{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### Updates to Assignment\n", "\n", "#### If you were working on the older version:\n", "* Please click on the \"Coursera\" icon in the top right to open up the folder directory. \n", "* Navigate to the folder: Week 3/ Planar data classification with one hidden layer. You can see your prior work in version 6b: \"Planar data classification with one hidden layer v6b.ipynb\"\n", "\n", "#### List of bug fixes and enhancements\n", "* Clarifies that the classifier will learn to classify regions as either red or blue.\n", "* compute_cost function fixes np.squeeze by casting it as a float.\n", "* compute_cost instructions clarify the purpose of np.squeeze.\n", "* compute_cost clarifies that \"parameters\" parameter is not needed, but is kept in the function definition until the auto-grader is also updated.\n", "* nn_model removes extraction of parameter values, as the entire parameter dictionary is passed to the invoked functions." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Planar data classification with one hidden layer\n", "\n", "Welcome to your week 3 programming assignment. It's time to build your first neural network, which will have a hidden layer. You will see a big difference between this model and the one you implemented using logistic regression. \n", "\n", "**You will learn how to:**\n", "- Implement a 2-class classification neural network with a single hidden layer\n", "- Use units with a non-linear activation function, such as tanh \n", "- Compute the cross entropy loss \n", "- Implement forward and backward propagation\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1 - Packages ##\n", "\n", "Let's first import all the packages that you will need during this assignment.\n", "- [numpy](https://www.numpy.org/) is the fundamental package for scientific computing with Python.\n", "- [sklearn](http://scikit-learn.org/stable/) provides simple and efficient tools for data mining and data analysis. \n", "- [matplotlib](http://matplotlib.org) is a library for plotting graphs in Python.\n", "- testCases provides some test examples to assess the correctness of your functions\n", "- planar_utils provide various useful functions used in this assignment" ] }, { "cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [], "source": [ "# Package imports\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from testCases_v2 import *\n", "import sklearn\n", "import sklearn.datasets\n", "import sklearn.linear_model\n", "from planar_utils import (\n", " plot_decision_boundary,\n", " sigmoid,\n", " load_planar_dataset,\n", " load_extra_datasets,\n", ")\n", "\n", "%matplotlib inline\n", "\n", "np.random.seed(1) # set a seed so that the results are consistent" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2 - Dataset ##\n", "\n", "First, let's get the dataset you will work on. The following code will load a \"flower\" 2-class dataset into variables `X` and `Y`." ] }, { "cell_type": "code", "execution_count": 113, "metadata": {}, "outputs": [], "source": [ "X, Y = load_planar_dataset()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visualize the dataset using matplotlib. The data looks like a \"flower\" with some red (label y=0) and some blue (y=1) points. Your goal is to build a model to fit this data. In other words, we want the classifier to define regions as either red or blue." ] }, { "cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Visualize the data:\n", "plt.scatter(X[0, :], X[1, :], c=Y, s=40, cmap=plt.cm.Spectral);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You have:\n", " - a numpy-array (matrix) X that contains your features (x1, x2)\n", " - a numpy-array (vector) Y that contains your labels (red:0, blue:1).\n", "\n", "Lets first get a better sense of what our data is like. \n", "\n", "**Exercise**: How many training examples do you have? In addition, what is the `shape` of the variables `X` and `Y`? \n", "\n", "**Hint**: How do you get the shape of a numpy array? [(help)](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.shape.html)" ] }, { "cell_type": "code", "execution_count": 115, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The shape of X is: (2, 400)\n", "The shape of Y is: (1, 400)\n", "I have m = 400 training examples!\n" ] } ], "source": [ "### START CODE HERE ### (≈ 3 lines of code)\n", "shape_X = X.shape\n", "shape_Y = Y.shape\n", "m = shape_X[1] # training set size\n", "### END CODE HERE ###\n", "\n", "print(\"The shape of X is: \" + str(shape_X))\n", "print(\"The shape of Y is: \" + str(shape_Y))\n", "print(\"I have m = %d training examples!\" % (m))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
**shape of X** (2, 400)
**shape of Y**(1, 400)
**m** 400
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3 - Simple Logistic Regression\n", "\n", "Before building a full neural network, lets first see how logistic regression performs on this problem. You can use sklearn's built-in functions to do that. Run the code below to train a logistic regression classifier on the dataset." ] }, { "cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [], "source": [ "# Train the logistic regression classifier\n", "clf = sklearn.linear_model.LogisticRegressionCV()\n", "Y_reshaped = Y.ravel()\n", "clf.fit(X.T, Y_reshaped);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can now plot the decision boundary of these models. Run the code below." ] }, { "cell_type": "code", "execution_count": 117, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy of logistic regression: 47 % (percentage of correctly labelled datapoints)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/4g/qjqbhxd90rn8zxwsc9bvjt1m0000gp/T/ipykernel_83512/2850944514.py:9: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " % float(\n" ] }, { "data": { "image/png": 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LlI6ODpqbmwuuX1GiZjy1+4823ItbX1GnrlAoFArFkiVqZHjTmV9PjOOFWFEj+/iUk1u34NatC9wbhUKhUCgU06GU64hyFFYoFAqFQrEsUKJGoVAoFArFskCJGoVCoVAoFMsCJWoUCoVCoVAsC5SoUSgUCoVCsSxQokahUCgUCsWyQIkahUKhUCgUywIlahQKhUKhUCwLlKhRKBQKhUKxLFCiRqFQKBQKxbJAiRqFQqFQKBTLAiVqFAqFQqFQLAuUqFEoFAqFQrEsUKJGoVAoFArFskCJGoVCoVAoFMsCJWoUCoVCoVAsC5SoUSgUCoVCsSxQokahUCgUCsWyQIkahUKhUCgUywIlahQKhUKhUCwLlKhRKBQKhUKxLFCiRqFQKBQKxbJAiRqFQqFQKBTLAiVqFAqFQqFQLAuUqFEoFAqFQrEsUKJGoVAoFArFskCJGoVCoVAoFMsCJWoUCoVCoVAsC5SoUSgUihWCaUrSKRPDkAvdFYViTrAsdAcUCoVCMbekUiaD/WnCo+bEMo9Xo6rWisOhnm0Vywd1NSsUCsUyJpU0uXw+mSNoACJhk/YLSeIxs8CWCsXSY8mKmv/+3/87Qgg+/vGPL3RXFAqFYtHS15PGLKBbpISerhRSqukoxfJgSYqal19+ma985Svs2LFjobuiUCgUi5ZUyiQWLW6JSaekstYolg1LTtREIhHe85738NWvfpVAILDQ3VEoFIpFSypZngWm3HYKxWJnyYmaj3zkIzz88MPcf//9Jdsmk0lCoVDOn0KhUKwUtDLv8OW2UygWO0sq+uk73/kOBw4c4OWXXy6r/ec//3k++9nPznGvFIqlx5DNz1lPC0ndjicTZUP4Et5MbKG7pZhlnC4NXQfDKNxGCHB79fnrlEIxhywZUdPR0cEf/uEf8uSTT+JwOMra5tOf/jSf+MQnJt6HQiFWrVo1V11UKADIpCXJpImmgcOpIYRY6C5NYKCxt/ZGzntbEfKKH8X+wDb2jBxnz8hxFk9vFdeKEIKqGiv9vemCbfyVOrquvnXF8mDJiJpXXnmF/v5+du/ePbHMMAyeeeYZvvSlL5FMJtH13KcNu92O3W6f764qViiZtKSvN0UkdEUs6DpU1VjxV+qLQtw8W72b854WAKTInXN4pXIbLiPBltD5heiaYo7w+jSGBsHITF1ntUJ17ZIZBhSKkiyZq/m+++7j6NGjOcve//73s2nTJv7kT/5kiqBRKOaTTEZy+UKCzFUDh2FAf2+aTEZSU2ddmM6NEdUdnPatyc435ENKXglsYVPoAhrKcXQhMDKSSNjAMMFmE7g9WUufYUiCwxlGgwZGRqJbBP6ATkXAUtLK0tudzitoANJpGB40qK5VTjWK5cGSETVer5dt27blLHO73VRVVU1ZrlDMN8ODmSmC5ur1FQEdmy3/4BGPGQwPZYhFTKTM+kIEqix4ivg6SJkNxR0Px3V7dBzOwoPTZVdjcakiBDGLi0F7gNrkcLGWillGSslgf4bhoQyTvyTdAjV1Vob6M6TTV1aYKclAX4bgiEHLajsWS35hk0yaRCPFw7VHhjJUVlvQtIW3JCoU18qSETUKxWJFSsnoSBFFM8boiEFN3VTRERzO0NeT6/MQi5rEoimqqi1U57HwJJMm3e0pUqkrA91gfwaHU9C0yo7FOnWAymgWBJS0wWSEsnrONwN9GUaGpl5DRgZ6uwr7w6RTkr7uFI2rbCQTklTKRNcFLpeG0ASxEoIGwDQhmZA4XUrUKJY+S1rUPPXUUwvdBYUC06RgxtbJZNJT5UQyaU4RNJMZGszgdGu4PVeERiYj6biYzBvRkohLOi4laV1rn/LkXZkaRZbw6xFSUpEOlzgTxWySScu8gqZcImGTi+eSpCcJXE2H6lor5SYK7u1OkUlLhAZen06g0oLNrqakFEsPddUqFNeIphV2U5lMPrev0eHSg9nVA15wOFM0RDeVkoRDUxs0xfvwpCM5UU9TkRyrWE9KLOnnnSVFvu9qukwWNACmAf09adKp8jIFp5IS08xahoLDBhfPJYlGZi60FIqFQokaheIaEULg9ZWesvH5pwqFctLTJ+K5bULB/INgzO3jwqbdnNh9B/tqrmPAnptxWwD39e1Dk2ZBYSOFxmH/Jn7SdB9JbWEdm1cKRmbunLKDIwY2+8ymlTovp0mVKYoUisWCehxTKGaBqhoL4bBBISOIx6vld+ItZ7y5qo1h5A6CEriw5Xo61m2bmAcTwCVtC6sjHdzbvw/LWMfqk0O8ueuXvBzYyiV3c14TkxQaIzYfBwJbuGXocBkdVFwLFtvc+rJ4K3SCQ8Wte4XouJRkzXrHokhHoFCUg7LUKBSzgM2u0dJmx5pngPL5dRqabXm3KxbdNNHGk9vm6mN0rt2aFTSQnQvTNORY3vuL7mYes+6kqyNJNGIgpaQyNcqqWG/RY0qhcdK3FkPdIuYcr08va/pypkiTGTsBZ9LlWRMVisWCumMpFLOEw6mxep2dVW02auut1DVYWbPBQUOTrWC4bEXAgijxKwxU5RpUJwshU2i0r9teeGMh6Gpax1DSTuflFH09aaSUjNgq0ChRvVmzErOUl71bMXN0XVBbX3iqT9PA7pi56hkdyRAJz3yKKxpWokaxdFDTTwrFLCKEwOXWcbnLa2+xCJpbbHS1p/JGUDWusmF3ZFVPPG7S150imbgyQIUD1aTtJYSHEAzXNtHQcY7REQOHQ8NSlUGWMfeVCCbxeso7F8XM8Vda0HQY7MvNR+Nya9Q2WLHZBNGIyehIhljULCvabpyZTDtNxiw3hEqhWAQoUaNQLDAut86a9Q5GgxmiERMJuFwaFQEL1rF8M5GwQVd7asq2hlZeThlTv/JTHx7M0FbfyaHAlsIbSBPfyCDDlyPYmqxU5HFyVswuvgoLXp9OMiExTYnVKrBOStbo8epjGYfLVzRCUHZYdyEcDmXQVywd1J1KoVgE6BZBZbWVyuqp6xJxM6+gAXCHg9lRq5hThhC4Q1cyBKfTkqroME2xXrqdtVNqQGVHQUHr6ayTcH9PGq9PVxln5wEhBA5n4c85WEaSR8hOWVXVWBjou7awbCHAYhXEYyZ2h1DXgGLRoyS4QrFIyWQkqaRB5+VkwTb2ZJzq3vbC2f9ME2c4SMVw/5RVD/Q9T110AABhmgjTACkR0mTjoeeoGuga34Xyq1gkpJKlzS66BdZudOAPXPszq5TQeTlF+8Uk508nGOzP+mQpFIsVZalRKBYI0zQZGTIIBbPhtharwFdhwWKB4aFMju9MMdYffZGwv5qUw5ljdRGmiWZk2HLgmRzvGYs1O/DpRorbjj3JhXSAgcY2DN2CKzJKfcd5rOlcIZWew1wqivLRdIFpFv8uxvVtKQf06WKaMDSQIZU0aWi2qTBvxaJEiRqFYgEIhzL0dKZz/B0MQzKQKFwyoRD2RIw9z/yMwZ07uVizjrRuRRgGdZ3naTl3FFc0t+xBZVU20qa3O00oaFDBABUjA0WPYVHloBYFFRU6Q4PFp5SkCSPDGaqqrbg9WsmClpXVOh6vTldHqmA178mEQyYVUTOndIdCsVhQokahmGfCIYPujumLl2LYkgnuHD3M3dEjhFMavedjyDxP9L4KDX+lTnDYKJiZ+GqEKC+fjmLu8VdaGLqqknc+gmOiprrWSjRSePrS4RRU11oZHTHKEjQT+x/JKFGjWJQonxqFYh6RMltVebbx+LSsvzDgs5msWW+nqsaCzSawWLKhwU0tNuqbskkAp1NA0VuhlazsrZgfLNZsBe5SZNLZa83h1GhusaHl2cTl1mhutSOEIBKeXtz31bWmFIrFgrLUKBTzSDRiXnPekHxEQiaRUAJvhUZdgw2LJfsEXl07NalbJi1zcqGUIhQ0CY8m8FdaqKmz5PWlkHJsnzI78KoombnDYi392U7+itxenbUbHYRDBsmERNOylrfxsh1SSjLT9JnSdfX9KhYnStQoFPPIXD/hhkdNUskkLavthYXFDMYjKbPWnUw610lUSkkoaDA0mJk4N00Df8BCVa1FiZs5wOvTS04deiv0HPGpaWJKriEpJcFhg+GhNJlpzob6/GrqSbE4UdNPCsU8ol/jWKDrYC1RPDuZkIRDhQc9XZ9aP6pcwiGTRPyKMBvqz9Dbnc4Ra6aZjd7quJQsGamjmD5uj1a0bIIQUFlV/HlVSklfT5r+3ukLGos1K6yklMRjJsHhDKMjGTLTsP4pFHOFEjUKxTzi9l5b8cKmFju6pfQORkcKixohRMlBr+i+g1l/nGTCLBqJk4hLgkX6oZgZQghWtdpx5vGt0XVobr1SWqMQWSEys++mps5KOiW5dD5J+8UkfT1pervTnD+ToKcrpYSsYkFR008KxTyi64KqGguD/dPL9Kpp0NBsw+nSyJSxaamn5oqATiJhzmhgG9/3aBnZbYPDmWsSUIr86BZBy2o78bhJNGwgZbbopderI0pM+QWHM/T3zjzTsNUiaL+YzJvvMRQ0MDKSphaVx0axMKi7jUIxz1RWZ392QwOZKXV5fH6d2noLqWS23pM0JXaHhrfiSpkCi4WSUwalnEmFENQ1WPH6dILDGZLJrANpKilL1gqyWATptCRcRsSMipKZW5xODaezfIN7MmHS1zPzdAJuj0Zo1ChaUDMaMUnETZwu5XejmH+UqFEo5hkhBFU1VvyVFiIhg4yRLV7o8V4RLk4XeacXACoCFhLx4gNTRRmOnEII3B49J9/IQF+a4RLJ3ewOwcWzibIKJeYLJVYsHMHhmVtodAvU1lu5dL5w3ptxQkFDiRrFgqBEjUKxQOi6oGIG9Xl8FWPWlQJlFOwOgbdiZgNKoMrCaDBTMBGb26Mx0DfVwlSImfZjOSGlnLBYWW1iQadl4rGZ1fByOAUuj45plrbkAWQMZaFTLAxK1CgUSwxNE6xqs9PbnSISyh2kvD6NukbbjEOpLWO+Gr1d6SkDYEVAx2qFaKS8fZUThbMcMTKS0KhBMmmQSmanfMana3RLVjhWVuXP9zPnlHlITYf6Biv9vRkyGUkiLknEMwwXr6YxgdWqTHSKhWHl3XEUinnGNMYHORNNCDw+DYdTu6ZBTdcFTavspNOSeCzr2+J06VjLSMxWCptNo2W1nWTCJJHI9tnl1tAtomjF8Jz+WaBplQ2bfWUNbsGRDP092ZpeEhitrGO4pREpNHzBQap62xnsy5BMmDQ0zb8zrcerk0wUn4ISGjQ02ejuTCFnWJy9nOlPhWIuUKJGoZhDwiGDns5Ujsl+eCjrL9O0ylZWeHYxrFaBtWJufsZ2h1YyNLgQazc4Vlz0SyRs0Ned9XVKOlwcvfFeIv5qhGkCEqnp2BIxtr30awgO4qsw572mVkXAwvBg8enDltU2gsPGjAWNP6DP+LpRKK4VdeUpFHNEPGbQ3ZHKO4DEYyad7Ulkuc4pi4RCzsuTcbmvzQq1VBnszwoaU9M4dOtDRH2VAEhNQ2pZ8ZKyOTh8y4PEXZ6yQuJnG6tVjIVb51/fuMqGw1E6YzFko/Amo2lQXWuhtqFEdkiFYg5RlhqFYo4YGig+aCXi2YysLvfSMdVXBCx5Q9EnE6iamo4/EZek0ya6Lpal6EmnzQnH7f7GNuKeivwNNQ0DC12rN+M7u38ee3gFt0dnzQYHoyMZolETZFaIVgQsWK0CKctzBnY4s3XGkkkTIbLvVVkMxUKjRI1CMQeYpiQaKW2/D4eMJSVqLJbsk35Xe34LVFWNJWdKJRbNTsmkJuWr0XWors2GtC8XJudtGWhoA2lmnVPyoWn0Na1h24WFETWQ/R6raqxU1UxdJ0S2snupJI9Wm8BiFVisS+f6VSx/ls9dRaFYRJQ7q1Qsidlixe3RaVtnJzhsEAkZSClxujT8lZYcgRaPGXRcSk3Z3jCgb8yZ9mqrzlLFahEIkf3eM1ZbYUEzhmGx4psjX6jZwF9ZOuv11QUyFYrFgLoqFYo5QNOyFgmjhGuCbYaFJRcam02jtl6jtr6w/0R/b/EEgQN9aSr8Opq+ND+DyWi6wOfXGR0xcEVGCVXWIgtlHpQSV3R0UVe6DlRaCI0apJL51XmgyqKcgRWLEnVVKhRzgBCirOmVmSTfWwqkUrnVvPMhJWWVWljsSGDAFiC8Zg2h+kYaLp8pLGjG2BE7j76IxZymZ/MVVfhzC7BaxrIK19Qtz+tWsfRRV6ZCMUdUVlmIhI2CmX/rGqxYrjGke7GSyZQ3/1aq8OZip89exTM1exi2B7ILmsCaTBDo72Kktimr3CarAilpivexJXZpQfo7HXRdUN9ko6ZekkpKhAZ2+8JmRFYoSqFEjUIxR2i6oKXNztBghuBwZsJ/xuHMOmnOd46S+aRcsVaq8OZiZsAe4KeN9yCvGuTTdgcjtU3UdF0gUlFN3OMDwJJMsK7vDLenT6OzdMScrgucrqX7PSlWFkrUKBRziKYLauqsVNdayGRAExRMuGeaEtPM+uMs9dBYm03D7oBkong7t3vpzoDvq9yJFAJZwCl4qL6FWx7/LobVhhQa9ngEXUjERkf2QlAoFLOOEjUKxTwghMBawKc2lTQZGsgQChkwNlvhrdCpqrFgsy3dQd/ntzDQWzyCJjRqUlm99M4xojvpdtUVbWNqOoMNrTR0nJtYJiWkUxK7Y2mIGsOQJOJZE6PDqS1qPyCFApSoUSgWlGTCpP1iMie0W0oIBbPh0i1r7NiXaP2k8cGwGMGRDJXVS+82FLM4S7YRUpJ0uqYuXwK6wDQl/b1pQkFjIj2BEODz69TWW5e8JVGxfFmad0uFYpnQ05UqmKvGNKG3a2qel6VCJlXab2SpOgo7jRLzaoAUAlsinrPMYs0mrVvMSCnpvJxidMTIybckJYyOGHReTi258h6KlYMSNQrFApGImwUjo660kSQTSzBDH4V9h3LbzENH5gBvJkZ9vB9RpOqjME1qei7nLKusti766KHwqEE8Vvi84jGTcGjph+IrlidK1CgUC0QqWZ5YKZQAbbHjKyPj7FLOSnvz0BEEFEwf3Xb6ENb0FUtboMqCP7D4I96CI6UFSzltFIqFQIkahWKBEGX6JZTIuL9o8Xg1HM7C56hbWNL1n+qSQzzc/RQV6UjOcpuRYnfnK2zpP47LreEP6LSusVNbv/itNADpMqYEy5laVCgWgqV7R1EoljhutzZRL6gQQstWUF6KCCFobrXT25UiEs61SjmcgoZm25JPPliXGOSOgZcZsFcCEEiHaIr3YZEmrLIvcO+mRzxmMDyUKcvPaalOGyqWP+rSVCgWCE0XVFZZGBosHPZcWWVZ0pEmui5oarGTTplEoybIbGiww7k0hdo4EjjuW8crlVtJ6I6J5fXxfnzpCIF0eOE6VyZSSuIxk9Fg1ocmPQ3ry1KeNlQsb5b2nUWhWOJU1VqoKOBn4a/M5qpZDlhtGv6ABX+lZckLGoCD/i08V7MnR9AA9Dmq+XHT/YxaPQvUs/KQUtLTmaLjUopQ0JiWoLHZxKIuxqlY2SyPO6ZCsUQRQlDfaKOyyiQ0apBJSyxWga9Cx7ZE89Msd2K6g/2VW/Ouk0IjrVl4ObCN+/v3zXPPymewP0M4NP2oOrsjO6W4lK2HiuWNEjUKxSLAZteorlUiZilwztMCFB7UpdC44FlFamA/Nlk8o/JCYJqSkeGZ9ctmE0veD0qxvFF3UYVCoSiBlJJI2KDjUpLOsA2K5KeBrLCJXzU1tVhIxM1S3S9IJLI0cyYpVg7KUqNQKBRFkFLS250tGQBgiSeQRSw1YxvhMJPz0LvpUyyxXklUJLdikaNEjUKhWFDGo3DGa0W5PTp2x+IxIgdHDEaDBpGKShJOD85oqGgBJyFNWqI92M30PPayPKSUjAzNfEpsOTh5K5Y3StQoFIoFI5U06epI5WRNHujL4HJpNKxa+Dw2UkouGJWcvPtmor7AxHItk8bULVPEjZAmmpRcP3JsvrtaFrGoiXENyYADVWrIUCxu1BWqUCwBYlGDkaEMsWjWmuFyawSqLLjcSze0NpORtF9M5h1kYzGTjktJ2tbYy868PBd026p55cZ7kFeJl3FBI0wDqV35DnzpCHf3v0R1KjjPPS2Paym54Q/oeLzKUqNY3ChRo1AscoYH0wz05U4ZRMImkXCK2nrrkn16Dg5niloNUklJOGzgq1i489tXc11W0Fxdq2IsFbRmGKw/+BwOr5UWd4z6xGApb5sFRS9TA7vcGvH4lWSJgSoLHq+2JMo8KFY2S/NuqFCsEOIxc4qgmUx/bxqna2lm6B0NTlU0SbuTnpb1jFbVgoTeUC83aR04zFSePcwtI1Yvg86qwg2EwLDa0EyDLZFOvOUqhgXE7dURIl20NIfFCs2tNiVgFEsSJWoUikVMcLi0s+nIcIaGJts89GZ2MY3ckXWwrpnj19+D1ATjeWBGaps4L3fyqp7f0JgYmNf+RS3O0o2kScbtwmNbGqJS1wWV1RaGBgoL5erapVF4U6HIx9L4JSoUK5R4rLQPxDWF6C4gVuuVgTPm9nH8hnuQmpad6hFi4i8tdH7RcCfRec774jLKCMkWGvXezJIRAaYhSacKXy+1DVZV10mxpFGiRqFYzJQxVi6N4XQq/sorg2fX6s3Z3C/5xIHQMITOYeeaeewdBFKjBJLBomXULWaademe+evUNSBNScflJKHR/KLG7hBUqJpOiiWOEjUKxSKmnGiTVEoSjVxDnO4C4fPrOJxZETNQvwq0IucqBGe8bZjm/GV/E8CtQ4eyorGAsLlp6ChWuTQ++1DIIBEv/PklE5JwaGmci0JRCCVqFIpFjD9gKcsU09WeIplYWtNQmiZY1WbHX6lj6taS7VN2F6F5HnSb4328qvc3uDOxnOU2I8XtA/vZFjo7r/25FkZHSn92wRnWhFIoFgtq8lShWMTY7BpNq2x0tReP/pEShoeWnsOwpgnqGmw4RYqwtBXN1Ct1nVDain+ec/W3xHp4T/sjdDtrCVvcOIwkq2K96CwtEZlJl/7cMkrTKJY4StQoFIscj1fH6RTEi0wdAIRDBg1N89SpWaYyGSRs85ZuKARzUYAonTLJGGCxgNU61YAtgKZ4/6wfdz6xWCBdIpjOokYExRJHXcIKxRIglSo9kM+08vJiYF20ncveVYUbSIkzGiZgTwOz58yazQOUzokgc7o0auutSzL3TzEqAhbi8eKqRkU+KZY6y+tXq1AsQwxDllWvZwnkfivI6mg3jnS8qDJrvXwCj2f2blmxqEH7peSUkPh4zKT9YpJ4bHk5zXordOz2wtN7NrvAp6KfFEscJWoUikWOkSlvusW2iCpbTxcdk9f0/garkckVNmb2dUPnWW7WLs5aPhgpJb3d6YIzWVJCb3caWSz17hJj3DE7X0Sd26vR0mZHW8A6WwrFbKBsjQrFIkfXyxto3K6lK2oAalIjvLPzUY641nDes4qMZsUbGWHTyFk20oc+i1l7E3FJusSUXiopSSbkRNj5ckC3CJpa7KRTJrExC5XLpWFdIhmRFYpSLBlR8/nPf54f/vCHnDp1CqfTya233srf/u3fsnHjxoXumkIxp+gWgdujEY0Ud5pZDlMHLiPBzeET3Bw+cWWhBrOdYrBYVt3JpFLmsvOtAbDaNCqUkFEsQ5bMVf3000/zkY98hH379vHkk0+STqd58MEHiUajC901hWLOydbjKbw+UKmrp+1poJVp/SrXSqZQKBYHS8ZS89hjj+W8//rXv05tbS2vvPIKd9555wL1av5IalZGrD50TCqTQfR5ztWhWFgcTo3mNhu9nWnSk/KNCAGBKgvVtUvmp7wocLk1NG3CZScvup6dmlkqGIZEymy/l0otKoVitlmyd8LR0VEAKisrF7gnc0tSs/JC1S7OelsxRXZ6wZFJsCt4ih2jp5ds3R/F9HG5dFav14jHTFJJiaaD26OjaVkfEdM0sdm1nEKRivxomqC61kp/b+EQ5+paK2IJOM6GQwbDg+mJEggWC/irLFRWWZS4Uaw4lqSoMU2Tj3/849x2221s27atYLtkMkkyeaXSbigUmo/uzRopYeEnjfcRtHmR4soTY8LiYF/1LsIWF7cPHVzAHirmGyEELreOy52N4AmOGAwNpDEmZYJ1ezTqGqxqOqoE/kodKSWD/Zmc0k5CQHWtJafg5mJleDDNQF9uGuBMBgb7MsQiJs2tNiVsFCuKJXnX+8hHPsKxY8f4zne+U7Td5z//eSoqKib+Vq0qktxrEXKsYj1Bmy9H0EzmuH8Dgzb//HZKsWgYGsjQ35MraACiEZPLF5M501SKqQghqKy2snajg7pGK1U1Fuoas+8rq0vXolpoUklziqCZTCxqllXvSXHtTPeXlhY6GbH0HfsXI4v/UeQqPvrRj/LII4/wzDPP0NzcXLTtpz/9aT7xiU9MvA+FQktK2JzwrS36YxHS5JRvDbcPHpizPiQ1K6e9q+ly1iIRNCQG2RS+gNNIlt5YMWek0yZDA4UHNCMDwwNp6hqXVi2o+SARN0nETUCiWzRSSRMps342Tpe2ZCwb5QiWkeHMkrA4LRYkkNDtmAicRhKtyB24117FEf9G2l2NmEKjKjnC9tEzrI9czusWIIGznlaO+DcyZA8AUJUcZmfwNOsi7RPbhCxuTvnWELR6sZlp1kQ6WBXvVa4GZbJkrnYpJR/72Mf40Y9+xFNPPcXq1atLbmO327Hb7fPQu9lHAlGLq3iBPwRhi3vO+tDjqObRhjtJiyuXSYergVcCW3iw73laYj1zdmxFcULB0gPaaNCgtl4uCb+Q+SCVNOnuTJFM5B+ohgbAZhM0tdiw2Re/ETuZLB2WnkpKMmmJRflZleScp4WD/k0MjwkOVybOttGz7AienlK89Iynlb21NyGQE5b0IbufvXU30+ms456Bl3JEiAReqNrFUf/GnOSSQzY/v667hUF7gFuGDnPQv4mXKndk94tAIDntW0NtYohX9zyDwyxe2FaxhETNRz7yEb71rW/xk5/8BK/XS29vLwAVFRU4nc4F7t3sIwCbmSalF37SFkgc5txYTKK6g1803Ikh9CnCykDn8frbeHvHY1SkI2XvMyUsnPat5rS3jYTuwJuOsDl0gbWRjiVX8XihKWdqSUowDLAs/vG5LIyMJBIxMM2s+HC5y7eqZNKSyxeSRaOdIFtjq/1ikrZ1DiyWxS0Eys3+234xSetauwpPL8L+wFZeqdzGZOeqmO7gpcrtnPG08mDvswQy2XtdVHfyVO2NADmuAeOvz/pW0xzvY0Pk8sS6bmdtVtAATHYnGHt9xL8J3TQ4WLk1u68xSTT+f8Ae4Mm6W3ldz1OzeNbLkyUjar785S8DcPfdd+cs/9rXvsb73ve++e/QPLAhfInjFesK+tRIobEu3D4nxz7pW4sh9PzHFgIpBcd867ltzFE5ZHHT66hBCmiID+DL5OYPiupOftx0HxGLa2IfMd1Br7OWfVU7MYSGIXQqU6NsDZ1jffhyUdPvSqfcAUpbBtP2UkoGetOMDOdap6xWQX2TFZe79EkODaanCJqo189QXTOmpuMZHaayvxNNZutsjY5kqKpZ3H41Hp9GOFTaYpdOS4LDi/98FophW0VW0EDuA9zY66DNx3+2PszqSAe3DbzCMzV7smKjgKAW0uRoxYYcUXPMty5roSlwL0eaHPOvz4qqPPuVQqPbVceAPUBNcmRmJ7pCWDKiZjnVYCmXHaOnOeNtI61ZpogLIU3qEoM0x3vn5NiXXY0FxRRkf2SX3Y3sGTnO3tobaXc1XvkxSklLrJu7+1/CaaaI6g6+3/wgCd2e84Md339cd0wsH7AHeKr2Ji64mnio7/mCwsZAwxAaVplZkXPNvgqd4cHCPjUAXp+2LGr59PWk8/qPpNOSzsspWlbbS2b9nbx9xmLlxO47Ga5fBaaJAKSmYYtH2br/KSpGBhgNGoteBHi9OoO2TMlyD5A9/8V+PgvF/sDWgmICmFh+0d3ERXcTpbJbS6ExZPfnLOty1hUWNABCIy2K+78JaXLZ1ahETQmWjKhZiXgzMV7f/WuerLuVUZsPIc2JJ4TWaDf39L84ZwO6UewHOEZG6Pys8R5GbL4pTzgdrgZ+2PwAO4dPsb9qG0mLo/COcrbNHrfd3cRPGu/ljsFXqEyNToibAXuAA/4tXHY3IYXAYSTYMnqencFT2GTxQX45YXdoeCs0wqP551OEYFkMYqlU8QgeKWFoIE1TS3HfufFnIgkcvek+RgO12QXaFdmccjg5fMtD7HnmZ/jio9fe+TlGaIJVrTYunktS6pkvU2ZR1OVEQrNxyd1EUrPhzURojfZMmeaO6XYuuZuK+i5OUMY9cRxt0hcyZKsgXcSNoFwEZN0BFEVRomaRU5Ua5R0dj9LtqGXQHkDDpCXWMy1flplQlxwqGk4upImJYNhWUdBcGrF6eK7u+pl1QAj6ndX8YNVDODJxdo6eIZAa5fH628f2nz1mQndwMLCZS+5G3tD16xUlbBoabWjaVCuG1SpoaLZiH6vaLaUknZaYZnbdUvKtKMchOhI2MQxZ1nmNVDcwWlWff6XQkBp0rN3KdWdemG5XFwSrTcPtEUTCxUXLSnIUlsD+wDYOBTZhok0489qNJHcO7GdNtHOi7Snvmgm/ldlCSJOWWHfOMYpagqD0eshGWKWUlaYUStQsAQTQlOinKdE/b8fcOnqOU761BddLoZG8ajpprkhYnLxYuSPHUnV1X0ZsFeyv3MatQ4fmvD+LBaEJ6httVNdkHWilCTZ7rgNtOGQw1J8mmbwy6HkrNGrrbEtioDOM8iwMZglRI0R23OhvWo0wTaRWwE9N0+hvXkPF4Msz6u9C4A9YiYSLR8X4AyvnCf/lyu0c9G+euE+Mi5akZuPJult5dc8z+DIRJIJL7sbZPbjMRi3tDJ6eWBS2lhGhWuo+KiUCSaejDn8qTHUqeG39XMYoUaPIS3UqyC2DB3mh+rqsmBiz2Ey8LuPJYlYRAlnE9CqFxinfGm4cPoJFrqxIKotV4A9M/SmPjmTo7Z5aBiA8ahKPJmhd41j0wqbckg96iUgln19ndMQgY7VNWPkKYeoWPBVL59bo8mi4PBqxAlXcrTZBRZ7rYzET1+2c9q6mz16FhsmqWC9rI+1YZXHLXVyzcci/Kf+9aUzZPt5wB+ak+9ns3sck9/S/RF1yaGKJw0hOhGgX3qz0/VQKjTO+1ZyuWMvNg4fYOXq6aPuVytK60hXzyo7RM1Slghyu2Ei3sw4JVKQjjNjzTznNOSV++GnNSlR3UjEp8mrQ5qfd1YAhNGqSI7TEejCFxjlPCxfdzaQ1C5WpUTaHzlOVWvx+FOWSTpt5Bc04mQwM9KdpaFrcyfl8FZaiWXOzbUo7RFdWWwgFDZzRMELKwsJGSlxGgiU0Q4cQgqZVNvp704wGjZz0th6vRl2jbUlNOV50N/HL2luQYtzfSXLBvYqXKnfwcM/TVBWxUlx0NxcXD0JgTlo/2w9oD/U+S9tV+bvWRS5z2rem+Ialjj9udRoTY/uqd1GVCtIc75txX5crStQoitIU76cpfmXa67mq6xi1eSeedOaVMm48lrEnuYRm45d1t9DlqkfI7G3MFBqOTByNbA4KkCA0eh3VHK9Yz/XDR9kzcmJOT2E+kDIbFVSKUNCgrkEu6ggpi1VQXWthsD+/sNH0bOHJUths2Srnia6zdKzfXrCdQLIldG7G/V0otLGpyJo6STyWzZDscAqs1qWVpGjIVsGTdbdeNc2c/R/X7fyk6V7eefkRXAWS0CV1e2mryNXM4gNaIB2esqwp3k9jrI8eZ81UH8ViYd5FENLksH+jEjV5WFpXvGLB0ZCLM3uMNKlKjuA2EpgIftFwJ93ObISLFNqECEvojqygEWLiZjJ+o9lfuZ1znqVTRqMQ41W8yyGdXvxTdZXVFuoarOhXPYK53Bqtq+1lF+50uXS2NaXY1n0ku+CqkCEhTQKpENuDZ2aj2wuCrgs8Xh2vT19yggbgSMWG7IsC00dpzcq3W19Ll6M27/beTLRoKoqiTL4epptCREqqE8N5AzgE8KreZ1kd6czuV0rE2P596QgWc/rBDVJodDtrF+e9eIFRlhrFtGiO9XBkPDPmbHB1eeSS7Qs82QiN3SPHAehw1TPgqMq/fdEIBJND/s2si3SU7scippyIoXESccliryQihMBfaaEioJOImxMZhWdShVzTBLfGT1LZn+RAYDMRqwcA3cywMXyRG4ePrqgIusXGZXdzSVGSERYebbiTt3Q+PsUy0hbtwmqkSWuWaVtgBBLdNDC5Mi1VlkCSWbvQzcOHCzaxygwP9L9AaPgIHWPT4dXJERoSA+yr2snRig3TFmMmgqdqboSxhKfl+BytBJSoUUyL5ngfgeQoQZt3ej/CfPPWY8tuHDrMBfcqBh2VV0TOVW2FNPGmoziNOH3O2qyDX3YNILll6BBrol0AnPe05Dg3l43QGLIHSGi2JV1jpdyIIaBsi85iQAiB03XtUTwC2By+wKbwBYJWL4bQ8aUjSszMIiaCdlcDQ3Y/FtOgNdaFv4w0FEZZ+WKyfjGH/Zu4eyA3Ss0iDW4ffIW9dTdPveeU8J1xZeL8VvsjAIxYvRz2b+KspxVT03O3HX899t9lxLlzYH/ONH0hfJkoW6+a3rx++Bi9jmr67VUT51eyv1ICgrPeVgDOeNrYV7WTV/X8hvpJTsorESVqVhAGGiGrB4GJLx2dURkCAby69xkeabybkNVbtpOdxUzjMpKEbN6JZZ5MjJuGj7Au0s51wVP02yu55GrkpG8NCYtzQrhIoVGTHObB3udwGQl6HDVc8KwipVnxp0JsDF/EbSQm9pvSrNeUe8JcIlWaC7HYI5oWEhNBxOJCIPFkYnl9IBTXRrejhl/V3ULM4pwo3rivehfeVJitofNsCl/AbuZ3Yq9OjtDnqC75QCKFxnnPqimiBmBD5DI2M82LVTsI2iqurCjyuxbSZP2ksgaBdJi7B17mroGXMdGQAoZtfgA86SjdrlqSmh1vOkJzvO+aSrpYpcHrup/iuG8dR/wbiFlcpe+rV4WrQzZk/ZHGu3ln+y/wGHEAglYvQ7YKLNKgMT6AdQUIdyVqVgAZofFKYCsnfOsmCmS601F2BU+zNXR22sO/NxPjbR2PccG9igueVfTbK3NKHeQgJVYzzW9f+ilWDEasXsJWD3YjSW1yOOfYtclhapPD3DByjC5nLX2OaoSUNMf7qE0OT7RrTAzQmBgo2D9fOjJ9Z8GxvrqNOE5jboqEzhcVfgvB4fLM0C730vO7mAkGGocCmzjmW09iLLu1LxVmV/AUm8IXVmSpjblgyFbBzxvuuhJIMEmchK0e9lXt5KXK7dwx+AqbwhenbL999Cy9zvz+MldjiMLDV1usm9ZYNyO2ChKaDVcmzmMNdxCyevKWnLGaGbaNTnUQF5DNQizJuQfN9hS1RRrsGD3NKd8aYkVrRBUv52AIC99f9SD39z7Pgcpt9Ez6LC1mhu2jp7l++PiyrqunRM0yx0DjFw130XvV00/U4uK5mt0EbV5uHzww7f1apMmGyGU2RC4T1+38qOl+IhZXzjHGo44e6HsBK9lBNpAOl3w6FkBzvJ/mMsy5+dgcOn+lIm4+itwYto2eKTnAJTUrZ7xtnPO0kNRsBFIhNofOsyreW9bgaCJI6jYsZmZO5sAdTg2fXy/pWzNe6Xq5YyJ4vP42OlwNOd97yOrhmdobCNq83DJU2B9CUT4H/JuzgqZQnhjAROPp2htxGEnaJmXeBVgd7WTT6HlOVawtOf3iK+M+UjkpTcPrup/i8frbGHBU5ViBPZkYD/U+h3vMurFQ9DqqCdp8pRuWsOIkNTs/b7wHcZVwyWgWDvq3ENcd3DWw/1q7u2hRomaZc9rbRo+jZuqPYOz98Yr1rA9fom7SU8h0cRpJ3tT5JAcDWzjlW0Nas44Vtexh98iJnCec+SCQDnPdyAkOBrbkmVc3AZHrczP2ZNQa7WZHiciXkMXNT5vuJao7swuEIGT1cMnTzLrwJe7pf6ngU1BSs3IgsIVT3jVZi9lY4c89c/AZ1TdasVhgeDC/sLFYoKnVNpF5eCmRTJiEQ8aEw7CvQkcrkofljLdtiqABJt4f8W9ibaRj3q/TpUJa6HS4GkjodjyZKM2x/NMtBoILnlVl5VwR0mR/5dYpokYAdw7upyId5sXqXUV3k8+yUgy3EedNXb+kz15Fp6seiaAuOURzrHdRWC6GbP6yp52KMubvk3cKTwhO+daybfTsssrLNRklapY5JyrWFV0vpMlJ31rqBq7thu40U9w6dIibhg6T1G1Y58gKUS43DB/Fm45yMLCZ8FiEi8XMsCl0gQ2hi5yuWMN5TwsZoeNPhdgWOsv68OWiNzcJPNZwx5WQ8PHlYzePc55WqpPBvJk+E5qNHzfdl2v+Hiv82eFq4KHeZ6lJDqNJOStOykIIaupsVFZnC0JGQgYZA3Q9m9DO59eXVEI2ANOUdHemiIZzw9D7e9PUN1nxFcgCfMK3luy3l/98s7+BNdRe429guSGBoxUb2F+5beJBBSFwZeLcMbB/iiDJaJayc65kK1lXEra48GZiOesEsGv0NKbQeLlqR16H34Z4P5tD56d9TgKoTw4tSmdavcxM6GUFQZTwHzrjbVu21kklapY5o1ZP0QtcCo1hWwXn3c2YQqc6OUwgHUYC3Y5aLrmbyGg6VclR1kcuFXTwG0dH4loEPimTI1xGrZ6JCJdxoVUzeGDa027dzlpGJjse5uGIfyPbR89MEUcvV27PO58/Hjr6WP0dE9+TPzXKnuHjrIte+7y9rmtUVmtUVi/9it35BA1kx7yezjS6LnB79KvWSUYsvqKD7XjtMEUuRys28EL1dVcWjF2fMd3B4/W38+qeZ2iJ906stpnpaUcdZor4xewOnsSXiXDQv4Vhux8Ah5Fg6+g5rhs5OaXi9lKnJdYzFstZGJuRJKVfew6G2LileRmiRM0yx2ZmyGhFBjQpGbBX8sv62yYW1cYGyOgWhu2BK9l4vYIXqnZy09Bhts/AuXihEFBWKGk5dDtqi9+0hSBmcRKyunOOmRY6p71tRbebTNBWwa/qb2Vk+Bg3jOXeWekkE2ZeQTOZof70FFETChpomTRYiv0GTGxGcbG+0kgJCy9XFsi8PDa9sa9qJ6s6r/iRjfuwDNn8ZU2T6KaB+yorzdWsi3SwNtJBXHdgCA13Jr4opormArcRZ334Eme9bQXLeOweOUlct3M4sPmayju4JkWLLjeWv5fgCmd9+NKknC55EFOrXvc7qyfCFyey8QqBqem8ULObb7e8hkuuWa5uu6zI/TwjFjeGNv3nhwOV2xi2luE4uAIIh/JPZZqaxkhVPUO1TQzjJpO5MuBJKRkazFDbdQHMYr8BjbXR9tnu8pLmsrspO51UCCEYsfunWLhuHjxU1kCbDaG+VFZuIEF2EPZmYstW0Ixzx+ArtIxN6wlpTvwBbA+eZsfoaW4aPsL24OkZCxopNDaEL81WlxcdylKzzNk2epaTvrWkNUv5ZuESP5awxcPj9bdzT/+LbJiU22G5U58YQIqtRds4Mwm8V1mGLDPNDSElR/wb8+biWGmYZu5gJoGOtVtpX7+DjG3MHC8lHdEe7h56BW8mhpGBdErSfOEkPS0bMLCAdlU4r2niSkZYu8SzSM82cd1evPDnpHaTaU70sz50kbPetiKRSyaeTIwbh4/OUm+XDxZp8FDvs/TZqzjnbSWu2/Gmo2wMX8yJGr1l6BARi4uL7ubsgskJ+wBNmkgh8tSakmwIXypaFHSpoyw1yxyPEed13XtxZ7Lhitok5T/t+ibjjP2Anq3ZQ1pce4bXpUJzvI+KVLiw5UtKto2eQb/qadKTiRFIBqf/eQtBr6N6Zp1dZtiuKolwYcv1XNh6wxVBAyAEPe56ftT0ABHdOfEtOOJRdr7wOLZU1uQuTAMxZrlxhYPcduzJiUKoiiyeTKykoBlvdzX3DLzETcNHcOTxrdPNDFtD53lT5y+XfD6ouWLcmfn2wQM80PcCNw8fmZIGQwD3973AjcNHcE6aSvJkYtw6dJC3dj5GbSLX8V03DXYGT3HXMn9IUpaaFUB1Ksi72n9Op6uePnsVGibtzgb6ndcwYApBGgsX3c0rxlojgId6f8PPGu+98oQqroSHt0U72RU8lXe760eO8+Qkv6WymFT4bqXjrdDp700jJcRdXjrWbcvbTgqNhG7jYGAztw+8gsUCmQz4gkPc/OT3GKpvIRSoyRav7O/GP9RLVbOVlXYrNNC47G4kbHFjN1O0Rbtyou5aYt3YjBQpzZrX4iKkSW2RAo67gqfYHjzNsM2PKTRcmRgIgdNIYCkzykdRHA3JdcFT7AyeJmxxIcgW9Bz/tt7Y/SuGbRUM2SrQpUFTvL9koMdyYGX9klcwGtm8MS2xHgAiFhcDjsqZV7Qd22doLFx6pRBIh3lbx6Oc8q3lrLd1olTDltB5Vkc7CzpQr4l2ctvAKzxffR3j9aokU/2ZchCClnjPHJzF0kPXBfWNVnq60vSuWpv1kdHyX7tSaJzxrua2wYMEqiwM9GWn/zQpqem5TE3P5Un7Ba93+VsbR6w+jleso8dRQ1qzENMdGJolK8gR/KZmD7tGTnL9yHEE2eSatw0eyFtDKevnIbll6GDRY+pIalIjc3xmCg1JRSaad11lajQnAeFKQImaFcqG8CVO+dYWblCGZ72JwD7p6W7IVsFJ31pGrR7sRpq10XZao93LzrnPaaa4LniS64Inp7XdttA51kQ7OONdzajVQ4ejjqjVXbC8hECyZ/hYyf2aCDpc9VxwryKjZfPubApfnJL/Y6nj81vQLYKzHk/J0NeMZiGlWQlUmcRjJpE8kVOaBk0tdoS2VGL5ZsYp72qerrkhWzpkIuFk9tMbf2+ic6Aya/0aj7jbELmMRRrsq9o5kesJoCoZ5PbBA9eUsFOhmCuUqFmh1CcGWR3pyDqaFUppXkLYCGBNpAMJ7KvayRH/pompGCFNzntbqEqO8HD3UziXcNXr2cRlJCemqMIWF99vejCbXTjP53xP/4vYSvh6xHQ7v2i4i6Gx8HuJQLglBwNbuWXoINtHz87JeSwUbo9OtStNdwkdokkDq5lBCEHjKhvhkMHIUIZUUqJp2QSE/kodq215uxX22yt5uuYGECK3FlqB3/WhwGa2j56dmIpaE+1kdbSTAXtlNqNwOkplOjQfXVcoZsTy/kUrCiKAXSMnZ56SW0q2jp7FbSQ46VvLEf+m7OKxJ7/x/8O2Cp6sm6YvyQrBm4nxts7Hc8PupaQmMcQbu37J+kjxMGMJPFZ/B8NjYbVyLPReCg0pBM9X716WoffrI5eLTpsKabIu3D6RnE0Iga/CQusaB+s3O1m70UlNvXXZCxqAoxXrp9QAKoaJxiV3U84yQbaYY0usRwmaeSKiO7nkauSyq4FksTxjiikoS80KZjxL57QYM1tvGz3LLUOHkMBBf+FEUFJo9LhqGbAF1Px6HjxGnHsHXuKOwVeI6w7sZqpsZ74eRw0DjqrCDaTk2erdNHb0l5UPZKlQlRotGDYspIlFGlwXPLEwnVtkdDrrp+U3J5AkZiFjrWJmxHU7z1Tv4dIkC7puGmwOnefmocPLLovyXLD8H1UUBSm31kgOY8n6WmPdmELQZ68iUsgvZHwTadLhqr+Gni5/rNLAl4lOKzrhsruxZGLFqNXND5sfIK7Zrql/UkqiEYOu9iQXzia4dD7B0GAaI7Mw/lJ3DbzMttGzaFedvz8d5nVdv561LNJLnmm6C0mh4U3ndzpVXBuS4n5gKWHhJ433ctndlHM/NTSdYxXreaL+1mXmnTg3KEvNCqYp3jvtWi0ASJPnqncxavWVta0AjGuIslLkxxB6SYdZgJDVw7PVe3ig/wWSmpVOZx0ZzUIgFaImOVxy3JNS0tudJhTM9e9JJjKMDGZY1WbH7pjf71dHctvQQXYPH+OMVs9lez0jFTWMuCr4UdMDtMa62Bk8vSgLF84nDfGBwn5zVyMlNjNNa6xr7ju2guh01nLYv4luZx0SqE0Ms330DGuiHTm/vRMV6xi1egv6OLa7m+hy1tEc75uvri9JlKhZwbiMJBvDFzntXVNWoq0rCILWirLTdJtCo1ZFSsw61ckRzDIexaXQuOhp5lnjOk751mJoV0KYK5NB7ul/keoiGUaDw8YUQTOOYUBne5I16x2IGaZtnymmKenviHJ2cxND9S0Ty6WmccnVxGV3M/f2vTArhUGXKttHz3DRs6p0w7Fp5TsG96s8MrPI0Yr1PF+9G6Q5UVS1z1FJn/NWtgXPcOvQwYlf8EnvmqL7EtLklHe1EjUlUI/PK5zbBg+yaix3TdmZhvPUiyrYVJq4MzFWxXpLN1ZMi7WRdqwyU1amYik0jleszxE0ACM2Hz9tupcRqzf/dlIyMlTcHyeTpmSxyblgsD/D+ep1WUFz9TWpZRMJ7K27ibi2cn1EGhKD3DR4KPumyHViNdM81Pss61S5iFlj2OrLChrIrRI/9vqYfwPtroaJxTGLs+h9VQqNiMU1J31dTihLzQrHIg1e1fsbehw1nPG2EdcdJHQb/faqmRVMm+QwPO60+WDvc8suV81iwCoN7u97gUfrb6cs54kCjtwZ4KXKbdQkg/Q4axASmuJ9bAxfxJJMkk6X/u6GBtNYrAKHc36ek0xTEhzO0LlzS+FGQmBKjcca7uCG4SM0xfvnvbq8aUpCowbRiIE0weHU8AcsWKzz15Ndo6exm2l+U7Mnq2tyEulJ3JkYb+58QqVdmGX2Ve0q3kCaHKtYT+vYQ6XTSBAWhf0ThTRxG/FZ7uXyQ4kaBQJoTAzQmBgAssncflV7Mxe8LVd8biY/5ZUIAxfSxGamWRdpZ0fwNL4C2S4V105LrIdX9/yGRxvuLBmCX2i9FBqX3Ku47F41IT07XPXsr9zKHd37MPRL6EbxfDmJuOTyhSROl0bTKhu6ZW4H7UTCxEAj7qko2bbfXsnPG++hLj7Aq3t/M2+p4pMJk47LSYxJhq5oxGRoIENDkxWff/5uv5vDF6hPDHDIv4lznlZMTcduJNkSOs/O4KkVkT5/PpFAl7O2eCOh0W+vnHi7KXSR/ZXbCj7+Lffq2rOFEjWKKWhI7u9/gcuRy5zwrWXEVoHdTOFLR65UhS3CG7p+pbKNziMt8V7WRS5z3tOS33G7nPpRYmo2kwwW9jbfAU23UdN9mbYzh3GHg0V3E49lB/LWNfa59bGRWStDyczXk9b1O6p4su5WXtvz9Nz1awzTlHRcSlJIC/Z0pbHaNJyu+fMACKTD3DPwMncPvExG6FikMe+Wq5XCoC2AqZUuvzE5IeKW0DlO+tYQtTin/I6FNKmPD6hp/DJQokaRFwG0xbppi3VPLIvpDi65m3Izk05GSpxGgpqkykcz39w58ApRi4seZ21OVmcpNCrSoWxUxXSHsHFBIDQGGloZqlvFrucfwxccLLpZMiGJRkw8c1hTyeHQ0ISksr+L4ZrGgnWgJiOFRpernkGbv6hj9GwQChoFBc04I0NpnK759/cRZKcuFXNHUi8jhYKUOXWZHGaKN3T9ir21N9HtqptYLqTJ+vBlbh98RU3jl4ESNYqycRkJNoUucNK3tmDY4e6RE+qHtwBYZYbXdj9Fh6ueM942oroTbybGxvAFfOkI32557bUdQNMwgZO77+DGX/+opDwKjxpzKmo0XeAP6LScPcpwbVNZtcogO0BccjfNuaiJREqLhnz1qBTLg7Jy/QjB+vDlnEUeI87rep4iaPXSb69EQ9IY78dlJOaop8sPJWoU0+K2wYOkNSvnvK05id8kWUGzNXRuAXu3stGQtMZ6JhwPJ7MreIpDgc1TNypTDGQPkPVhOXD7a2g9e4SqvsJVyQ1z7oVtVa2F0bN9bDz0HGd23opE5kaZ5GHeciaVcfrlzAoqFi89jmqOVGyk01WPBOoSQ2wfPUNbrJuKTIT6+AC9jqr81+RYTqDN4Qt59+1Ph/Gnw3N7AssUJWoU00LH5L7+fewKnuSsp5WEbsebibIhfGnZVYVeTtw4fAS7meKgf3O2gOYYdjNJSrNNKwFjOFDNsZvup/7yGTYefj6vsNF1GB1JY0qB261hs8++kEjEJaYBDR3nqOzvoqttI+3rdxSdijKFRtUcW2kgG+UUjRS3xDicyqNlMWMgOO9p4aRvDWGLG6eRZEPkEhtDFznnbeU31XtyKp/3OGvodtWxa+QkNw0f4bbBA/y46T5MyP19janZu/tfUlbtOUCJGsWMqEqNUjV8ZKG7oSgTQdZasz14hh5nDWlhIZAeJaY7+VnTvdPcWfYG3duyHu/oEE2XTk9pEgqahIJXBnWrFRpX2XA4Z29KanTkSliRPRlnzelDmBYrnas35xc20sRuplkdmfuMuRUBnaGB3Pw+CaebcEUVmmlQMdxPoLLAxooFJy10Hm24M8dHLWpxMWgPcLhiI1GLa0rl83HhciiwmcZ4P6vivbyx61e8ULUrx0emKhXkpqEjrIorp9+5QIkaxaJjcir/yuSoKoQ5i+iYORlJ/ekIu4ePcaByW07W03LpWLuVxkunS/rYpNNw+UKKtrWzV1IhlZr6lNt2+hAj1fVEfYGccxHSRCC5v+/5eSkKaLVq1DdZ6e1Kk7Q7Ob3zVobrrpQr0IwM20JnuXH4KLp6Wl90vFS5g15HNTDJyjL23UVLJMAT0uRoxXpWxXupTgV5Xc9ThC0uIhYXDiNJQE0rzSlK1CgWDSaCF6t2cMy3Piccsio5zL39L01ECkigz1E9Nv1lw5OJsSl0Qd0sZsgNI8epSw5xtGIjXY4aZBmhqAAIQcLtI21zYEslEKK0n0jn5SRrNsxOSQVdn1r5ypJJc92zj9K5divdbRtJOVxo0mR1pIPrgqdmfepJyuwUmCQ75Tb5vCr8FkynnZ+tfhVxuyvHd8nULRzxbyJqcXFf/z4VWr2ISAkLJ31rCk/Jlrh2pdDod1TlLPNmYmp6vgxu+bcdE6/v+cHtOesyyRicfKLkPpSoUSwanq65gTPetik3jWGbn5803stbOp/AaSR4su5WOq6qUH3Ev4kdwdPcPHRIDRAzoCXWS0usFwnsD2zjQGBSpt4SN/GWNhtOM5t8r5SoyWSywqa59drz2PgqdGLRqVYXi5Gh7cxhWs8cxl9np7Zan3XfBSmzmYKHBzOkktl9W62CQJUFf6U+cW7n6jeTcLjyW8CE4Ly3lW2jZ1d84c3FxIA9gKGVGBpLONhfXT1ekeXWo5/k7j8tkhX5B9d+DCVqFIuCYVsFZ3yr866TQiOtWTgY2IwhdDpd9RPLJ3PEvxF3JsaO0TNz3t/ligBuGDnG5tB59lXt4Ly3rXBjKalIh/FZ0yAFZpn38VhUEhw2CFRd2+3HW6EzNJghnWcaCsCiQ7VfzIkz5mB/huHBXJ+ZdFrS35smHjdoaLIhhOBUsSd+slMVp32rqR9QomYxkBaW0uUNSiCkSVu0u3TDZcR3v/LunPeHf+rP37CYoJkllKhRLArOeFqvlGTIgxQaZ7yrs1WpizwhHfRvZuvoWeWncI14jDj39L9Er6OGWJ4MpwAIwa7gqaxlTIiypp/G6e9NE4sZ1NbbsM6wDpKmCVra7HR1JEnEcw9sswkaW2xY5qBcQzxmThE0kwmPmnh9Jl6fTkx3FN2XFBpR3TnbXVTMkL21NzJk95duOH6xX30vGvsBbAudnf3OLQC3Hv3kxOuiFpafzkNnykSJGsWiIG4pfvOHbDhuqVEzYXEwaK+krkxzvolgxObDFBoVqTA2Wbwi9UpCR/Kanmf4WeM9JPSxzLdjtb2k0NgaPMPG8MWJ9t4KLSfiqRSRkEkilqB1jWPGBR4tVkHrGgeJuEl0LOGd05UtPzBXZRr6e0sXfhwZzuD16TiMJIki17aQpkqstkgYtXi46FlVuqE0qU4GCVk9pDRrdpkQCCkRmNzX90JOpuDFxq5XZ3C+LVs9/ODqdXzif9QXbjwPlpXZRokaxaLAlYkXLr8wTplmgEwZETwSOOFby8HAloloBt002BC+xE3Dh1WBvzEq0yHe0fEop72rOe9pIa1ZqEwG2Ro6R0NiIOcbq66xEgomp7X/TCZb4buuoYy08kVwOLV5qRAeCRtTrEL5SCWy4m5T+CKH/RuLWiBVkcLFQbu7oaxklJ5MlFf3PoMuTU57V9PprEMKQX1ikE2hC7gXgUj9s4c/XLzBLPiuLFaUqFEsCjaGL3FosnNqIcp4+jbKiN55qXJ79niThJKh6ZzyrabXUc0bu36prDZjOMwUO0dPs3N0aj6ayVhtGq1rbLRfTE0rW+7oiEFtvZzbApizxGB/eWJXaNlz2T56mjPeNuK6PU+RQsmqWDcNiYFZ76di+hhCzybTK/FwdXf/y7iMrHjfMXpmXn34HHvfzL+fyVr+CvqtrHCUqFEsCvzpMBYjRaZYIbhC89iTkZJLrmZailSzHbF6rwioq/YlhUbQ5uWofwN7Rk5M5xQUgMOps3ajnQtnk5hl1kyUEgwDLIv8bpROmSQT5ak1ny8rrF1GcqJIYa+zZmK9kCabQhe4deigitYrQburgSMVG+h11ACSpng/O0ZP0xTvn9XjVCVHSmbW1qQx63XDbvm3HYgbHgDgwODF4tNB/2NWD70sWeS3EcVKoinez2V3Y8EEcMUciScTK+Gfc8q3prhTMoITvnUTokYCPY4aRq1erGaaVfFeNT1VBF3XaF1jp/NyqmBk0tWUUWS7bExTkoibSAl2uzZjf53xfaXT2Wd3cxr1rPyVV6yFvkyUN3T/mmGrj0F7JRoGTbF+nOb0pupWIi8HtnKgclvO77XDVU+7u5FbBg/OqpWkOd6HJx0hanHlvTcIabIufLns3/6uV1+x9L5G+4PCDX8A/GDcd6WIoFGUhRI1ikXDttA5LnuaC66XQsNqpEgXseYIJK5Mcee2sMVd3MQsBDGLEwPBgL2SvbU3EbJ5J1brZoadwdNcP3JMPWUXwGbTWL3OTnA4Q39v8Wk8j09D0679k5RSMjyYDbWeHF7u8WrUNdimJW5MMxueHQoaE1Npepl3y6pqC1bb1EGxMh2iMh0quw8rnW5HTTbTNbnpG8Zfv1B9HY3x/lmznAjggb4X+FnjPRhXHVNIE186wi1Dh3O2Kem7oph3lKhRLBqa4n1sGT3LiYr1udNMY6+3Bc+gywxH/JuKOl5OjsjJh91Ml5w7180MQzY/P2u8B/OqKSpDs3AgsIWMZuGWoUPTOseVhBCCQJWVeMwkHMofFSUEVNVkI0ikzFpYImET05TYHRq+Cr1swdPfmyY4PHXOKxI2SSTGoqzKCPFOJk0un5+aSNAow8VK06CyRt1WZ4NjFeuLWlSFNDlesY67BvbP2jFrk8P89Zeb+Pdv93D6RYmRFhi6IOx3c7myiiM7fnfWjqWYG9SvT7FoEMDtgweoSY5wxL+REVsFAIFUiJ2jp9gQvkRCt3PO20ZMd0y92UnJ2kg7tcnhosdZG2nnlG9N4X5Ik/WRy+yv3IYUomA22CMVG9gePI3HWHphj/NJfZMNTUszGswVHBYrNDTbcDg0jIykqz1JPCeyyGCgN01Dsw2Pt7jzdzJh5hU042TSMDKUoabOWnQ/6VR+QVMu2XNV9rvpMmjzc6xiPV3OWgTQHOujx1FddLpZCo0+e3XZxyiWgj+H/50BamCNzM49C8oKUFAsDpSoUSwqBNkw2I3hixM5ICbPYTvHHC+frrmBLteV+WfdzLA1dI4bh46UnBJqivfREO+nN89NU0gTXZpsGr3Aj5vvL3ozE0jOeVvZFTw17fNcSWiaoL7JRlWtJBo2ME2wOwQudzaXjJSSzvbcBHoZi5Wkw4UlnaKrPU7LGjvOIiHbVwumfASHM1TXWgpGWUkpab9YnqCx2rJCabyt06VRXWvB5Z69KuQrhZPeNTxTc33Wejr2ezzlc5VO8QDoMvd7LzodNN0wZiFQ88tLDyVqFIsSAQUd8ryZGK/teZpRi4chux9NmjQkBsp24BPAq3p+w6/rbuayuwkhJYzdUN2ZOA/0PY9Npko+nQkk8fGkdIqSWK0Cf+XUW04sak4ImoTDxcXNu+lvWj1RWNM33E+8/TC7KGyBy6RLKxHTLB48FxzJkCkzit9i0WhbayOTlmi6mJPMxYuRlLDQ7m4kodnwZqI0x3qvKXv3oM3PMzXXgxA5IkaWkWhTAueamvizXcqvRXEFJWoUS5aKTISKTGRG29pkhlf1PsuI1UuHq4GM0KlOjdAc60NDktSsJaOtTLIiSHFthEPZp+2Ew8WBO19L2uZATgqHCgWqeTFwP97e51gb6yqwl9IDqyheYYORoTJj0AFNz1qgbPaVIWYkcNi/if2Brdlij2Pq0JlJcMfgflZHC30vhbn16Cf51/89jLY3lr9uWJEvSwJSQCRQOhO5YmWhRI1iRRNIhwmMhqcst5tpVkc6uehpLuyoiGR95PJcd3HZM17Q+MKWPaRsjqnx3WNP7U/X3kjr5Z9ikVPFR7oMS43HV7x0Qrnh55CtEL6SOOTfxEtVO68sGPsc47qdJ+pu49W9z9AS680JY4YSocx/GqfpfALLDApaC2CgwYNhmfss0oqlhRI1CkUBbhg5SqernrRmyStsbhg+htMoP9fIiNXLGW8bMd2Jy4izIXyJQHqqoFpp2OyCtNXGQOPqwglrhCCt27jgbmbDVUIyk5FllS6w5QmzzjmEdkVgFcNiAW8Jx+XlRFKz8kpga/6VQiCBn7TeS8/qimk71F5L2VnDtnK+A0X5KFGjUBTAn47whq5f8ZuaPfQ6ayeWOzMJ9owcZ0voXFn7MRE8VXM9Z31rcvwEDgW2sCF0gbsG9qOt4KriFX4LFxOunCmnfGjSZNTqmbLcyJT32Y1/9HHdzllPK2GLG6eRYF2kHV8mitenEyrhcCwEtK5xTJRBWE449r554vXkrLbu0SRVPZGCPrMCsKUMrCmDtH16Q0rCbcUSTE7bH1cCGWWlUeRBiRqFogiV6RBv6N5L0OoZyyicoS4xOC3nyOerdnLWuzr75qon2TPe1diMNLcNH5rFXi8tLFZBXaC0iUQisJlTPXl1vbwhUbcIDvo38XLldkAgMJEIXq7czpbQOa5PvEJ41CjonyoErNlgW1JOwZNT8APcXazqcoEU/JpR3vyQlpEwTb/5cMCBJ5iciJyeTL5l48vjHiumEjWKPChRo1CUgT8dwZ+evlNySlg4XrG+sFleCI7513PjyDGs0yygOWjzc8K3liG7H4uZYU20i/XhS0uyEOcqT5JAbJgRp79gmQwJrIl2TFlusWbDw2PR4oNvd8uGHL8QyZXpixO+dViaDHZkDtDdkZriuGq1CVa12bAskoF0su/Kp9/4O4WLG+ak4J8ZhkUry5JiWKf/2aTtFoYaPFT1RHJEzPjrq4WNBKQGIzWuaR9LsTJQokahmEPOeloLDtITCI2znha2hC+Uvd9XAlvYX7n9SoSWlHQ76zgQ2MLruvfiX4K+OjeNHuMx1535466lZGP4It5MbNIiSSxqEg0bJWtHVdZYeax6W+GYbiE4VrGe63wnWbtRIzRqkIibCAEerz6RU2c++e5X3l1eJeafzm0/Yh4bhibQzPyZYySQdFrIzNDHJVphJ+mw4B1J4IilAEHCbSVj1fCOJLCmryjMhMvCSJ2bzDSnuRQrB3VlKBRzyIjdV147a3ntAM67m9lfuR2YVJ9mUjTKLxru5B3tv5iYIhuxejnrbSOu2/FkYmwIX8oRB4WIa3YiVhc2I40vU9inYrZojfVwT98+flNzPRl0NGT2yRzBhvAl7hh4ZaJtOm3SeTlFKll8GlBo2VpM6eZaYhZn0bam0Gl3NbIhcgl/wAKB2TirXG49+kkODF4p4zGlIrMpcYdTOKMp+DL4HHEiFfaFnWrRBCN1bqqvsqbAldDqkTr3NR0iY9cZqXcDufsJBxzYkgaaIclYtRkLJ8XKQYkahWIO8aWjZbWbTr6dQ/7NBXPoSKERtnq47G6iLdrFMzXXc3qsKvm4OX9/YBu7gie5cfhoXqESsrh5oWonl93N2TIRQFVyhBuGj9Ia6ym7nzNhQ+QybdEuLnhWMWr1YDPTrIl0UJG58jlKU9JxqXgFcLdHw+XRsNkENptGn1a8PEJ2x5KUNrNb4pQU/OOOOZOsO8KUWP8ghDPqQzMlpiaw+jITzrXOUJKq3gi6eSUqyBVO4R+MMdDoIe5duESP0Qo7pgaB/liO5STpyFpOUo45GkqEmLt9K5Yl6mpRKOaQDeFLvFC1q3ioqyw/301KWBh0VBZtI6RJl7OOXkc1p8cclKXIja86FNiC00iyY/RMzrYhi5sfNj9ASrNOCBqAIVsFj9Xfwb39L5bsq4mg11FNXLfjzsSpSw7liKeo7mDEVoFFGtQkhtHJdWCxyQybihQlDYeNkjllohGTaOTKfk3/IDQW3QSEIKlZ6XbUUJkKYjPThKxe0sKCNxPl//fqIsUMx1Lwu0aTNA4MY8lkp2pMARGfDYTAE0wyLkPHe+8fihNzW9EME0fCmFieYw2RUNMVoadNJ72AA3zcayfusY1ZTkwyVl1ZThSLjmn9Qg4fPszPfvYzKisrefvb30519ZViYqFQiI9//OP827/926x3UqFYqjjMFGsj7Zz3tOQXNlKyLnKp7BIPsky/jrSmc8qzuqiYOhDYwtbRczmiYl/VzjFBkz8B3m9q9tAW7cSaJwEewDnPKl6o2kXMcsWRsyIV5rbBV6hMjfJs9R4uu5smzsNuJLlu5CQ7Rk9PDOSZtORipoLTtZvoq2xCahpV0SGaL56gsrsdaVwRNHGXh67Vm+lvbMOwWME0MS3Z25otmaCyv4u204ewByME+rsIVjcUDR3fX3XF4oI0J/yhJFDVFSZY6y7oEOvvjeALZvMWjZ+LkOAbTU2Ztpn82hlN510+eZkEfMNxhhq9Bfs+LyjLiWKRU/ZE7RNPPMGNN97Id77zHf72b/+WTZs2sXfv3on18Xicf//3f5+TTk7m//yf/0NbWxsOh4ObbrqJl156ac6PqVBcC3cPvERjvC/7ZnxaYux/c7yXu/v3l70vm5nGlw4XrYsjEeimiSlKVLbW7fQ5qibeJzQbl9xNhUtDCEFaWLjobs67+qynlV/V3UpMz/VdGbV6+EXDnXy/+SEuuxpzhFlSt7Ovehf7qnYipWRoIM1zsUZ+vfVVdFe3krHYMDQL/e4aDuy4h5MbbiAzpqeClbW8fPcb6Fy9mZTTjWG1YdjsSN2C1C0knW562jbywoNv5/ym3aw9ug89k0bkycmf/9MUOa/c4RT1l4PomanbW+OZKYJm8utiUlSUWD/exhUpT/gqFCuZskXNZz7zGf6//+//49ixY1y6dIlPfepTvP71r+exxx6by/7l8N3vfpdPfOIT/OVf/iUHDhxg586dPPTQQ/T3989bHxSK6WKRJq/teZrXdf2a9eFLNMT6WB++xOu6fs1rep6ZMv1SDAFsD54pvF6a2Mw0ValgyYKAAEmpE40YxKIGId1ZtNYVgIYklC8BHhrPV+/KH10kssN2QrcXtJIc8W+iI+aiM2zn9K7bAXLbjr3uWrOFwfoWDE3n2I33Yep6bhbiyccefy0EHRt2cGrPXex87lFquy5cETZSgixQD/qq8xCAnpFUDE51sg4MRCfazBWinPLhCsUKp2w74vHjx/nGN74BgBCCT33qUzQ3N/PWt76V73znO9xwww1z1slx/uf//J988IMf5P3vfz8A//zP/8zPf/5z/u3f/o0//dM/nfPjKxQzRQCNiQEaEwPXvK8tofP0Oqo5723NcRgW0kSTJg/1PosmzbJS1o+eGiAVSwEQd0agpXh7E4HdTE1Z3umqI6EXKS5YquK5aXLC1YZszUY8FWxvmnSu2UzGaiNjm57jbKSiiotbrmfHi79k/ZF99Det5syu26a1D0E2w+5IrRs5KauwLWHMqaCRQNJ+xfKmp9OsOXGSTQcO4ozGiHncHL/xBi5t3IDUlZ+LYuVStqix2+0Eg8GcZe9+97vRNI13vOMd/P3f//1s9y2HVCrFK6+8wqc//emJZZqmcf/99/PCCy/k3SaZTJJMXqnNEwqF5rSPCsV8oCG5t+8FGkc6OOlfz6grgEVmWBvtZNvoWSoy2dBbf2qUUas3r/VFmCb+wR6csStRV854BE9wkEhFVVERsmqkfYqNN2pxFc4BUwYSiDvcpOzOwvWfADSNcKAGZzQEplm87dUIwXBdMxFfAE9oZCK/z3T7rEnQMmZO7SE5x/HuAggHstN69liM1/6/b+IOhSeElDMW485HfsGO51/gkff+Noa1jGgvhWIZUrao2bVrF3v37mXPnj05y9/5zncipeS9733vrHduMoODgxiGQV1dXc7yuro6Tp06lXebz3/+83z2s5+d034pFPNNKmnS1ZFCT55jG1fqT7k9Gp5mG+gCAdzb9yI/bboXA3KEjZAmlnSKDUf2Tdn3mpMHOHLzAwUT4DVePEV6IAJ12UFzPJTZftrDb74/85FdANZkkozVXlJoCNNkuLZ5eoJmHNNksL4FT2gEWyo+cxF2VWmGpNOCZY58XiQQ9dmI+WwA3Pf9H+YImsn4h0e47/s/5Il3vWNO+qJQLHbKFjX/9b/+V5555pm86971rnchpeSrX/3qrHVsNvj0pz/NJz7xiYn3oVCIVatWLWCPFIriSClJJCSppIkmBC6PllPbKJOWtF9MYuQJPopGTDovJ2lZbUcIQU1qhDd3PsGBwBYueFowhYZuZqjvOs+qk4dxJKb6hlQOdLPllac5vfNWDKsNYZpjjr2SxounWXf8Jc7U1fIPD/9WdoOxUGZMSbM2UjDrbL68LTmrNY26zvOEKmsYrm0q+PkI08SaSpBwzSwKSCAx9Oxtr7KvCz2dwrDayt5eAgmXFVPPFVQjtS5ckdGxY0yDyX4yeT4bU8BwrYuo3wFC4B0epqa3r+gu6zs6sUeiJD35E+IF+vvZdOAQdZ2dSKHRtaaNU9ftIuL3T6fnCsWipGxR86Y3vYk3velN7N27l3vuuWfK+ne/+92Ew3OXmr26uhpd1+nry/1B9/X1UV9fn3cbu92O3b5wCasUiumQiJv0dE3NkmuzC6pqLHh9OiPDmbyC5so+JJGwideXnRoJpMPc1/8idw28TEqzYjfSnD8RLepDXNt9iareDgYbWoi7vVjSKWq6L2NPjtUQyretJhipdVHdG82bdVYAmmlgCm2qhUWaVPe0k3RZqe28wKWN15GxWPO0k0ghsoJmphYWoeEOBwHQTYM1J1/h7I5bytt27P9o9dTMxIbNwlCDm6qe6JRthJRoRgbTYp0i7rwjA7SdOcxITQPt67ahja02BUT8dkZq3DDJd2f1yfxW6ckIYNOhQxy+faq/0MaDh7jpyV8hhUAb64tveJhNrxzkqTe+ns51a0vuX6FYzEw74cCrXvUq/uAP/oC/+Zu/wTo2bzs4OMj73/9+nn32WT70oQ/NeicBbDYbe/bs4Ve/+hVvfOMbATBNk1/96ld89KMfnZNjKhTzRTJp0n4picwTCJVKSno60wzZM2QyJcoC6ILodfXU/OsdU1Pwj/HW9q/gDhfPYKybBnVdUxPgmULQ05rfmzhrTchmndUn5ZIxLBope5rbHn2MU9fdQdxbkRPaXt9xHs9oF795+DW85j++zfZ9T3L05gfIjFtQhMjmjBnP2FKqllYhpETPpKnuvjRxLk2XTtO+bi1xd+2EoBhvmz1uNjoKTcPUBUMNHpKu/P4q0QoHCaeFQH8cRywNSNI2nbhH4/Vf+wbBmgbC/mqQJp7gEL7RYWypBKYQjNT66VxfiS2RLVSZclhyHJHHsSeSU5blwxGfWsSyurubm5/8FZAbSaVJiZSSu3/yU374e79LzDvzXDiOSIS1J06y6ux5XJEwCZeL89u2cn7rFjK28i1iCsVMmbao2bt3L7/zO7/Dk08+ybe+9S0uXrzIf/kv/4UNGzZw6NChOejiFT7xiU/w3ve+l+uvv54bb7yRL37xi0Sj0YloKIVisSClJBwyiEVMhAb+gI7dUTgqZag/nVfQTCadlphm8ekNaUhOHzT5XwUEDcC5bdvYvu/FiSf1chmPSjqza2fBNtEKB1GfHUc0jW5IMhaNpMsCQvDSA3dx+89+TtLlI1xRhWZkqO7rpL+5gaff8DoydhuP/M5vsfO557lh7w8ZaFzNYN0qIv5KMhbbmOWmTAvNVX45433XjSADTY1YMhmG6mo5s2snI7U1aKk0zRc68Y5EsaRNnLEI7tAIoUCAntZWhuuriXltJS1Ehs3CYPNUUXDktlu47tnnqOzvyjkDUwhSDjuHbrsFqYmCgmmcntZVbHnlQMnTH2homLJsy/4DmJMsNJMRZMs4bDh0hEN3TC8iDMA/OMievU/TdPFSTnVtz2iI6p5eNu8/wOPvejtxz9R0AArFbDJtUXPrrbdy6NAhfv/3f5/du3djmiZ/9Vd/xac+9ak5r2L7jne8g4GBAf7iL/6C3t5edu3axWOPPTbFeVihWEgi4QzdHemcKZ7gsIHNLljVZsNyVXFC05SMhmXJpFHSJGfAyIcpBGF/RdH9nNp9HeuPHMURi5UtbEwhQAieft3DRErsHyFIeKY+lXevbuP7H/4QLWfPERgcJGOxsP/+WwlOykwerfDx/GtexYupFNXdvdhSDoSpIaYbMD1uZRFioor0SK2LlLOKs7s2X2knJZteOcCuZ5/HPjlSMuDnxfvuoXvNmukdtwBHbrmJpNPBzudewBm74svU09rCiw/cR7SixGc6RufataSsVqzpdMGK2aamcWnTxinr6i+3F/2+NSlpuHx52qKmsq+PV33ru1gm9enq/95gkDt+9nPlwKyYc2aU7/rMmTPs37+f5uZmuru7OX36NLFYDLf72iq1lsNHP/pRNd2kWLTEYwZd7fmjYJJJybEOje99+PdzEsu5wmHedvJfytq/KUTRJGyalJzdvr3oPhJuF4+9+53c+bNHqO7tmxBJ+XxhAGJeD+3r13Pqul2EqorXnSrZf4uFS5s3calIm5YzZ9n88kF6WrcwWuWasf/M5O0saTNvev9tL77EnmeenbLcExzl3h/9hEff/S6GGgpbvabTl9PX7eLMzh1Ud/dgTacZrQyULWYm7+e51zzE3T95JK+4FcDL99w9USri6nUlmUF+v1sefxK9gMgaR5OSho5Oats76G9RwRqKuWPaoua///f/zl/+5V/ye7/3e3zhC1/g3Llz/PZv/zY7duzgm9/8JrfcUp7TnUKxVLn16CcnXt/9p7m+C6/5f9+khvzRKQJwxuJseXk/x2+6cWJ50uHA0DT0POn7r0YKQdLpwB5PTHnqlsD5bVsZaCpVuRHCAT8//53foqqnl+reXgJ9AzRduoRnUi6n/qZG9j34AMGa6iJ7ml3WHz5C04U+Tu25r6yMyBMUia4SgCVj4gqniPmuBA7Y4nF2Pfd83t1pMjvVt/vpZ3jynW+fzikU76amMdBcOLqrHNo3buTXb9K57dHHcSQSE8tTNhsv33s353bkF7U9LatoPXO2oLXGFILethLZF6/CPzBAdYlorHEkcO+PfsLP3v87RH2+aR1HoSiXaYuaf/zHf+THP/4xr371qwHYtm0bL730En/2Z3/G3XffnZPsTqFYSux6dWbi9Wu0Pyjc8E+nOmFCNstrqRu8JBuBMlnUGFYrFzdvYs3xEyWnoHTT5MCdd1DT3c3aYycmhFDSYefE9ddz9OYbp2XZGGqov2KJkJJA/wD2RIJIRUXpaaZZxhZP4BtIcnHz7uyC6VhoSrWVJo5YOkfUtJ0+g2YUFpKalDS2d+AKh6/JeXYu6Fy/ju+uW0ttVxfuUJiEy0nvqlVFswmfvH43q0/nL7EhyQrmMzt35F1fCN9IsOy2ArCmUtz6i8d48p1vR8tkaDt9hsr+fgzdQse6NQw2NMzcMqdQMANRc/To0Zzq3ABWq5UvfOELvPa1r521jikUs42Uks/d9V40aRLzeJCahjMcYcORI9Rf7uDp70h6W1ZxducOmMEYZk2myipMaJ/0dD3O4dtuYdW589iSyaL+MimHgwtbt3Bux3Zeufsu/AODSE1jqK4275TDtBCCkbraa9vHDLEk0jRcDDHYtHr6WX7LyCwsJFMEjDMSRWpa3gKXk3FEY4tO1AAgBP3N+YuL5mOgqYkX77uHm361N8dheNxf6pnXv3baFpSUfXoRTeNCce3Ro9zw66exJ5MYmoYAdux7kd7mJp564+tJ22zYEwlSdrvKjqyYFtO+C14taCZz1113XVNnFIqZ4Nj75onXecOYpWTNiZNs3/cib//yVwCIu1x0t7XSdvoMwjQnbvC1Xd1s3/cS57dtJRzwM1xbS3dba1mDbMrpwKR4lVgJpOxTayRF/H5+8Vvv4pbHnqC+q3vKelMITF1n7xtfny3iCKQcDvpXlT+oLVasiQwNl0LZUO0ZPKVrZhJrLEPS7Sma3M+aigJXBu2Yx1NQ0EhgsKGF7taNuEIWHNERoj47kYADwzLDkPJFwKk9u+lvamLzgYPUdXQghUbn2tWcvm4Xocrp+0v1NzeTcDpwxKcK9WLc+tiTE68nT7vWdnbxxn/9GtZUCt00Mcacng/fdgvhQGDa/VOsPISUK6f0aygUoqKigic2P4hbV+p/sTOegh/gnh/cXtY2ejpN65mzeINBUnYHlzeuZ8OhI+x8YV9BR9hCUSSSrEAJ+3w884bXZk3jJXjo29+hrqOroLVFAgfuvINjN99YoAX4+/rYcuAQjRcv4opEydisXNy0ieM37CFUVVWyD0sJYUqaz2UzEU8HCRi6oL/Zy9qTx2g+18XZ7TfnFzXSxJJKEfGb9LVecVK1JRK8/f/8M/pV2QwlghO772Cgec1YyJk2cUxTE/S1+EjncTpeqWw8cJCbf/nraW1TSvzntBWCjM3Ko+9+17z6dykWF5lkjOe++DZGR0fxFbEoKlGjWFD+7OEPz9q+Vp84yc1P/BJrKoWpaVnriyyQtn8amEJgWCw88t7fKvk06xkJ8qZ//TdEgeMmnE5+8KEPkrGVef1dQ5HIRY+U1LWHsMcz0/6OEg6dgWYfpkWjsq+P1/77Nzm163b6WtblTkeZJrppsPXFX/LYb72N9FUZxre++BLXP/2bnGUda7ZwfusNeT/3bIZgg4bLh9CkyUBjIxc3b1rZieWkZNuLL7Hr2efRxqwuRXMplVifD1MIhmtr+fl7f2umvVQsccoVNepxQzHrfPcr7554ffin/nk5ZtP5C9zxyC+A7A1zskl7JjfRyWhSQibD1hdf5oVXP1S0bSTg55Hffg8PfO8HOK/K6hqsrOTxd769fEEDy1bQaIZJTUcIe8Io/7uREimgb5Uvm6Tuqs9m46Fnqe5t59KGncS8/mzYvABPcJCO9eunCBqA4zfegGG1ZvPUJBJIoHPNloJdEABCxz8Yorb7MuuOHueWx58kFAhw9OYbubB1S064/opACI7dfBNnd2xn9anTrD16nKq+voIW0Jlc0ZqUVPf1EejrXzC/L8XSQIkaRdkUC2XO4afz0JmruO43z+XUs5nMbMgCbcwv54VXPVhSaIzU1/GfH/swte0drDp/AVPXuLhpE8HamlnoydLHEU1R05GtMj19QVNB0p0rCnc8v2/iuw/7q4n6q7LWGpE9wmhlHWga3qE44aqr6jYJwand13Fmx3bqOzqxJlIgime9FaZBOFBLXffliWW+kRFuf/RxNr9ykEff9XaMFVhzLulyZT/LnTu442c/p+3MWUxNoJkyazk1TdrXr6O6uwdXNDqj36V/aGjaokaYJnrGIGO1LNuHBMUVlKhZ4UwOY4aZhTIvNP7+fqr6++f8OBbDQDOMsqOM+ltWqURjV2FJGdR0TlPQIEnZdQaavGTsuZ+9nk6z6tx5NCkZqa6nfcOYH9Zka8nY68qBGAm3Na8/jGmx0L26DT1t0nx+ZNrnNX4uVf39vOOfvsJj73oHw/UrM9O5qes8/YbXcaKrm3XHjuOKRIi53ZzfvpX+pia2vfgSu3/z3PTyEI2RmUYkVHV3D9v2vciq8xfQpCTmcXPquus4cf1uFVG1jFGiZgUwm34ri4m69g52PP8Cje0d83K8uMs5EXmkmBmeYAIhp2c9S9ot9LZV5H3KtqZSE9a5rtWbi4Z3S8A7kmC4obAlxrAI0lYNS9os7Oyt6fgHewruw5JO8+pvfYcXHryfS5s3rcxrRggGmpvyJho8uWc3LWfPUdXbl2NZLTU1lbZYChZTvZpVZ89x94+zJuPxYzgjUa579jmaz53niXe+TQmbZYoSNUuYkqHMy5i2k6e482c/R86TOdkUgjM7dyrz9TXiCpfO5TOZuNNC/ypvwc896XCQHquFFPLXFM1XIwB7PFNwfbaRIFTlpKo3mn+9aeKIR6jq6yp6HD2T4Y5fPMYNe5/mxfvv5dLmTcWPu4IwrFaeeMfb2fHCC2w8dATbWMLWuMuFMxYr6Itz/Mbry3LItiRT3PHIL6Y46wsAKanu7WX7vpdmVLhTsfhRomaRMdlvBUr4rvyPOe7MAuMbHGTL/leo6+zG1DX6mps5tfs64h43tz36OMC0K00XY7xUwdVPjNkikX6O37Bn1o61UhFlfl0SSDp0+lt8RYWk1HXO7tjGpgOHENIo2G58n7IMH95IhR1rIoMvmLxyLYxdZ7ZUgh37fokoUSRpvMf2eJy7fvZzTF2nfcP60gdfIWRsVg7cdSeHbr8NVziMoVuIu11c/9QzbNn/ClII5FidM01KTu6+jsO33VrWvlefPJVTXPNqNCnZeOgQh2+7ZeU5da8AlKiZJ641Bf9KwhaPc9dPfjZlWikwMMjmg4foWdWMnikvDLicaAtTCEZqanjkvb/FxkOH2f7Ci7gjESArdC5s2cwr99xF2jE1ad5KZzzVfW1XN1JAT0sLHevXFRwskk4LeglrjQRMXTDYWNhCM5mjN99My9nzVPd20NW2qai1Jp6nevgUhGCkzk3MZ8c7ksCaNNCMDJsOvUR9xzksmfwFS/Puaux8rt/7FO3r1ylL31WYuk7E7594v//euzm1exdrj5/AGYkSd7u5sHUL4YC/4D6upnKgH7NELTVHPIEjGiPuLe4Urlh6KFEziyxX35X5RBgGD373+1TmcfwdHw4aOjpLVqsul2wSN53nx6Kaxisp+wcH0TMGocoAKSVm8lLd3cN9P/gRjngcc0xIbDp4mIjPyy/f9hZG8yQKDAccuMOpovtNuKwMNbgxrOX5oiTcLn7+nndxy+O/QkiJzJPbJ1vbCML+Mr9LIUi6rNnQ8TGq+gM0X0xPOyxZAN7RENU9vQw2lk7guNKJ+P1lW2XyYVgsZX0/hmUF+jqtAJSoKcFkvxVYeb4r803L2XNlRTKVI2gee8dbuetnv8Aej+edpsrmJFnNgbvuzMlUKjWNkVqVC6MYrlCIB/7z+1jSWauFNump2BWO8NC3/5Mf/e77p1i3ki4rwSon/qF4jjgYfz1S5SRU45peZ6Tkuueeo+XCOVyROCduuAdTyx2wpCboX5VN1jdTjtx2C8HqKnY+v4/KgYFpb++IxWZ8bEX5dKxbx9aXXym43hSCwYYGUk5nwTaKpcuKFTVlp+Bf5n4ri401J06W9SRcbL0pBP1NTfS1tvLYu97BvT/8ERUjwQlrgmaahCoqePp1r2W4UYnUmbDp4CEs6XResahJiSMWY92xE5y8fveU9aM1LlIOC76ROPZYdlo24bIQqnSSKGd66CpWnzzFhiPHAKju72LtsZc4t+1G5CRhIyS4QkmSzmvLVdK+cQPtGzdgi0a5+6eP0NDRWbblJupbhEUxlyF9zU30NzRQ3dtb8Po8cstN13QMPZ2mprsHzTAYqalR01iLiBUpaj770Af56x9M82lQMS84CkQ/5MPMk2wvm8ZecuTW7E0rVFXJj3/3AzReukxdRycI6F21KhsaqvwbZkzbqTMlnbRbT5/OK2oA4l4bca/tSq6Sa/guNr9yYOJaGKpt5uyOW6bsUwDeYBIEjNRd+wCUcrt54p1vZ+2x42x76WX8Q8MF25pCEKyuZqRGJV+cF4Tg1295I/d/74dU9/VlH2YmXasv3n8fXWvXzGzXpsmO5/ex9eX9WMeslBJoX7+OfQ/cT8Ljno0zUFwDK1LUKOYYKbGk0khNFM4FISWNly6z/shRPKOjxN1uzm/dQriigprunpLCRgIDjQ3UdXVjalq2+KRpYuo6zz/0AD1tbVcaC0H36ja6V7fl35li2oxPOxVCANZUGQ611yospZzIdyKBC5t3A3KiCOXVffKOJAlVuWan0rYQnN++jfPbtrLm+Elu/8WjE8cZxxQChOCl++8teq6eYJD1R47hGx4mY7NxaeMGule3qeicGZJ0ufj577yHxkuXaTlzFmsqRbC6inPbtxH3lBa1wjBYde48De3tWFJpLOk0Ugiq+vrwBkenhIq3nD1HdU8vP3v/74CUOGMx4i4XSZd6eJ5vlKhRzBrCNNlw+Aib979CxUgQgMG6WmIeLzU93diSKcIVFZzduZ36y+2sunBx4gnbFIJV5y8QrAyUZakZbKjnsXe/k+qeHtpOn8GSShOsruLC1i3KsXceGKmpxt7eUdBaY2qC4XkuCxF3e4lWFC84CuAKJwkHZtGfQggubNtCymHn+r1PUzFyJSPxSE01L913L/2rmgtuvm3fi+x+5tmcZeuOHWewrpZfvu0tamCcKTN8mKkYGuL+7/0ATyg8EZAwHsVW6N4kAFckwsP//k08odBE+841azhw1+0ElZVu3lCiRjE7SMntP3+U1SdP5Syu6uunuu+K42/F8DDX73164v34oDj+3zc8QtTjwRWJFEzCZWoaT73+tSAEg42NDDY2zvrpKIpz+rpdNF5uL7heMyWnr9s55/244Vd7J66djLU8fxzNmL3cRpPpXLeWzrVrqOzrxxmLEXN7yFg9WJMGgb4oMa9tik/PuiNH2XOVoBmnqq+fe370Ex579zvVVOk8YU0keOjb/4l9rBjtZNFejp/fuKAZf9908SIN7e08+u53rtiyGfONsm0qZoXVJ0+x5uSpKTV9rr4RiEl/+dDIPvGc2bkDI09Y7mggwI9+9wPEKipmqeeKmdC+fh3ntm7JhkpPWj7++uiNN8y52PQPDLLlwMGJ945YFGTh3CSQve7StjkM5RWC4fo6glWNeIMagf4YntEk3pEE9e0hGi4GscXHpuWk5MZf7S2Yxk8AdV3dVPf0AtmcQE3nL7Dm+AlqurpmVDtJUZx1x07giMVmnNTz6vuaJiWaYXDrY49fe+cUZaEsNYpZYdOBg3kdd2eCIDu99NJ999B08SKBvgFibhed69aRUFEGiwMheO41r2KwsYEtL+/HFxwFIFhdzbGbbuDCls1z3oV1R49NVIGGbLbfqt4OhupW5U/AJyXCNMpLwHcNOKJpqnqyyRuvHuRsKZOGyyESDh3dCE84mxZCAtv3vYgtkaC6pxeLcSVr8mhlgBceepC+IlNbiunRevrMrO9Tk5Kq/gECff3TrjCumD5K1ChmhcDA4KyVLJhw+rVY6Fi/no71Kr38omQsWeHpXTuxJxJIIUjZ7fM2VeIZHUWYudfcuuP7Ga2qI2Ox5QqbsWtz08FnGVj1AFGfb876VTGUzUdT7FOwJwyE6SDiC+AJFa4KLoCWc+fzrvOOjPDAd7/HY+9+h5qCnSWsqenVJpsOvpERJWrmATX9pJgVDMvs6WMBDKib9OJGSjTDRDOy0z1JpzProD2Pvh9Jp3NKdJAzFmbPMz+nurc9ZyrKMzrE9n2/pLb7EqvOnpuzPgnDxBErXcJDQDZ6asv1Mz6WJrPpC/Y89ZsZ70ORy3BtDaY2N9dw2m6fk/0qclGWGsWscHnjBtYfPlK2taZQJIEpBAONDYzMc+SMokykxDOaxDccx5rKioaUTSdU6SBaMX9WGoALWzaz4cjRKcudsTDb9j9FymYn6fRgSSdxxrLTQaYQJcPRr4VyC3ZmGwtGahpJOlzYEzPLNqxJSX1nJ+5QaE6tTyuFM7t2su74iWlvVyoBY9Jhp1dNE84LylKjmBVO7NmNqWnZvBxlMB7yOD4GZGvzCGIeD7953cNz1EvFNSEllb1RqnqjWFJXrCDWlEF1b5RAX3RenVf7VjXT1dZa8JqzpZJ4R4cmBA1kRUC+mlSzhakLjOk86QtBwnHtIdvOaPSa96GAgaZGjt54A5DfAR6ywnjy+4yuMVCiptfhW2/FnEVrtqIw6lNWzAqhqkp+/ZY3cfePf4o1lUKODTTjlhuTrIIedyY+vXM7wepqNhw+ijscIuF0cW77Nk7v2qFqsixSHNE03tEkkD/CzRdMEvPaSboLJFycbYTgqTe+gZsff4I1k1IJFJIUphAkXC46Z5hNttw+RQIOfEPxsn0zLOnkxO9jnOkWzYy5VSbb2eLAXXcQrKlm24svExgcBLIPXGIsn1bHurUcv2EPhtWKZpqMVlaSttnY+dwL7HhhH4Kx+5xpIjWNQ7fdwsk91y3sSa0ghJQrJy4wFApRUVHBbR//Hha7Smg1F1iSKdacOElNTw+mptE9Vo6g7fQZ7PE4oUCAszu2M9Sgai4tNWo6Qzgj6YKDrQRiXhuDTfNX48gWT+MbTuCMpNBMEz0dZ+3xV6jvuJAjEkwhkELwq7e+mZ621jntkzAldZdHsSWNosJEAkmHTsqVYvu+l2g9cwbNlMQdDkyLBWc0WnI61xSCvuZmnnjX22f1HBSAlNiSSYSUJO12dMPA1PWiWZ4d0Shtp07jikSJedxc3LxJJU+cJTLJGM998W2Mjo7iKzLVqkSNQqEoi6ZzI1gyxfPApK0a3WsD89IfdzBBVW922uXqat/u0V6ue+6XWDKZbGbXtWs4fOst8yamhSnxDcXxDcfR8txhxxf1tfhIuqxj25jomQwZq5U1J05yx88fLXoME5C6zqPvfqd6SFAse8oVNWr6SZEXTzDImhMncUZjRL0eOtesxhFPYGoaQ/V1hWs6KZYtpaJCZBltZgtLypgiaCa/jlbU86P/8nugZUjZ7GTsc5ub5mqkJhitcTFa5aBiMI5vOIHGFdFlWARD9Z4JQZPdRiNjy/bz4uZNtJw5S8tYpFa+T3W0upoXHnpACZqlipTUdnax9vgJnNEoMa+Xc9u2MthQrzJIXwNK1ChyEKbJDb/ey6YDh5BjJnvNNNn9zLMTN9aUzcaJ6/dw5NabVcG9FUTMa8Nawlck5pufsFX/QIlcMFLiDqUZWLXAEUGaxmitm1CVE2c0jWZIMlaNhNtadOCSmsbTb3gdW15+hc2vHMAdyTo7R3xeOtau5dy2rdm0+4X2ISWtp8+w+ZWDVPX1Yeo6HWvXcOKGPQzXqXT9C42WyXDXTx+h5dx5TE0gTInUNDYeOsz5LZt47jWvVvfWGaJEjSKHXc89z6YDh7KlDKTMG81iS6XY+fwLeINBnn341eqpYoUQDjjwjiTQTDlFTIxbaSIV8yBqpMQVLpEkTQhckQSwOMKcpa5NW/BJTeP4TTdw/MbrcUaiSE0j4XKW/r1Jyc2PP8nGI0evZPnOZFh98hSrT57i6de/lvaNG0ruw57IWmZVfpXZ54b/f3v3HRzXdd4P/3vu3d4XZQGCAEEQYG9gV6ElUo2y5ciyY1mJZUd0HL1xXtkTjzzjyEkmmsx4fnLGmoljJXGcX944HsdFkWRJkazeLYmSSIKdBEmQBNH7Yvvu3Xvvef+42AUW2AaS2IbnMwNB3Hq2YPe55zzned56B00XLgJAsiI2U7Wl3RWnOxG229Fx801FG185o6CGJOljMaw7eCivXRcMQOvpMzi7ZTNGly5d6KGRKVa/H6uPHEPz2XMQZRkTdR50bmnXOhEvcHCp6gSMLHPA0+uHqPBkXggDoIgMI00OqLqFP7o0hTMnK8+ki8sQ4/HyXyplDJF5tAdpOdOJ1VP1e2YmGgtce81uevElPN24FNE0O6aYqmJNxxGsO9QBm98PABir8+Dkrp24vGb11T2ORUKQZSw73wX75CQkoxE9q1YiYpt+/YzhMFYdP6EdNKbBAKw9fATHr7suuWwqKAqWnTuP2oFBcMYwsLw5r795QZax/Ow5tJ48BXMohJDDgfObNqK3rbViZ4IoqCFJDZe6oZOV3BecojKGtuMnKagpEE9fH2576rcQZTn5ZWUOhdB04SI6t2zGx7fdesWBDVM5rL4YbL4oRFlbIgm6TAg5DCm3KZl06Gt1wxKQYJpqzBi16BG2Gwo2Y6ePKeDgYDlCG7t3FEsvBtGzaiUsAQm6uApVYIjYDVAKEHwVy9pDHRn7sDFogcvK4ydx4vpdqeepKm5+/oVkHk9C1cgo9vzvizgy4cXxG65byKGXveaz53D9K6/BGItBFQQwVcXON99G59Z2HNq7B1wQsORyDwQ1e8K9TpZR19+P/hUtqBkYxC2/fQ7mcBiKIIABWH/oMHxVbrzxxS8g6HKlvQ1DNIrbn3wKNcMjyfeDc3wCjRcvYaB5Gd76wj3lH/CnUbl/2WTecjXXm03gHHafb4FGQ2bSSXHc8sxzKQENMH0kvubIMay4gkqoACDIKpZ0T6JqOARDVIFOVmGMyKgZDKKuxz+nvxIEhrDTiIl6GybqbdqySgGXIHmeycievgswRFU0nveidiAI12gYVcMhLO3ywj0UrMwu15yjeng461ZwxjlqBgfnnN5yphPN57u0wGfG6Ynb2vL+B3CNjl3jAVeOhkvduPn5F2CIabWcBFUFg/b8rT18BNvfekc7XcnvwFFQZFh9ftzxP0/BGIkAAERVTQZEdu8k9v36f6CT0n9u3/Dyq6gaGdVua+o1TPyu7+nF9nfevaLHWeooqCFJk9VV87p8opgZWXgtZ87AEItl/LJSGcP6Q4ev6LZr+/zQSWrKl1nitzEia5WCS0jEmmMnE+cQpShM0QjihhqIU/2p2Iwf+2QMVSX2uK4VnkeAqaZZeljTcSRrRXCVMaw6duyqxlbJtrz3PjhLn7zOAKw9chTmQDCvRG0OYMLjwZqOIxDjctq/e4FzWAMBtJw5M+c8q8+HZee7Mn5eCJxj5fGTMESjOcdSbiioIUljS5bAW12dd6sDgXNcWL9ugUdFAMDT15/1y0rgHFUjoxDnM9umctRfmoQpmrlIHANg88eSjStLgaIXEHQYM8+0MIYVZzpwcd02ADztLBIDYJuMQYznv9xaFhjDQMvynH/DAy3L55zmGhvPOsMjcA73CM3UpGOb9KFmeDhtTaKZms+dw2RtDYaXNmR8jVTG0L+iBSGnEy2dnTkLMC7vPDvntPqe3px5Z6KioGZg7oxduaOcmkXKEghg9dFjaLjYDYGrGG5sROeWzfjgM3di36+fBBQl6x+T1niyIe2HI8mBc9T2D2DliZOwTfoQtVpwcd1a9K9oyZy8l2egmc9RekJtvx+GWO4vdcYBQ1RGNNcMSaFwDoFj7lEx1wIY10g/qob7cH7zDVlvhnEOq1+Cv7qy2nKc2rkDjVM7a2ZTGUPMbMKltWvnnKfodFmXoDkA2VB5ORjXQj4zHpwxGKcu9/5dn8Zn/vvXMEYiKZ+zKmMI2204sO92AMi4tJTAoG3wSHd6Pipx3yoFNYtQw6Vu7P3tcxBUNfkH5RoZxZqOIzi1Yzve/OLnsebIMSw7dz65YyLRgDKhZ2UbPvz0vorNoF8oTFVx40uvoPX0mWTynsoYWjrPYnhpA9784hfSbqEdWtaEtpOnMt6uyhgm6jx5N83TSQrMIbksP9QsAQnWgIQ5H8lTAd2kZykO33xLztthXIUxEgVQWUHNcFMjDuy7Hde99gaA6V1PACCZTHj9S19MG5x0r1mFVUePZz2Yubxq5UIMueyFHPaMydkJTFURmErqDbpceGH/V7Hu0GG0nTgJUySKiMWC85s34vS2rcnWCpM11agdGMy67OytrZ1z+khDQ84xq4KAsfrKq1lEQc0iYQyHseL0GbhGx9B28hQYT601kghNNhw8hPUHD6FnZRue+9P9UPU6xIwmuCbGUT04BFUQMbi8GUGXsxgPo+xtOvARVpzW1sBnJ+/VDgzihpdfxbv33D3nepfWrMa2d96bc2SXIHCOk1PdhfNhCUh5X5YzIGYqnY8K+0Q0a8NHDkDWm8GmGgpmwpkAUygAoDBtHQrp/OZNGGxehlVHj6NmcAiKTkRfWysurlubse7MmW1b0XbiVNpZ2sQMwqW1a+Zcr66nF2sPd6B2YBCqKKCvtRVntm6Bf545euUsZrGgZ2VbxjwW7T2pTwkKIzYbOrduwUStB4yrGGlsnPO5era9HXX9AxnvV+Ac59o3zzndX12F/uXN2k6rNONRGcPFdWsrsi9V6XxSkQWz7uAhbHv392Ccg08FM9mO0BmApq4LqBkcwot/8hXIRgPGlizB2JIlBRpxZRLjcaw7eDjjcy9wjuZz52Gb9M35cFN1OrzxxS/gjiefgkGSgKnXURUYBJXj+HW75lVHhE3tzMiFAwg6jeBi6czIGWLZZ5gYADA9avu7MdKwHEgX2HAOQVEg6+WFGWQJCLpc6NiTfwE3f1UV3vjiF7D32edhiMXABQEc2o6boNOJN+79wzlbgDe//yHaPzyQMkux6ugxrDx2HO/cczf62lqv5UMqaR0334T6nt45Cf2JAPyjO25LPn+GaBTXv/Iams+dT+lb1te6Ah98el8y2OheuxrN587NaZeRuM2TO7ZnbJPx/mc+jTt//Rs4vJPJ6yZGNeHx4JNb916bB15iqKFlhWs9cRK7X371iq6rMobOre04eGvuqfzFyDbpw9KLFyEqKsbrPBhuasya++Lp68Onf/Vk1tvk0D780h19AdqM28oTJ9F89hx08TjG6+pwdks7Rpfmnm6eyeyPwTMQzHm5uI5hcIU7723UhdB4bhxilrxlDkAyAJ966Wl0fOqzkPWG1MBmKvem7fgBvPe526li7ixiPI6WzrOoGRgEFxj6W1rS5nstvXARtz3zbNrb0CpMC3j6zx9EdB6FA8ud3TuJbW+/g2UXLiaL63lratBx0+5kgCfIMj7zy1/DPTKadkbMV1WFl756f3KJkKnqnHYZk9VVOLlzBy5sWD/nM4cpChjnUHU66GISVp44ibYTJ7Q+fg47zm3ehAvr1+W9VF0qqKElAThH+wcfZp2qzyax7S9RNIpodJKEG15+FcvPngOgJQAKnMNX5ca7d38WkzU1MIXDkHU6xE2m5PXm1HvJIFthrpjFgpO7duLkrp1XNnjOYQ7GYfdGUyoCp70ogKFmZ0kFNAAg60UIsew7tmIWIwZalmHL+7/DpXXbMVbfBDDtPWwJ+rC88whUnQIxLlNQM4ui16Nr4wZ0bdyQ9XLrDh3OWuRPVFXc/tQzeHH/VxfN50fA7cI7X7gHplAINr8fktEIv9udEni0dJ5F9fBI2usLnMM1Po4Vp07j3BbtwGZmuwxLMAiVCYhaLSm3aZv0oe34cTR1XYB7bBwMgM/txpntW9G5tR1ntm9d0MddSiioqUCCooCpKpzj47D5A1d1W/p4HIZotCLXXgHA4vej7eQpOMcnAAB9K1age80qcFFMfwXOsfe3z6G+t2+6psvUh7rdO4m7fvEryKIIo6TlrAw1LsWJ66/DQMtyTNbWQBEEiFmCFgZoXXoXAueoHgzC5pdSAt3ZQW/i394aM1R9huehiHRy9qUzDkBUOD6+/TbsffY5bDj4NqImM2JmG8S4BGtwumDkvT/5KU5etxNHdt9IPczmydM/kHO7sXtsDO0ffIgjn9pdoFGVhqjVmrYNBQC0nTiZM6m47cSJZFCTxBjCdnvKSaZQGDe88ioaL1yc8zfh8Hqx6/U3seRyD969+7OLJrCkoKaCLOm+jA0ffYyGnl4AQMh29dO+qiAgbjDAEI2i7cQpNHV1QZRljNfX42z7ZkzW1lz1fVxrDZe6sfbQYdT19QMABpuX4fT2bRhe1pRyufUff4Jt7/4++W8GYMWZTtzwyqs4svsGnN65Y84XXX1PT/L5nU3gHFxRYJxRMdTTP4DbnnoGH955B7o2bcSldWux4tTpjMl73tpajNUvTFDjGI/A6teCrZmPKrHWnjhNFRgmPBaEXSaUIiHHjBcDICgqZIMer3/pi2i41I0tv38fNVNHx7JOj/G6JsQNRhgjIWz46CBknX5O2wBy9bQ+Rh04ft0uKDodPH39qBoZgSqIU7VYppcRmKqiqesCGi51g3GOsSX1uLR2bcVtIzcHQ9l3SQGwBHMXhtRJEvb9+kk4vN6MBf8AYNm582g9eQpdmzZe0XjLDQU1FWLV0WO4/rU3Ugo6WYLBK156ArQv2UurV8E5PoE7nnwqWWOBAageGsaaI0dxaM9NODWPXTcLbdOHH2HL+x+kHAk1XriIZV0X8Mkte5PTsCtOncb2GQHNTKKiYMe7v4c1GMLBWcl0K053Zj3Kmv1cJ7bTXvfaG+hta8XBW/agemgYrvExrS7c1OUS9UPeu/uuBZkxYIoK11gk8/lTv8drLQiWeN0WWSdAF888W8MBKIkZJsYw1LwMtt/5wQH0tm1A96p2LZ+AqwAToJOiaD11EGe2xSvuC3QhDTYvw9KLl3LO1uilOJaf6cSGg4fgGp/QailNXefSmtU4cOc+WIIB3PbUM7D7/MnPsJXHT2DbO+/h7c9/bs4BSTkLOeywT05mfN741GVyaTtxEs6Jibw+39cePrJogprFMR9V4aw+P3a9/iaA1K68uXY5JaT701IZgyqKOL1jG25/6mkYYrGU20vcz/Z33kPDxUtXM/xrxtPXhy3vfwBgbndiANj51ttwD48AnGPzBwfSPm5g+jGuO9yBquHhlPOMkUjG7rqZJPq/tJ04Bclkwktf+WMcvvkmBFwuKKKIsNWKk7t24H/3PwB/1cJsg7VNxnK+HzgAfRlU2A3mmEFi0HZsJXj6+mCKRNHbtgEX122fTpCcyrGR9Uacbd+Nhkv9CzXkinRqx/acAU3CrjffhmPCCwDJchIMWn7Jl3/0Y9zzHz+Dzad1BRc4hzB1GUMshtufegZ2r3dhHkQRTHhqcz5v5/MIQFYeP5nX/TEArrGxyux1lgbN1FSAVcePZz0/22yNCsDvdsMxOal9WTMGxjlCDgfe+4O7UDU6BlM4kvn6jGH9JwcxsKLlKh7BtbHm8JGssygqY1hz5ChO7dwOx+RkzttTGbDy2Al8fMd0gaqgU0uczTfpN4EzwDU+DgCQDQac2rmjoDNcFv/cqqPplX5eScBlgtUXg16amyysHeUaEDNPf7QZYhJkUYfuVe3pb3Bq5oCp5uTOqLLCOSwBCeZQHIxzSEYdgk4j1AXuRD68rAknd2zHhoOHsg8PmNOINSHXM60tJSpo//0H+P3dn73isZaKtuMnsOHg4YyfySqAibo6XFw3t+LzbOZQKO+/VlUUy+99fYUoqKkA7pHRrLMH2d7KAoCRxgYoeh0MkShCLifOb1yPi+u1rYJrD3eATwU6aa/POZb09JbEl4FnIHviosA5agcGIMbzq00icC3ZbqaujRuw7nDHFYyOQdYXcGmDc5hCcehkFSoAXR4zMAxA1Fr6HwlcZBhudsA9HILVL6XkAvndJvhqzCnvRb/bjfH6puxbWBkDoIM+piBeQoUGc9FJCjy9fujjanLm0QIJrrEwxpZMdVBfQIf33oyGi5fgHh9P/yXNGDhjWZPjc2EAms+dR/rF4vJhiEZx3etvZgxoOICA243X/ujevLZbh202mMLhnIGNKjD0rGy7ghGXp/L56yUZKTpd1sADSD9bw6FtR247cSq5DmkNBuHp6wcDw4UN68Hy+DBi0KaU59N3iKkqwDkaL15Cy5lOGKJRBFwunN+0ERNXWLo7XefhdJcxh0JQBSHr1mlAO2qKmVKXOryeWpzZ2o61HUfnXD7bjJigqgUrMW/xax2oRSX1/ZCrCi8ARGwl0t8pB1UUMN5gh9ejwhBTwBkgmXRpt59P1tZgsqY2r8BbVFTMoyVocXEOT68fuvh0F/IZZ6FmIIghvQDJvLDB9Nt/eA8+/cvfwBQOJw8qEu8nX1UV3FMzlFdDVFVYff6UxOKFZpucRPO589BJEvzuKvSsaptTfHA+Vpw6re1MzXC+liAchJJp5+Us5zdtwK433sp6GT71n1M7ts9nqGWNgpoK0NvWmqyZko7KgIDTBWswAJ2sHbFHTSboJQnCrMqyicTWG196Bd6aGowubchx2wwTnlpwQYAgyxBUVZuRSPPlISgKVh85hjUdR+CYnEx+yU73QOrBmqPHcGZrOz659ZZ5z/z0trViTcfRrAl4jgkvbn/6t3ndngDg0rq5ZeE/ufUWBB1ObPj4E5gjWvKtOhVUpgscVMYwXl+HoQIkO5oDEmoyFNXLWYW3DKk6AdE8llkurFsNSyj3o5RLcAt7JpaABH08fWCe2NHmmIhibOnCBjVaH6M/weojR7DyxEkYI1GE7Haca9+Ec5s34fP/9/+DJRS+6vux+QsT1AiyjOtffR2tp06Dz5hpkt4w4INP34meKzw4cXi9UHOUdNDH41h17DhaznSiamQUik6Hy6vacGb7NkzWpO407dq4AauOHU/bXT3xL1UQ8N7dn73iA8VyREFNBehevQrtv/8A1kAgw5ub4b27P4uA2wXn+DhUQUTT+fPY9NEnGbcCqoK29HTw1r3Y+t77EOX0pekFzjGwfDlu+5+n0dB9WUvSdDhwZusWdG7boq3lQvuguPWZZ7Hkck/K/SRuY+bvtR1HEXS6cHrHtnk9D51btmD1kWPJVhCznwcGQC/LaU+fTQXgrfOgrzVNmXfGcHrndpzZtgXVIyMQZAW+mmrU9/Ri9+9ehijLUAVBywdQVYwtWYK3vvC5hV+e4xzuEW0raLkGKTlxDmMkAs4YJHP+u7RGG2vRdG4cgoq0rwOH1t9KNpRRUBOUss6+MUz1+CrA0nDUasGx3Tfi2O4b55x3bvNmbDrwUd5JxZnEzIUpMXDDK69hxZnO5Ax0IsFWH5Ow5/kX8Op9917Rbqy40ZjXJoNdb76dPNDTyTLaTpxC68nTeOsL96TkLip6PV79oy/hutfewPJz55O3zQEEnE6c37QR59s3ITaPv5NKQEFNBVB1Orz2R/fijiefht3ngyowbbsw51BEEe/dfVcyUh+b6t666423suefqBxLL3XjA5MJb99zN2559jkwlSevk/ijG2xqxMaPP9GWv6aua/X7sf2dd9HQ3Y23/vDzUEUR6w53YMnlnrx3Y63/5CDObNsyr4JRgSo33rnnbux5/gWtt1EeHyAza7TMrLA7vKwpZ8EqLoop/bAur16FgeXNycahik6HnlVtGFm6tCD5RoaonPHIPRcOQDKVbjIhU1WsPdyBtYc7kgUlJzy1OLFrJ7rTNFmcewMM40vsyVms2cUGOQO8demLpZWqfJLVS+HVPL19K1rOnIF90ndFgQ2H1hZgsrr62g9uFsf4BFqnGs7OxqAd7LS//yFe/fJ9877t7lWrsOnAxxnPn/n5M3v3Jucce55/AU/9v3+eUgFbMpvx3uf+AIcCAdQMDoEzhpGlDRVbLDUfFNRUiKDLhWf/7Gto6rqAxosXISgqJurq0LVhXdojWsbzyJWZuszAihb87/4HsPnDA2jqugBBURCxWXFu40a0f/AhgLlbyQGgofsyVh85ijPbtmLN4SN5PxYGwBIKwTU2Bq/Hk/f1AKCvrRVP//mDWHniBOp7eqemjwU0XLqU9YhWAXBq5w7ETUb0t7TAWze/+02IG404u6X9iq57tUT56pIx/e7SPKJjqoqbn38h2dQvwTU6hptf+B2c4xM4tvuGnLcTdhgxyhjcoyHopennKmbWweuxQjKX18ehZNLBHMycAcQBxA3FD1TjJhNevv+PseOtt9Fy5uy8ApvEJQ/vubkgj2P52XNZd1AKnKO+rw+mUChjxeBMvHUe9LS1ovHCxYzLRZkwALp4HK2nTqNz65Y554ftdvTYc9e2WQzK66+YZMVFET2rV6Fn9aqMl6nt78e6g4dRPTySfas3YxhubJy6YY7VR45ixZnOZGEsSzCIrXn0lVrTcQQX1q9LNmKbD0HRvnhMoTCM0QgiViskU+4p6KjNihPXX4cT118HANj5xlvglwUgy1q2CODcls0IOZ3zHmex6aMynOMRbalhnhKvn99lRNhRmknCLWc60TwroAGmA+n2Dw+gZ1VbXgFwxG5AxKaHPqZAVDhkvVBWS04zBZ1GOMciWf8GA+7SqAods1jw/mfvwsFb9sI1OoZ1hw5j2YWLM/LpWDKfD9DelwK0RP2P7rgN/a0rCjJOQyyaUhwwE31MmndQAwDv/cFd2P27l7H83PnkzjBBVbWq7VL2v1/OGGoGBoE0QQ2ZRkHNIrLy2HFc/+rryQaMQOacEoFznNmmVd/d+NEnWNtxJHl68oo5MACOSV9el51N1onQSRJuf/IpNEzl4aiMoWfVSnR8ajcCVe68bytqMedcilIZyytgKjWmoARPn7Yck3gd86kizQEoAiCZ9Qi4TYha0yd3l4LVHUdz1h9adfQ4Pr7jtvxukDHETbry2eWUgaIXMVFvRdVQaE4vLwCIWPUIukqrWWfMYsFw8zIMNy9D9eAQVh4/AZvPh6jFgktr12BsST0aL1yEMRJF0OlAX+uKgnaT9rvcOXdFKqKIiO3KlioVvR7v3nM3jo6Po/nseejiEnzV1ehpXYEvP/GvOa+/WPo3XQ0KahYJu9eL6199fTr5bUq6nToC5zh8024ML2uCGI9jw8fpE4rTXX82lTFIZhOGGpfm1QAvcZ2B5uW4/alnUsYqcI5l585jSfdlvPSVP4Y/zzX2S2vXov39D7PeX29ba9l1a2YqR22aHJF8QhPJKGKoxbUQw7rm3GNjOesPuUdHCzii0hF0mRDXi3COR2AKx8EAyHoBAbdJm6Up0UAVAMaX1GM8TfPWCzm6gy+kS+vWYMfb72TcGKEyhovr1kA2XNmspntkBOsOdaDxwgUIioqxJfUYWboUcZMJQ42N8PT3Z1366m9ZfkX3u5hQ2LdIrDp6PGsdGe3IXUDPyja88sf34eR1WnM/T/9AzmnRTFTG0Nu6AmAMJ67blTOgSdTN8dbWompkGIzzOdcROIdekpJtIfIRcLtwdsvmrO0gjt2YOyej1Fj8MTB17k6vXLQiX+UzKyXnOFLnwBV/yVSCmFWPkWUO9KyuQs+qKgy0uhGoMpd0QFOq4kYjPr791mSpiZlUxhCxWnFk95V1HG/uPIvP/vy/seLUaZgiURgkCfU9vbj1t89h+1vv4OTOzG0nVMYQtNuveDv5YkJBzSJRm6ParnaEp02NDjc1Jk8X5fyq786WmA4/tUtrBTCwogUf3X6rFkQwBg5tJwGA5GkBlxOHb/4Uju6+HrZAMOsRS0NPL2x5tDpI+OTWW3By145kYavELQdcTrx2373wemqv5GEWlSE2/z5NHICiExa80uw1wTnWHO6AIZa7xUOhChuWNMbSFh8k89O1cQPe+vznMFk7XRdGEQRcXLcWv/vq/YjYbfO+TXMgiE+9+NKcA7XE/68/3AFRVXFw783aZ+NUQMWnfqIWC17/0h8mS2SQzGj5aZFQBTFnrkW69drZBZ+y34eg9dDhHKoo4v3P3InRpUuT55/d0o7etlasPHYCrrExKHo9ela2obetNeW+V3ccySsvxOGdRNDlymtsXBDQcfNNOLlrJ5ZeuAT91Fr2cGNhtlsvBJ7nsGduFVV0AoaXOcriy2/t4Q7sfOudrJdRGUPYZsOltbl75RCSr96pzyWbzw+9FEPQ4UD8KnLuVh0/nmzkmY7KGNYe6sCrX74PfStasProcbhHRrSyECtX4tJVLHktNhTULBL9rS2o7+3NeH5yqWiWoMuJ/uXNWHK5J+3MicoYvDXVOPqp3WjqugBRUTDhqcWFDevTFn0K2+05t9/GjcY880Lm/0cumUy4tL4yvgAjNgOcE9GM52uzMgxRi5YEHLHqEbYbyiKI00kStrz3fsbzE0Fv0OHAG1/6ImRDAftqkcWBMQRd12Y3ZM3AYO6+dIODAAB/dTUO3rr3mtzvYkRBzSLRtXEDNh34CDopnrFGQmK302wH9t2Ou37xKxgjkZTrqoxBNujx/mfvwmRtDfra0lTfvQJ9rSugiCJEJf3yCofWzG28fm6S4WISM+sQNelgjKZPamQAJuqsiNjLYKlplqauC3OqP8+UeLxvf/5uBNyugoyJkCvFBSH3THkZHGyUg7LIqenu7sbXv/51tLS0wGw2o7W1FY8++iikK0xgXYxiZjNev/cPETcYkuu0wFQXXUHAe39wV8aCcyGnEy888FV0bm1HfKqhmyyK6Nq4AS888NWUtedrQTKZcGrHtow7wRmAo5+6kbY3MobRRjsk43Se0MyfCY+lLAMaADCFw3MSNdNeLpJ5poqQUjGwvDnr+SpjtLPpGimLmZrOzk6oqoqf/vSnaGtrw8mTJ/Hggw8iFArh8ccfL/bwysZYQwOe+fM/Q9vJ02jo7gZTVYw2NOD85o0I56hGGbHbcPDWW3Bo7x7o4nHIev2CBhVHd98IMS5j3VR+TaJIlSoK6LjpJnQVcdtnKdFLSjK3JtHqQdYJmKi3IlomHbfTCdvteW3/D19B0mY+dJIESyAA2WDI+bdBSC4XNqxH+/sfak2E07yvGeeLqpP2QmKcX2WXsSL54Q9/iJ/85Ce4ePFi3tfx+/1wOp248dtPQWdcvL0xyoklEEDLmU4YwxGEHHZcWrtmXo0MK5kpJMHTm1p4D5juZTTU7ETcVBbHLXMIsoz7/uXfoI/FMtYLGauvx8tf/fI1vV9TKIQtv38frafOJJc/x+rrcPTGGwpW1XbBqBzmkARR5lB0DBGrASiDhPFKUTM4iNv+55nkbr7EtnHGOQ7sux3nN28q7gBLnBwL44Mf3QufzweHI3O39vL8xAPg8/lQVVWV9TKxWAyxGdtB/X7/Qg+LXGNhux2ndu4o9jBKD+eoHkzfkZsBAAeqhkIYXl5+bR8ArUnrJ7fuxe6XXpmTi6BObV0+dMuea3qfplAId/3iV4DK4HfVwhCLwBr0oWp4GLc+8yze/8yduLhh/TW9z0KxTkbhHglDVHny+VQFBq/HgqCrfGoWlbOxJUvw2//n62g7eUrr/6QoGGtYgrPtmxFw518hnWRXlkFNV1cXnnjiiZxLT4899hj+/u//vkCjIqRwTOE4dFkaWDIApqgMXUyBbCzP2hYXNqyHIorY9u57yc7cAOCtrcHHt9+K0aUN1/T+1h06js72mxB0TeeI2SbH0XrqIFzjQ7j+tTfQu7Kt7CpPW30x1Ey1UgCmA0SmclRPnR6iwKYgJLMZp3dsx2laalowRV1+euSRR/AP//APWS9z5swZrFmzJvnv/v5+3HzzzdizZw/+4z/+I+t1083UNDU10fITKXs2bxRVw6GcW9+HG+1lnVsDAOActQMDMIUjCDod8+7cng+LPwJPX1DLT2IzcsW4CnBg08evwz06iI/uuA3n2jdf8/tfMJxjaZcXopK+RgoHoIoMfW3ustjqTxavslh++s53voP9+/dnvcyKFdPr2AMDA9i7dy9uuOEG/Pu//3vO2zcajTCW2VEVIflQRZZXLZ9yKLKXE2MpRRyvOc5RNRzWttTO/mJnAgCOc5uux/a3n4Njwrtw41gAprAMnZK9kriocJjCcUStZR78EoIiBzW1tbWorc2vPH1/fz/27t2Lbdu24Wc/+xmExb6dlyxqEasBKgOEDN9XicJ7MXNZrjAXlCEqQ1SQeaaCMUStDgTctYhfQcHHYhKU7B2nE0S5LPeLEDJHWXzi9ff3Y8+ePWhubsbjjz+O0RkdeesXeQE2sjhxkcFXbYZ7LJL2fAZgstZKSwp50MXz++KPma3oXr16gUdzbcn6/A7+8r0cIaWuLIKa119/HV1dXejq6kJjY2PKeWW6I52Qq+avNoNxwDmeGthwBng9VoSctPSaD1XM7wt9orYGvprqBR7NtSWZdIjrBejiasacGlkv0IweqRhlEZ7v378fnPO0P4QsWozBV2tBX5sbE3VW+GrMGK+3oq/NjaCbdrPkK2rRQRFZxgrWACDIcXTcvKtgY7pmGMOER9sUMfvxJbZ2S0YR5mAc+ljmthSElAsKzwkpc6pOoCDmajCtXkvNVN2fdEYbXVDKtEuyIaYVEUxbzwiANRiHNRgHAMRMIsbrbWVbtJEQeucSQoqHaztvrL4YRIVD1gsIOo2QTLqC5gOFnCYwDrhHwhBmFqibWsor2wJ1nMM+mX9/LENUQX23D0MtTsSN9PVAyg+9awkhRcFUjto+P8xhORlEcAD2yRiCDgPGl9gKGtgEXSaEHEaYgxJEWYWiExCxGcp6WzzjgG4eO5sSj9Q1HMLosvKsRk0WNwpqCCFFUTUYhCms5XEkq9xO/bb6Jcj6CHy1hS2SyQWGsKNyEqw5w5w2E7kwAOawDEFWoerKIu2SkCR6xxJCCk6MK7AGpIxftgyAwxsFU4uwGYBziHEFoqQA5b4ZgTGEbfqsSdBprwbAEIkvxIgIWVA0U0MIKThzKJ5z9kBQOQxRGTGLviBjAuew+WJwjEegn6pdo4gMfrcJ/mpz2db88VebYQnG5z1jo5dU5J+NQ0hpoJkaQkjhcA5TUIJ1MpbX7AEr4EyJazSM6qFQSjE+UeFwjUVQ2xco21kbyazH6FJ7cikq30dRyOeekGuFZmoIIQUhKCo8vX4Yo0peswYcgFSgHTiGSBzOCW1eIt3WZ0soDutkDBAYdHEFiiggbDeUTc5JxG5A38oqWP0xWCejMEaVnM+/XCaPjZCZKKghhBREbV8Ahmj6mimzcaCgQYNtauYo07g4gOrh1Do2VcMh+KtMmKy1lMXSFBcYgi4TVMZgGgzmvLxEVYZJGaJQnBCy4AwRGaaInFcwwwHIBgETddYCjExjiGWfuZi5O2vmj2MiCleG/lulKmI3IFu3Kw5AMgiQqU4NKUMU1BBCFpw5KOWVy6HoGCZrzBhsdhZ0aUcVsrdJANLP4jAAjvFI3t2wSwEXGCY96bfKJ54Db52tcAMi5BqiUJyQMiDIKmy+GIyRODhjiFr0CDmM4GLpL3sA+SedDjc5IRvFBR7NXCGHAabwlW9htgSksqo6HHCbAAa4RiMQZmybV3QCxuutiFoLtOOMkGuMghpCSpwpKKG2PwA2Iy6wBCS4RsMYabJDMpf+F5Bk0uVcelIFrWN0MYQdRjjHIxm7WefClDLbKcQYAm4zAk4TzKE4BEWFohcRtRS2PQUh1xotPxFSwnQxBZ6pgGZ2Poegcnh6AxDk0l/6CNsNWTthcwABlwkoUksCLjAML3MgbhCT48l76zO0HKCyJDBE7AaEXCZtdoYCGlLmaKaGkBLm8EYAnjmfQ1C1gnH+anOhhzZvEYse1oCUcloicJBMInw1hW2JMJuiFzHY4oQpLMMUkqbGpYNtMgpTOH2SMwegigwRW3l28Cak0lBQQ0gJMwcztxKYeZmSDmo4R01/AJZg+irCqsgw0ugojcaRjCFq1afklEhGEUsu+wGVp4w/EZCN1xe28SYhJLMynTMlZHFgOdZAGFCc/kjzYArLsGYIaBgAQeGw+mOFHlbeZKMOg81ORKypPZQkk4iRJjsidpqlIaRU0EwNISUsZtJl7ZPEUfpF0qyT0ZwVhO3eKAJVpTvbJBtFjDY5IMgqdHEVKgP0ce3/TaE4JdgSUiJK+9OQkErFOay+GOyTUegkFarIEHIaEXCZUuqzBNwmWEKZtxozTCXYljCdnH1HEQMglkGyM6AtlRn9cbjGUrdCy4mt0JRbQ0hR0fITIYWmcnh6/agZCsEQVSCqHPq4CudYBA2XJqGLKcmLRq16+N1GAKm7cRL/P+GxIG4q7WOTbLueElSxPD6K7N4oqkbCKQENoAVlnr5AMsGYEFIc5fFJQkgFcY2FYQrLAFKXZBL5JbX9MzpCMwavx4rRBhtiJl1yq3HUosdwk72kl2wSQk5T1pkaDiDoMhZqOFeMKRyu0XD686Z+u0fSn08IKYzSPsQjpMIwlcM+Gc34Jc8AGCQFxrCMWGIHDmMIO4wIO4wpwU65iNj0iJp1MKbp/cShtUYo9SU0ALAEJQhZppwYtB5SuphcXn2TOIdOUsHAEdeLRasVRMi1UEZ/eYSUP52kQMiRPsIBGCPx6aBmpjIKZpIYw0ijHdVDIVgC2hb1ROJwzKTDWIOtoH2erpSgqDkTngFAlDnk0p94AjiH3RuFYyIK3VROkyowBFxG+GospbHFnpB5oqCGkFJUjsFLFlwUMLbUDjGuwDS1mytm0pV8PtBMik7Iq4WCUqRWD/PlHg7BMRlLyXcSVA7HRBTGiIzhRjuMMQWMc8QNIhR94XtyETJf5fOJQkgFiBtFKCKDmKVXEIOWM1OJFL2IkKs8vxwjNgNUgYHNKsKXwKEFarKh9B+fIRKHY1KrDTT7sTAAxoiMpi5vcrmNA4gbBQRcJoScJprFISWrPA4pCKkUjMFfZc7aAylq0pV87ZnFiAsMEx5Lcvks5TwAYIC3rritHvJlmzVDMxsDUvKHGAB9TEX1cBiN5yfgGI9M53cRUkLok5OQAvNXmaCPybD5pWSORuLrQTZoyzSkNIVcJnDG4B4NJ/NQAG0GbqLOOt0xnXOYgxIswTjAOSSjDiGXsWS2ruslZd7dyBOXFzjgHg0DnMNf5H5dhMxGQQ0hhcYYxpfYEHLKsE1GoZMUrfje1A4nmtovbWGnEWGHAcaIDEHhkPUC4kYxmQclSgrqev3Qx9VksGqFBPdYGGNLbNoutiJTp2oHXc07zTUeQcBtAi+RQI0QgIIaQoojTePESiTIMpq6LsA+OQnJaELPqpWIWivg6J4xxNLlPXGOul4/dHFtFoelnoWagSCG9ML0jE6RhOxGbRbpanDAEpAQKoPt+GTxoKCGELIgmjvP4vpXX4cxFoPKGBjn2PXGmzi9fSs6br4JXKi8I3xLQII+nn7PfmKZ0TERxdjS4gY1YbsB6jDA1KubrTEHKaghpYWCGkKKQJBV2Hwx6CUFqsAQthsQM1dOU8SGi5dw8/++mPy3MJVUyjjH+oOHAQCH9+4pwsgWliUoZV3WYdACH3Be9Nf6agMaBsAajCMyGaXAhpQMCmoIKTCbN4Kq4dRy+g5vFFGzDqON9pJJJs3EFAph5fGT8PT1AWAYWtaErk0bEDNPt2zY+t774Iwlg5mZGIB1hzpwaucORK3Wwg28AFgefTlLIWwVePpt6fPFoSUNh5zGogdphAAU1BBSUI7RMNzjkbTnGSMyavsCGF7mKNkviKUXL2HPc/8LUVGSW3qXXrqEzR8ewFtfuAdDzctg93pRPTKS9XYY52g+dx5nt7QXYNSFI5lEmIOZz+fQdrgV+/VVBQZFYBDVzNuy80kkZgBEhcMUilOHclISSvuQkJAKYg7E4BqPZKwPwgCYIjIMERnmgISa/gA8PT5UDQZhiFxlUuc1YPd6sffZ5yDKMtjUkX7iR5Rl3PrMs7AEAjBGozlviwsCjJHclys3Qefcjuqz+d0l0ISUMQTdppzd00PW/I57sxWTJKSQKKghpBA4R/VgMBkEZLwYgNr+ADz9AVgCEsxhGTZfDEsu+1E1GCxqwbM1HUczVtMVOIegKFh19DiCdkfOL0umqgi4nAsxzKJS9CIm6rUltZnPQaK7esSqL5mO5L4qE+IGMX0hQQATdda869DIZdIaglQ+eicSUgDmYBxiHvkWwPRRbyJ4SPy2+WJwTBRvdqPxwoW0OTIJAudounABUZsVfa0roGZYYuEA4gYDela2LdBIiyvoMmGkyYGoRT9dVFEvwOuxYLTRXvSlpwQuChhqdiDgNkGdMSTJKGJkqR1BtwmSSYe4XshaATuuF7Qkd0JKAL0TCSkAXVzJO0ch23mOiQj8VabCfTGqHKZIHILCETXbYfP5MVHXiKCjCoIio2aoF5aQP3lxQVEAAIf23gxPXz/0kpQSCCX+76Pbb4Oir9waPckaRJyDcYAzlEwwMxMXBXjrrJistUCUVXCG1MaVjCFq0cHmm7ura+aMTik+NrI4UVBDSAEoYn4dnnMFPqLCYYjKC1+8jXPYvVE4xyLJZNLTO24DU1VwQdB+M+Di+h2oGbyMNR2/h6AqGGloAAD4q6rw0le+jO1vv4vGixeTj2mypgYdN+1GX1vrwo6/VDCmBTQljgssbSNO22QUdp+U8XpRi44ShElJoaCGkAKI2PRQWWqTwJkSJ+fz/ccKkFbjmIhq/X1m4VNH5DML543VNeHUjr3Y9NHrOLu1PXm6v7oKb33x8zAHg7D6/ZCMJvir3HRUXy44h3MskjHQZgBMYRliXEmd3SGkiCioIaQAuCjAV2NJHygg/9olnGk5DwtJUFS40owTQPqARBDg9SzFx7fdgYm6ujlnR2w2RGy2azxKstD0MSWlaWcmlqCEQCns6CIEFNQQUjD+Kq3qqnMsnJxtybUbaiYOIOgwzruBoD4qwxqQwFSOuEFEyGHIehsWf+blhsxj4xhpaJn39UjpYnnutMun4CAhhUJBDSGFwhj81WYEXFozQZs3AlNUyXm1xFdL3CjC68m/GSRTOWr6A7CE4im7V9wjIUzUWxFypi9tL+ZxdJ7m3iBkKeRGpnCOut4+tJzphDEaRcDpRNfGDfBXVxV7ZHPIejHnLCKD9r4kpFRQUENIgXFRQMhphH0ic77CTIrIEKgyI+A2gQtMK84XlMA4R9yoQ8huAIS5t1LTH4A5pBXtSzmXA9WDISiikDbJU9FdWaUHmfIqstJJEvY++zwaLvdAFVgyWt34yUGc2LUDHTd9qiD5RkzVks0Z1yogZ2rLoeoEhOwGbZYvzfkcgKJjiFR4p3lSXiioIaRIMhWym4kDGGh1gwsMgqLCc9kPU0ROSSx2DzOMLbUhap0OUPRRGZZQ+irEiW7RzrFw2qAmbDegajg078eTqKZL0rvxpVdQ39MLAHNmtTZ+fBBhux2dW7ekva4upsDqj0FUVMh6ESGncf7BJ+dwjUVg90YgTE3GcQAhhwETtRaYogpEWYWiF7RAhTF466wwRWSIsjp3OzcDxhpKp+4OIQAFNYQUjaIXweNqxsCGA1BFBi4wgHN4ev0wTC1XzbyOoHJ4egMYXO5E3KT9SVsCubtFm6IKBFmFOuvLUdUJ8NWY4RpL36Nq9hgZAF+NGUqaLcFEY/dOYvm58xnP5wA2fvQxzrZvTtlZlqhEbfNLKUuIrtEwJmst8Ffnl6AryArqegLQS0rKe4IBsPolWP1SMthl0GYHJ+qsCDuMGFzuhHM8AttkFALXLhO2G+CrNiffb4SUCnpHElIkQacR5nD2nk6+qeRiUzgOY4b8m+TMy3gEY0vt2ml5JnkKKke6DBpftRkqB9zjkZxtHcbrrQi50ufnEM3SixfBWebt+AyAJRiCe3Q0ZQeZezgE61Ti9uzXwT0ahioyBHM898ZwHJ4ef8by8bODHAAQFI7agSBGAYQdRnjrrPB6LBAUri2dpVnuJKQUUFBDSJGEHQbEvCIMUWXOFxYHIOumv7As/twzL5aApPWGYukLqc2msiz5M4xBzeM2BACxhS4EWAFEWQYHA8vRFUuUpwNXQVZhn4xlnclzjoW1ZT/GIMYV2L1RWP0SBFVFXK/tdHONZQ9M00kEyq7RMMJ2g7bExBhUHQUzpLRR7ydCioUxDDc5ELYb5nzVRS16DC13Jbde57OziAHJ5NOQwwg+nYs6BwcQdGqJx5nkuwtKVGhPby5ejydr3ywAUAQBvhm7oCzB7FvrGQCdzGGIKtBHZSy55INjIgqdrEJQAUNMgXs0AsbzLxsw+/b1cRXGiHwF1yakOGimhpAi4qKAsaV2iHEFprAMcI6YRT9npiWeY9YksRMlsSzABYbxJTbUDATT9uyR9QJ8tdnzMWR9fq0drnS31GIysLwZAYcD1kAgbXCjMoZL69ZCMk0vJbE8t8gzVUXtYAjCrMTzazWnIii0VZ+UD/o0IqQEKFM7WkIuU9qlo6Ar986iwKzcirDDiOEmB2KW6WMXlQEBtwlDy51QRQFMUWEKSjAFJQizZmYiNgNUIftsT9Sky2upa9FjDO997rNQdLo53ctVxhBwuXBoz00pp8eNYl6749zDIejkzAnnV0vR09cEKR80U0NIGVD0Iry1FlSNhtPOvEgmEYGquTMvMasew1YnBEUFUzkUUdBmc1QO93AINm80eWTDAUQsOowvtUMVBXCBweuxonoolL5DMwO8dfkXA1zsxpYswYsPfAXrPzmIFafOQKcoiJrNONu+Gad2bEPclBqURi16yDphznbqhMRrYpAWZvmPQ5shnNmWY877iJASQ0ENIWUiUG2GohfgHI/AENMSSlWBIeAywldjyZofo4oCkPhu4hy1U4X5Zi9XWMIyTF1eDKxwQdGLCLpM4IzBNRqCTp6es4kbRUzUWRe+W3iF8VdV4cCd+3Bg3x0QFAWqKGau88IYxhpsqOv1a/nfs8+e9ftaSrzS3jorwBiM4TicY2GYw1p+jcqAoMuk7ZKj5UdSQiioIaSMRKx6CIoKXUwFF7UlJ3WelXxNoXjGwnyAtu24/rIP/a1aR+2Q04iQwwBjRIagcMh6QSuNT0XXrhxjUHW5P35jFj0Gm51wjoVhCcavKIBJzOjMp3Fq3KAFrTGrHuaAhNr+QMr5Agfs3ijMQQlDzU4KbEjJoKCGkFLAOYxhGfbJKPSSAlVkCDmM2i6mqRkYmzcK90gopdaJczwKf7UZkzXmvIMMmy+Wc3u4TuYwB+OI2KcqDjOGmIVmZQqCc5jCcdgmYzBEZe29YDci6DKhri+Q+/qzMAABpwE2X/bdVIm31USdRSslwJjWP2wwmLyd2beri6twjYUxUU9d2ElpoKCGkGLjHFVDIdhnBBscgDEswzEewfAyB0xhGdUZWhc4xrUeUr7aWfktXAtMdHEtSArbtO7cuvjcujhzhgTA6o9NBzWkMNK9F+KAIRrWit7lcxNInZnxu4xTu+dyd18P2fQwRmQYoiHETCIEhWctJ8CgBclejzXr8ichhUJBDSFFZvdGYfPFAMzNk9DFVXj6AhBkNePsCgPgmIjAX2VK1rUxByRUDwUhKjx5BF7NQvBVmaGIAjiyBzYMtJW3GGyTMdgzvBcElee1hCTrGACGuFGAr8YCyayHazSc874ZAGtwelnS7tN+5+zUzQFdXEHcSF8npPhoIZSQYuIcjoloxrMZtCJqOiV780uBA+apLyRTSMuBSAQlLPHDAdd4BJyxvGZqZAN9PBQU53BMdW5PJ/E6ZttiD2hLhzpZhSUkwz0ShiCrUMTcsyiJ4CXxM/N+c8l3FomQhUafWoQUkS6u5qwxks98Ccd01WHXiHZUnuk2LUEJsi57wX4G5OwpRK4tUVahz9LgFJgussgx/b6Y+f9AalBijMio6/EjlGMZcT5JxLOvFzOKUOaZrE7IQqGghpBiukYrPAxaBWCdpMAYy50z43eboApzA5vEv/0uIyTqwFySwnYjJuqtkEwiFIFBnfoUz7Q0aZAUePoCiGeYebuagEbr0E61ikjpoKCGkCKSDULOpQEGQDIIWZcdZB1DdGq7dz4YGPpb3Qg5UvtOKSLDhMei1SchBaXoBMi6zK8zoL0XohY9gi4Thpa70LeqClzIvpzIoS1h6qeK9F1tHJ2cGWJah3ZKJielhA7FCCkmxhBwm+DM0Ek50adpbIkN9T1+YFYRtsQXVNBhhNUXy6sPU2JWh4sM4w12TNRx6CUFnIHqzxQTY/BXmeAeSZ/Uqy09CYjYUrfWC3L2MCXdqykZBPirzJANItxDQRik/NsshBwGSCYdQk6jVtSRkBJCQQ0hRearNsMQkWEJxVOWAji0BMzRRjviRh2GljvhGg3DPKMImyIyiAqHa0ayscqQsTMzh9bsMmKbPrrmIoNkpo+CUhBwm2CIyLAFpJSt2YD2XhhptE8HnZzDPhmd99JRorVC3ChCMusRqDKjeih9uYCZEsnj40tsFPiSklV2YXYsFkN7ezsYYzh69Gixh0PI1WNa4DK2xIaYWQdFZIjrBfiqzRhY4UpulY0bdRhtdKCvzY3B5U6ErXqIaXZFJYrzpcuXYQAm6qimSMliDOMNNowstSNq1Xo/xQ0ifDVT74VEnhPnqOkPwD2ce6t2OhzTu+VCTiPCNv2chOPZl2cAJmssFNCQklZ2h2ff/e530dDQgGPHjhV7KIRcO4l2BM7c3bhVnQDE1YytDhJH94rIoJtRa0bWC/B6LIjYc98HKSLGELEbsuaq2HyxK26bkLwbzpP3J5niqOvrQ8zoQtysVQeeGeBwpgXDYQe9d0hpK6ug5uWXX8Zrr72GZ555Bi+//HKxh0NI0Vj9uVsdCCpHf4sTosyhiozyZSqI3Zu5tlE+GJDc3dZy+gx2/077PGWcQxF1iJqtGFuyDN1r1mK8vlZLKKf8GVIGyuZdOjw8jAcffBC/+MUvYLHQFkKyuIly7l1OAgcUvYiYVa8tW1BAUzH0Obbt51pKUkSGsN0A59g4dv/uZTDOIXBtKVOnyLAFfWg+fwI3vfgUBDVEAQ0pG2XxTuWcY//+/fjGN76B7du35329WCwGv9+f8kNIJchnl5MqMHCKYypSPq+rKswNbvjUdUeXagnHa44cAZC5xg0ArDly9KrGSkghFTWoeeSRR8AYy/rT2dmJJ554AoFAAN/73vfmdfuPPfYYnE5n8qepqWmBHgkhhRV0GnMeqQdcRpqdqVBhmyFnPRuvxwpvrQWyXvuYVxkQchowtNyZ7Lje0H0ZAs98SwLnaOi+fA1HTsjCKmpOzXe+8x3s378/62VWrFiBt956CwcOHIDRmJqktn37dtx///34+c9/nva63/ve9/Dwww8n/+33+ymwIRUhbtIh4DTC5ovNCW4SpfT9VeZiDI0UgL/aDOuMbd8zJerZhBxGQGAIVJsBztMHuPn24CCkTBQ1qKmtrUVtbW3Oy/34xz/G97///eS/BwYGsG/fPjz55JPYtWtXxusZjcY5gRAhlWKi3gpFL8AxEYEwlWLDAUSsekzUW7VdUqQixU06jC61o2YgkBJ0JAorjjQ5gJnb9jPM2A02L4PN58s4W6MyhqHmZddw5IQsrLLY/bRsWeoflc2mbTlsbW1FY2NjMYZESPExBl+NBf4qM4yROJgKSEYRioGaCy4GEbsB/W1uWH0xGKKythXcqkfYbsh72bFzaztWHTueccYncRlCygUdyhFS5rjAELVqdU0ooFlcVFFAoMqM8QY7xpfYtDoy88ijmqytxYd33qHd1ozrJf7/wzvvwGRNzbUdNCELqCxmamZbvnw5eJbkNkIIIfnp2rQR4/X1WNPRgSWXewAAg83NOLNtCybzSA8gpJSUZVBDCCHk2vF6anHgzn3FHgYhV42WnwghhBBSESioIYQQQkhFoKCGEEIIIRWBghpCCCGEVAQKagghhBBSESioIYQQQkhFoKCGEEIIIRWBghpCCCGEVAQKagghhBBSESioIYQQQkhFoKCGEEIIIRWBghpCCCGEVAQKagghhBBSESioIYQQQkhFoKCGEEIIIRWBghpCCCGEVAQKagghhBBSESioIYQQQkhFoKCGEEIIIRWBghpCCCGEVAQKagghhBBSESioIYQQQkhFoKCGEEIIIRWBghpCCCGEVAQKagghhBBSESioIYQQQkhFoKCGEEIIIRWBghpCCCGEVAQKagghhBBSESioIYQQQkhF0BV7AIXEOQcAyLFwkUdCCCGEkHwlvrcT3+OZMJ7rEhWkr68PTU1NxR4GIYQQQq5Ab28vGhsbM56/qIIaVVUxMDAAu90Oxlixh7Ng/H4/mpqa0NvbC4fDUezhLDr0/BcfvQbFRc9/8VXaa8A5RyAQQENDAwQhc+bMolp+EgQha4RXaRwOR0W8mcsVPf/FR69BcdHzX3yV9Bo4nc6cl6FEYUIIIYRUBApqCCGEEFIRKKipQEajEY8++iiMRmOxh7Io0fNffPQaFBc9/8W3WF+DRZUoTAghhJDKRTM1hBBCCKkIFNQQQgghpCJQUEMIIYSQikBBDSGEEEIqAgU1i0QsFkN7ezsYYzh69Gixh7NodHd34+tf/zpaWlpgNpvR2tqKRx99FJIkFXtoFetf/uVfsHz5cphMJuzatQuffPJJsYe0aDz22GPYsWMH7HY7PB4P7rnnHpw9e7bYw1q0fvCDH4Axhm9/+9vFHkrBUFCzSHz3u99FQ0NDsYex6HR2dkJVVfz0pz/FqVOn8I//+I/4t3/7N/z1X/91sYdWkZ588kk8/PDDePTRR9HR0YHNmzdj3759GBkZKfbQFoV3330XDz30ED766CO8/vrriMfjuOOOOxAKhYo9tEXn4MGD+OlPf4pNmzYVeygFRVu6F4GXX34ZDz/8MJ555hmsX78eR44cQXt7e7GHtWj98Ic/xE9+8hNcvHix2EOpOLt27cKOHTvwz//8zwC0fm9NTU341re+hUceeaTIo1t8RkdH4fF48O677+Kmm24q9nAWjWAwiK1bt+Jf//Vf8f3vfx/t7e340Y9+VOxhFQTN1FS44eFhPPjgg/jFL34Bi8VS7OEQAD6fD1VVVcUeRsWRJAmHDx/GbbfdljxNEATcdtttOHDgQBFHtnj5fD4AoPd7gT300EO46667Uv4WFotF1dByseGcY//+/fjGN76B7du3o7u7u9hDWvS6urrwxBNP4PHHHy/2UCrO2NgYFEVBXV1dyul1dXXo7Ows0qgWL1VV8e1vfxs33ngjNmzYUOzhLBq/+c1v0NHRgYMHDxZ7KEVBMzVl6JFHHgFjLOtPZ2cnnnjiCQQCAXzve98r9pArTr6vwUz9/f248847ce+99+LBBx8s0sgJKYyHHnoIJ0+exG9+85tiD2XR6O3txV/+5V/il7/8JUwmU7GHUxSUU1OGRkdHMT4+nvUyK1aswJe+9CW88MILYIwlT1cUBaIo4v7778fPf/7zhR5qxcr3NTAYDACAgYEB7NmzB9dddx3+67/+C4JAxxPXmiRJsFgsePrpp3HPPfckT3/ggQcwOTmJ559/vniDW2S++c1v4vnnn8d7772HlpaWYg9n0Xjuuefw+c9/HqIoJk9TFAWMMQiCgFgslnJeJaKgpoL19PTA7/cn/z0wMIB9+/bh6aefxq5du9DY2FjE0S0e/f392Lt3L7Zt24b//u//rvgPlWLatWsXdu7ciSeeeAKAtgSybNkyfPOb36RE4QLgnONb3/oWnn32WbzzzjtYuXJlsYe0qAQCAVy+fDnltK997WtYs2YN/uqv/mpRLANSTk0FW7ZsWcq/bTYbAKC1tZUCmgLp7+/Hnj170NzcjMcffxyjo6PJ8+rr64s4ssr08MMP44EHHsD27duxc+dO/OhHP0IoFMLXvva1Yg9tUXjooYfwq1/9Cs8//zzsdjuGhoYAAE6nE2azucijq3x2u31O4GK1WlFdXb0oAhqAghpCFtTrr7+Orq4udHV1zQkkaZL02rvvvvswOjqKv/u7v8PQ0BDa29vxyiuvzEkeJgvjJz/5CQBgz549Kaf/7Gc/w/79+ws/ILLo0PITIYQQQioCZSsSQgghpCJQUEMIIYSQikBBDSGEEEIqAgU1hBBCCKkIFNQQQgghpCJQUEMIIYSQikBBDSGEEEIqAgU1hBBCCKkIFNQQQirC4OAgvvzlL2PVqlUQBAHf/va3iz0kQkiBUVBDCKkIsVgMtbW1+Nu//Vts3ry52MMhhBQBBTWEkLIwOjqK+vp6/J//83+Sp3344YcwGAx48803sXz5cvzTP/0T/uRP/gROp7OIIyWEFAs1tCSElIXa2lr853/+J+655x7ccccdWL16Nb761a/im9/8Jm699dZiD48QUgIoqCGElI3PfOYzePDBB3H//fdj+/btsFqteOyxx4o9LEJIiaDlJ0JIWXn88cchyzKeeuop/PKXv4TRaCz2kAghJYKCGkJIWblw4QIGBgagqiq6u7uLPRxCSAmh5SdCSNmQJAlf+cpXcN9992H16tX4sz/7M5w4cQIej6fYQyOElAAKagghZeNv/uZv4PP58OMf/xg2mw0vvfQS/vRP/xQvvvgiAODo0aMAgGAwiNHRURw9ehQGgwHr1q0r4qgJIYXCOOe82IMghJBc3nnnHdx+++14++23sXv3bgBAd3c3Nm/ejB/84Af4i7/4CzDG5lyvubmZlqkIWSQoqCGEEEJIRaBEYUIIIYRUBApqCCGEEFIRKKghhBBCSEWgoIYQQgghFYGCGkIIIYRUBApqCCGEEFIRKKghhBBCSEWgoIYQQgghFYGCGkIIIYRUBApqCCGEEFIRKKghhBBCSEWgoIYQQgghFeH/BxmNl/DCcQGPAAAAAElFTkSuQmCC", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot the decision boundary for logistic regression\n", "plot_decision_boundary(lambda x: clf.predict(x), X, Y)\n", "plt.title(\"Logistic Regression\")\n", "\n", "# Print accuracy\n", "LR_predictions = clf.predict(X.T)\n", "print(\n", " \"Accuracy of logistic regression: %d \"\n", " % float(\n", " (np.dot(Y, LR_predictions) + np.dot(1 - Y, 1 - LR_predictions))\n", " / float(Y.size)\n", " * 100\n", " )\n", " + \"% \"\n", " + \"(percentage of correctly labelled datapoints)\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", "
**Accuracy** 47%
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Interpretation**: The dataset is not linearly separable, so logistic regression doesn't perform well. Hopefully a neural network will do better. Let's try this now! " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4 - Neural Network model\n", "\n", "Logistic regression did not work well on the \"flower dataset\". You are going to train a Neural Network with a single hidden layer.\n", "\n", "**Here is our model**:\n", "\n", "\n", "**Mathematically**:\n", "\n", "For one example $x^{(i)}$:\n", "$$z^{[1] (i)} = W^{[1]} x^{(i)} + b^{[1]}\\tag{1}$$ \n", "$$a^{[1] (i)} = \\tanh(z^{[1] (i)})\\tag{2}$$\n", "$$z^{[2] (i)} = W^{[2]} a^{[1] (i)} + b^{[2]}\\tag{3}$$\n", "$$\\hat{y}^{(i)} = a^{[2] (i)} = \\sigma(z^{ [2] (i)})\\tag{4}$$\n", "$$y^{(i)}_{prediction} = \\begin{cases} 1 & \\mbox{if } a^{[2](i)} > 0.5 \\\\ 0 & \\mbox{otherwise } \\end{cases}\\tag{5}$$\n", "\n", "Given the predictions on all the examples, you can also compute the cost $J$ as follows: \n", "$$J = - \\frac{1}{m} \\sum\\limits_{i = 0}^{m} \\large\\left(\\small y^{(i)}\\log\\left(a^{[2] (i)}\\right) + (1-y^{(i)})\\log\\left(1- a^{[2] (i)}\\right) \\large \\right) \\small \\tag{6}$$\n", "\n", "**Reminder**: The general methodology to build a Neural Network is to:\n", " 1. Define the neural network structure ( # of input units, # of hidden units, etc). \n", " 2. Initialize the model's parameters\n", " 3. Loop:\n", " - Implement forward propagation\n", " - Compute loss\n", " - Implement backward propagation to get the gradients\n", " - Update parameters (gradient descent)\n", "\n", "You often build helper functions to compute steps 1-3 and then merge them into one function we call `nn_model()`. Once you've built `nn_model()` and learnt the right parameters, you can make predictions on new data." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 4.1 - Defining the neural network structure ####\n", "\n", "**Exercise**: Define three variables:\n", " - n_x: the size of the input layer\n", " - n_h: the size of the hidden layer (set this to 4) \n", " - n_y: the size of the output layer\n", "\n", "**Hint**: Use shapes of X and Y to find n_x and n_y. Also, hard code the hidden layer size to be 4." ] }, { "cell_type": "code", "execution_count": 118, "metadata": {}, "outputs": [], "source": [ "# GRADED FUNCTION: layer_sizes\n", "\n", "\n", "def layer_sizes(X, Y):\n", " \"\"\"\n", " Arguments:\n", " X -- input dataset of shape (input size, number of examples)\n", " Y -- labels of shape (output size, number of examples)\n", "\n", " Returns:\n", " n_x -- the size of the input layer\n", " n_h -- the size of the hidden layer\n", " n_y -- the size of the output layer\n", " \"\"\"\n", " ### START CODE HERE ### (≈ 3 lines of code)\n", " n_x = X.shape[0]\n", " n_h = 4\n", " n_y = Y.shape[0]\n", " ### END CODE HERE ###\n", " return (n_x, n_h, n_y)" ] }, { "cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The size of the input layer is: n_x = 5\n", "The size of the hidden layer is: n_h = 4\n", "The size of the output layer is: n_y = 2\n" ] } ], "source": [ "X_assess, Y_assess = layer_sizes_test_case()\n", "(n_x, n_h, n_y) = layer_sizes(X_assess, Y_assess)\n", "print(\"The size of the input layer is: n_x = \" + str(n_x))\n", "print(\"The size of the hidden layer is: n_h = \" + str(n_h))\n", "print(\"The size of the output layer is: n_y = \" + str(n_y))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output** (these are not the sizes you will use for your network, they are just used to assess the function you've just coded).\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
**n_x** 5
**n_h** 4
**n_y** 2
" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 4.2 - Initialize the model's parameters ####\n", "\n", "**Exercise**: Implement the function `initialize_parameters()`.\n", "\n", "**Instructions**:\n", "- Make sure your parameters' sizes are right. Refer to the neural network figure above if needed.\n", "- You will initialize the weights matrices with random values. \n", " - Use: `np.random.randn(a,b) * 0.01` to randomly initialize a matrix of shape (a,b).\n", "- You will initialize the bias vectors as zeros. \n", " - Use: `np.zeros((a,b))` to initialize a matrix of shape (a,b) with zeros." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# GRADED FUNCTION: initialize_parameters\n", "\n", "\n", "def initialize_parameters(n_x, n_h, n_y):\n", " \"\"\"\n", " Argument:\n", " n_x -- size of the input layer\n", " n_h -- size of the hidden layer\n", " n_y -- size of the output layer\n", "\n", " Returns:\n", " params -- python dictionary containing your parameters:\n", " W1 -- weight matrix of shape (n_h, n_x)\n", " b1 -- bias vector of shape (n_h, 1)\n", " W2 -- weight matrix of shape (n_y, n_h)\n", " b2 -- bias vector of shape (n_y, 1)\n", " \"\"\"\n", "\n", " np.random.seed(\n", " 2\n", " ) # we set up a seed so that your output matches ours although the initialization is random.\n", "\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " scale_factor = 0.01\n", " W1 = np.random.randn(n_h, n_x) * scale_factor\n", " b1 = np.zeros((n_h, 1))\n", " W2 = np.random.randn(n_y, n_h) * scale_factor\n", " b2 = np.zeros((n_y, 1))\n", " ### END CODE HERE ###\n", "\n", " assert W1.shape == (n_h, n_x)\n", " assert b1.shape == (n_h, 1)\n", " assert W2.shape == (n_y, n_h)\n", " assert b2.shape == (n_y, 1)\n", "\n", " parameters = {\"W1\": W1, \"b1\": b1, \"W2\": W2, \"b2\": b2}\n", "\n", " return parameters" ] }, { "cell_type": "code", "execution_count": 121, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "W1 = [[-0.00416758 -0.00056267]\n", " [-0.02136196 0.01640271]\n", " [-0.01793436 -0.00841747]\n", " [ 0.00502881 -0.01245288]]\n", "b1 = [[0.]\n", " [0.]\n", " [0.]\n", " [0.]]\n", "W2 = [[-0.01057952 -0.00909008 0.00551454 0.02292208]]\n", "b2 = [[0.]]\n" ] } ], "source": [ "n_x, n_h, n_y = initialize_parameters_test_case()\n", "\n", "parameters = initialize_parameters(n_x, n_h, n_y)\n", "print(\"W1 = \" + str(parameters[\"W1\"]))\n", "print(\"b1 = \" + str(parameters[\"b1\"]))\n", "print(\"W2 = \" + str(parameters[\"W2\"]))\n", "print(\"b2 = \" + str(parameters[\"b2\"]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "
**W1** [[-0.00416758 -0.00056267]\n", " [-0.02136196 0.01640271]\n", " [-0.01793436 -0.00841747]\n", " [ 0.00502881 -0.01245288]]
**b1** [[ 0.]\n", " [ 0.]\n", " [ 0.]\n", " [ 0.]]
**W2** [[-0.01057952 -0.00909008 0.00551454 0.02292208]]
**b2** [[ 0.]]
\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 4.3 - The Loop ####\n", "\n", "**Question**: Implement `forward_propagation()`.\n", "\n", "**Instructions**:\n", "- Look above at the mathematical representation of your classifier.\n", "- You can use the function `sigmoid()`. It is built-in (imported) in the notebook.\n", "- You can use the function `np.tanh()`. It is part of the numpy library.\n", "- The steps you have to implement are:\n", " 1. Retrieve each parameter from the dictionary \"parameters\" (which is the output of `initialize_parameters()`) by using `parameters[\"..\"]`.\n", " 2. Implement Forward Propagation. Compute $Z^{[1]}, A^{[1]}, Z^{[2]}$ and $A^{[2]}$ (the vector of all your predictions on all the examples in the training set).\n", "- Values needed in the backpropagation are stored in \"`cache`\". The `cache` will be given as an input to the backpropagation function." ] }, { "cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [], "source": [ "# GRADED FUNCTION: forward_propagation\n", "\n", "\n", "def forward_propagation(X, parameters):\n", " \"\"\"\n", " Argument:\n", " X -- input data of size (n_x, m)\n", " parameters -- python dictionary containing your parameters (output of initialization function)\n", "\n", " Returns:\n", " A2 -- The sigmoid output of the second activation\n", " cache -- a dictionary containing \"Z1\", \"A1\", \"Z2\" and \"A2\"\n", " \"\"\"\n", " # Retrieve each parameter from the dictionary \"parameters\"\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " W1 = parameters.get(\"W1\")\n", " b1 = parameters.get(\"b1\")\n", " W2 = parameters.get(\"W2\")\n", " b2 = parameters.get(\"b2\")\n", " ### END CODE HERE ###\n", "\n", " # Implement Forward Propagation to calculate A2 (probabilities)\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " Z1 = np.dot(W1, X) + b1\n", " A1 = np.tanh(Z1)\n", " Z2 = np.dot(W2, A1) + b2\n", " A2 = sigmoid(Z2)\n", " ### END CODE HERE ###\n", "\n", " assert A2.shape == (1, X.shape[1])\n", "\n", " # Values needed in the backpropagation are stored in \"cache\". This will be given as an input to the backpropagation\n", " cache = {\"Z1\": Z1, \"A1\": A1, \"Z2\": Z2, \"A2\": A2}\n", "\n", " return A2, cache" ] }, { "cell_type": "code", "execution_count": 133, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Z1: [[ 1.7386459 1.74687437 1.74830797]\n", " [-0.81350569 -0.73394355 -0.78767559]\n", " [ 0.29893918 0.32272601 0.34788465]\n", " [-0.2278403 -0.2632236 -0.22336567]]\n", " A1: [[ 0.9400694 0.94101876 0.94118266]\n", " [-0.67151964 -0.62547205 -0.65709025]\n", " [ 0.29034152 0.31196971 0.33449821]\n", " [-0.22397799 -0.25730819 -0.2197236 ]]\n", " Z2: [[-1.30737426 -1.30844761 -1.30717618]]\n", " A2: [[ 0.9400694 0.94101876 0.94118266]\n", " [-0.67151964 -0.62547205 -0.65709025]\n", " [ 0.29034152 0.31196971 0.33449821]\n", " [-0.22397799 -0.25730819 -0.2197236 ]]\n", "\n", "0.26281864019752443 0.09199904522700109 -1.3076660128732143 0.21287768171914198\n" ] } ], "source": [ "X_assess, parameters = forward_propagation_test_case()\n", "A2, cache = forward_propagation(X_assess, parameters)\n", "\n", "print(\n", " f\"Z1: {cache.get(\"Z1\")}\\n \\\n", " A1: {cache.get(\"A1\")}\\n \\\n", " Z2: {cache.get(\"Z2\")}\\n \\\n", " A2: {cache.get(\"A1\")}\\n\"\n", ")\n", "\n", "# Note: we use the mean here just to make sure that your output matches ours.\n", "print(\n", " np.mean(cache[\"Z1\"]),\n", " np.mean(cache[\"A1\"]),\n", " np.mean(cache[\"Z2\"]),\n", " np.mean(cache[\"A2\"]),\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", " \n", " \n", " \n", "
0.262818640198 0.091999045227 -1.30766601287 0.212877681719
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that you have computed $A^{[2]}$ (in the Python variable \"`A2`\"), which contains $a^{[2](i)}$ for every example, you can compute the cost function as follows:\n", "\n", "$$J = - \\frac{1}{m} \\sum\\limits_{i = 1}^{m} \\large{(} \\small y^{(i)}\\log\\left(a^{[2] (i)}\\right) + (1-y^{(i)})\\log\\left(1- a^{[2] (i)}\\right) \\large{)} \\small\\tag{13}$$\n", "\n", "**Exercise**: Implement `compute_cost()` to compute the value of the cost $J$.\n", "\n", "**Instructions**:\n", "- There are many ways to implement the cross-entropy loss. To help you, we give you how we would have implemented\n", "$- \\sum\\limits_{i=0}^{m} y^{(i)}\\log(a^{[2](i)})$:\n", "```python\n", "logprobs = np.multiply(np.log(A2),Y)\n", "cost = - np.sum(logprobs) # no need to use a for loop!\n", "```\n", "\n", "(you can use either `np.multiply()` and then `np.sum()` or directly `np.dot()`). \n", "Note that if you use `np.multiply` followed by `np.sum` the end result will be a type `float`, whereas if you use `np.dot`, the result will be a 2D numpy array. We can use `np.squeeze()` to remove redundant dimensions (in the case of single float, this will be reduced to a zero-dimension array). We can cast the array as a type `float` using `float()`." ] }, { "cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [], "source": [ "# GRADED FUNCTION: compute_cost\n", "\n", "\n", "def compute_cost(A2, Y, parameters):\n", " \"\"\"\n", " Computes the cross-entropy cost given in equation (13)\n", "\n", " Arguments:\n", " A2 -- The sigmoid output of the second activation, of shape (1, number of examples)\n", " Y -- \"true\" labels vector of shape (1, number of examples)\n", " parameters -- python dictionary containing your parameters W1, b1, W2 and b2\n", " [Note that the parameters argument is not used in this function,\n", " but the auto-grader currently expects this parameter.\n", " Future version of this notebook will fix both the notebook\n", " and the auto-grader so that `parameters` is not needed.\n", " For now, please include `parameters` in the function signature,\n", " and also when invoking this function.]\n", "\n", " Returns:\n", " cost -- cross-entropy cost given equation (13)\n", "\n", " \"\"\"\n", "\n", " m = Y.shape[1] # number of example\n", "\n", " # Compute the cross-entropy cost\n", " ### START CODE HERE ### (≈ 2 lines of code)\n", " logprobs = np.multiply(np.log(A2), Y) + np.multiply((1 - Y), np.log(1 - A2))\n", " cost = (-1 / m) * np.sum(logprobs)\n", " ### END CODE HERE ###\n", "\n", " cost = float(np.squeeze(cost)) # makes sure cost is the dimension we expect.\n", " # E.g., turns [[17]] into 17\n", " assert isinstance(cost, float)\n", "\n", " return cost" ] }, { "cell_type": "code", "execution_count": 135, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "cost = 0.6930587610394646\n" ] } ], "source": [ "A2, Y_assess, parameters = compute_cost_test_case()\n", "\n", "print(\"cost = \" + str(compute_cost(A2, Y_assess, parameters)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", " \n", " \n", " \n", " \n", " \n", "
**cost** 0.693058761...
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using the cache computed during forward propagation, you can now implement backward propagation.\n", "\n", "**Question**: Implement the function `backward_propagation()`.\n", "\n", "**Instructions**:\n", "Backpropagation is usually the hardest (most mathematical) part in deep learning. To help you, here again is the slide from the lecture on backpropagation. You'll want to use the six equations on the right of this slide, since you are building a vectorized implementation. \n", "\n", "\n", "\n", "\n", "\n", "- Tips:\n", " - To compute dZ1 you'll need to compute $g^{[1]'}(Z^{[1]})$. Since $g^{[1]}(.)$ is the tanh activation function, if $a = g^{[1]}(z)$ then $g^{[1]'}(z) = 1-a^2$. So you can compute \n", " $g^{[1]'}(Z^{[1]})$ using `(1 - np.power(A1, 2))`." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# GRADED FUNCTION: backward_propagation\n", "\n", "\n", "def backward_propagation(parameters, cache, X, Y):\n", " \"\"\"\n", " Implement the backward propagation using the instructions above.\n", "\n", " Arguments:\n", " parameters -- python dictionary containing our parameters\n", " cache -- a dictionary containing \"Z1\", \"A1\", \"Z2\" and \"A2\".\n", " X -- input data of shape (2, number of examples)\n", " Y -- \"true\" labels vector of shape (1, number of examples)\n", "\n", " Returns:\n", " grads -- python dictionary containing your gradients with respect to different parameters\n", " \"\"\"\n", " m = X.shape[1]\n", "\n", " # First, retrieve W1 and W2 from the dictionary \"parameters\".\n", " ### START CODE HERE ### (≈ 2 lines of code)\n", " W1 = parameters.get(\"W1\")\n", " W2 = parameters.get(\"W2\")\n", " ### END CODE HERE ###\n", "\n", " # Retrieve also A1 and A2 from dictionary \"cache\".\n", " ### START CODE HERE ### (≈ 2 lines of code)\n", " A1 = cache.get(\"A1\")\n", " A2 = cache.get(\"A2\")\n", " ### END CODE HERE ###\n", "\n", " # Backward propagation: calculate dW1, db1, dW2, db2.\n", " ### START CODE HERE ### (≈ 6 lines of code, corresponding to 6 equations on slide above)\n", " dZ2 = A2 - Y\n", " dW2 = (1 / m) * np.dot(dZ2, A1.T)\n", " db2 = (1 / m) * np.sum(dZ2, axis=1, keepdims=True)\n", " dZ1 = np.dot(W2.T, dZ2) * (\n", " 1 - np.power(A1, 2)\n", " ) # note the use of element-wise matrix multiplication (Hadamard product)\n", " dW1 = (1 / m) * np.dot(dZ1, X.T)\n", " db1 = (1 / m) * np.sum(dZ1, axis=1, keepdims=True)\n", " ### END CODE HERE ###\n", "\n", " grads = {\"dW1\": dW1, \"db1\": db1, \"dW2\": dW2, \"db2\": db2}\n", "\n", " return grads" ] }, { "cell_type": "code", "execution_count": 137, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dW1 = [[ 0.00301023 -0.00747267]\n", " [ 0.00257968 -0.00641288]\n", " [-0.00156892 0.003893 ]\n", " [-0.00652037 0.01618243]]\n", "db1 = [[ 0.00176201]\n", " [ 0.00150995]\n", " [-0.00091736]\n", " [-0.00381422]]\n", "dW2 = [[ 0.00078841 0.01765429 -0.00084166 -0.01022527]]\n", "db2 = [[-0.16655712]]\n" ] } ], "source": [ "parameters, cache, X_assess, Y_assess = backward_propagation_test_case()\n", "\n", "grads = backward_propagation(parameters, cache, X_assess, Y_assess)\n", "print(\"dW1 = \" + str(grads[\"dW1\"]))\n", "print(\"db1 = \" + str(grads[\"db1\"]))\n", "print(\"dW2 = \" + str(grads[\"dW2\"]))\n", "print(\"db2 = \" + str(grads[\"db2\"]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected output**:\n", "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "
**dW1** [[ 0.00301023 -0.00747267]\n", " [ 0.00257968 -0.00641288]\n", " [-0.00156892 0.003893 ]\n", " [-0.00652037 0.01618243]]
**db1** [[ 0.00176201]\n", " [ 0.00150995]\n", " [-0.00091736]\n", " [-0.00381422]]
**dW2** [[ 0.00078841 0.01765429 -0.00084166 -0.01022527]]
**db2** [[-0.16655712]]
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Question**: Implement the update rule. Use gradient descent. You have to use (dW1, db1, dW2, db2) in order to update (W1, b1, W2, b2).\n", "\n", "**General gradient descent rule**: $ \\theta = \\theta - \\alpha \\frac{\\partial J }{ \\partial \\theta }$ where $\\alpha$ is the learning rate and $\\theta$ represents a parameter.\n", "\n", "**Illustration**: The gradient descent algorithm with a good learning rate (converging) and a bad learning rate (diverging). Images courtesy of Adam Harley.\n", "\n", " \n", "\n" ] }, { "cell_type": "code", "execution_count": 138, "metadata": {}, "outputs": [], "source": [ "# GRADED FUNCTION: update_parameters\n", "\n", "\n", "def update_parameters(parameters, grads, learning_rate):\n", " \"\"\"\n", " Updates parameters using the gradient descent update rule given above\n", "\n", " Arguments:\n", " parameters -- python dictionary containing your parameters\n", " grads -- python dictionary containing your gradients\n", "\n", " Returns:\n", " parameters -- python dictionary containing your updated parameters\n", " \"\"\"\n", " # Retrieve each parameter from the dictionary \"parameters\"\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " W1 = parameters.get(\"W1\")\n", " b1 = parameters.get(\"b1\")\n", " W2 = parameters.get(\"W2\")\n", " b2 = parameters.get(\"b2\")\n", " ### END CODE HERE ###\n", "\n", " # Retrieve each gradient from the dictionary \"grads\"\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " dW1 = grads.get(\"dW1\")\n", " db1 = grads.get(\"db1\")\n", " dW2 = grads.get(\"dW2\")\n", " db2 = grads.get(\"db2\")\n", " ## END CODE HERE ###\n", "\n", " # Update rule for each parameter\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " W1 -= learning_rate * dW1\n", " b1 -= learning_rate * db1\n", " W2 -= learning_rate * dW2\n", " b2 -= learning_rate * db2\n", " ### END CODE HERE ###\n", "\n", " parameters = {\"W1\": W1, \"b1\": b1, \"W2\": W2, \"b2\": b2}\n", "\n", " return parameters" ] }, { "cell_type": "code", "execution_count": 139, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "W1 = [[-0.00643025 0.01936718]\n", " [-0.02410458 0.03978052]\n", " [-0.01653973 -0.02096177]\n", " [ 0.01046864 -0.05990141]]\n", "b1 = [[-1.02420756e-06]\n", " [ 1.27373948e-05]\n", " [ 8.32996807e-07]\n", " [-3.20136836e-06]]\n", "W2 = [[-0.01041081 -0.04463285 0.01758031 0.04747113]]\n", "b2 = [[0.00010457]]\n" ] } ], "source": [ "parameters, grads = update_parameters_test_case()\n", "parameters = update_parameters(parameters, grads, 1.2)\n", "\n", "print(\"W1 = \" + str(parameters[\"W1\"]))\n", "print(\"b1 = \" + str(parameters[\"b1\"]))\n", "print(\"W2 = \" + str(parameters[\"W2\"]))\n", "print(\"b2 = \" + str(parameters[\"b2\"]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "
**W1** [[-0.00643025 0.01936718]\n", " [-0.02410458 0.03978052]\n", " [-0.01653973 -0.02096177]\n", " [ 0.01046864 -0.05990141]]
**b1** [[ -1.02420756e-06]\n", " [ 1.27373948e-05]\n", " [ 8.32996807e-07]\n", " [ -3.20136836e-06]]
**W2** [[-0.01041081 -0.04463285 0.01758031 0.04747113]]
**b2** [[ 0.00010457]]
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 4.4 - Integrate parts 4.1, 4.2 and 4.3 in nn_model() ####\n", "\n", "**Question**: Build your neural network model in `nn_model()`.\n", "\n", "**Instructions**: The neural network model has to use the previous functions in the right order." ] }, { "cell_type": "code", "execution_count": 140, "metadata": {}, "outputs": [], "source": [ "# NN_model\n", "def nn_model(X, Y, n_h, learning_rate, num_iterations=10000, print_cost=False):\n", " n_x = layer_sizes(X, Y)[0]\n", " n_y = layer_sizes(X, Y)[2]\n", "\n", " # Initialize parameters\n", " parameters = initialize_parameters(n_x, n_h, n_y)\n", " W1 = parameters[\"W1\"]\n", " b1 = parameters[\"b1\"]\n", " W2 = parameters[\"W2\"]\n", " b2 = parameters[\"b2\"]\n", "\n", " # Loop (gradient descent)\n", " for i in range(0, num_iterations):\n", " # Forward propagation. Inputs: \"X, parameters\". Outputs: \"A2, cache\"\n", " A2, cache = forward_propagation(X, parameters)\n", " # Cost function. Inputs: \"A2, Y, parameters\". Outputs: \"cost\"\n", " cost = compute_cost(A2, Y, parameters)\n", " # Backpropagation. Inputs: \"parameters, cache, X, Y\". Outputs: \"grads\"\n", " grads = backward_propagation(parameters, cache, X, Y)\n", " # Update rule for each parameter\n", " parameters = update_parameters(parameters, grads, learning_rate)\n", " # If print_cost=True, Print the cost every 1000 iterations\n", " if print_cost and i % 1000 == 0:\n", " print(\"Cost after iteration %i: %f\" % (i, cost))\n", " # Returns parameters learnt by the model. They can then be used to predict output\n", " return parameters" ] }, { "cell_type": "code", "execution_count": 141, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Cost after iteration 0: 0.692739\n", "Cost after iteration 1000: 0.000257\n", "Cost after iteration 2000: 0.000127\n", "Cost after iteration 3000: 0.000084\n", "Cost after iteration 4000: 0.000063\n", "Cost after iteration 5000: 0.000050\n", "Cost after iteration 6000: 0.000042\n", "Cost after iteration 7000: 0.000036\n", "Cost after iteration 8000: 0.000031\n", "Cost after iteration 9000: 0.000028\n", "W1 = [[-0.65400312 1.21068652]\n", " [-0.75688005 1.38443617]\n", " [ 0.57449374 -1.0957478 ]\n", " [ 0.76242342 -1.40517716]]\n", "b1 = [[ 0.2841426 ]\n", " [ 0.34699428]\n", " [-0.23981061]\n", " [-0.35351855]]\n", "W2 = [[-2.42329584 -3.22274999 1.97978376 3.31771228]]\n", "b2 = [[0.20282644]]\n" ] } ], "source": [ "X_assess, Y_assess = nn_model_test_case()\n", "parameters = nn_model(\n", " X_assess, Y_assess, 4, 1.02, num_iterations=10000, print_cost=True\n", ")\n", "print(\"W1 = \" + str(parameters[\"W1\"]))\n", "print(\"b1 = \" + str(parameters[\"b1\"]))\n", "print(\"W2 = \" + str(parameters[\"W2\"]))\n", "print(\"b2 = \" + str(parameters[\"b2\"]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "
\n", " **cost after iteration 0**\n", " \n", " 0.692739\n", "
\n", "
$\\vdots$
\n", "
\n", "
$\\vdots$
\n", "
**W1** [[-0.65848169 1.21866811]\n", " [-0.76204273 1.39377573]\n", " [ 0.5792005 -1.10397703]\n", " [ 0.76773391 -1.41477129]]
**b1** [[ 0.287592 ]\n", " [ 0.3511264 ]\n", " [-0.2431246 ]\n", " [-0.35772805]]
**W2** [[-2.45566237 -3.27042274 2.00784958 3.36773273]]
**b2** [[ 0.20459656]]
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 4.5 Predictions\n", "\n", "**Question**: Use your model to predict by building predict().\n", "Use forward propagation to predict results.\n", "\n", "**Reminder**: predictions = $y_{prediction} = \\mathbb 1 \\text{{activation > 0.5}} = \\begin{cases}\n", " 1 & \\text{if}\\ activation > 0.5 \\\\\n", " 0 & \\text{otherwise}\n", " \\end{cases}$ \n", " \n", "As an example, if you would like to set the entries of a matrix X to 0 and 1 based on a threshold you would do: ```X_new = (X > threshold)```" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# GRADED FUNCTION: predict\n", "\n", "\n", "def predict(parameters, X):\n", " \"\"\"\n", " Using the learned parameters, predicts a class for each example in X\n", "\n", " Arguments:\n", " parameters -- python dictionary containing your parameters\n", " X -- input data of size (n_x, m)\n", "\n", " Returns\n", " predictions -- vector of predictions of our model (red: 0 / blue: 1)\n", " \"\"\"\n", "\n", " # Computes probabilities using forward propagation, and classifies to 0/1 using 0.5 as the threshold.\n", " ### START CODE HERE ### (≈ 2 lines of code)\n", " A2, _ = forward_propagation(X, parameters)\n", " predictions = A2 > 0.5\n", " ### END CODE HERE ###\n", "\n", " return predictions" ] }, { "cell_type": "code", "execution_count": 143, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "predictions mean = 0.6666666666666666\n" ] } ], "source": [ "parameters, X_assess = predict_test_case()\n", "\n", "predictions = predict(parameters, X_assess)\n", "print(\"predictions mean = \" + str(np.mean(predictions)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**: \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", "
**predictions mean** 0.666666666667
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is time to run the model and see how it performs on a planar dataset. Run the following code to test your model with a single hidden layer of $n_h$ hidden units." ] }, { "cell_type": "code", "execution_count": 144, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Cost after iteration 0: 0.693048\n", "Cost after iteration 1000: 0.288083\n", "Cost after iteration 2000: 0.254385\n", "Cost after iteration 3000: 0.233864\n", "Cost after iteration 4000: 0.226792\n", "Cost after iteration 5000: 0.222644\n", "Cost after iteration 6000: 0.219731\n", "Cost after iteration 7000: 0.217504\n", "Cost after iteration 8000: 0.219477\n", "Cost after iteration 9000: 0.218613\n" ] }, { "data": { "text/plain": [ "Text(0.5, 1.0, 'Decision Boundary for hidden layer size 4')" ] }, "execution_count": 144, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Build a model with a n_h-dimensional hidden layer\n", "parameters = nn_model(X, Y, 4, 1.2, num_iterations=10000, print_cost=True)\n", "\n", "# Plot the decision boundary\n", "plot_decision_boundary(lambda x: predict(parameters, x.T), X, Y)\n", "plt.title(\"Decision Boundary for hidden layer size \" + str(4))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", "
**Cost after iteration 9000** 0.218607
\n" ] }, { "cell_type": "code", "execution_count": 145, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 90%\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/var/folders/4g/qjqbhxd90rn8zxwsc9bvjt1m0000gp/T/ipykernel_83512/3070864498.py:5: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " % float(\n" ] } ], "source": [ "# Print accuracy\n", "predictions = predict(parameters, X)\n", "print(\n", " \"Accuracy: %d\"\n", " % float(\n", " (np.dot(Y, predictions.T) + np.dot(1 - Y, 1 - predictions.T))\n", " / float(Y.size)\n", " * 100\n", " )\n", " + \"%\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**: \n", "\n", "\n", " \n", " \n", " \n", " \n", "
**Accuracy** 90%
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Accuracy is really high compared to Logistic Regression. The model has learnt the leaf patterns of the flower! Neural networks are able to learn even highly non-linear decision boundaries, unlike logistic regression. \n", "\n", "Now, let's try out several hidden layer sizes." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 4.6 - Tuning hidden layer size (optional/ungraded exercise) ###\n", "\n", "Run the following code. It may take 1-2 minutes. You will observe different behaviors of the model for various hidden layer sizes." ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy for 1 hidden units: 67.5 %\n", "Accuracy for 2 hidden units: 67.25 %\n", "Accuracy for 3 hidden units: 90.75 %\n", "Accuracy for 4 hidden units: 90.5 %\n", "Accuracy for 5 hidden units: 91.25 %\n", "Accuracy for 20 hidden units: 90.0 %\n", "Accuracy for 50 hidden units: 90.75 %\n" ] }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# This may take about 2 minutes to run\n", "\n", "plt.figure(figsize=(16, 32))\n", "hidden_layer_sizes = [1, 2, 3, 4, 5, 20, 50]\n", "for i, n_h in enumerate(hidden_layer_sizes):\n", " plt.subplot(5, 2, i + 1)\n", " plt.title(\"Hidden Layer of size %d\" % n_h)\n", " parameters = nn_model(X, Y, n_h, 1.2, num_iterations=5000)\n", " plot_decision_boundary(lambda x: predict(parameters, x.T), X, Y)\n", " predictions = predict(parameters, X)\n", " accuracy = float(\n", " (np.dot(Y, predictions.T) + np.dot(1 - Y, 1 - predictions.T))\n", " / float(Y.size)\n", " * 100\n", " )\n", " print(\"Accuracy for {} hidden units: {} %\".format(n_h, accuracy))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Interpretation**:\n", "- The larger models (with more hidden units) are able to fit the training set better, until eventually the largest models overfit the data. \n", "- The best hidden layer size seems to be around n_h = 5. Indeed, a value around here seems to fits the data well without also incurring noticeable overfitting.\n", "- You will also learn later about regularization, which lets you use very large models (such as n_h = 50) without much overfitting. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Optional questions**:\n", "\n", "**Note**: Remember to submit the assignment by clicking the blue \"Submit Assignment\" button at the upper-right. \n", "\n", "Some optional/ungraded questions that you can explore if you wish: \n", "- What happens when you change the tanh activation for a sigmoid activation or a ReLU activation?\n", "- Play with the learning_rate. What happens?\n", "- What if we change the dataset? (See part 5 below!)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "**You've learnt to:**\n", "- Build a complete neural network with a hidden layer\n", "- Make a good use of a non-linear unit\n", "- Implemented forward propagation and backpropagation, and trained a neural network\n", "- See the impact of varying the hidden layer size, including overfitting." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nice work! " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5) Performance on other datasets" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you want, you can rerun the whole notebook (minus the dataset part) for each of the following datasets." ] }, { "cell_type": "code", "execution_count": 149, "metadata": { "scrolled": false }, "outputs": [ { "ename": "NameError", "evalue": "name 'dataset' is not defined", "output_type": "error", "traceback": [ "\u001b[31m---------------------------------------------------------------------------\u001b[39m", "\u001b[31mNameError\u001b[39m Traceback (most recent call last)", "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[149]\u001b[39m\u001b[32m, line 17\u001b[39m\n\u001b[32m 6\u001b[39m datasets = {\n\u001b[32m 7\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mnoisy_circles\u001b[39m\u001b[33m\"\u001b[39m: noisy_circles,\n\u001b[32m 8\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mnoisy_moons\u001b[39m\u001b[33m\"\u001b[39m: noisy_moons,\n\u001b[32m 9\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mblobs\u001b[39m\u001b[33m\"\u001b[39m: blobs,\n\u001b[32m 10\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mgaussian_quantiles\u001b[39m\u001b[33m\"\u001b[39m: gaussian_quantiles,\n\u001b[32m 11\u001b[39m }\n\u001b[32m 13\u001b[39m \u001b[38;5;66;03m### START CODE HERE ### (choose your dataset)\u001b[39;00m\n\u001b[32m 14\u001b[39m \n\u001b[32m 15\u001b[39m \u001b[38;5;66;03m### END CODE HERE ###\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m17\u001b[39m X, Y = datasets[\u001b[43mdataset\u001b[49m]\n\u001b[32m 18\u001b[39m X, Y = X.T, Y.reshape(\u001b[32m1\u001b[39m, Y.shape[\u001b[32m0\u001b[39m])\n\u001b[32m 20\u001b[39m \u001b[38;5;66;03m# make blobs binary\u001b[39;00m\n", "\u001b[31mNameError\u001b[39m: name 'dataset' is not defined" ] } ], "source": [ "# Datasets\n", "noisy_circles, noisy_moons, blobs, gaussian_quantiles, no_structure = (\n", " load_extra_datasets()\n", ")\n", "\n", "datasets = {\n", " \"noisy_circles\": noisy_circles,\n", " \"noisy_moons\": noisy_moons,\n", " \"blobs\": blobs,\n", " \"gaussian_quantiles\": gaussian_quantiles,\n", "}\n", "\n", "### START CODE HERE ### (choose your dataset)\n", "\n", "### END CODE HERE ###\n", "\n", "X, Y = datasets[dataset]\n", "X, Y = X.T, Y.reshape(1, Y.shape[0])\n", "\n", "# make blobs binary\n", "if dataset == \"blobs\":\n", " Y = Y % 2\n", "\n", "# Visualize the data\n", "plt.scatter(X[0, :], X[1, :], c=Y, s=40, cmap=plt.cm.Spectral);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Congrats on finishing this Programming Assignment!\n", "\n", "Reference:\n", "- http://scs.ryerson.ca/~aharley/neural-networks/\n", "- http://cs231n.github.io/neural-networks-case-study/" ] } ], "metadata": { "coursera": { "course_slug": "neural-networks-deep-learning", "graded_item_id": "wRuwL", "launcher_item_id": "NI888" }, "kernelspec": { "display_name": ".venv", "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": "3.13.0" }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }