{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Hadamard Multitask QEP Regression\n", "\n", "## Introduction\n", "\n", "This notebook demonstrates how to perform \"Hadamard\" multitask regression. \n", "This differs from the [multitask qep regression example notebook](./Multitask_QEP_Regression.ipynb) in one key way:\n", "\n", "- Here, we assume that we have observations for **one task per input**. For each input, we specify the task of the input that we observe. (The kernel that we learn is expressed as a Hadamard product of an input kernel and a task kernel)\n", "- In the other notebook, we assume that we observe all tasks per input. (The kernel in that notebook is the Kronecker product of an input kernel and a task kernel).\n", "\n", "Multitask regression, first introduced in [this paper](https://papers.nips.cc/paper/3189-multi-task-gaussian-process-prediction.pdf) learns similarities in the outputs simultaneously. It's useful when you are performing regression on multiple functions that share the same inputs, especially if they have similarities (such as being sinusodial).\n", "\n", "Given inputs $x$ and $x'$, and tasks $i$ and $j$, the covariance between two datapoints and two tasks is given by\n", "\n", "$$ k([x, i], [x', j]) = k_\\text{inputs}(x, x') * k_\\text{tasks}(i, j)\n", "$$\n", "\n", "where $k_\\text{inputs}$ is a standard kernel (e.g. RBF) that operates on the inputs.\n", "$k_\\text{task}$ is a special kernel - the `IndexKernel` - which is a lookup table containing inter-task covariance." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The autoreload extension is already loaded. To reload it, use:\n", " %reload_ext autoreload\n" ] } ], "source": [ "import math\n", "import torch\n", "import qpytorch\n", "from matplotlib import pyplot as plt\n", "\n", "%matplotlib inline\n", "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Set up training data\n", "\n", "In the next cell, we set up the training data for this example. For each task we'll be using 50 random points on [0,1), which we evaluate the function on and add Gaussian noise to get the training labels. Note that different inputs are used for each task.\n", "\n", "We'll have two functions - a sine function (y1) and a cosine function (y2)." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "TASK_NOISES = [math.sqrt(0.3), math.sqrt(0.1)]\n", "torch.manual_seed(1)\n", "train_x1 = torch.rand(20)\n", "train_x2 = torch.rand(20)\n", "\n", "train_i_task1 = torch.full((train_x1.shape[0],1), dtype=torch.long, fill_value=0)\n", "train_i_task2 = torch.full((train_x2.shape[0],1), dtype=torch.long, fill_value=1)\n", "\n", "train_f1 = torch.sin(train_x1 * (2 * math.pi))\n", "train_f2 = torch.cos(train_x2 * (2 * math.pi))\n", "\n", "train_noise1 = torch.randn(train_f1.size())\n", "train_noise2 = torch.randn(train_f2.size())\n", "\n", "full_train_x = torch.cat([train_x1, train_x2])\n", "full_train_i = torch.cat([train_i_task1, train_i_task2])\n", "full_train_f = torch.cat([train_f1, train_f2])\n", "full_train_noise = torch.cat([TASK_NOISES[0] * train_noise1, TASK_NOISES[1] * train_noise2])\n", "full_train_y = full_train_f + full_train_noise\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Set up a Hadamard multitask model\n", "\n", "The model should be somewhat similar to the `ExactQEP` model in the [simple regression example](../01_Exact_QEPs/Simple_QEP_Regression.ipynb).\n", "\n", "The differences:\n", "\n", "1. The model takes two input: the inputs (x) and indices. The indices indicate which task the observation is for.\n", "2. Rather than just using a RBFKernel, we're using that in conjunction with a IndexKernel.\n", "3. We don't use a ScaleKernel, since the IndexKernel will do some scaling for us. (This way we're not overparameterizing the kernel.)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "POWER = 1.0\n", "class MultitaskQEPModel(qpytorch.models.ExactQEP):\n", " def __init__(self, train_x, train_y, likelihood):\n", " super(MultitaskQEPModel, self).__init__(train_x, train_y, likelihood)\n", " self.power = torch.tensor(POWER)\n", " self.mean_module = qpytorch.means.ConstantMean()\n", " self.covar_module = qpytorch.kernels.RBFKernel()\n", " \n", " # We learn an IndexKernel for 2 tasks\n", " # (so we'll actually learn 2x2=4 tasks with correlations)\n", " self.task_covar_module = qpytorch.kernels.IndexKernel(num_tasks=2, rank=1)\n", "\n", " def forward(self,x,i):\n", " mean_x = self.mean_module(x)\n", " \n", " # Get input-input covariance\n", " covar_x = self.covar_module(x)\n", " # Get task-task covariance\n", " covar_i = self.task_covar_module(i)\n", " # Multiply the two together to get the covariance we want\n", " covar = covar_x.mul(covar_i)\n", " \n", " return qpytorch.distributions.MultivariateQExponential(mean_x, covar, power=self.power)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Training the model\n", "\n", "In the next cell, we handle using Type-II MLE to train the hyperparameters of the q-exponential process.\n", "\n", "See the [simple regression example](../01_Exact_QEPs/Simple_QEP_Regression.ipynb) for more info on this step." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/shiweilan/miniconda/envs/qpytorch-dev/lib/python3.10/site-packages/linear_operator/utils/interpolation.py:71: UserWarning: torch.sparse.SparseTensor(indices, values, shape, *, device=) is deprecated. Please use torch.sparse_coo_tensor(indices, values, shape, dtype=, device=). (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/torch/csrc/utils/tensor_new.cpp:620.)\n", " summing_matrix = cls(summing_matrix_indices, summing_matrix_values, size)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Iter 25/100 - Loss: 1.331\n", "Iter 50/100 - Loss: 1.044\n", "Iter 75/100 - Loss: 1.022\n", "Iter 100/100 - Loss: 1.020\n" ] } ], "source": [ "# this is for running the notebook in our testing framework\n", "import os\n", "smoke_test = ('CI' in os.environ)\n", "training_iterations = 2 if smoke_test else 100\n", "\n", "# We define the training loop in a function, which will let us use\n", "# it again later for a different likelihood.\n", "def train_model(train_data, likelihood_cls: type[qpytorch.likelihoods.Likelihood]):\n", " likelihood = likelihood_cls(num_tasks=2, power=torch.tensor(POWER))\n", " (train_x, train_i), train_y = train_data\n", " # Here we have two terms that we're passing in as train_inputs\n", " model = MultitaskQEPModel((train_x, train_i), train_y, likelihood)\n", " # Find optimal model hyperparameters\n", " model.train()\n", " likelihood.train()\n", "\n", " # Use the adam optimizer\n", " optimizer = torch.optim.Adam(model.parameters(), lr=0.1) # Includes QExponentialLikelihood parameters\n", "\n", " # \"Loss\" for QEPs - the marginal log likelihood\n", " mll = qpytorch.mlls.ExactMarginalLogLikelihood(likelihood, model)\n", "\n", " for i in range(training_iterations):\n", " optimizer.zero_grad()\n", " output = model(train_x, train_i)\n", " loss = -mll(output, train_y, [train_i])\n", " loss.backward()\n", " if (i + 1) % 25 == 0:\n", " print(f'Iter {i+1}/{training_iterations} - Loss: {loss.item():.3f}')\n", " optimizer.step()\n", "\n", " \n", " # Set into eval mode\n", " model.eval()\n", " likelihood.eval()\n", "\n", " return model, likelihood\n", "\n", "model, likelihood = train_model(\n", " ((full_train_x, full_train_i), full_train_y), \n", " qpytorch.likelihoods.QExponentialLikelihood\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Make predictions with the model" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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ixAaPRUPz0vlD20PzbNiwod5lqTOvqvuv6nyq7Iu6y1P1N1ZnmapeL5SYRZ9RDcyasVW0j1WHFNWZV5V117QxlPhgKhi7vVTnGqkNS7WXSUlJtcYdd+vWjYeI6wrD0NY1pis7qG17rQu7oc5vp4tjT8PzFE4VGRlZbd7Ro0dzqE7VedU9T9Q59lVZsWIFb78yPlWT+7Sm9tVoOlipA5UioU4t1NmBntyo5hmp/ar1wMhDSeqfPAnUUYKeIGgecmOTh6E2qHbZzz//jNGjR/OQ2N9//43BgwfXuR3UnYO8E8qnImptpuxCQUNv9XVGoTqpNNRP2/TYY49Vvk/7QOsnzwa55/v164e9e/di+fLlXBZC6bIn1zoNHdBTH7nTCSprQUMHu3btqvMJqb66rqpA7eaoRiN1fklOTmYvL9V3JXf/4sWLq81LXS6olBF1v6Ce4sS4cePY9U+lMmj7z58/z8MItA8fffRR5Xep1Akdh5ooa7jV9hntPz1tqjKk1NC8L7zwAv7880/2EtCxpvOiKtT9RpN5Vd1/VedTdb/VWZ6qv7E6y1T1eqFhL7oelN2KqKYflUSiUQXanqpDb+rMq861SuE29Dvec889MAeMwV6qc43UhqXaSyq1RdtM5cGouxCFaJFH7OLFi/y71By90PY1pis7qG17rQu7oc5vp4tj/9JLL3EIzq233sodrOhcJ281vUfndtV51T1PVDn2VDeVvKLUYpXWTV3IlixZwu1X//e//2l8n9bYvipM0FOQkZHBiQG+vr4c6E/ZchcvXuRsVqWngIJ9X3rpJe7g4ObmxiVK6P81SzTU1pGFgn4pQJiWTU9XdUHrU7eUSc2nf1pHzSBj2j/yhFD3COr+0bVr11pLf0RERHAJGmViFpWZ2Lt3r0LXkBfhxRdfVAQGBvL2kfdl06ZNdZZ+oWOs5IsvvlD06tWLn6zoyS4oKIi70lAWuSrUF7h9yy23cIayKtnFDc1L66nrt615Xqozr6r7r85xUmW/1T3uqvzG6i5T1euFPAJvvfUWz09eWvJk1JV5q+q86lyrlKlKXgFddzeyJHupzjVSF5ZoLynJZsiQIdz1iK4x2kd6XZcnW9vXmK7soLbttTr7pM68qv52urJv1EWLRg0CAwN5XjpnqdMUnb9VUfc8UeV4XrlyRXHHHXew3aB9b9OmDZcnrNmlTN37tKb21Yr+UU/eCtqC4kjIYzBnzhyO/1IXeuojTwYVFP7++++xZs0a9m4IgqAZVAibimO/+uqrld4DwTgQeykIlmtfTTLBylygYQHqtELJCnV1QKmPHj16cEYgnQDvvvsu3nvvPZ1spyBYCjTMRZ2PqJuTYFyIvRQEy7Wv4lk1YahlIj2hUNwJxWlR1q8gCIIg9lIQzAkRqyYMBXNTkDV5HEi4qlsuSRAEwVIQeykIpotJVgMQKvD09GSxStnYIlQFQRDqRuylIJgu4lk1YajTVcuWLbFv3z5O1BIEQRDEXgqCuSFi1YSZMWMGd7j48ssvDb0pgiAIRo3YS0EwXXRaDWDRokXo1KkT3N3deerTp0+tfaYF9Th58iTHqVKv3g8++EAOnyCYMWJHG4fYS0EwfXTqWaUODjY2NjxUTauh7g9UponKLVGPe0EQBEHsqCAIglGFAXh7e7Ng1aQIviAIgiB2VBAEy0Jv1QAotpL63+bl5XE4QG1QcXualFChfOohS31prays9LWpgiBYEPS8npOTw5U1qN+9MSN2VBAEi7SjCh1z+vRp7jNtY2Oj8PDwUGzYsKHOeZV9p2WSYyDngJwD+j4HYmJiFMaK2FG5HsQmyjkAC7ajOg8DKC4uRnR0NPd1pg5L1MN+165dtdYFrelZpe+Eh4cjJiaGE7QEQRC0TXZ2NsLCwrhoPCUuGiNiRwVBsGQ7qveY1SFDhqB58+b45ptvVNp52mkSrSJWBUHQBaZoZ8SOCoJgSXZU7wFaFIda1XsqCIIgiB0VBEEwSILVrFmzMGLECB7Kp8DbX3/9FTt37sTmzZt1uVpBEASzQeyoIAiWjk7FanJyMh555BEkJCSwe5gaBJBQHTp0qC5XKwiCYDaIHRUEwdLRqVhdvHixLhcvCIJg9ogd1W7pr5KSEi0uURAqsLOz4yZIgonXWRUEQRAEQ0B5xImJiZypLAi6wtPTE4GBgVIXXgeIWBUEQRDMGqVQ9ff3h7Ozs4gJQesPQ/n5+RyyQwQFBckR1jIiVgVBEASzHvpXClXqhigIusDJyYn/kmClc01CArSLcfcWFARBEIRGoIxRJY+qIOgS5TkmcdHaR8SqIAiCYPZYWVkZehMEM0fOMd0hYlUQBEEQBEEwWkSsCoIgCIIJExERgc8//xzmgrntj9B4RKwKgiAIghESExODxx57DMHBwbC3t0eTJk3wv//9D2lpabBk3nrrLR5yp8nW1ha+vr647bbbWOCq286dumrScqSsmXEjYlUQBEEQVODo0aMYPHgw/9U1165dQ48ePXD58mUsX74cV65cwddff43t27ejT58+SE9PN2iFhfLychiS9u3bc3fM6Oho7NixAw888AA+/PBD9O3bl9u7C+aFiFVBEARBUIGlS5eyMFq2bJnOj9ezzz7L3tQtW7ZgwIABCA8Px4gRI7Bt2zbExcXh9ddfrzY/CbTx48fDxcUFISEhWLBgQbU6oOSNpGU4ODiwp/a5556r/Jy8kS+++CJ/j77fu3dv9jgq+fHHH7ng/Z9//ol27drxMr7//ns4Ojre5JEkzy8JeiV79+7FrbfeyqWdwsLCeL15eXmVn1Opp1GjRvHnTZs2xS+//KLS8SGPKhXgp33p2LEjpk+fjl27duHs2bP4+OOPK+ej34pEv5ubG8//0EMPVdZDvXHjBgYNGsT/9/LyYg/r5MmT+fWmTZvQv39/3m8qeXbXXXfh6tWrKm2boH1ErAqCIAhCHURFReHYsWM4fvw4Vq5cye+tWLGCX9P79Lm2Ia/p5s2b8cwzz1TW71RCgmvChAm8LSRClcydOxedO3fGiRMn8Oqrr7Jo3Lp1K3+2evVqfPbZZ/jmm2/YU/vHH3+wwFMybdo0HDhwgPfr9OnT7KUcPnw4z6uEit6TCCSReu7cOd4GEnK07KoeV9ou+owgcUfLGTNmDC+XPiPxSutTQuKQwh3oIWDVqlVYuHBhpZhUlzZt2rCgX7NmTeV7VEbq3XffxalTp3i/SaAqBSmJZ+X2R0ZGsqf2iy++4NckqGfOnMledPJmW1tb49577zW4R9liURgxWVlZdCXyX0EQBLEzYkfVpaCgQHH+/Hn+qwl0D1JOVlZW1f4qJ21z8OBBXu7atWtr/fzTTz/lz5OSkvh1kyZNFMOHD682z7hx4xQjRozg/3/yySeKVq1aKYqLi29aVlRUlMLGxkYRFxdX7f3bb79dMWvWLP7/kiVLeH0nT56sNs///vc/xeDBgytfb968WeHg4KDIyMjg11OmTFFMnTq12nf27NmjsLa25t8jMjKSl3v48OHKzy9cuMDvffbZZ3UenzfffFPRuXPnWj975ZVXFE5OTnV+98iRI7z8nJwcfr1jxw5+rdzmukhJSeH5zpw5o7NzzZTJ0rFeE8+qIAiCINTBzz//zEPO/zp3qv2l9+lzHTqTVJ6X4lhrvr5w4QL/nzylBQUFaNasGZ544gmsXbsWpaWl/NmZM2fYI9qqVSu4urpWTjSkXnXYm0ISOnXqVG0d5EGlcIH4+Hh+TUP4I0eOZI8rQd5MCiGoutxhw4axd/L69eu8fXQMu3fvXs07qvy+psesar1T8n5TmAGFQFAoAIVUEBTrWh/kVaawCjpm7u7uXKFAle8JukHarQqCIAhCHZAga9u2bTVBpeTQoUPo1q2b1o9dixYtWHCRmKOh55rQ+xRj6efnp9LyaLibhrkp3pVCAyi8gMIGSJDm5uZya1ASdTVbhJK4VELhCDWL3vfs2RPNmzfn8IGnn36aRTCJUyW07CeffLJafKwSEo+XLl2CtqFjQ7GvyqF8Esc0kZCm40Vik14XFxfXuxwSuFR94bvvvuO4WBLYHTp0aPB7gm4QsSoIgiAIKkBxiyRalH91BSX0DB06lOM3Z8yYUS1uNTExkYXXI488Uk08Hjx4sNoy6DWJbCW0DBJgNFHyFnkwyavatWtX9qxSnCglQmki5ml7QkND+biQZ1UJCfnz58+z+K4N2gby8JJQJuFLkKjWtIzUxYsXOTFq1qxZla+pzNdHH33Egp2oWcmBPMYEHQMl9B3aDhKqymNCsbaC4ZAwAEEQBEGoB39/f05sIu8qlY+iv/Sa3tcVX331FWfpkxdw9+7dnIREQoxELGXtv//++9Xm37dvH+bMmcPeSqoE8Pvvv3OSFUHezsWLF3OmPJXEotAFEq/kOaThfxKcJH4pMYmG5w8fPsxloDZs2NDgdtJ3KdmMtuf+++/nSgFKXnnlFezfv58Tqk6ePMlD6+vWratMsGrdujUnYJH3lbzUJFoff/zxm5LKaoNELgl3CkEg0T1//nwe4u/SpQteeumlSu8tiVH6jPabqhlQslVV6BiQ6F+/fj1SUlLYG0xea3pg+Pbbb7lk2D///MPJVoIBURgxkmAlCILYGbGjjUFbSS+FhYWK8vJy/j/9pde65saNG4pJkyYpAgICFHZ2doqwsDDF9OnTFampqdXmowSrt99+W/HAAw8onJ2dFYGBgYovvvii8nNK1Ordu7fC3d1d4eLiorjlllsU27Ztq/ycEq/eeOMNRUREBK8nKChIce+99ypOnz5dmWDl4eFR53b26tWLk2v++eefmz6j5KmhQ4cqXF1ded2dOnVSvP/++5WfJyQkKEaOHMmJWeHh4YqlS5fy/jSUYKVMbqPkMG9vb0X//v35OzV/l19//ZX3i5bfp08fxZ9//snfO3HiROU877zzDh8zSpyj401s3bpV0bZtW/4ebfPOnTvrTXojJMEKOkuwsqJ/YKRkZ2fDw8MDWVlZHOAsCIIgdkbsqDoUFhayt5DiGKkuqCDoCks+17J1rNckDEAQBEEQBEEwWkSsCoIgCIIgCEaLiFVBEARBEATBaBGxKgiCIAiCIBgtIlYFQRAEQRAEo0XEqiAIgiAIgmC0iFgVBEEQBEEQjBYRq4IgCIIgCILRImJVEARBEARBsEyxSr2Fe/bsCTc3N+6hPHr0aERGRupylYIgCGaF2FFBECwdnYrVXbt24dlnn8XBgwexdetWlJSU4I477kBeXp4uVysIgmA2iB21XCZPngwrKys89dRTN31G91b6jOYRBHPHVpcL37RpU7XXP/74I3tYjx07httuu02XqxYEQTALxI5aNmFhYVixYgU+++wzODk5Vfag//XXXxEeHm7ozRME84tZzcrK4r/e3t76XK0gCILZIHbUsujWrRsL1jVr1lS+R/8nodq1a9fK98rLyzlkpGnTpixqO3fujFWrVlV+XlZWhilTplR+3rp1a3zxxRfV1kVeWgrXmzdvHoKCguDj48MeXBoVFQSz9axWhS6k559/Hv369UOHDh1qnaeoqIgnJdnZ2fraPEEQBKNH7Kh2UCiA/HzoHWdnwMpK/e899thjWLJkCSZMmMCvf/jhBzz66KPYuXNn5TwkVH/++Wd8/fXXaNmyJXbv3o2HH34Yfn5+GDBgAJ87oaGh+P3331mE7t+/H1OnTmVROnbs2Mrl7Nixg9+jv1euXMG4cePQpUsXPPHEE9o5CIJgzGKVns7Onj2LvXv31jkPXWxvv/22vjZJEATBpBA7qh1IqLq6Qu/k5gIuLup/j0TnrFmzEBUVxa/37dvHoQFKsUpOng8++ADbtm1Dnz59+L1mzZrx/fabb75hsWpnZ1ft/koe1gMHDuC3336rJla9vLzw1VdfwcbGBm3atMHIkSOxfft2EauC+YvVadOmYf369fykR092dUEX48yZM6t5Vmn4QxAEwdIRO2q5kHeURCPlfSgUCv6/r69v5efkAc3Pz8fQoUOrfa+4uLhaqMCCBQvYKxsdHY2CggL+nLymVWnfvj0LVSXkZT1z5oxO908QDCpW6aKaPn061q5dy0+A9CRXHw4ODjwJgiAIYkd1ORxPXk5DrFdTKBSAHliUorMquf/uzIYNGxASElLtM+U9lTyxL774Ij755BP2vlJJyblz5+LQoUPV5icPbFWo4gCFEAiC2YpVGrKijMV169bxhZGYmMjve3h4VGY1CoIgCGJH9QnFjWoyHG9Ihg8fzp5QEo/Dhg2r9lm7du1YlJLHlIb8a4NCB/r27Ytnnnmm8r2rV6/qfLsFwejF6qJFi/jvwIEDq71PgeJSG04QBEHsqKAaNDR/4cKFyv9XhZxB5DWdMWMGe0H79+/PVSNIoLq7u2PSpEmcdLV06VJs3ryZRzmXLVuGI0eONDjiKQgWEQYgmAZHjx7Fyy+/jDlz5qBHjx6G3hxBEP5F7KighIRnXbz77rsc20qJyteuXYOnpyeXvXrttdf48yeffBInTpzg7H7yzo4fP569rBs3bpQDLBg9VgojtoSUYEUhA/SEWN9FaikUlZYhJacIqbnFyC8qRX5xGfJLylBYXIbC0jJYW1nBzsYKttbWsLWxgr2NNTyc7eDr6gAfF3t4OdvD2rr2uinPPfcc5s+fz39r1t4TBHPG3O2Mue9fQ1AB/evXr7MH0dHR0dCbI5gxlnyuZevYzuitdJWgPqm5RYhKy0dydiGSc4qQkV/M9QE1xcbaCl4u9gj3dkZzPxeUZCYjPT2Nn7JXrlxZGYRPQ0b0DEPZpk2aNJGfThAEQRAEgyFi1YgoK1cgJj0f11PzcC01D9kFJVpffip5ZnOKcDwqAzPvaF35GQlWIiUlBd27d698X5uOdwk1EATTobCkDI521WMjBUEQDIGIVSMgNiMf5+KzcSU5F8Wl+isRMuGVuVg+71WUl5VVilLlX1tbW67pp00ouJ+6olBgv8TFCoJx88eJOJQrgBb+rjwS4+MqZQUFQTAMIlYNRG5RKc7HZ+N8fBYy8g3Td7n77XcjILw5Pn32vps+27xjDwb3v6XR66COK6mpqRJqIAgmBj22JmUX8rTvSiq8XezRMsAV7YLc4elsb+jNEwTBghCxqmfiMwtwPDoDV5PzUG5EuW0UBkBeVeXfDWcSUOSRgP4tfeHmWL1ItDpERERUW4euQw0EQdAN6XnFOHQtnacQTye0C3Zn8epgK6ECgiDoFhGreoDE2NWUXByLykB8ZiGMCVdPH7h5+cLTLwi9h9+PQ5tWITMlAa4ePriYmMOxs92beKFHEy/Y2lirvfyff/6Za+qWlpbqJdRAEATdE5dZwNPOyGS0DHBD1zBP+LtbVvazIAj6Q8SqDqGEJhrqPxqVjkwDDfU3hKdfIGYv2wEbOzv2fPYZOQ5lJSWwta8Y5qMY2gNX0zim9raWvnxjUocJEyagbdu21TypSqjNH9UBFATBNCkpq7BxNIV4OaFbuCea+7lWjqIIgiBoAxGrOhKp5+KzcPh6OnIKS2HsKIUpQTeZqq+VUGWC9acT0MwvG0PbBcDZXv1Tx9ramrurKP8KgmA+xGUU8OThZIeu4Z7oEOIBOw1GYwRBEGoiYlXLIvVsXBaO3DANkaoJ11Ly8PPBKNzRLhARvqo11/b390dgYCDCwsIwZcoULF68GDExMfy+IAjmRVZBCXZGprAd7BHhjU4hHhqFEAmCICgRC6IFyv8VqUv2Xcc/F5PNVqgqySsqwx8n47AjMhmlZQ17SENDQ3Hjxg0e9qeWf/SXXtP7giCYr53YFZmCJftu4ER0hkq2QjAMlEcwdepUeHt78+jayZMnMXDgQDz//PMNJtB+/vnnettOQffnAcWi776UgivJOTAmxLPayB/2UlIuDlxNNVj5KUNBOVInozMRm56PER2DuKVrfTg4/Pc5GcOqrwVBMO8yfeRppQTTvs190TbIzWhiWj/beklv65oxtJVG30tMTMT777+PDRs2IC4ujkekunTpwkLy9ttv18q2bdq0iZNdd+7ciWbNmnH3wjVr1sDOTvNKMILpONui0/O5zvu11Fx+yCQ8nIxr5FPEqoZcS8nF/qtpSMkpgiWTmluMlUdiMKJDIJr5uRp6cwRB0DIxl87gr+/mYtQTLyGsVUeNl0MjTpvPJeJUbCYGtPJDsKeTVrfTHKERqH79+sHT0xNz585Fx44dUVJSgs2bN+PZZ5/FxYsXtbKeq1evIigoCH379q18j7ysgvmSklOE8wnZiEzMrhSoxoyEAWjQbeq3IzFYdzLe4oWqEqoY8OepeBy9ka7t81MQBANzZOs6XDl1CEe3rdPK8hKzCvkB9+8zCcgutKwRKXV55pln2At9+PBhjBkzBq1atUL79u0xc+ZMHDx4kOeJjo7GPffcA1dXV7i7u2Ps2LFISkqqXMZbb73FnljqHEjD9h4eHnjwwQeRk1MxzEulBadPn87LoXUpa2PXDANITk7GqFGj4OTkhKZNm+KXX365aXszMzPx+OOPw8/Pj7dl8ODBOHXqlMrbQlDy7Zw5c9CiRQsegQsPD2fPshLKd6B9JAFPgpr2nUS9oFoLZQrJobwTmqjtuikIVULEqookZxdi7YlY/H40lmM6hJvDAvZcTmXPicSmCYJpQ53nrl04g9jL53By1wZ+78TOv/l1zKWzSE+Ka/Q6IhNzsHT/DU7EoqFIoTrp6ek8PE8eVBeXm5NZSayRsCOxRvPu2rULW7duxbVr1zBu3LibPKd//PEH1q9fzxPN+9FHH/FnX3zxBd555x3OIUhISMCRI0dq/SlI1JJQpJbZq1atwsKFC1nAVuWBBx7g9zZu3Ihjx45xaUIKVaDtU2VbiFmzZvHr2bNn4/z58/j1118REBDAn5FXediwYXBzc8OePXuwb98+FunDhw9HcXGxnEJ1kJZbhO0XkrB473UOyTHFEWEJA2iA1NwiHLyWxvEc0mipYajeYmZ+MUZ1DtaovJUgCIanauc5JbmZadVaM3+6JVIrdVr3Xk5l4TqkbQACPaSxgJIrV65wXkSbNm3qPH7bt2/HmTNncP36da62QixdupS9ryQ6e/bsye+RqKWYVBJ5xMSJE/m75LEk7ya9b2Njw1VbauPSpUssQMnDq1wmVXWhGtpK9u7dy5+TWFXmJMybN4+FKYlbSuBqaFvIw0ri+auvvsKkSZP48+bNm6N///78/5UrV/L3v//++8q45yVLlrBwp3jbO+64oxFno3mhUChwPTUPJ2MyEZWWr9MQH30gntV6WgvSMBW5yi8niVBVB+rSRcN8VMJGEATTgzrP2djU/rBpbWODCa/M1er6yNOz4kg0d8SisCJBtTbUFy5cYJGqFKpEu3btWLzRZ1UfPpTikKD41Jpe0YbWQx0HqzZ3IRFN61FCw/25ubnw8fFhb6dyIiFN3lRVtoXWU1RUVGfiGK2DRDx9X7l8CgUoLCystg5LP28iE3NYu1C4Yl1CVRchPrpEXF81IK/gwWvp/GOXiytVY6hj1+9HY3Bft1B4u9zcZEAQBOOFOs9FlXni9Ul33fTZ81/+jtCW7bW+TjK3J6IzcTUlD3e0C0CYtzMsmZYtW7L3UBtJVDWz+mm52m7MQkKVhCd5OGtSVdTWty0UD9vQOkgw1xYvS3Gylkx5uQKRSTkcVpOWW3dIBIXw5GVlVJQoqxLi03PovSx0XTy84B0QAmNDxOq/JOcU4uiNDPaiikjVDpT9S4L13q4h0jdcEEwUuqnRTUz5V9dQt7zVx2PRNdwL/Zr7WGxDAfIYUnzmggUL8Nxzz90Ut0rJTDQMT3GkNCm9qxTnSZ+Rh1VbkBe1tLSU41CVYQCRkZG8HiUUn0pltsgDW1sYiaoCnQQrhQVQolZNaB0UCkDluyiBS4DaJTTfmzhYLyE+2sYyrUAVKFnqjxNx+OVgtHhTdUB+cRlWHZekNEEwNdy9fOHm5YvQlh1w/3Nv81967erpo/N1kyamTOXlh6PZkWCpkFAtKytDr169sHr1aly+fJmHyr/88kv06dMHQ4YM4XJW5Ak/fvw4x4w+8sgjGDBgAHr06KG17WjdujUnMSmbupBoJTFZ1RNK20LbNHr0aGzZsoUz9Pfv34/XX38dR48eVWk9jo6OeOWVV/Dyyy9z7C0N7VPVA4qPJWg/qQYsJZVRghWFGJAnl8R8bGwsLLE60Yp/K2uoWuudQngolEdfIT7awtZS26JeTcnlovaS2a97ikrKsfZ4LCddNfFRrUWrIAiGxScgCLOX7YCNnR17VfuMHIeykhLY2tvrtY7zisMx6NvcB92beBlNMwF9QQX6SYRS8tELL7zA2fo03E1D4YsWLeLjsW7dOi49ddttt8Ha2ppF5fz587W+LZTIRAKVhDBl57/33nucsa+EtuXvv/9mcfroo48iJSWFE7Zou5TZ/KpAyyTv7BtvvIH4+HgOLXjqqaf4M2dnZ+zevZsF7X333ccJWSEhIRzjakme1vS8Yuy5nMLtz9Wl++13IyC8eTVPqq5DfLSBlUIf4zoakp2dzZmKWVlZWjkRqZPK6dhMnIvL5v8L+sXW2gqju4ZYfCyaYN52xlz2j7yaVBPVWGji44zhHQLVrjJCyTfkgaPaoOS5EwRdoetzrai0jJsRnY7JalS4IpWgI7FaM8Rn5oI1lWJ1cBt/dA77L9bY0HbU2hK8qNRtav3peCzecx2HrqWLUDUQpeUKbh6grjebhpCouLSqQ0mCIOgXKoGz8KVH+K+uoKxmCteioU9BsDQuJGTjp/03eES4sXk1FMpjqBAfTTHLMAB6QojNKOAY1MvJudy1QTAOqCwNxQiP6Raqck1Fil2iQtTU9USbcViCIGiHqiVwdFmvkUbEVh+LQ5/mPugZYXlhAYJlFvTfEZmCmHTtPaR5+gUaPMRHXcxSrP6w7wZnlArGK1jXkmDtHgJ/N8c6O+ikpqbyhUTZn8SKFSu4UDQ9jFCQfZMmTfS85YIgGLoEDnmV9l1JRXxmAYa1D4STfe3JIoJgylAnyEPX03EsKoNHiLVNVWFK17AxC1WzFav5FhyPWlYGFBdao7jQCiVF1nByLYOTazmsjSzgg7zda47H4YHuofBxreh2UpWqpU+U3hMK2K9alNqIw60FwewxdAkc6s7z6+FojOocVOdDryCYIglZBdh6PqneeqmWhlmKVXOG9Flmii0So+yRRFO0A5Ki7ZEaZ4fCfGuUltysSq1tFHD1KIOrZyncvMoQGFGEiHaFaNquAO4+hguRKCiuEKxje4bBw8nupg461IuaavspRanyL2WKUrs+QRAMB5W4WT7vVZTTE3ItJXDGv/hfv3ddQSNovx2JwZB2AWgTWH9ShzzcCrqmsecYeVMPXEvD8ajGx6WaGyJWTYDcLGtcPu6CyOPOuHTcGZkp1YVdbVhZK2Bnp0BxkTXKy6yQnW7LExF5zAW7VlfM5x1YzMK1TY88dOyXCwcn/V4gFINGMaxje4RVG86jenpU8LqqJ1UJ1fmj4tCCIOiG1FTqiGMaJXBKyhTYeCYRydlF6N/CF9bW1eNYlR2T8vPzG+yQJAiNgc6xquecOlBYC3lTqSyVoGexSvXQ5s6dywWEqT7c2rVruWCw0DBpCbY4/o87zux3RdwVBygUVtU8pX6hxQgML0ZAk2IEhBfBP6wEzm5lsHcsh72jArZ2VI4CKC0hsWuL3Awb5GTYICvNFrGXHXHjvCMSrjsgPdGeJ1oXfbfzrTnoeUc2mnUs0FvoAF2c605SDGso7GrpVkO1A6kdn/KvIFgShrCjDz0E7DsYioh2+WjaoQDNOhQgrFUhbO2Mo8tVbVBsX0pOEe7sGFTtwdfGxobbfSr7z1OtTknMErQJnfMkVOkco3ONzjl12qQevJaGIzcyxJtqKLGal5eHzp0747HHHuMCvkL95OdY49RuNxzd7obrZ6v3xQ5qWoRW3fLQuns+3zhIkKoC3Vw8fUt5qmRENv8pzLNG1EVHXDvjhBM73ZAab48jWz148goowS3Ds9B/dCacXHQvEBOyCrkLx6hOwZWeEWqpR0WlqY3glClTuIsJtRWk9wXBUtC3HSWtefZshT06f8iVJ8LWvhwRbQvRvk8uOvXPhZd/aWUJHE+/IPQefj8ObVqFzJQEg5XAiU6njj7RuLtzcLVYeLIjhFKwCoIuIKGqPNdUISOvGJvOJRpVPWNjRW9NAehJVl2PgKZFZudvv8w1PU2FGxccsWetJ07vc0XZvzGnVlYKtOiSj+6Dc3iIXtexpXQWkLf1yBZ3nNzlhsL8iidD8tYOGpuO/ndn6iVEoEOIB4a2+6/bSVFREezt7Ss9NsXFxXBwuDkhSxAsoSmAvuxoaSnw8S+JOHLAGtfOOvGUl1XdtxEQno4eQ8rQrncGAiP+86oaQwkcBztr3NkhCBG+1TvmUevSkhKpFCNoHxr6V8ejejYuC7supXB1HGNksJE1BTCqmFUSJjRV3XlzpawUOL3HDbvWeiL6olM1D2r327PRbVAOPP30V9WAQgaati/kafQzKTiz1xXblntzAteGxX7YtdoLQ8ano8/ILNjZ60600gXs4mCDvs19+XVVYUo3QxGqgqB7O2prCzRrWwzn4EIMGJPJD7PJMXYc7/7Pb+nITmuFpGhvbPgB2PCDHyLaFaDvXZnodGsu7B3sjaLF87qT8bitlS+6hntVvk9iQh1BIQi6qIRDsalXknPl4JqqWP3www/x9ttvw5wpKrDCvr88sfcPT2SmVgSA2diVszi99Z5MhLb87yZjKOwdFOh+ew66DszB8R1u2LzMB2kJ9vhjkT+L1vufS0LbXrrrIkNdxqg6QPtgD52tQxDMFV3Y0YzkOBQXZqBZBytsW/443zocnCYgMOIVREf64cZ5J57+WFSGnkOz0WdkJsfRGxLKpt4ZmYKM/GIMbOV/U+KVIOgT6sD4/MwXMeiRGfBu0lYOvimHAdTmEaB4RXMIAyjMt8LedZ7YtdobedkVT/ZUSqrfqEz0vSuLS0oZsxf48BYPbP3Zu1Jg9xiShXueSoGLu26GMGysrXBv1xCEeVeP3RUEbWNuYQDasqPLD0dXxtLNvKN1PXNSjN5j8PJ/CxnJ/2Vgteudy6MxVG3E0IR7O2NkpyA42olXVdA/JLPGP/okVv70HW4dPRH3PvN/Rv8zDJYwgLqhIV5zG+alJKY9LFK9kJ9TYSh9g4tx+4PpHI9qq8MhdW1hYwv0uTML3QdnY+NPPti9xgtHt3nwkOCY6cmcbKFtqGPH+tMJGNczDN4uhh9WFARTQRd2tP6aqikY/6IXug68jotHXXBggwfOH3apTM5q2TUPQx9KR/NOBRxuZKjEq9+PxuDuLiE31XQWBF1BnRhjE5Jw8Fo6Nqxbrbcub+aIUYUBmBMlxRWe1O0rvCtFKpWbGvpQGroOyoEphk1RBYJ7nkxF59tysWJeAJJjHPDjO8HoMiAHD/wviTtlaTu2h0paPdgzXFoqCoIBUbWmarveeTylxNmx7Tu6zR2XT7jw1LR9AYY/koqWXQsMsAdAam4xVnKlgBAEekjHK0H3VO3EaIgub+aETitp5ubm4uTJkzwR169f5/9HR0fDXCHHw6FN7vhwcgT++s6Phap/aDEmvJKAV767gR5DTFOoVoXK17ywKBpDxqfB2lrB1QM+nRaO+Ova94Bm5pfgr1Px3NlDECwRY7Ojyhql9dUq9QspwYMvJOG1H69zqJOtXTmun3PColfC8P3sYCRFG8a7mVdUhlXHYnAlOccg6xcshxPRGZg4ax53c6sNep9GLIyRvGxrHNlvi9hYWEbM6s6dOzFo0KCb3p80aZJK7TJNqXQVHcVzB1yw4QdfzqAnPP1KMPyRNPQYkg1rExeodRFzyQE/vhuMjCQ72DuUY+zMJE4W0zZtg9wwvEOQ1pcrCMYes2ooO1o1ZpXITEnEZ9PG3FRTdcZXq+HpV39tyew0G2xb4Y396z25ox495FJlkWET0+Dqqf94fdLZt7b0Rfcm3npft2DeUCmqbReSEJlYcR+MvXyu1hGJmQvW6K3LW32kJ9ri+nknbhIUf80BCdftkfVvbsrChcDTT8P8S1cNHDjQIvoxk2Bb940frp1xrqxNSokF/e7O1GmZJ2MgrFURZi6IwrIPgnDpuAt+/jAIMZGOuOvxFI51VRJz6Qz++m4uRj3xEsJadVR7PRcScuDlbI/ezQxTbFwQDIWx2FESpLOX7YCNnR17VfuMHKdyTVWqE33fsylcr/mv7/1w7oArV0U5tt0NdzycjlvvzdDriBMdzt2XUpFdUIoBrfykUoCgFdJyizjXoraWqcbQ5U354Hj5lDOunHTG5ZNO3MGyNkLDy2BlZTxeNolZbQQZybbsSaVWpXww7csx4L4MDB6bofX4TWOGKgJMfT+Ok6+2r/DBrjVeiLnsgMmzEyq9Jke2rsOVU4dwdNs6jcQqceBaGnelaeFf0VFHEAT9UlWY0k1X3eL/VM5qytvxfJP881s/xF1x5L9Ht7lh7IwkhLfWb+m+kzGZyC4swYgOQbC31VN/acEsuZSUw/VTaxb5N4Yub2kJdji5yxUnd7vxNVcVat9OrZRDmhchuFkR13qn6c5ufmo1BTCb0lWaYKxhAJThv32lF2f4l/7bcYqG+kdMTuUWhJbM6b2uWD4vAEX5NvAOzMfop3fD07cA377+OHIz0/kCnfr+dxpnQtIN5YEeofB3kwQJwTLCABqLtsIAtE15OXB4szt7WgtybLhrH41G3Tk5DY56aPFclQB3R9zTJRguDuK/EdSjvFyBPVdScTwqo855SouLK0ck9NXlLSPZltuoUwv3mEv/3S/pOiNhSh0yW3ataN9eW3dKYytdJWJVDcopeWqzBzb+6IPczAqj1rxTPu6emsLD4UIFSdH2+Pa1kH9rLsYDGEa9qWo9PJpkQro52uKh3uFwtpcbi9B4RKwaRqwqycmw4TAq5QiVh28JxkxLRoe+edAn7k52GN0lmEdvBEEV8otL8feZRMSk665JjroPgJeOO3OIzflDLlCU/5sMaa1Ay8756DwgFx375cDVo+GHQWMTq3K3V5FLJ5yw7ht/JFyrMGR+IcUY9UQK2vfJM1jtQGMlILwY0z+PwRfPuSErNRjAHgCjAOytlgk5/sWPNFp+TmEp1p9KwJjuodw8QBAE04Uaojz8aiJ3vlo13x9p8fb44a0Q9Byaxa2fnfTkZc0uKMHKozEY1SlYmpEIDZKQVYANpxP4fmRo8nOseZSCEhhT4//z2DbrmM8Jzx375Rp14yFVELHaANQPm0pQnTtYESfp5FqGOx5O+7cciz5+ItPE07cUL32ThYUvWSP+GsXmbAHwIIA/b6rNqAlxmQWccTmsff1ZyIIgmAatu+fjpW+iuL3zzlVeOLLVA5dPOmP8i4l6q81aVFKOtSfiMKRtANoFm19IiKAdzsRmYUdkMjevMSQ5GTZ8rZAntbiwIiTR0bkMPe/IRt+7MhEQbtiWx9pExGod5GZZY8vPPtVKrfQdlcmlVnTVYtTccHYrx5jp+zB/Br26G8AabssILNXK8s/HZ8PX1QHdm3hpZXmCIBgWewcFRj2eig59cvHrnECkJdhzbdbb7s3AnY+l8ue6hgTI5nOJyCooQZ/mUn1E+A+q970jMgVn47IMeliy02yw43dv7N/ggZKiCpFKSVFUbaPb4OxaY1BNHRGrNSgttsLuPzyxbbk3CvNsKntc05C/OTylNLaElLp4+XvC1XMsFOVlyMu+F8ASODo7aS0Tcu/lVPi42CPC10UryxMEwfA0bV+IF7+O4koBBzZ4YvdaL0Qec8bE1xMQ3PTmskC64OC1NBasQ9sFSLiRgJzCEh72T6gjjlsf99acDBts/dUbB//2qEzuDm9dwOXf2vYy75BEEatVApNP7XLDhiU+lXXHQpoXcvKUodoD6gJtlJBStzbjGz9vg5WNHVbPz8TBvz1RVLgI188mctvZxlKuUODvswkY3zMcXi66za4UBEF/kHfogf8lc17Ayk8DuNnK59PDce8zKbhlRJZebswXErKRW1SKuzoFwdHOeGpOCvolNiOfhWp+cZlB7q0lxVbYQ060X71RmF9xHka0I5GaxuEz5ixSlYhY/Td5av33foi9XFHewd27FHc+mmo2nafSk+KQl5XBZTNO7trA753Y+Td6Dr1X4xJS6qAs0XH/c8lQKKxwaKMHfvk4EFY2CnS5LVcrcWZ/norHuJ5hckMRBDOjXa88vPR1FH6dG4iLR1zw++cBuHzCCWOfT9ZLiSvK9F55JIZLW3k6ywOxpXE8OgN7LqWyY0Tf91Za5andrqxP0pMqkmRCWxTirsdTueyUJYhUJRZduiruqgPWf++LyGMVQ8gOTuUY9EA6BozJMKuYj5l3tG5wHk1KSGnqwSYvyZEtHhwHTMN6nW9tvGAlmvq68A2lvp7lglATKV1l2NJV6tgOSib5e4kv5xH4BBXjkdcT9FY20Mnehj2soV4VnQoF86Zm21R931tJn6ye748b5534tbtPKUY+loLut+fAWg/9K4ytdJW1pWb4L/swEJ883YSFqo2tAreOzsDrP13n2A9zEqrEhFfmcqmo2qD36XN9QRfZuBlJ7LUuL7fiNq1n92sn3vR6ah72XE7VyrIEQTAuyHZQd8Bpn8bAK6CEk6++fD4c+/7yYA9UXVAs4cKXHuG/jaGguAxrjsfhXLxhk2sE3ZORV4yVR6LrFaq6urcWFVjhz2998dmz4SxU7R3KMeyRVMz64Tp6DtWPUDVGLCoMIDXeDmsXWuPC4VAAFSdY10HZGDEpDb7Bpp88VRfdb78bAeHN8emz9930WWNLSGkChVY8+EIie0qoEPjS94Pw5IdxaN6p8bHBx6IyuEKAlJ0RBPMkom0hXlgYhRWfBOLsflesnh+A6IuOGPNccq3VArQZS0iVAracS0JGXgn6tfCRURwz5GpKLleDoPAyfd9bzx92YW9qxr9D/p1vy8E9T6VwKUhLxyLEanqSLbb+6oMjm93Zm0d4Bx7Ho2/6cNsxS0LZ7k3511CQYB3/UiKKC6xx9oArFr8ZjGmfxCC4WeMzfbdfSIKXix2CPCqGTwRBML+yeI++GY8dv3thww++XJM1/roDJs+Oh09Qqc5jCY/cSEdaXhGGdwiEg60ZJDYI3Db1wLU0/m01uTU25t5KWf5rF/rj5C43fu3lX4Ix05PRrrd+u7gZM2YtVhOj7PHPSi8c3+GG8rIK37mN7VaUlb6G4sLrUJR/h5hLuk8wMgaoVJSbly88/YLQe/j9OLRpFTJTErRWQkoTaPTk4dcS8O2sEFw764xvXgvFc59F882mMVC88l+n4jG+VzjcHKVzgyCYIxSaTmEBYS0LsfSDIMRdccSn05rg4VcT8N3rg2+aPzczrZoHrLFx+tdS8vDbkRiM6iyJV6ZOXhG1TU1AbEaB3u+tp/a4YtWX/sjLsuW2qAPuy+B67uYWjthYzDLB6sUF0dj8qzcPEf3HVgBvAjhg0AQjXWJnY8X9rd0d7eDuZMtCzZqTjRT8pFhcVAQbO3suv5GWW4SUrFwUKWw0eorUJgW51vjqhTAkXHeAb3Axpn8Wo5XWcP7uDhjbIwx2NhYa5COohCRYmUaCVX1kJNvip3eDEB3pBCsrBTrdugen9w7m+s41UbZ6piFcbUAlrUZ2DEK4jyRemSJU7WHj2QTkFWl+zyktLoaNnV2lV7WspKSyCk599701C/xxbHuFtglqVoTxLyQitKVxjPYONrIEK7PyrN64AUyZAvzzTzi/JqPVoV8uQpqtw5ZfJqO8rG7DZWqQBvVxdUCopxNCvJwQ7OkEVwf1f86SsnJk5pdw+9JrKbn8ZKnvFnJOruWY+kEs5j8fzn2Nv/u/EDwzNwaOzo3bjuTsIo4vu7NjoMSWCYIZ4+VfimmfxGLNQj+u5Xxq921o3f06Io9RtnaBTuP0C0vKuEXrra180S1cuumZCiQqj0ZlYP+VtFrLUqlDVWFKgrUhoRp51BkrPg1AVqode1MHj03HsIfTYWtvtL5Dg2NWYtXXFzh5kgSoAt1vz+YhooBwioHshXa9fzeaBCNNsbe1RnM/F7Twd0Ool5NWaoqS19HPzYGnLmGeXK4jOj0PV1PycCU5l1/rAw+fMkz9MBbzZ4Rxvdsf3wnGE+/FwaaRZ+ilpBz4uNrjlmbSNlEQ1KFnhDcSsgqQnlfM2dFZBaWNvqnrErrRU+3V0BZF7LGKPBZGPe4AUOe8aJ3G6dNx2RWZwg/It7f1l9EcI4cqO2w5n8ihHPrukPnX977Y80fFQ41fSDHnbkS0M40RDENiVmLV1RX45RfgUPoNuPuVGHWCkTpD+9RKtHWAG9cRtdXxkDYJYhLDNA1sXYazcdk4EZ2BnELdZyP6h5Zg6vtxWPBiGC4dd8Gq+QEY+3xSowsfU9tEasnaMqAieF0QhIZp4e/KU9W+6CRco9PzeYrLKFCpnrW+6XtXFjsplrwdgPycbrC2OY7b7v0TV09/pvM4fep4lZJbhLs6BklHPSMe9t90NpE7k+m9ZCbFVl+taD7U7+5M3DUlRWJTLVGsEsOHA5e3l6KmQ9AYE4zqw9vFnuNF2ga5GSzblNbbvYkXuoZ54lJyDpeFIs+BLqEC3xNfS8APbwVzpyt68iQPeWOgZxIqRUIxvIEeFYZCEAT1oAdlf3dHnnpEeLN4jc8sxI20PK5Hqe+bf31QGbyZC2Ox+I0gJFz3wZ4/JuO+aSPQc0hqg0O0jSU1pwi/Ho7GsPYB/NAvGE+2PzkuDmuY7a8ptK6jW92x+it/FBdaw8WjFONfSuLObLok5tIZ/PXdXIx64iW9tFbXNRbVwUqTIGh9Qh5E8p7ScHy4t7NRxllSaMCuSynILtBtXVrqg0ylPIhJ/xePzlpoy+riYIMHe4VzApogKJEEK+0IAfK2kmeR6lSWlBnHbYUKrK/8NLCyJNCAMekY9Xiq3tpo08N+/xa+sLY2PltuSWQXlmDTmUTOzdAnhflWWPVlANcTJ1p0zseEVxM47E3XrFnwHvauW4ZbR0/Evc/8n9rflwQrA6JuELS+sLG2Qvtgd/Ro4g0PZ+MWUjQs2MTHGUeup3Nwuq6SsW4dnclNHCi255c5gfDwi+Vi4I2Bsj3XnYzH2B6hUhtRELQIiTEKV6KpqLQMlxJzuac6hQ0YEir/QyM1AU2KsHmpL3at9kZyjD0mzkqEo4vu4/FpNIrifod3CIKHk3HbdnOFHqB2RCarVORfm8Rft8dP7wQjJc6eW4sPeyQNt49L1+mDUrqO6wsbEovyrBobttZW6BDigR4RXiZZD5SSLsgIRKXl62T5VHVmydvBOHfQFa4epfjfl42vwUqQ9/ruzsHi7TBDqCSbrbW1Wg994lnVDXRroUTNozfSkWAEJbBO7nLFr3MDUVpsjcAmRZjyTpxW7IkqONhZ4/Y2AWgdKGEB+oKqNGy/kMxJtvrmyFY39qiWFFnD06+EH5iattf9NTDzDqp+UT+qluk0Ns+qFKA0kEjtGu6JR/s3xaA2/iYpVAkvF3vc1y0Uw9oHcmKWtqEn0IdnJSCkRSFys2zx/ewQFOQ1fj3XU/Ow63KKVrZRMB7OxmVxbdDcYuOJnbRkyLtDIzEUevNAj1B+SDQkXQbkcpc8d+9SJEY54PPnwnHtrH5i2MmrR0XnKXZeXxVWLBmy8csOROldqJYUW+G3z/2xfG4QC9XWPfIwc2GUXoQqMeGVuVyOszboffrcVBGxqkcoBJWG+yf3i8DA1v4a1UU1RtoFu3O3KF83B50M4z3+bhw8fEuQFO3A2ZS11PlWm5PRmVzlQDB9qFYwiYCt55OMJlZSqE6olzNGdw1h0WrIJMfw1kV4/qtohLYo5I5Bi14JxdFtbhonsCx86RH+qyrn47Pxy6Eok2m2YGpQCMq280n440Sc3hP+0hJsMf/5MK7zSzXehz2SiifejYOrh/4eTrrffjeX46wNel9bjTAMgYhVPdHMzwUP39IEd7QPNFlPakPVC8b3DEPHEA+tL5uC0R97Kx52DuW4eMSF69RpA0oUu5Ks/yEiQXuk5haxN5VEgGAaopUebEd2MlwMp6dvKaZ9GoOO/XNQVmKNX+cE4e8lPihXU1Mc2boOV04dwtFt69T6HjVhWXkkBnsup3BFBUF7yb/kTT0Tl6X3Q3rhiDO3+o294ggX9zLc+8xeXD11F+Kuqv4go22s/k3QNsZEbU0QsapjyItA3oR7uoTA11X7nkdjK20zpF0A7uwYpPWwACppRcWTCUqSOLix8TExFK290QAZooL2hv1XHI5GWq5hk3gE9WkV4IZJfSMwoLUfx3PqG3tHBSb9XwJufzCNX29b7sOjNsWFVg0msMRcOovYy+eqJbDQa3qfPle1icDRGxn4+WCU2J9GQh7U9afj8depeL3UA695D9m23Bvf/18ICnJsEN6GSqZFITn2O40eZLSB679lOkNbdsD9z73Nf+m1sZbpVBVJsNIRNMTfr4Uv10k1lycbdRNdqAWhto3HpqU+2PKzD2xsFXj641g069h4oUmdwKhCALWvFYwfivn752ISLiTU7hUf2zMMIZ5OKi9PEqwMS15RKXZfSsHFRMOMchzZ4o7fPg9AWakVwloXYspbcXCvo7SQNhNYlNDtgRJZqMQVdRQUVE/go6Y1e66k6D3TnyjMs8byeQE4s68ijKTroDj0v/sI7OwV+Pb1x5Gbmc4Ccer73+k9E79UxTKdlD/j6WzHo73kYKLXdrbWsLeh5kCuCHB3NBo7qhexumDBAsydOxeJiYno3Lkz5s+fj169epllNQD6sam2HhXN1kXSkak98a47GafVRgI0VEcekFO73bi48oz50fAObLwgdnO05UQQc4kjNldScoo4UaW+kkjmKlb1bUf1TVRaHv65mMzD5Prm2hknrjySl20DT98STHk3HiHNb7Zbx7b/ieXzXkV5WVmtCSzjX/xI47hAdyc73NbSVzrtqUB8ZgF2RqYgKdswsb9J0XZ8viTHOMDGrhxjpiXjt8+CtP4go008ne3YLtJor5ezPVdMcXOw1ZozzeSrAaxcuRIzZ87Em2++iePHj7ORHTZsGJKTk2FutAxwxSN9I9C3ha/FC1WChN8D3cMQ4eustWNsbQ2MfzGxMkHi+zdCuPByYyEPMHmCKUBfME5Ox2bysL+ha3caAkuwo018XDDxlibo3cyba0/rExqhodJ4/mFFyEy1w/wZYTh7wEWvCSzUaGX96QSsPhbLI1PCzeQUlmDjmQSO+TWUUKXzgipJkFClxN9p82Jxy4hso8vEd3eyQ+cwDw7Le+K2Zni0X1POmekU6okwb2dujmNKo74696z27t0bPXv2xFdffcWvy8vLERYWhunTp+PVV181C8+qj6s9BrbyR7iP9kSZOUHdbbZfTOYYQ22RmWKLz6aHIyfdFh365mLyG/EsZBtLqJcTZy3LcJzp1ks0R8+qIeyooT3oVOGB/uqTglxr/PRuEC6dcOGM7rseT8XA+6nI+n/zUHzqp8/eVznEqvw7c8EahLZsr5XtsLayYqFxSzMfDlOydKjix/GoDG5EY6jSXzSqt/VXb24uQTTrmM9xz25eZTedGzXR5rnR0AhhywA3tApwRZCH6jYQlu5ZLS4uxrFjxzBkyJD/Vmhtza8PHDgAU4eG+W9r5YsJvZuIUG2gu83QdgFseLWFp18pHn0znodgzu53xeZl2ll2bEYBNpxO0FlnLkH94b5fDkUbpLC3sWDudrQ2/NwcuGpA76beLNz0hZNrOZ54Pw5978qEQmGFv77zw2+fBaC0RL8JLJSAdSI6Ez/uv8FNFUisWSJULYE6oS3Zdx37r6YZTKhSfOqP7wRXCtX+92RwzkRVoWqoTHzbfztg0kP6lP5NMaCVn96Fqj7QaYBeamoqysrKEBAQUO19en3x4sWb5i8qKuKpqlI3Vihxqn9LP4lxVIM+zX14eG/flVSt/AbUfnXs/5KxfF4gtv7ig6CmRfAJPIC/vpuLUU+8hLBWHTUuKE1xkSM7BkmXKwNBnqojNzJw4Goa37gtGXO2o/VBtoJCqpr5ubKXVV/hHza2wJjpyfAPK8a6b/xwaJMHUhPsMHl2PFzcy+HpF4jZy3ZUJrD0GTmuzgSWxlJQXIY9l1NZsPWM8ObSgFR1xdwhZwGNxB25ka73DP+aJMfaYclbwVznm5wj909PRu/htV9TygcZT78g9B5+Pw5tWoXMlASdZOK7OdrykD6dE0725u99N6pskg8//BBvv/02jBka8h/U2p9jPgT16dXUm4fU9l7WjmDteUc292CmclYr5gaiXZ8TlSVDNBWrypp9W84ncncuU4rrMZfEvE1nExGTrps2vuaOKdhRdaCEkAm9w7HnSio389AHdMnfdm8mfENKsPQ9f1w95Yx5TwXiyQ9TEdikuJowJfugC6FalbyiMk4oOhZVIVqpEYs5hipRzsC5+Gz2KlMMr6G5cNgZyz4MQmGeDdx9SvHoG/Fo0rbuWFl9PMgEejhyEncLP1eLcqbo9Gz39fWFjY0NkpKSqr1PrwMDA2+af9asWRzvoJxiYmJgTEP+t7asGPIXodo4yNjSsdQW/UadRpO2SSgussapXU/SIKJGtQ9rQqWRKFZS0B/0kEC1J0Womqcd1RTyJpKT4O4uwXr1IrXrlYf2fd6gegHISnXFF/8Lw/nDhmsbS15GqpiweO91fuCnhCNzICu/BDsjk/H9nuvYFZlicKFaWT91dggL1Yh2BZi5IKpeoaqEhGnVMABtCVVfNwc+/yk8huoUW5JQ1bln1d7eHt27d8f27dsxevToysQAej1t2rSb5ndwcODJGLP8KQ7EHDtPGQoq7UUXMtVXbCwfTB5Ez7QADkGhaAVgNXIzb68W6K5pyRDqhmJrY8XtcQXdQbFo1FFMm0l45oK52FFt0NzPFf69HdjzTvHluoIecPOyKLHKCpdPfAvgO1jb/Imi/L74fnYwhjx4FSMml1dLvNInFB5AQ+TkaaV6mF3CPdVKKjSWxNvo9HycjsvCtZRcFojGQFGBFZbPDcTpvRX1Uyl+efTTybC1q2ix29gwM026Q97SzIeTpix5lE/nYQBUbmXSpEno0aMH1wT8/PPPkZeXh0cffRTGDtUlo6f5CF/DPUmbMzSUQVQVrJoYAyoJUlH7kMrGHAJwK1WlBDC1svZhY6AhKYqbpHPBko2FrqASNFSOJsMA9TVNBVO2o9qGnAb3dw/F4evpOHgtXScxze9NHHzTe+VlAyvsiuIJbFveAllpWbj/uWQuAm8oaN8p+ZAmL2c7tAp0Q5tAdxY4xkpiViEuJmbzNlN4gzGRElcRn5oY5cCNZ+6blow+d2bV2mJX12KVRhD6Nffl5ClrC/OiGkSsjhs3DikpKXjjjTe4mHWXLl2wadOmm5IFjAnKriPPX88IL4sIZje0YKU4pUPX0jU2BlTbMCC8+b+e1AcBrAfwBFXmxPNfDtZKyZBTMVkoLlXgjnYBYji06Fkh79Ch6+lSfcEM7aguoYfG3s18EOLlxC2TKc5Zm/z3AFxVTNHD1FRYWZ0H8AmObPFAUrQ9Jr+RAE9fwyYBEfSwR3aUJqqm0CbQDU19XQzemY+u8/isAkSn5eNycq7R1kmm8I5fPgpEQa4N3LxLOaGuafvCal72qi12ew69Vyedqaj6RadQD05IlrJl/yHtVmvQxMcZg9v4w9PZeJ9MzY2oqChsPBqJy0l5Grepq177cAbfTIBSjJl+EP1GaW8In2KFhncI1HvRcnODbliU4U1eFm1jjnVWG4O57x+1a92og4S8+mpm5mX3xNIPgrgffFVhY6zNWcK8nRDq5cz5Fh5Oug1nI5tNwpl+j6j0fP5rqJJT6tRP3bLMh8uVNWlbwHW7Pf5tuauLFrt1QXZrYBs/+Lup3ubUUuyMUVUDMCRUBuK2Vn4sRgT9EhERcdN7uZlpasWcVi0Z0muYBzb+tA752fdgw+LeaNUtFn4h2hlipqGr0vJyLmslXnfNbmTHozOx/0qqwVoiC+aFi4Mt7usaggPX0thTr+2ogJrF/4nW3fO51fMPNGR8wwELXwrDmOlJ3MlIiSHiG2uDvM6ULEqTUrxSVRvyuPq42MPX1YFD3hxsrdUKc6LyUnnFpcgtLEVqbhE3cKApLa/YqMVpzSYQv3wciPOHXP+LT30qBbZVQjtq97JXoI0wM4I8qFSzvX2wR6OXZa5YvFgllzsFp/dp5iMtUg3Ezz//jMmTJ6O0tFRjY1CzZEjPO4CFL+YjOtIZi98Ixv++jIGTi3YM6LWUPKw7GY+7OgfBwdb869tpM+N38/lExOkwMUawTCimr18LXwR5OGLzuSTuetZYGqqZ6Rtcgv99EV2ZjPPbZ4GIvexYKXb0Gd+ornilKSot/6Z7oZO9NZzsbeFkZ8PilSSbUqDTHxKo+SVl7M2mY2wsSVGaQCUPf3w7GKnx9rCl+qn/S0avO7IbCDO7ucVuY8PMmvu78mguPUQIdWPRR4dc7oPa+HN8j2A4JkyYgLZt23LGc2OMQdUSIfYOwGNvJ+DzaRU9nJd9EITH34mDtZa0JWWx/nYkBnd3CdH5sJquOXr0KF5++WXMmTOHE3h0EbN2IqaiwH9JmQnf3QSjhxoIPNTLAX+djm90q1ZVamY6OCkwaXYCti0vwqaffLB/vSeunSnHXY8frjO+MS8r3Sg8rrUla1HCk7ElPemCY9vd8PvnAVzu0CughOunhrYs0sjL3pgEqoGt/TghTmgYixSrzvY26N/SF+2C3CW728igNpJUlkcbxsDduwyPvR2P+TPDcPGIC7dOvOepxpfKUpKaW4wVh6MxqnMwgk2sbExVli5dih07dmDZsmVaF6vJOYXYdj6ZM/4FQR94ONthXM8wbL+QVDn0rSmqFP+nkfOhD6UjpEURvv8/JyRGUX1Ouo5o2nJTSFP/eyYapcfVEigptsLahX44+DeVOgRadcvDxNcSuDNZfWi7MxV5U29v488hLIJqWNSRIqNCWXZ9m/tKlp2R4e/vzwXOw8LCMGXKFHzz7Xe4eiOq0W3q6Gl5/EuJWPpeMHat8YJfaDH63qW9Wp75xWVYfSwWd7QPROtAN5NKaqM2nnQDXrlyJb+3YsUKLo9EDwlUiL5JkyaN6ulNWf5Hb2RYfLtUQf9Qd6fhHYLg7+6IPZdS9XIOUgOBe57agHVfd/tXqG4E8A6Ad8lvCStrawyfOB171i3TeUa5UHtZqqXvBSHuqiOsrBS44+E0fshQZbRNW52p7GysMKCVPzqGSmyqulhMNQBqUUZxIQHuppdlZylQP3MqgK70qt5IzsL6sylaScShbM+NP/rC2lqBJ96P4wQJbT8IUeHm3txO1vgrBVTdxrqGtjQ1DddT87ArMtlgdVOlGoBlVQNoCMpG//tMAj9Y6oMb5y/gy+cTADz17zubAUwkuaSXjHLhZk7tccXKTwJQmG8DV49STHg1Uev3gIbwd3fAiA5BRl0D15jtjNkXEaUsu9vb+uPBnmEiVI0c6rpTtU1d0wBPDOsQqJUuMUPGp6P77dkoL7fCT+8FcX1EbUK6jmIyKfEqv9jwNRdVSWqzta0YWPkvgaLiL71Pn2uSQLXuZBz+OBEnBf4Fo4HKNY3vHa43+0/JOsDTACbR2AuAYVzz2cqK/qLWJFLKOBe0T3GRFVZ/5Y+f3g1modq0Qz5mLorWq1Cl+1e3Jl54sGe42QpVfWC2YpVOkI4hHpjcNwKdQj1Nwtsl3AyVEuvfwrfRh4Z+/nEzktC0fQH3eqaWiblZdZ/+VHZm4UuP8F91vYrU2z4qLQ/GntR26BB1+7oZep8+V5WSsnLsv5qKpQducKUEQTA23B3t8ECPULQN0n2ojjK+MazVCQyd8BNs7a/Q2B4Uik0AqLKJ3U1JpJRxLmg/258SbPf9WRGfOuiBdDwzJ1avDRwoiWp0lxBu1y61uRuHWYrVAA9HjO8VjiHtAvhkEUwb6iZGDx6NhcrJPPpmPLwDi5GWYI8lbwejtLj2h5iqZWfUhbJp156Iw57LKSbRmYmS2qr+VRXyxJ6Pz8bSA1HcNUfqpgqmEMd6a0tfjUZrVH2AVcY3Pj//d4yYdDve/b0ct4xI+/fTVwDspboF4kDRETRAtGedJwtVapvq5lWKqR/EYtQTqbDRY5ZOsKcjJvQOl3btWsIsxeoD3UNlyN/MoHjjcG/nRi/H1bMMj78bD0fnMlw/64zl8wK4gwlBbfViLp3lzjVVy87Qa3qfPlfHYFJy0e9HY5CW27gSOrpOaqOSYV9//TX/pdf0fkNcTcnFz4eiuQtVdoFhYlMFQdOHX/J2Odipd/tT5wGWEm+Uo3kOTsDYGWkY+/w5wCoDQC/Y2p2Hp/9suHr6NjqJVPiPnAwbrqu9doE/Skus0bZXLl78Ogpteug3PrVruCfu7x4GN0fTLmtoTJhlgpVgnlARaioVpY3EnUvHnfHt6yEoL7PCwPvTcffUVJ211aPhny5hnpyAZW9rbdRJbcXFxRw7XBdxmQXYdzmV/xorkmBVHbGjtZOZX4w/T8UjLbfuXvVV+8Jr2gq6KqlxCqz4NAzXzlQ8eLfunoNxM1Pg6Wf8ce7GzsldrhyfmpdlCxu7cox6PBW3js7USs6DqpB9v6NdAFpaYCfMbB3rNRGrgkmRkVeM5UeiUVTS+G5UR7a6YfncIP7/6KeT4eK+tMG2eo2JLaOWvre29DOpEldVY3GP3khHrAl0nxKxWh0Rq3VTVFqGTWcT64y11sUDbHkZsHutF/5e4sPeP0eXMtz7dAp6DM3Wq7AyJ2/qmq/8cWpPhV0NalaEh15KQEjzuh9CdIGvqz3u6hQMLwtNosqWagCC8B9kCEZ2DOLWgI2l59Ac3PloKv9/3dd+sLV/iJMdakMbSRA5haVcQmfVsVgkm0CRfOo8dTExmxPGKMPfFISqIKgDtUu+u3MwekR41fo5ZenTg6o2s/iprufA+zPwwqIohLeuSPhcPi+Qh68zUyyq9LlWvKlzpjZhoWptU1E7dcb8KL0L1ZYBrhjXM9xihao+MK4xSUFQgSY+LhjQ2k8rx+r2B9PR965MKBRW+OWjQMRdqYgfq1pCSxd1H385FI01x2MRXaM/tzFAfcMPX0/Hkv03sPFMYqPbVuqbUhlRFdSArnEa8RjeIRC21tWvd3pA1dUDbEB4CaZ/HoORj6XwsPX5Q674+PEI7FzliTIjPYc1rZKibdKTbPHDW8FY+n4wD/uTN/X5+dEY/kgabPUYJkq3B+qGSR5VYwvxMjfkMU4wSSgGlBKXTsdmNdrY3PdsMrLSbHHugCvWfdsHzu594ROYo5W2evURlZbPE9V/JM9OS39Xg2UIU9WCaym5OBefzdukj44/2qYw34q7lH3+hANOnwI8pEmMoAZtg9zh5WyPv07F8wObLvvCKyGn7e0PZqBd7zz8/kUAbpx3wp/f+uPIVg+MmZ6EZh2MawSmapKZIVrFUvWWnau9uMlLSZE1e1OphvaQ8foVqcoa7iM6BEq2v54QsSqYLINa+3OyFXkqGwMNy02clYBFr4Qi6oIT3L13YuJrMfANLtW4rZ46JGUXYsPpBLg62KKFvysPKYV4OulcuFK8Hh27G6n5uJKSiwI9dfjRReHv/X95YPtKb/ayED/9BDz3nKG3TDA1qNMhNRAgwZqYVaiTvvC1EdS0GNM+jcGRLe5Y/70fEq474KuZ4eh5RxbumpIKNy/DXZtVk8yqVknRd6tYSoqlBKqU2Apb3LxTPsZMS0ZghH6H/AlfNwfc3SkYHs6S7a8vJMFKMGlIYC0/HI0sLZRPysu2xoIXwrg2H9VinfapfgtI09DaX9/NxagnXkKbjl1YuDbzdeU2fc72jX+uLC0rR1peMWIz8nE9NR/xmQUmUQe2Lmio9PAWD2z52RtZqRU3Db/QYrzzDjB1kj1ULRtr7glI5r5/uoCulW0XknEhIbvidXFxZV94Emi6fIAlO7R+sR8ObawYGrB3LOcYV6pa4uis/+tVV1VSVCU5xg4blvjizN6KBCqqm3r31BR0G5yjcb1cpZ3VxDtMdnlY+0AZ9teznRHPqmDSUNOHUZ2D8dvRGBSXljfKQLm4l+Opj2Ix/4UwpMXb4+tXQvDsvFi9eTVqDrGdisniSVlJwM/NoWJydeAhKAdba04QoXqRVPCcOkkVlZajqKSM/1KpL/I8p+YWcdxpZn6JSQ7v14R2gXp9b1zii5S4CsHg6VeCYRPTOKN61C1hKgtVQagNW24gEMgZ3nuvpFYTpiRYdTnSQnaIuu31HpaFtQv9EXPJEVt+9sH+9R6cQHTLiCy9DnlTEllDVVJ0ASWbbf7ZB0c2u3ObbCtrBfrfnYnhk9Lg5FKu91AGEsa9m/rglmbe0tDBAIhYFUweEnD0pLv+dDwLmcYYKHefMjz9cSy+mhmG5BgHfDMrBM/MjYWzW+NLZTVmiI0qCdBk6e1ML590Yq9TTGRFn3dXj1IMeSgdfUZmwc7e9IW4YHwNBHxcHbDxbIJWyuWpQ0S7Qk4aogezv3/wRWq8PdZ8FcBx2XdMSEO3QTl66chESWQB4c3x6bP31ZpkFtqyvdY9y/+s9OYuVKXFFU+dHfrkYsTkVA6XMEQoAyVPDWsfgBb+pld20FyQMADBZDh69ChefvllzJkzBz169Ljp84PX0nDgappWCnonx9pxSEBOhi2atC3Akx/G6mQIztBDbKZC3FV7bFjsh4tHXSqHRqnX94AxGTf9LlJntToSBqCd+s7UQCA9T//xkcqQl4MbKeTFh22ScjSBzn/ytDo46fZBjbr4kVitmWQ2c8EarYnV9ERbrj97aJMHigoqRGqzDvkYOSUVTdsXGszOujvZcXkzcooIdSNhAILwL0uXLsWOHTuwbNmyWsVq76bePOR9OSmXX783cfBN8+RmplXzENRloPxDS/DkR7FY+GIYJ119938heILatDZi+MmYhthMhYxkW2z80QfHtrtzeTHK/iUvKnmWDJl0IlgWVD9zXM8wbi9siNEN8qD2G5WFHkOysXedJ4u6zBQ7rPvaH5uWesLZbRke+F8A2vRopZP16zLJLOaSA3au8sKp3W483E+ENC/kGthteuZrpVGCpnY21MuJy1JRuJlgWMSzKhg1UVFRSE1N5Sf5ESNGIDk5mXvXb9y4kZ/sfX190aRJk8r5KW6V4lcpRvPY9j8b3ZEqOtIBX78ayoW7w1oXYur7sRxTpguvRU206bUwNQpyrTm7f/caT+7yQ3QZkMNDgX4h9SfTiWe1OuJZ1R5kc/ZdScORG+kwJCXFVji61R07fvfi8ADCyqoU7W8pRK9hWWjbK0/rIQLaTDIrzLPm8AaqfnDtbEXrWaJVtzwMuj8DrbprR6Q2xs52CvXAwNb+3C5baBjxrAoWTUREROX/laWcUlJS0L1798r3q9Y8pNgiSrhacTi60bFWlJS1/vu5uG/a+1i3aCDHSS58OQxPfaibpCtd1HE0NUpLgP3rPbH1Fx/kZVd4M5p1zMeoJ1LRpI1x1ZwULA+6NqkIPA0Jbz2fiJIyw1ynORmxCG2ZgYdnWeHrV9ahMP9JKBR9cPaAK08u7sXoeUcuZ8yHNC/SivBrbJIZ+Qyo/NTRbe44s8+1Mh6VRkso/nbAmHS9dJ5qyM5Sd8SBrf3QOcxT59siqI4kWAlGzc8//4zJkyejtLS00rAo/9ra2uLHH3+86TseTnYY2SkIa47HNUoIKpOygpr+hGfnNceiV0ORcM0BC14MxVMfx2mtrJU+6jgaO/STUOvEv5f4Ii2h4iYYEF6Eux5P5YLp0jNdMCZaB7rBy8UO608laKVsnrrcHOL0E7U1APAogInIyw7EzlXePHn4lqBtzzy0uyUPLbvk6zy+tSo5GTaIPOaMyGMu/Dc38z/J4R9WhJ5Ds9F9SI5eSgSqYmdpuJ/aeYd5/+ftFYwDCQMQjJ7jx49X86QqOXbsGLp161bn987EZmHV7lP4bNqYmwzUjK9Ww9Mv8Kbv1JeUlZ7kjDULBiA7zRE+QcVcNcA7UDtGVp91HI2Na2eoa48voiOd+LWbdym3TaThzDrasteLhAFUR8IAdAeVh6NKAdRYQ5/UF+JkZe2A20YvR3rSEEQedUFx0X913GztyjlZiUKaQlsWIqxlIdswbTwMlpeBS8nFX7NH7BVH9qLGXamo2qHExb0MXQdls0gNbakdj6+27Cx5y2lUjpwdgvHZGRGrgsmIVWtra5SXl1f+bUisEjsuJuPo1WSVhWDDWaNN4BN0ib1/JKoefycOYa2KGrF3lktilD02/ODLbW4rM/zHpmPgmIxGeX9ErFZHxKpuIZuy/2oaDl/XbxyrKjGYFNt65ZQTLhx2wflDLkhPvNnuObuVIahZEbz8SuHuUwoP31J4+JRy8X3q7mdtreC/VOdUUU6lpWzYQ5qbSX9tuFV14g0HJNywrxzar0pIi0K07p6PNj3yENGuQO9tUVWhVYAb7mgfwPWqBc2QmFXB4qGEqsDAQISFhWHKlClYvHgxYmJi+P2GGNDKj7s2KVuyNhRr1XDW6DQ07xyLb18LYQP91QthmPBKIjr1r6hAIDRMZqotNi/1weEt7lCUW/HN8JY7s7iof2bKSSx+Q/PuMoKgb8im9GvhiwB3B2w+l1RvcxJdrb+uECeqPdy2Zz5P9z6TguQYe1w/58iNBmIvOyL+mgPyc2xw9ZR2hr3pgTOoaRGCmxWhafsCFqnaiO9vbNepuiDPbt/mvujV1FtryxR0g8SsCkZPaGgobty4AXt7ezbIU6dORXFxMRwcGq57Z21thbs6BXFLVurg1BCqJWWV4rnPYrD0gyBcPOKCH98JxsgpKRg8lsIHNN5Ny8nwX/tfse+O/XK4RE1AeMVvs/VXzbrLCIKhoYLx3i4O2HA6Hqm5uk8UUjfWnWxTQHgxT7eMULaRtWKPaFK0PXtIs1JtK/6m2CI3y4YfJsvLwSWlyKtKuHiUwdWzDG6e9LcUrh5lvMzg5kXwCSrRSfc4TbtO1Qcl447oEIhmfhUjO4KFitX3338fGzZswMmTJ1lkZGZm6mpVggVQVZiSYFVFqCqh1qRU1Hnl0Ri1utDU57GgeqtT3onDuq/9sHedFxesT4m1x/3PJRnlMJchKS60wt4/PbkrDXlxiKYd8jHq8VTu0kNxwjGXNO8uY+6ILTUdvLkeazj+uZiECwk5Ol0XxdzPXrajMsSpz8hxase629orOIzJGEOZGtt1qj6ojS7VT6X6uYKFi1XyfD3wwAPo06cPD9sKgiGhlomU5fnHiXiUN1ANQFWPBSX/3PdsCvxCS/DHIj8c3uyB1Dg7PDwrEZ5+us9uNYUyVNR1Z+uvPshJrzA1gU2KuCNN1Qz/xjRvsATElpoW5LEb3iEIwZ5O2BWZgtJy3WXfN7aclDGjK7tA8alD2wXw7ySYDjpPsKLSQs8//7xGnlVJDBC0zamYTPxzMVnr2fkXDjtzWEBRvg0nLDz4YiI69NF9pxtdxXI1Bgr3Pb7dHZuX+SA9qcLN7B1QwjGp3W/P5mSNqmijeYMlJFhpaktNZf/MkaTsQqw/nYBsA5S3MnW0bReofmr/lj7o3kTiU3WBru2MUT1aFBUV8Q5XnQRBm1Ch5y4qFHsmYapsQqCKx6Jtr3zMXBDN5WBoqPuHN0OwZoEfZ+PqkqqxXIaG+pdT0tTHUyKwfF4gC1V371KMmZaEV3+4jp533CxUCbrhUDxwbdD76tyQBLGjxkSAuyMm9A5HywBXnT6wLnzpEf5rTmjTLjjb2+C+biEiVE0Yo0qw+vDDD/H2228bejMEM4cqBGQWFGu9NiK1AX3u82gux7RrtTfHskYetYKT65MYM32s1jyfuozl0nS4/8hWD2xf7l3pSaV6ilSGqv/dmbB3VH3wRrp4NR6xo8YFxcxTfCTVfd51KVnrXa90kXxkbDTGLoR4OeHOjkFwdTAquSOoiVq/3quvvoqPP/643nkuXLiANm3aQBNmzZqFmTNnVr4mzyqVKxIEbUIVAsh4/XYkRutZu5Rcdc+TqWjVNR/L5wYiJY68uD9h9fyNeGaeFewdGn+jMpYYz6ICKxza5IGdq7yQmVIhUik7eOD9Geg3KlOtWqmW1sVLl7ZU7Khx0jHUA0Gejth4JqHRdsfYHlh1RWPsAg2M9Yrwxi3NfNjmCxYUs0o92dPS0uqdp1mzZpz9r8+Y1bKyMpSUSEyQoB65RSX4+3Qi8ovrSoayQnG5FcpgpdGNJC/bEYvfcEBZ6e38vodPHgbefwod+xc16kai7VguTeqk7l3niQMbPFCQWzGuTw0SBo9NR587s9TypOqii5cpxKzq05ZKzKpxUVJWjj2XU3AqJkvjZTTcvMR8khI1sQs07D+iQxDCfaRtqkU2BfDz8+PJWKATNzExUcpiCRrTzVvBYrWuR7YyhQLx+daIKSTjaKWh5/N+AJ8hKy0U677pi3Xf/InXf7KFT5BmFQNUqwWrXej4xF52wJ4/vHB8hxvKyyqOhV9IMW67L4PjURvrNTbnzGZjt6WC/qAuSYPbBKCZryu2nk9CbpH6dqDh5iUfwVxQ1y6EeTtz/VQXGfY3K3QWxBEdHY309HT+S55PqrdKtGjRAq6u2gk2VwpV6mTk7OxcmRAjCOpQXFqG7MJabhgKBYqLCmGXmkJzIabQQcMbySoAGwHMJp8IgLvx0RQFegzJxqAH0uEfpvmogK5jPKmQ/7F/3HDwbw/EX/uvz3ezDvk83N/uljydFAEX9GtLBf0T4euCiX2acHWSyMQco39gNXZsra3Qt4UPuoV7iRYwQ3QmVt944w389NNPla+7du3Kf3fs2IGBAwc2evlktJVC1cfHPOPaBP1AEszOngTrzaLRzqFCoJWUJSG+UKFSSEDtNxIqY/UqJs3ujgPr++DSCReO9zy82R0d++Xi9gfT1SrMrcsYT9LY1047cdLUyd2uld2mbO3Kua0seVLDWxtfEXFzRde2VDBs8hXFz7fwd8X2C8koLFG/NakkJQJ+bg4Y3iEQvq6qN4sRTAudiVWKr6JJVyhjVMmjKgiNxcnehof882oZkrN3cISNlRXsrRUoKLdq1I3EJzAHT30cx/25//nNG+cOuOL0XjeeWnTOZ29rh765cHYr13n3mqpQ28VLJ51xZq8rzh5wQV7Wf6YhMKIIt4zI4hqpLu767Xsu6N6WCoaHCtVTnPWuSykqe1ktLSmxNmgwtXsTL/Rt7gsbSaIya0y+loMM/QvagkqblJcrUFDTu1EZXtL47Pbs9BSuiUhF/Ke83RGJN+zxz29eOP6PO66ccubJ5gsFWnXLQ+fbctGhT93CtTExntTvOzHKHtfOOOHaGWdcPOKMwvz/iqBS6amO/XLQe3g2wtsU/ncIBEHQCRRjSV7WtkHuHBrQUCMBbT+wmmJr2yHtAtRKphRMF5MXq4KgTdwcbdkDWljaOA9iXTeSP7+bU60mYmBEMR56OQnDJ6Xh2DZ3nNzthoTrDrhw2JUna2sFAiKKEd6qEGH/TkFNi7hElqoUF1ohNd4OKXH2SIm1R9QFR1w754SCnOoV+qmAf8f+uejUPwfNOhZwO1lBEPRLU4plvaUJDl5Lw4nozHrbQ1tSUqIS8qD2jPBGr6be4k21IESsGjkRERFcroYmc8DY94cMvruTHRQFJShqpGBV3jhUrYk4dEI6T0nR9hwremq3GxJvOCDhWsVEMa6EtY0Crh5lcKHJ/b+/ZWVWKCm0QnGRNXfOKi6wRnqSLbJSa1e29o7liGhXgOYdC9CiSz6atC2UZClBMAKob/1trfzQJsgNuyJTEJtRYOhNMgqowP+QtgHsVRUsCxGrBiImJgZvvvkmNm3ahNTUVAQFBWH06NGcTGHJCWNvvfVWZRczGxsbeHp6ol27drjvvvvw9NNPw8FB9QD6nTt3YtCgQcjIyODlqAqJSg8nO2Tml6C4rFzvRfwDwosx7OF0njJTbBFzyQExlxx5ir7kyB7R7HRbnlTFya2My0xRl63gZkXsOQ1tUQgbsQCCYLT4uznigR5huJKcg92XUpHVQGiAuUJ1U/u18EX7YHcJ/bNQ5Fb1L0ePHsXLL7+MOXPmoEePHjo96NeuXUOfPn3QqlUrLF++HE2bNsW5c+fw0ksvYePGjTh48CC8vb1hCKjKAok1awPWI2rfvj22bduG8vJyLpxOovO9997DsmXL+P9ubm463wYWrM4kWIvR2NtDY2oievqV8tSxX15lvdOsNFvkZtogL8sGedk2/P/8HBvY2CpgZ1/ORfntHMph56Dg75JIlcQoQTBdWvi7IcLHBSdjMnHoejqKGznqYyrY2Viha7gXekR4wcFW4pIsGamQ+C9Lly7lUjAkiHTNs88+y51ptmzZggEDBiA8PBwjRoxggRYXF4fXX3+92vw5OTkYP348XFxcEBISggULFlR+RsPI5I2kZZDXMTg4GM8991zl50VFRXjxxRf5e/T93r17s+BTQlnG5HX8888/2YNJy/j+++/h6Oh4U7OF//3vfxg8+D8v4d69e3HrrbfCycmJ2+LSevPyKkQVkZycjFGjRvHnJMh/+eUXlY6Pra0tAgMDeV86duyI6dOnY9euXTh79my1FpX0W9GDBYlXmv+hhx7idRI3btxgryrh5VVRd2/y5Mn8mrzZ/fv35/0mL/Zdd92Fq1ev3rQd1lZW8HSy50oAjYFKWVHtw9qg99XpNkWb4ulbitAWRWjdPR/dBuXgtnszMfyRNAx9KB0D789E37uy0HNoDrrclouItoUiVAXBDLC1sUaPCG882i+CxRuFCpgrZOco0eyRvhHsURWhKpjv2a4CUVFROHbsGI4fP46VK1fyeytWrODX9D59rm2ouPfmzZvxzDPPsIirCgmuCRMm8LZULfA+d+5cdO7cGSdOnOCe4iQat27dyp+tXr0an332Gb755htcvnwZf/zxBws8JdOmTcOBAwd4v06fPo0HHngAw4cP53mV5OfnswgkkUoeXtoGEnK07KoeV9ou+owgcUfLGTNmDC+XPiPxSutTQuKQwh3oIWDVqlVYuHBhpZhUF+qRToJ+zZo11cqXvfvuuzh16hTvNwlUpSAl8azc/sjISCQkJOCLL77g1ySoZ86cyd707du3sxf53nvvZU9uTainNIUEaKssirJ6hVSxEARBE5ztbXFrSz881q8pJxmZk2gl89jMzwUP9QrnuqnujmpkkgpmjUWHAVCyjxKleKCe3d27d698X9tdgUgk0jLbtm1b6+f0PsVY0nZQwwOiX79+LFIJCh3Yt28fC9ShQ4dyVxsSuUOGDIGdnR17WHv16sXz0mdLlizhv+SlJMjLSp5Fev+DDz6oFH0kJEkQK3nwwQfx66+/YsqUKfyaRB15WkmcEh9++CELV2WiVMuWLfHll1+yp3jRokW8TgppOHz4MHr27MnzLF68uM79VlWwkjdayWOPPVatjzqtn9aVm5vLnX2UoRR0HKvGrCr3QckPP/zArS/Pnz+PDh061CpYKWaKCk9HZ2nWIlVqIgqCoO3a0OR1pDqjx6MycDouCwXF6jcVMAZoFKt1oBt7jKWwv1AbFi1Wf/75Z/bElZaWVopS5V8aitZlIW51RDDFt9Z8/fnnn/P/yVNK/yexRp7OO++8k4feafvPnDnDHlESuFWh0ICqSVwUktCpU6dq85AQveWWWxAfH89Cl4bwR44cWSn6yJtJHtWqQ/u0T+SdvH79Oi5dusTbUFX4k9hUJ9GpJsri+krI+00hELQtJPCVnlESyhTSUN8DAyWyHTp0iJPbqn6vNrFK0HqHtgvApovpiNMgM9fSayLqGjotKBmFyv74SKawYGFdsPq28GUv66WkXJyOzURCViFMAfIKtwt2Z8EtXlShPixarJIgI09fVUGlhIRMt27dtL5O6udNYuXChQs89FwTep9iLMnTpwo03E3D3BTvSqEBFF5AYQMU40keRsqoJ1FHf6tStac4hSPUHJYmD2Xz5s05fICy8NeuXVtNvNOyn3zyyWrxsUrIu0tiVdvQsaHYV+VQ/rBhw3giwUzHi8QmvS4uLq53OSTmmzRpgu+++46FOIlVEqkNfc/e1gb3dg3BX6fiEZWWr/b2W2JNRF33Ag/3cUYzX1c09XPhpg6CYMkxrST8aErOLsSp2CxcSsoxumQsutUEezpxZn9LfzezCmMQdIdY93+huEUSLcq/uoI8mjR8T8PuM2bMqBa3mpiYyMLrkUceqSYeqTpAVeh11eF0WgYJMJooeYs8mORVpR7i5FmlOFFKhNJEzNP2hIaG8nEhz6oSEvI0bE7iuzZoG8hjTUJZGQZAorpm0paqXLx4kcMXZs2aVfmaKgV89NFHLNgJikGtCnmMCToGSug7tB0kVJXHhGJtVcXOxhp3dw7GhjMJuJbyXzKZoD+BGuHrgpYBrixS5UYnCDfj7+6Ioe0cMai1H6LT83E5OZftVWHN7nx6xMvZDq0C3dA+yIMrrQiCOli8WKV4Ror5JMFD8ZkUV0lJQcp4UV3w1VdfoW/fvuwFpJJMVUtXUdb++++/X21+ilGlklpUh5W8p7///js2bKgoLk/eThJjlOXv7OzMoQ0kXslzSMKYBCeJ308++YTFK8XCUvwpDftXFZ+1Qd+lYXbanvvvv79ajdNXXnmFwwQooerxxx/nSgMkXmn7aP9at27NYQnkfaUYVgoJoPjWmklltUEil4R7zdJVXbp04WOk9N6SGJ0/fz6eeuoprhRAyVZVoWNAon/9+vUcHkHrJq81HZdvv/2Wa9uSN1YZD6yOB2NUp2BuiXgmLkut7wrqQ8ltTXycOaZNBKogqGermvm58kStpGMy8nEjLR/xmQVIySlCWbl2czKqQg+SYd7OiPBxRhNvFxGoQqOweLFKXkPKIifhQ8Jm6tSpPBysTvF5daFkJPICUlOAsWPHcoUAEswkRum9mjVWX3jhBZ6fiuW7u7vj008/ZaFLUAwoeRcpu51EK1UC+OuvvypjUimRioQeLYPKYvn6+rLIpHJNDUFeU0rWoiQpZYysEhK7FGpAZbbIQ0nxpBQ2MG7cuMp5aN0kZCnpKiAggLdj9uzZDa6XhDsJSQpd8PDw4PhT8qhWbQpAw/4k1F977TVOrCJP77x583D33f+VgSLhT8eMxOijjz7Kop2+Q6ENFL5AQ/8kqun7AwcOhDpQ0hX1pfZyscOey6lc/1TQLgHujmgb5MYilTKgBUHQHLJZTXxceCJKysqRmFXI8a1J2YXccIAmTcIGKG7Wx9Uefq4OFX/dHDiGXFtVVATBSqHtdHctkp2dzWIlKyuLRVpVCgsLOZGHvJJUE1QQdEVD59qV5FxsPpdodLFhpoiLgw3aBXlw3J2+WirWZ2fMAXPfP0G7UEUBEq25RSUoKVOw95Wm0nIFOyWo5qmjnTULVJqoUoqLxItbPNk6tjPirhCERtLC3xXujqFYdzIeuUWalbayZKhsTYSvMzqEeKCpjwt7gARBMFxJLJoAcQIJxoOIVUHQUkLDg73CsPFMIuIy1S9tZYlQswUSqORFlUx+QRAEoS5ErAqClnBztMP93UNx8FoaDt9IlzjWOryo1KGmU6gHwr2dpZOXIAiC0CAiVgVBi9AQNhXopizYTWcTJSzgX9yd7NAxxINrK0p8myAIgqAOIlYFQQeQWH34libYcj7RYuuxkheVivV3CvHg0lM1G08IgiAIgiqIWBUEHUFJCvd0CcG5+CzsvZyKfBPt262JF5U8qBSPKrGogiAIQmMRsSoIOqZ9sAea+7niwNU0nI7NQrnxVotrVGep5v6u6BDsgTDvm9v3CoIgCIKmiFgVBD1A9QgHtfFnjyN1vqJC3OZUuL9tkDvvoyAIgiBoGxGrgqDnElfjeoZxr+7D19O55aGp4eZoy+K0TaAbfFx11+lNEARBEAgRq4KgZ2iIvFWAG083UvO4zFVchnHXZqXY0+b+Lmjp74ZQLxnmFwRBEPSHtR7XJfzL5MmTWbA89dRTNx2TZ599lj+jeQTzJ8LXBWN7hLG3lcSrnY2VURXt797Ei7ft8VubYnCbAK5yIPGogiAIgj4Rz6qBCAsLw4oVK/DZZ5/Bycmpsgf9r7/+ivDwcENtlmAggj2deCouLce11FxEJuYgKi2fe3LrCwc7a4R5ObMgpYL93i72elu3IAiCINSFeFYNRLdu3ViwrlmzpvI9+j8J1a5du1a+V15ejg8//BBNmzZlUdu5c2esWrWq8vOysjJMmTKl8vPWrVvjiy++qLYu8tKOHj0a8+bNQ1BQEHx8fNiDW1JSoqe9FVTF3tYabQLdueTV1NuaYUTHQHQJ8+REJhtrK63WQPV1tefY0wGt/TC+Vzieuq05RnUO5vWJUBUEQRDM3rN648YNvPvuu/jnn3+QmJiI4OBgPPzww3j99ddhb68bjw1VBMrPh0FwdqZYRPW+89hjj2HJkiWYMGECv/7hhx/w6KOPYufOnZXzkFD9+eef8fXXX6Nly5bYvXs3H0c/Pz8MGDCAxWxoaCh+//13FqH79+/H1KlTWZSOHTu2cjk7duzg9+jvlStXMG7cOHTp0gVPPPGE9g6CoFUou56EK01EaVk5knKKkJRdiNzCUuQXlyK3qIz/5hWVQQEFrGCFmMgzWPPNx7j/6VfQpmNXToiimFOeHG3h4+LAQtXWRp5VjR1D2FFBEASLEasXL15kIfXNN9+gRYsWOHv2LAujvLw89vDpAhKqrq4wCLm5gIuLet+hm86sWbMQFRXFr/ft28ehAUqxWlRUhA8++ADbtm1Dnz59+L1mzZph7969fFxJrNrZ2eHtt9+uXCZ5WA8cOIDffvutmlj18vLCV199BRsbG7Rp0wYjR47E9u3bRayaECQuQzydeKqP59Z8gcgTB5FzdgcefmK03rZPMA87KgiCYDFidfjw4TwpIZEVGRmJRYsWiZH9F/KOkmj88ccfoVAo+P++vr6Vx4w8oPn5+Rg6dGi1Y1tcXFwtVGDBggXslY2OjkZBQQF/Tl7TqrRv356FqhLysp45c0b7P7xgEOiBJzU1lZOfVq5cye/RtdazZ0+0bduWz6smTZrIr2NiiB0VBEHQc4JVVlYWvL29dToUTx5OQ0Dr1gQKBZg2bVql6KxK7r87s2HDBoSEhFT7zMGhor4leWJffPFFfPLJJ+x9dXNzw9y5c3Ho0KFq85MHtiokashjI5gHERERlf9XZutTTPLEiRMr36cHIsH00bUdFQRBsFixSl7C+fPn1+tVpWFvmpRkZ2ertQ66R6s7FG8MnhPyhJLAGDZsWLXP2rVrx6KUPKY05F8bFDrQt29fPPPMM5XvXb16VefbLRgXFNdMiXSlpaU3iVLyqL/11lvsfRXvqmmjDzsqCIJgbKidYfHqq6+ysKpvojirqsTFxbEoe+CBB+qNkaRkIg8Pj8qJsuXNHRISFy5cwPnz56sN0xPkJSWv6YwZM/DTTz+xCD1+/DjfrOg1QUlXR48exebNm3Hp0iXMnj0bR44cMdDeCIaCkvRIqNYGVYyg86Kq91UwLGJHBUEQdOhZfeGFFxosWE/xqUri4+MxaNAg9v59++239X6Pko1mzpxZzSNgCYLV3b0i27s2KBOYYltJyF+7dg2enp5c9uq1117jz5988kmcOHGCs/vpQWH8+PHsZd24caMe90AwBuhcIVFaG7a2thwbLRgHYkcFQRBUx0qhw0A28qiSUO3evTsPU9b0HDYEiVXysFKMVk1BRwX0r1+/ztnvjo6OWt5yQTC9cy02NpYT69LS0m767NixY/yQI6hnZ4wBXdpRQRAEbaBrO2OtSwM7cOBALnJP8VUpKSlcJ5AmQRC0D9XbXb9+Pf/f2rri0pbWqKaN2FFBEAQdJlht3bqVkwFooptoVSQrWRB0A11rgYGBHD5Dnc0WL16MmJgY+Pv7yyE3QcSOCoIg6DgMoLFIGIBgDJhKGIASygSn7kbkVaXLm6pNKEudCZY3TG7u+ycIgvnbGb3WWRUEQfdUFaYkWEWoCoIgCKaMNAcXBEEQBEEQjBYRq4IgCIIgCILRImJVEARBEARBMFpErAqCIAiCIAhGi4hVQRAEQRAEwWgRsWrGUNmiqVOnwtvbm7PCT548yY0ann/++Xq/Rz3kP//8c71tpyAIgiAIgkWVrvps6yW9rm/G0FZqf4c6eb3//vvYsGEDd6mhou3UKpOE5O23366V7dq0aRP3g9+5cyeaNWsGX19frFmzBnZ2dlpZviAIgiAIgq4xS7Fq7Ny4cQP9+vWDp6cn5s6di44dO6KkpASbN2/Gs88+i4sXL2plPVevXkVQUBD69u1b+R55WQVBEARBEEwFCQMwAM888wwPyx8+fBhjxoxBq1at0L59e8ycORMHDx7keaKjo3HPPffA1dWVu0GMHTsWSUlJlct466232BO7bNkyHranzhEPPvggcnJy+PPJkydj+vTpvBxaF81D1AwDSE5OxqhRo+Dk5MQdmn755ZebtjczMxOPP/44/Pz8eFsGDx6MU6dOqbwtRHl5OebMmYMWLVpwkfrw8HD2LCuhlqC0jyTgSVDTvpOoFwRBEATBshGxqmfS09N5eJ48qC4uLjd9TmKNhB2JNZp3165d3B/82rVrGDdu3E2e0z/++APr16/nieb96KOP+LMvvvgC77zzDveKT0hIwJEjR2rdHhK1JBR37NiBVatWYeHChSxgq/LAAw/wexs3bsSxY8fQrVs3DlWg7VNlW4hZs2bx69mzZ+P8+fP49ddfERAQwJ+RV3nYsGFwc3PDnj17sG/fPhbpw4cP51ahgiAIgiBYLhIGoGeuXLnCiU9t2rSpc57t27fjzJkz3I8+LCyM31u6dCl7X0l09uzZk98jUUsxqSTyiIkTJ/J3yWNJ3k1638bGBoGBgbWu59KlSyxAycOrXObixYvRtm3bynn27t3Ln5NYVbbtnDdvHgtTEreUwNXQtpCHlcTzV199hUmTJvHnzZs3R//+/fn/K1eu5O9///337AUmlixZwsKd4m3vuOOORh93QRAEQRBMExGreoaEakNcuHCBRapSqBLt2rVj8UafKYUlDbkrxSFB8ak1vaINrcfW1hbdu3evfI9ENK1HCQ335+bmwsfHp9p3CwoK2JuqpL5tofUUFRXVmThG6yARX/X7RGFhYbV1CIIgCIJgeYhY1TMtW7Zk76E2kqhqZvXTcslDqU1IqJLwJA9nTaqK2vq2heJhG1oHCeba4mUpTlYQBEEQBMtFYlb1DCUPUXzmggULkJeXV2syEw3DUxwpTUoozpM+Iw+rtiAvamlpKcehKomMjOT1KKH4VCqzRR5YSo6qOlEpLFUFOglWCguoDVrH5cuXuXxXzXVQOIMgCIIgCJaLiFUDQEK1rKwMvXr1wurVq1mo0VD5l19+iT59+mDIkCFczmrChAk4fvw4x4w+8sgjGDBgAHr06KG17WjdujUnMT355JM4dOgQi1bK+q/qCaVtoW0aPXo0tmzZwhn6+/fvx+uvv46jR4+qtB5HR0e88sorePnllzn2lob2qeoBxccStJ8kfCmpjBKsKFaXPLnPPfccYmNjtba/giAIgiCYHiJWDQAV6CcROmjQILzwwgvo0KEDhg4dyp7HRYsW8RD6unXr4OXlhdtuu40FI32HEpG0DSUyBQcHsxC+7777OGGKPJxKaFv+/vtv3o5HH32Uy2xRWaqoqKjKbH5VoCoAtK9vvPEGe46psoEyptXZ2Rm7d+/mcla0DfT5lClTOGaVSmUJgiAIgmC5WClUyfgxENnZ2TwMnJWVdZNoISFDHjiqDUqeO0HQFXKumTf12RlzwNz3TxAE87cz4lkVBEEQBEEQjBYRq4IgCIIgCILRImJVEARBEARBMFpErAqCIAiCIAhGi4hVQRAEQRAEwWgxebGq7Y5NgiDnmCAIgiAYDybbbtXe3h7W1taIj4/nlpz0mmqCCoK2oKpuxcXFSElJ4XONzjFBEARBEPSLyYpVEg9UYzUhIYEFqyDoCmpaQA0L6JwTBEEQBEG/mKxYJcjTRSKC+ttT+1JB0DY2NjawtbUVr70gCIIgGAiTFqsEDf3b2dnxJAiCIAiCIJgXOh3XvPvuu9nzSe1Qg4KCMHHiRBmyFwRBEDsqCIJgHGJ10KBB+O233xAZGYnVq1fj6tWruP/++3W5SkEQBLNC7KggCJaOlYJSnvXEn3/+idGjR6OoqEilYfvs7Gx4eHggKysL7u7uetlGQRAsC1OzM2JHBUGwNDuqt5jV9PR0/PLLL+jbt2+dQpVELE1KaKeVB0EQBEEXKO2LHp/bNUbsqCAIFmlHFTrm5ZdfVjg7O9PWK2655RZFampqnfO++eabPJ9McgzkHJBzQN/nQExMjMJYETsq14PYRDkHYMF2VO0wgFdffRUff/xxvfNcuHABbdq04f+npqayNyAqKgpvv/02u4nXr19faymgmp5V6k5F3/Xx8VG5dBCp+7CwMMTExJjEkJ6l7Iu57Y/si/n8LmQCc3JyEBwcrLdaumJH9Yc5Xavmtj+yL8ZJthHaUbXFKnXzSUtLq3eeZs2a1drtJzY2lg/A/v370adPH+gCU4s/s5R9Mbf9kX0xTkzldxE7qj9M5ZywxP2RfTFOso3wHFM7ZpVam9KkCeQpJap6TwVBECwNsaOCIAhGkGB16NAhHDlyBP3794eXlxeXrZo9ezaaN2+uM6+qIAiCOSF2VBAEQYd1Vqmf+po1a3D77bejdevWmDJlCjp16oRdu3bBwcFBZ8eelv3mm2/qdB36wpz2xdz2R/bFODGn34UQO9p4zO2cMKf9kX0xThyM8BzTa51VQRAEQRAEQVAH/aS+CoIgCIIgCIIGiFgVBEEQBEEQjBYRq4IgCIIgCILRImJVEARBEARBMFpMUqwuWLAAERERcHR0RO/evXH48OF65//999+5oxbN37FjR/z9998wxX357rvvcOutt3IpMJqGDBnS4L4b8++iZMWKFdyhbPTo0TAm1N2fzMxMPPvsswgKCuIsylatWhnNuabuvnz++edcxcPJyYkbecyYMQOFhYUwNLt378aoUaO4SwqdM3/88UeD39m5cye6devGv0mLFi3w448/6mVbjR2xo8ZpR83NloodFTuqFRQmxooVKxT29vaKH374QXHu3DnFE088ofD09FQkJSXVOv++ffsUNjY2ijlz5ijOnz+v+L//+z+FnZ2d4syZMwpT25eHHnpIsWDBAsWJEycUFy5cUEyePFnh4eGhiI2NVZjavii5fv26IiQkRHHrrbcq7rnnHoWxoO7+FBUVKXr06KG48847FXv37uX92rlzp+LkyZMKU9uXX375ReHg4MB/aT82b96sCAoKUsyYMUNhaP7++2/F66+/rlizZg33oV67dm2981+7dk3h7OysmDlzJl//8+fPZ3uwadMmhSUjdtQ47ai52VKxo2JHtYXJidVevXopnn322crXZWVliuDgYMWHH35Y6/xjx45VjBw5stp7vXv3Vjz55JMKU9uXmpSWlirc3NwUP/30k8IU94W2v2/fvorvv/9eMWnSJKMxsJrsz6JFixTNmjVTFBcXK4wNdfeF5h08eHC190js9evXT2FMqCJWX375ZUX79u2rvTdu3DjFsGHDFJaM2FHjtKPmZkvFjood1RYmFQZQXFyMY8eO8bCNEmtra3594MCBWr9D71ednxg2bFid8xvzvtQkPz8fJSUl8Pb2hinuyzvvvAN/f39uGGFMaLI/f/75J3dmozCAgIAAdOjQAR988AHKyspgavvSt29f/o5y6PHatWscznDnnXfC1DDW69+QiB01TjtqbrZU7KjYUZNot6oLUlNT+eZPYqAq9PrixYu1ficxMbHW+el9U9uXmrzyyiscu1fzZmwK+7J3714sXrwYJ0+ehLGhyf6QoPvnn38wYcIEFnZXrlzBM888wzdB6gRiSvvy0EMP8feoVTI5MEtLS/HUU0/htddeg6lR1/WfnZ2NgoICjsm1NMSOGqcdNTdbKnZU7Kg2MSnPqvAfH330EQfTr127loPwTYmcnBxMnDiRE8Z8fX1hDpSXl7Nn49tvv0X37t0xbtw4vP766/j6669halBCEnmFFy5ciOPHj3Pb5A0bNuDdd9819KYJglYxZTtqjrZU7KhgFp5VuhhtbGyQlJRU7X16HRgYWOt36H115jfmfVEyb948NrLbtm1Dp06dYGjU3ZerV6/ixo0bnNVd1UgRtra2iIyMRPPmzWFKvw1VALCzs+PvKWnbti179mg4zN7eHqayL7Nnz+Yb4OOPP86vqYJGXl4epk6dygKchiVNhbquf3d3d4v0qhJiR43TjpqbLRU7KnZUm5jOXQfgGz55rbZv317twqTXFC9YG/R+1fmJrVu31jm/Me8LMWfOHPZwbdq0CT169IAxoO6+UBmxM2fO8LCVcrr77rsxaNAg/j+VSjK136Zfv3489K+8URCXLl1iEWsooarpvlAMX01BqhThFXlNpoOxXv+GROyocdpRc7OlYkfFjmoVhYlBpTCorM6PP/7IpWimTp3KZT0SExP584kTJypeffXVaqWrbG1tFfPmzeMyJW+++aZRla5SZ18++ugjLmmyatUqRUJCQuWUk5OjMLV9qYkxZbBqsj/R0dGcUTxt2jRFZGSkYv369Qp/f3/Fe++9pzC1faFrhPZl+fLlXPppy5YtiubNm3NlDUND5zqVHKKJzNenn37K/4+KiuLPaT9of2qWrnrppZf4+qfSb1K6SuyosdpRc7OlYkfFjmoLkxOrBNVKDA8PZ4NDpTEOHjxY+dmAAQP4Yq3Kb7/9pmjVqhXPT2VsNmzYoDDFfWnSpAnfoGtOJC5M8XcxVgOr6f7s37+fy6LRjYbKWL3//vtcUsbU9qWkpETx1ltvsUB1dHRUhIWFKZ555hlFRkaGwtDs2LGj1mtAuf30l/an5ne6dOnC+06/y5IlSwy09caF2FHjtKPmZkvFjood1QZW9I92fbWCIAiCIAiCYIExq4IgCIIgCIJlIWJVEARBEARBMFpErAqCIAiCIAhGi4hVQRAEQRAEwWgRsSoIgiAIgiAYLSJWBUEQBEEQBKNFxKogCIIgCIJgtIhYFQRBEARBEIwWEauCIAiCIAiC0SJiVRAEQRAEQTBaRKwKgiAIgiAIRouIVUEQBEEQBAHGyv8DchgNfCbYtKYAAAAASUVORK5CYII=\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Initialize plots\n", "f, (y1_ax, y2_ax) = plt.subplots(1, 2, figsize=(8, 3))\n", "\n", "# Test points every 0.02 in [0,1]\n", "test_x = torch.linspace(0, 1, 51)\n", "test_i_task1 = torch.full((test_x.shape[0],1), dtype=torch.long, fill_value=0)\n", "test_i_task2 = torch.full((test_x.shape[0],1), dtype=torch.long, fill_value=1)\n", "\n", "# Make predictions - one task at a time\n", "# We control the task we cae about using the indices\n", "\n", "# The qpytorch.settings.fast_pred_var flag activates LOVE (for fast variances)\n", "# See https://arxiv.org/abs/1803.06058\n", "with torch.no_grad(), qpytorch.settings.fast_pred_var():\n", " observed_pred_y1 = likelihood(model(test_x, test_i_task1), [test_i_task1])\n", " observed_pred_y2 = likelihood(model(test_x, test_i_task2), [test_i_task2])\n", "\n", "\n", "# Define plotting function\n", "def ax_plot(ax, train_y, train_x, rand_var, title, **kwargs):\n", " # Get lower and upper confidence bounds\n", " # lower, upper = rand_var.confidence_region(**kwargs)\n", " m, s = rand_var.mean, rand_var.stddev\n", " r = rand_var.rescalor\n", " lower = m - r * s\n", " upper = m + r * s\n", " # Plot training data as black stars\n", " ax.plot(train_x.detach().numpy(), train_y.detach().numpy(), 'k*')\n", " # Predictive mean as blue line\n", " ax.plot(test_x.detach().numpy(), rand_var.mean.detach().numpy(), 'b')\n", " # Shade in confidence \n", " ax.fill_between(test_x.detach().numpy(), lower.detach().numpy(), upper.detach().numpy(), alpha=0.5)\n", " ax.set_ylim([-3, 3])\n", " ax.legend(['Observed Data', 'Mean', 'Confidence'])\n", " ax.set_title(title)\n", "\n", "# Plot both tasks\n", "train_y1 = train_f1 + TASK_NOISES[0] * train_noise1\n", "train_y2 = train_f2 + TASK_NOISES[1] * train_noise2\n", "ax_plot(y1_ax, train_y1, train_x1, observed_pred_y1, fr'Task 1 ($\\sigma_y^2 = {TASK_NOISES[0]}$)')\n", "ax_plot(y2_ax, train_y2, train_x2, observed_pred_y2, fr'Task 2 ($\\sigma_y^2 = {TASK_NOISES[1]}$)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Task-specific Noise\n", "\n", "In this notebook so far, we assumed that each task had the same noise. However, \n", "this may be too strong an assumption. In this section, we use the `HadamardQExponentialLikelihood`\n", "to learn uncorrelated noises for each task." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Iter 25/100 - Loss: 1.334\n", "Iter 50/100 - Loss: 1.001\n", "Iter 75/100 - Loss: 0.951\n", "Iter 100/100 - Loss: 0.951\n" ] } ], "source": [ "model_hd, likelihood_hd = train_model(\n", " ((full_train_x, full_train_i), full_train_y), \n", " qpytorch.likelihoods.HadamardQExponentialLikelihood\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, we compare the models when the tasks have significantly different noises. \n", "Note that the training loss achieved using the `HadamardQExponentialLikelihood` is lower\n", "than using `QExponentialLikelihood`, which learns the same noise across all tasks. \n", "We also see that the predictive distribution for task 2 is much tighter." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "with torch.no_grad(), qpytorch.settings.fast_pred_var():\n", " observed_pred_y1_hd = likelihood_hd(model_hd(test_x, test_i_task1), [test_i_task1])\n", " observed_pred_y2_hd = likelihood_hd(model_hd(test_x, test_i_task2), [test_i_task2])\n", "\n", "train_y1 = train_f1 + TASK_NOISES[0] * train_noise1\n", "train_y2 = train_f2 + TASK_NOISES[1] * train_noise2\n", "\n", "fig = plt.figure(figsize=(8, 7))\n", "subfigs = fig.subfigures(2, 1)\n", "subfigs[0].suptitle('Shared noise')\n", "subfigs[1].suptitle('Task-specific noise')\n", "\n", "for row, (subfig, pred_y1, pred_y2) in enumerate(zip(subfigs, (observed_pred_y1, observed_pred_y1_hd), (observed_pred_y2, observed_pred_y2_hd))):\n", " y1_ax, y2_ax = subfig.subplots(1, 2)\n", " ax_plot(y1_ax, train_y1, train_x1, pred_y1, fr'Task 1 ($\\sigma_y^2 = {TASK_NOISES[0]**2:.2f}$)', rescale=True)\n", " ax_plot(y2_ax, train_y2, train_x2, pred_y2, fr'Task 2 ($\\sigma_y^2 = {TASK_NOISES[1]**2:.2f}$)', rescale=True)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Failure case of task-specific noise\n", "\n", "The downside to this approach is that, since each task has its own noise, learning\n", "the noise parameter requires more data. We demonstrate this failure case below,\n", "where each task has the same noise. In the low-data regime, learning a single\n", "noise parameter gives accurate results, however the task-specific noises are not accurate,\n", "with task 1 overestimating the noise, and task 2 underestimating.\n", "\n", "This can be mitigated by setting the `noise_prior` argument of the likelihood." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Iter 25/100 - Loss: 1.366\n", "Iter 50/100 - Loss: 1.223\n", "Iter 75/100 - Loss: 1.223\n", "Iter 100/100 - Loss: 1.223\n", "likelihood.noise=tensor([0.0184], grad_fn=)\n", "Iter 25/100 - Loss: 1.367\n", "Iter 50/100 - Loss: 1.176\n", "Iter 75/100 - Loss: 1.172\n", "Iter 100/100 - Loss: 1.171\n", "likelihood.noise=tensor([0.0266, 0.0076], grad_fn=)\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(8, 7))\n", "subfigs = fig.subfigures(2, 1)\n", "subfigs[0].suptitle('Shared noise')\n", "subfigs[1].suptitle('Task-specific noise')\n", "\n", "# Reduce the size of the training set to show the effect of independent noises\n", "# in low data settings\n", "N_train = 10\n", "TASK_NOISE = TASK_NOISES[0]\n", "full_train_x = torch.cat([train_x1[:N_train], train_x2[:N_train]])\n", "full_train_i = torch.cat([train_i_task1[:N_train], train_i_task2[:N_train]])\n", "full_train_f = torch.cat([train_f1[:N_train], train_f2[:N_train]])\n", "full_train_noise = torch.cat([TASK_NOISE * train_noise1[:N_train], TASK_NOISE * train_noise2[:N_train]])\n", "full_train_y = full_train_f + full_train_noise\n", "\n", "likelihoods = (qpytorch.likelihoods.QExponentialLikelihood, qpytorch.likelihoods.HadamardQExponentialLikelihood)\n", "for row, (subfig, likelihood_cls) in enumerate(zip(subfigs, likelihoods)):\n", " model, likelihood = train_model(\n", " ((full_train_x, full_train_i), full_train_y), \n", " likelihood_cls\n", " )\n", "\n", " with torch.no_grad(), qpytorch.settings.fast_pred_var():\n", " observed_pred_y1 = likelihood(model(test_x, test_i_task1), [test_i_task1])\n", " observed_pred_y2 = likelihood(model(test_x, test_i_task2), [test_i_task2])\n", "\n", " y1_ax, y2_ax = subfig.subplots(1, 2)\n", " train_x1_sub = train_x1[:N_train]\n", " train_x2_sub = train_x2[:N_train]\n", " train_y1_sub = train_f1[:N_train] + TASK_NOISE * train_noise1[:N_train]\n", " train_y2_sub = train_f2[:N_train] + TASK_NOISE * train_noise2[:N_train]\n", " ax_plot(y1_ax, train_y1_sub, train_x1_sub, observed_pred_y1, fr'Task 1 ($\\sigma_y^2 = {TASK_NOISE**2:.2f}$)')\n", " ax_plot(y2_ax, train_y2_sub, train_x2_sub, observed_pred_y2, fr'Task 2 ($\\sigma_y^2 = {TASK_NOISE**2:.2f}$)')\n", "\n", " # Print the standard deviation, sigma_y which should be \n", " # close to TASK_NOISE\n", " print(f\"{likelihood.noise=}\")" ] } ], "metadata": { "@webio": { "lastCommId": null, "lastKernelId": null }, "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.18" } }, "nbformat": 4, "nbformat_minor": 4 }