{ "cells": [ { "cell_type": "markdown", "id": "d7732643-d6e3-4652-9a4f-61f60d647f72", "metadata": {}, "source": [ "# Estimation of tree height using GEDI dataset - Perceptron 1 - 2023" ] }, { "cell_type": "markdown", "id": "231ce9c1", "metadata": {}, "source": [ "Ref: https://medium.com/biaslyai/pytorch-introduction-to-neural-network-feedforward-neural-network-model-e7231cff47cb\n", "\n", " jupyter-notebook Tree_Height_05Perceptron_intro_2023.ipynb\n", "\n", "python package \n", "\n", " pip3 install pytorch torchvision torchaudio scikit-learn pandas" ] }, { "cell_type": "code", "execution_count": 1, "id": "58b12f60-2a68-458c-a85a-5c3127d7d9fc", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/gpfs/gibbs/project/dijk/ahf38/conda_envs/geo_comp2/lib/python3.8/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", " from .autonotebook import tqdm as notebook_tqdm\n" ] } ], "source": [ "import torch\n", "import torch.nn as nn\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import scipy\n", "import pandas as pd\n", "from sklearn.metrics import r2_score\n", "from sklearn.model_selection import train_test_split" ] }, { "cell_type": "markdown", "id": "8f3f045f-bf11-478c-bf5a-8e0da1c09511", "metadata": {}, "source": [ "Single-layer perceptron takes data as input and its weights are summed up then an activation function is applied before sent to the output layer. Here is an example for a data with 3 features (ie, predictors):" ] }, { "attachments": { "2af60855-7e5b-48c2-a340-04b5ed755e4a.png": { "image/png": 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" } }, "cell_type": "markdown", "id": "8ca92439-d084-41ad-98b7-bdd66e3c19b5", "metadata": {}, "source": [ "![image.png](attachment:2af60855-7e5b-48c2-a340-04b5ed755e4a.png)" ] }, { "cell_type": "markdown", "id": "c2210a8f-ce68-465c-8cb7-1cf735a37ab5", "metadata": {}, "source": [ "The use of an activation function depends on the expected output range or ditribution, which we will discuss in more details later. There are several options for activation function. To learn more about activation functions, checkout this great [blogpost](https://www.analyticsvidhya.com/blog/2020/01/fundamentals-deep-learning-activation-functions-when-to-use-them/). " ] }, { "cell_type": "markdown", "id": "7c76382c-97fe-4301-8e65-424aefe8e1c4", "metadata": {}, "source": [ "**Question 1**: what is the difference between the Perceptron shown above an a simple linear regression? " ] }, { "cell_type": "markdown", "id": "032b4914-c8fb-48ef-944a-41263fe70a12", "metadata": {}, "source": [ "Now let's see how we can implement a Perceptron:" ] }, { "cell_type": "code", "execution_count": 2, "id": "b88a28fb-e0a2-486b-9e36-ab446370f810", "metadata": { "tags": [] }, "outputs": [], "source": [ "class Perceptron(torch.nn.Module):\n", " def __init__(self,input_size, output_size, use_activation_fn=False):\n", " super(Perceptron, self).__init__()\n", " self.fc = nn.Linear(input_size,output_size) # Initializes weights with uniform distribution centered in zero\n", " self.activation_fn = nn.ReLU() # instead of Heaviside step fn\n", " self.use_activation_fn = use_activation_fn # If we want to use an activation function\n", " def forward(self, x):\n", " output = self.fc(x)\n", " if self.use_activation_fn:\n", " output = self.activation_fn(output) # To add the non-linearity. Try training you Perceptron with and without the non-linearity\n", " return output" ] }, { "cell_type": "markdown", "id": "a62a3727-f3e5-493c-a3b4-0a0a2da80f4f", "metadata": {}, "source": [ "The building blocks of the Perceptron code:\n", "- nn.Linear: Applies a linear transformation to the incoming data: y = xA^T + b\n", "- nn.ReLU: Applies the rectified linear unit function element-wise" ] }, { "cell_type": "markdown", "id": "127b95e2-d4b3-42dc-825b-eb60fdcba81c", "metadata": {}, "source": [ "Before we try to solve a real-world problem let's see how it works on a simpler data. For data, I will create a simple 2D regression problem." ] }, { "cell_type": "code", "execution_count": 3, "id": "62f4e1f2-929e-4829-812a-c1deae2e3562", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Test data')" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# CREATE RANDOM DATA POINTS\n", "# from sklearn.datasets import make_blobs\n", "from sklearn.datasets import make_regression\n", "\n", "x_train, y_train = make_regression(n_samples=100, n_features=2, random_state=0) \n", "x_train = torch.FloatTensor(x_train)\n", "y_train = torch.FloatTensor(y_train)\n", "\n", "x_test, y_test = make_regression(n_samples=50, n_features=2, random_state=1) \n", "x_test = torch.FloatTensor(x_test)\n", "y_test = torch.FloatTensor(y_test)\n", "\n", "\n", "#Visualize the data\n", "fig,ax=plt.subplots(1,2,figsize=(10,5), sharey=True)\n", "ax[0].scatter(x_train[:,0],x_train[:,1],c=y_train)\n", "ax[0].set_xlabel('X')\n", "ax[0].set_ylabel('Y')\n", "ax[0].set_title('Training data')\n", "\n", "ax[1].scatter(x_test[:,0],x_test[:,1],c=y_test)\n", "ax[1].set_xlabel('X')\n", "ax[1].set_title('Test data')" ] }, { "cell_type": "markdown", "id": "395243cd-b329-45e5-b839-50248d2df9e1", "metadata": {}, "source": [ "Let's have a quick look at the distributions:" ] }, { "cell_type": "code", "execution_count": 4, "id": "448d903d-d091-4bc8-ba38-729ec1e234a8", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data_train = np.concatenate([x_train, y_train[:,None]],axis=1)\n", "n_plots_x = int(np.ceil(np.sqrt(data_train.shape[1])))\n", "n_plots_y = int(np.floor(np.sqrt(data_train.shape[1])))\n", "fig, ax = plt.subplots(1, 3, figsize=(15, 5), dpi=100, facecolor='w', edgecolor='k')\n", "ax=ax.ravel()\n", "for idx in range(data_train.shape[1]):\n", " ax[idx].hist(data_train[:,idx].flatten())\n", "fig.tight_layout()" ] }, { "cell_type": "markdown", "id": "033b5902-c7df-4dfc-9c6a-4e175a4a4c6a", "metadata": {}, "source": [ "Now let's initialize our Perceptron model, define the type of optimizer and loss we want to use:" ] }, { "cell_type": "code", "execution_count": 5, "id": "dcd27df5-fe85-40e7-b6b5-29a06e290c8a", "metadata": { "tags": [] }, "outputs": [], "source": [ "model = Perceptron(input_size=2, output_size=1)\n", "criterion = torch.nn.MSELoss()\n", "optimizer = torch.optim.SGD(model.parameters(), lr = 0.01) #Check slides for a review on SGD" ] }, { "cell_type": "markdown", "id": "fefbca67-3623-4a34-8dd0-7c6f7e333adb", "metadata": {}, "source": [ "Just for curiosity, let's se how bad a naive model would perform in this task" ] }, { "cell_type": "code", "execution_count": 6, "id": "3ae3a9f1-8bc2-4a25-9a51-66685c565a82", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "x_test.shape: torch.Size([50, 2])\n", "y_pred.shape: torch.Size([50, 1])\n", "y_test.shape: torch.Size([50])\n", "Test loss before training 4668.76123046875\n" ] }, { "data": { "text/plain": [ "Text(0.5, 1.0, 'slope: -132.293, r_value: -0.805')" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.eval()\n", "y_pred = model(x_test)\n", "print('x_test.shape: ',x_test.shape)\n", "print('y_pred.shape: ',y_pred.shape)\n", "print('y_test.shape: ',y_test.shape)\n", "before_train = criterion(y_pred.squeeze(), y_test)\n", "print('Test loss before training' , before_train.item())\n", "\n", "y_pred = y_pred.detach().numpy().squeeze()\n", "slope, intercept, r_value, p_value, std_err = scipy.stats.linregress(y_pred, y_test)\n", "\n", "# # Fit line\n", "# x = np.arange(-150,150)\n", "\n", "fig,ax=plt.subplots()\n", "ax.scatter(y_pred, y_test)\n", "# ax.plot(x, intercept + slope*x, 'r', label='fitted line')\n", "ax.set_xlabel('Prediction')\n", "ax.set_ylabel('True')\n", "ax.set_title('slope: {:.3f}, r_value: {:.3f}'.format(slope, r_value))" ] }, { "cell_type": "markdown", "id": "854869aa-777b-4e55-804c-20abcad6d815", "metadata": {}, "source": [ "**Question 1.1**: Can you make sense of this model's output range? " ] }, { "cell_type": "markdown", "id": "0edd1a7e-8911-43c7-97d1-f9862d776bae", "metadata": {}, "source": [ "Now let's train our Perceptron to model this data" ] }, { "cell_type": "code", "execution_count": 7, "id": "21cdb3da-ca7d-42c8-bdbe-c542ac69ff70", "metadata": { "tags": [] }, "outputs": [], "source": [ "model.train()\n", "epoch = 1000\n", "all_loss=[]\n", "for epoch in range(epoch):\n", " optimizer.zero_grad()\n", " # Forward pass\n", " y_pred = model(x_train)\n", " # Compute Loss\n", " loss = criterion(y_pred.squeeze(), y_train)\n", " \n", " # Backward pass\n", " loss.backward()\n", " optimizer.step()\n", " \n", " all_loss.append(loss.item())" ] }, { "cell_type": "code", "execution_count": 8, "id": "e9d48f19-513c-4628-bb70-1e727f57d28e", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig,ax=plt.subplots()\n", "ax.plot(all_loss)" ] }, { "cell_type": "code", "execution_count": 9, "id": "576ba478-b5c6-42cc-a811-88a4b3ef4915", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Test loss after Training 298.5340576171875\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.eval()\n", "with torch.no_grad():\n", " y_pred = model(x_test)\n", " after_train = criterion(y_pred.squeeze(), y_test) \n", " print('Test loss after Training' , after_train.item())\n", "\n", " y_pred = y_pred.detach().numpy().squeeze()\n", " slope, intercept, r_value, p_value, std_err = scipy.stats.linregress(y_pred, y_test)\n", "\n", " # Fit line\n", " x = np.arange(-150,150)\n", "\n", " fig,ax=plt.subplots()\n", " ax.scatter(y_pred, y_test)\n", " ax.plot(x, intercept + slope*x, 'r', label='fitted line')\n", " ax.set_xlabel('Prediction')\n", " ax.set_ylabel('True')\n", " ax.set_title('slope: {:.3f}, r_value: {:.3f}'.format(slope, r_value))" ] }, { "cell_type": "markdown", "id": "77ae39c9-c5ca-443f-bd16-a8e57bfa34eb", "metadata": {}, "source": [ "This results is not bad, but note that we didn't use any activation function. Now let's see what happens when we add an activation" ] }, { "cell_type": "code", "execution_count": 10, "id": "406723ed-892d-446b-afb9-25c09aaf50fe", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Test loss after Training 1798.18310546875\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Add activation and retrain the model \n", "del model, optimizer\n", "model = Perceptron(input_size=2, output_size=1, use_activation_fn=True)\n", "criterion = torch.nn.MSELoss()\n", "optimizer = torch.optim.SGD(model.parameters(), lr = 0.01)\n", "\n", "model.train()\n", "epoch = 1000\n", "all_loss=[]\n", "for epoch in range(epoch):\n", " optimizer.zero_grad()\n", " # Forward pass\n", " y_pred = model(x_train)\n", " # Compute Loss\n", " loss = criterion(y_pred.squeeze(), y_train)\n", " \n", " # Backward pass\n", " loss.backward()\n", " optimizer.step()\n", " \n", " all_loss.append(loss.item())\n", "\n", "model.eval()\n", "with torch.no_grad():\n", " y_pred = model(x_test)\n", " after_train = criterion(y_pred.squeeze(), y_test) \n", " print('Test loss after Training' , after_train.item())\n", "\n", " y_pred = y_pred.detach().numpy().squeeze()\n", " slope, intercept, r_value, p_value, std_err = scipy.stats.linregress(y_pred, y_test)\n", "\n", " # Fit line\n", " x = np.arange(-150,150)\n", "\n", " fig,ax=plt.subplots()\n", " ax.scatter(y_pred, y_test)\n", " ax.plot(x, intercept + slope*x, 'r', label='fitted line')\n", " ax.set_xlabel('Prediction')\n", " ax.set_ylabel('True')\n", " ax.set_title('slope: {:.3f}, r_value: {:.3f}'.format(slope, r_value))" ] }, { "cell_type": "markdown", "id": "31566549-7a6f-4c39-ac04-c2f797cbb503", "metadata": {}, "source": [ "**Question 2**: what is happenng to this model? Why do we have so many predicted outputs with 'zeros'?" ] }, { "cell_type": "markdown", "id": "8a5559d1-41bc-4a2c-8013-a842364fac68", "metadata": {}, "source": [ "Let's see what happens when the data and target are normalized" ] }, { "cell_type": "code", "execution_count": 11, "id": "f294e85c-d49a-4d4a-a2c7-b3ee8cea230a", "metadata": { "tags": [] }, "outputs": [], "source": [ "#Now normalize the data\n", "from sklearn.preprocessing import MinMaxScaler\n", "scaler = MinMaxScaler()\n", "\n", "data_train = np.concatenate([x_train, y_train[:,None]],axis=1)\n", "data_train = scaler.fit_transform(data_train)\n", "data_test = np.concatenate([x_test, y_test[:,None]],axis=1)\n", "data_test = scaler.transform(data_test)" ] }, { "cell_type": "code", "execution_count": 12, "id": "bcd65c51-535b-4ddd-ad15-58a7d31e802b", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n_plots_x = int(np.ceil(np.sqrt(data_train.shape[1])))\n", "n_plots_y = int(np.floor(np.sqrt(data_train.shape[1])))\n", "fig, ax = plt.subplots(1, 3, figsize=(15, 5), dpi=100, facecolor='w', edgecolor='k')\n", "ax=ax.ravel()\n", "for idx in range(data_train.shape[1]):\n", " ax[idx].hist(data_train[:,idx].flatten())\n", "fig.tight_layout()" ] }, { "cell_type": "code", "execution_count": 13, "id": "4cd0f06c-76a8-4f27-a23a-1bc7b85df2bf", "metadata": { "tags": [] }, "outputs": [], "source": [ "x_train,y_train = data_train[:,:2],data_train[:,2]\n", "x_test,y_test = data_test[:,:2],data_test[:,2]\n", "\n", "x_train = torch.FloatTensor(x_train)\n", "y_train = torch.FloatTensor(y_train)\n", "\n", "x_test = torch.FloatTensor(x_test)\n", "y_test = torch.FloatTensor(y_test)" ] }, { "cell_type": "code", "execution_count": 14, "id": "63a2405b-a272-4751-a6d0-a4e365cbb544", "metadata": { "tags": [] }, "outputs": [], "source": [ "del model, optimizer\n", "model = Perceptron(input_size=2, output_size=1, use_activation_fn=True)\n", "criterion = torch.nn.MSELoss()\n", "optimizer = torch.optim.SGD(model.parameters(), lr = 0.01)" ] }, { "cell_type": "code", "execution_count": 15, "id": "8da01d5c-e312-4b6a-8909-98a1f2957e35", "metadata": { "tags": [] }, "outputs": [], "source": [ "model.train()\n", "epoch = 1000\n", "all_loss=[]\n", "for epoch in range(epoch):\n", " optimizer.zero_grad()\n", " # Forward pass\n", " y_pred = model(x_train)\n", " # Compute Loss\n", " loss = criterion(y_pred.squeeze(), y_train)\n", " \n", " # Backward pass\n", " loss.backward()\n", " optimizer.step()\n", " \n", " all_loss.append(loss.item())" ] }, { "cell_type": "code", "execution_count": 16, "id": "7ddb9006-fdd8-4732-bc42-851991445d47", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig,ax=plt.subplots()\n", "ax.plot(all_loss)" ] }, { "cell_type": "code", "execution_count": 17, "id": "c74713da-ea8c-4069-aba0-009d7d812bb4", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Test loss after Training 0.0005619959556497633\n", "0.18696567 0.80532324\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.eval()\n", "with torch.no_grad():\n", " y_pred = model(x_test)\n", " after_train = criterion(y_pred.squeeze(), y_test) \n", " print('Test loss after Training' , after_train.item())\n", "\n", " y_pred = y_pred.detach().numpy().squeeze()\n", " slope, intercept, r_value, p_value, std_err = scipy.stats.linregress(y_pred, y_test)\n", "\n", " # Fit line\n", " print(y_test.numpy().min(),y_test.numpy().max())\n", " x = np.linspace(y_test.numpy().min(),y_test.numpy().max(),len(y_test))\n", "\n", " fig,ax=plt.subplots()\n", " ax.scatter(y_pred, y_test)\n", " ax.plot(x, intercept + slope*x, 'r', label='fitted line')\n", " ax.set_xlabel('Prediction')\n", " ax.set_ylabel('True')\n", " ax.set_title('slope: {:.3f}, r_value: {:.3f}'.format(slope, r_value))" ] }, { "cell_type": "markdown", "id": "8ab32742-1b39-40ec-b7f2-474f5459665a", "metadata": {}, "source": [ "Now that we know how to implement a Perceptron and how it works on a toy data, let's see a more interesting dataset. For that, we will use the tree height dataset. For simplicity, let's start with just few variables: latitude (x) and longitude (y)." ] }, { "cell_type": "code", "execution_count": 18, "id": "d4baf219-69cf-43cb-931c-cfdfef792bdb", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(66522, 3)\n", " x y h\n", "0 6.894317 49.482459 2.73\n", "1 7.023274 49.510552 10.75\n", "2 7.394650 49.590488 21.20\n", "3 7.396895 49.590968 20.00\n", "4 7.397643 49.591128 24.23\n" ] } ], "source": [ "### Try the the tree height with Perceptron \n", "# data = pd.read_csv('./tree_height/txt/eu_x_y_height_predictors.txt', sep=\" \")\n", "data = pd.read_csv('./tree_height/txt/eu_x_y_height.txt', sep=\" \")\n", "print(data.shape)\n", "print(data.head())" ] }, { "cell_type": "code", "execution_count": 19, "id": "28b39994-e920-4aad-a50f-61adabce41f7", "metadata": { "tags": [] }, "outputs": [], "source": [ "#Normalize the data\n", "from sklearn.preprocessing import MinMaxScaler\n", "scaler = MinMaxScaler()\n", "data = scaler.fit_transform(data)\n", "\n", "# data[:,2] = 2*data[:,2]-1" ] }, { "cell_type": "code", "execution_count": 20, "id": "a2529ed9-00a6-4391-a072-00f68280a634", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(array([5.287e+03, 2.447e+03, 1.626e+03, 1.406e+03, 1.308e+03, 1.327e+03,\n", " 1.483e+03, 1.721e+03, 1.957e+03, 2.022e+03, 2.131e+03, 2.314e+03,\n", " 2.726e+03, 3.055e+03, 3.551e+03, 3.900e+03, 3.956e+03, 4.169e+03,\n", " 4.049e+03, 3.536e+03, 3.120e+03, 2.561e+03, 1.923e+03, 1.473e+03,\n", " 1.069e+03, 7.340e+02, 5.460e+02, 3.720e+02, 2.410e+02, 1.860e+02,\n", " 1.010e+02, 7.200e+01, 7.300e+01, 4.300e+01, 1.500e+01, 6.000e+00,\n", " 6.000e+00, 6.000e+00, 2.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n", " 1.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n", " 0.000e+00, 1.000e+00]),\n", " array([0. , 0.02, 0.04, 0.06, 0.08, 0.1 , 0.12, 0.14, 0.16, 0.18, 0.2 ,\n", " 0.22, 0.24, 0.26, 0.28, 0.3 , 0.32, 0.34, 0.36, 0.38, 0.4 , 0.42,\n", " 0.44, 0.46, 0.48, 0.5 , 0.52, 0.54, 0.56, 0.58, 0.6 , 0.62, 0.64,\n", " 0.66, 0.68, 0.7 , 0.72, 0.74, 0.76, 0.78, 0.8 , 0.82, 0.84, 0.86,\n", " 0.88, 0.9 , 0.92, 0.94, 0.96, 0.98, 1. ]),\n", " )" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Inspect the ranges \n", "fig,ax = plt.subplots(1,3,figsize=(15,5))\n", "ax[0].hist(data[:,0],50)\n", "ax[1].hist(data[:,1],50)\n", "ax[2].hist(data[:,2],50)" ] }, { "cell_type": "code", "execution_count": 21, "id": "0c21aafd-7367-4172-9f9a-6cf04eef0f20", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "X_train.shape: torch.Size([46565, 2]), X_test.shape: torch.Size([19957, 2]), y_train.shape: torch.Size([46565]), y_test.shape: torch.Size([19957])\n" ] } ], "source": [ "#Split the data\n", "X_train, X_test, y_train, y_test = train_test_split(data[:,:2], data[:,2], test_size=0.30, random_state=0)\n", "X_train = torch.FloatTensor(X_train)\n", "y_train = torch.FloatTensor(y_train)\n", "X_test = torch.FloatTensor(X_test)\n", "y_test = torch.FloatTensor(y_test)\n", "print('X_train.shape: {}, X_test.shape: {}, y_train.shape: {}, y_test.shape: {}'.format(X_train.shape, X_test.shape, y_train.shape, y_test.shape))" ] }, { "cell_type": "code", "execution_count": 22, "id": "f4608af6-afc4-4201-90df-196f7dec7b7f", "metadata": { "tags": [] }, "outputs": [], "source": [ "# Create percetron\n", "model = Perceptron(input_size=2, output_size=1)\n", "criterion = torch.nn.MSELoss()\n", "optimizer = torch.optim.SGD(model.parameters(), lr = 0.01)" ] }, { "cell_type": "code", "execution_count": 23, "id": "4751f542-6105-459f-8de0-1386860c6dcc", "metadata": { "tags": [] }, "outputs": [], "source": [ "model.train()\n", "epoch = 2000\n", "all_loss=[]\n", "for epoch in range(epoch):\n", " optimizer.zero_grad()\n", " # Forward pass\n", " y_pred = model(X_train)\n", " # Compute Loss\n", " loss = criterion(y_pred.squeeze(), y_train)\n", " \n", " # Backward pass\n", " loss.backward()\n", " optimizer.step()\n", " \n", " all_loss.append(loss.item())" ] }, { "cell_type": "code", "execution_count": 24, "id": "681f2273-6361-4aff-9837-4a84f921cee6", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig,ax=plt.subplots()\n", "ax.plot(all_loss)" ] }, { "cell_type": "code", "execution_count": 25, "id": "43652372-29f9-4e83-bd5f-cde9aff3a5bd", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Test loss after Training 0.021724332123994827\n" ] }, { "data": { "image/png": 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lLVu2ZG3btmV33HGHYTtzCcUXL15k3t7e7M4772R79uxh27ZtY3fccQeLiYkxeX/PPvss8/PzYy+99BLbvXs3279/P/viiy/Y888/b1SbiG9CMWOMFRQUsKioKNarVy+2Y8cOlpyczIYNG8ZatGjBzp49a7Rtp06dWKdOnYweO3v2LAsICGDDhg1jycnJbPv27SwuLo61bt2aFRQUWH1tWwnF77zzDgPAfvjhB5vvgxBbKLghzV51dTWbPn066927NwsMDGS+vr6sW7du7LXXXjMqAGdupktVVRWbN28ei46OZt7e3iwqKoo9//zz7ObNm0bbRUdHs7Fjx7JvvvmG9ezZk/n4+LAOHTqwDz74wKQ9t27dYq+88grr1q0b8/HxYUFBQaxXr15szpw5hpknjP01w+bAgQO83ucPP/zABg0axDQaDQsNDWVPPvkku379utE23AX5qaeeMjx29uxZ9re//Y1FR0czjUbDNBoN6969O3vppZdYUVGRyetUVlayefPmsXbt2jEvLy/Wvn17tmDBAqMginsdSz+NX58xxuLj41lkZKTN9yhEcHPu3DlDO1JTU01+f/PmTTZlyhTWqlUr5ufnx4YMGcIOHTrE7rjjDpvBDWOMJScns759+zJfX1/WsWNHtmrVKpPZUpz169ez22+/nfn7+zNfX1/WqVMn9uSTT7ITJ04Ytjlw4AADwF577TVe7+/ChQts/PjxLDAwkPn5+bG7776bnTx50mS76OhoszO7Tpw4we6++27m5+fHAgMD2fjx402CUXNsBTddu3ZlHTp0sDqjjhC+FIw1KpxBCBFFhw4dEBcXZ7Y7nlhXXl6O0NBQrFixAjNnzpS6OYQQN0A5N4QQWTt48CDatGmDadOmSd0UQoiboOCGECJrY8eORV5entHinPZgjBnVijH3Qx3YhHgWCm4IcYG8vDwakpLIp59+alIrpunPTz/9JHUzCSECkjznJikpCe+99x60Wi169uyJFStWYOjQoRa3/+KLL/Duu+/i/PnzCAoKwujRo/H+++/T1EFCiFlFRUXIzc21uk23bt3QokULF7WIECI2SYObrVu3YtKkSUhKSkJiYiI+/vhjrF27FtnZ2Wjfvr3J9ocPH8Ydd9yB5cuX4/7778fVq1cxffp0dOnSxeGVjQkhhBDiWSQNbm6//Xb079/fqAJojx49MH78eCxdutRk+/fffx+rV69GTk6O4bH//ve/ePfdd42KUhFCCCGk+ZJs+YXa2lqcPHkS8+fPN3p81KhROHr0qNnnDB48GAsXLkRycjLuvfdeFBQU4JtvvsHYsWMtvk5NTY1RuXO9Xo/i4mKEhYU5VaadEEIIIa7DGEN5eTlat25te3FdierrsKtXrzIA7MiRI0aPv/XWW6xr164Wn/f111+zgIAA5uXlxQCwcePGsdraWovbc8Wx6Id+6Id+6Id+6Mf9f65cuWIzxpB84cymvSeMMYs9KtnZ2XjhhRfw6quv4p577oFWq8VLL72E6dOnY926dWafs2DBAsydO9fw79LSUrRv3x5XrlxxaOVgQgghhLheWVkZ2rVrxyv5X7LgJjw8HCqVymSl5IKCAkRERJh9ztKlS5GYmIiXXnoJQMMKxP7+/hg6dCjefPNNREVFmTxHrVabXUE3MDCQghtCCCHEzfBJKZGszo2Pjw/i4+ORmppq9HhqaioGDx5s9jmVlZUm42wqlQoAqAgXIYQQQgBIXMRv7ty5WLt2LdavX4+zZ89izpw5uHz5MqZPnw6gYUjpySefNGx///33Y/v27Vi9ejUuXryII0eO4IUXXsDAgQPRunVrqd4GIYQQQmRE0pybRx99FEVFRXj99deh1WoRFxeH5ORkREdHAwC0Wi0uX75s2H7y5MkoLy/HqlWr8I9//APBwcEYPnw4li1bJtVbIIQQQojMSF6h2NXKysoQFBSE0tJSyrkhhBBC3IQ9129aW4oQQgghHoWCG0IIIYR4FApuCCGEEOJRKLghhBBCiEeh4IYQQgghHkXy5RcIIcRVdHqGY7nFKCivRqsWGgyMCYVKSQvoEuJpKLghhDQLKVlaLNmdDW1pteGxqCANXrs/FqPjTJduIYS4LxqWIoR4vJQsLZ7flGEU2ABAfmk1nt+UgZQsrUQtI4SIgYIbQohH0+kZluzOhrlqpdxjS3ZnQ6dvVvVMCfFoFNwQQjzasdxikx6bxhgAbWk1juUWO7R/nZ4hLacIOzOvIi2niIIkQmSAcm4IIR6toNxyYOPIdo1RHg8h8kQ9N4QQj9aqhUbQ7Tj25PFQ7w4hrkU9N4QQjzYwJhRRQRrkl1abzbtRAIgMapgWbk3jaeTh/mos3mU5j0eBhjyekbGRSM3Op94dQlyMghtCiEdTKRV47f5YPL8pAwrAKCDhKty8dn+s1Xo35oafrOHyeFbtP48Ve8+bBEFc787qJ/pTgEOICGhYihDi8UbHRWH1E/0RGWQ89BQZpLEZYFgafuJjw5E8mqVFiASo54YQ0iyMjovCyNhIuyoUW5tGzkdJVZ3F3zWepZXQKczBVyCEmEPBDSGk2VApFXYFEramkVuiABDk542SSsvBDceRWVqEEOtoWIoQQixwJPDg+oGeHhzDa3t7Z2kRQmyjnhtCCPlT04U1wwPUdu8j8s+ZUCNjI/Hl8csWZ2kBDbOmbM3SIoTYj4IbQgiB+RlRkYFqBPt5o7SyzuI08ohANf79SF8U3qoxyePhZmlZMq5PFFRKBa1WTojAKLghhDR73IyopgHM9bIaw2OWppEvHtcTiZ3Dze53dFwUnh0Wg48P5pr9/Sd/Pr7rFy3VwSFEQJRzQwhp1mwtrKkAEOznjYhA+6eR6/QMu36xvOI4A/DxwVxarZwQgVHPDSGkWeOzsGZJZR2+mNIfSqXCrqEjR2dbNa1yTENUhNiHghtCSLPGd0ZUYUUNHujbRpR9m0N1cAhxHA1LEUKaNbEW1nT0OU1RHRxC7EfBDSGkWeMW1rQ08KOA41O2be2bD6qDQ4j9KLghhDRr3MKaAEyCEL4Lazqzb0ucCaoIae4ouCGENHvOLKzpzL6fGxYDBYQPqghp7hSMsWa1JG1ZWRmCgoJQWlqKwMBAqZtDCJERMYvpWdq3ueKBVOeGEFP2XL8puCGEEB6kCHwIIX+x5/pNU8EJIcSG5NNavLIzC8UVtYbHhOxdsXe1ckKIdZRzQwghVixNzsaMzRlGgQ3QUIOGqggTIk8U3BBCmhWdniEtpwg7M68iLacIOr3lkfnk09csrgsFNBTaW7I72+o+CCGuJ3lwk5SUhJiYGGg0GsTHx+PQoUMWt508eTIUCoXJT8+ePV3YYkKIu0rJ0mLIsv2YsCYdL36ZiQlr0jFk2X6zvS86PcMrO7Ns7pOrIkwIkQ9Jg5utW7di9uzZWLhwIU6dOoWhQ4fi3nvvxeXLl81uv3LlSmi1WsPPlStXEBoair///e8ubjkhxN1wK3/zXaTyWG4xiivqeO37yIVC6r0hREYkDW4++OADTJkyBVOnTkWPHj2wYsUKtGvXDqtXrza7fVBQECIjIw0/J06cwM2bN/H000+7uOWEEHdia+VvwHR4yZ5lD1YduIDb3kpF8ulrzjWUECIIyYKb2tpanDx5EqNGjTJ6fNSoUTh69Civfaxbtw4jRoxAdHS0xW1qampQVlZm9EMIaV74rPzddHjJ3mUPiivqMGPzKSxNzna0mYQQgUgW3BQWFkKn0yEiIsLo8YiICOTn59t8vlarxXfffYepU6da3W7p0qUICgoy/LRr186pdhNC3E9qtu1zCmDcW8OtC2Wvjw/mIvk0zaAiREqSJxQrFMaFqhhjJo+Zs3HjRgQHB2P8+PFWt1uwYAFKS0sNP1euXHGmuYQQN6PTM/wvk99wUePeGm5dKEdK6c3ffhq19XoHnkkIEYJkwU14eDhUKpVJL01BQYFJb05TjDGsX78ekyZNgo+Pj9Vt1Wo1AgMDjX4IIc1HQ2Jwrc3tQv29TRap5NaFsrcHp6y6HoOW7qUaOIRIRLLgxsfHB/Hx8UhNTTV6PDU1FYMHD7b63J9++gkXLlzAlClTxGwiIcQD8E0MfrBvG7NLHoyOi8LhecOxZdogzLizE+/XLa6ooyJ/hEhE0uUX5s6di0mTJmHAgAFISEjAJ598gsuXL2P69OkAGoaUrl69is8++8zoeevWrcPtt9+OuLg4KZpNCHEjfBODR8RGWlzjSaVUoLSqFtszrtr9+kt2Z2NkbCStFUWIC0ka3Dz66KMoKirC66+/Dq1Wi7i4OCQnJxtmP2m1WpOaN6Wlpdi2bRtWrlwpRZMJIW6GSwzOL602OxVcASAySIObFTUYsmy/2dW5AeD5TRlmn29N41lYtHYUIa5Dq4ITQjweV8APgFGAwvWlPDssBp8czDUJXrjfB/l5o6SSX0E/c1Y+1hcP9G3j8PMJIfZdvyWfLUUIIWLjEoMjmyQGRwZp8OHE/tj1i9ZigT8GOBXYAPbXzCGEOEfSYSlCCHGV0XFRGBkbaZJTY6vAnzO4Ia+ms7AIIeKi4IYQ0myolAqT3Je9PAv82Ysb0nrt/lhKJibExSi4IYQ0WylZWqw7kufUPhQAgv28ofZSIr+sxvB45J/JyKPjogDA4kwsQojwKLghhDRL3GKatnDBy83KOihgPiF56UO9zA55ccFLSpYWS3Znm52JxQU/hBDhUHBD3JpOz5CeU4S0i4UAGoYcBnUMoztiYhPfXBuGhuAFgEmA0rR3xtx0b26mVtOE5fzSajy/KQOrn+hPAQ4hAqPghritlCwt5m8/YzSTZdWBCwj288Y7D/WiCwaxim/l4uHdWxqOpeHdI/B5Wh4uFVciOtQPE2+PRuaVEuzMvGp2qInrHbI0E0sBKvJHiBgouCFuKSVLi+l/1i1pqqSyDtM3ZeAjuiMmVvCdnv3LlVLo9Ayp2fkmPTdvJp9F40phTYea0i8WWe0das5F/igHiYiJghvidnR6hsW7frW5Hd0RE2sGxoQi1N8bxRXWa9gUVdTiv/vOY8W+8ya/a1oCVdtoqAkA5m87w6stfHuRPIU75SBREOaeKLghbudYbrHRrBRLmusdMeFHpVTgwb5teM2WWmkmsLGEAZi//QxKK+t4L9fQnIr8uVMOkjsFYcQYVSgmbseeu9zmdkfcHOj0DGk5RdiZeRVpOUXQ6e1bQabx81sH+/J6jr1r1JTwDGwUaLhYxkeHOPWe3IWtHCSgocdVDu+fC8KaDityQRit9i5v1HND3I49d7nN6Y64OXD2Ttrc86XEAIzrE4Vh7+43rpETqMbicT09rnfA1gw1ueQgUSK4+6OeG+J2BsaEIjJQbXO7KCp771GcvZO29Hwp+atV+Phgrskwa35ZDaZ7YO8A355UqXtc7QnCiDxRcEPcjkqpwOJxPW1uR2XvPYezwxnWni+lihqd1d/P335GFkM0QuHbkyp1j2sqzyU5pA7CiGUU3BC3NDouCh890R/Bft4mvwvx86Zp4B7G2TtpMRfHNMfccemIkso6pOcUCbIvORgYE4qoIA0s3XJwOUhS9rjq9Az/y7zGa1upgzBiGeXcELfFrfJMFYpdz9XTY50dznDlHbbaS4m3x8dhxuZTguwv7WIhEruEC7IvqamUCrx2fyye35RhcSkLqXtcj+UWo7ii1uZ2of7eNOwtYxTcELemUiqQ2CXcY07+7kCK6bHODme48g67pl6P8wW3kDSxH2ZtOQXnR5U8K1AfHReF1U/0t7mUhVT4BsIP9m1DN1EyRsENIYQ3qWqUcMMZ+aXVZvNmFGi4OFq6k7b1fKFtOJKHk4tGYtUEBWZsNq2k3bTXwhpPrNPE9brKsTge30B4RGykyC0hzqCcG0IIL1LWKOGGMwDTfgw+wxnWni+Gkqo6HMstxpjeDblhUUHGF8zIIA2SJvazmZsT4ueNQR09L7gBGj6ThE5heKBvGyR0ks9QsjvkBRHbqOeGEMKL1DVKnB3O4J6/eFc28svEz8Hhhjes9VIolQqLa6QBDauRy+Wi31y4Q14QsY2CG0IIL3KoUSLMcIZrplY3Ht7geima4mb9NQ24qMS/tOSeF0Rso+CGEMKLXGqUWAoULOFmdu3Nzue1jpQQ/H1UvIct5Jx/0pzR5+LeKLghhPDibFKvFKRabqGiVofvs7QY07s1r+3tDdiIa9Dn4r4ooZgQwouzSb2uJvVyC6/szPKo6sKEuBMKbojbcHY1aOI8Lhch0szsH7GmgTtCDsstFFfU2bX2kKXjm457QuxHw1LELVgqHLdobCxC/H1oTNyF3CEXwdXLLVhSUF7Nq5qzueM71N8HfdsFIfNKqVHFXEo2JsQ2BWOsWd0GlJWVISgoCKWlpQgMDJS6OR5FrJL8lgrHmUMnfgIAOzOv4sUvM6VuBuaM6Iovj1+2Ws3ZnuMb+GsIUE49ZYS4gj3XbwpuiCDEKsmv0zMMWbaf9104nfgJAKTlFGHCmnRJ2xDs543SyjqToKXxMToyNtKu47vxPiKDNDg8b7iseswIEZM912/KuSFOs5S4yZXkT8nSOrxve4cXxK6US9yDrSqzrmKrmnP6xSKHhs9srYJOSHNHwQ1xCp+S/It3/YojFwodSoh0pCAcnfg9j71Jta5ebqGpv/Vvg5LKOou/547RtJwip17HlaudE+JOKKGYOIVPSf78sho8vvZnw2P2DFc5UxCOTvyewdEhT0tVZl3h12tlvLZjTs7ncuVq58SYWDmGRBgU3BCnOBJA2LOCtDOrOdOJ3/05uwp505ldF2/cwsp9F8RtNICz+eW8tssvcSzokmPBxOZErBxDIhwaliJOcSSA4JsXw90Z3RsXCQb+wwu0aq94XFlzRahVyBuvPj2oY7jg7XTGtlNX7X6OHAsmNidi5hgS4Uge3CQlJSEmJgYajQbx8fE4dOiQ1e1ramqwcOFCREdHQ61Wo1OnTli/fr2LWkuacjRx01ZeTEqWFkOW7ceENelY/+d6QAo7XoRO/MJr/Jm8+GUmJqxJx5Bl+0U7mduzCjlfnjBUKbeCic0BF9TvOHUV/9pxxumAm4hP0mGprVu3Yvbs2UhKSkJiYiI+/vhj3HvvvcjOzkb79u3NPueRRx7B9evXsW7dOnTu3BkFBQWor693ccsJh0vcfH5TBhSwf71lcxcbS0MRfM4XSgWwakI/OvELzNnhIUcIvQq5Ts9QUFbjTJNkYdFYGvpwJXvWJ2sccNOaVNKStOfmgw8+wJQpUzB16lT06NEDK1asQLt27bB69Wqz26ekpOCnn35CcnIyRowYgQ4dOmDgwIEYPHiwi1tOGrNUkp+PpsNazpbN1zMgxF/t4LOJOUIND9lLyFXIU7K0iH8zFW8ln3W2WZJSAHhjD/UMuIqj65N5Qg+hu5MsuKmtrcXJkycxatQoo8dHjRqFo0ePmn3Orl27MGDAALz77rto06YNunbtin/+85+oqqqy+Do1NTUoKysz+pGaJ64VMzouCofnDceWaYOw8rG++GLK7YgMtDxcZSkvRoiy+XRiEZYYw0N82Bry5JtblZKlxfRNGVanZrsLKnMgDnPnZGdutGgyg/QkG5YqLCyETqdDRESE0eMRERHIz883+5yLFy/i8OHD0Gg02LFjBwoLCzFjxgwUFxdbzLtZunQplixZInj7HeXJWfZc4iZn8Tjzw1XWEiKFCEzoxCIsoYeH+LI15MnQMEQDNFQkNjclV6dnWLwrW9B2yQEF8MKxdE5+7LZ2DleOpskM0pM8oVjRJEuUMWbyGEev10OhUOCLL77AwIEDMWbMGHzwwQfYuHGjxd6bBQsWoLS01PBz5coVwd8DX80ty96RFaSdDUyUCuBmhfvnVciJkMND9uKOoYhA80ON//rfGcS/mWoxyflYbjHyyzwvEKAAXhjWzsnL9563a1/cVeux29rj29PXPKZX3l1J1nMTHh4OlUpl0ktTUFBg0pvDiYqKQps2bRAUFGR4rEePHmCM4Y8//kCXLl1MnqNWq6FWS5+DYStvQYGGvIWRsZEeNcvH3hWknalrAzTk3MzcfAqrlQq37wmTC1ufiSvuVqvr9WYfNzfU1DjJucbC8+TAX61CRY3OrudQz4Bw+OSS2SPYzxsMwPK95wyPeUqvvDuSrOfGx8cH8fHxSE1NNXo8NTXVYoJwYmIirl27hlu3bhkeO3fuHJRKJdq2bStqe50lVd6CHDSuM5LQKcxq8CZU2Xyajikca5+J2DVXuDtre/JlGic5hwdIf2NjyUcT4+0qo0D1bYQlRH4fAMy4sxPmjOiCm5V1Jsepp/bKuwNJh6Xmzp2LtWvXYv369Th79izmzJmDy5cvY/r06QAahpSefPJJw/YTJ05EWFgYnn76aWRnZ+PgwYN46aWX8Mwzz8DX11eqt8GLVHkL7siZ2VeAZweKUnFkiNFZziR0cscAGBAZKL8hnKggDQZ3CbcrkKf6NsIS6lzbJaIFvjxuPt2Bat9IR9I6N48++iiKiorw+uuvQ6vVIi4uDsnJyYiOjgYAaLVaXL582bB9QEAAUlNT8X//938YMGAAwsLC8Mgjj+DNN9+U6i3wJmXeghzYuw4LN5y18Ugu3tjj2PRdChSFZe8Qo7OEuLMurKjB4nGxmL4pQ6BWCYPrfbG0/lVUkAaLxvZAiL+a1i4SiVDn2uJbNbx75an2jetIvrbUjBkzMGPGDLO/27hxo8lj3bt3NxnKcgdyyFuQiqMzxFRKBSYnxmDt4VxaW0omms6IE5NQM+cSOoXhoyf6Y/72M7KYDj5nRBej475p0BgeoAZYQ2AGAPf1bk1BjQj45PcpFQBj5nNwuHN2qL8Pr9ejmy3Xkny2VHMhZd6ClJydIeZIDg6tLeUZnAlOmx4Do+OicPKVkfh08m3wlvA7plQAXVq1MHmcCxrVXkr88+tf8Pi6n12yxEVzZuucrAAwbWiMxd8DDefsyCB+KRF0s+VaFNy4kBR5C1ISqrLt6LgofDixH0L8vW2+picHis3NwJhQBPva/sybMncM6PQMq/ZfwLObTqJOwtyHhtl85oP65lYqQg5snZMXjIm1ec4WqtgkEZaCMdasspzKysoQFBSE0tJSBAYGStIGe/NP3FVaThEmrEm3ud2WaYOsDnWYG9YK9ffBw/3bYPcv15DfaL2gED9vvDU+DmN6t3au8UQWVu49bzS1lo+mQ54pWVqXD0nZWmctxM8bJ14ZaRR8DVm232LuBjcEcnjecI88V0jN1jnZ1u+5wBQwX7DUE29epWDP9VvynJvmyJV5C1ISYoaYpQUbb1bUYs2hXPj5qIwfr6zDy9vOAFBgTG86mbi7WcM7Y/2Riyitsr44boDaC2880BORQb5GFx5u6QVXs3XHeLOyDqv2n8eLI7oC4F8qYuORXExOjKEAR2C2zsm2fj8yNhKzR3TBhiN5KKn6K4iOpDo3kqFhKSIaZ2eI8RnWqqw1LYJ2q6YeMzZnYGmy55Xdb25USgWeHhxjc7tbNfVoFagxqqPEHT9yteFInmFIlu+NwBt7zlIOjsykZGkxZNl+LN973hDYBPt6Y86Irjg8bzgFNhKh4IaIZmBMKCItlM0HbI9FOzsV+OODuUg+fc3h5xPbXLEIbD3PfablFBn9W6gibWIpqaoz1GKyJ9mUcnBcx9bxbSlPqrSqDiv2nkNqtvl1Eon4aFiKiCY1O99i2Xw+ib9CTJ18ZWcW7omLom58EbhuEVi+AZPxdu4w9XZvdj4SOoXZteyIJy/XIie2ju/muqSOu6CeGyIKW2Xzg/y8bSbZCTF1sriijioVi8CVM3sSOoY7tJ07TL1ddyQPKVlau0seUBVucfE5vpvzkjrugIIbIjg+ZfN9vVUYGRtpdT83K2ogxA2PO9zBuxOhpvjzNahTGIL9rE8JD/bzxqAmCZ8DY0JNEs7liPtbObLsCB3bwuN7fOeXVvHa35ELN0QdtiXm0bAUERyfXAdb5chTsrSYufmUQ+sKNeUOd/DuxJ47ViFmBaqUCrw9Pg4zNp+yuM07D/Uy2/WvVMh/OICbBRXeQo1WLTT46aW78HlaHq9lR1q10Mi+tITc29cU3+O7uKKW1/5WHcgx/D+tEu46FNwQQTQ+gZ2/fsv2E2D5rrO2Xo9/fP2LIIFNqL83Fc+yk62LkasXgU3J0lq80Af5euGZxBijXkCu/Ucu3MCtGutTyOWi8ftrWFcqltdyLTcrak3q48jpAuq6vCzh8D1uQwPUvPOkONywFtW9ER8FN8Rp5k5gfBw6d8Nk3ZyULC3++fVpVNSYTvFuKkDtZfPi9eYDcbK+S5QbSwUTx/dtjZGxkRgYE+rSRWAt1TnilFbVY/ne8/jy+BVDzoojx6KcaEurMWNzBu7u3tLs++CO5nF9ojBzs+nfRi4XUEufnVzaZwnf4zYysCFIe35Ths2ijRxKNHYdyrkhDuGmSL6x+1dMN5N4x8c3GVcR/2aqIfmUOxnyvdt+ZEBbq8mXzw2LoUrFdrCURFlcUYv1R/IM6xzdrKhxSbl5nZ5h/vYzvC4a+aXVmL4pw+FjUY72/XYDgGmCcWSQBh9O7Iddv2hdlvdkL1fnZQnJnuUUuDypiED+gTwlGrsGBTfEIks1HriiVRPWpGPdkTynXqOksg7Pb8pA8ulrNpOQmxoZG4nVT/RHVJMEzDB/HyRNbFgXhvDDJwkcaDgpz9x8CuP6NNxxi7kI7Kr953kvmSC/S6RwuPfm56MyFIYL8VfLeqaOO88kajxzzRwG4F9jeuBYbjF2Zl5FkK8P3nu4t92vQ8ng4qJhKWKWpbHycX2i8MnBXEEvJgwN9WiKK/iv/RPs523IBRkZG+lWCYtyZG/Bu12/aPHhxP54Y4/xMSJUuXmdnmGDk4Gzp6ms1WH53nPoFhmAGgv1o5pqfAF1ZWKvq/OyxBDk520xuH7xy1No3OnkyAKvNNFBXBTcEBOWxsq1pdX4+GCuKK9pT2ADAE8P/mt9neayVpeY7LnIcHfdIf4+ODxvuCgXzGO5xUZr9JC/LNmdjff/1ofXttwF1NWJva7MyxKarTwvAGg6mmbPscolg9NEB3FRcEOM6PQMi3fZNzzkasF+3pg1vLPg+3W3KatCcuQiU1BeLVpgKec7eqlpS6sBBXjNphoYEypJYq+tistyvcDzHZ51lJDDtsQ6Cm6Ikf/sO4f8MmEuLAoACoXpXY4lof4+uFlRa/PEwtU0ETIYcccpq0IaGBOKYCvd8OaIedctxzt6OSm8VWNxpk7jCygASZYI4PJWbLVPbhd4sdcjo1XCXYcSionB0uRsrNx3QbD9MQBThthe0ZmbffDmA3GGf5sT7OeNj/68y2yc1Pzil5mYsCYd8W+kYuXec3bPwHDlUgJylZqdb1dgE+wrbv0g7s6fmNeqhcZiRePIII2hN0bKxF4+7ZMbIXoMm56/Qv29MSWxA7ZMG0SrhLsQ9dwQAEDyaa0o+TTfntbiuWEx2HriD7MXz8Z3caPjorBa2R+Ld2Ub9R4F+3rj6cQYzBreGSqlwmI3e0lVHZbvPY8NR/PwzkO9eJ1EaPE7bijyV7ue83RiB1H/Htyd//RNGXY/199biYo6fgm37qbpcM7ouCirCfVSJ/baap/cCNFjyJ1LnknsYKgNJdf368mo54ZAp2d4ZWeWKPvmkpAnJ3TAi3d3MZlVYP4uzjjU0Hgr0S0ywDAUtXjXr1aHrkoq6zCdZ4+LO09ZFcqx3GLkl9Xw3l6hAJ4d1slsmQAhjY6LQtLEfnavL+bJgQ1gOpzD5T090LcNEjqFGf1ODom91tonNwNjQh2a+dSUAsB3WfkU2EiIem4IjuUW814nxVEr9p1HZKAGbz/YCyH+Pmbv4iz1yFwvqzEkPmZfLeN9IZ6//YzNHhep72zlwN73xhiQuGyf0Qw3sfKTxvRujVVQYMZm+3twPE3kn8syBPn6YGfmVV69IO6a2CsVlVKBpxM7YPne807tR+j11Yj9qOeGuOzCnV9WjZmbM1BaVWtyF8enoukLX2biPwf45wSVVNZh1X7r28vhzlZqeYWVdj+n6dR9cfOT5Dx3zzWeuL09Fo3tgTf2ZBvlmQ1Ztt/q37xxQToxCy56klnDu9hchZ4vT74pkjsKbohLL9wMwL92nEFtkyJkfIaHmj6Hjw1Hc60OmdhTat0T6fQMW45ddno/YpXUTz7dsDp8c+elUmDm5lMOJb27Y2KvlLhV6IXgyTdFckfDUsRwgXfVmjzFFXWIfzMVf49va0i4E+sOp6SyzmrXsLtOWRVKQ76NMH97obviU7K0NBz1p52Z15xKene3xF6OVLWnQvzVTj2fhvukR8ENMbrAu2oAoLy6HuuP5GH9kTxEBWnQv32waK9lK3Di7myb1rlpDjUpxAgqhdgnN0xJGty0Mk2fb1DpbpW8paw9Zc8x3BxvitwBBTcEwF8X+Pnbz1itd+KlBBwYHbJKW1qNPWfyhd1pI3y6ht31ztZZYnSbC7FPsYupeSJPyu+QoqpyY3yP4TkjuuDL41dMborsTfwmwqPghhiMjI3E4l3ZACwHN0IHNmIL8eNfbM7d7myFYGs2jT2E7Ir3pAu1q3hKfocUtaeaDn/FR4fwmmU2a3gXzBrexei5NytqTBaUbU7VzuWCghtiIGT+hVzQPBvrrOUc2YtBuK54T7lQu4Kn5XfYU3tKqNwuc8Nf4/pE4ZODubyGnbh2pGQ1JMBL1eNE/kKzpYiBJ94tcwnFxDJLs2nsFeLnjZGxkYK0aWBMKCIDnUvqdBcaL8dPw56Y3+HK2lPWll755GAunh0Ww3uWGZ9yFkLPJiSWUc8NMXCk3ok78MSgTWiNc472Zudj3ZE8u/dx08bMNHuolApMGNje6WJq7qDaibFeT0x6d1XtKT7DX7t+0eKnl+7CyUs3bebiubrHiVhHwQ0B0PBF33BU+LWl5ICGOPjhco4GxoQi0NcbG47koaSK/2KagLCBZJmdr93cLBrbA5MTY6z22Eg1ldoZrqqqzDcYOZ5bDCWPvxlVO5cXCm4IAGDV/vN2rQrtLhQA4qNDpG6G20g+fQ2v7MwyqkAc7OuNET1a4ZuMqzafL1QgqdMz7Mi0/XrNWXgLtdVARcqp1M5wVe0pvkHGzM0ZRkF+qL83HuzbBiOaLIpJ1c7lRfKcm6SkJMTExECj0SA+Ph6HDh2yuO2PP/4IhUJh8vPbb7+5sMWeR6dn2ODAMIQ7YABW/5gjdTPcwtLkbMzYfMpkaYWSqjpsy7iKYD9vl1VybljvzPOCbSFZu0hayyURb5kM4diqqjwyNtLphVvDA/jldDXtvSyuqMO6I3kmy18092rnciNpz83WrVsxe/ZsJCUlITExER9//DHuvfdeZGdno3379haf9/vvvyMwMNDw75YtW7qiuR7rWG6x3cMP7mT53nPoFhkg67tVqSWf1uLjg5aHJRkAMGZxmAAQNqnVma57jbcS1R66MjjH2kVSiqnUYuDywNJzipB2sRBAw7BpaWUthizb73yPlAB5vVyw+OHE/gjx98GYuEiz+WqemPgtd5IGNx988AGmTJmCqVOnAgBWrFiB77//HqtXr8bSpUstPq9Vq1YIDg52USs9X35pldRNEJ07nMylotMzvLIzy+Z2JVX1Zh8XI6nVma57Tw9sAKC0qg6p2flm/+aelNiamp1vNLS2ysLCuVyQMXtEV3QI9+OVX1RYUeN0+7j4aNaWDDTuPFIqYPRvT0z8ljvJgpva2lqcPHkS8+fPN3p81KhROHr0qNXn9uvXD9XV1YiNjcUrr7yCu+66y+K2NTU1qKn56yAuKytzruEeqLiiVuomiM5dTuZSaBgCcvwYWDRW+JO2kMUFPVFlrQ7TN2XgIzNTksVIbJUiMdlSlWJzuG2W7z1neMxWb46QuS9NR8XYn/9+JrGDYf08urFyLclybgoLC6HT6RAREWH0eEREBPLzzZfij4qKwieffIJt27Zh+/bt6NatG+6++24cPHjQ4ussXboUQUFBhp927doJ+j48QSjPsWd3x6dAoU7PnB7LdzfODAEpALyxR/jaHVxSqef/9Z1jrm6KUImt3Hfh9d2/4ra39mLCmnS8+GWmSa6JGKwNrfFlK7/IVo6MM7h2J5/RUmAjEclnSykUxh86Y8zkMU63bt3QrVs3w78TEhJw5coVvP/++xg2bJjZ5yxYsABz5841/LusrIwCnCYiA5tH9n7xLevd0O46u8RZztzBijnEMbx7hO2Nmjlzf3shplKb+y40JnbFXSHWFrOVXyRkdW5L8stqMO+bXzC0a0u3mYrvKSTruQkPD4dKpTLppSkoKDDpzbFm0KBBOH/ecqEvtVqNwMBAox9ibGBMKEL9faRuhuisvUdLs0u0pdWYvikDK/ee99heHCE+fzFqd3x6NE/wfXqipn977qINwKRXgk9iq6XvQmNiV9wV6nhqHHybY2lWVqBGuPv+bzKuuqzHi/xFsuDGx8cH8fHxSE1NNXo8NTUVgwcP5r2fU6dOISrKc++qXUGlVODNB+KkboboIoN8zT7Opwt8+d5zSHxnn0eemIT4/MWo3XE8r0jwfXqivMIKk8dsTaW21Nui0zMs3sVvOMhW4OAMvtO0+bIWLI2Oi8LhecOxZdogrHysL7ZMG4TX7osV9PU57jIV3xNIOiw1d+5cTJo0CQMGDEBCQgI++eQTXL58GdOnTwfQMKR09epVfPbZZwAaZlN16NABPXv2RG1tLTZt2oRt27Zh27ZtUr4NjzCmdxSe+yPG6nRgKWi8lE6Vp+c0nTrbOEGysLyGVxd4flmNxy5+58znH6jxQn5ZNdJyigTtdvfzkXzU3C0s33se3SJbmByTjZfU4JsIvGr/ebsXz+Xby8I3KTklS4vFu361qw222Aq+uercnDSepbHsHc5yp6n47k7Ss8ejjz6KoqIivP7669BqtYiLi0NycjKio6MBAFqtFpcvXzZsX1tbi3/+85+4evUqfH190bNnT+zZswdjxoyR6i14lAVjYvHzxWJk/lEqdVMMhAhsAONu+IaTZ7bDK6B76olpwZhY9GkbjJe2nUZFjY7388qq6zFnayYAIDJQjcXjegoS/D3cvy3+l3nN6f14Ou5iObx7hNk1kPjmQqVkaR1ay8tcz5G5ffPJZ7NnhhQfji7VMDAmFH4+KlTWWv4eqL2UqHHg/OROU/HdmYIx5pmJBBaUlZUhKCgIpaWllH/ThE7P0Hvx96iw8oUWmv+fJxAxD8KnB0djVM8oDIwJRWp2PqZvynB6n1umDfLIE1NKllaQv4+5Kcr20ukZ4l5LQVUzqFsjhFB/H6Mp/fYkw+v0zKQwnj2sfd6WAhbu1oDrCbW3DaH+3lh0X09cLqrA8r3nLS7V4EhP61t7fsWaQ3lWt1Eo/pry7YiVj/XFA33bOL6DZsie67fkyy8Q+UjPKXJpYAPA8HoP928DPx+VKK+x4eglTFiTjsR39uEfX/0iyD49cfE7LvdICPO3n3E60VSlVGDi7TSzka+mtYqa5ndYK3PgzOwkrufI3Odtq1oyGj3X3jYUV9QhMlCDF0d0xUcO5BdZknz6ms3ABnAusAFojSmx0aA2MTiaUyjJ6zIAe85oRa8sm1/mfEVSjieemISYfsspqaxDek4REruEO7yPlCwt1h2+JEh7mqPG+R16fUM9IkvDQs4E69aGWeypluxIG7jnOJJfZA7fat3OEGpVc2Id9dwQg+N5ws964MtdSuZ78uJ3qdnmi2c6qmE9IMcI2YvUnHHBw4zN1hfRDPd3fnaSuePHnmrJjtwwNG43l1/0QN82SOgU5lBOnNgLttIaU65DwQ0B0HCXfCzvptTNkDVPPjGlZGmxXvCV4R3/GwnZi0TMazwspBcg9XL9kTyTIbDz18t5Pff89VuorbN/SPwfX/8i6LRqsYebHR0qI/ajYSkCnZ5h/vYzUjdD9jx18TuxekmcSbj2xJwmIfj7KFFR+1cvZwuNCuXVjufJcT07W445P/z31xAYwxt7ztoVnFpaENOW/LJqi2tsOcKe3qNBMaFI51Hj52/921CFYglQcEOQfrEIJZXidcW6q6ggDR67rT3vVYbdlRi9JCF+3hjU0fHgxhNzmoRQq2Pw9QK4BdqdCWwa++m88/l2fw2BnXK+QXaav/2MIOUZBsaEItjXGyVVts+HvjwmQIT4eWPZ3/p45HlD7ii4ITh6QZpEYjlbNLYHJifGNIuT0l6Bc20AYOlDvZz623HrI9HQlLE6HYMYtyH21DWSo5LKOqzafwEvjuji1H5USgWeTuzAq97Pgd9v2NzmrfFxzeIcIkeUcyNTjadtHrlQiCPnC0VbqfpKcaWg+3N3of7ezSaw0ekZdmReFXy/ej2cWl298fpIRDwKAMF+3i59zfF9W4uy3w1HcwU5N84a3gUab2EujSECJGoTx1DPjQzZWpFX6JWqC2/R3XFjbz5g/m6Lb/l4dyLW7JBZWzLQ+DrjyDFLq4KLiztyJyd0wIp99lcmdlSgrzjBVEllnWBVf5UKYb7XlDsmHQpuZIZP+XFuCqdQWfc1umZVpNqq54bF4J64KKTlFBkFManZ+bzKx7sbsU6+TW+gHTlmaVVwcYX6++CNB+IQJECwYc8aS7d45LM4Sojj+VhusdVlF+zB5Y554o2R3FFwIyN8VqcGhF98rW2wL05eKnFqH54g2M8bfdoGm5SAD1B74VZNvcn22tKGmRpTEjtgRGykW56wXJW468gxK2XdpeagqKIWb+zJxr1xkU7vKzJIg0cHtOPVA7RdxPXChDiehar35Oejgl7PkHxaa7WAIhEH5dzIiD2zVhpX9nRWdJif0/vwBCWVdZix+ZTJZ2AusGls3ZE8TFiTjiHL9gtac8MVuMRdV7D3mBVrOQ7yF21ptdP1jUL9vfHTS3chpqW/MI1ygFDFNYWs91RZq8Pj6362WUCRiIOCGxlxpvy4o3R6hq9O/OHUPkgDdzxhSZG4y/eYfbhfW5FbQjjOdDgWV9Th5KWbkk/fd7a4pivrfTVdV4sIj4IbkVhbpM7SdoXl9q995OwJ5VhusaBrLjVn7nrCcnXiLt9j9nYPXHVdrpw9XAvKqxEfHYJQfx9hGmSHKIGq/qbnuLbel5C978QU5dyIwNxsJ3NjrClZWize9atRcKFU8DvRCLX4GmXzC4s7YW08kus208k/PZrrktex95g9eYmWA3EXeYWVuOO9AyYrk4thdM8I3NYhFKEBakQGCpec68xaaM7wtHOwXJKnKbgRmKXZTk1ni6RkaTF9U4bJ8/kGNoAwaxxJ3ZXsqd7YcxZrD+fKPmkwJUuL9344J/rrOHLMetpJ3xMpAAT5eWPF3nO8Z0s56/tfr2N8vzYifK+kuRHxpHMw3xt7V6BhKQFZm+3UeMiitl5vc2zXWpkFIRdfc2VCaXMj9xwcLsCurRd/RXZHjtmcglsitogIgTX5r6twQ798h//5EKI+jj2ESoKWC+7GXi7J09RzIyBbs524IYtPj+baHNtlDFg4pgdaBaoRHqAGGFBYUSN4N59KqcCisbGYsdm0F4k4R+gp+0ISa7FMc2bd1RlzRna16/3r9AwbqM6N7N3XOwrfnnbtRYs7j67afwFfHr8sWC/BoI5hCPbz5p13kxATBo2PktcyDJYI0fsuB7Zu7KU4D1LPjYD4dqMfz+OXS1BaVYsH+rZBYudwJHYJxwN92yChU5jgB0cLDcW4nF5tAgXdn1yTBsVYLNOSxM7hdh+zx3KLUV5tfQo+cV5UkAarHuvn8Gyp/b8VCNsgOyzfe87kGOZqTyWfdqyWztODY3hvm5ZbhB8dDGyUCuDDicL0vssB3xt7V54H6aomIL5jp/6863e4JsLdnkFTwTlnrpaJsl+55I9wyX7fuaCL2N4E4saJiOeul4vbOIKRPVrho0kDoFIqsPP0VaRm2x+oCFXJV2gzN5/Cf/XAfTzXsbK15I0ljg6C6RmgLa3CzsyrHlGxmO/5zZXnQQpuBMTlr+SXVps96LmT/UP922IHjyqdrhoDrpDpCcqTyCFp0NETuDP4drtL0bbmrrpeD5VSgZQsLfY6ENjIGQMw68tTOHOtBAvGWK/jxGfJGzG8sees4f/dvWIx3/ObK8+DNCwloMYF0ZqezhvPFhncOdzmSrwhft4Y1NE1wc1tHUJc8jrNkVySBi0l+4lFqQCeHRbD62Tt6raRBh3C/Hgv+eKuPj6Yi2QrOUFyef9yn3xgC3djb+k2RorzIAU3AhsdF4XVT/RHZJMZSI1ni6iUCrzzUC+r+1n6UC+XdVM+Zcc4M+FPyCn7zpDiBK5nwCcHc22erOVycWmO/jUmVtTcK1s3cK6yaGeWxVlUrsw9s8ZdC4By+N7Yu/I8SMNSIhgdF4WRsZFmCxlxeQXHcouh8Vaius54Gq4C/O94heLjpcSdXcPw47kil71mcxApk65mqU7gDLZnSMjl4tLceCkVyLh0EwW3hK9OPio2Al0jApDQMRzH84p5LaYppqKKWhzLLTY7zC+XXDjAOOnW1dPShcDd2DcdXpbqPEjBjUhUSoXJAconr4ChoSu1X/sQlx4MwX5ql71Wc/C3/m2x7G+9ZZEkKOUJ3NbJWk4Xl+akXs/w+LqfEeovfO/KD9nX8UP2daw6kIPIQLVd06vFYuk4k0MuXFPu/J2wdmPvajQs5SL25hUs3vWry7ondXqG3Q5OnSTmbcv4A6nZ+VI3A4D0J/C9Vv4OUretuSuuEDfouF5WI3lgA1g+zmzlikjB3b8T3I29WKVL+KLgxgUcySvIL6txWU2A9Jwi6MQvUtvsyGX8XOoT+LojeRZzb6RuGxEXV8AtQM1vkOBv/dsI3gZriawNRUx7yCLnSy6TDzwFBTciaFoSPP1ikUN5BUcuFGLHqatYd+gidmT84XR5cUukWjDOk8mpeB+fZD+xWQr0rLWNeAYG4FYNv4KMyVnC93ZaS2RNydLiX//LEvw17SWXyQeehHJuBGYurybY17Fx7VUHLpg8JkY9BD312ohGLuPnlpL9gny9UFIlfiVga7k3ltpGmh+hiwLOvruLxXOlpcWLpSCXyQeehIIbAVkqBlVSJdyYs7bJ6uJCOP0Hv+UgiP3kNH7eNNkv90YFVrpwJou1QK9x25LPXMPn6Zdd1i7iGn4+SlTWuvZOqt5CT7dOz7B4l2vWVrNm1l2dkdg53O0rFMsRDUsJxJX1OrgptkIMUaVkaXE4R/qhE08UpPGS3fg5l+yn9lJixb7zLs01sBXocW1rH+rvohYRV7IU2Ih5Sc+5YX4Zj2O5xcgvk76XsEtEgKRJt56MghuBuLpeh7a0Guk5ztWlceXK0M2RjgHfZ+Ub5V/JIcFYp2eYv/2MS1/TnkTJkspakVtD5CQiUG3Henv2+S7rutlkdrkMF8upZ9fT0LCUQKT4sszcnIF3Hu7l8PAUFVAT162aeszYbDymL4c1ZNIvFrl8eq49iZIKuoltFvx9VPhk0gBAATy+9mdRXkMB84UkpQ4q7F1UltjPoZ6bzz//HImJiWjdujUuXboEAFixYgV27txp976SkpIQExMDjUaD+Ph4HDp0iNfzjhw5Ai8vL/Tt29fu1xSDFF+Wkqo6p9YjkcvdS3MihzVk0pzs8bPX3d1b2hXMJXQMF7E1RC4qanXI1pbhk4M5or2GpVmLA2NCERkoTYBDM6Ncw+7gZvXq1Zg7dy7GjBmDkpIS6HQN2e3BwcFYsWKFXfvaunUrZs+ejYULF+LUqVMYOnQo7r33Xly+bD2ZsLS0FE8++STuvvtue5svGj4Lhzk6a8oWR/NvpL57aY7ksYaMa19332837ArmBnUKQ4BanGEK4pwQgdeLeiv5LH46J34piqY3ciqlAovHWV8tXCyN1xkk4rE7uPnvf/+LNWvWYOHChVCp/joBDRgwAGfO2DeO/8EHH2DKlCmYOnUqevTogRUrVqBdu3ZYvXq11ec999xzmDhxIhISEuxtvmhs1etgAJ4aHC346zpTT4ULyIhrSV0DR4qeEXuCOZVSgXce7C1yi4gj3hrfC1MSO0jdDLuZu5EbHReFaUNdt2hwsJ83vphyOw7PG06BjQvYHdzk5uaiX79+Jo+r1WpUVFTw3k9tbS1OnjyJUaNGGT0+atQoHD161OLzNmzYgJycHLz22mv8G+0illYE52w9/odoK+U6MsTUOCAjrnfkwg1Jem8GdQpz+YrNfIK5xsUvfzxX4KKWEXsE+XljRGyk1M3gzVrV35QsLdYeynVZW0oq66BUKmgoykXsDm5iYmKQmZlp8vh3332H2Fj+F8rCwkLodDpEREQYPR4REYH8fPNVKs+fP4/58+fjiy++gJcXv1zompoalJWVGf2IaXRcFBaNNf93uF5WLVoip6NDTKPjotC/XaDArSF8rDqQgyHL9rs8/0alVOCdh3q59DUB6wF4SpYWQ5btx4Q16Xjxy0x8k3HVhS0jfKXlFLnVkhkM5nNb+JTuUCqAaUM7CNoeOUw/by7sDm5eeuklzJw5E1u3bgVjDMeOHcNbb72Ff/3rX3jppZfsboCiydQIxpjJYwCg0+kwceJELFmyBF27duW9/6VLlyIoKMjw065dO7vbaA+dnuFf/zM/PCfGPboQ65G0DQ0QrkHELlIlGI+Oi8KcEV1c+pqWAnB7F5Ul0jl8vsCtlswI8fPGSDM9TXxmiuoZMLx7JD56or9gw/ev7jyD5NPXTJbokUOJCE9j91Twp59+GvX19Xj55ZdRWVmJiRMnok2bNli5ciUee+wx3vsJDw+HSqUy6aUpKCgw6c0BgPLycpw4cQKnTp3CrFmzAAB6vR6MMXh5eeGHH37A8OHDTZ63YMECzJ071/DvsrIyUQIcnZ7hWG4xPk/LlfU0W3MYoy+WVLiFBc1NVxXbrOFdsPnny7heXiP6a4X4eZsNwF1Z/JI4L/OPMiSf1mJMb/dYMuNmZZ3ZZT/4DuMXlFfjgb5tTCp7/2f/eTgSj5RX6zBj8yn4+Zw2WmpCDiUiPI1DdW6mTZuGadOmobCwEHq9Hq1atbJ7Hz4+PoiPj0dqaioefPBBw+Opqal44IEHTLYPDAw0SVhOSkrC/v378c033yAmxnximFqthlqttrt99jC3npQrKBXAqgnOZ90X3ZLvyak5aJxgbG7tJbGkZuejxkXLwdfUm38dqrXkfl7edhr3xEUalsz4777zWOHCZTzsZS6Q4TuMz23HVc/mdI0IwIzNpxxuU9M1tPJFWFanuXOqiF94uHOzLubOnYtJkyZhwIABSEhIwCeffILLly9j+vTpABp6Xa5evYrPPvsMSqUScXFxRs9v1aoVNBqNyeOuZGk9KVfQMyDE38fp/VTX0cqZcuDKukOuPm4ra3VIzylCYhfjcwbVWnI/t2rqkX6xCImdGz7LrSeuSNwi68wFMlzeUH5ptdnvgK0ie2N6t0YSgFd2ZqG4wvmeeil7cD2V3cFNTEyM2ZwYzsWLF3nv69FHH0VRURFef/11aLVaxMXFITk5GdHRDVOmtVqtzZo3UpJDl7oQF4fKWvFXhSa2uarukFTHbdrFQpPghmotuae0nIbgRs49b9YCFC5v6PlNGVDAfD7korGxhqGoVi00RotbpmRp8caes0aBTYifNwZ3CsP+swWostBTaY1UPbieyu7gZvbs2Ub/rqurw6lTp5CSkuJQQvGMGTMwY8YMs7/buHGj1ecuXrwYixcvtvs1hSKHL7azF4eULC1+u85/Cj8Rh62kcC6ny9yJ1l7SHbem7bV1B03k6dz1cqTlFCG/tErqpgCASYDCpwowV7pj/vYzJnmSvj4q/Ot/xo9HBmowYWB7lFbVYv2RPJP93aysw54z5mf62oN6M4Vhd3Dz4osvmn38ww8/xIkTJ5xukDuR+iB0dpYUNzRBpGftJGwup8uZBESppqMGaryg0zOj98ndQU+n49Ct/JB9HT9kX0eAWvrlCeeM6Iovj182+n5E2vH9MDcBpLJWZ5oXU1aN5XvPOd9gG6g3UxiCHZn33nsvFixYgA0bNgi1S9mT+iAc1yfK4bt3OQypEdtJ4ZZyY6wlINrq5Sm+Jf7sKHPe/u43bDiaZ3LRGRkbiWA/b5fPMiTOu1Uj7ZB2qL83nh3WEQOiQ5B2sRBAQ+LvoI5hNs+N3DlQLmgxTWEJFtx88803CA1tXh+K1F3qOzOv4eXRPRwKcOQwpEaAVRP6YUxv84GNtQDUUgKirV4enZ6hqEKa4AYwH5Qdyy2mwIY4pLiiDrGvphh9R7Zl/MGr10ZO50BaTFN4dgc3/fr1M0ooZowhPz8fN27cQFJSkqCNkzs+SWliyi+rwar9F/CiA8XYpB5SI8AziR0wpndri7+3dfJtmoBoq5fn2WEx2PWLVtITurmgjI5F4gx7ejUbk9NxZ88wGuHH7uBm/PjxRv9WKpVo2bIl7rzzTnTv3l2odrkNLilNqmJWy/eeQ7fIALu/FFIPqRGYrZzamD2Fxmz18gDAxwddt46ONU2DsrxCSmgnwuE7rVrqc+DCMd3RKlDj9AQBYp5dwU19fT06dOiAe+65B5GR7rN4mti4YlbLU89h1YELLn99R2ojcENqcumWbW74JIPbU2hMTl3sfBWUVyMlS4vle+VbAI64Jz7TqqVOK/j1WhlaBdJNpljsWlvKy8sLzz//PGpqpBuzlyuVUmEoauVqfFZcbopWBJcWn7F1WwsUNl5XTE5d7HyF+6tlldBJPI+174XUa2T9L/MaXvwyExPWpEuygK6ns3vhzNtvvx2nTjledtqTDYwJhb+PSpLXduTiNjouCh890R8+KuoOdaVgP29e21k7+TZNQPzezU6MYf4+gAJu19tE3Iut3k8urSCyycKYrj4jSrWAriezO7iZMWMG/vGPf2DVqlVIS0vD6dOnjX6aOyvFm0Xl6Pjx6LgoTL+jk8CtIdaUVNbxPpFZOvlGBmkMCZO19XokZ10Xq7mi6NMuCIUSTUknzQPfOmCj46JweN5wbJk2CM8kdgDg+skh3Ost2Z1NK4QLhHfOzTPPPIMVK1bg0UcfBQC88MILht8pFAowxqBQKKDT6SztwuMdyy3GrRrh3r+XAqjncZwH+3lDr2cmBdL40OkZth6X99ownoiBf64Ul9NlqXbN52l54jdYYL9cKcWUIR2lbgbxYIvG8p9WrVIqMDAmFHO/yhS3UVbQ8gvC4h3cfPrpp3jnnXeQmyuPGRdyJHTeg0KpAHS2o5uSyjo8vu5nRAZqsHicfdMJj+UW43o53UFLQVtabXYxSXOarkrcWG6R+802KqqoBRho6QUiGnsXFZZLUr475s/JEe9hKcYaTj/R0dFWf5ozoacW1vEIbBrLL6vGdDvHbemLJK2Zm50fZ3fXjKnCihqM6xNFgQ0Rhb3nNrmcC6Weou4p7Mq5sbYaOGlIKA725ZcsKqYF28/wHrelL5K0Sqr4599YorQzvAnx84bay+50O8HlFVbiE5nU3iHypFQAfj6OHav2ntv4bt9CI856Wo1nPxLn2XXUdO3aFaGhoVZ/mjOVUoGn/0xIk9LNyjqkXyzite3AmFC3vfP3JI4mEqZkafFp+iW7njO8WyvU1Ovtfi2hKABEBqqx5dhl6rUhVq2a0A/PDbN/woMjQYKt0gtAw1pWf+vf1u722ELLLwjPrhB0yZIlCAoKEqstHmHW8C745OBFVNRKm1idllMkWd0dYh9HEwl1eob528/Y/XrlEi52yJ22JwxsT8X7iFUv3t0F98RF4R4AG47m2bX+2KKx9q+5x2c5neKKOmw4mmfXfvmg5ReEZ1dw89hjj6FVq1ZitcVjeHspAYmDG76TGY/lFtPds0zYO+affrHIoQUnparFBPx1Epey54i4h5X7zuOrE1fw2v2xeOehXpi+KYP3c0P81Q69piuX01EogPf/1getg309ZvkFnZ5ZnNXparyDG8q34UcuKxwndOTXayOXJDpif45AWg6/ocfGgny98FD/ttiRec3u5zpr0dgemJwYA5VS4VDbSfPTeBHMe+Mi8B3Pek7OnNcal17IL63CG3vOorii1uH9WcIYUFJZi4fjhR/mkkJKltYkKIySsEfK7tlSxDq5BAulVfwCLEoolp7jiYT2fyfLqutRUlUHKW6mwluoDXdxXH4DIdawP3/mbz8DtRf/Hkdnz2tc6YXIIF9RAhvOpeJK0fbtSilZWjy/KcOkt0vKysu8gxu9Xk9DUjyIHSx48bwqvbGHX4LqwJhQSS50xJgjiYT2zpICGu4W/2/LKUhRBLXxd4PWNiP2KKmsw/949jaG+HkLNuNI7JvV6FA/UffvCjo9w5Ld2WZvtaSsvCz9fFAPc7OiRtRgoZ7nAcJ3MU2VUoFQGUxfb64C1F6GZRTskZKlxX8kWIHeUcFmLjij46IwZ0RXiVpEPNVb4+MEy/MQ82ZVqQAmJXQQbf+uYqv4YeMJE65EwY2AUrK0mLFZmrtic/jedaikyy9t9p5MaG81sNHpGdJyirAz8yrScoqg+3OZDXdbTbuksg7fZ+WbPD5reGdEBjqW/ElIU88Ni8GY3q0F2ZdOz6DXM9Fql00bGgMfGdSbchbf64yrUzbEqUbUDDk6LVdMfO86KiWf2dV8JcRYTvy2lKD32G3tZFEm3l6ztmRgFfoZXXxUSgUWj+uJ5/+cCSOT+wLihqYNjcGCMcIMdZr77glFAeDZYcK1VWp8rzOuzu90/7BRJlbtvyCLWVIcc8MA5uj0DBW1NC1XKkqV+e5zawl67lofRs+AGZtPmSQXWlr5nBB7fHtaK0heh6XvnhACNV7Ifn20xwQ2gO3ih1JVXqbgRgA6PcOGI/IqI//04Bhe487HcotlM4zWHBXeMl20lE+Cnjubb2Z5kNFxUTg8bzi2TBuEO7pS8UliPyHyOqx994TwzkO94SthnSkxNJ4c0PSKI2XlZQpuBHAstxglPKdeu0KwnzdmDe/Ma1u5TF1vrsx11cpldWKxlFTWYdV+02RolVKBgTGh+OXKTQlaRTyBs+czsb979q5U7i4s9b5GBmkcmjAhBMq5EUB+aZVLX89bpUCdjlksEf7OQ714R8lU50Y6lrpqxQw4AzVeKKuWbvkFzicHczBreGeT47ThRoFywIhjnD2fiX2ztzc7364lVtxJ4+KHcqhQTD03AhCzyJM5s+7qgo/MRMlRQRp8ZGeUPDAmFN4W8j6IuCx11dpzgrbnkwv198bR+XfLYqHUilqd2cVdqSeROEqIvA6xb/a2n/rD5fVeXIkrfvhA3zZI6BQm6ZIS1HMjgNAA105l7dIqQLAoWaVUIECtws1K6e/mm4sQP28sfaiXxSCUS9Dj0z1uz2myuKIOZ66WYmzvKHx72vUVQ5syt7gr9SQSR43rE+X0xfSmyDeqNyvrsWr/Bbw4oouor0Oo50YQkYGuPSHP2NxQzlqoKFlF64a51Iw7O6GmXm+oW9OUvdV7/exIUMwvq0bnlgG8txeX6XsfGBOKII1nJVwS4Vhb9PWTg7lIPn3NpC4UXzo9wxt7xK8ftXzvOUmWI2huqOdGAPbcaQtl/vYzGBkbKUi3X62Ochxc6a3k3wz/b2lhOa567/K952zuz54j4JUdp2Uz9d/c4q7fZ+Wjpt5zu+2Jcyqs1ORiAGY1WVrEnoUbXZnIv2R3tmDnb2Ie9dwIgLvTVsC+C40zSirrkC7Ayso6PUN5tTwuds2RtYXl+FTvbaFRWT3hNyWXwCbYzxuDGiVW6vQMszZnYMbmDFTXy6ONxP007aixZ+FGV+Z7SbEcQXNDwY1ApChE9sXPeU7v41husUfUTnFX1haW46r3Wguay6vds9et8Yy+lCwt+r/xgyzygIhz+rQNlLoJRuxZuNHV+V6UPC8uCm4EotMzBPn64J8ju6KFxjWjfT+dL3Q68/7azUqBWkMcZW1hOU+r3hsZqDaa0cdVgy2tooR2T/DLH2VSN8EE34UbbVXaFRolz4tL8uAmKSkJMTEx0Gg0iI+Px6FDhyxue/jwYSQmJiIsLAy+vr7o3r07li9f7sLWmpeSpcWQZfsxYU06/vHNaZS7qI5IRY3O6a7NzD9KhGkMcZqlO7nRcVFYNNZ9y7X/352dsPKxvtgybRCOzL/bENiIXQ2WkMZs9ZTwqbQrFCmWI2huJA1utm7ditmzZ2PhwoU4deoUhg4dinvvvReXL182u72/vz9mzZqFgwcP4uzZs3jllVfwyiuv4JNPPnFxy/8i5jokfDjftUkJbXJh6U7OVbM4xPL5z5eRV1hpUqrA0ysxE3nh01NirdLuR0/0x5TEDoK05b7ezk9bJ9ZJOlvqgw8+wJQpUzB16lQAwIoVK/D9999j9erVWLp0qcn2/fr1Q79+/Qz/7tChA7Zv345Dhw7h2WefdVm7OXK483S2a7NDmJ9ALSGOUqDh5GnpTs7dg4CSqjos33sOG47m4p1G9X0o54C4gq3vV2NcesHL93RDcUUtQgPUiAz8q4ZYkK8P1h3Jc7pNaw7lIj46RJJlCZoLyXpuamtrcfLkSYwaNcro8VGjRuHo0aO89nHq1CkcPXoUd9xxhxhNtEnqi44CQHx0iFP7mJTQQZC2EOdYW1jOU4KAkso6TG80cyXc37XFL4lzfL0lz2Kwmz0LNzZOL5jz1S94Y89ZvJvyG0qrag3P5fJyhPCvHWew45T99XgIP5IdrYWFhdDpdIiIiDB6PCIiAvn5+Vaf27ZtW6jVagwYMAAzZ8409PyYU1NTg7KyMqMfoUh90WEATl5ybpFBlVJBA1MSigxU21xYztMSD7lVwfWMTujuIj46GFV17jdFn8/CjTo9w8q95zDdTHpB06nkKqUC4/oI09tSXFGHOVszMWFNOoYs20+F/QQmeRE/RZPquIwxk8eaOnToEG7duoX09HTMnz8fnTt3xoQJE8xuu3TpUixZskSw9jYmh4uOswFW+sUiSuiUyJwRXc0uHtkUd7eYX1rtEZ8Vtyp4nc79LpbN1clLJby3tbSgrytEh/piWNeW6NsuBK2DfW0uSZOSpcXiXdnILzN/HuXex792nEFVnR6tWqjx5fErgrebC6KkWkHbE0nWcxMeHg6VSmXSS1NQUGDSm9NUTEwMevXqhWnTpmHOnDlYvHixxW0XLFiA0tJSw8+VK8IdmK6eOmhOqK+PU88/mlMoUEsIX0oFkDSxP14c0YVXUqFKqcCisT08IrDhbDiaCz2j4MbTzBnRRdKyBZeKq/B5+mW89M0v+PH36zYDm+c3ZVgMbBrjelkeX/uzKGUL7KnHQ/iRLLjx8fFBfHw8UlNTjR5PTU3F4MGDee+HMYaamhqLv1er1QgMDDT6EQo3dVDKQ/G36+VOPf+PYqpz42rDu7fEmN78785SsrR46ZvTIrbI9Uoq6xDiRzk3niRA7YVZw7vg8Lzh2DJtEGbd1UmytugZ8PHBXCxNNj/LUA6TQZriW4+H8CNphtjcuXOxdu1arF+/HmfPnsWcOXNw+fJlTJ8+HUBDr8uTTz5p2P7DDz/E7t27cf78eZw/fx4bNmzA+++/jyeeeEKqt4DRcVGYfbd0K7xedjI4kdOXu7nYe/YGkk9f47VtSpYW0zdl2LXEgrsIb6FGsJ+31M0gArlVU4/U7HzDgr4v3N0Vof7O9Sw7a82hXNSaWc5D6skg1kidy+kpJM25efTRR1FUVITXX38dWq0WcXFxSE5ORnR0NABAq9Ua1bzR6/VYsGABcnNz4eXlhU6dOuGdd97Bc889J9VbAADUS9iNmF9ahZ2ZV9Gqhcbm+LI5SloRXBKv7MzCPXHWa13o9AyLd7lvfRtbIgM1eHt8L8zYnCF1U4hAuAUhU7PzsWR3NooraiVtj54Bn6flYcrQjkaPyzmAkEMupyeQPKF4xowZmDFjhtnfbdy40ejf//d//4f/+7//c0Gr7CNl7kDq2QKkni0AYN8KuJw2wb5iNY1YUVxRh2O5xUhotHhkU8dyi3nlA7ibxnVHqAves2hLq7Fq/3ms2HteNr3Cl8z0bssxgLCnHg+xzf0KF8iQXHIH7FkBl+Olop4bqdi6e5Tz3aWjmtYd8cT32NxtOJInSmCjAODno7L7edGhpoVKB8aESj5k1pg99XgIPxTcCCC8hTyCG3sz7lOytFi574K4jSIW2bp7DA+Qx3ElpGA/b6PprnK8gybOKamqE3yfUX/Wq/ngkT52PU+pMF+oVKVU4M0H4gRqHX+LxvZA0sT+JoUA+dTjIfaRfFjKE0QGyucE3Tjj3tqQBzdbgEhD46203f0sl359Ad2srMOpyzcNJ3FPq+HTnCkABPl5o6RS2ODmwb6t8bcB7TCoYxhUSgWSJvbDrC2nwCfVcdrQGPh4mb+HH9M7Cs/9EYOPD+YK2l5LQvy8MDkxBiqlAvfEReJYbjEKyqsdzpck1lHPjQAGxoTKbtbH3mzrVZ7lPFugObB2HtPpGdJyivC9jc/QXX18MBdLdmUhLacIACyuxExcR+OlxJi4SIefz312Tw+OEaZBjezIvIbH1/5sqOI7pndrrJrQ32Z7nhsWgwVjYq1ut2BMLJIm9kOov/H5OypIg+eGCftebo8JMwQw3IyyB/q2QUKnMApsREDBjYfakXnV6tAU5TpIq7JWj1X7z5s83nh9m8/SLknQMtfYcPSSoew8ALMrMRPXqanX41pplcPPD/pzuHHW8M6IaCFOLkvjnMIxvaOsBh8MQL/2/NbdG9O7NY4vHIkt0wZh5WN9sWXaIPz00l3YeuIPgVre4MDvN2iJBRei4EYAx3KLBe+KdRY3G8cSynWQ3oYjeUYBKFcxtTn1qHEXLABYNNb6XTYRDwOQeaXUqX1wU8ArasWZPdo4p7CqVoevT161uK0C9lX7bdqTclyEc3pNvd5o4VgiLgpuBCDXXpB8K3diclg6orkrqforAJVjxVRX4N7v4l2/4vVvKQfMXZVU1uE/+87h+U0ZuFUj/PIEHC6ncODbqVZr6Dhb7TftonjL0tASC65BwY0A5NoLYu3Lzy0dQaTFBcbNOQeKAcgvq/HImj7NydpDuS4Lzsur+VXsdvzGU7zbPlpiwTUouBGAXHtBQm1MJR4dF4XVT/R3qHYEEQYXGMu1948QvuS4RIijN57WZpoKgb7v4qPgRgByWEDTHD5T1EfGRkJtYaokEVdUo2qkcu39I8QdKWD8/bLXoI5hos6ADff3vBpWckNXNYHopVuBwSy+X+xjucW4KbNk6OZiXJ+/1paSa+8fIe6IwblqvyqlAu881EvYRjVGX3TRUXAjgOTT1zBrizwW/1P8+cP3i03do9L56sQfhhWLG+dA0XmPEOcEqL0wMtbxuj1Aw7D9R0/0N+kBjwxUY86ILngmsQMC1I7VwS28VeNU24htVKHYSSlZWszYfErqZhhE2rl4JnWPSudmZR0GLd2Htx+Mw+i4KEMO1JLd2c0muVipAK9Ks4TY41ZNvc0q7Y3p9MxsxeDRcVEYGWu+mrBOz5B8RuvQ7DAahhYfBTdO0OkZ5m8/I3UzEObvg1fG9kBkkK/dZbz1jK4sUiquqMXzmzIM68o0PZkWlFXjreTfpG6mYBRoGDJ4JrED2gT74o09Z6VuEvFQfHulU7K0JjcUUY1uErkaOI3p9Awbj+Qiv8z+HpjIQDWt/O0CNCzlhPSLRbIo3ldUUYvIIF+Hynj/TFMSZaFx7YvGBcWeGdJRdkt7OIOhIcD5LitfVqsyE8/Dp3fEUuFMbWk1pm/KwBu7f0VaTpFJsc0hy/Y7HJhX1+uR6qFLq8gJBTdO4NbGkQPHc2eo50Zq1gqOiZ7YKAHu/RbeslyHiRBnKBXAzQrrvSp8CmeuO5JnWCYkJUsrSBXx0so6wzISRDwU3DhFPoFBYXkNdmZeNbnLsCWhY7iIrSL2sBSg/pXYaJwfFRmoxlMJ0a5omihWHbiAADXVWCLC0zNg5uZTVgMIewpncsuEzN9+xumzfuNlJKhSsXgo58YJCR3DsepAjtTNgAIw6iKNsiOpeFCnMASoVbhVI78CXM2NtW70kbGRaKH2/rMsfMOw1aCOYVh/ONd1DRRYaZX0Q7rEsy3ZnY2RsZFmh+vt6e3mQhCh0hAa99aKXTCwuaKeGycM6iRuoSe+msb+jVfPtUWlVODRAe3EaRjhxVbBMW6M//F1P2PVgRysOnAB//z6F6Rm56OkkoZ2iHyECHQ+DPb1xn29o6BxosCorfWl5DBjiUpxiIeCGyfINR/C3m7P4d0jxG0QsYi7n7RUl8jSGD8XwObcuOWCVhJi2/29I3HilZH46In+iApyLnAorarDntNa3N7R+VlFlgIIORTOlEOA5akouHESlw8R0UJeMz/sWRU3XcQVcIl1kUEawzTwpqwlPHKPHb5Anx2Rh92n85GanY/RcVE4PG84tkwbhOWP9MHf+rexe4kX7vg+dbnE6XZZCiCkLpzpzPIQxDYKbgQwOi4KHzzaT+pmmGWr21OnZ1jjxnkb7mrSoPbYMm0QDs8bbjE3ylbCIwM8Jldqzogu8KcFXN0e11usUiowMCYUkUG+GNq1JT55Ih5qL/tCCAagrLre4cCDz/pSXOHMSB49TQoIN+wGAHFtAh1eHoLYRgnFApFrOW1b3Z7HcotRXSezhbGagT1n8pHYOdzqya25jMcrFcCzwzrh44PSJ+cT53C9xaVVtYJV2nZkPpGt4d7GGhfOTM3Ox/ojeYZik033t/ShXvg9vxzL9553oFXG9p0tQG29Hj60cLEo6K8qELmNnfJdFbe5XEDl5uaflYmtJX3L7ZgSi54Bm3++hMpaCrI9wWdpuZjuZC0YZwX5emP2iC6815fiCme+en/PhrILTXpyGg8fzxrexWS9KUfoGfB5Wp7T+yHmUc+NQLjktPzSatlUv+Fz19JcLqByw1XqtTZVVY7HlFguFVdK3QQikO+yrkv22lyPS0lVHZbvPY8vj1+xa609ABbXkwIaCrcWlFdjwsD2WL73nNPtpeNePBTcCIRLTnt+kzxWB392WAyvLzR3AW0uCzXKia1aF42Pqabd5J4mOtRP6iYQD2CpLIalpH1Lmq4nZW79KSUAZ/sa6bgXDw1LCYhLTnN2GqQQdv2i5TUNvPGMASINa0OD9iQ8uiNu+HTi7dGCJmsSAghTDdhSOQZnAxulApiU0MHJvRBLqOdGYCNjI+Hv44XpX5xEhYQzWeypfjkyNhIqBaDz5K4BGbM1NNi0mzw8QI1/fJXp0IrEcsPQMGtk+L9/xE0ZLEJLPI8z1YD5rD/lqGlDYyiZWEQU3AjIXNellPgmCx/LLabARiIKBVBUbjtIadpN/kDf1vj4oGdM4U/NLpC6CcQBvt5KDOwQilB/H+zIvCZ1c2zicz7U6ZlRro1ezwQ/nysUwLNDY7BgDPWYi4mCG4FwXZdyihH4JgvTjCnpMAbM+vIUzlwr4X2yS8nSekxgQ9xXVZ0eP513nyKSts6H5m5Og32FHyp9/2998HB8W8H3S4xRn5gAxOy6dATfaeCc8AC17Y2IqD4+mIvk09bvfnV6hiPnCzH3q19c1CpC3B+f82FKltbs9PUSERZ3bR3sK/g+iSnquRGArUqyrmRP8SpOPRXxk4VXdmbhnrgoi2tMLd6VjfwyeRxnhLgDPudDnZ5h/vYzLmkPLbngOtRzIwA5DetYW6vIkh2/XBWxRYSv4oo6s2uBcXeVFNgQYh8+58NV+y+gxEXJ7OP6mL95IcKTPLhJSkpCTEwMNBoN4uPjcejQIYvbbt++HSNHjkTLli0RGBiIhIQEfP/99y5srXlyKIQ3667ONtcqsuRWNc1SkYumgbIr7yoJEcKsuzphSmIHyab2z7qrM1Y+1pfX+VCnZ9hwhF/+WtP8Gz8f+y+fHx/MxbeZdDPpCpIOS23duhWzZ89GUlISEhMT8fHHH+Pee+9FdnY22rdvb7L9wYMHMXLkSLz99tsIDg7Ghg0bcP/99+Pnn39Gv37SLVwph0qyXSIC7J7maKCgOwm5aBoop18sctldJSFCSOzcEgmdwjC8ewQeX/ezy1/fW6XAA33b8Nr2WG4x77yaDx/vD6VCYVS1+LvT1zDry0y72jfry0z8crUUC8fSbCkxSdpz88EHH2DKlCmYOnUqevTogRUrVqBdu3ZYvXq12e1XrFiBl19+Gbfddhu6dOmCt99+G126dMHu3btd3HJjciiE50zvUUQLSiiWA3Pj8Wk5RRK1xjVoJXDPolQANysaShtINVy/5dhl3gX79mbn89rO30eFQR3DkNApDA/0bYOETmFQKRW4r28bJE3sZ/fK5WsO5WJpcradzyL2kCy4qa2txcmTJzFq1Cijx0eNGoWjR4/y2oder0d5eTlCQ6VP0OIqyQaoXX+ydjZJTUljwJJTwFLSo1zm4AkvxM8LQ7uES90MIiA9A2ZuPoWULC2KK2olaUN+WY3Z3LWmUrK0WHckj9c+K2p1SLUQCN0TFwVfB4L0NYdyUVtPkznEIllwU1hYCJ1Oh4iICKPHIyIikJ/PL5r+97//jYqKCjzyyCMWt6mpqUFZWZnRj1hGx0Xh6cQY0fZviT0zo8zp2y5EwNYQe0VZSXpM6Oi5F/+Synqk/CrdIotEPEt2ZyPEz4f39nd1ayno69vqNeLKd9jD0hIOq/afR2Wt/dXoaVVwcUk+FVzRJN+DMWbymDlbtmzB4sWLsXPnTrRq1cridkuXLsWSJUucbicfOj3D1yf+cMlrAQ1dpY/d1g5Bvj7Q6RlUSoVJhc2BMaE2Ax+quyCNWXd1QmLnllY/o0GdwhDs5+2ReTee2yfVvHHLHdys5N9z89O5G5g2NAbbMq4K0uNja5jekfId5pZwaEhIznOkiQBoVXAxSRbchIeHQ6VSmfTSFBQUmPTmNLV161ZMmTIFX3/9NUaMGGF12wULFmDu3LmGf5eVlaFdu3aON9yKY7nFLp2uW1Grw7ojeVh3JA9RQRqM6xOFXb9ojb60UUEavHZ/rNUZAwNjQuGjUqCW1mBwmWA/b8wZ2c1m4KlSKvDOQ70wXSarzRPCV1FFLYJ9vXkl7OpZwzDN5MHR2Hj0klOvq1QA8dHWe6MdzQdKzc43Cm7sSUg2h1YFF49kw1I+Pj6Ij49Hamqq0eOpqakYPHiwxedt2bIFkydPxubNmzF27Fibr6NWqxEYGGj0IxYp691oS6vx8cFck7uR/NJqPL8pAylZWovP1ekZBTYu9vTgGN5DiaPjovDRE/0RGWic+E2raBM5S/oxx+4L/zcnnZ8mrWfAyUs3rW7j6ASMnZnXoNMz6PQMaTlF+M7KeZWPibdHO/V8Ypmkw1Jz587FpEmTMGDAACQkJOCTTz7B5cuXMX36dAANvS5Xr17FZ599BqAhsHnyySexcuVKDBo0yNDr4+vri6CgIMneB0cO9W6aYmhIVl2yO7th9W8zF1S+dR6IMPzVKswa3tmu5zRdGbxVCw3q6/WYtOGYSK10rUExoUjnkQRKPNutmnpB9mPrRnNgTCjvXqXGiipqsWr/BXx5/LIgVekzr5Q4XsKDWCXpVPBHH30UK1aswOuvv46+ffvi4MGDSE5ORnR0QzSr1Wpx+fJlw/Yff/wx6uvrMXPmTERFRRl+XnzxRaneghGu3o3c5h5xY+CWZhD88Cu/BG4iDC+lwuLMC2u4lcG5qajFVdLMRhGSAg1DdBTYECEVltdYnQ6uUirwdGIHh/a9fO85wZbbkVN1e0+jYIw1q/GIsrIyBAUFobS0VJQhKm51cEB+CZMrH+trtrjVqOU/4tz1Cgla1Dxxwa+9y2Q0lZZThAlr0oVplIQ8NWGaSMtWvqFOzxD/Zqqkx94XU29HYmfPnREpNHuu35Ivv+BpuHo3kUHyG6KyNGzWPUK8PCRiigt6LU0t5WtgTCgiWvCfbiuVhWN6YNrQGDQdEVUqgPt6R1FgQ0RhK9+QS9aXlNzugD0IBTciGB0XhcPzhuOLKbebnNCloID1Qn9xbaTPV2pubA0V8qFSKjCOZ5l5KWlLq7D2UC6axnGMAd+edi4hkxBL+NxEcMn6wRIl5xf+Wc2ZCE/yOjeeSqVUILFLOALUKpRV21/gSShcbGWt0F9LWn5BMs6MuadkabHmkPyTwf+Xec3sDSrdtBKxNb6JsJS4yyXrp18sQlpOEXJulOPn3JsuqbAsx0konoKCGxHp9AxVDlSudEbT/IVIHnVuIoOoiJ9UHD25OVJhVQqh/t6SleEn/Cng2cGmrZsIlVKBxM7hhvyX2no94t9MRXm1MLO3zAn193Zq2RxiHQU3IjqWW4w6Fy4dogDg663Ch1P6o7CihneF4vjoEI8/ucmRMyc3RyqsSqFfu2Ds++2G1M0gNkQEqhEVpMapK+ItTyMle28iTl66KWpgAwBvPhDn1LI5xDoKbkTk6ml+XBesUqkwOyvKkpOXblJgI4EH+rQ2ObnxXT7DXaaQ8g1s/NUqVNRIN3zbHIX4eeGhfm0R6OuDLccuCx7YLBrbA5eKK/FZmnMVh53lyMLCrvh+0YLF4qLgRkTh/tLkstj7xXSXC6WnaRtiXHo9JUuLJbuzeS2f4S5j9QoACgVMkokb/z4ySINFY3tgxuZTrmxas1dSWc97VWx7cJ/p5MQYHMstljy4cWRhYbG/X7YKqxLn0WwpMUl0zNr7xQwPoIRiKYT6/zWNm6uPxHf5DLkWjGyK4a/ApmlbGye7j+ndGh890R9RMiyh4KnE6q1l+CuguFlRI9mM0WA/b3zkYC0p7vslFiFmSxLrKLgRUeEt10/zC/GzP49DT+tKSYJL5OaSg63NKGo6nVWlVOC1+2PFb6SAFE0ucpFBGqNChqPjorBobKwsyicQx4X4eWNkbCRSsrSYufmUxV47sQT7eWPOiK44+cpIh4tkqpQKjOvjeIFNvjyp15xbb2tn5lWk5RQ5VcNLCDQsJSIphg5uVtYhNTvfri/1z3lFIraImKNotHKxreRgS9NZuYKRL31zWvTkRyFw57opiR0wIjbSJJ8o+bQWMzbT6ufu7mZlHdIvFmHxrl9dnst3b1wkVk3s7/RQj07PsOsX8Wswucvwsi32DKm7CvXciICLYK/drJRk2MD+yrd0q+xqrNHKxXzv3sxtNzouCg/0bS1o28S27dRV6Jscn8mnr2HWFgpsPMW7Kb8hv8z1PdcHfisQZD+umI3o56PyiKng9g6puwr13AjMXATraraKVjWV0CkMqw5cELlVpCkuWOF792Zpu2oX11JyVkllHR5f97Phzg4AJRN7mF/+KJXkdavr9fjPvnOYM7KbU/txyWwpD7intDWkLmXiNPXcCMhSBCsFe76cgzqGwYuOBJfjghVbycGNl89oOq5dW69HcpZ7ruqeX1qN6ZsyMH/7GambQjzIRz9ddDrfwxXDRbdqdG6fUGzPkLqrUc+NQKxFsFKw58upUirQt20wTlwuEa9BxEjj2htccvDzmzJMiik2nlGUmp1v0isY7OuFSjfrueFw75MWziRCqqnXIz2nCIldHF9tm7vhyC+tFvWc7u4Jxc4MqYuN7tcFIqeKsY4UrSqvoQuMqyhgWnvD0mry3IwiAGZ7BUuq5J9ITMQzMraVRwxvCC3tYqFTz288G1HMP6+7JxQ7O6QuJuq5EYhcInBzF05bdHqGnIIK8RpFDML8ffDGA3FmZxBwC/g1rVAMAEOW7ZdNryCRj6yrZfh1yWhs/vkSLhVXol2ILz48kIOSKnFuVhI7heFIjjvMrnQ+JOFuOMTKoXTkJlRubPVwcQUdpXifFNwIRA4RuKNT747lFqOerpwuUVRRizf2ZEOphNnPSaVUmCSCp+UUyaZXkMiLtrQamVdKMGVoRwANeX9iBTb+ahWm39HJLYIbvpMpbGl8w7E3O1/Qis6OVE6WG75D6lK8TxqWEsjAmFAE+3lL8tpBvl74YsrtODxvuEM1BeTS69Rc2DtFkj4fYg13fIi9UnxFjQ7l1fWSnef4CvbzxqCOwgQ3QMMFfGBMqKCJ+3NGdJGs/ovQbA2pS/U+qefGA5RW1UOpVDgcHYf6+djeiAjG3imScugVJPJ1/no50nKKoGdM1B4+BYA39mTj7fFxsp+6b28hU1uEzKmMCtJg1vAuguxLLiwNqUvZM0XBjUCO5RZLOuvD0bv7lCwtFmw/LXBriC2Wqg6bw2dc28dLiZp6vRhNJTK36kAOVh3IQbCvuD0q3DG7/7cC+PmoTGbpNR2WkEppZR2e35QhaK+BkL2ni8a6/3CUOeaG1KVEw1ICkXrowJG7e64uz81KmnEjFT7HjbWZG9wFxctNTpYBarqfEotYuTZNfZNx1Wz5ATkENoDl9dgcwdWVOn/9lvMN+9Mbe7Ilq9rbnFBwIxAphw5C/b2RX1Zt12JlcqvL01zxPW6sjWvPvrszKtyk1o23qiEIc49QjLgrIYrHpWRpMWTZfkxYky5oBXeplyVoLug2SiDc0IEUs1qKK+owZ2smAP4zpuRUl8dd+XorUVXn2FCQI1MkLY1rL08951AbpHCzsg5zRnTBl8ev0PHnAH+1ChU17hHIyoEzw/XPb8oQ5eZP6mUJmgvquRGISqnAuD7SZ7/zvSuQehjNEzgT2ACOTZHkxrUf6NsGCZ3CoFIqwJh79b+VVtXhp5fuQqg/JbLbq2urAKmb4FYc6VF3Ra+2lMsSNBcU3AhEp2fY9Yv03Yx8x5tpBo6wFE1iFGsxS5CfN2aP6IqRsZGCvLbcp+Y2tTPzGo7nFqO4olbqprids/nlUjfBLTRej81eruzVpptM8dCwlEDkNMzDZyaOlMNonqhx50movw9ev78nwlqoUVBejfAANY7lFuHTo5dQUlWHkso6LN97Dl8ev+xQ0cWmwvzVTrbetYoqap0uj99cVTvYW9icOFs8zpUBB91kiod6bgQixwjcWpvkMozmiYoravF/X55CaVUtHujbBuXVdfjPvgsms1mESiw8muN+gULODVrug4jD2eJxrgo4FADio0Nc8lrNEfXcCESOEbi1Nun0DFtP/OHC1jQ/S3ZnY3j3CIvj90IkFqZkafFNxlVnm+pyh84XIDJQg/wy+d0UuCulAhjdMwLJWdelboroQvy8cXf3CPipVWgX4ofuES1QXFUrSPE4V60IzgCcvHRTVrVhPAn13AiE+0K4Ku/dR2X5lfiMN6dfLJK06KCn44YGPz2aa3Xoz5nEQp2eYe5XvzjeSAndqtHjVg3VVxKSngE/nZe2F48790QGijtUqtczfJPxBz5Lu4S3ks/i5e2nofZSGpLsndG4rpTY5Njj7ykouBGItUJrYqjVWb6nYLA93pzmBovfeYLle8/z2s6Rk9zRC4Vmi6m5Cy64aZqMTRwnh2nir90fi8Xjeor6GqXVxoGx0LVjRsdF4dlhMYLsyxo59vh7CgpuBGSp0JrQbN2YBPt585iJ417Th90V3+DDkZPctgz3H1ZUAAjS0Oi4p7i7RysE+fqgpl6PF+/uYvNcJRT2548QVYkB+2a/KtCweHGInbMWw/x9HJrNRfihs4rAuEJr6TlF+OLnPPx0vlDwuylb392SyjqbaxYldAzHqgM5graL2M+RYn6cylr3H9ZhAEqq6qmwnwCcKSoplL1nC7D3bIHh334+SlTWuq5NfNdrs8We2a8MDYsX2+uBvq2pgJ+IqOdGBKnZ+fjnN78gOeu6IbDx91G5tA22hjkGdQpzu/oonsrRKau3dfCcRMQO4f64rzfN3nNGVZ0ewX7eslrawpWBDUeIJHW+w8RBvl4On0fv7h7h0PMIPxTcCIwr29006nf12j+2hjlUSgXeeaiXi1pDzAn29XZqyupTgzt4TL5K7o0KrDmUK3Uz3F6dTt/sB5yLb9U4vQ++w8Sz7uri+MQMD/nuypXkwU1SUhJiYmKg0WgQHx+PQ4cOWdxWq9Vi4sSJ6NatG5RKJWbPnu26hvIgh8Uo7anMOTouCh890R8RLdyrCJyn+PBxxwMbAPDxUuLu7i0FbJHrKQBEBqqx9jAFNkKoqNHB30fy07qkhFjWw9bsV+48Gx7g+GsVChCEEcsk/RZs3boVs2fPxsKFC3Hq1CkMHToU9957Ly5fvmx2+5qaGrRs2RILFy5Enz59XNxa26SuUuxoZU5Puft3F9yJcVBH54aVkk9rsf+3G8I0SkKP3daOpoULqEKCoSA5aRXo/IQOa7NfG59nI4N8HX4NmiklLkmDmw8++ABTpkzB1KlT0aNHD6xYsQLt2rXD6tWrzW7foUMHrFy5Ek8++SSCgoJc3FrbpK5ZEOTrjdkjuvBes4gbQssvozsIV3G2NDwnJUuLGZszbCaXy5lSAXw4sR9+v35L6qYQTyLQd8LS7NfGFZC5Hh57OLPuFeFPstlStbW1OHnyJObPn2/0+KhRo3D06FHBXqempgY1NX9dvMvKygTbd1PhAdIO75RU1WH53vP48vgVm2sWyWEIrTlQKoxnt0UGafDYbe1RU69HWk6RQ9VUuc/O3ekZEOTng4Pn3L/3ichHYYVwN2vc7NdjucUoKK82qYDM9fBM35Rh136dvbmRK52eWfxbuZpkwU1hYSF0Oh0iIowzxiMiIpCfny/Y6yxduhRLliwRbH9WySRS0P5Z0MpasqrUQ2jNxX8e7YuwFhoUlFcjr7ACW45dxvK95wy/jwrS2L14pid9dmk5RS5PtvdkCsjmNCSZcIEXklUpFUZTy3V6hrScIsMFfGRsJJIm9sfMzRm8/vZBvp5ZgSUlS4slu7ONzk2OnN+EInnmmaJJwgdjzOQxZyxYsAClpaWGnytXrgi276aEvGNwlq2CVlIPoTUXYS00SOgUBrWXEiv2njcZAnSksqpnfXbN/VIsLPprAtnaMuzMvIq0nCJBCvo1lpKlxZBl+zFhTTpe/DITE9ak47a39uKTQznwsrIkTmMlVfWYLmA1ZTmwNEtY6MrR9pAsuAkPD4dKpTLppSkoKDDpzXGGWq1GYGCg0Y9Y5JYgZm3NIrm11VMVlFdbHQLkHrOnsqqnfHah/t5I6BgudTM8QmSgGs8kdpC6GbLwVvJZQ+AxZNl+wS6sli7gxRW1yLxSijorS+KYM3/7GcGDLykIfX4TimTBjY+PD+Lj45Gammr0eGpqKgYPHixRq5zj6sUz+bB0ly/HtnqiVi00NoeR7F0801M+uzcfiMOgTmGCTN1tzkL9vXHw5eG8JxI0J0L1HIiRo1hSWYd0D1jjT+jzm1AkHZaaO3cu1q5di/Xr1+Ps2bOYM2cOLl++jOnTpwNoGFJ68sknjZ6TmZmJzMxM3Lp1Czdu3EBmZiays+WRXOnqxTP5sHSX78qVb92Fv1qFaUM7CLYeDjcjgu8wEt/tuM/One/5hndviTG9G8rPj+/bWurmuLXiijqcvHSTV9Ab6u+N+fd0c1nbpCZUz4FYeW5pF6VdxV0IQp/fhCJpcPPoo49ixYoVeP3119G3b18cPHgQycnJiI6OBtBQtK9pzZt+/fqhX79+OHnyJDZv3ox+/fphzJgxUjTfLEvTB0P8vF2eSBag9rI63XB0XBT++1g/F7ZI3ipqdFhzKE+w6dU9olrgWG4x7wRHe4abRsdFufUwxLShnQz/Tz0Ozisor7ZZm0UB4O/xbbExLc/FrZOWED0H4l2Y5XIb7Di+5y1XD6dLnrY9Y8YMzJgxw+zvNm7caPIYY/K/Xx0dFwW9HnhlZxaKK2oBADcr61y+ltM9PSPw7elrFqfkpWRp8eruX13apuZk/283sP+3G4gM1CDYzxullXVme1scXTzz7u4RWH8kT4imulTTGh9cj4OnzACTQmF5DXZmXkWrFhp8OLEf3thz1ujvGRmkwbg+UfjkYK7Levwe7NsaOzKvuejVbHMmQBHrwuzsAp9ywH1/80urBT2/OUvy4MYTpWRpzU4LdHgNEgdty7iKbRlXAZhOyeOS4+QfKrq/62Xmv/SAc0X9jue553h9yxY+Ru+V63Gg49ExSgXwxp6zhn9HBWmwaGwsQvx9DNOV46NDcMd7B1z69y128fnOFmcCFDECcH8fldNVyuWg8fe3aSkCoYqWOkLyqeCeRq7F8Ron1sm1jZ7K2t+5cbVTe+j0DBuPXnKuYRI5/UcZ3tpjnCc3Oi4Kzw6LkahF7q3pMGp+aTVmbs5AaVUtHujbBgmdwnDy0k2X94z9JKPijM5WBBYjR/HZYR09ppAfn2rOrkY9NwKTa4E1hoYoesnubLTQeMuyjc3RorE9HPriH8stRkmVvO6M7bH2cC5euqc7fLwa7q90eoZdv3hO3Q9XUCgAc6P0jb/rI2MjoVIqkJotXGFUPppW5paaED0Ho+OiMGdEV6MinI4K8fPGrOFdnN6PnNiq5uxq1HMjMDkXWOMS69I8YPqhJ1CgYTjBkVkcaw7lCN8gF2IM+LxRYqtcbwrkzFr6IfddT79YhCPnC/HVCfGKlzbGXcbkEtgoFUDSROF6DmYN74zIQOcqICsALH2ol8f02jTGVXPmegylfI8U3AjMPQqsyeTM08w5OovDU1YDv1Rcafh/Od8UuLOZX2Tg8XU/41aNa5a4iAzSYIqMZvGtmtAPY3oLNySiUiqweFxPw+wze4X6e0s2TNPcUHAjMHcosJbQMVz2bRSLn4/8Dnl7Luw6PcMrO7NEbI3rRIf6Gf7fPW4K3I8rhi7H922NlY/1xZZpg3B43nAE+rq+KGOov/FM1KggDT56oj/G9Ba+hpKl/BI+Ft3XkwIbF6GcG4E1zhyXG25K3qBOYQ6tZOsJnh3aCSv2nbe53cIxPXC5uAKfp1+2ua2z7Fno71husaG8gDtTKoBJCR0M/7Y1nZSYCvb1RmmV+fICrhQd5o8H+rYB0DALc4UAOSn2WnRfT0QGalyW69E4v2Rvdj4+S7uEOh5jcZGBFMS7ivxuYz2AIbKX4EC2VEvH3JQ8V9fdkZq/jwqlVfwCg/AWarQP9Re5RQ2O5/EflvKU4ZtpQ2MMycSAPKt7y92QLuGSBzYA8NWJK9DpmaSzMCMDNS7P9VApFSitqsX6I3k2AxsFnJ+xRexDwY1IRsdF4cj84bi/t/jVVwd1DMXKx/pizoguFrMMg/z+Guvlaty4uu6O1CpqddjAc/r067t/xVvJZ21vKIAV+87zXvvG3YdvlArguWExWDDGdFotd1MQ1MyCbkcE+3ljz2l5zC7j8sakSAqXMmjgG8xJWeulOaNhKRGplAr8d2I8WgdnY82hXNFmEKRfLEYLjRdSswssbsMFMlTjhp+bLg78Gk/btaZvu2CLU4DlzEsJzBvdA08N7mDUY9PUyNhILN5FVbP5kNMhUFBejdNXSlz6mk2DBp2eiToNuen+9XrGK5gL9ffBWw/GUa6Ni1Fw4wILxsTiH6O641/bTyM5Kx+VtcLPXLAW2Bjasf0M1biRKe7u11o59pQsLf6144zbBTYAMPOuLnhmSIzNi82x3GLkl9W4qFXuyVupkF2va3iAGjsyr7r0NSMbVV1PydJiye5so3Nb06rszjC3/2Bffj2Mj93WDjX1eqTlFEla96W5oeDGRfb/dh3bMq5Kerd1s7IOm9Lds6ptc2Atn8bdl8tYue88vjpxxebFxlNyisTEJ3HVVbhJCmANq5OL7fk7O0KlUAJgSOgYjkGdwix+N7iq7M5Ovba0f74z0T788a+aVEIGXMQ6Cm5cQE5DQQdlVBKdGLOUTyOn48cZWh4XG3fPKWpOGg8LFVa4prdtU/pllFfXAwBWHchBZKAa1fV6s98Nc5Wa7SX0d0+ogIvYRgnFLiCn6qsVtTqE+vvQjBSZsZYUKafjRwhLdmdbrMo8MCbUpGYJkafG6wa5KijlAhtOflmN1SE6RwtlcoT+7nFHvbXvABEGBTcuILeu9vF9hS9sRZwzrk+UxTtLuR0/zrB1sVEpFXi4fxvXNorYZdZdnQwF+0bGRiItpwj5ZdWyDkod+Q7p9AxHLgjf0+1swEX4oWEpF5BbV7ufjxce7t8G32S4NgGQWLbrFy1eHt3DbIAjt+NHCKnZ+WaTp3V6hm9Pu3aRR2KfWzUNvSffZ+XjjT3ZbtGraO93yFwCsdA86aZFjii4cYGBMaEI8fN2+fRiS1YduCB1E0gT1mZLeWL13vVH8jAwJtQk78DThuA80cajl7CRZ70oqXEJz/bUwXFV8r4n3rTICQ1LuYBKqcCgjlSZklhn6U7OU6v3mss7oLtZIhRHiufV1uvxrx1ZLrmJuOmiJOzmioIbkej0DGk5RdiZeRVpOUXoGB4gdZOIzFm7k3NmsT65Mpd3QHezxFGh/sYLdjZOeOYjJUuLQUv3umzttjf2nKWkYhHRsJQIzI3XhlBJeWLDTRsn1caL9R25cAOrDuRY3d4dNO2p8cQhOOIaC+/tjtYhfg5VKJaijhSfwp3EcdRzIzDuS9I0b0Au+TZEvt7YY3t6qEqpQEKnMHSJaOGiVomraU9N4yE4Quzx6u5fcSy3CPf1bm3X4plS1pGiYVjxUHAjIFeO1xLPY8/0UHcfvrG24OHouCi8cHcX1zeKuLWKGh2W7z2PXou/x8q953kP+UiZxO7u32M5o+BGIK4erxWKAkCghkYn5YLvnRw3fOOO+CR6nrte5roGEY9SWavD8r3nEP9mKlKybK+cLlXvSYBaKclq5s0FBTcC4IaixF5bxVvgBde4vT3Yj4qmyQXfOzmVUoFxfdyzfLu/WoXZI7piZGykye90eoYj5wuxl8dCsIRYU1JZh+mbMmwGOFL1nnRqGUCLaIqIghsnuXK81tEF88L8fTBtaIzJnT43m6B9qJ8QzSNNaLzsO3EpFUB8dAivbXV6hl2/2L4rlaNbNQ131kOW7Te68KRkaTFk2X48vu5nWS0OSdybraUOBsaEIliCCR8xNINWVDQe4SR3KDpWVFGL3b9o8eht7VCv0+NaSRVah/hi8J+r6m47eUXqJnqk6nr7LtB6Bpy8dJPX7Al3OO5sabyIIAC3XvWcyJetWUmp2flW16cSS2xUoMtfszmh4MZJ7pLtnl9WjZX7zhs99uGBHEQFadAywMfCs4ir8T2e3OW4s6bxqs2MMQpsiGjMfV90eob0i0WYv+2MBC0CrpZUSvK6zQUFN05y92x3bWm12/cAeBJbx5NOz3AstxgpWZ6x/hK3iCAhYmr6vXLF2lG2bD91Fa/eH0d5NyKh4MZJ3KwVOkETZ1maGs1JPn0Nr+zMEj1xnRBPYW5tKSkK9plTXq3D8tTfkdi5pV0FBwk/lFDsJCo6RoRibmo0t4zHMxuPYcbmUxTYEGKnxt8rKQv2mbPqQA4mrEk3Sa4nzqPgRgCj46KQNLG/Ry1qSFxrzoguJmvgJJ++htveSsWENenY/9sNiVpGiHsK9vUyWVtKron42tJqXtPWCX8U3AhEqQT8fFRSN4O4oVB/b8wablyRd2lyNvXUEOKEkqp6nLp80+gxuSfi/+OrX2gxTYFQcCOAlCwtpm/KQEWtTuqmEDf0YN82RsNRyae1+PhgroQtIsQzfHwwF8mn/+oNkfsEkIpaHV788pTUzfAIkgc3SUlJiImJgUajQXx8PA4dOmR1+59++gnx8fHQaDTo2LEjPvroIxe11DydnmHxrmxJ20Dc24hGlXp1eoaXt52WsDWEeJaXt5029IbwLZIppW9Pa1Fbr5e6GW5P0uBm69atmD17NhYuXIhTp05h6NChuPfee3H58mWz2+fm5mLMmDEYOnQoTp06hX/961944YUXsG3bNhe3/C/HcouRXybvrk4iX01nSKXnFOFWTb2ELSLEs9yqqUf6xSIADUUy3cHnaXlSN8HtSRrcfPDBB5gyZQqmTp2KHj16YMWKFWjXrh1Wr15tdvuPPvoI7du3x4oVK9CjRw9MnToVzzzzDN5//30Xt/wvch/DJfLWdIZU2sVCCVtDiGdKy2kIbtzlfH2pmAr8OUuy4Ka2thYnT57EqFGjjB4fNWoUjh49avY5aWlpJtvfc889OHHiBOrqzCde1tTUoKyszOhHSHIfwyXyNWdEV5MZUqA5d4SIoGFYyl3O19G03p/TJAtuCgsLodPpEBERYfR4REQE8vPNV1/Nz883u319fT0KC83f8S5duhRBQUGGn3bt2gnzBv40MCYUkYHu8YUh8hEZqMas4Z1NHuezrhQhxD4JHcMBcOdrtcStsW1SQgepm+D2JE8oViiM71QZYyaP2dre3OOcBQsWoLS01PBz5Yqwi0SqlAosHkdF/Ag/ij9/Fo/rabYi6aCOYZKsUEyIpwr288agP28aGs7XPSVukXXPDYuBj5fkl2a3J9lfMDw8HCqVyqSXpqCgwKR3hhMZGWl2ey8vL4SFmb/jVavVCAwMNPoR2ui4KHz0RH+zFyV/B2vfCDk4ERWkwX29mw5/ELE9NywGUUHGvXqRQRqTwmKNqZQKvPNQL1c0z27Bft4mx7i141SpAKYNjcGLd5v2UBHpBGq88PTgDvhiyu2Y3Qw+m3ce6mV0I2HtfO0K1lZZeG5YDBaMoZtlIUi2tpSPjw/i4+ORmpqKBx980PB4amoqHnjgAbPPSUhIwO7du40e++GHHzBgwAB4e0t7tzs6LgojYyORfrHoz+Q1hoSO4RjUKQyp2flYvOtX5JfVWHx+ZKAaEwa2R4dwf7RqoUF8dAhOXrqJgvJqhPuroWcNK9hevVkFBgYFFGgdokFip5a4LSYUaRcKsebQRZRW16FXmyDcExuJkuo6tGqhMaxbcl9v1y0WF6RRYURsJMqr6+Dn44X2oX746sQVo7+BUgE0rlcV7OuNu3u0wq2aehy5UIhbNX/VDfL1VqJOx1BvZ4GriEA1hnQOx/nrZTibfwt1ur+erwQQ6OuFlgE+uHKzCtX1f/1OARiVaI9ooUb3qBbQM6B9qC9GdI/A1pNXsO9sgdE+gYYg4J2HemF0XBReHt0Dx3KLUVBebfRZWMOdfBfvyjaaiReo8UK/9iEY0jkMXVu1wLFLxbh2swqRQb4I9fdGeIAaeUWV+PRoLkqq+M+4ahOkQWzrQAT6euPQuRsouFVr+F2ovw/G922NkbGRhlldjd9PfHQIjucWI+1iIXR6hvLqeigUQIcwf0xK6GC4A+0RFWjyfjh+3kroGTP6+3O8lYAeCqcLm3krAR+VEhV1plNsVWj4rOUw+VapaDj2mhxSCFB7YelDvRDq74OjOYW4erMKrYM18FIqse5wrkmNLT9vJe7o1gqdWvrj9g5hUKoUKLxVY3IMJnYJR/eoQJPzQgsfJTqEB+DSzUqUWTmWooI0WDS2B0L81Sgor0aonw9OX72J/526hrKqOvioFNBDgfLqOpRVO18HLLKFN/LLTfMr/X1UAGNGn29koBqLx/U0eyNhOF/nFOGztDzs/930e2wPJf783KxsowAwdWgHzL83FkfPF+KbjD/wW34Z/NVeuKdnBJ5O7Eg9NgJSMG5cRwJbt27FpEmT8NFHHyEhIQGffPIJ1qxZg19//RXR0dFYsGABrl69is8++wxAw1TwuLg4PPfcc5g2bRrS0tIwffp0bNmyBQ8//DCv1ywrK0NQUBBKS0tF6cWxhFvNufFFgQte+F70hGxHflk1im/VINTfB+EBapy9Vobjl4tRWVOPcH812ob6YXDncAzq2NAjZq7t+aVVKLxVg+KKOmhLqwAArYMbAq5BncLMrpPE92/QdFvuwpqeU4S0i4XQMyDEzwfhLdSIDDRuU3FFLUIDGh63tU9Lv+P7+ej0zGxAK8Rnaa29fJ/HBcY/5xYBUOC2DiE4d70cV25WITrUzygAceY17Xk/5j4jAFZ/1/RvfFtMqCGo4o6FIF9v/PCrFtrSKlTW6hHT0h8JHcPw1OC/uvmtvb/aej0+PZqHY7lFqKzVoU/bYAzoEIrvs6/hWO5NeCmAdqH+iAjSQKVQIFDjDYUCCPT1RkllLbSl1WgT7ItBHcNwPK8Yaw/loLLur9Orr7cCnVq2QHl1Ler1DG1D/KBSKFBTr0e7ED88HN8Wgzs35IZwxzmgQEKnMAzqaPmY0umZXdtb+2ws/V0+T8vDpeJKtAvxQ/eIFiiuqrX7+DDejy+6RrTAsbxiQ6CW0DEcSoUCBbdqUFheg+KKGuSXVqN1iC8GN/peNd5P42PYmWOXe+61m5U4fqkYGZduok7PMCgmDKN7RqK4qg6F5TW4WVnb8JlrvFFaVQelAobvPGB8nuzbLhibf75k0k7iOHuu35IGN0BDEb93330XWq0WcXFxWL58OYYNGwYAmDx5MvLy8vDjjz8atv/pp58wZ84c/Prrr2jdujXmzZuH6dOn8349qYIbQkjzImagSEhz5FbBjatRcEMIIYS4H3uu39RHRgghhBCPQsENIYQQQjwKBTeEEEII8SgU3BBCCCHEo1BwQwghhBCPQsENIYQQQjwKBTeEEEII8SgU3BBCCCHEo1BwQwghhBCPItnCmVLhCjKXlZVJ3BJCCCGE8MVdt/ksrNDsgpvy8nIAQLt27SRuCSGEEELsVV5ejqCgIKvbNLu1pfR6Pa5du4YWLVpAoWhei9iVlZWhXbt2uHLlCq2rJSH6HOSBPgd5oM9BHtzhc2CMoby8HK1bt4ZSaT2rptn13CiVSrRt21bqZkgqMDBQtgdvc0KfgzzQ5yAP9DnIg9w/B1s9NhxKKCaEEEKIR6HghhBCCCEehYKbZkStVuO1116DWq2WuinNGn0O8kCfgzzQ5yAPnvY5NLuEYkIIIYR4Nuq5IYQQQohHoeCGEEIIIR6FghtCCCGEeBQKbgghhBDiUSi4cWNJSUmIiYmBRqNBfHw8Dh06ZHHb7du3Y+TIkWjZsiUCAwORkJCA77//3uL2X375JRQKBcaPHy9Cyz2LGJ9DSUkJZs6ciaioKGg0GvTo0QPJyclivg23J8bnsGLFCnTr1g2+vr5o164d5syZg+rqajHfhtuz53M4fPgwEhMTERYWBl9fX3Tv3h3Lly832W7btm2IjY2FWq1GbGwsduzYIeZb8AhCfw5r1qzB0KFDERISgpCQEIwYMQLHjh0T+204jhG39OWXXzJvb2+2Zs0alp2dzV588UXm7+/PLl26ZHb7F198kS1btowdO3aMnTt3ji1YsIB5e3uzjIwMk23z8vJYmzZt2NChQ9kDDzwg8jtxb2J8DjU1NWzAgAFszJgx7PDhwywvL48dOnSIZWZmuuptuR0xPodNmzYxtVrNvvjiC5abm8u+//57FhUVxWbPnu2qt+V27P0cMjIy2ObNm1lWVhbLzc1ln3/+OfPz82Mff/yxYZujR48ylUrF3n77bXb27Fn29ttvMy8vL5aenu6qt+V2xPgcJk6cyD788EN26tQpdvbsWfb000+zoKAg9scff7jqbdmFghs3NXDgQDZ9+nSjx7p3787mz5/Pex+xsbFsyZIlRo/V19ezxMREtnbtWvbUU09RcGODGJ/D6tWrWceOHVltba1g7fR0YnwOM2fOZMOHDzfaZu7cuWzIkCHONdaDCfE5PPjgg+yJJ54w/PuRRx5ho0ePNtrmnnvuYY899phzjfVgYnwOTdXX17MWLVqwTz/91OF2iomGpdxQbW0tTp48iVGjRhk9PmrUKBw9epTXPvR6PcrLyxEaGmr0+Ouvv46WLVtiypQpgrXXU4n1OezatQsJCQmYOXMmIiIiEBcXh7fffhs6nU7Q9nsKsT6HIUOG4OTJk4au94sXLyI5ORljx44VrvEeRIjP4dSpUzh69CjuuOMOw2NpaWkm+7znnnt477O5EetzaKqyshJ1dXUm1xC5aHYLZ3qCwsJC6HQ6REREGD0eERGB/Px8Xvv497//jYqKCjzyyCOGx44cOYJ169YhMzNTyOZ6LLE+h4sXL2L//v14/PHHkZycjPPnz2PmzJmor6/Hq6++Kuh78ARifQ6PPfYYbty4gSFDhoAxhvr6ejz//POYP3++oO33FM58Dm3btsWNGzdQX1+PxYsXY+rUqYbf5efnO/XZNjdifQ5NzZ8/H23atMGIESMEabfQKLhxYwqFwujfjDGTx8zZsmULFi9ejJ07d6JVq1YAgPLycjzxxBNYs2YNwsPDRWmvpxLycwAaehFatWqFTz75BCqVCvHx8bh27Rree+89Cm6sEPpz+PHHH/HWW28hKSkJt99+Oy5cuIAXX3wRUVFRWLRokeDt9xSOfA6HDh3CrVu3kJ6ejvnz56Nz586YMGGCU/ts7sT4HDjvvvsutmzZgh9//BEajUbQdguFghs3FB4eDpVKZRKFFxQUmETrTW3duhVTpkzB119/bRRx5+TkIC8vD/fff7/hMb1eDwDw8vLC77//jk6dOgn4LtyfGJ8DAERFRcHb2xsqlcrwWI8ePZCfn4/a2lr4+PgI9yY8gFifw6JFizBp0iTD3WuvXr1QUVGBZ599FgsXLoRSSaP6jTnzOcTExABo+Btfv34dixcvNlxUIyMjHdpncyXW58B5//338fbbb2Pv3r3o3bu3sI0XEH073ZCPjw/i4+ORmppq9HhqaioGDx5s8XlbtmzB5MmTsXnzZpO8ge7du+PMmTPIzMw0/IwbNw533XUXMjMz0a5dO1HeizsT43MAgMTERFy4cMEQXALAuXPnEBUVRYGNGWJ9DpWVlSYBjEqlAmuYiCFM4z2Io59DU4wx1NTUGP6dkJBgss8ffvjBrn02J2J9DgDw3nvv4Y033kBKSgoGDBggSHtFI1EiM3ESN9Vv3bp1LDs7m82ePZv5+/uzvLw8xhhj8+fPZ5MmTTJsv3nzZubl5cU+/PBDptVqDT8lJSUWX4NmS9kmxudw+fJlFhAQwGbNmsV+//139u2337JWrVqxN9980+Xvz12I8Tm89tprrEWLFmzLli3s4sWL7IcffmCdOnVijzzyiMvfn7uw93NYtWoV27VrFzt37hw7d+4cW79+PQsMDGQLFy40bHPkyBGmUqnYO++8w86ePcveeecdmgpugxifw7Jly5iPjw/75ptvjL4z5eXlLn9/fFBw48Y+/PBDFh0dzXx8fFj//v3ZTz/9ZPjdU089xe644w7Dv++44w4GwOTnqaeesrh/Cm74EeNzOHr0KLv99tuZWq1mHTt2ZG+99Rarr6930TtyT0J/DnV1dWzx4sWsU6dOTKPRsHbt2rEZM2awmzdvuu5NuSF7Pof//Oc/rGfPnszPz48FBgayfv36saSkJKbT6Yz2+fXXX7Nu3boxb29v1r17d7Zt2zZXvR23JfTnEB0dbfY789prr7nwXfGnYIz6VwkhhBDiOSjnhhBCCCEehYIbQgghhHgUCm4IIYQQ4lEouCGEEEKIR6HghhBCCCEehYIbQgghhHgUCm4IIYQQ4lEouCGEuJ3Fixejb9++hn9PnjwZ48ePd2qfQuyDECIPFNwQQgQzefJkKBQKKBQKeHt7o2PHjvjnP/+JiooKUV935cqV2LhxI69t8/LyoFAokJmZ6fA+CCHyRquCE0IENXr0aGzYsAF1dXU4dOgQpk6dioqKCqxevdpou7q6Onh7ewvymkFBQbLYByFEHqjnhhAiKLVajcjISLRr1w4TJ07E448/jv/973+GoaT169ejY8eOUKvVYIyhtLQUzz77LFq1aoXAwEAMHz4cv/zyi9E+33nnHURERKBFixaYMmUKqqurjX7fdEhJr9dj2bJl6Ny5M9RqNdq3b4+33noLABATEwMA6NevHxQKBe68806z+6ipqcELL7yAVq1aQaPRYMiQITh+/Ljh9z/++CMUCgX27duHAQMGwM/PD4MHD8bvv/8u4F+TEOIICm4IIaLy9fVFXV0dAODChQv46quvsG3bNsOw0NixY5Gfn4/k5GScPHkS/fv3x913343i4mIAwFdffYXXXnsNb731Fk6cOIGoqCgkJSVZfc0FCxZg2bJlWLRoEbKzs7F582ZEREQAAI4dOwYA2Lt3L7RaLbZv3252Hy+//DK2bduGTz/9FBkZGejcuTPuueceQ7s4CxcuxL///W+cOHECXl5eeOaZZxz+WxFCBCLxwp2EEA/SdCX5n3/+mYWFhbFHHnmEvfbaa8zb25sVFBQYfr9v3z4WGBjIqqurjfbTqVMn9vHHHzPGGEtISGDTp083+v3tt9/O+vTpY/Z1y8rKmFqtZmvWrDHbxtzcXAaAnTp1ymLbb926xby9vdkXX3xh+H1tbS1r3bo1e/fddxljjB04cIABYHv37jVss2fPHgaAVVVVWf4jEUJ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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.eval()\n", "with torch.no_grad():\n", " y_pred = model(X_test)\n", " after_train = criterion(y_pred.squeeze(), y_test) \n", " print('Test loss after Training' , after_train.item())\n", "\n", " y_pred = y_pred.detach().numpy().squeeze()\n", " slope, intercept, r_value, p_value, std_err = scipy.stats.linregress(y_pred, y_test)\n", "\n", " fig,ax=plt.subplots()\n", " ax.scatter(y_pred, y_test)\n", " ax.set_xlabel('Prediction')\n", " ax.set_ylabel('True')\n", " ax.set_title('slope: {:.3f}, r_value: {:.3f}'.format(slope, r_value))" ] }, { "cell_type": "markdown", "id": "00aa6061-6b38-4f96-9ad8-018135d57a90", "metadata": {}, "source": [ "**Question 3**: As we can see, the Perceptron didn't perform well with the setup described above. Based on what we have discussed so far, what is wrong with our setup (model and data) and how can we make it better? " ] }, { "cell_type": "code", "execution_count": null, "id": "097c3d68-f635-4df7-9202-b05d1010a7b8", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.6" } }, "nbformat": 4, "nbformat_minor": 5 }