From bb9d335483233696c0a1062dac11cf1d248b463b Mon Sep 17 00:00:00 2001 From: Haris Mahmood Date: Wed, 26 Jun 2024 01:59:10 +0500 Subject: [PATCH] chore: Update the resnet demo notebook --- examples_and_demos/resnet_to_tensorflow.ipynb | 2199 +++++++++-------- 1 file changed, 1231 insertions(+), 968 deletions(-) diff --git a/examples_and_demos/resnet_to_tensorflow.ipynb b/examples_and_demos/resnet_to_tensorflow.ipynb index 50271a34..5de95cf0 100644 --- a/examples_and_demos/resnet_to_tensorflow.ipynb +++ b/examples_and_demos/resnet_to_tensorflow.ipynb @@ -1,997 +1,1260 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Training PyTorch ResNet in your TensorFlow Projects" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Installation\n", - "\n", - "Since we want the packages to be available after installing, after running the first cell, the notebook will automatically restart.\n", - "\n", - "You can then do Runtime -> Run all after the notebook has restarted, to run all of the cells.\n", - "\n", - "Make sure you run this demo with GPU enabled!" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!pip install -q ivy\n", - "\n", - "!python3 -m pip install torchvision\n", - "!python3 -m pip install astor\n", - "\n", - "exit()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Framework Incompatibility\n", - "Practitioners with large codebases written in other frameworks, such as PyTorch, are unable to take advantage of TensorFlow's rich ecosystem of state-of-the-art (SOTA) deployment toolings, as this requires converting their code manually and inaccurately.\n", - "\n", - "[Ivy’s transpiler](https://unify.ai/blog/unifying-with-ivy) allows ML practitioners to dynamically connect libraries, layers and models from different frameworks together. For PyTorch users, the transpiler provides a seamless and accurate way to introduce code written in PyTorch to TensorFlow pipelines.\n", - "\n", - "In this blog post, we’ll go through an example of how the transpiler can be used to convert a model from PyTorch to TensorFlow and train the converted model in TensorFlow." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Transpiling a PyTorch model to TensorFlow\n", - "\n", - "#### About the transpiled model\n", - "To illustrate a typical transpilation workflow, we’ll be converting a pre-trained ResNet model from PyTorch to TensorFlow, and using the transpiled model to run inference.\n", - "\n", - "ResNet owes its name to its residual blocks with skip connections that enable the model to be extremely deep. Even though including skip connections is a common idea in the community now, it was a revolutionary architectural choice and allowed ResNet to reach up to 152 layers with no vanishing or exploding gradient problems during training.\n", - "\n", - "Architecturally, a ResNet block is similar to a ConvNext block but differs in terms of the specific convolutional layers used, grouped convolution, normalization, activation function, and downsampling. Going through the details of the models is outside the scope of this demo, interested readers might want to go through the [paper](https://arxiv.org/pdf/1512.03385)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Setting-up the source model\n", - "\n", - "We import the necessary libraries. We’ll mostly use the PyTorch's Torchvision API to load the model, Ivy to transpile it from PyTorch to TensorFlow, and TensorFlow functions to fine-tune the transpiled model." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ + "cells": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-06-25 12:04:11.200351: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n", - "2024-06-25 12:04:11.225145: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", - "To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" - ] - } - ], - "source": [ - "import warnings\n", - "warnings.filterwarnings(\"ignore\")\n", - "import logging\n", - "import tensorflow as tf\n", - "try:\n", - " tf.config.experimental.set_memory_growth(\n", - " tf.config.list_physical_devices(\"GPU\")[0], True\n", - " )\n", - "except:\n", - " pass\n", - "\n", - "# Filter TensorFlow info and warning messages\n", - "tf.get_logger().setLevel(logging.ERROR)\n", - "import os\n", - "import ivy\n", - "ivy.set_default_device(\"gpu:0\")\n", - "import torch\n", - "import torchvision\n", - "from torchvision import datasets, models, transforms\n", - "\n", - "torch.manual_seed(0)\n", - "tf.random.set_seed(0)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Load the Data\n", - "\n", - "We will use torchvision and torch.utils.data packages for loading the data.\n", - "\n", - "The problem we’re going to solve today is to train a model to classify ants and bees. We have about 120 training images each for ants and bees. There are 75 validation images for each class. Usually, this is a very small dataset to generalize upon, if trained from scratch. Since we are using transfer learning, we should be able to generalize reasonably well.\n", - "\n", - "This dataset is a very small subset of imagenet." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "> **Note:** Download the data from [here](https://download.pytorch.org/tutorial/hymenoptera_data.zip) and extract it to the current directory by running the following cell" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import requests\n", - "import os\n", - "import zipfile\n", - "\n", - "# URL of the zip file you want to download\n", - "url = 'https://download.pytorch.org/tutorial/hymenoptera_data.zip' # Replace with your URL\n", - "\n", - "# Send a GET request to the URL\n", - "response = requests.get(url)\n", - "\n", - "# Check if the request was successful (status code 200)\n", - "if response.status_code == 200:\n", - " # Get the file name from the URL\n", - " filename = os.path.basename(url)\n", - " \n", - " # Specify where you want to save the zip file (current working directory in Colab)\n", - " zip_save_path = os.path.join(os.getcwd(), filename)\n", - " \n", - " # Write the content to the zip file\n", - " with open(zip_save_path, 'wb') as f:\n", - " f.write(response.content)\n", - " \n", - " print(f\"Zip file downloaded successfully as '{filename}' in the current working directory.\")\n", - " \n", - " # Extract the contents of the zip file\n", - " with zipfile.ZipFile(zip_save_path, 'r') as zip_ref:\n", - " zip_ref.extractall(os.getcwd())\n", - " \n", - " print(\"Zip file contents extracted successfully.\")\n", - " \n", - " # Optionally, you can remove the zip file after extraction\n", - " os.remove(zip_save_path)\n", - " print(f\"Zip file '{filename}' deleted.\")\n", - " \n", - "else:\n", - " print(f\"Failed to download zip file from '{url}'. Status code: {response.status_code}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# Data augmentation and normalization for training\n", - "# Just normalization for validation\n", - "data_transforms = {\n", - " 'train': transforms.Compose([\n", - " transforms.RandomResizedCrop(224),\n", - " transforms.RandomHorizontalFlip(),\n", - " transforms.ToTensor(),\n", - " transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n", - " ]),\n", - " 'val': transforms.Compose([\n", - " transforms.Resize(256),\n", - " transforms.CenterCrop(224),\n", - " transforms.ToTensor(),\n", - " transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n", - " ]),\n", - "}\n", - "\n", - "data_dir = 'data/hymenoptera_data'\n", - "\n", - "image_datasets = {\n", - " x: datasets.ImageFolder(\n", - " os.path.join(data_dir, x), data_transforms[x]\n", - " ) for x in ['train', 'val']\n", - "}\n", - "\n", - "dataloaders = {\n", - " x: torch.utils.data.DataLoader(\n", - " image_datasets[x], batch_size=4,\n", - " shuffle=True,\n", - " num_workers=4\n", - " ) for x in ['train', 'val']\n", - "}\n", - "\n", - "dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}\n", - "class_names = image_datasets['train'].classes\n", - "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Visualize a few images\n", - "\n", - "We also load an input tensor to be passed as the input for transpilation" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "metadata": { + "id": "A7JLwbmuROvJ" + }, + "source": [ + "# Training PyTorch ResNet in your TensorFlow Projects" + ] + }, { - "data": { - "image/png": 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t9lR1+3xQSvGMZzzji66+u7i4yFOf+lRe9apXsbq6ylvf+lYuvfRSXv3qVwOgteZ3f/d3ef7zn8/VV1/Nq171Kg4ePMjp06e56aabaLfbvPe97wXgl37pl7jpppu44YYbePWrX81VV13F1tYWt9xyC3/7t3/L1tYW4M/tvn37eMpTnsLevXu54447+M3f/E1e8IIXnGfYnWGGLwsemeShGWb40uOLSTP++7//e/nhH/5hWVhYkGazKd/7vd8rm5ubD1r/pptukhtvvFHm5uYkSRK55JJL5JWvfKXcfPPN56139OhRefnLXy779u2TMAzl4MGD8sIXvlDe9a53Tdf5z//5P8v1118v8/PzUqvV5IorrpA3velN56U7PxRe97rXiVJK7rjjjod1jLtx++23y7Of/WxpNpuyvLwsr371q+XWW28VQN75zndO13vFK14hjUbjQd9//etfLw98XXzkIx+R6667TqIomqYcb2xsyI/+6I/KFVdcIY1GQ+bm5uSGG26QP/mTP/ln23jdddfJvn37/sXHJiLynve8Rx7zmMdIkiRy5MgRectb3iK/93u/J4Dcf//90/U+X9rrM57xDHnGM55x3rJ3vOMdcvHFF4sxZppyfMstt8j3fM/3yIUXXihxHMuePXvkhS984YPugwei3+8LIC996Uv/xcc2STP+X//rf8nP/uzPyp49e6RWq8kLXvCC81LEJ/jUpz4l3/7t3y5LS0sSx7EcPnxYvuu7vks+8IEPnLfe6uqq/OiP/qgcOnRIwjCUffv2ybOe9Sx5+9vfPl3nd37nd+TpT3/6dFuXXHKJ/H//3/8n3W73YbV9lmY8w78GSuRfOFyZYYavULzyla/kgx/8ILfccgtBEExTQr9WcP3113P48OEHFVb7WkC/32dxcZG3vvWtDyqs9rWA973vfbzwhS/k1ltv5dGPfvQj3ZwvO7a3tynLksc//vE85jGP4S/+4i8e6SbN8FWImQdlhq8pnDx5kpWVFZ761Kc+0k35kqLX63HrrbfyC7/wC490U74s+NCHPsTBgwen4YqvNdx000289KUv/bogJ+DDdSsrKw9Zin+GGR4uZgrKDF8zuP322zlz5gzgjadPetKTHuEWzTDD1yc+9rGPTQ29KysrPPaxj32EWzTDVyNmBGWGGWaYYYYZZviKwyMa4vmt3/otjhw5QpIk3HDDDXz84x9/JJszwwwzzDDDDDN8heARIyh//Md/zE/+5E/y+te/nltuuYXHPvax3HjjjdMSyzPMMMMMM8www9cvHrEQzw033MATn/jEaQ0J5xyHDh3ix37sx/iZn/mZL/hd5xxnzpyh1Wr9sxUfZ5hhhhlmmGGGrwyICP1+nwMHDqD1F9ZIHpFCbXme88lPfpKf/dmfnS7TWvPsZz+bj370ow9aP8uy86o0nj59mquuuurfpK0zzDDDDDPMMMOXFidPnuSCCy74gus8IgRlY2MDay179+49b/nevXu58847H7T+m9/85oecmOo9P7rCoqTYQigzhcvAlmBLQQTEgUNhrSAWnIP1PODkKGZOcmqR5Y5NzVqpWDCOhhMu2qsIExg6WO8rLl+xOIFhAedGAZujhEOLJe2k4LPHHatjeNweCBLFyY6gkoh4pc3Lv8cx2hzy/r8STm5kNFvQG2tuPSHsnYP9CzDMYL0HGz1oJYrnP1nxjd8AxVhY39L85T84PndSOLgS8JLnhRgS8kGPu48JAxdz/FzBYh0So2gmgCq5d1WzstLk1HrIxmaHw/sMRy4MCGs1htslc1GfYSFsjwyL8zH9Idx9yqCdIogS2s0eSaC47X7H8mLM/FzC2oZlqzNm/x7DtVdljIoW47zGLZ/tE9cGXHzhMnfckTJMM1qNGs16SLczQumA1lxEEoRsdgYMx2NarYDFpYTVtZJ2I2EwBrElL/jmx7JSK/j9d32SlaU6taTO2fWUPM/Yt3cPz3nec7n0yuv4lV/9ZYo8QymFiGIq/4mfKG1HUZPqbwpEgfLL4PMJhl+8EqfE7+I8iN/ig5b/S7G7uWrX53/pdr/Y730p8YW02l3tuvTIQZ75jc/n6mufDiicA4XBoXBYlPZfUCicEwSL0hpctQ/tr75fw2DLEqVA6QDBIQZEwFST6zkl4ASpvmWcQsQCDq2r94gIgsMVliIryfOMcTomzcaMsjGjXsrWIGO1s854Y5PB9iZ2PECVKVoKlAhBYFD1hKjWYLHeYrE1T3OuSb0dkdQigrhOEMToIIQoIQhigqCGCSLQBgJVnUONQiPO4Y/egYCzFluWOARblpTjIUWvy2Czw9bqJr2zx1Ab9xHkG9T0mIWao1EzxEFAEggRObkIaRmQpQVplpM6Q+lCNAYwhCpGGSi0ISdgLJrCGEoDRRQBkb9SJkCiBAk11oSUpcaVJS4rcKWlLFOsaMSlXHDlpXznhd/LBeEFSFGiSn88hAbiEOohLAS4WKPTHNe1qCEoK4hYVBCgdIDToOqhfyDHJXRSpNtFtWu4VoTONSpQ0DZIoEEHUAPiahQ/Lv3NUzMoFNIrIa3uG1t1IChcPERfEsH+avZqkeoVI4jRlJ2Sk39/iqCzRTtQRFFCoJvk4wwXl6RZTufMOnv3LtE+fAjVmPeb3h6y9embKPqfo5aEWBnRuPYqonI/Rl+GUw3KE5uUakD9QIPOZ9+PyK20LlrCcQXBkavp/eMHiWtb9LbO0rzoYuILnog6cCks7UV6Kcf/77sJtz5Lqwk23SKOzqJVRBAvoWoDgkuvQPWaFHesUc4tEi9eQXpyBMVpotpxlLG4bC+4OWz+aeK5BLP4TOTw85CBITv1Ccxew/CuY1DUqe1ZJu+dohwcRwcLlAtX8v/jZt76O3/4sCoRf1WUuv/Zn/1ZfvInf3L6udfrcejQIVqjlDnpYwuwhcIVUKRgBfJCKEr/O86//UqBxCoOaMNcYKntjXj0C/dy8miX//OhjNs2Cz47gD01uOFCoWkVjcyhDBgrbBYhoVMcWR6yPRJipzlEzuGGcKKnuagFZwYpm2dK3v8u2LvouP/YmPXCcFAcRVFSjBT7Dwg1rUhqAgWsrSskVjz6YkXdBNy3GtAKBly8AHefMHQ3hVO3R6Qa7HBAqxGzuOcQa6v309Y5S21DnmtGruTZT9DUwoLPKMPxY2PMoT0cu7dkdXudvYsOs6ekm0VgWpzdNJxayxE7ZP+ekEG/5N5jOVluufqKiEYUc/exPttbY0pxnDwTcO1lkA8sd9w7oLvZpb1QcP/RNerhPLZQSJEBimZTs7mdUXZyDu5dQomAU6R5wbHjQ4oiYDjoUpSG0Ghu+dTHee7TIkLGXLQQcLZjcVlBoEKazSaNZoMoTvj0p24lS9OKamh2bFS7ej8l+N6KiiHs7pXPn9n2X4WKMOxQoof883m8Ah7MM+SBX3qojXH+UXy+fX2l4Ytp10IroTU3z/K+CwHjOYcGROFEUFpV5fCl+ulAFEoCQOHEgrIobXBWkWcZWivCMEFpEOU7QCUAQolDZOd+0VbhpERwKMBJiRLBFgVSFKSjEcPhGJGAXKAoYVhaxsMxaT8n7Y8phxkuy1AUiII4rNFImoTNBq2FNvsW5lloLtBot6m1YuJGQhTV0FGMiWJMGEMYo2mgTYRo7dsufvCFCCIOEcGKQ5wnJWJLRAlZlpJHMaUJUBaKcUm51aCQgMBC4EpMWhKhaNQV9aAk0YJzkGEZUTAqHXGmyCTABRGiIyJVopQiloTSedI1oMQohSodpSvRWqNxYDWEEVobTyCMpjQFzpagNNo6xCqiIGJf+wAXxochL6F0/toYDWEAYYCYAGkGqL0KNxDU6Qw9KnBK0IHBmQAVhWAALUgDdOKwbg3ROarRhEYdXYI0jCchykAdJMZvY1RCoVD16p4zDkYCOsRZC9ahlUOKPkoZ5MA8Klbg/FMuYrEKXMNRzqdIL6OpUupRQj1cQUxJxphuPibWjgMssWj2IvUVVBgy6hxHZ2O0GhO5PrntMF+/hCSM0MMESQ5QRBqbR9RyaJgxQdwh0X0kWIDxAkl+nPllS6/XpZFYau0E1WoiBw4zHByns7XKnqhDu1YiZpO41QGnwQ7QTUvYOkjpMobuJI25JXI34Nyxu1jeX9BodlB2jFIpRW6hfpq4tRdCoL0X6XYoogEuaHF6/TSNaIFab0QxuI96UzPOUmyrQZxF/t3wMOwZjwhBWV5exhjD6urqectXV1cfckr7OI6J4/hBy/OhkDkockVZQJYL4wxKB7kF6xTiBKX8AMQBp/saMYoDF4XsuSLgwuu6KFtw5H64c03RGQqjTDjYhDmEPIcoAZQiUJA7uOUWYZAK47LkyhVYWtCcHQqhhkuWHVv3DfjgKYXVClSJGGEUO9b6wv5lw5GDwv2nFWtdqMeWwAjbfeGuezS9juFz90YcmhuztiUEYYxyJZ1ORhJlJDFceU1BY+EE62dK7jkmnNjMeeoT6yzHTeYXHemoyUp9nYv2COsdxcGFiD0itKKc1Q2DRIsMR4pza326ac7Vl1u0qrPdH1KkDpGSUBmGI8twVBLXa+jCsd3v8b//BpZaCh3V0WGEELLWGbJvAS699AArcykf+vhZysLRbiR0x2PWu8J8u0atETJKU0bDAluUEDlsKZSlsNGB9/1dRqMdktkF5lur3H/OYcUyKjLfyzmHUZ5wBElCvT2PKIMTqV7YVB2NQ/AjYJzyD4IAyr/U1URRkUplqX7fJcfsdFjTzxVBmP4joPzLabeCMiEk/uODqckDn0mlFOctVP5eeyjFQ8nOT5muN9WJ/Hk4r9XstFPtfH/3hqe7fmDDRKbLZPL5vMkGK43qoRjYA9rtpidvZ/lkU2rX+fSbUgRJNOWYopRXNqTEicLLI6rqqC0K8WqCgEjptyWCSLVN8eFjT3AEcaCUb7fIjujiL0PV6U8PWlNa8YMfl1GWGWk6Jh2OGA3GdAdjtocj1rtdOqsbdLc26A7WKIfb6Cz1SkKSoOOIRq3NSmuR5mKLueU5FhdatJIGcdIkqtUIGxFBkGDCGB1GEISgQ0RCfK87uQH8MYgITkCcwzmLc4Jznqg4L/lgtMIahY4NQaSJ4houaiF5F+dSikKwgUJsQFkYyrBAGYuyoJRBGYM2oAuhzB02cKjYEeoArcCEhliBdZbcGVzhEKVwkfHXSXkVK8jBaMGKxgSJv3bKUbocZY2/ZkaB1l6JmNyLSkA5EIcUDpUCdYO0nFdB8hJsgRTin2mtEKvQgIQG6hHMtdGdDtIfIfMxgsKVoK0B40CqAY5z6CDA5g6Gpf+bDiEASQvU5L4CZOywqwWm75BYg7IgGqcFVWqMFZLQMS66SDRCEoMrh1grjPtbOK2ooZGhQ4YpumERNNnpo9SCTYIIsJuI2kD6x2GphRQNaF5AqQp0llGcPke9liK1HiYaINSwmz3C5kmMEcKwg7hzuOI+zGAZ7RzbJ+7DpKvE8z2SRo6LO+h2SVkIuihwkSD5MUweU2sNkcFxNk/dh9iMLC+p6z4m6SHpBkGSouoKdAvo40iRjTsJ47OM1s4gw7sx8Qous9TrqyRLe1G9mEGtgH/BnJqPCEGJoojrrruOD3zgA7zoRS8CvPH1Ax/4wD87Ydpu5CkMxpAWkBWQF5ViIlBa/2J0TqGVoEWhtSK2wnoHTiiFhIphWXD6WM5n73QYK7SN4pIWjHNFlECpIdKCLbwC2NtOSUtFaYUcxXYGiLCnpTjVEbKB0DDCgoZ7+6CM4uCiQzlIS0UtVjgc114kfO6oMMihcEJ3pLjpk45vuSFluZYS12FYCqFOWVmE4z3hCZcpxkPN6qrjquaIJz5KuP4axa//EXzwloR0lJPbjEsPKg60LJcdFG4/dY6NTp3+2JJbIQhD9s0vEoeW/tjigoJOx5FGBYqYdtuTuVOrfZSMaNdrZKVjmI4xIWCFZhIxyjMa9QhtDCvLSzTabc6ub7GxucXhQ4o8c3R7Q+o1uOCgod/tsry8hzLXFNYwHqWgc1StwJUJg23F4pzmyotCbvrEOa68LGFlruDUqRFbq35GVYfg8IJYqz3H4cc8msIEFFK9nK2jLAuUlDhXeJl+0jeK34KzFiMarcA6Nx2R4/woetJVWrFTLmKtm05gN3l5KiqiYB3KTTrzidTrX5IKxW4PulJqagoTEbRWaG38bLxK+ZFwRSYmREVV6xsBg662u9Ox+t7KL7POTQmXTI/DgdZorXcRp2mL/PLJvlBV/+6Vid0jHGcdzsdaQATnBGvtNJSya5N+31PuJNiKoMhk+6iK/+yQq0lATmtDONfE62M+gGFxOHEV6dDVhh0TNWwSmhERPyAxmom6opQiigK/rptQIPw2lQ//qWqpEjVVJXRFViwl1lmycc44GzAajRgNU3qDEYPhmPWNbVY3zzHcXGfY2WSQd9GupKGFMKwRNZrU2y2W5+bYu7DI3GKTWrtBrd6gliTUkjpBHGPiBB3EBCYGE2CVQalgKgB6QlIik7CUU9iKSIuT6tj8D2s9CQ91gJgQEwToKETXapRxHRlFBGIoUeRiyGyA0QZnNIGyKEqMsijlKI3FOlClQiuFQyGlRgcKQghKSyJgrWAQrBJKFDgwVqEKjdGgtMOvERNqBcbilHh+oACjUYGG0nhCUnrFgkChtPLkoXRIN0fNBeilGElBOgXaFlCWSBni43/Kb6sWo+druDJFetuoWo5qJJis8C+5OECVGiXanzij0UYgd1jtNyWRwvULjPNtxIhXT7ZHuLUxLDV8+1x1X59OyVc7NANBqxF2827qR5q41U36PYdJu8SNGmWoGaVjmtmIoCxwNmNw9nba4Som3KbM16jV+pDdj9aL4Bpok2ECgyszTt33adp7T1FPRuj6mDI9ihsco9baJpUCqRWIOQPqGFJcBOMB2fFjNAKLSVJs1EGHQ1TNMomOBjFYd5qAkKCm6JzrUW4r9u5bwdWH2HCEruc4O0KHFhoRMPAd8egcWe9mktad9E6eZK6dkSyAVl2ShSG6rgjcPEEwmry5HhYesRDPT/7kT/KKV7yCJzzhCVx//fW89a1vZTgc8qpXvephb2NjC0YZWCcUBRUZAXQ1dlSKIIAo0bT3aba3NEFuSYaWwWbJmaKgvqY5NhTCAhoKDijh8W3FRzbhtlU42YLDS5qFBnRGCq0draZDa+dDmHXFXRshcQyX7M052xFCFNsDCBGyXDizpajlijN9R3e9ZHUbXvZ0xQ1XaT70GcGWCodw94ZiNVXsaTvuOQXzc5oXPweM0txzQvPx2y0XXRjx6CuEza0mofQY93KWIwgbMY3YsbUxpuYGrHcEFRme+0TNZteQ1APuPe6453TKKD/L8kILEzjarZhBP8e5EfNzbfpDS5CE9HoGo8fUQkdalMzNGZI4wRjNnvmSUV6n0zdY0yAOQ4p8zMrSNgdXhPb8InlWkKYhx0722NiM2LcnxISWc2d7zDWWCHSItSPqtTrnzg2pB02cE9Y2HMVwzCc/NWJlsU1oFFFQjeRdJemL959YZSjRWAXKBMDOC1xrHzIW57BOpr4F51Q1YlaI1lhn0aoafTmmHdNut4rsEjR2lACvzkFFcM77404n7dREdPHri/USuVIKJWDETcNQVgRRsqMuoDHVJu1E8ZFd+6/UkYkyIrsbrVSlcvgNuIo4qemKikl/r5ick12ijNpZJngV2E32A4gSXEU2VNWBTgiOVyd2JBI1bbdUYbnqWKZn+YG0SSGisWIQJZSi0DqCijR6viPTY56oOUqBrsI/Ul0XBSg9oWtVJ46A8edNnPWjGu3Pp6uUGZzFlhlFUZBmGePRmPFwSDYeMxwO2OoOWO/06JzboLt9lmzUoSyGRLYkUgFJPaYZt1iYW6S1OMfi8jzzi02a7TpRXCdIGsRJQlJLUGGECkKMjlAqAB1gROFU4NvtPCEULy/sEBIliFaI9SfCWVeFt0Bw1fMCiEaZAB0EqDBEdAjOIFpTOEdRljijcM5UuqPDBRYXWsSWuEBhlSUgR5WAjrwyUvoQiwQKSk8oldJoNEpVRNwZVBAjxoAyiAVrA1ABOvB+GSrCKkqhAq+oOOt8SKV0Xs0ovDqmLahQQTOA+RAGERRjcKW/EXRQ7ceBARUHMF+H0RA9TCEJkMDghgXGaR+eyP0tKMahIgWEGOu8AqTx4avCVu8CQaIAnWnsmT7BxXVoGsCBVXRvO05+7hi6LGgwYnP9bij3krsuQXdMblJCvReoUboI8hHaDSjSLmXvczB/JyocEiZ9TJiCnENzGhGvVAQxDHonKIf3EiVdinwAocNIl0yNMbUSpYSgCFGuj7ZnoViHwRb6zGlsb4AaF5glS4EQhn6A5RyINkiZobTBOotNU+pzEXrREtZLgprFKT9gIARd8+9jTYjrnCDgGDI6QWRO0z6yglkR7GoH0xYIt9CMUazuekn983jECMp3f/d3s76+zs///M9z7tw5rr32Wv7qr/7qQcbZLwRTV0ShwjrAUkl31QuvOgfawMoVisuer7njloB3/xk+/ucccw5WAsfcXk92yoF/7s8OBGNgbIVT6zCfQeuQ4nDTUi5oWoEQxX6kML+kue+c5ugpeNJFAfNt4cyWYzsXNIqaUeRW2BwIYwuhEdb6ig/frdnfEo5tCAcW4dEtWO3BX3/c4ZywNBfyzd+gWFkJ6G7Dow5ndLegFlh6mwGfvgOagabdMDQbgpYtLrow4v6gztnugIsORtxzzjC0Ac1awjUX1HlU0CcMh7RafWwxphfF1OcSnnzdmH0tuPNYj7tPGZKoz5WPbdGca3DqZIzunOXSy9qcPQVBnHHFpXWO3l+wsQlpvs16r8vynoB2WxC1xD0nmpw8vsrefUMazYC7793g7LGSvfvmaLVbCD7UI6JwuWCUsLq1TaYbZC2hPd9iu9OnP8qI6jFxHDIxA3qFYCcsIt4R6T0uolBKoyaehGkYw/e6fsxdkQOlvSKjJt2WeKLyBR6eiaLgnKvWZRJR8J1dRRimHEGm3XEVgvEky7/49JRwWNS0g5x0Ql49mcRD/JdFHBMRQ02UD6g6ezVVT3Z395O2OCaOnWrbuza9O/wyIVa7ecPE9yDsJhq7Dmzyy+7t7AoBTdUUOf/8VpGW80NEFekTEaxzgNkhQFNyKlU4RsAFTMMJyvmQgKM60oliU3We2vkwkVQhAXGoCRl1IMp55c05bJaRpyPGacY4SxmORwzHKaPhiK2tDmub22ysb5Jur1MOt3FZn0QJJk6IwxrNRou5hQVWFhZZmJujsdAibtdpNOokcZ2g1iQMI6IwQEwCgQHxCoXSesdbg2IabazuW1EOJV69sspfXWcn5Nz/P/nPKm/cDIKAOAxI4pgiiJBCkztHIs6HPVRIEVQ3sgJRGq0UsVLkGIrAk0IlJcqUlNpgBHQohErRQEHpsFrjJMBW97V22l9HpVChwhhD6DS2LLCBRnToPUWuxDmHUQaMQcXgshJXFGjxRmblAtAKBhaVBNA2qMUadpSiy+oUaYcLjX+OCodEDt2McO0a0huhxiksNJDCQWGhAMkFlEUCIDYQgiqq8146/3w5h5RQpimqHKFDBZslqmeRlqbUirIQynPrJMU2adZDDddQ2RrZ2mcIWleSbd9L0Qpp1uYYFCM0i/TPnqHdMli7ieIoqJOITgGLDg0i25S9o+hyCcouJo4pspMEyVmKcg2xQ8TWEEkpwxKV+OdcCot2fcjOYMPTSHeD7Nwp6K2Td7rU9xWUoSVCowLQzuG0Q6Nx1iHOEdcstFLUngJRgjYBtnBYNGiLNl61tlELNVonCDeRskt9OcMs93BmgGr3IAoQrTFxiStOAxEPF4+oSfa1r33tvyik80AcvkFxYB7CuHoBWihGimKkGHWEwYYi6yv2XGWwItx+Z8bRdaHI4USk+Ib9cORSxcn7oRzDSltBYugZx96GYt8ifO54yQUrwmX7FWMRUl3QNjC3AKsdGGdCI4TtjuWjWYgO/cW89IBwtgdRBKcHwjBVfPPVmv0LMEgVWQEL85rT2/B9z4YyVxw7JZxYg1tPONa7ljuOCuQho1Q4ssex1dOsnSpZalkOtVO6I81HPuuozSm+59mWfnfMUkP420/ArUeFLHecPZdx5AJh7WxB6kqeel3AcjumLDLe9485YdOwsu8CNs/1OLAypNFaoD/O2Exb3H6sz+E9axw+2OLeey1rZ8e02hmRHTFKFwh0TpYOuGBfnVGZcfZknc11zerqcRwpQZCgTEwzaaBrA4xKyW2CkR5JUDLq50hoieOYwAhuDB1rWV4JyNOYrBRayyHNhkaJF8a8AuB7Ut/Zu2lMnoo4SCXVO+eqbko8tanc9ud1ptqvixMUDqVk2l8+FFWZhD+Eqj2i0OKtujIJolT+De9jUdPv6QnpUKpSAiqvi1JVxpkfyaMVmsB3wtZWioRvkKqOadKGSXhkJ8wiFUnzXwqU8r4A519cxmivLEyWKV1lRHm2MPld8H3VJLxAFT7xIyZ//jWqImr+DDsnO98Xf84rHcbvh4ni4c+sUpPz5Vuu8M+wcv4XRY5SYXUu/XlwrvQkRflz7/DX3CnBiUI5n22j9aTx1Rmq7ovpha1IH5URtrQOKw5bFNgiw6Yj0tGYUeqzdLZHKVvDMdtbfbbOrtPdXCUdbsJoi7AoCRUEcUzSmmOuPkd7bp755QUWFuZpNXxIJ27USRp14rhGENVRZhJaibBKT71USqo71jmUcmijcdr5kJoDnMMiXi0pfSchrhrxO7DWYp31BKVSi4zRhKHBRIoyVlAYCgupQGKhsEJk/UOm1ETFMv46O0WAD8eIFlRY4JRGBZ5chOLDNwqDcj5c6aygnEYZb2wW5SAw6NIQhAonBYGLqhCmQjtBWUtlQkGFGu0MLrc4m1UDEgWhRsYCgwBpG3Q7gCSiGOaQFYSNGF2PcU75ewmFMxq90KYc5phxiWpYgihElSDjEhGFCqsBTuWFQVkkK9BeusS5EmUVw41VKNaJFtvEwQKylaH2GVwAKhek20HK+2ntrdG/916S+jZ269PUa5qB3IceN0hqj2JjvEYjgjO3HWV78xaW9kFcP4dORqhaBtaTPa0FlZ9Cyr1AHwkMebFBa1lozkOeKIrxGK0dKhAwgi3FX/d0RDHYgnid8uQdqP79RI0BZZlSZIKO/DPvxSpFoAzawrijUXlI3LSohYKgDa50lW/CoUIHRiNOo5xCx01ku4PYAlUokiUN0YAAhbQFXbNexS57UK4D1zzsPv6rIovn82HhImF5BRDvEVFKYXNwhbBYaoq+kHXBjYWtz4HkisNzcHQTOqnwD/d7b0eSw3ITkkAhgWZuQfPi74ootkp+5X8KH+kJeQ+uvlyxJxGigR9p1CIhTUM2+hrBgbN0RpaRg/1t6ORQQ8gtBBrmY+GKQ4qVFbAZHFt1nGzCvmXFue09NJo9VtKR71SN5tRZx/7aiCSA9U04uMfy5Gs1vW3H1lBx54mSu88qXvI8MMkielRwzaNKjp/JOL69xHCcUc8ysv6IT91t2X8wwQYxH7mjTjFqUyphLjnIJz+8RmEt+/ZZxrrJ7feUrG1sEoUZS+2CbGvM5lqENhHD0Zizm44wyFC2pNVssPdAwm13jZivl4TkRFGNQgrGY0US5yRJwbOfscLR+ws+e+eYw/sdYWLZkpLDKzVKHWBHhv5oTOZgczNFKc3e5TnacwVXXBFN4iTVlZdp3NoF2necDtAK5RQ4jdKGSptAix8hU5EYN9mU9iGfyRDfVpuecIwJPMWpOvBKgQFwSk19FFNCoyaKDdMQyQQThQWYEiXfrCp9EQdeIPeeC7dTxEjt8k8IOyRqp6G7VQ3Z2faufXkK5gmG75o9gZgYUafbV+cJKH47Vf/gKuYy+W/qvZGddQQfljQiO8ZcmYSXwFWxol2Cy3n7U5MTp3TlCZmEbiolRfmXI8ohWnC4iQ+4Go3jO3hbZb4ASrQnUOLDVZML5MmYxdkSl+eUeUaeeXIyHueM8hH9dMx6b8BGp0dvtcNwdZVyvInk2wRlThglRPU6tXqduYUF5lsLNNsLtOfatFot6kmdpF4nbtQIGzWMiX3ISgeINvj4o7+nHd4Lg1XYsgQsJjCe1FmmSpqtvDLKCmKrqykW5xyls9XffWerjfcg6VCjQ4WOQ8hAWYVFkyqhhg+hWHHVfQFGNKV2hMqhREidQQeC1haDBWsq5U/hlEGMRrsSg0YkwTpNaXZIjzHGqyEocAFGvMqolMKNMpQqkAivbor1YSKncGWB0aX3fmi88rqdIRKiohA1V0MGGa6bEoQGVfoMLlEgeYFKQlQtgVoCoxSGBaoZ+RstK1DOoGq6Ms8LYsQrELZ6KrSgtQNrkbSLRFuUKiVKQ9R6A5fWMDWNO76NWztDoW+jeemFEB2nGZ4hUKBGQq09QG03cePThGEfhmNk+3OMi216WU69fYYyKNBGMFoQXeIkxYpDl8eh6GEzRVn2adTA1BxhHcQVWFHYUnybRUEJplQEpUJ6Z9g8+hfU4vtJWgNsUFDmPrvaWaHIBec0WMNgHY7+U0YzMOy9yGeaivKBv6IQylwg9M+UtaDLCJIWefc060c3sOk2B/YYdJCBTIzaDlwBcgrMmK8bgqITQYcTcgIo0JG/oQgcJhSipsKmQn5Os68mXLao2e5YRgZcLtie4rEXOS7dq7hrS3PfWoSO6oTRkE7XsWfJ8P7PFRztCd/QU1y133Bxy5KEQlEo+iPH9khxaL4kCh3DAcQI8zU4JIqxhbURdMdw5pxivatZblsSBbeeAglh2Nf0tzqUY0szhkT7OizdwvDxe0uu3A8M4Fu+WaPKmFAKtgeOMx0hMAbbc9x8q6U70hxaEg4cXOKKx+7lE5+8kzNbmu2Ow0Q+DPWZu0tc0WNpXuNswGjrXvQoY42MjYEgYYfhcEyepShnOXrcdzbNRowxmv7YEsYhB5dL1sOY3IaMx4bHXL6X7taYce5oNWOa8xdx7P5TjLKCKy5JuPNeWN8wDIcdutuGC/fXOasduVWIDBmXESpyPO/pe/jMrY5jJ9dpNwKyLCWuze/qaMGPiIWJo2HqfUBjJ523Uv6FJj6coquX7+4wgQ9ZWKoEj2rTPjSkplkrlUNjEo4QTyEmoQ5k0tnvKC6T4JJGe/8F7ApJ+X8riuNHeLLTVUspfpSqpZISdsIUjklDZRq2migxUxUEMNPwUUUE7GQzgpaKnmg1ObKqvkPVuoliwoRgTdQWN227VGEib9zckT9k10/P/yr9anIuJwaXSdu0ZucM7xCkyRlyCDjff3v/jq9PobQD45OARRnEFYTOq2Pl5Ow7hWB8+Bfx3jSqDkgrSuu8CddasAU2L8iHKXk+YpSOGI3GpOmQwXhMZ5CyvrnBdmeT8eYmdtjBFX2MLjBJQtJYoNVsM99sMr88z1y7Tb3VptZoUms0iJM6ca1BGFdZOsYTE+eq+0jEKz5SZeAoPUlWAgkRKyjnO0gnDov1xK2sCJYqEVVgrTf1inLe9G1dRV6A0GBCRWg0uQqxEhCKrwuTu5KxQKIMARojBo3FGIcuq3vcmSrk6LBlDmIIdOSfIeXvv0AXFLZE2QLtIq/qaK9uGaUJCEBptFZEocYZh7MBSimywRAbZJhQgaqyloIAE1d3vnNQFKhQoaIAl4PqOqiVEEPQjrFpipQWOxyhk8RnGRYlpDkSBARJRLk9RLojgtAbalXh70mntCcqWkMpqNyfOxdpGIxQkkKo0eWQTNZoNA6SrZ9FdRIYzIGC9X+4HTrnMPVz6DM9GvU1SgZgHLY8TjwXU/YL8v5JGs0GnWNHCcMTLOwxuGALzBBnFBivTloLkjsILYoBJu2TZ4Z0NMRt9dHzI+KWf3Kc9dmQpgRXCjJW9LsOa4U4PoZsDYgWesQ1wYVCEAZgHSXiTdBKwIacuq1k+7SmaBQ0DzgirSlL8aGwApxViPFBROMERY1QN9k622X9zJBQCdk4JNEFSInVnnAbV+LcOjZ4+OEd+ConKMqr45gICCcmREVpq2dc+1i7DoSVCxxPX1YcqMHeTUMfhQrg8AHhkssFk8DhFtzVEc6d7PP377O40nHb8ZJECXMBRCn0NuGDqyHXHynR2tEdCq4zpr1oGWjlH1bxGW5XNYUzA2GzD5vVyzEENvuKNBW6PeiWwkc+Izz56px9TfjUUcWFexUH9zvKUrjrBHz6tObQRQdZ295me7NOr9Pl4N6MRx3U3LsW89m7Cx514RZkcHyouPwxe7jkkhqHWgWfOQp//DdQFoYjBxKknxJiuXyf5sxWgbERLrRQWAYDTa1VoCip1zVGOdLMsjKXU5QFSkKshcsPa/YswEJ7wPYgYN/eJu1WnU9+ept5Qo6t5nQ6BYFxjAaObFzjsY+d57PFkDNnQwqps9GLyIuMe09lLC9qGrUa436f2+8ZceWBiHE3JMtzGi3Hhz90ipe8jEkXDVB1jm5neL/LQCqqMsjiOzpdvfAR0GLA+RRNH/aYmCWpRmwV13Fuahb1G/Ix+UkP6ipWo2RXKASm0aNJhqSqGjXt3qf1NipFRkmldfgOeXJcSswuQuZ/UXpH2qn4uG+anJ9xY62dhmkmJGNCGpQBnKCNNwA6u7MNJuvulo8qOOcetFx2k6Bd35OK2LnJaZ8YYqfER6bnazJaZ+cv/nK6qnNVnuo55ztlNYkT7VJvtAjWlj46oA3iVPXsV1k+GpxYtNJVKMihnEWKgjJPKfOcfDRmPExJi5H3mwzHDPtDtrYGbHU6dDprjAZb2PEA4wp0GJDUmyzEC8zNL9JemKPVatKYb1Gr1WjUEqJGg6jeIoxqBGGCCSK09iErh/LlmSq5ypb4l5arwiFotApQCpwtkKoui8/asShrvRokPtTjfQPeTKucQ4tFSckke0kbnzEWBjVMVCejgZIMdIpWPpMwtxpj/LqiLMaZyttRIvjtKaexVGG3ScemQElG6DKKMqQUcNqCyTA6QrsQU4IOFNboqZG1sEKhcm/gNpo8HVMLgChCN+qIqtRRfGeqnEXGKcrUoR7hCkEXFiIN9QjdTih7Q8zQTk3wlA7XHaFqEYQKVQux3QGqXvNZKEqQ0qGCAClsZahWqBxPbpSlf+J2dLFJcsFhAjMi7ZxGR03GeY7ZahJsreB0zMZd97PPdrHDHtI7S9LYItMObUBFKco5TFLgtu7HRAdxxf0kc2s0961gtSa3gg79LeETjzU2F4KawTEm753EpQHj7R5FlmHqQw7sDUht4RUvBVhfsDTvataPFuiww8HDCbEZoRcEFTkv2BlLUfjBW2URYrCeM9pwNJs1tNak4wFloX1YuBAoKzOteCnVOI3SCww3tulvdQkiRb2u8YXJXFWTxr+DSymwVtC15oPeLV8IX9UExY4UZd+TAj1JCysE7RTa+NedVng3t/bZUGdPOhooEuUonNBbhWMiHLxSE9cdB6Ihnz0JH/gwpFpTL+BpF8BFByBOhLvXhf5YMRxCahWdLowyoTc27LvA0WrDcKgoSp/G2B8pCmuoRZZ+BvsXLZGGu0fCfFvxDRcpSqu486R3uK91LT/03dBuQZnB8ROKmz4Vk9Q1t99h2ddap92EoK5BO77xcQWdbcc9a4JzhmbdgCu4/+gW5UhzZJ/lmdfA1lhotmF1rBiXhtWOxYSapJmx0SmwpeJpT4hQJmA0DLnrxBhlFEcuCNm32KC3PWa9BwePzBOE89x6T49vf0FJkRk0Tf7wTzaZa5Y87vKAdDTkRBcu2L/I2oZlNA74h0+sMRwqWu0G2/0BaMWFR/aQpZZ+mhPYiIMrEXfesU1nqcaTrlvk9jvWKJ1wwaFJau4OQVEV8XBVBwZUozntdRWtQUwVGdL+ZVoZDydahlSMwpMMP/LWVXxHplksOwrJrmiN97ngPRiTsMtOp6uqFNmdZTshn0rVwRs6dxMLXXU4UqkV03kqlF+uMTthkPPqlkzSl88nEBMSM1FavJLkCUzpHDrQvqOZdPq7/CO7tz8hHs65qaIy3cdEGTqPnPgdT89dtfrEO8Mk5DQJj03dskyLpymp0n4BZ331WKV9JoWzldFZC0a8JyXX/nwFonAVMdHiK8yKrqpJT4y3ZQllQZmPybKMPM0YD0c+hTgt6A8H9LojNjcGbHRWSQeb5INtXD7EOEsURUStBvVmi+X2Movzc1VF2CZxvUEjqhM1QsJ6kzCpgwrRxlc7FTHeI6DEXzOhygazVG9zdoyu3jyKKypyQMW8BapKtyC+erad3NMGJ64iNRkOi9MKC4gOcEFMaUJcHJBb39FowDmDFN7r4oISZbzCpZQjjARXltjCQRmjYk2pQSSfhvG8UlOii4AQcEFaEe8G0wfIaXTgU8nFKHQRYMSriGGcIKWiGGYEyqBC7Y3DLkSJhazEFSVkDswYXfOZQJJZn7ETafRcHSlKZJBi8xydBKgoQacpZAUuDlBzDcJhihuM0Ynx74nSosqqKrH1oTGVA+JLFRQbp0mCM6TdjDjWqP5ZbD8h3rNMsXYfwcZ+KNvozTNk43uJGtuko1WSFU8cylJwKkdpizGavH+SeEET1LdImmNsuE2yXMduaorSYYyi1FTZNYLOhNKlpJufJRpZjO0ThyXpdkneC1CNKv1be8WEMiDtKiT1SUqDzpBkAVRdcJE3mDvjB2lYXxdGKehvWB+Oa4G1CaN0hM0A7VCFj9JYvE9HAy7VlKnlvk/8NeF4i/aiIm4pdGyxpX9HG+PvMZtbVBnhOiH/EnxVExTlFFL47sGJN3FN5F1HZfYSVcWw/Yug3YbGBT4bwhaKuzbgjjsUckII6opmCHtrwsKcYlscm13haFex0oaFltAZOla3C063hTCEubZma8MyEkVcNzS0JUEonCKzUOSaixsBj7/EE6I7z3nz2KhU3HC1cPVhxYF9wqdvs/z952DfPlhaMpxe28t48yz52PnCZqbLsXMpVx92tBP45N3wxEcbHnelIu1bbr4NPnpPxOpqSfZPZ7lwJSQ2loVlxZHDIU87EGDzIZ+LhbNduOxQnXfdNOa5T1FcepHi3LZh7EICBlz76Bb1WsHiHlhIanzgE5rHXZ4QJQUbnZgzGyGrpzvcfmdEt2+57baznFu1sNeysTWm2Y45aHLixNDdFsbjlKzIadVjkth3FHGUERLTT1PC0KDyjJFTREpxbnXEnScXueiyec6cGXPqdFFdcHXe9XfTEbxUhMWnpaL0VN7f6Tj9WgI+o6MKIuwoEWpKAIQdZURRKS0PVAp8lKPKRNkdvpkoKN6cOhnoT0iJSLWt8w/lITv6qUKh1LSdE/jteQLjR8920rs/gLzswEzCRZNtuyrkUZ2gSdE4wdeVAd/pi8h5CsqEqDxU+z8v1C5PjH6IdatF05RuBdMaL5oqrbYihiIIxitU1UgzMKY6L1TGS+ent6DKIBGQskRciZQFkvtwTjr2XpN0nDIcDun1h2xv99na7LK+vkF/tImUPVSeYbTQqNVo1FvUWy3mlpdZmF9gvtmk3kiI6glJvUU9aqCSEB0nqCBB6WCHrE28RK6qBYNUKoTvXJx1nohV19KKoHEY8TV8xE06Fp9SbKVSA60DsbtUOFBoHL7TCXWI6Bh0DVTsOw6tEFulyFZPQ2nBWAiUwiAYDIEOyJVFV1JjmafYwBKYCLEOZ73KIcphVUqJb5cqashYYYPCK1pGo8QTL2U0gXWE+OGFTiJC1aDoDZA0JcproBJUaCCOpiqpKy0ySiFS6KSB1tVAQEeoWgztBnmaIzbzht245sO9WYmJQ6QW4RaaFNtd4oFB6on3ZYmu/DzV8MLpyryWgd0kq91P7LqoNCA0Z8nO9Wlc+gT6J9ZwJw7RvVuQzj0Q3ofRHW+0RnCBJs8dgXUY5bCRoEYjXLZG1CoI24KuDSlUhgRUHXv1nDjvL8rSEqMapMNjDNc7mMYq1DaJ60I+KDGh4LR/bzkBmznykVBrGFrLIIlFYpCAqi6dmkaPfcTBYUtffV1qikxB6SxL8zGqzCD1YSPrFK7yggUOipFl8757sVtnUGpMMpfR3GvRofUZtd5j7TNrx4psFc6dzpDLvvCrYje+qgmKVM7lSfaiclWcrPBSmcMPNHyZdYhjxWWPEbaPCcOeYqMLZzI4NobRQFgIYF9bOLwErUU40FZ87DbNiTXHx+5VrA0UTRTl2HH7vXDVIcWBFcf+y6CIhLMdzZE9ilosxEDkhEMKlLFccWXM/GLObUfhvR8TLjoA9XrArfcbzq5mjDM/H0+rBmtnHJ/53JB2rGjW4PFXWExtyK2F4gOf9TfZ4y4LiSO4+/550n6XdpKzVM/RJmR7mHHFIRgMFelWzNmOIpd5HrV/m4N7Ukwz5L6NkvFQM04NvZHlzuMBp1dzHnWkxv52jyAq6PSX+duPDOl2He2aY21LcXptwGDcZW6uzt33OtY26kRhwsqektJkHN0uuewiTX4cjhxypFmN0TgnjBRhEtDtjInrEQcOKNbPdhElXHyoxtl7odFusKRCVteHbJ4b01kbsWc5Qj1E5UFvInXoUPtOy1moSCmT0Az+d2fFj8JVVdPA+yuBaoSifJaDc3ba0ZqqnoZzlSQ6CcnonRdIFbXzL058DRWo1Bhd/a3qXFUVB5qQZlXVO1GKqsaF/2yMOc9TIpX64UT8yB9PMCaF1yafJyGUByock9DOlGQgVb2V6tkwetp5TsJCqF3qze79Vdvd/fMLhYbc1NuyQ4oeSG4m6+wmaBPSCXb67ColWGWYzL8kVZVSxHckplKfSuU7ZiXaK2xVITNlpZoHJicvUvJsQFGkDIZjhsOMbJyytd1ns7NNd2udwdYWaW8TV6QYUcRBRKOe0Gi0mJ9fpDU/x9ziHM1mk3q9Qa1eI64lmCQhiGpgIsSEvuAa/h1UDaXw2rfySlnV6YsSH9+31XmoygVPiEwhVCEeQVfhR1dWvE05tLG40mJcldFjq0qzhTfvK3JvMDWhr4dCiHMhUuYorbDKUWAxaHAxyloCVRAGjtw6r7BUmVCudH7n2ntonNOUAqX2yQJOFUBUhYVyv03xBe+MVj4DRCuMq2HKtPJTWcJahJYmo/4AOiOCFpBE6Mr4KoVXVVyZo0aZH5aEIaK0r1OSaNRcHZ1lyDDHFSkqGKOVRsQiZY4kMapew3W2KcdjgiTyf3e2up98+2xZUgy3IegQxX2y7BhRO6fYHmPMFmqwid2cQ8aa0fGjDFYzIlYxwTYqGYNyuAwk0IjxoWTrhFIJ2mZkgy3imiJqRkgQ4Ep/faxIVfTN/+4sSOrT5F2+TZltUV/qk8yV6AbYwOGcRitDaQs0UIw88astO2pLgo3A6WrQLlRKok9ZL/EDZ5dplBOa+9usLF1Iv9NjaX8NV57DWE9eC+39W65UYMANhGx7yNy8xpiUYN6i24LTFikVEnrCFxSGdFVz7nOO7tjC1wtBCdsQzHnJd5KeKJG/qP6l7HsQlyns2D+wyQos1TSNgWDPQnAMQgd7FbQQLohheV5xdgzrG5D3hKbW5Bp6mbA057hwUdES4UmHoQghbwsSaY59Bk5ZzcFlyApHNoaoABsqtrst1rsdzpyzfp6gArpbwolNxaAORSmc3oAzQ+Fxlykec7hHpyec3FBcczUstkoWEiHR8ImjivtOWWKBPa0O1jrqiWC05dAS3HFC8b6Pl4RhSHMu5Nxq6qe4GAdsbQecGiScOJahMNx1KmQwFrb6EVk+ojfM+dTtGet9SJqKM+dKVuZCtjsZeW6oJQlB6P0jd9yTMtcMyLOM3Grm5iLCuOTA/iU+/E+nOHJoxN7lMedWA5RRzNcdx+6xqDAiyxVB0kerkMWFOTaDEd31AS4xBEHAcDRm70qDwgq1xkPcpiKeUIj1kmyVmeG7A+1HcDIJe/jfp8W9oKrYWjGVqrYEVUruhHRMusnJd7wAoSbBG6pFTHwnfp3qt6ojPb+8PBPfLdXY2es4u9dxk5DQ+SQDeYgOHztt2I7RlKnqMv053fSuYmrVZ6wPg+hdxGZKaqY73/n8wPDOTllyNfXbnH+8ct76D5xe/YHK0WRnDqHEv5g98aperNZNQ2sivjaOQoN105CaA5TTVZptiRHBpRlZOqbIc8bjnDzvk2VDhmnGoJcx6I5Y3VhnrbPKqLuBHg7RtkdNaYJonmazztzcHHPtBRYWl6m1m9TrMc1Gg7DeJEkSkiTGRBFWBwgBqBAR32lPCgB6olslpZsSEKQUnPjKggqF2KrWCQ5lNbnzxMA4gBKr/HaU8xWqndY+tKkdlOKLAUoJzptqXekoXVXsT+Gzh0wdKyGxEpwr/LxloaHUmkJrtAhGhYSmIAjAhJoiU5UJ1qHwYQKM8VdJSq88Og0FlEGG0ymBTdAuxOU5ocoJdAMnQoDB6YTCVHdtXkBUYBoxsVHYcYpyQmCdn4unIuE+TKn9nD2kUFeoIARlcU6hGjF6qUWRZ7h0gCq2CEwNHQY+1G8URIagHlEO+gRxhE4SRHlvmnKeLFkp6Nx7F8XwNsLa3UTJOdxgC1UTbHgOipJy1aHsMsXGArVgH7qdo4IBhBbRiqIUdKRRoaKslCOnfKr8yBZE2uAGAYGrUV8xqIYiy1JcrrDaoURjSxiPHKP1AVFW0owtcWtMNC9IqH2BPerUmgcYrR8nKlKcg7CtCOZAFhxBCNkIylJjnI82WARl/FQjNle4sSLWsHigRbwnpt0IceMtKD3pL5Umn7wYSg2FxQ40tYYQ1kaYeomZg0I7dKV0KqvQBRR9oXuuwBaK5sK/jHJ8VRMUqfu4mi5Bch/yUVXsmxJcBq7wLwMdVimhiULHDl2HQ3XNhXf7OXTcwKd5t+cgWNAs5pq+DmllJXtdyXJLMDGkJSQRaFGcHQqrqTfbzi1FRE3N6XVAMvYuCnmq6StFHAhLUYe1vmU0FNJc+OwJxXwkXL03Y1DAyU0/I3GtrljdVqgmnFoTHnONZmVvg7vvEuZrA554GaxuwtrIE5qlOUcSwbFzhic/EfbN17j+ypTP3Se8/5OWfpoiznHqxFnmAxjminMb+GqKJueu4xlRZFheChmlmtIZNofQ6UOYDTCqZJRa1sSiFRw+ANvdkixzDDMhDEriICbNoZakXHbYccddA7a2Sja2NEvzAUtLOafOBgyGMYcO78eKYavTpd0KWT3T5dy5HNHeBBkGIUuLCY6A4SgjswWXX7oCMA1p7LoDqCqc+IcCquwd5VONja5CPr48NThPZsWbJdH4lNXKz6L0dLM+bMKkfgZTvwSqmrBuEipBMfGu7krG8etMCAEKqjL6vqefhKImJMXuHFLV0U9rhFSqkD/OyvQpu7Jnqgb76p07ZGRCsBRM5+0RqlCnTGhbpdRU1EYLladGTcNbExFIMS3QvEPWHqDW7KhWu+qyTM9TVXb/8+A84lNRSWHi59FVGf9J1d4qEOf8efMvRU9OFfiO3jqU8yGdvMyxeU6WjRmPB4zzjCxLGY8y+r0hnc4WvU6HwfY6druHDPugUgyaWtikNtegsbzIfGuB+fl5Wu0mSaNJEsc063XiWhMTRRCGiIn8fSogTG5KqdJjq3MoRVWx3xeO82ErrwBKFXLzyppFKDwZsGUV4vCqSSnTgjHe0F2dLbdrO4V4YiIYEIOREKVDlBFcXCKhoAuD6JBCWzIB7SAQ0Mrhq19WypcWT4DETWvqKC2UYrFiq6JsYJwichZnc/IiA1Pixg5lhEJV00dYjVahJwRBiFKWtN8jK7YJ5tuEjTqIUAzGvpZRPfY1OozZmVqCyiA7LlA1jVUaKQWdWlQUoRfa5GspJs9wIai4gTEKpwVijYkNrldgez1vLg3rXnkqFZQWHQoy2ECPThDP9cB2KDrb6HqAijOwJWqsKUZD8kHE3KF5yihE6wZO56CgyIUgKCmdf65EaYoQShzDYYazTbaOpyiBvZcXJHsLBCgrtc1ahTiNGzj6x8GUY5LDjjgWylDACKUTiiKg242xtomyOUZBsOTQLdANPyAphzKtQCxKIYEfALhCUaaarKNohpqst0bm1rzqZr2fsxBw1ClIsOKomYDA9sHk6D0Q1HMIBBtqnFTVfvHftVlA1i1BQ3OvQreKB0bqvyC+qgmKsgrJlPeLlVCOwJUaVwg2hWIoiJ9Pyj/cojBRFQZwCiOO6x+nUZcp1s4I950TNkKIG4Y9+yM20ARYVgTCSBgVirVtxclNoRYrPtdTFA7aiWLPJjgXUGrNuU3LUtuXMW8khjJQrMwVhBHcc0JoGEXHwtENR7Pu2W2ewXOuF664THPx5Yr/9/+Ej98BV10Daxsx959WzEd9NrahmwrzTS9v/vWnCi5YNlx+OOLwgYI7j7aJUFy+f8CJvcKxfkCW5/Qyzb2nHbXIIfmYubkm47IgzxxlqWiGlgPLIePUG1hDBUk45sAFgiHhwJ6YPcuWyw4LZ087xoUlmatx530F860A69q4sEBcwefuHJMXcM8x2N5jefaTI+64x7/oWnVFZ3uEcTlSZuhSOH68TytyRK2Q1GUc3KsZdMdYq8lFWNm/+BBXX6ap5T5U47y3QZlpj6qUqSadE4zzxaEEP4updn6WF6nm2RFRUwuqKEVJFQyuQi4TOKjqUyjAV750k/l1Knowsc3iqrRm5UM3/vtS/VvFi6QquFXB97+TjKGK+VAVX6vqgii1E2vaSQmWqdohVMbX83Ue8GUlfAc4bTPVy9B6cmfMToXXyZmu/B/T8IxW01om588ttBMGmqZRMSEantTbXSrPA0nJJBQ1abqrjM3KwI5HxnfsIrsKik2ujXiDMdVPVVpckTMe98jzFJtmjMcjxmXGaJSzvV2wsblJf3uVcXeDcriFG+doHGFsiFWNufYSzeV55leWaLfmqNUbvqZJs04tqROHCWEYQxjigqqMvLCTpj4lDxUh9NXDvAeOihQr6yvaKktV1WU6L5CqyvtrqgyKKstMVWxY4zsdKkVN8BkgEzprHdiyuhdViVLeSxNJSFYEFGKI0ZhJQUD8lyRQFMahAocqA7TkKEqU9tWXc+UNtBTOp3IrjVXKq5pWobRB6QInBaqs6mjokkD5onZifF0aVxgEy3g4ZGS7RMqSmICwUScf59hRipESHSUYbVAIReGVJ2NBu7yaQyf0mW8FqBCCRoS06xSdDClKTF7iwhwxGqU1WxsnMOMONdNExQYdB2A1Yq3P5lEaXIcyXyUOx9jS4tzIKy2J4EYWnfVBIB2eJe6coUgdQVzDqB7aOJzz1WWdAqe8Ib0MNeNaRHfTMZKQTq9A5wX6ZMligidTaJR1lNaHibKxpuYCgrpFdIkyXoQThNIK4zJnbeSomwW07ZNQoIMAHTiMgtI5bKF82A/ACOKgEIMUinLbsHZfSdHSLM1ZKMuqFhOUOmKUB2RFjV5qKG3GQpiyp+kH7CoWVE0TxgZbWq/oWfw0DU4RDIVs5Mt9GCNIa+d19HDwVU1Q8lUh7Xmzqzgh73umWIz9u73MvUO5HMMklV4HoOOq8JOFZuCgoVhegtW+4s5+yGfvCGk3QvIs5nCYUa8LgmbUNT6umAj3pl6WDUNhq+fIKZmLNE0pONwUlpZjLr0C4jLn1Clha0tYH/qx7qOPCHv3ep/DyTOw3YvYt1Jy+SWGRjOgv+FvgCNLmmMnFJddMOCiPTmbm4qzW4pvfQY85lJFWjg+dZviQ5+Dzx0ruepCy8bmJqFyLLU0803HoxdyTKzIioD7T+ac7Gqe9YQGUqSM9joW5xV3nrIkrYgnrITMN/wU6Gc3xxw4EJANFX9/S8kTHxfRGwGhZmSWGA03iArL0mIdbQPEGhaSktuPacapZn5xjgv3BFx4JCMbx9x5d4fFJWG+nmFHimbT0moqzjkISkXjQMShPfDJz1kOXGDRB0qOn2hSFgVZd/sBV94rJ5MQj3M7nRpU6cEwVSOkIgQ+4uGLVvlMjwmhALHW3x/VqNcrK5XCsMsgqqiyECoZ0ylVFT6ruvpJyEJR6SdqEvHZBV8bYlJATU8Nnn4frpJj9C6CIUqhcJXfaqJUnL/NyWdVmWrdZL96kpG0w3k8t9sVApv8EXWeB2YSlpnOH7Q764eHJig+9DJp4IRU7ATGpoTPsZOpw07HO+nbq6NgMjOS2jUxoig1LfevKkIyScHFWYo8J89SyixnOB566XycMhoP2R6P6HcG9DdGbG+dJc02yPMRUmaEgaYexNSaddrNOeYXlmkuLdBoe59JkrSrGYgTojgmjGqVD8KgxN8zToOyk/NaFcOr+FopAsrPyq0rRUQENM5XydXiw0IC2rtfq7CDV01EWZ9ajJqGKB3eV+SLs/mCbVJlpBgqhYYA0Y6A3GdyqYgy9C7GWGlCBYrSVx1WoJQQGoXECl2G6NwX3LK2xAJFpQAZcX5SQHxaaSH4svQiqCJDVE4eFQSFRReAdujAYk2BlIp+mpJYIS1HjFXPExptCFot6ottiv4QOx5RloKKI8RaClfgigKjDaEN0BpMEHpXJl7tUaHBNOuM+30YZmg7JNKAgXy8TXfrbpqxI+2usRQHREkMKmRa88cW6MCRjfp0VldZ2OMr0lrJUbEgBRR5iiOkkG1O3nczeadDUhuykghJ3eBsiSo0ZaDIrKFwEYM0IA3bnI58NVenIxqRoEtL0BeCRkZgfDp96SAvrO+n6pbGHkdtT4hEpZ+s04mvlaJD6s1lOtvbqDIklhTBoW1IIIrS5T5sWO7M1F0KjEuLyQJ6pwTp+GrKbqBQEZRKyHMYUWcrbzLsW+r1hDAMyMdbpGlBs6Zoz8VYsQRhyDDNkLLERS3i5UNE9RrZ3fcjbgtd0xAoXGLYLRj/c/iqJijptmJUKSU2h3zol+UjX+cB8cVuXOkzGCYVR8Uo4kim+d9aC9t9xZkN4UDdYQk42lGM7ZhBUCcvfcbAqFeSCugk5JoDDa597BHuvP0ePnb3kMHAsWcho+EcV1zT5Mk/EnDm7pI/+z+aa/aUzCeaDgn7ViwXX1iwZz806sK5cwE33xzgmg5XwsdubVGzBXsWSgaF45P3tlleqXPnyTXuPwVxS/PYayyRrlN2LfvbKVcdiblnFf7+EwVXHs4ItKLTF5aXA57/vBAtOf1Oydl1zUc+bbnumpz7js7RiEoW5je5IIfGQp9RfoCGuYC6u5cjByOoxbznppytbcepUyWdYYO7787Y2N7i8kMZ99xnSBYa3PnxPhKtszCXo+I2exYTCqfAFrSaho9/JscR0OmM2LdY5/SZERcvGPYutTgz36ARx/Q6KZ0wp7uR8tGPxnz7C9tceIHhlpuF2+/tc8njd/fHk47OZzZ4KJ9qTqUgAExf2FX8H188TFf1JiYFzQCkquY5GesqvdPhT3r13R32JPzDrm9VjZp+mpCWHaGgClxUxESqfydqhpoYRKUK47A7hDIJZlX3LNOmV2Nlbxb22/Hb333GJlVjdbXOhKQ8cL2JgvFA78jk50TFmMxFtJugPHA969w0FOYmnp5po3eMwV42kl3+nCo8Jr62rrgqBDfZziRqxoSY4BUTV6CqirDFaEyejcnyjHGakaZjxoMRg2GfzlaH3voGWXdInm4itkfgFCYIicKYRjWPzvz8Is35OerNBvVanaTeIkgahLW6HymHMYQGq70pd2K8RiZF5HayxSaX3eGmCpVy1pfrF38N1YRVOlcpfxZxBYipSIlP8xSByaRMVry/wc+E7VDaZ36IOLRzlUG7qp5sDUrFREGECRWmFkKpsK5ATOm/U4AECluVsJ/U8tFK+RnhqywiXXkZ/IjcXxCn/MScxiki5T1ipS29qdeBOI0VXyXZlNZPrjfssrBYJ0+HFDIALGZoQPkpHaJajQLIxyNkXKCNIWhEPjRVWrRzqCyDMPKETYfeZFoIJoiIm3MMxpvoIocRKAo2T92GuNM4bQnqdbY372E5aaCSNk58oNA5COMG6bBkeOo0cQsa7aqsQSAQgRtCVhYU5YDRoMQWJRLB6nZEIwgpQ4eLInQ0j2kuUpvbTzaCONnLyjOWcYWj3B7DuM94sEoh2wzHawRZh1ilaErEjYkTqC0UJHuEaCEgKxTWalzpKAroWctmv0NeGGoSUoYaSYWN046kpWhcEPqJJC3+PeEcmYPCauzIz4U2vxSStPxUD0HuB1DjEWyoOmn9QuomRRdrjEYbaFfgHGSjgPtvE2ptQ2N+TFZoUHV6so+is8z4vjWWe44Aw8gadJjQoYbEPGx8VROU/mkh0p6A2LzKYy98hUWbV5X4qj4hL4U8V9VQTRgG1QixekGe2tIkVqFT4WCj5LILLFsObj8Dtw4NeaZQuXDhvOGJj1rhuc8/QhTBgfk2JzsFR9SISxcUW12hvuRglKNyx8lzQl0bXKpJy5CzHYMEhm4OV14Oj39awGhoueVeR5E6LmhtMhg4VjeEyy5UXPuEjEY9pxZoVnsRBw5fwskTd9AbNjh9KqMdj9nYzNBiSNGc2XAUuTfhPvEJ0NsKOHp6H8adZbFdAMKwlxElOfVWxqinWN2OOXufY23jBNdc1GBvK2VtHHD/muXc2YIgVBw74yjLghP3Ca3GmLVWzpnNgPHpIYNhTqyE+YUQa1M2uxkKoV+EnD5X48x6jSjcIisCBsOCRx0UBkNN4TRaW1oJ5H3HVifiwHKT7d6YD354zLWPtiy1I86uVWnGDzBhTrJCtDZTZQCqDnxiKFFeoXClX0GJj7N7xbUylzpXhTeYqiWTztROskwecO+pingID4aCqR9kYl3Z8YzIdNnE58Gujt3L7DvZO1OCMjGOqJ3CZpMqrV7V8V3hrpODTyH2HhmjTUXSJkqSsFP4Tnb2Xx337uycqXJSqSSyq80PvB4T7CYuD8zUmexRqniFnhI0piExpaTKiqqMhYIvwmbdrvNRhSUcOCkRmyNZSjFKGY/G5OmYtMgYj8eMhilbWz06Wx3GmxuMumuU5RhUinaWmk6oRXXidpvG4iIL88u05xeI6gm1RoMoqhMnDYJ6nSBJ/FQKJsAqTx60eJIi1SR+lSbiFRTxna3BF48TjFfrnJ16oPxhKUR2DL9qIoFVx6hUNVt75Q+Zmqud+DRkLKWrfCzVRIjgUNphzKT8e4zVVWaRM2gxOOsoQh8OECsoWx2HA8RgVEYkJTXnfFKa8s+QKEUpQonzIVR8qFSJwZUOCUocOUrnRFIQ2ALnCkodo1zJaJwzSkc4qVGMxozSbZL2JDvITzSoWi1MI8bYnLTXRwcBcT0G4xVwpzTGOiRLEaMg0ig0knuTadRsEfRH2H5BkWcYl9I5dSdzCx22tlY5eOhCume7jDdq1PddgQ7nIDIQhphkHq0jQq0Z9AY09wUYZSjE4YwmdZZhXjKSglQHDGNNkLTRSZ29+y6kvtym1l4gaM4RtpfQ9TamEHStRal8desyzYm0RZUFatRluL5OvnWG8epRiu5ZlF6j1bQEcYluCGVY+tTgTChLsC5GgjkGnZxyHNMdCQf2xwz7ljO3O+IaXNKKcJIyLiEIfX85yiErhXoOUdNRn0sImxoblDjrlbBRYcjbK9jmQc6dPo5klsCW1EIo8pj1M44zxy17LzQcuDyiUIZuMc9mtIfj9/eI+ls8ejFC2Qarazm6XWO8MI+sPOjV8XnxVU1QykzhjCBWYUeQZT7+JT7LjtL6GGxeCHkJRTViEwFJ/dMdoMidYtg3BDjCQOgWOTp3PGmf43CpOJ3XuKer6WpHUg+45MKIo8e7nDi+yYHmGJcWzM/DyS6kPYV0cv7iDzTn1uG2E46DNUFKxV0nUvpZSTOCC5YM3fEijWbKYjNj7OCjtwkXNEvWu4pCa264TtFqRGxuQDPI2D8n/OPNx7ivDntqaxy+QBMmIck5y2MeY7n6Uk06rjPs53R7liIvGW4PWF8rqZmcU6cc4yLm9mOGWtxjed6yMYBzG5DmAWU2YnNzm5pRjEchhpBmQ8hKy9nNgJNnByAxmQkYno7Z6gxotx21xRgT+plTN4YFT3ksrK7XGOaW7Q2LcRntdhMdBIjtcOHBFrff62Pa11zdYuPUkD176pgwZDvyZfmLNODjn8x4yuND5ltJdcXVrn99yMBJJSdrH+PdWaPqsKuXumg97QAVfjQoU6LiMy1UZXr1A2G/TaN2tjjpgCdGUmCHzEzCQRMPRbXviZjhFZ0dsmHEj5InigRQjazFm3erfngSrpmEi3aCPhMCVpnA9Y6CMtnYhMC4yQzK1XlR6oGF2HapI7vCRNP97yIo01DQ7l19HtfbQ6Ule0JZ1VaZHHeljvgSDdVxCr7olJmsI77QlwqqemaWSYUyZQVXZhT5CJuNGY+HjNOUMh0xSDO6nSGDzT79TofB9ib5cIsi64KyxAHUopB6UqPemqe2uMzcyh7qrQWSdoM4jmhEDaKkiYljVJygwsiX2K/Oi64mfLQI4qrAlKpGRkyKzlW6kBh/LcUi2CrFPECcrSaGrEJhCm+kdmp6/RCLURPztr9uFvEG8yrNnqpyrHL4lFBxleHbeYe0DnBBRB7GWBNgtEbpiEIELZbIQGCFsBBUUE3DIIpAOyLjyEtvPHciWK19dVALxgqBVeRAaQRnqIyWBdgU58a4Msa5EIe/ZmmWUuQFiDDOC7YG2zSKkqajSk0GUQVJY45aPSEMDFl/RJFm6DBABwZXOFyZEebWE7NQgVFop1BFgUkMtUaTwWBEMRoTqhH01jDLA+aWItLO/TTnluhufJqoViecvwSJIpRShK05dBhSa4EyluFQCJTFhUJpHJmGzdzRcQ6W2+y76rHMXXCI5kUXMHdwP8M8o9Mfsp3nbHV6DM6dAxTJ/JitfpcgiAgCQ2igVW8QBop4316CxQXixf2ozTP07ruTYLxJnU10lCGBw+qS1GpSF2BdQtHcT7AVsbXZoeykFPOG0WoBWYyQs3UuReY0mbMU1qtZw1LhxkLbGGr1gEjXSJoJqU5JbUZearp5jb6b57bbTtG9/wwHVmJWohZ503Buy7F1VsjKmK1uRtzTjJ1hw+1j3SxgVZ1WS9Er+vQ6MWf7Nbplje2iiVl+6PfFQ+GrmqCkA2HbQToS8gJsVQTJiYDz8d7S+Yy0SjlFK5+FE1R1eCIDoRIKLPsWHEvLsNV3fPjTipP3wlJDWGyOOGIVpqa5oDWmNTzJx48m/NOxkr0Ni800W0PN/evCRQ0h7Zec7RjuOSdctSQsBXDbeslmpsnGlvWe5qpQ+JtP9Dl+v2V7Tbhoj+9Q7zzjuPU4qAiufzzc+Zmc4+c0j70EQmPZ3x4xzuH0WHFZQxiPHM2a8NTrNavnatx2Yo6VaINT5yxFpLlgr3BoacRmV3H0tLA+dNxxzBeD2r8MzTpcfaTktpMhUT3iTK9kc2hBZ+zb28TZkiAvWNssvYNej7nkcJuLDjVRoxEjKbnrzDyaLQ4djLnymj1ExZCP/WOPAxfFzM9ZtrsGK4pub539+xOGQ0tMCxWsYEzKxniESgccOJRw1YGST9+qyYqUds1ybkNTazzE/A3i64e4KpNDazXN5Dn/9vf5/kpXxMF5AuA9AZNQUfXTTXwD1ejeuarCbLWlSVhi0gB27UzOD3M42dXJ4GsgMJHKqxH2Dt2Q86SYaehjQksmvEHt7NBPr6OmYZEJaYOJuFFlX1Cx9SosMyEH552hh2mrP6/+CTsqy0OVxt99LLuzfbTW0zZMCNSkX51kv1CFPUpXKVV6JyBWnUaUskhZ4LIcKQqybExWpJTpmCwdMh55v8lgOGRrfZP++iZFr0M27EI+JlaOIDC0gjqNZovaYpvW0h4a7SVq7XnCVouoVieJE2pxDR3W0VGCBAGYAHHaCzjKKyba+EyVieFaV/PhTGbYnhBcT1D8MauJNOQKoKzStAXR3udTVqEeV9XHUIJPDLATQ7A33SpVZQlULzmpfDv+ntMYfKaTMwKBoAODMQmlihAXYIlQzpGo6rwXjkIbXyVWW0/GotDPOKx9uChT3pIryoeyymCSQQVWifd4VfVYTF4iNaEU4+eFygusCyjHOZL5SeVqrRYmjRh2U8pyHVsW1OoZSIZLM3StThDXCYOAdDyiRAjCEKcsWTFA6QiT+he8CkJAsOMUTc0P4uZbDNZSbNolUT02T3+Oi556Fdv3n6Gd5NjQ0dsImA/rKLOMtYGvadMMCRqWoOEoC4eRgNw6cjS2Xmc7rpMfOMIlj38GFz/5GwhaLXrWcTpNObG5web2NsPBmCzNGI9SRFn0dodRlpLoGJv5+YeiMMJgqYWa5fYC7foyrfYyFx6+Grd6jvzcZxnld2N0h4yAoYpJkzbbHUU6rtErhHNbXQ46X7ICq2i3FWFdEANZ7qrnSZM5oZs76oUPOooLuP9Yn7Cec+gaX9phUMT07DKb/YgoCFnYd4icMaPSsTVykGqKukaSiFFUcC4tyVTChm3Sr7xNWxLRTWtspTFrJqZrIkiWWPkXpPF8VROUs+t+xmBXQqD8y7+qmFWVF/aDVidgNNRrEIb+Z6MOSU2R1CGqQZA4anO+S1gZwFA0N31ECAvHFXvhMS2Q0HJuHebTjCvCgo+lIbd0I/Y0mxzd7DDOSlYRjq0qHn+p5doLFaORcOIstEPhgpawXQoNC5+61fGZ42M+YhV7FuHnfhCyMazUNb2BcN82fPZe4XGHc8yK4+6jmrgGP/o9fvK/+0/BBz8ppAUEEdx2NzTUkKU4p1G39EaOu09HLC8qxoOCRqi44SoYKcfH74g5tWZptSJe/I2afqdAcNyNsDwf8g1XKU6dKvn4fT0OLDquONIgcJbtnmYsGZcedtxzMuNxFwtr/RKjhjz7hhq1RsS9JzY4dbxJOdZ0tgJKVVK4La65OCQOLINBTpImJOMRZ+5e5arHaubmS+Ig4q77+lz7bYsUmSOqaaTI2LPsOLe1qyPnvL7cexOUwtmqDoLBEwu9M8L1acFeQfET0Fcmw2odxFVqjKumTNA7Ri7n0yrFufOIz+frkieZLjvKSeVb8Wxlp1aITMKPMg2XeGuBVES6MvxVbUDt9mhwnlfEmzBtlQYs59UaUahqtC3TyrsPRVC8QlK15yFCabvX9edrl9ekmvvngX6U3Z4d59w01GOriqjiqlo1XuKaFItlmqSs8LU+UIgWCvEk2WiFkgKXp9gsw2UjiiwlLQrS0Zh0kDEajul2u/R7W4zWz5L3O+TZALE5oYJaZEiimGZrnubSMo2VNq3FOWp1T0xMo0ZQaxLFNXQYY3QNZcIqM8YzqkkquC8UWHl8qhol2lWet4q4OuUnCJvUngHrjdJVjvq0ro1SvpCeeLUFXeV8OVeJI5Xpu6oaq8RhxJv4XTWxkhWZTpoZOEXpBG2r9J/AoLRQM5Yi0BRBDHaM8XX0fQ0pDc5qSqeIIosKcyjwKaQYJHB+QrqimmAZQImftTcAY/DGbKcwzretsKBKiBzYoiS3mjwT8tKfo6TRpDaKyQYw7HXJbEGznSNFSq1RQDYmjlMCCQmcpshzCleSjkZsrx9naWWOmponEoWKvUpDWfowVqBJWjHFsEbn5HGETZJ0g/LoJ2gEKYPBOVRQYzjIMBsHaNcSrCQIJUEdVOgIGyDGX3uLwqoaZWMfzasu5YobnsvcRVeQL87RLTP6qWWjW7C6bVlbGzEa9elt9whNiJiS3toQZ8VPSiiOsBbSaLWphQHbw5TeaJvlRcu+pXnCZpvmXBu9ME95epF043NkxTZrPYvas49BHNGc28tWvkXZNthUk2aFnwaikRMtCeGcYTAuKESBU4wcDApN5Py7bnutZOOspgwKkn118qjBZlpj2y2SlwmROIhiyv8/ef/1Y1uW33lin2W2OzZ8XG/z5k2fWd6xqmiKzW6yqTZsjRrSCBpAAiRIEKAH/Qd60fwDeumGIM20AA2mR+xptmOTRRbJ8pmV3t978/rwESeO23YZPax9zr1VZDeq36bQJ5HIREQcu/fZ67u+7ucrap8yky506CsHbfy7spaJsxzXgrLM8SLn1BtMFTFDM4klopuSJtF/8Nr5N91+pQFKVUNUBz1UxUHH1QqM85QGhAKtw8/iGPr9YI4drsHqGUHSgThtkz3aI2LB8Uiznyu+v+d411hujeDhA8FXn4Ob5yHqeeTccann+F8+F/E/fqrZqxtMmuBqS4HgkwM4sYIXL0t6GcxLxzBzWA+Xu4Kbz3geFpJ7Bx6fO9ZjyQfveT5+DHkBee3JK8Gf/AzKEgZacGfH8nu/IfFildqWPHt5xlpXMM49o1zw0/dTzm9aLm01PN51nExCL8Ffvqn56osN21tdTkeeS+cbDo8d33hBsLG5wr1HEdXskBculHzuhmdtZYOmKIj9lNoVvPhcF5c8w0cfHBGrQ9Juxp+/aSjLnJVY8nDf8vHdksFwm7W0YjIWTEcemXXIuhnSjXn5RsKrzwr2D2Nul5ZBv4fdaDgVEY8e1WyuDXjw0HPwcMKf/HnDi1csq52U2/c6nM7mfP41/9eM357Anjjbto0uekyW7IMFoRCLUfOiXUTaxRLx5KKPCChWyKeYjNaEKGSo5/ZPG2qfWoD/2k0EicixoOXDq13EnRfM/2LezhM5agG+BELqJ76U5W9t8Fy0dIm3filhLRpGn55VtJSeWgZnUdomPe0Atie+kOU/SznJP/ldK8s8Lc8sCJ+/SQbiqZ8v/n/JmDz1N8HlG9itsAtvPS7t6/AShAqtmuAx0Po3LLaxWFNh65KmqWjKeZijU+fUZcNkXHA6GjOZHlJNjmjGx5g6DPlLtCTSEWnWodMd0Fvfor+xTn/YJe4NiLp9oqSLTvrBDBvFSJmATPBC4ZxBiNb8u5wSKVsA+yT6LhdGWUL3xkK6w9q2fK4FHj5MCxfCY+xCqiFMzOZJk450raQjABGaWIULv3WtDOSRSA+RIEw99gEAGQfeh7ZRKWIECdortBIYJcAIlIhQDpQ3KN06aJTCSI8WoalXSY1SJsTxfTtczztQIjhsWukSfADYUoFWlDJCSEGkanAJvonBlng5oxY5Xnh0ltJZGwTZZi4pmgmj0QG+rIJhtddtv9MpmowoVsyagsnpIbPxLdYvXGI6zRkIgz51mEi1Q6ElwnWRUhEnEae7d+lFI7o9TzF/jB6EGUhO9LC6ZDR6nezMeUSyhaUh7vXxMqWQc7SWIfYtI2bNKpPsApe++Zus3HiFaHOb3HnmE8dJPmP/ZMze8SkHx6eU5ZQ4TqiRnIwmjCdzTOUBS6/b4crWOQpT0ul2qKZzytmcpqnRKjQhb6+tkV64hFWeh48OUbVg7KbU4xgfD6EwbJ89x7Dbw999F+N2SbsWFTn0uqQRlsLDtPEQWQojKGqPkRLIOD2p8SJFpCm7pzHzjmRuh1Sdc7h4BaEcJAJhahpSChwqCVcKnKVpGsrGMrYNpfcUrqG2nsYoitog4ohaOrpRRG0roPs3rOZ/8+1XGqB0O4KeltjKI3XI+wsZZOtEC2Tk0VoQxZ40hm7mGawLNq9AZxhaA0UUEhtCgI2hf0Hw+LHhZOIZl5ZCeN7dDa7uFeWZFJ5VCb2u50yn4KKsmc01uRXE0vPiecHZVTgu4YcfKDo2SE0Pc4nTnrQPj04825uWb96E9+9BOXf84Z+DVZKNoWO1L+kX4b38xXueGsFGT5JlknfeL5jODS9cAqkcN64JjIHxGyXffzMYpwYZXNwUTI4MxzPPeK6ZjipmM8W92w23P7Nsryr2d+DOvmGoPPPa881fj9nbW+XWbcW5tRlFKRGx5o///GO6ieTlGykf34dbd8dsrcCk0OxNFfN5yQefnvBbX9Rc3DbkM4NSCUejMcYZnrshmRZn+PBWzXhvB312zLUvXOHxSc27d+asbvSpyzlSeO7dneFswpeeHdPVGT/+0QTXbPK53/75Yx9aRS1WGKRSrQwQ0h6L0QfBV9L2h/CkhVLJMA/HWLNclBcpE9qdp0eFPoeFd2AxpA3ayniWnpcnss9SoVj6WsJitaxrQ4lF8RtLycY/5fCV8ucX/fCgLnhmFq/FhyKtJRnjRWt5+XlgIGhxjpBt8kcs+1XEU16UBRMgEYi24+Q/luIRUv4cG6O1/g8Ctl+UdxYsim8XT+sXYO7paHQbVV40e7bSjnBtO6qpaaqSusypyhlNWVHOC/LZJEwgHs05GR2TT49w+Sm6mqOpSaLAmvSTLkl3hc7GNt0zm6TDDt2si0p76E6POOmh4y4yyZAqRsiIUHbmEeoptkkA2CejEFo5cVFoFvxMT8CXc22aRoDwAtvGiT1h8+IWQM45FAtzcbg2CSHwSlH6heG6jRjbMMPHmNbjg2cxANCIBaAJoDmIOYZCgNURSicoFXbx3kgMoLXDqSArKR2o+mBQBh17pDVorxFK42RIJVkBTSNQKDIBGocQMUonyFjjIokWCiUkDY4wJNMSSbPsHpJKE2cZAhnMrrkln4+ZTiZY09Az69hBHxGBjCRR3CVRMdX8gE4yosaRbVzi+MEBq4NnmBrNbH7KuWfO0hlexIsYLRyxz4nkmDjLIQ2eDu8lrpkgk4rJ9C0O955h7eLXKIShSQc4O0S7GmuaYCjWW0SXvsTWxVeILz1Lsn0em3QRxjGrTjid5Dx+fMjuziHT2ZjuoEuUpoxOR+SlD2Wd8xKlHCqKsFpz5dINHt5/QCwi8jJnno/BG+p6iNKOc9tncVvn6b3yLR688SOO3H1cAZ0o450fvYcwDWcubvLc+ipidoT2FVncDXsaPHNfcaoSnFPUzpK7gtIrTmaaIs6wm31M2uexEcxND907i14/g8i6JGkHqROSWOPLGaJqwBmsramLKcVkjvEeVzY4a6irnFwoCmepVChFNBhyb+hkXc76v6nX6m++/UoDFKnDXAolW8tg+2WyNkzvjCJQ2hPH0OkE1mT7BnTWgmnV1aEEyi+E3lpyfM8y2oWO9mwNBKdTQeQ9V9dgpQM7B4JB5JEdiLXntSuO03nNwZFHKsnawNPvOSyC8bFjLiVn1nrcLy2Px3POZKBKR3fq2e4IDvqCu/uEYjlnOTWCtCP53/6eZ3PDc3Ak+Pgu7E1iPrlXc3lzzsUN2N33pH3N8biHaKZ87RXPdAJVI/jya4rr5xyHp/D6RxFHJ4aL/Yb1FctgKJF34dZjzc3tE66vW4z1fLoruX0n5WjviHI+4wgYlzH/3b8ruXWv4tI2DCLF7QcxF7YzTqcFP/rQoFRMP9PgIx7uNfQ6ip1xzlp/ys3rmt09h7WWx48P2Lnneeb8GrpfcO7aKX/xRk5dTPHVnF5/lcGgR1nX7B8YHq8Knr8JyRuSk8Owq3zSThoWCGcdqHY32l7MQ9RSAoE5EbItvGqNnd4/iRc730ohzoUUjBfL4jYhCNKDbaWLlkFYJlnaBYdFAoWf96D4oIS0D+/CTg5YpnHaez0tlSx/Kn7u3dKaYloQ9RSo8K1XxreyB08WQkS7kKm2K0QE5sS2oEIu0Uu4hci2D0PklvrKgil5KmnzFLPD8v9an89iOvESbKmnnsMtmazlsdJqCei8YDmt10tYmFBcqFwNgMZWeFdj6pKmLKnKOWUxoy4aivGcfHTC6fERk9M58/kxrpqjbU0qDEkEaRwR93oM+qtkw3WyzS2SlSFxNyNOO+i0Q5QGcEKU4lWKlxFCt+eJd08la8TyPBHLz3LBmrCUc5bldi2htpiFsgCEvu228QvviW9BASznONFCHURIASknWntLSJk5QjEa3uFlkM6kEMRKYZpQRii8CNF/ZxE0OEWYKBxH+FJjjaUhfDcaCcoLlBVoL0DGGAxeNOA1shHExtNYSS1ipsJjHcReMveCWOjg2RExqdYksURHMULGWCVwKmwMYhnT012UUAjrSVVClOnw5r3HO0kxHTOZh41O3xvohbSRsjHJoEPS1QyyLqU5otNNSHqGk6OCODvHdG+Pk3SCqxs621eRkSNJHURTSAuIHVaEzUZFHWr+9SGPD15HrJ0h9ymnxMzqM6hcoROLjCRp7wYrV79I5/pN/HALHa2iyLBiitYdqibi8GDC+HTK5vYWlSvYOzjCe0U+c8ynhtm4YPvMCtdvPkfcSYnTjN5wldPDY4rGYsoKeXRCY3KENjgcvaxD99oW6+5V5qRMd2c440nTHi6fYgpLkdYtmE84fgyjScHGcxkzrbk7VuSFpNPNqEoYpClT2cWsDihkTBUPsZ0+nbVt4u1zdDY3SbM+SdxtQwaGejrFljV1nePKOTJOSJIhSmhoHMXJPkLFuLyicROMtZimRkiJrRxGP2F5f5nbrzZAEYJYg609ddXuahSIKJhfu/0g7SQJ9IeS1YuebCXc1xu/8KahVMhHSOuIa0niYV1CfwDEgksbku98zZOuOO6MdNB84yDWRpFgmDrOnIPDwlPU0BjBShd2Y/C1x8aSOHYo4zmcQRoJPn4cLv7HucfYYDRzCIrSM595zqxD1Wj6Uc0gERxIxV+8HfHC5YaNHnz4mefLrzlOxzUrvRjhS65sCr70JcHhyRo7Ozmz+YyTU8P+qeBPjjwrQ8vKmmJnJCgaQU/VZInneCJ5sAen38v5/DXPet/QCE3tUk5GFcILjk8VP8kt07LmN7/RY+fQMhkVpKklSQbcfZzz3meOC2ciLq43XLoiie2Q3fEJu48dh5OYSBnMvOKgzvgn/599tlYdnYHmyy8LHj4qmOcp87nh8hXFhXMRn31msVGEUb8QnG/NhM65ENMShArr1jQIhF4TSejS8D54VZRq2YbW6SAkSi3q5v2ynt4vehtE6HZYUBVh3V7s9AOVHVBIOPdCKVv7t8v0BSwpHdrkSiv9+Jbil4sNsQhgagl0/FNpocULaNmOUOMfFh5aw2+QGPzy7xc/8+1rXDART563BSNt6+vyOZ96HghyVGBbnvS14P3S4xO2By1LI1h2k4SWVIHzNrBcBFliwfa41mcTbCgCYT1WBoamHTe+7H7Bhvr0pimoijlNWdEUc5pqTjWbUZyOmR/vUY5PaKY5uh6jZYPSnh6SXtQlTrvolVV6GxukwzWSldYIm/ZRaYZIO8i0g4xSvIzb9xM+m/BRBYQRmCPNoujOE+YZLeRD326Q/OJYB4cIzoekmG3ZLOEWU9htSHW5haQT2BqHxbUsiBILPsahwzPiESGFA0uJLxISI1wwUVuPsm3RnXRYIZE+QcmQQjIInA3FWb7tMLG+lYwkNBi8lDgUjVPMrWReS/KyZm4bcqHJSUJdvzDUpSd3ICONKySq8azHgrUoJs6S0C0kFbVVCGUZpFBl4b3ZuqGmRipF0kkxwmMQGFNTGcNpMaU4rhlWBXpgkMqju302NtfY/+wh2y/1MeySZSV1pKnzObHzHN89pB5NWfOO3uoa0TBC2xoZ1dgIrAqXkMp7rK0onKC0e3x47w2mySaPD3aZuhgfr7N2ps/mxjpnzl8lO3OOztYGaWcNRIISKUo2pGmf09OCk1HOeDSnqGumxZRy5hifzpmMxpy7eJ58fIrdVmiVcP3qZR48OCDLOuyWu9TGY0XEyaSgMhVRqnHec/bMJtn6OhvPX6NwksOT98hPp2ilqIVCxyn5fIbVmvms4mS3ocgdolsxXZfsjQwiyoiSdZqmxzzKULqPzTJsbwWZrqDTAVF/jc7li0TdHh5NLSO0AFs6vE5RnQQdx1RI6tJjk5RJUbIzOuV0UtIYi6lCWaI1BikUkdIolZLGvf+kNf5XGqAEUxp4LYigNZSFnysliBWkEWSpYLDu6Q7Dl9bX4GuwNWGXKMA7gTee8YlHpJp/9DvQ0Y4/+5dQzgXvvgOiK9k51sxVw7VtzfYVxZGV1JHhO1+0HB/C/r7np5/A9lBglUBKy2hekOeOtQ6MS0FvCnsVJBLOrSnyxOBywXzuSbUnSz0fvCvYmUvOrwgSKVhP51zdkoxnnj+9BYWVbOzCyxcL0lTw8L7gYCzor3iOJpaT3BFrSCJDksLmUPCtL0vyKUzHjtu7lh/lGVpWdBIY5Y7RrGY6hY01wfqK5/C4QApYX02oK0cnFRgsjx6P+fILHQY9Rapq3r5TUeSecS547YZFNh58l8ef5kwngvJRxLmrksRLJlPL+StrXJQFK/2If/nnc86sR2wOS9YHNefOdrlwXnP9nCMuak63GyZ21h7xpyQETzDD4sGZQK37RURTtKyYby/4AQW0/EO7y1VPHksqBIGGxjls623xNqQWPGFCbNidBoratf+KxQn0C5zCssfEP+0k+DkhaLmT5im5Zvn2/NIq2j6oRAgNSwAiCcgkxEtdS9csmlkXVffL9GkLiqSQhBF8/ikfTLiDkAJc2xwbvl20SAprA5BfAJ1F18eip0N4UDIkRpaMAL5d2BeduK23pH1+KWQA+63U5KVYen/wvi3h8+F9GoNtSupyTlXOacqSvJzRTCeUo2PKoz3q0Qm2LFC+JNUGLRVaOfpxRF9ndAar6PVtso0Nkn4PnaXEaUocp0RpF5JOcJyriOACDIBResAJrDVoJUCoUNjlfRi+xqIIT9AGZbAuVMLTMle0FhRc6O6wIoBJiWzdQBKBQ8nAivh2uKX0LozvEAqJR3kTPm+esHzCB2+OFw5jBcYH8Oqlwyu3BLBeWVwksLVGaIVWoZ7eC09jNZGSCGVCAkgKrFTUFma1ZFor5o2nriy2CfKRU47YeSKrQMTYRGGtoxSSSKbEWgfZSMZkicZFKhShuTA93EeaYScJrI1xFLYmjTUykugsIVFgRYGbGZq5ZXw6oZhNIZ9wNj6LylboJxKqGfPRKRvPnmE2uU2nN+To0Rjt1xkfHKFtzu77E6587et01hPqIwsaZCyRwgdrgIKmthS2YWJO2Tu8xW405lQ66mzAytZlhtcu0Ll+nuTsENPPcFFMnPQRRCgh0CJBiojD4zHTvGFWOorJmKppmE9yZidzBIbzly6xc++A1ZVVTkdj4jhhdDJGSs98XlDPS5xrmJ6esDpISKMI6TXdrMdwYIlSzbnnrnC0M+XWT28jspimkKg0QbgOdeloTiy2FHQyTV16vJVkWYqL+6juCv1OFy9TGp1QdwNr6FyMTwZEnXVyp5FFQ7eTIlWEkpL+Wo9OHGON4fjwCOMl88KSFzmVlAzPnmH94kUmoyk79+9hZyO888Q6oj8YsLq2QW/YQwjzH1zTf/H2Kw1QkjS4wvEea5ZrVtvwGZYgRUjqDDYEURoSEkEKIOyG6jDFXkgPMQzW4S//zHKn69nogywDS3L7oUVGgtsTTzEBuZVyeVPSfVzyIPf8q3cFf/AFR1/C8VRx675jsKp58QXN3iPDOg2XtgVHuacRUM8EeSNQGraG0HOOygsaBLcOPJGFrdUK70Jb7u98W7K2KmlKz96h4HtvJbz1acHJCQwSeLDvWBlqfva2Y613wlpfEEnJi1fhb1+VnF2XnJymTJqGf/hblrzx7BzGnN9oyJTnx+95vv+hwErPKzc1F7YEl87AX73VcPlMikRx7WKJaTSWiMcHljv3Yr7yqufZC4arFyX/8k8s033B2Q3Byank5LSmt57SWUn44U/36WUpX7oJXXnM+nbEvb2Uk5MT3vrA8K0vSi6fkwxXY/6HPy15cL3LK1csv/YVweu3Aph4IvFASBwYhGnaHahCqNBvEvQfj7BhUZCqnYDaSjrWi6XkAwLZeiHCSeEAiZAaERR2HGYpK3kZEhZIEQqt3KL19Oc9GKEEsGVfFgZR/wTGLKST5QK8kFMQSyZjeRMiMEI+/L1r36KQMhA40ofdfCsfBRbmSaJILApHlmzMAlE8HWFeyDPgrF++tvCftgjPibZyH4SQoaLftZHjRSH9k/b89rOVqNazYp0PA99MmKUSXoZFi7BISxWy/wsmyVnbym4N3pbYoqSe5zRVqD8vT48pR8dUpwfY6TE0OdI3ZNoQSYikR+mIfr9HfzAkHm4Qra+T9IeknQ46zdBJjyjqoeIFOFm81yAvOUmQ0FzwtonFYo8NSoQKn6/0Amc9xjs0oj32Jpiz8VjbtJ0johV33BN2zC8Mz+BFoPO9bL0uLjBkou0/WUS8w3wXj7cB+QilkCaYW6VoVZIAeTAyxNwFEieD90U5EEJRxTrMErIBmDQetANlwrGYGs1ppclrT20V2jsiZYglCAVCO6rGUliB8QJlLbGEYW9AEkdATiahH8dUOsYRnl8g6KoYI0AqgVIJvgDvLFoosihBKok1HWpTIssSaxyzvGTUTEi6I86du8b8ZMZq1zPZeY+8c49ITCEekPRX2d0/wlYNVdXg3YTHb8LWeoyLMmo7RmFbhTZsapwAqzy5LzixOXnX8vv/m3/M1rXzTIqc3cMDOuc2WdteQ6sK6SMgQYsY5QUSTdN4isoSZ328nDArCvK8whQVkVIMhyvkdRUY3/b47u4eYIxlNp2Ec8g46soQ6Q7zWcF0UtDNZuTFnKqpiVcGJJ2MS689y627hxxNJ6xurJC7ih4C5yWxhmxo6K1D1YVZv080W2dUNsSlpt9bwXdWqeMUVERpBegUnXbxWQSRQicJUarpJAmr/QFxpCiKgmnZMG8sqBTV63LuwhbrZzfprq8wnxW8+eO32N3ZQagY5Rt6nQ4b6+usrK2gEoX9zwWgRClQAnV4I0IKDJ7GhfSOUhBnntVzgmwlCLuuBNt4vAmbT+dAJR49FEQrgt51z1dHkr/4Q0+xKzmz4li57Oh2oZg5osOaO17w+KHh/rtwfw+OTy2ziefeOcEgEVRCsr6l+S//z4rrz0h+9O8Ue7cFa6pC7IFXMHKKB8cCKwTzEk7mgiyFuhJUjeOdA881KzmZCtCOL9eSOzvrzEYFLzwb8dKLK7zz2V0KKfjONwXTH0ge7Aoe/5Xg8rqjG4O3gsfHjq9FApcLfvY+DCPD9pZFdwVfvDFjf3KG/cMZn39+gveCF1/NSF1EMze89lyNlpIrW5K8GiI44f5+RRX3ee8zg/QVV87BYPM87380ZnJ8SnUmZTJ3HOyXpFlEZ1szWHF8Z2ONS9eucHHD8cN//4gHk5rDImN1dYXjyZxHexGTvOGFQUJZzXnnk4LV1T7z40OO579wQrcLYNhw21ZSMCgvkUoQJheHFA+EfpTFDBkvRBtHlkv/CEKGKb8LyUa0xkfCHIxQz+FaNadlPbwAEQaLLYe1tf8uPa/OIXFPmBLfAosWLzzxMKjF3MBlNDWYWuXyddP6ErwIDIldMiyyfb8tqGijHt7bp2SnsPgJv/jwaBfKJ3LXUgbyLd+zMIISWJnw8wCIZPjIwuelCIyUb4+F0OHxcEFC44lHxXuDcJ6o/RvnLFGUoBLNrJoHRkq0oMkvpDaHqQtsk1PVOWVdUOcN1SSnmoyopweI2YiomKExKGlRwhJJiUoiomxAZ3WNZHONeLBO1OmTJDFRkiCTBBkniChC6BZ8+Wgp70E4BoGGCh6QJRRrjbELr8jioxUL/wQLP9ITIzHe4VUAAL6VegKHEhgVr0IxmpdPnmcBJoX07fknsTisC+AjyHxtw6v06PaY1RYM4KVu02oO7wS1hwZQhNlBeIVEI6TECIgsCC9xWjKzMK4jDIJEWqgMznoiKdHCI1yClQkVFoxFI/Fak6qI9WGfuTP4BuIE4tSDjHBOt9jbUXqBr8N3W6UxkcxwTUmDIdKCyBjiWKOjGNXJ6EqBmRYIO2G09wk6vcvGYIjzh3T8lPrggKgvcXKCimcYUubE5KdzVtfPcnB3CieOLA26jmyBuHIqsEzO4nzEnJhT6flodx/5o7/i19d/k2deeIaLz1/k4NExP33jTZ65eY4bm1vEMm43Pw6DZ+90wtHJjHlZMylKqtpS1wbpBDpWECuO9o/ZPrdJ2kmREu599oi8aCiKAu88jXXU7RylWEcoHVEYQ2EtpWvIrEHHMVs3zrJx8yyTcY7CU85GyDimNJL+UNBddSQ9iDNBT8esivNMZE5n8xxJugqig49imsbhlSROM1Qa47VAGItxNcQpjTIcT8bMRrPgU0tjrNRMTU5nc4MLV8+ik4jj8YSP37/DycmEldUVaObUM0sWSzqRoK5mJHHnP2mN/5UGKLYiFP94cDWo5AkNnaQQx57BOqS9YEINaoDANb6ltCEZQrQKqg8iBqTnlb9tkVry6U89V6557h+DmYLJPdupp3dRMK0bfvRjeGdX0FOwmgh0SGNha8FQwtmzKdV0hnSO+1NHfxVcpBiVMVmasDnImVUQCcHFoUelUIw8xURgkBweCGaxp07hww89Ip1zZqtmd7dk5+6Mf/Rb8NUvevrDiLNdy7/9nuXdh4rX7zjW+9BYQVkL8h94fvvLlmfOzJHK85P3HCZV/N6vKW7fFezuWs6uQlXCdCR5eKzJC0NuI3p9D6rDm58aelTMreRRKdk9rtlcEaQdxcOjjN39nG4Uo3TGNJ9y97BmZWjDAEWd8tILmlrMsfUpbloyLmryJGd1NSIRHWZNxHM3SpQ/wVc1IpZ89/unXL+c8M0vD4B2QVzcRNDfPaGHIyzbCmiC6Q71JHZsfZjgSWuMEGH7t4jOgkBHCc60NeViIZtIROj/JgxJXzALFtrOFWFaql6Ilp0DBK2osRRTQiPtU6TIYo0LTE4LYJZvbQEe+PkEDU/eg1/ISwvGhzb6uohNL4BBCzakWEhM7X2eYnRs+/hyabRddKLI9jU8eX0BQMjl4qt1FGrHCamqha9TCh0YFiFbV4UgijT9Xp/R0QneQ7/bQyeKST5FI2hwREq2a7/HmCo0xFY5TVVQlSXlfE4zyykmI5rJCF+O0T5HqxolLD0dvCDIBLIh8XCFeHUN3d8g7gxJ0w4qSlBJhog7CN32DKjgowl8Vigok7h2UN/CwEr7N62PBlqQsvD0yFY49C3AWUyfbgFXe6wlwcjqnj7uS2ArWvDj2ip7FbpOaPtNfMtkWYGSOkhAbfyaFgw774LXSWm8dUjvwuZNSqSWqEhhWn9QSoR0Gm8FQuhwnBTYKGbURBSVANEgGoeqQoRZqfDd8FZjjMHZGiU0WmqM16h0QNrrM6sKpJ9DmkKSEMm4jZGDsW0yS6V4BFEckSYdqpnFmgLJLBTYNTndRCDVgEIHSUJOGzKlmT34iOxMSpYdUxRzrGloKglxjYsMcqVHY4b4yjHPTyiPcsqdE86cG9FPHLazkN18kPG8pIm6VH6VJFvnK59/lTMvXmVSVTzYO8BVhh/88feZjvbx4jnSfsrl8336UUJYSi2zaUFVOabTEtt4XGPwxrM6WOXMmS2yYUZR5vS6Mf1BBxVBUeVt/1GFVhoVeeq8IlGeTjcD0XrGraMsSqztkqQJqpvxzCvPcrw7Y/5wn5ioBbcOnTrixKMzj0gkoq6II8n6ufNkw22UTdA+RkcxTjqk0kS9Tmj7bkL5X+0NU6XQTUWapSTdhG5ngNea/WaP2HVIOh1m8zn5cc583qAlXL9+AX3tAnfe1zz4ZAZ1w/T4mEY4+vWA7pnhL7G6h9uvNEDRWpCoIEuIqC3pwuNUmMSZ9aC7GuQb5wKVKFOP6oCIPSoTyB6IrF1gGqiPJdM9SErP51715LFi8kBSz9vym0SQRQ4twOWS1zLPmSvQW/FsrcBnO57R3LCZCd773ozZieW7bzv2p4abfcHGwDEXGr9fU1eOSWnpSMnVDY/XCqHhxauOx/egWwpMInhz4vj+x4orK5bz6477jy3zUvJ7n4eqXuHe+wl9ecTVs557e4ZLNwV/+9uCQa/DG2/k/IsfOH5yp8trVwXjwyn3jiHuKf7ybceF3kOGqcBYxYM9z6ypuLFZcvVsxKd3atL1IZFu6OmaixcS7u8LRgcNa6spTjru7Ka899ljtrsJ6VqXg2NDbSuev6HY3FK8fBV+8gaMjwvq+pi9oy7z44qNKwP29+dMCsn2MGY+qrj65YiHOwVJAnFHMz6dsTboMOhlf8MATL9QEYI0IBZsAWF+jg+9ITrofOFCpMKiKhYUx8LkuSAZhGyL3BYLtkTrCOdkKxgKwOCcwAsbdl8KRFtCtihDo/UtSH4ek/zi61/AiMUsINrY6cKk+vRwvoWMJACkQAoV5gotd/iLro3wO6kktnmqXfQpoBOwU8v4LCWL8JqkWEw8DWhH0MoSQjxJ/7TPJoA4jrDOobSmtCUSRaQ1vX6ffD4jiWKyKEYJwdH+IfPS0kzndHs9YiF56eYL3Ll3h53RQWgtXQggrqFp5riqCYmdak4xK6imM5rxmPL0EFGMiO2MWJVkHUuEI4oUQifYeAiDTfSwj+qvorMVVNRDxiki6oDOIMpAh34TTxgEZ7xHeE8k3NJwDCDtAryEAZS4cN44goynkGE4n7dP+lEI51RQ+trzhSfTgrUIQo/xtp071Bq6CcPahFMtUHQB0NgwPVu1vqUg9wlAtdIJGGGxPhivlfUhli0srvWiRFritMJHklqFrhInRBsbljjlccqhRAymh3MVUtY426BNhRINoQcmorES5wxpFFE7zaSsmXrPWj/DNVDllo5P8fQRukPcifEi1Pkbo3CFQJpwXltrsYmANKLa38OKU8azA8p5wZkrl9BigFIphdR426DtOqmIcWYPkcyIYyhd+/3BY+OcbA26fkBTdpjsH9MxJZoJTVlSlxA1IFtmyguBkYpk/TxxdYm4yTh79RxRL6M/XGXn4THf/df/lt3PHjDsxVjmiCSm399CrSRo2aGsa6bjKbNJSVW6gK/mJa6qOSlPKMuKl7/wAt/85jcoixHOz4kSRVGlWCvY22lI44zZdI7Wgm43JklDOqsxTdgEOIsQgizLkCrl4vWLfHL+EScPT+gOhtTVOMwhUwInHbb13jVFBRn0V9dRugNeopOMOItIVARSIlREY9tCRWNQcYxQkqzbI826DIcDjHFUjQmhV2cpp2OcTOmkKbGM2Frr0e10ufPxHVZXVpkN1pmfHDA7HiO0oxCG7pnBL7/G/9J/+T/BW5pBKkJkGLdoeAQExF0YnIVsVaBTULHHKxAJqBRESvgWa8BIpvcED16HB+957NSz3hVsvCix6Qo5BSe5YSsTRD7sOKc5nB57LnQcL1wQrF4TRD04mMNzF8Lu6F//y4oolYxLx3OrwXb3waFguK64ctaR3zeUgK89vUHE7/yDhKPHltnc8qf7nrkRpHFNL9a8/ELG9e2Ujz+d89FuxfXLEcc7FXv7JXPTkEtHMZN87RX49V/XNEbTTA29xKEU7E8sD6ZDbpyf83vn4PEB/PnPHMMspAkaZ6m8pBkrOjLk1o+nEccnjo/uTHn1vGPnAO7vCEwjGHYTjk4K7j0o2Iw9vW5MlEr2Dudcu5bxu9/2vPOhpSyG7O5WyESRRYrZyJH1FY8eTalczedvRpxZ6/D9P53wztsdzm5FfO2lmjfvlFw/p7CF5HCUsbb+14//shL+qUnEQVlxhLmvtmUqwq5VCtqkRTj2wrmnkiYOJSVStju7FrAI4YMS5NuCHSef4iF8iPfKYKil9TYtDbGt/2RB8//iaweWUspCIvAt6lp0kyxirMFzIpZky2K6bDBIBilkYTWRUgZPRGuAXLAoYRe/tIe0z+mXAMU53/pZWLIFzotlV0UoeyOwACqYkjtZB9MEk3LjatZ7a2gdsbKyQpn0qPICWzb0+j3uHZ2Cs3z7W99iOp3y1rvvUMzmXLxygU6cYkyxcLLgrKUswpwrU5XL6vpiNqYcHVBPDxj6MakughFeK+JIo6MIoj423cAPNpG9ATIbEMVddNwJxrWoA1GGlzFOBIM0qDB00DmkkDghg+/DEYzOLXBzLI5/mHG0kNxoj59byHaunQ2DaCVEGebtsGCfXCvdCYSXKBl8OU7IFuSGz9+0EXnnPU62kDe8KGyAR61U0x4zESRNaxwY13JooS8lGHTDeZSomDqOwhTgTGGB2Fu8tzih8RhSleO0QwqLI0cmBmFtGHrYMjdWxjTOMc8bSi8x2hHrCpVPscd72EGGcaE1U0cRzqsAuJWDwlBUY7SLlxKmihTT+ZRhb0q6Mmd88Bm2UvS3Migbsk7MzHRo8i6pXMWbA2xTIHuOyAlq67A29L7EqUWqE47HM+JGEUcNnbSmvymRnZBu8qEBECscjZU8PppxWM45MRXVZ/fomrPsHZ7w1k9eZ3RwQG+Qsba+wt7+Ee+99THjU8Nzz73E9pkrnExm7DzcpyhKZpMJhweHCGtZWV1hZdBDRZrR6IhPbr3HK6/eZNBfxZiCxvY4mRYMigGJiImjiG5vDedqamswdc1aJ0NJSafTpdcfhKnOUcRgtc8zL97g8Ue7uKagKHMK3SE3c5LY4p3ANAorMnSaIaIM33rwkjQm6cQIqZFSI4WmNDYUuMkInSYIrfBKI6MEh6KoKqyzzGYzyqKgO+wj0ZiyotuJOX/xHB9/9Cm2LtlYGzAZ9Gmmo8ChCqAxfy0Q8B+7/WoDlJ6nowTNHGwVnNhSQ9yH4QXon5WhKyUKLbEiAZLW3BWuNngrOH5b8ukfeQ7vhYtLbwWiLpgoofawMXTMpGQgHN4I5hWMTgRFIRhFit2xpz70nImhygVXzsDP7gfg9PlNy+p6WALyWrB37Ll/MOXcUDBIFS+eF1QIzlxKWLsoiHH883+lKZuGrCMh8VzOYv7B73cQVcXRI0c3ExweKt75UPLS9ZqLXXjvHc9HD+E7v6WIs7P87I0YVT9iYx1++xuKwQp8+6uC8kTQ1CF+aK1nVEjWV+HZM4LTE8nJ3POjT0MJZGUN/V7F6dgyOhHMS8/6mufcoCC3jt/6QsPnbyToqM+DRzPu7Ri+/usR3ZWzxPIEMzvl0bxgfjDloJPw/HXJpxNH0wjmSF5+ecDf/XaX99+f4Z3n1gcVWbfL5naf7MGML3+uw49/OGXW7POdZ37h4D9Z+wlyTDCGKu/CLk0InDAhHusCheK9a2f3NIAIpVtetB0lIvhQRChLEy0IAI9wMlDoXuFFaMn0S2+LDSBGyaV/REqJWI7ShgVwWa7vv/BWFqbYZZMqPDHU+ifAYFHihmgBiHNYY5c7+OVSucBG7eJIK/FY75agTvgFA/AEnMgFMgl8d1hovSPs0P1S7lFtpNYaQ6/b5+zWNke7R7x07SamCtNWb964wUfvv88cy9H4lOPJnPPrW+zv7TI5OubK1YvcvpXQ5HNmp2PKeU6cRnR6Xc6fOYdzYSaMbUqqsiCfV8xnOcXpMfX8gMSdEouaRClirdCZQPdiZNbF6VVEvInsriKiAUp3UVGKTFKE7rSyQgwuHEctFxKHR2FBaNwiUt0mxZwUofSs7RjxrR9FAQ4VUju+Zbl8mMQcouuL2HaoiseB1aG3RJowIsDKJ34X337usk2xC9Wmqtr0i/ehsskQDMqB82uwopU53SIuDE6qdpyAICKYWENNe3g8LTRRJGm0RAqIG48WklpIEh2RmJqmnJHZmqipqHQA9A2axkWkSR9nDKPZnHkFc2/QCiI7x1WO1I1IpEPqsgXLEUI7lBCYxmIomdcTOq6PlOEzk0C31yUf3+OZzw8Ydtc53PuYrd4axb4Bv8ag32X3qCHuZrhSEpeerCeQaRggaxoCiyVrkh7UdoKpU+JhSpQ1JAOB6IGJwtR32Ub2G+c4neQh0uwTjj69TbO3S+MtsbesrXa5duN6MM4rw+rqFu+/e4933r1LnAxBxZye1kxGpygsm5sr9Lpd1lZ7bG6ucv2Za1gxQ8UNw7WEOBZENkLUnmHURwN7D3bo9RNkpNg/nGKKkm4k2NI9nDNIFaRTrWOUjkk7mqSboDoZ9amhiXvkbJC7Eqkc2JrGaSqRoTpdbGu2j5KEKElIsg5xlLCoCaCpsUpTIymaml4/I+tlJGlCYwxVWVLkOZ1Ol7XVdVSssdUcTI0WcHp0hLCG1UGXRzu7NPMppipAWXSk0Fr9tevff+z2Kw1QdAJaejChlE3GkK4KOtuedAVk3yETAbHAR2HX87RWENhuT/eM49LnBdJ7xgeC3EhUZ5WzL7yCO36XwbBmbdUzRHLwEB7tBlNrIwTHxvP40LNzItj7SHB719Nbhbs7nsQ7Hp0qfGopjcA2DpxkMvZ88fmUb3xnwPx0xj/7I8f6XHHvRxWHj+HDB5Jeann5vOeoEvQlFAcl5UHN8YllNfG8+yDn3rFnfdPz6mXFSSmQieZwHPHo0x2KY4i1wVYeP3ecuz5jduR4/e3zXNh4yJVzgi88I7hyyfGVVzVZ5Hj0WPCH3zPkpefv/6ZmowMf3HP88D3NzEq+9SXP3/6KwJgw62c91ZzM13lwt6EXeV654rAu4s1bji9ay2Cg+exeHysKHo009rMaGRtiaXnmXMqkVhztzdk/idG9PqY2vPFOxXDL88IVjzCeeS3JFhNtl6d227sBIGxLVLRyBB4hQuQSbxBOI2WMcCosNsIBJvgifGielVK302nBiXARD8uTXzIs0msgGGy11KFm3yuQBhfXOGPBCrRrky+tbCRbH4JcxH/bybcsTLuwTHos5B7ZghyNANv2hcg29ivb5lVvw+5YLrwTHm9NADcufFaS4LOR7URbWm+LRiBc6HJZeCuEE23LLiA8TrtWqgoTa62WSO9JrGet0+PGiy9xOJ5QFTXf+fpv8Jf/7nu8eu0Gr7/xM0ZHc956uM/xg/usrAzZTiP2DvYZjcZkccwnb7+NyY+4fm6V7uqQD27dJS8MW1tn+Md/6w843b2LtQ1NU1DXBVVRkE9z8pNT7PiEuJ7TlSWxEMQyJc0S4n6E7CX4dAX0GjpZQSQZUiWoKENkGSaJiFQUSs0WspkL54OXwf8hnAdMu4iHHhTnwVuFk+KJCbYFdxC6TRaNw64FgAugKRdlgFKADJOApQ/PZVTboWJVKKQDLKY910FJi10ybRKFbdNFQbYWLshRwR0VAHrwqASAaeWie6V9egEKj5cRNkpRQpFIgRRBxjRojBT04pQYhctPSesZsTB02qGqhZL4WmJ8QkgFKSQmMEEESckaQ2VPSURN15dExuFdjZcVIhEgIrz3VHWDqQLA1pEOs7KanK3VlMfjintvvcPll85AbTi685dof558dsTq+g3mHc9of4etLUE5cSSZwGoLkUeY0K5tcMisYfVcxHFe06SKqBfi0UJ7VKJorMdYMCTUvQFy3KOYCUrnmM+nRIlma3OIatN8z964xqd37zDc2KBxkqYWPN7bYzx5jIgSvPFtOV7N6lqf1bUVNjaGDAYZUWZZX+0xGCboKDBqSI1yKW5S8/DwIWVZkXYznIDNM9so67H5jFgmxCojTjM6aY8s62KsRmvHcH3AyWRKuX9KttLFb10jn4K1iqSZUZNRRusQZwgXPusoS4kHXbJenyiKg0qMw8Ux47JkVlesrG+wsr5O1ulgqiqAyqYh63RYWVsjimPmsxlVXTAeTyjzCZ1uSq+XcnA65XjvkOODAwyGtNtFCIVZMLe/7Br/n/C3/9O7+bDTjBOBiiAaQroB8YZA9T0iI+wGRfiPFwLUYi7Kk1hoesFzbgWyvuDj78PDY4eqDfOjY/Sk4PKqZ+4kNJ6sA4VVjJ3nmU3Py5cdgy7c2/fc3dHkBk6OGspKYIDjwtIcCo6qiMOxocGz1fVcudblmdc87/0bQ+QtD+9Y7j2QPB4ZPtmvOdOD3sCTpZqm9vzTf16hnOfTx5ZnNgTXNgVf/QrcuCJQSL74iuUnH0je/ATOdA1XtjyVgQ8/gTc+dPjIU240eDvFVp5bjxz9Dnz7y5q7D7fxbsxmL+dLL8DfOx+x1hGUE8M3ny+Znko2tjwvXl7j449LLp3PMaXAdyV6ULL3nqOnLIP1lN2jmk/v7/K5Kwpr4GQ0Y+PiNo/nFdOq5H/3X2wxOdjj0XHCn/1ZzvZKyuqgob8pmRcdJtOa7bWaX3vJM8lzIm0pm19sH2wv2jzxkIjWnvh0PDYUf5u2MC0Ku9K2fyIkU1ppaME4SIH3rb21lVMkst0Vs2QmFj1igYqD0HSlly/NO7M0PYaXsyg0C6VQy9fvW//HYsgerVAlAmviROgtCY8ig3l1IS61c2yUWlhnA8TxNuz4vQclVTjvF34I3PJ5Qx8KS7re+7CzFbTTjhfx6HDHIIJIj6lr+qtDrIf/6n/1X/Hf/Tf/X+bHE56/dpXv/+mf8+D+Dn//9/+Ay6sD/uif/T9Jqylf+9yXOdra4NHBEVUasXt6zM7th4hYcDqd4r3myoXr/Be/+T/je//9v0F0ar70a1+nKQuKWU4+nTGfnVIVJ+i6ILaeSEXoJEZ3e+jVLrqXIJIOxCtY3UdEHWSUIOMuMs4gSsJ8GBHabQNb5gGLDSYEvAhMQpDNFNLLNq7rES4AUESAt6Hwrz1izoSYuhBLvw6LbjwZRiyEtI9/4v2hPX9Uayp2Co9FCYW1EusF0lu0f3J8ofVS4ZCtnG1buScMnvGolqrz1gTWppU3F3SjEO1HEElUrHEqoVEaG2u80/SimCTLqCYTdDlBiZDwcN6RSDBKY6WiaRpqO8VbhXISHcckTYloGlRREgmDtDXKFNiqABqcMGgUyoY+m8l4jJ82bbpMMjo6Jj++y2Y8Ius0zPcP2f/wAd1BRNSUGHeEr9c42ZmSijllc0zkayKVUMwKkr5CSIOQYS6bE5rKeWTfIwaesShY00H8FU4gnUdqTZUbCj3k2K1znAsMCtlJGKxkrJ8/R5opxicHvPDyTcbjEU1d0R0O2d875P79R9TWcOPGi7z19vthjAaeqspZXc3IOpLV9R7nzm0wGKbEqcN5Q12DqQ1eybZ1fEaZGzqdIZvbG3jhGE/HPLq7y/7jEYnv88ILfTrdIc57qqoiSSJq54iTCJWkPNw/ojo+5sPjxzzTgVeeWaGnU2ZNAt3zIJIQ4c4y0mGPTr9L2umhtMIYhzUeZyvyytIdDlnZXEdHmqIoMHVNrCIGgz4IgU5DDFzOBVVZMp1OyVJNt5Ph6obZySmHB3vYyKM6XUoERVmTdTr/MWPeX7v9SgMUKUHHAplANIBsG+I1EFnwliyCC/6pT0QgwLaegNAqjfAeb6HOBbKB8ynY+YRb//4D1jueaA0ObYQoDANpuLDi2D0K3/lMQjf1nNuW7O87lI3YmTkq6bi+7jm7CkZ4OhaU0gySBmHheLfirT/xfO+HNYcjR9cKklTz4NhTWc/+BE4/dmTOs9q1fDbzGBcYo7VUk0SO9S7sHfUYjyVXz015/qbi9T+q+GcjeG4Lbu/B0RT2T+H4TcF3vpBxaWWGt4KdQ0d/VXB64rl9e0a/K/Eziast59YcP35zlfnJhEsXapoavvKy4tGDglv3HfnEcjgX9IcZsZuHmPea4GefWO7vNkgJb74v2Z1Bd3XOKHd87nnNy+eGzPZq6lryaCeUF/3pjxt+7TXNYDBkZ2S5cSPltSsJ+3sNnWTOS1dj7p7Wf+3YCyHCrBDdZjxF66FYRH1lWNTxIc4qhAzx4tZP4hdjrmVYzB0CZ8ELjdJq6dnAt9SnDxLAAnRI6XFELQ1nW1nJgww71QBGwg546Y5pF7GwC15EksUydtyeoDjZSkHt5ttDW3Pfbj8W3pj2fq5dJIVqW0Ub26IdsbwY+NYcG5p1xeIVLecPSt/Wp3nwSKTzoeyr9UssoJGKNaf5hA0Eu/d3+C//4R/wJ3/4h1zc2mDgO3zrha9zPh4SHY3ITsZsrA/heMqrV17gxWcTfvjp+xReonUPYyyxm/L89WfZHPZ597s/pNo/4MLnL2KNoc4LymlBPhpTTU+w+SmeEqclPu0Q9/qoXhc/GECnE+SbqAeqA1GKjGNUnIGK2ih2FArPxJP2VSHbEjkBjfNoL8KibD3Oq/b4hYkKi02OXbAjtGRYK645H6LVsk06gQ9zeSR4LxHKI2zbuSOCsOi8CSqcDxFj2TJwToSfhYPnA7L1vmV/JFCHx29Nut7ZFg+1SR+vkBbUoljQL8Y0hIi9UBqho/D+lQQd42RKlGUI76mKgo5yxATTrJahq2RT9XlYWjppBqrLvCzR3hCZBuMbEu/JmpoUqL2FokHWFVI4jJVQC5StcPmY+ckRTVGHdl0MqdLMDh8zXD2GzhwZN1TzQ7wzpKkAN8ZxxOT4MZFQdLoNxsxIlMUJQT23kIaDIlofTllDZRv0asRoajhjBWnjUHXYfERJTK4kO2PFbtNFr21gD3N0NyFdXUUKuHPrM65cOUfa6XD77n2quia1cLB/wvHxmMvPXGV//4iHdx+wsbnKmbObxIlCC0sWe65e3UIqmM3HRLUg0hJrLU1jKZuG0cmE04Mps9mcyWjC4wePsXjm8xkbaxcRfsjR4YTZeIqwHrygrkukCsev1+3TWVmhwFLnhmvdFF2P+fTTQ85dPkO8vgVpHx0lqG6XrN+l0++SZClRFCO0DDJhY6lqQ9bpMtxYRSc6fA8aS5okxFohfISMYqwUmKpmMj5lXuasrK8Qx6Fq4O7H99n97AGNLcjWulTOM57MWN3YZPvsNkLMf+k1/lcaoKguZGcEydATDUFmQBz4TNnKOU4Boo342fBfES3WirDTcSOYfAgnn4X5OlkCoxyqY0dpNDZVTE8b8onlkfM4J/i169DrwNEJpAmsdD2bm47THU83guOpJ408cQRJq18f5oK6gZPcU+9MefNAMDr1vLQOER4tDVdSye0m0I5JO8Sv7wVDLcltaKZdH3rwEf/+u+CqGp3GVM91sLYi8o4HxxBFgpvPS17Tntff9tw/lfzZT+dcXHFEAu7sepKeYDJ3PH9pSi8VHOxbPtsRDLpg8zlnzziORoLjieeH7ziePVfyzAVIU8Ve1efHHxZsDUHahqNG8GisiWTMfFbyww8Mv/87Ga9cNRydNJw5H/PJR11qDD2hqJqIlWGP0aThL972bK4bvvJczedecCRxwo9f19w8n/CVVyVboxRguYukPXZKhWnF4XcALlyoRZA+Anux6AsJv/OuLcpqTaQLh6qXIanjZZB9lpOIxaIwi3BetUkb6dWiZxWBDQuFkAjRBODDExnHuQU30gKop96HX4ICT2t8CT/1Nuzi29fxcxySJ7yHlmkJmGsRaRUt4FhIRouW2fD4wreMTDtA0Yuw1XcLNkAENiHYUDymLQiTLvhYnFKMTk852N3nA/se/tw5yv097ty/xxdf/A3W+tt89YVXePDOD7jUGaKtRiH58Ufv8sHOI8pY0R2u81u/8Xd49YVX+O//23/O5PSYjcvrnN84w6VnzhNfTENddt7QzEqaYkZTTVGuIhaQxBlJkqCyPro3xCcDXJyh4gSvYoRKUVHwnYSFV7SsiSdEyIP5V0BgUoVfzrZxwc6HaHwwgbaHSoY62ZZhk+0xaE3HXi1BjvCuTVUtUl+iFWDCEfRSh2PjQ/eM8A7tXPuYLbMm24nHSISzWHxofHXh9bpWQFoUukkEspWuXSsfLmTDAEKftBKHwrxWzpIRKtJESYQoU6JOTNSNID9G2YpShNqGTHhyQESaQgis1KTZgNoIrBcQG6wp8A60EiHhKC3Ot/sHDdYalCnxRjKdzTk+PGEyPqKoDM5bSmvY7A9ItAUx4+LNc0weP6Y4fIQxM6q5RUSSOM6J45g618RJhRcFxjUIJWmMR9SA8q3ZPXS/VDVUqaAqBQe5oBsLOJUc7oIaGrqXhjyexRw0KTZWyH5G3M84e+4Mg9VV9nYfs765zeloyu7jPbbOn2UynjE6mZDPC06OR+zsnCKE5OTkBOtqzp7ZxNuGupxx97OPGa6s0tRBZu12OoxOR+ztHTE6mdFJMta6PYQRnB7OmE4meKWZ53NefuHrqCbh7e//G567vMWgn3H9+etsnt9CKo+TUFU1ZVkRpx3M9JCtVTg7cJRG8Whvn421LbpJRpak6ESF45yF7wsqFLvVDUzzEhFpeoMOSTdGKEEkYrRSONGglUI4jZKKpq44PRmR5zlSK3orfZyZMz+ecPBon/k8Jxv08JlCGcG5tbNcuXaNosypq/9MAErnPPSueFQMi4aisIMMm0cWDDwtTavE0ukuHNCAO4bJB4LDdz1m5Il0uN/pxBNFkknH89F9y+1Dx8k8fAHPrki+fMlxdltw/DgYreIGLp3zHDeeciSo68DcXF71GOHpNYbPjhPKuUIJx9HEceOCoKtgfwY/fgT92PGdm46rU8n+xHO2J/jJY8/nznqiVc+PbjmyCCZzy1oPjo8VpvH87nfgC7+ecOt1RyI9//t/6Pn8s2EnPDkxdIXgn/9AMC7gYOQ5mDmSWPDKSsQPP2x4sONY7Xo+O4CHI7i75/nyzQrnBUdTgcz6fP89Tz6d0Y890wJe/2xMbeD+ruXqpYxh4rlxKbymvBQ8e1VzcX1I3dSspHOOTyNm8zlZx5P2oLYlMolJLIynhq99XvC73xpw69aMu48t3bhiMjfMfMq07rLyc0c+gAatNVa3FfctG+GtWBpdF3XxywF++FabaYlvuQAPAfAsatnbZ1jCiEXRmmgXugV2UT6IJM5rHLb1eLSMDRrkoon2KcaipdllC6DEkkURrZyw2BeHBVEvnLsE8PIkqRH8Nr6NvS5yTGH8Q5AwhBc4a5FStJOEn4g9iyistQ6lggThCOe397YFba0MIlsw7yXewvraGmfWNjjdeciP334LDvc4219ntYm4EK9w8MZ7HL33Hl9/9mUG22e5a2a8+faP+M4//gNe+7Vv8n//v/3X/Df/73/C//X/8H/hhWee4cevH/D6z37C4ckJlS+5/Mp5Xn3ty1RmSj0/xeQTfFW26ZOEJOkQ9XvQH2K7A1TSw0cpLk4QKkJGKUJnCBEFb1GoE25r1mW7YXGhndeFYLlrO3U8C89JSEU9XYzrFtVpLQhcjLBc9MqEb3zLzKkWUnq19IQsziehBFiHaqUNJxZdObTJnzBtO7C74XHcwitkAe+wSKx1SOHaDJLAOBdaWoVEY8P5LSRYibMN1i/8KwKkwovQmOx0jI8TOlrS0VDlM5QtSJQndh6lJMoJisrAQJB0MyaTKbWWjPOasrQYpRAWUu/peAi1ZR58KFEUvkT7CNBM5zmPDubM8hKT5zhrcEbQWFhbu4gpHnF6esTm9pCZS5mezjG5wViLT0uSgaWoPA2CTLb7Ae9RKKxxyxSUFBIRSBsmpsEjOCw9G7VAVIrde4ZSeZJKcxr1mOQlSsQknQ4rgz7SWd5/8y1WhwNq03DweA9bFUjbEIkUiWQ4XOVg/4jdx4csyhsPDg6RzjK4dpYk0uDh9GhCWUIUx2TJkK2NC/SyLQ67U/YfPuZgdEjZVJSTimJSoTI4u3WZH/7lT9noJCjruPXJbXrrGVmvQ29lhd4wQUqNoGBlOGDY6ROlBbUfYWpPJy7Yinuhq0ZqnNbIRJH0MnSagNI4wBpL1RiQiqSbEHUz0rgTIHU4SVFotGrlb1cznRxTFFO0Dtc/pCCflJwen9KYEqss3eEqNQ7hFZev38Q4z6wcE//nIvEk64FFWWr6ofoCH9jc4DloWRTRVhoLQUjplYJmR3DyNswfeWweoshSQmUlWU9y6esStZXx//snNe8dWyId5vXsH1lGHwi+MocrW0EaOJjB6FRwOW146TUoG8HdR55eHC70pZL0RZieKWPBnTE8rDxzETOaGEalYyA9mZKcH3qe24bGek7ngpUBvHQTzq6EA3ZawO0dy7gIrYhnLku6oqKrHL0+XFr3HB8lfPJwldVojwub8Nx5y8/uKzZXNJsbhgsbkrJw5FXMmw8q4liw3odXryvqacT33yyoNBzlgk6vJlWeP30nLOxb64ovPOe5u+O4/RjOrJb8/V/vE1FzMMp5+07K3/q25t7jbfYePObShufDT2vu7lieO1ey89jycMfQVQVxP+Xl6xE3NgeMdktk2fC9Hzf0h5qmlLz8SsQr10sm4Qi3R/4JA7FkSATtQsCTHpHFPZ4gDZ48TAs6Wt+A84spxU8ZW1u4ItsYhvu5+y1SLwIvVCshhMVPyMWMHrPU/j1tfTuLlE4ALdIHsWBRfLZI1Sxe/GJIXTA7thHXZa3+E8BBmwRaNMEG/0pburbIKovFjj/cV3lHJ02omwaBRGpNr9Mhz6ehDcb5RYI7PAWCLOrgcsN3vv4Nfvgv/zVlPqHrPV+58Sx/60uv4puE/LDCZ322BgP6Z6+yuT3kJ7ff583v/SUWj7E50+qY3cOHfO0Lv87DB3f5qx99wHB9jWefe4EyGmOamrw+oSoOqcspWB/ASRohh31Ur4fo9aHbRSQJJBk+zvAqBh0jVIzxOhzDlnFyBBCqRJBjAnUVgMpyMrULzIYFpA0la7YFBk659jEkXocosvQaKS2hddjifbvD4ek+GRF2u+3p551p+Y/Qg4JXOByRcDjhsVYgncB404418K0/KDAxjmC2Z+FPsS19IiRKNoALvU82DClsVB2OZTh5wjmlwqgCL2MQKTqpyfoKOzqhmI5R1pKYAJoaIZFCI3yKYJ1mnJPqmEa4AIpcQm4KYm9IpULpkIgR1iONQFYlmFAlZ71jXnrGU0ORW2RtEHh6wwFRnjIykrTW1Du7HMYP6HQMyUBinMcW0NSGRoHqKMqioSM8qj0+1oZCuqZ2NMK3EflgSi5Lj20iPJ4HpWDFxpQuZhpl7J3E5Osder0M39Wkwx7VfM7DR4+Juz1WzmxwdHDAwcEBw36PujRMZmPm44pIJkQyQUnV9hlJpNLMZiWf3LqPx3P20iUG/RXWh9t0hj3m0xPqqmT93AXOrEvW+6vs3r3P/v4jIhUjhWTY63L92iXGR6dMDx9z/vI2z75yjc999ctcfuYaa9tbRFEfLyRaF0ih6KQdVNahMMdU0iGcopcIauGomprIVsTxGkpFofvGhc2UaSw4S7+fkvZ7qG4KIrwfQTidpVDY2mCKnLKuyCdTjAnMVaI0ZVFS5RV1XpB0Y0zcIxsOaCYTVgcD4jRhfjKjk3Yw1S+PUH6lAcrPxYUXF9EIvPKL60JgUaR48gfG48eC/I5g8oknPwDXeJQCpcMGuyk9SsPmS4pqVPGFq7B3DOPGhzizA1mArwW39mLGD2rmI0fsPd/5hufMFcHBkaBwgrkVDKRD1paB9thYECWWTgylF8wnhsR7truAhE/3PFoLTpTHGEkaw9HMMzt1bHTDbntegURxdhXePjT84Q/hHxv48XtwONG896nhhXMlPXFIoj351HNtXWOV55uveF5+JcYbx49/ZPkXP7CcWZP8vW8Kvv6qY3/P8i/+3LFzLGic5/e/IUio+dlnMXkl+M2vpvydr8asruSMJ5JPHkbcvJJy91bCZDTjmasNw8Ty6S3N/qPbDHqeRzuenX3HrdsT9o4EtdD8zjckz12E3VN47kafN96OyPQUIRK0Nty5X9AZCG5upkzHMazwBGAsjr8IzEBLthNYDh12/aL9+zaiK55apBH254ypeBmGAnqLkCqAE/EUW+L8sg9lMaFYqtCPGtQTgfcRzrbj29uBfAiFfOo1L8rSoJVo2vcQJIcWmMjlm1sO3Vto6ssCMN++9yXYCEBEeNlOn7XL4rjlxGEpQ7+HD/0w2kM/SXnumevcvXuPXn+Fw9GES1sXuffwLjJNGE1O0QTmQAiBaxwXz57jd779W/z4T7+HymtEUZE5y9Vul+m7P2Fr4wrdKEVde5bDvV2YTsmLEa9tbvGDT17nX/3T/wcj4+mLjCztsrq13bIlBbfu3eHbv/EdfvTOdymbCld4KBoi49BKEGcRaqVHPOgQ9zJUJ0XEGSQZMgmtsF7GOKmRIgbpW65MLMcUeMASJpF71yajBOHYOxNAgxdYHwaOqrYivhESaVtAIQmSivR40SyTO0JEIAXOWSQK5y1K2lYuC2maYLT1WL+IpYeOFeGDvARtIsiHZl+HawvXgpwSxkC1vpM2pYOUoc6eIA2FiDHL610wuYSzXQgQrsEph9EBVMeRpqMyMu8oZ/t0qdBRROprROSIEECQytwsZ9CRRP1N8kmBaU7xokIRiuc63Yy4J8irGllDIg3aNFjrcZVHOoOqcmw5o8krqCQ4QZJlZMkKur/K7FHDStJQlEd4OSHuepK+CgMFS0slwGhPIyxpG4UTVYw1MSrzeFHTOEvtgpcoCk3/nDrPRMWYAs67lFEnZdLtIocDXKRJOzEiiyjmU8bTgkhF9LoZk9k0zKYREts4yrwin4Xk3mhy3Kb+QllilnXRcUwcac6d3eL82ctI0yOVfQadDt0k4fLmM1jjGU9r7o32ODw45vBoxGg0YjKd0tQNJ3sH3PKWfhoTRwUvvHKD3/uDv8PVZ26ioi7eK+oqMES2FpjSoYVC6Rgje8zMDG9qsrrC1AXzYkZih0RJhDEGX9ZI5ZAorPGkWUpvOEBnKV4Gn5UPVC8qilAe6qakKktORyc4Ga6BURKhcNR52RaZKs6sneF4MkNGKfO6otvvYUzDYGXIYNjh7sf3f+k1/lcaoCy0e6/aDSSw3H62UUCxdBIKKMAcSGafeub3PE1O6wkIFwRvw/RX4QSzuWP/jYYHjzzvfyxwheeihktDwWYKV7cF26uedx7XODyTSOGNYz/3JBNPb0NweSB5/V3Fmagh05BpTy2hMdDre9ZSiBLB3rFmkFi6qeeo8OQlrGpBHkXcnlgu9ywvloJZJYgTMF5xlMOga9jIJJ98WvBf35PsHdXEqebtTwVnO6BNw+hAceuh5/HY8Q/+YZ+XbsyZFxpnK156ybNzCGevCH7tCwNufyxYW5vwxZcMcUfzjS8Irm0rinnN+mpFYQSv3VQ8etznZK9g+5zk4sWY9z/TnBxotBE8uNfw7seO47LhWy9HSN/wyX3L67fGCKEop47PPe+4eTEmH0NfWfKTObocUUiHkx1qY0lTxe99e0gaCz5+lHL1Ck8IlL9+JgCwrGGH1vzqf+4uT5iJNskjXDsosAk6vdLQGmql1Mvnc+2cmgW+WIzwWcz18TaUuDkXEjlWBrAghWo7Phfnq1tKSHIRk6ZlPFjwLAuXbTihnXMoGeiUMARQtLJQ6CZZOA3Eor4f8EqHunNrsca2so9sqcWWFXKGMysrbHd7fHY6ZdDfpnQx69EQdfY6528+w3e/910kltLkRGmCM4bnr93gxcvPEB+XvLf7I7zWjGcjPnjvp5xIxfTZ17j223+Psze/RPPZbcx0hmpy7v9oj9h6LqYdznfW+PZ3/gFf/9q3mc1yLj/7DDtHj8mt47v//vvYLKc7yHBVjXAVUlmiLCbpaZJBRtzJUEkXGQ+Q0RDdSjtIDVqzLIWS7WfY9suAaFk2GebNeNHGzh1q2RobKKNFEipMDnAgTCjAEyqwWY42FRR8KYGBa833QoTxAajAmIoQ+XbStkVwYnm+qlYutCKA3QBRmjbpE2H8YvGzYTqx9QhUiI57Dz6wf7Y9uReYXPrwXqXzSC8xmNB+7AXKx6FpNvL4yIOISJ1BnI6Jy4JeL0ZUFleVSCExIsHaAdJHKGcRUYdGRTRmjBWeSjkyLImM6Q16ZEPF/LDEehPAFw3K2lAe5x21yRHNjKQqQ7eM8EhvSHsx5y5d4vYHCePJKesXFI01VNYjYk/cAxrJZOZprMfrmKaoGcqM0yNJ4VKyoWB1NcFHNYWvqK0Bp1BCUrqIEs3MRpxUkPVSxFoPmaUIYVAalPAUtgFnSbOMpq6wKiLNEiKl6XW6nM5y8lmJNSWmnrOyscX1a6/RiTscn0zIq5rtsxt85cuvcf3qBQa9FdI0opiPySdzxscneOGxXnPh/Do3n7uIbwxvv/4e77z1AQ8e3GM2GTObjuh3+lw8v8nXfv2rnL96nZXBWSLVA6+w3jCr55RzgyJiOOxhignOdajdGrKeoLHMxjlllCO3arwtqMqEppYkWUwUZcRZwnC4SpxlCCUxzrateRqvJUprqukMYxrmsxnCWTqdDiYKjbXaOZyEfr9DlqwHVJEk7DzcJ1YRSkjiJKE33CBZdEb8krdfaYDCYir6YmMZrj2hI4DAsC+F/YmnuiOY3fOUR56mFBgH1gh841kYC8KcC0ciBKP3HT0Jf+ei5/G64Oymx+cCW3jyUrLzyEPjuHE2YrWj+Ldv1vy37wuG9wXf+YLi2rmUk9Lz9gPBl67B2mrN5b7HpqGKP00haTSjUnJpW1DMaw4KyGuYzj10LFtJxLiJ+GTkuXDG8cmOZjDUeF+TKMfVDc/DseH2XoiBqqoizSNu3Y2xI8d0LpiUgvWznq3VipPjlB++tc4g2mVj6OllgteeU0wnhh990ONzL2xx8/qIr3zBUFWaH/60z6XNYzre0u0paDwfftpw46yjqeH7t/qUxREvnctp6oLx3LM/hUkh+B9/WDJIw1C0zz9nqSt4dKL4298ccv++xjjDRjbhJx/AoCc5OrF8slPwlZcF59Yy0BXaV2zEBwBPBvy2HgDHgjZ/2mm00P5Zgs/lfQg/C4VaYYYNzuLaBIUS7X2lx2FaZ+oiwBsW9+B3afsucFhvlzvoEGMPRjLvQqIjDAIMu2q3kHCeGt638BwsgEpbsBF8CC1j0pI2TxihFtCI9q0v7h2izZLFrBzhBVK3mWjn8T5U31srWBkMmIwOkBe2+L3f/g6PHo7QNqXcn3Lp8nkeP3jMoNsl8p69vTFra+s0pqI+Ldh/sE+SduisrrC3d4thx1KLMVXpuHv/Q/zJy6y5bS586yuIxlBWU373TMof/7/+KdN33gUsa711Ll64zHe/+1fc/fQO3//+X7Bx9hx1DZeuX8Y3E3zZRoySmKjTIe32SLsDdNpDpX1U2kOlHaSKAp2qYqRsByfig8eEwICFOK7Ei5a7egoohPK11guy6A3B46xvJTnZJorbz3iRnCEYihdDEZeDIb1qpRRPaJgPJmTpBV4F4CAkWGPw1uDa4jZsg3UCj0IQmBnnwpwdIdzi1MA3rvV2+MUpvTwfjWiHHooAjlw7X0kKGXwn0oAOHhThNS5WpC4hwVBNC6pxgdYNcWXDdF+vkd0Vah8zbRqytYwo3mDv6Jij8SmmsaiWmdKRQ8hQ8R5ZMAJs0EgRWJS3NLVhklfMC4PHEolQ86+wKO8ZrK0w2DyHn72FNSXE0DQ2DH/tgMolduyZVZ5COmTjqVRKYTMK2+d06pjUNSIucTpGxSWlCQu4EF3GjQcraTp9VqMu/ShGaon2gkRq6rKhmM3pZF1krCicDxvW6YyiLuk0GdPJDOclaxvrXLn+LM7B/uEhpap4/vkXeO6lF4kTwcnhHj/72bt0sg6XLm1z9cpFzp8/S7/fIYo1iwGc03nO/fsPOR1PsdYyzQusM6x0I9bWetx86RkuXr1C2hviRQyEVJoAGttwOJpycDSiKafEqibKUoqmS2FyfGOZjgsaOYaLc+w8p44UNhaoSAIla+tDuoPgZ5FIcuNorEd2NNZDMSuwRY0rK4SWdOIeUZpQhxmLxNKQiC713NMkgPIcHx4xmxwRp13iOGZ1c5O4P6QqfnmDLPyKAxTfzlkRJvg8lsb51tUmBNCA3YfqnmB2F+oc6ppQPtWArcNdpATjoKhhnIedjRLQX/Vc2IAztaC3DcWJ596Hmt1Hjoczx5WLitf+7pAoLtgrNP/uzYZGS565GdHXjt7A8P5Hhkcz+NI5wW+9CN0VQV5JRrue/NDiSs/EwiAVDCKoI09hBELHbKQCJSyfPAyLknQNH38KUZISS8PeJHhRIimIlaCrBM9tCmbTiP3DUK6TdAQ3L3m+/4OGG2dr1Lxi7Zxhd9fz8V3Pztjz4sUpSVMyH6+xVxv2Dh2ZthwfTTg3cByeeG4dwG98vmY9PaIpLbvzDITkk7sl85GnNp5JLZhUHmtr8srToPlf/17C114AISw/fjvjk7uGc52K+aRiPnO881nDw72CM5sZn3uhw0sXEobdgsfHCd+/5Xn5C8O2vmoh4gc/hJQqAAJYTuoNA/3CwrO8gLfni4CWz2g9Jb6tMpfBmS68aGn/ABxEa0Zd1Ncvk0Pt49u2VTSUaoRSM+d9GJKHCkkMAd6aJXTy7eMsJ/EsYryLGPByd/1E2llEWcXyvQhUm15iEYdeSEPBBdnWqjuUEkgVYao6lNJpGabcRhFFXnN75x5rqxVJusJvf+nXeednb/Le2z9hzhydSBKpeGl7I5guk4iT+3c5OneRDz/9mJ2Hn1G5kq50lPmc2Hdx04KoKdEYxnfucPjZXT699wndoQoauLfEsSKqp+ze+oC92x/x6NPbZFpw8dwFzt98nsGlmnd++peIpsILT5R0SLIeujNAp3101kdlPUScgJLBAyR1kNZc8CS1o4TCp7bIay/PggW4kEuAZxcysffLMFWwIUvs4lh6lh0mwYQcKBYh7eLkWkpxjpDQ8SJqj0ub8mrBYujisVhrKCtLFHkiuWj6lS3oWDAmC9knnL+1NCgbGowXQFy48AakC/4TL3woxQpjugkzk8ELi9UuROpVBxc3JE7h6hJLTS0qbJGjkdhYYpHkZY2LPEZpSieZuoS9+Zzc1jgBUTBTobXD+opqHuKmjYJOQOFhkrJT1KWhmtsw5dh6tArfSNkURLaETLJ+/hrjWwOMMagkADprQWnFcCAZz2F/5jluHIiIaZ5SMOCgEpRzyyCJ6XYiJDXdCISqKXwKqod0YcCljHv4SCLjCBknuNrjXMR8NkOJkNArK0duHUJYalOCFdS1Iet0OLO2RZx0Ga6uUzeGq1cvcubMWSaznJ2dBzz67A6JaPi1b32Dmy+/xLkLZ/HeURRTHj4+wlrPdDzj5GTCZ3d3+Nmb7/Lws3vMx2PQntWVmItXtrj63CU2L58j7XaIlcJjML6BdjiklIL9/RNGJ2PseMI6NXVVYysDTYSuDM24pBEHMF1nerxHIefoFVBK0l9LSLRACxsmZjcGYSxSanSSYMuKpqoQNoxiiJMIHUcIrVDek6gwXLJB4YzGNIayKhidHGFsTSR7DFZXiXsdVBzh8v+kJf5XG6CwkHeekniW3QEW/BSaR4L8rqM8EpQTaIzH1MHsimU5hbauPbMCRtOwH10Zejp9QbYWKpTz+57Hd0B3YHff8nAKxJ4zQ0dvbUZxYhlEnr70fGXDEZ3WPDgUjEbBJX3qJD+47xEdwd/9IuycKN66LZnOHUXtuLujubHuWO86Bpnk3qHEx4phVuIl7BwL3vsUntmyDPopI7vKGw9yjDWsdiQ6ExSNY60DNTWXhoLHu4ISSW9gODjyvH7XMykVL5+37B7Ax48FUSK5fxDx6LDm2Y2Gu/eOubNn6PRiul3Pr71ooQlX3rxO+e7bmrODGe/dhoeTEpXsMplb3pkIkkzynS9rvvmCZe9I8RdvG1ZX4JmNiDfejtjqTWhmOX/8hufSNpztC27vG0YVDFLIreHVZx2Pd1c5PJrTmIpPPjbc3Zvyu/8LntS/t8u0bAmHdi3nSZgy3BaLPTxZWKBlLvxTKHbRD7GM+IbBbEKIJwmWFgiEP28Lz0SYIiyFABV8C7hQnS2EAmtDOsaBFQKhFEKrlqlrfQttemTxwhZm2WDYbZm9RQQ4/BGLT+Hp9xfSIAu7QfAv+AWseUrG1DrGuYaVlQ2SbsY7H72JlA/IRI+P3r1FHAu+9JUXeeP1v+Jkbw/d7VBLiccRxyljd8QnH6VUs4rVLGZ/5CmtZOQk8YULGDR/+q/+iDMP73H3g0/JEDw6fATasLHSZ7jaY1LO+bPv/RH//I//B6aFJa8tXkVsVSdw9Iit5y+icCjpEElMp5OSDTrE3QyVZog4hSgBFaNk0spbLXzzbQmdD+fDEgMuaFaWWafAjbUeJUQwIYd4uoB2aOSC6vLStQwYSKlaWc6z+D8BoS5fCxAW6VrAiw3SmxMIEcys1ltcUwMOqUDWhvnplDhNcUikVjhnqUuDa2w7ADFIe8pYIh/MtK6NKgf/SXgdCwK9rcto+1TCd8V5B01IuGE93oCQKcLm2HlJPZ+gvcFFgtJBbiSNUAiZgoPUR1S5pjvoUBclqiqRDqxTxBg6InB7xjoqYQP97xXWJTgbI62mcTWVNcSmQQlDJ47RUjLb+xS5mWKGK/QvXGKyd5Gi/IhuPEMloRm2Mo4olqyuejpTx/6h5piIgoTjUrE7axAiJislAxuhXc1GLyOKGyonKXVMpxsRqwSsxMYRTZxhREwOlLnDiRgnLZN5ydQYmjimnya40hOrhLJsWNvcYn1rEykier0e07wIGxpluXbtAvdufUY9OeHqjQtcv34OoSreeuttptN5qI7vdKlLy0cffMz3v/9D7t1/TBQnXDi7TnpplWwQsbIacfHCGbYubiOzhJPRCSqKWFmBOBaEDZAFKSgLw+hkij0ds74KxlQURUmdG+IGehai0Zj8k49R0uAG29gsYz6xbAw6uDKnxiFVhfcaLxVE4bvgjMFZi/CWSCuSKIZI0wiPco5YCoRs0InGNBHeVozHY6aTMY2p2VpdZWVzC93rYrzE218s3fyP3361AYqS+GjRfMkTQ2Mt8MdQ3YFi11OcCso5mMrjDIgGXB0uVo7QOTKvBXunIBxsrkBvAMnAc3osOH47FJqVVjDqeu6eStCWy2vQVPD2n1oaL9i5a/jaUPDFoeDBJ57v3fZ8NAqXjto6aiN465bnCxcVr3xOMfE9/vzHYzIcF/uWxsHVNbgz0VjhmeUF2c3zrKwKoqnk448OOZoYhoOK08MdbO3Y0PD5dSg7ikcnjhfPBQZoNDLsTx2F9MSVoDmFeQX/5nXPu7c83Ujwd78lkUryx2/Azz6Fh0eSlb4lS+Dc0PPxI8/+iUUbeDjyTExFV+Ycr8Uczxq+9IInpuEDL7l94Hn1uuAf/aannijOv5pw7Zzgzr7GEnFv15GclcwLxfpA8fbtGXe6GZ2u5//0P5fEVnMyV2ys1nz64QH9jkX6oFvnedkecPFz/11eoP1T7MIy7vmEQVmYRINBkpaqF60s6JcPGXakYT6KdwFQLCadah0u/b79J6SV28fx9klAaLGrbc27YiHduAVgAGtt+3wCL5ciVOjkWaRzFtHiJWm0ABk8kRaWvwueiPA5tNv4pawTZDAlFc5aBsMuvbjL0e4BqinBZ0hnWe93WUkiHu0+4Hvfe4CxOV6FgXQyifFNyWx6AkTc/tmPePHSc3ztC1/l356OcRF8dnqKnYxIkojP9h4hdu6iymDILSNHYxuO8imV8zRa8tHObSoBKu1y85WXeeut99ieHxDNu3z8wSzQ/1KgdYckHqLTITrroOIUnXZRcYbQIT2xiOpK4VGtB8ktzoWWDfHtuUJ7/IVQy2Om2lZd2qSfa2fCLKYbLbxK0CYffCguk09OusCmyIUEJ9tk+CJeHhgb1zQY76htTTMeUVez0GhSOkaHR5wWBUoJ+v0BjfFoA7WbkAx6rJ49j5BpyAa1JllcO7CwBWNegGun1wrrUG2ia/G98EKgpAzJD+lBNaAcsqgoRyfk+YykAuk1JZK5gDqSJM4QNxqlHCqL2N09wDmD6Dhc4YlarTEVEbEXNE0oKNQuVOFbIgwQNYamqfHeoQGvBI0LG8SD+2/z8GDG1qtfJl7rsXb5RU7v/wTbHOFluwEwDuscUSLY2JDsjQ1FnnASR4yimCPpEDIiMtCojEQnGGFJhEBFDhVBkkRUVYVQESaKmXpFVXjGhaPfz4iVxgqDjFK++qUvc/W5m/zgez/m3se3MRI6Kx2iKEWICBl12N07ob8+4MWXnuWVV15idHjM/u2P+f2/+202zm5QOcPjz+4zL8IQw88+u8/B/hF3bt9nMh6zsjLg86+9glQOLaDfFwy3OmyfHbK9tUk27NHr9Ug7KcbV5PUEoSSR6mI9VJXl5GSGbZrQWmw9mtBk653DG4t2jo51cFJhjjRNDOU8IbYV49MY6RuytIuSMQ6NXF1D9Trk8znz8Ywmn5HEmjhLQuuskuCCJwtv24oER5QmUMwYHR1RVyU6TlnbPkucZWEKt5KYpvplVvbl7VcaoCwik+2lA4xH5hK77ykfeop9yMdQTgSuYTGhnLr0OBMWj8ZD3sDJzGMa2F4TdPoQ9yR5Aw8+hWLu6F+WdLoJXkh2Dkt0BM/0BJPG88kPHdrAdkewfkZTOANzy3UrcBKyMyGxM56D1IpqNebiVxW/fcbxwY7k9i3P7950rK4Ew11UwIPHnl6aIjLJLJIcjMYUtmEzE/RTeP5Kh5PjGXkd0xsY1rqWl6+GJsoPH3kenzrOrsFOLmkaKA1Y4ylKx4NT+D/+fcHVqzHjUcNvfR4ms5isC//49yPO9Epu3Yf3PnN8tBcMeK+92OeLz3ge351xZ7fmd76m+Dvf1MxPar7xquR//EvB73wz5XTa5+33Y549e4S18N4ngo1uzoCK06ni1r7kuKiQSjAuKn77q4pYbnFyWHA8nvPhXUfiCooZPDyqOZo7njv7BJgslnOPx+KXFSELVkS0tfLt5nnZMYJ4crF2bfnY8vftI7q2ol62qQhnQUiF0q0xUqhlH0gAQO6JhOBtWAhlGzW2IV0RvCJPpiQvX73wy/fhvQ0LVWuuDTWDC1GHVtJiuchAG3kWTxgB5cPuWXi3vKdAtUlah9aKxjsmkynPvnCFHpbY1rw9eojD8/JrL9M1EeP9h4Bk5AIzEpFx4fpLfPremwzTPolxyNoxuX+ff/tglxMF9aDDYVlyu3qIFIZIh16gnlJQV3gBca/HKTC3hlpI5rHnzPZ5jqdzPn74GdMm59HBI45Oj3jGnWWzFxMnKVmvT38wIOt1idIwkVirGKVihFTLWUSSECd9mi1ZNL0qpXBOYN2ikca2BXgq+IFaH4mQ4Lxtz6lF02vwjmDlMmYu8MHnJkQrnIjWx7I4q8LrUTiMk4BBektVFZT5iNnhLqM7H1KNHqF9TTMtmNQ147Khmuf4ymFNxVBJ4lTRP3cB/9wXSLafJVlZRSiL8MHDIP2CNvMYT+t1CQtVBOCCFGls+7lEPsx7UgIiSdR4YqDKJ6hmjtThGuKIkTKl//+n7r+DdU3Ts17s94Q3fHnltXZOvbt35+7pMDlnCWk0kkEDAgkBEkcuIVO4jIsyFIUKGx+gbBAuEKbwkXQAGQwSKM2MJseOu8Pu3r1zXjl8+XvjE/zH+63Vw5HO8UwVLlvvP3vFb6293vDcz31f1++qaQ4tHmNQlDinEa0ltjcvUtgM4R3KV8LbUCrq9QZhoMknGc5V8EmPxfsCrwWp1KTGI3ODmLJcxoXFeI8Wu6zd3WHEkLC5QqOYoF2EyTVK2aq4tGALh1WCZkuyuBxw466lsKDrMTWv6Q8mZIWh6BfMNiIOnzyDcwXZuEcr1MhQ0mq1sE6CDJC1JuN+QufYUWyRYXzBOM059+hjBLUGa6vb5FlJVhjmF+d54NEHMYWh0Z5l8dAKyyuLLB9epFavc+P6LV5/7kXm63XmFpe5fXedG7fXGA7GWBkwHub09vbIpuncnZkWtUaNja1V4lgx06wzN9dhdr5Je6bF7Pws9VYTHWqUDrB+ynfC4YVDiIDRJOHGtVv0+3vM1SwhEuWh1W5DXhCbITVZUFOWRqQpR2v0Vwts6mi2F0kiSeQsPk4oSk9cbxPVY0a9kuEgoxhPiLVAhI3KyagEWmnyosQ6QxRKgjBEhZLJaEIySRgOh3gEjeYM9XYLFegDYOTbtKfv7/gTXaBUYraqhS1yDz0oNz3ZpmeyC+kAygl4U6n4bVkxS6oZMGQljDIYpp7CwkJLEGugFATCM3tSsHgKkhRM5hl7gZAzFG/s0hsa7vU8R+qeKLDoAKJmyLDUnFgoURLevO7BSx5ZdGRGUMSwvOCY9BWDm7Dz5oTRHmzn8FuvwV/4qEdZuLMRcPRMzPzRJUye8cqrQ86ekByuxzTGBTc2DAM34dhMZRddn0gWQ5hzrlocpw/q7UwwTqGfeVodxQfeoVnbsQRN+OB7Fa9fnGNrtc/x5ZKzi5L3v9uzGCuu322xPY45ND9mlI45dUTyVz4Ly7Wc24uCd2aSBx6A1fU5ett9FmcKpHHkiWOzn5GnA6w1XLxquXTNEMYxjVAxKhxnz8IPf0xy4Q3FhRuOY3M1bt1zTFJB4AUvv1VggVq9wSgT/PhHS86eDOnzdhdhv7FQOof3an+jXGk2po6N/Vb3QYdkuth44acBv3Lafan0AM6aqvFgDTrQVZteVO167xQePWWfaLyXB10YP8XlVwKEajGsJg2+cg+oELBV+q+dujh89ZCp6iZHaQ37WP19W+yBR579kVKFOd+3z/uDhXgK+Xq7PzRdQjVSaaJ6DVNk4EqiKCTMLWtvXqSjBMvLHWqBoGcL1gfbvOPIfRyabSK0Icw8wxJGA8OLL71FPQhpzM9gR318XtBcWGA3K9kc9+l0FjmyMksy7tHtbiPigCxNyI2hrRQBgn6WkAqJDQK8FgijGQ/GRI0me8mExtIim/mIdG+DztGYlc5RgpoibDUImjWCOCYIa+gwQuoQJXU12pFVfIGcOnP2e2laAmrqWJqKmKsCd/8cMiUGy2o0N9X7SKmq58n0mpFM7eWCSmTqHa7I8Uri1ZSH4wTIitVxoBZSlSjaGospJ9hkj6S/QVF2obeHntykHG0TBYKRKVnv5uzuDCoYmclpmZSalsh6DRFa+ud3iI5u0nzoKaLWDDKoI7XGi3I6rtovlhVO2EqYbSsbsqPKdWKa5q3lPl1YgnXkJsVmE4JyXOlJlEDGIZ3WDFJGiNYy6fYqh04/zHBg0M4QyRrDiSF2AqU9s/U6K0dOUZgxYjLEJyADjwolXockRmOFpCirYs4jsVJVLh4gL3ZQLuP2pU2KSY0gz1jq7NJekgTS4nR175sMSuHxMUQ1Rb0d4VOB15paHBCoGpP+AFvmeCEYpUm1gEZ14ladpcOzqChga3uIdZ4xsHz2FO94+lle+Oa32NpcozG7yPYoYef2BVwJ6SQBJTj70P0sHTnEbGeGE6dP4bVgZrZBb6/Pq9+5yJuvvM7WrdvMttp85TsvsjecIIIQrQOcV2RjQzoYE9Yki8sL1BoRk2QE2mE8BJEmiiOazTZBEGPKalcdxSGt1gxRVEdPr3vnLNY6rl27wd2bd9GBJBQe4XKyNGNkLPPNOs16SUuUxIGjHllKl9Ed90nlNpl1jIVHDIfkUZPcemrtBSKt2DOCwe6IEI9v13BljmvVabaaeFlgi0ofpoM6OtTkxlMYw2A0xDqLF5J6q0Vcj1GBpEwswhuCoApd/X6PP9EFCh4oQEzAbYLpeZI9SPagmAhc6afCR4/JPd6CVKAiyMrKztvPIMtgvi2IArCFJ9YQ1T0zJyFaEXgj2HpFsPlKznYx4JmjEpvUGHVTdscVc2BuDg7Nl6zveDJX2ZB1DfLEc2NLUjo43oSTy9AzBV/5L/DmmufarkUD45Hl1jV44rQlzwUiTZktN1ntWkzp2NzSvHMxJWo5vIE3tyzOeDInUDaiNs65ZwWznerBOxsH7EwsZVECgpkI5luVkHZYCm5e9YzWt5mre2xWifEWO5Jbd5q8ccsR6QkhOX/q3ZLPfEKTjOvcW/W0Ykt/5LGF4O5qirGSIockVbx+KWJ5tqAuc67ednz3qmd1KJnxghtbhkfPKX7iAxBqx5kPQyNQfPtNS4MhZ04ojKzcNHu9hKJX8PijLR4+EXJnM6A2D98LfN/XDzg33cnK/RjvqTD1bWVH1eqkGtW4aUHi98WlANIhha0KDqhw8M5Oya37SgSJ9xaHqlzAqnLnWAvWFwc8lv0OC0JiCj/ttlS2PUnl7hDSTRcUB8JVQsH9qsOB9BIh9PRnVjqVinfx9shnum8/uA8kbxemnsrJY0vHzEyTE/ed5sblN4iFpVFa8ntbiLBOa+kQh+aPMNi+zRtvnOd4PaQ9G7CztkFLawId05xto6I6q6s3mSR96o2QWAW02k18Q9CMAra2Nih9gheWOAgJGy10vUmZ5+yMJrSiOqWWdCdjZBjR6nQIm9CZWyKvaWYkNDsLDJIct7dFGYVIFRBHjapzUq9BUEOFdZSOEVof/P0PshR5O1SvKvy+l3MzLVSgoqfuF4DT0YiYdqWm0NypjXv/WvLV6VRTkal12Kl1VU4znUovq1GYqEL8SmsrsaE3TMY98uEmfnwLlY2IAollyMxsyIxaZjQesz3e5c7WkN4wBxlWY0ELrTgmqM+TWk1ruEVx8zts+jGLp56mtXIcoz2Oikw5zQg8AM15Z6cicDvt9O0XKVVRYqxHlxaVltg0pcxSZGEpcPRdQEtJVFKg63XG/Vs0ah1KYrY3LoDx1ahKaCIBBQIfRdTqs2inGai1qrSWVcfPekmSVfddYcuqIEdgvZuK36H0KUb0EU4SlBpdlPgyw+QOUVbnF1GlMRelILdgrUbrGmluWRttkZSg0TSimJXZBZYX2wjpwRSEoaY9P4PVmsEkZZSXeOsIG3V64zG/+/t/gJ1kSBlhfcjaZh+hJHGgEbWYeqxRoebMfWeJoohJlpCXhhs3bnLr6h3efOUy/e1NanHApu0zznK8iikd9HtDer0h2mkoClTiIDBsdzOiOGR+vkOoNGFQY5IW5LlHJjlaSxqzTZSSBEGAliFKTftSztAbJrz4wmv09vroQFALAxQZ4yxlu1uQ9FPaTYWPY1Qc4EWKNw6tYNztMhykmH6PpDFDLWrhpCLsjLFZzk4pyPoZjVBh8yYq0KR5B6ksWiuGgz5xvc4kdRQjg/OwurpOUZqqkLSW9kyHRqOOFJJkPCKOQ+Io/IGW+D/RBYpMPXLLY3Yg73qSASR9cCmVSqwAX4KtNpDIALyCwggmRdU5KQto1SDSniKFeihoLghmz3rCRYGPPXYHuquCW3cdSydSlo9H3Fz3bI0CdrMSqRRxXaFCy670bKzDyEOrIyn3HG/ueJpasDQvuN6DnV7B3jb0CsFT84qFpqceelZmBRc3BZspjHPJ9m3DsJ/RGzuWraA1Z0kKcEYwqyvEdaAVaSYY6giXF9QLSGyNCMF8zeAKR1o6trY8l685luYtm7uSb72qeHSpWhiv3IabO56NHU853OLsnCAKDKMN6NQElJaXzisGQ8e5Fbi7pWi1JEdnx0xST3/okXHIazcytK+6Rzf3PFEk+MAjjnSSclMKPvvBgHt3Yrq9gpOHMoqJYHOrIMnhdleytpvRbElOHlJ0E8f7nvBkY8nqjuQsU/EnVDtcX9loveVALeur6N59tcbB+M9PLZhuCrrCetz3aj+oeCMCU7l43NsANqhe11k7dfXYiiA6JdAqBN5N8fh+mgHkVUXyFBrvVJVN4qfWUmtx3uB9BXYSwk4psRUDxU3pJtPVpvrdEPtBuhwspK4qSpT34BxKgBJVKqlUiiK3nFw5RoTnh9/9Tr60u8rdSxexacZSp80jD72DJ5/9AN3nFdfXbiFEyvMvfYumEkibIzOHilqcPHOSMO4QSctOb5teOsZ6x/b1G5w7dY7/7qf/Mht7d7hw6zXWdtcZDzPGoxynAt7zoU9y6cplvIcPv/99JFlKWKuxfPgomfEsHD7C/Olj3NrZ4IUXX2MhqhEqS3zvOtJKgkaToB4R1CJUHCOCEKGDCu8t9wuUCsIm5TS6ADfNG5KV90bsG88VSgD7tnAx7YIxZcRMu28Vv6YKY9xnoey37PYF0eZA51TZgJ0I8L66ZkpTULqcbLhH0V/Fj7cQYkwtMITNerW46DZOBuQ+4c5Wj2trfYaZwIQaXVQcirnZNuceeZSNtOTe9iax1zQHfdTo68hBD/Hwu4gWjhFGDcrKWQ2UlTzF+el1ZKdTQD+NeBB4pcBWdAaNgWyItTkuCCjiGJEVBKKGyxyJzAjbnpAapx78AFfu3GI82mVPOnouAalQztD0jsJquskOFGOsz7Hh1O3kPBNnEECoBGNkNV4RiiiqUVBFChQmRRd9rAsJwhhtJoTaoINp8F9ZdbGkkkjvKVJBklmSsalG2KkhLwxeKlozM8w2m2g81lmCUFNr1BmmKSYb46XGSkmj2eD0mbMMxjk3h3cI6nWWlpfJyoKZ5RqzczNs3r0LueHQyiKz7TluXr9Ns9VgNBpz6dJl7ty4x3CvRyhgdmaGSVnS74+r8VWa0h8n2MJirIEiQZmSlUPznDx+jEmRkJUTTClJh2MOHVohsSnd4YSjrQUK4ygLc+BMq7rAEusL0jTn9dev8PxzF7DOgjPkRY6JHbkU0OpQRgF7NRAyZ46UWedwzmCcZ5IkWOVQyYSJ30SKCFVv0DiUkE0yNlJLMcppxpo86xDVQrJyljwf0G41yKyltAW90aDCdXjB7Tur+LzKJoqjgIWFObyxjPd6FEkKtmQw7O9frN/X8Se6QHEbglxDNoCkC/kIhKk67iYTmLRiGQgNOgTjBKWddk6GnjSFOACEYG8E7QBaKzB/zhMdAxlXFMmsK3jzMkyMYOUMxMuSstFiICWiV9DPPN+8NmLeGd5zyNOoCUbbgr0CRlpQGgiiiokw6lXxBn0DQivumxO0OpKvrin+8E1FEMcMJo7xpOCYh0YBbQ3johpHlCVs9mCuCRPvOXtfnbTQJDspNWdZnIHEG1Z7kmYQYOcdQVjDlgVxWUAmWWoq9ro1vrLhGKcZa0NHPZJ89WXNiXkHueXuHlxY8+SNgMNXDMfntshb1aWVmjrfvhyx3My4cWvMq7ctawPDYluC8dQ7bX70T53mY4/coEHBeKz59iuOIoXdtQQZStIU9kYBmfFkWUZ3DIsriv/954KKURKEOGfJuyPm6u0DEfRBlwSBFAFSVFkX3nu8ne54hat2TvvcigP9yduC2H2FpBCVDdPZSkMip4jng24IstLCToscL6tCxglfdW2ER2qFMFPbsq/KCucrAqdUmjiOmEwmNGt1JsmEpDRYVJWl4gW+ogMe7PzF1Fk2RUhQFTLT/Bzvqo6JlygHgXNgShr1eqVBMDnLswsMexN++EMfhfGQF37vD5jcvEl9kqIQ/Kmf/Ane/8E/xb2rG0QiIJJVSnZhEoY+QCsBZYkuJ/QHO7QdnFxe4sFTJ+klBc+/9iqFd4zzEfVmwNww5K/+2Z+hfXyJ9fUdXnrxDf7Df/ovDLp9PvqxT3B3dY3u7oBnn32KQ8ePcfKBc1zb2eVud4+3drcZpAUzy4dZmp3nyHKHzWKE3h0SNhoEUUQYBsgoRIUBOpgyIKbjLpBI6SsRtK86XdXkpwqD3BcSCzEN5nICvKkKkKnwlek15acCUj8dh+x3UuSULXOAr6fSdWghEaqC3imnq4ZukZH07lL0biBNl1A4PDletXHBNPcCza31bV5+/S3WtvuMhpbcghAFWhqOtEPOnl1hvgGjyYB1k+FcSFqMmXEZ8vbrTLIe5ZEH6TzwBLaziBcab6EK1d7vIkEF1XlbVCu8nI45Pb5MGQ33EGWPCrZfI0NRxIq55ixLMyuMbEZZSnbLHKeaxKFDuBE2k+QopFA0DURBgIg02bjAFaa6vYzHSA9OosMY7zW2sHgzpRlH9YOoB+sLnClw0lMoRxRD6TPiKeFbICmtp3BgnMQYTz4ukV4RCEUt8GgtadcbzLTqWGsZjAyNRkQQxRghyI0lKzKiqAEioNaaobRQZgXJaMDp+05z6PgRtnd3aTUbNJtNWq0OadlFALvbewxurzGejMmyHFcaXFbSakQcObzA9u6Q/ihjUhjSJGMwGlMUJWVROcJqSrO4MMfx40cIQokvCjozTco0JB1NuHnzJjMLHa5fu02ZTzh8ZIH5+Q7eVxubQFXjXms8vV7Kl77wbbbWt1HSEcoQGUnyOKQ0AbmSWBWyJhxjHTISIZPS0xCSMZA4gZeKoCiweUphh0x6XVR/yDi4R9cEhFoz064jZE5nZoZJmlAWc/R6HhVFyCAmN5I0K8mKgrt3VtGYCuTWbDHJJuxcuwkGnBMYPMYVB+L07+f4E12g5INqhpgNwSZvz4tNUVXcINBVrAAlnjKDPIfxBCYJhLoSLu4MoIbg+HHPwn2e5klQrf0fIhhsSVRDsjgjGHjN7k5MEGiOrQgeOFljbqHN1dsNbr20zpn5krgmiHA84gWFE9zowgNH4NSSxxSeOILECG7vKdYmEav9gOuDMU0lWIkV7dhg85Ll1DMXWrqtBhfWEzZ3BcOR51bPkzrB2VMhn/hRxe61nG9819LLJa9dNzTqJadPN7i+JnnywRrPvKvG3Tcsw1VBaSSjPY1OHSas8dg5wafnLZvdgm+8afjmBUscCJ55GD7xTsEbN0v+H78Pn3zSEyt4a1Xw3LUBTgY45xllnsJL3vOY5uMPO169aNkpSz7xdMFkp8adTc1yZ0wz8PzOVxVH5xyzrYD+EC5vFIhQUa9JnnpAcWQR8rTOrdsZKwuW7a5kkjfQzdq+4nXqzqDSa1iFE5VO46Ajj6ukG37fFAoHroppwbLv+gFwttLtVC6IKsGW6c5Tej1NMZb7L0PVmdnP06nEaiBRUqPxGCWwwhFaSc04oqDi2Ggs960sc+XGDeJmi8zBOE0r8WzpEZSIaZHCPhjMMdVDTAsvVWloAi9RFiKhaMYRSW/CE+eeZLM34Pa9NT710Y+zenON3tYatSxhvHqbsruLNo6Hn3iWD37sR5G0mJ0xdBo1Am+QVO6l3FVMA1SAF5aku4bY2mCl1eL44hH+3E/8HKcWjnG3f5u7e/f4Z//3/wvJRo93vvouPvNX/jyDvT6f++xneeLhh/m3v/lv6N29xusvvMjubpdvffX3OXnfGT770z/FysMPY+WIG1duMn/oGM8+/ThzQcyxmRbPv/4C5TBB12voqIYKasjpLF8reQC6cweDLjkVR0/fmxKFnZpac/3ba7RHVOOafRmR9VOhrZiKkPfJsxwUjFLKg2K1Gi1KcKCmnRTnLdYVJJNdku3rZDvXiFRBGNdwQYRTEd5Lyqyiwa6tb/DchSvcutsnMwbrQGKYD0uWgxpHDi1gk4yhv0Jbtql7CHTBuF8wkmD0hFZ6G7cxII0ltROPY2qzOAKkm5bvgspR5uz+rYOqSmysq0Zh2jiEs0TOMRinFLmkNrtEe7FNpAUlOTafMHKK+pyi183opglhIQjKgByL8iFCVSGFw0FKOTG4DLQGEQqcloRBiA80TkqkNUhyrCwoy4CgOY/UmloDgr4jTS0eQdCIkAq8cnhNBZZzHqxDTDWEgRJoHFoaaoGiGcYszM0ipSOst2jNdBAmR4cKq8H6EtAUxiOUJCs9Wzt7JP0hR1eWePqJx0gtJEmCtSU7O7uVi3AyYW8HWvMrtJozSBkimTDKJ4zHJXFDcHdzi34/Y5R6DDnWOZq1OrJRXTf9wZB6EDEzM8vq2jpnWicZjxJm52bpbe8RSIWyCpfmVUXmPfPzC7RabQCKsiAIDBrNaJRy9fIdLr91u5ItYLEWRFinc3SF1beusZ0OQFjqcczAh4yFJLUFy6okl45CKNK8xNqcRm4prGPsIB936ZY9Bl7T7jRJkoDBpE+jXicMI7a3W4hA4ZVE6JCk8BgHSVpgioy5VkSRdIkbirt379LrFzSiJivLh6g3G1gCht+/BOUHL1C++c1v8o/+0T/i/PnzbGxs8Nu//dv82I/92MHnvff83b/7d/lX/+pf0e/3ee9738u/+Bf/grNnzx58Tbfb5a/9tb/G7/7u7yKl5Cd+4if4p//0n9JsNn+g32XSg7quihLdAJ9DmVTdTKl9RW2UHiMht9XHJyPoDsA7waTwdDNB6ODoUc/RR2HmHKh5QIIvBOmuYHugMR1NFkheX43oJxF390rGmSQdDzg2t8f7nox577MhC4khNZ5AQeg87zgE1zfh9bvQqcOZJcFcE95ar3YBOyPDclTy9IOSGzcLRlt7zDWg9J6oEAQIXOEJ4pgX7qYUmSNH0B0Ljp1QxFmGmThuDUEXgiOzkv7IkGRjji7X+MhHBZ2ZEfcuC0YqYEllzEhYlYIHj6d88P2a4aYlHYc8ciynPxY8eFryk59UTAYSk0b84dqIf/0Vx2JHsjgPP/wuyWa35Pxlj3OCx+4L+aWfrBEz4eQhyfkrJXXucHe7xtomHJ6H8ciRFIoXr3vm50M2djIWlx2/9KcFSTdCBIJGyzLes3SHgpma5cKlnLd2SxaPzvGpR6u8meqoBKQHHRTeHn9US9D+CGWfj7Gv3fDTz08XlkoxPW3vV6JZMU3Hc1OwFkwFmFMHjZSVGFN5jXICi8VpcLpy3jhJFcInHYdaEbOtDmubWyipeOaxJ7hx7RatRovd0YhWVNn2+iYDoSttC35a+Hi8rEYMVujKHSQNyhkC52lHNZ558gnydMB3vn6D+U4D0Gxsdbl4+QpHZ5e4c+k8mxffoKNKkNA6fJjP/uW/ys7IUJOGP/zyl3np5edQquK0eFGNpoQDoSJKYQCLlpbd0R5pr8/qnWvUYs1jjzxMvF1HtOq88fpVvvLWRS79/X9Id3uVJ598hB/+0c/wV3/2p/n8H/4+SX+TokhwZsirL25w/c5Vnvzgh3j3Rz7Efa0GPpvQvX6ZVy7fZjaOSO5d48TMHEEcEUSNqSA0RkhdpREDCFFFAHhx4BqXyKmwuTrlkqr4tEyzafa1KPtJ0H4aEeC/Z8QzLdSqBb66Tg50SHK/YFFT0IiktJZ0ss149w5+uIMye8SRRYgG6BAVhnhv8aWlv7XH7bVbvHV3lTurA7xXGFeihOVIXXHfYoPFZp1aTWJHBRSWOBxxvJ5QeM/EWyYZ7A5zYmVolhnZ9e9ihz306fdC51B1nXqHE7YSBO+nWHuH9B7jLVZ4ZAmmcGTDBN/bRZBjY8XC4jKRcNBfZxJYhimkNuLV577DzvaYYS9DWkloDIGsitmRq5gsJqmC5KBi4fqppqz6W2c4qymNnt67glGeIBqzSCHRkUOHHsaGrLQMlCesVXlGpgARVqJjfAVts66i8lrv0MLRkJJGXCMIA7wKeMczT3Po2BGe/8a3iZoxRIpib5dmUCNuNVk8eYw0LxBFiRmNOHv/faR5we07a4xGPWpzHYTV5FmONXDy7FmOnj5DbzKhyHJ6/YQXnnuT4ShjlFt0o05qNTvdbU6dWmJmZpZxb0KoBdaVzM82GA2HbG6voUNJkZfkSQmFIB8MqIchywttFo8uMLvc4fiJQ8zNtQnjuAq+xJCWI7S1bO+M+IPf+0bFzgk0ZeEYJWOWDy+hOws89Mws4eoad26vMykKpAKBpihCSl/FRljpsS5nmJYU3pIXhswGFVhQQOEKUltS5J6chEnuyJIuzm/g2He0OrwKKKygP06RyjPTDDk016Q0msk4w3tLVA/xshpdWuwPMuH5wQuUyWTC448/zl/6S3+JH//xH/8jn/+H//Af8iu/8iv8+q//OqdOneLv/J2/wyc/+Uneeust4jgG4Kd+6qfY2NjgS1/6EmVZ8rM/+7P8/M//PP/u3/27H+h3sSXIWBAqj82qzgmiEsEKBYWtHk5egCgE46FgYw9642oh6JeCwHseOCm4/52wcM4THqJCQRuP6cH2bdgtAgZBjRsbhrWRJ2rPc/Qdj3H1wuuszDcRwnFtO6HhC840NGEkpoAkx3zdcWIWdvoextALKk3BKNUE3pOnOTXtcWMYp7CbOGoNyaSoyLJBzdH0hnONFrvOUZYppYHMCi5c9rQjwUtvedYGMKsE5yLFwopnJwvIhiXXXq/TqRfcu2P56puGZ496Dq8INjckp44XRNaT9Aw37oCKNc+eVty3At/8HUE6lBw9K3n/o4rza4qPPGF58oykNJDngpoXvLXr+Ss/4ihMh8wv0GjeRSO5egWGO3vIwnPtmuR6V/HASXjpYsmdzSEzHcnnPh5gxgHDXUGzE/LKrTEn5wsC63n9SsHtoeY9j0Bq0+miM12cfIXyVirEq7By0uxvG/GAwvlqcZ3qJ6vxzgF5E95+Yx8Zvp8zXB2V+NYh9ZQCKPzB9+xTYYXUVW6FdwglkEGMkB7tDbosGPV2GK7fYmNnjzBqcv75b1OM+ywfXiBNLB/48Pt5/sWX0KpDf5TgEHhXgisQ3iKVqDgSZpqW7CvXVqQ0ykMyHDE3UyedDPjd3/mPdOaP8diz70YKzfrqTbq3b1EvDPU4xMUxH/uRH+f+p97By89fpJt2uX77TUqbIKSitJWGQ3mBswJnKt5B4QoiJfC2AB1z/tprXF9b53/105+jERiOPPow7/jRP83NK1eZN5aXvv1Vvn3+Rc6/8gY/+5f+Mr/4i/9bHnniGX7zP/wnLl+7TuEydnf6fOG3f4fXXz6PkqKiT2ZQ5IpmFPH0uaPcN79ELQwJohAZhAgZVOd1ClLb1yC5/SBQURWwzguUpBIiO4nz8iB00U/F0cpP8f/TkVzVQXPsJ1QHB4WpwFhX6YqUxApDgCZUiswYSuMZ79xguPUqlH0aQYe4fQi7Hx03zaEJypJJIvjmi69z484qmZdkicO6EiU9p9oBDy13WOyE1OpQizw0auSjApv3OT1fY2wc/YFnd2gZZp69vkVIqOeb2GzAxDjaZ5/Bzx3ClUFl0AG0dfuermlWlMVbg3EFMhnjdjcp0z61cOpecgk7wz4qHRPONEmDOlprkt0tslFJ6S0dl1bdRKvJvEUrSxzGeF/gbEkWeiLpCY0ndJY0GVNmI0rnKcukSlnWMc5LhpOycj8pkLEnbEjGI8fOpCCqa5QFyqpY3C8yq41EdTdmxlJYS7M5g67VQYc8+PCjbG31uXjpJpPBgHedeye9SY9ed48gDJFK0em0yTZ20L6iQydpSn8yptascfbsO1CRZmurz6HlZdbCkNK7qtMT1Rjsjbhy7Rab3R4iboB2jDJDrzckt4ZJXlLs7JIMxhxanOXY8cMEqsbO1jZZlpLlCd2dPbJRzu2bd5DKEzcUrXaNhcUZjp46ytHjK4RhgEdijCCu1ylyx9r2Di++cIlLl64xSVJc5nFFgTGWSVqwur7FJMnY3O6RTJJK1Ra3mCDIncKkgrkowEhHicG6AEN1z4dGgvOUzhMpSVIYpFCUtiQroSgtaWHIjSfMEpwrcU4S1xoY6yjKgnoYosImqAiLZ25xnnZ7BhCUZXkAK/x+jx+4QPn0pz/Npz/96T/2c957/sk/+Sf87b/9t/nMZz4DwG/8xm+wvLzMf/7P/5nPfe5zXLp0iS984Qu89NJLPP300wD8s3/2z/ihH/oh/vE//sccPnz4j7xunufk+duAl+FwCEBQh7Dmq85JWeVdoCqnhtH7GyOByz3jPtzZdGz0quq7sFVL+PFTksc/AIsPevS8QGjwBbixIN0TDCeCjb6kl0CvrJHZKqm0LAtqQcKh+SrSejyRXL9j8DOCmcMdkomgXS85vpzwYVVAKWhFHhkItnLJ/Jxlpu751mWHE4pmx9NpCEa5YK7maIaClYYl0J5DTUWjHfHm3ZLAlwjpCGqC7a7lf/iqY33PMrEOURecOibxseLiBUFv2xHPezYHlpev5KTGc3NXYHFgU1666NhLY65ec5y/6WjXNYfaIa+tlwQG5ucsZx/KOanv51yvx6P37fHqG3MMeyNOHc0JtOPRE4KTK5Jvvmgo8zHnDkkCGfKbXyoIhMSUlU7/XU+FPHLc8O7HYr79mqeMNI8/0ODzX67TUTuY3YyX3zB8s3A0tWB3Ah/+oOJDD8L6SDGCqk+/f63hp2vMfpKvmLbqAap4eE+V9+H2BalMd9tOTYf105TbfUCXs/ipM6NyCDn8VJsilKIqZhyVFNOhvCPyoI2jEdfxuk6BYWWhw95wlxs3r+DKEqcU7Ujy2uvfRSDZvF3gA8kzj57h+luv8b7H38P/6/e+TGqrxFolq12hlx4VBhjv0LIS/OlAMtvo0JQNrly5jiBD6ohJkTLcusPK4Aw//Kkf4qU/+BI+SXj8/sfJxxNSLO945J3MN+b4wLNP8a2vf5Fu/zZZPsQ6cDKgWg0Eznl0ENKZmaE/7mFtRhFoxkryzcuv8lN//i/wmT//Z9nNMzb6Q2bnl3j/u96L6/d538c+yK/8o/+e737xq/ybf/cbpMWIH/szf4Z3vfcDfOu55/md3/ttXn79JVJy1jZugvWEIgYXIQiJ6/O0m3WUUkRRjAoCRKDZ58JULJp9O7FAIXH7MQFQaSuYOrHwQFlZkj0HImk7HQVLIatxAb7SAElVve50tLbvuFJCTePpq4LHAOPJgEnvLvn2t6j7LrpxCB03MEGFAPc+BOMp8jHeFrz25lXeurdFlkpKqXDCE0rLiZkWjxzpsFiXRJEj0A5nPbU4oB50sIWiJgQySWnFIbtJQVF6skIyGhVEzZwwsYidS4zLAnX6GaLZ4+Rm+iys7GN4bKWs9h7rquu4XgsQEeTGU+oQl+T0d9dxCmRrjtEoJWHAJM0ZqpiugLrS6FISOkvN5NSUIA48YSgxVmCLKoMnUGKKc6hE9j7JcU6jihThSiQRYaOFTZLKaSRBhA4RgfaCvT3DxsAThJJpvBJecuDSkmoaOxGEBKJGVGsgGnUeevopoqjBztZNtNa05ubY2ukyTPu0ZjpEBARxxGQ4JlCawW6Xfq9H1Ih54NFzdGbmSEcZ3e0Bcdig1+8zSA39m2tcubnBZJQyGCTMLC/wrve9m8sXrrJ67w67/T0EjlCH9LaH2Dyh2WpQn2kTxU1uXLrNzsYGQld6mzBQFIVlezJibr5GqzPP0aOHOHHiCAvL88S1EB1GOCfJMkOS9HFO8/x3L/Dbv/Uldra72KTEp47QO4xLuXPjGro8DEKRd/tk4xEijtG5JQ4kBWCMghxkKCmEJHeW0FhqmaVZgLMeJTV5TbInNTkKrCQpc9LSkpUWY0DkDqUqbVBejmg0GrRbHYKgRmE1TtbIrSIrJbHxBMqjpSTQwffYD/8/H/9NNSi3bt1ic3OTj33sYwcf63Q6vPOd7+S5557jc5/7HM899xwzMzMHxQnAxz72MaSUvPDCC3z2s5/9I6/7D/7BP+Dv/b2/90c+HkaAoJq/yaoKL3NfZY2oasPtc+htCa7fgfU+lFMOikTw8BF4x/sEi4969AwQTMdEO5BuQikFYV0iKNnadQRCU5c53fUbDDdu0Goodo1HL0TUFRxpSFRrkTfupNRlQrupuLwJZ5rQmPdEDlpzHp3C+rZECEstrBbJnR1QkeTISotTCyMWGo7bPbgz0PzQZ1qcezAi/X9OWO8FLNQNh1didgeWYLfEO0soBEnp6I0k465gJnTUZy07A8etniYrMwIpWGoDFNx3SPDV6/DKnZxR4sA5FuqWY0HKThSSOM/cgmF3x3NjY4t7uwOW64K66FGf8wjjGY0dXgbsbJR0/Da6BpOB5PUbBTfXM0rrKZF86FHBI4cMa7dLVk7FfOQxw+X1nMmmoWH7nDguuXUbnBQY77mwCY0mPH5ScPFGm0KF1Fcqm2J17EPWqvf2c3L2RzdiyrfYtxZXeOWpI8cJBHraCp8KPfy+ZZkpG6UqaCoU+ZRMMrX5VvbgKvHYC1DCMVuLeMfjj+N0k3ub62g/4vrGNomxUKsjtGIsPDVvMElKd7hDWIt44TtfpRVJ7jt6mJoOKYWkNAIvLFI4QuUIlCRqBEA1nw+toykU506d4Y6OuXbnKoun7mNj7S7nzjxIK6hx5dXzrN26hnWWztJhZs/O8OVvfJXJdsbm66vcvXGZL/3Wf2A03MHYHKU1QuhplwlQHicdS0srFKVlPPGUXmJKz2PPPMr/+m/8dQqtacaas60mWobsbu5x8cJFnnr2Hfz5v/BzbN5Z496Ny/zar/0PvHL+Zf7yX/mr/PgnPsaphRZ///90i+trqyQovIhZXDrKZz77YxxeaPPA6WW219YY7RXIIELpGCmDCr+NqPQlqhqz7avt5NStI6aBNd6B2x/JKZDCINFYL3BYXCUhqeIN2Ld1718fTHU/U02L9DjKAwG1NIpxWTBcv0iQ3qIRDanVFxHRDDoMsTpClAIzKVm/e4fheJdub49Ll+6QjavRi/RQjwznHniAR47dR8vuoLMeWibgS4RXSGUQ2qGDBq4swaeVO8xrSgSTEnyiqUlDQEkku/hxzjBNcY98ENmcR4oYp6pi3KtKV+PL6tknhMIFCltr4N0sstEhdatol6K8JJtMKMsc4cfgGzQWThJsbpKnA4ZKEjuIZWVhbgiFKR2FNZSmguAJBUZV94u0giz3lOQIHNqrKj+p1qgSc5Um1LLSC5qpJsiGrA8Msh9wSAhEXqK8JorBh2XlVLLgZI2Z1gwmiLjvwYdYWFrg1u27PPXsY9y4foOFY8e5ff06WVqwfPgkLs8RAoqiZHV9k6Q/IM8LClNy6/Y9drbfIE8NS/NzWCT98ZjxJCEIQrY3dyhyS73V4NwjZ9nYHHD75j3SpE8gAzxgvSEzOaoiKXLk5EmGg4yLl1bx5R6hVkRxgGxEBDpCGI/LPd3tAdeu3sRJiw+hVq9VnJRRgbOCi2/d5Pz5q7z8whtsbuxiCwNFijQlQaBo1hTNep08Teh3BwgPjVCSOEeW5wQyRKsIYxyZA2UtSVFgnCE0njmlaDmDR5EJS6IVXVmVByWCvPRkReV6NabKJyqlRfiAIBTU6p6FxTlajVlUEINqoIKIopT0BwlRWNJq1Kpn8f+vRLKbm5sALC8v/1cfX15ePvjc5uYmS0tL//UvoTVzc3MHX/M/Pf7W3/pb/I2/8TcO3h8Ohxw7dgxr991zlcDRCrB6Oiu2UI5hb52qONmjGv8AnVjwwBF45FlYesyhFqkecGNBvgl5H0QTGvMCO4DOmiP0AusHJKlBioDZdshCW9Bu6crzv9Pnvtjy0vaEkzOWo2FOuet58YbjzaDCYi/V4Nn7oC08w7FidSSI6p6mNTx+xGEDz72iZHXgef0ebPTh2P0tji4YxO4Wy8owSCyRcWw6w07PEiUlT8xIdmzlUomMY7lT8vk7gncdsWyNJ1AP8S1BQ8KTJyS3u564qfjAkwG3bpRcmjh0AIt1xwiYn5NMtiznbzv+05uWSdllvi75919wfOwdjrRUXL3jUTG8ccPyr3qK5bJvfQABAABJREFUH3sK0onlOzcNy6eO8qMLu7xxI2VtrHjsVEggDTXp+eY3cgqlSHJBIBxzdccbFy3XdgI+84mQowsRX/2OwUrFoQXNhfMTWodrAP8VdI2pHuSAPwLfc+FX6Sje66qIkVPIGtO8nP1USe/A62qnLDyqgjdUi5MUB0WMMTk60G+jzQV4KbDSUyLomwkvXnoFdAshBMONm2xsbxG155k5dhIRBGgkKisYb2+T9HbIk4zf/Pf/nuNHjqODBvOtOivtZW6vbdBqzjDYu8d8s4HG44xh1OsRJyl+lDHeKJCdoxydX8DWBPFiG91o013v88SZDncuvEV3exNvEl5fvcnHHv4kfWE5/8oF8q2Ciy9/i/HaDpEO0FrgVPW3KZ0CLdER5Cbn1u1baBezMnscoT03b1/l6NIKzUZMgaTuIkKhkA50kMLh49THcKpzjI+8/2M8F2t2N+5x+dIb/B//1v+ODz77Tp564hEWck9z/gxPvPfjnH3iYRrzMe/50HtpRR5Njy99aZdRz4KKECIEpq4dX40tKhjffs4w7EdAMu2Q7fuwBZqDzCW/L6Ddtw6Dt9MaR8hpc84fMHyr603iXFW8GKcwWlGMdtm+9hx26w1mZx1xY4VabRkXSXR9jjwtseWE61euc+HVC+yORuz0+5TWg9LIwqFdzoc/8F7e++kfRqo647WLJOuXEfkWshBoH4AocYCSAQ5LkglGmaEoBN56rJFkRaX+DZynzoRA5bT3UtLLBrfyEPHSaWStUY3BpKoC+ioVMMZ78iDCLB8m30yxoy7alOACsCWSATZylLmgXWsS1zQ73rJXligPUlgCqagHjnZczZOcL0FatKMaketqzC3KnDyzuCis7JQqoqRECUlr6QwyqhGVEAcCEXiy0pDHkrSIuD0yGNuAvQyZS2pRSWNZYptgvcIJiRWWlSPLNFsxF994jXZnjqs3r+Okpz7bIUlLwrhVkcFvr1KPIpxwFKVDBwHKBgz6I3rdhCL3tDttOrMtlg4dJjOGje0e/e4ehw4vUW/OsLa5w527m1y/ert6hqjKJlrlYFm0VCAKPIrdnR4qqOFkgBARxhpEWTAft1haWGYyTiiLjHE3ZVPuUa/VKbylVZ8hKzxaN/jaV77NxYt3ePX8Nba3dgBB4CyRz2nVFbU4IvWW3mhAnuZE3tNUmkYUIZ0g8wZnNUqKKugPg1QhmROkTrCsBAtYmkG1yU+0pKc8srB45d4efvvvjRfx07uvuueMgSw3NFpyOuqOqdVnEEqilSLLMvAlcfAD1Sd/Mlw8URQRRdEf+bh30yA2PxXCKZC6ehCZoaS76bl2C/pjz0xNEiuBEp7Th+H+d8LsIwK1VD31zJag7Fei2viUQM96nHH4rmRvCGMr6GYeK2N+5MOP0KrlDLo7KGWJlWdhtobuTdi7PUBLyTOPabZ2FQtLBTryvH7FcnvNM+l77p9TlMIxI0oscOaoZ25eELc9x2TCi3cEd9ckhfHcvZtw/ts1DseG165YtLcs1uH4fMFCTXBrVfCe055Sg9aWlVlBVkJDQRAIUusIfM5feI9AWs/dnuPNDUFjz8LI8MwxQXxMIr3jgaOeb1wVKFNQWMNrA1howUNLMBhZ7m0J/ssLgvc9qXj4IUenIci/6Lm4Yfk3X/cEEp56SPLxd21RpiEffDzmP37DYLHcvglbu4JXbjiMchRWcnk74uHDEdfXU44csxzp1LGp4RPPKi7cnmX1XsbCzIRJOlU9CvU9J3/flPP2AvR273Afy8V0ZLOPphcHwWqVLqWyfO47fvbdMm6K1a7cG+CExXkQrioClZAckLFUQIlnmA0RyqK9Z3fjHr60NOY7tNoLlGFIUXhEIGkGs8jmLLtbt8mLIbfu3mBjc5tabZkHHprhRKPDZ370U3zli/+Fm1cuEPgS7TzhKKMVNjh66AQ//PFP8cIbr3HhxkUe+qEPsvzwGR558lFe+a2v8M4n3sGphRl+f+ce3XLMoYdO8cynPsgXn3+O62t3cb0R9268ind7TLJdpHAYY3BK4VFYFxBqR6QsdS/54Y/8CPW4yZV7Vzl59DBPPP4oSdpDxXX2dsZQOCIk/b0eFy++gcs9a/fu8d1Xz3NvYw9fSpqzy+TJiDfefJ3x1gYPH3+AH/vz/x1xZ5nrt15npRExFwZk+Yhuv0d3d4CQVdYOct9SLCs6qt/HsVXmqqrz4d5+WAoBYurg2qf9yoPyBXyls9nvnnkv8VJiXfW+ExYlmHYrqnm8wFAaQ9kr2Xnzu8jtb1OrWYxZwBQCNd/GWkuSpKxtbPPWtStce/M2g50RaV4yLisEvRKOMHQ88vCjvOeHfoLG8vHqWosDqHfIdm5gB5uQp+AnYBOcddhCMPYG7SR158mQCOXJPRQOemVJlkji2BArQ9y/TC8tKofO8nFk2Jnqm6oFRjmPcQ6vI4LOIsPbF8lGe9TxWCtwsrJgK1dDh5KaVLjtPWSZAbVKaOmqfKx5qagFkjCAWCjKEvLvjR9REPiSMB3jaVASkYeCIncMRtvIRhs51YGFgaQWOnTuMa4kC0P6JiZLDUu+TqM0SGOxew5BQCnrqLBJUGsQ1RpsrG8yGY5QVrM36PHI009y984dsqJgdnmRzFlE1Jw6pyxST0XKQUVdVmFIs13jzOnTnDp9nL1en52dXTpzM8wvtFmcn2d1dZ1mTTMcjjl+ZJ5OrcFmv8tmPyNLDYEAHUQImeO8YXNjh+Wjx9HhfvfWMzPXYn5uniIvyMuCNMnwztHvDxh0+3Rut9hcGzJ7aIlWZ5Erl9b5ztdeocxLVJkhnSdyhvkQZuKAibJYYJil5LlhVjk6ATSRxDpkD4Epc6xWBMHUlYaicNU901Celg6IpcYpKIMArMOWlchaC7DWV5DCqeauWn8FOlLEcY1We5bSSpI8p97UKB3RbDVRUYj3EKgAWxak2X6u2vd3/DctUFZWVgDY2tri0KFDBx/f2triiSeeOPia7e3t/+r7jDF0u92D7/++j+m65SRYBTIQVUs2FYz7nu0tT00LTpyShKLC1bcX4Pg7YPacQIRQroOZUN1IRx2qJZCRB+OxEwHOMs4kKgp4YFFy6kiDxU6XosgIWo4oitE+YX6lTrioOb6dk2tB66jh8R9qcfh8n//+10r2BtBEkI7BLwlmI8vlNc+RGpw7BvMPCcLQk/U8D4/hTifg3sARSMs3n0843IZTbcfxBz2nlgTdoWdReepHBBe34F1noHCCe9swyqGlYJR6ru4FzDU0W33HXq9kmDpmlOTmNujSIQPB8dnKaWM9zMWe9Z5lpil4ouE5fUjSaguu3rF0R/D+p+HEYsAkD7DpmJOHgCDg5WuG+Y7jqUcUm7vL7KylHFsccbQtub4aE1nF5Tt9+qkDVUHL5mXBzsBQOMnJ2Q7f+BqcOKk5d9IRmJwvvmy4cTdjZqngk89QDaGp5p5M2RT7xNADf4+oYEb7BQrTXbQ/+Kr98c1BK6RycOyPh75HOOucmQpkqwh76asbWgoqAS0VnEtIiXMlYWDI+wMmvR0knnqzifcWi0REMbnzxHHMbLuFiCXD3TuYcQ/rcpRLObXQpha1aeYp4STn9NwSn/7UR1iZW+LNV95kZfEQazdu05xrs9bfYCfv0jk6x8KZI5zqLPKhh56gWOtx79alCiyHpCgNd9d3eeDhdxDnJTcuvIAIuizMhdy8VyKcrEBzSrNy6Cjd3R6SEuVLYido2oC7l29x7dZbfO7nf5IPfuJj+DBkfW+b/+s/++dsrW7y+Jn7uX71Ji++cZEiL/Amx3rISoMTECQFJxcXmTm6zM17d+mUAdtpwuMPLiNed6g9yRf/9W+zPt7iifc8Tqs5zyTJ8FJMT7mrQhS9rE6Zd1NnlTrIOvL7wmfBdDGWB10WU2lop/k7YjoS+l5xtEOKKttp/5L43oLXGgelxfU2yTfeYjZMaS6cwYaHiWZrLJ9+gGtvXGb1zgVevXSd8xdvkOVBNU8uSxAQ+IC5CB568ine//FPUV86hnER0kPcPIQ63iRsL5HtrVIM1igne5DsIMY9fGmJEXRqgkkOIpMoWxCGVbxCVjgS76ijWVCCOBtRy29g7hgmrkQvniGMZ/C20hh5FIYSaUrCwZCWEeROUpITBZ7AgRUB1gfoQCECAblBC41TilQWhLgKTDdNk9fKEdjKCZXLaWKymgIGZUEoc3KbV7BDFWJswcha3M4tTH4EJyqXRxxKGqFAC09aGsTcCgtzRwhvdRHpNlpCPY7IZUgmGwS1FosLh0iTnHFhiIKYyWRCq93Ge81ge6ca58WKNEkJggjvBTKQmKJgptlhfq7Bbm+PztwM5x58kMk45+tfe45eMqazMMfs4iKD/pC7t9fIswkLM7PoVg2vFCvLK/zoE59lL7H8+//4eXZW98D1EaLAG8va6jqpcdQagiCuodAcPXyEUX/C3durjIuUwhikh1BJurs7LGeH2N4rCdt32d0ZsLPRQ3pFqA31SFEjoE7BkfmIKNKcv7PGrpUVWwmBdZ6GKFn0Hm0NpY0YSI0xFiclaI3zkOcFuiwJ60E1kpOSwgsmCAYe8qm4WjMFIU6dbdU4tXr2hnHM408/w/ziElmREyqY6SzQarUIoxAVh5XFvRahlQKXsnn5yve9xP83LVBOnTrFysoKX/nKVw4KkuFwyAsvvMAv/MIvAPDud7+bfr/P+fPneeqppwD46le/inOOd77znT/YD5TT4kRWzh0lqwjxcgx2DMcOC5bPQCwh2QArYOFxQeOEwI49xS6ISBCueIIFIBCQCezIY4aCcuIRBh46rTnkZ5mZnyWI6hgLw/EOcRBy7MQSOtDUG5p88wYPP6BYGwXMHelTi3cou4Iig5WaYF4DWrE11vR2DRMh6EUwasOxGdBCMNx1jBPFTCgJO5bZyBDqim46EzlmW9UuX2u4NxbUIsGdSUCSlUQ1T6gEkYc8lVwtBTtDh0Dx2k3LYt0z34J6URJ4xbU9wbUtz/IM3NqAOJqmvwiI65KF2DAqGrTDnMcfVVy6bnn4tOf6dY3TcOSY4KGTHptbXpWCj74rYGVe8IVvpJw9lVAWlv5IsDvISEYCkVVFgHQChSfP4OknZxjvKfauZkiXcWhBsrMX8cLrYy7uOPLMU1QTngMNyn63oyK7VrthKauiperUiymEq9JVCFlxBaoEEEOFDKoWvH2glfeSKtis+glKTnNtfAVZwlQ6FaV8pRNQatphiUBoLAWCjHS4Tl4MCNtziIUORahBKZRRaF91XsZWECwcY6HeJtleY7R9j/5gi5vXn2dmZpG3Xv8aj519gPd98Mf42Kc/xaULl9m6t43July58RxfPv9fWB8PiVcOM4NmWdfp9gdcvHKLm996hfs6Lc7MnWbxvmMMu45kd4TF85WXvk5Udqnbko3VIbaMKZ0ld575xSP8wi/8b/j1//E3uHvzLWJZOTSurF4hmUzQQcHjjz9MRsxLF++wvnGPN69d5c1XX+HC+RcxaUnhJVYIKAskktn5OWykac8s8FN/4Wd5+uGH+Z3/9JtoBC9ffwOpQya2RM/O8K3//Jscu/8UL3znVeJ2A4gqd9S0WbWvO9of1VRdL6buKj21BleWcU9lNZbTYmYftle9Nc0onhal1dtm+jiZkmmrXnbVnZFVqrUbDxj03qLRHhB3OpRRk7A5h9YtetsZt6/cYG31NhvrPaQNKMsCaz0KibEFSw3Ne979BM9+9EdpLx/Dy2hfmw1eoaM6zYXjxK0FyvQY6dYa6cZ1fFYgRUasNLOxpV+rrP2yrEoNhyIvBcpYEm8ZqZw6jmazTz4qGN8yZNYQLtwHqoENK/dA4BU2GWPzPazOULK6N7TSIByhMERSkkeOaGaOOdugY3J2xwlYKIWglJ5cxVgZEaDwWdV5tV7gdYX/d7IyLxjtkRFoF6CEplWrseIMu5UrueIR4VHS0aoL5kvYTjW9seBGsstiNuZIPNUYKY+VAuIW7dYsxHWSSVrZv4XATUFhaW5Ik5y4XqfZaVUCT1ElSjvv0WHIcDSit7dDa76NiiLevHyN3Z0BzbjOAw8/hIxCLl28Tq/bo9fbo9MMObowT4ljZnGZufklZmfbnH38JGF7hl//1d/CdD2xDnFZn+5wQHdrk0hCLANqUY2sKBllOTPzC4h0zE6vi3MepRWNeoPxIGe8t07hLMIKfOGIoxqR9YR4ZkJYaTVohYbETGhGAf0MisJUADvh0MYzqxTSlVhTkkmNVzHSVyDKNC3wzhNMrfmFFFgdMzaKncwzEhIvFV4qLJ7C2So3aSr+84DSmtbsDCqK8FIxO7/IwkyLhfkFtAoJagFSS7QUBGo6bnf7L/L9HT9wgTIej7l+/frB+7du3eK1115jbm6O48eP89f/+l/n7//9v8/Zs2cPbMaHDx8+YKU8+OCDfOpTn+Lnfu7n+NVf/VXKsuQXf/EX+dznPvfHOnj+lw7jK8W4iqvRjUJA6AkOeeZPCKIZCGNPuS2IGp5gCaIlMKmHmqC24pFNjwiBAtzAY/pgRh6bC4SCqCF47J2H6duHuL2acWd7TFkYRn3LI4+eprMyj0n69LtdoqjBuSc6HElCTFKydiHh1m3JkvA8viIQSzPML9bY2LXc2tmhV3q2B+BfE8y2ILaenXXB4qzjkbJgfWAxXhJEgr2uIKvBwmkIOoJWFy6uQlII+oXm8lDweNsymVQckc2hZ/G44qMPCFziOX+xZGA9S776oxnrmY3gwhZ8oC4ohMfVY4gEaVFS5pAYuJsULM9KJiONTzVXr2TMBFXQ1vYavHnNc3nd0IwFV24IVkLL8dk+5QBeuwkPPjnLR2ccn//SgDt3YTnWbKcWJaEsHKtXJzzQcEwCSYZid7fkwtWMi1uODz4pKRPJvQMD19si2ar/8fY0U/A9OZnCT0WylcNnfyggYZoYzNtTIX+w4lUrofieV56+XdlaJcrLKhhuypVA2yqszTniSGJGQ/qbmygnaLdnCaM6XoTMzMyR9nNas00maY6sxeRlgHCKs+eOs9NY5OaNN9hLhuh6xPxii52tO3zt9/eYbG/y5msXefWFl1GypJ/skpmUZqDJ9vq8+sWv8ey5x8mc54tff45PPf0+9O42auEIKmhz/Ng8H3rfUzQXWrz8ytcoRrCwdAQzSMhWV7HCokLB+z/8YT792R/hzs46//qfv4UuHUHg2OhvE9WbLJw9w+u37vHK9oCLV69x8dWXmAyHRFGdUZ6jhaQwFiE1Rw6f4PTx4/zFn/tpdrMhut5AWEV7aZaf/8VfhNLx+osXuHTlOl/5g8/z2L0HsfWQu1vrfOWb3+LcIw/yoQ9+AiWmacwwHc1xwChBiKpLJPe7YdOsHDcVCgk/7ZxNxzuySqS23iG9OwD3Se+nBOCposXvG3g8TpSUEsospX/vNcz2FVqzdVyoyPpdhjshk5EF8xKD0R6bo4LNrCTxJR6HloJIFyx2ajzz9Dt55r0fpbl0bKpHeHs85Z2rhLFCgGxCFKJEiMtLkqSLL3NcYdCxp1N6SmcohcMaEK6YuvIEFJBnnqH3BNIhdUKLO+ytesa5o7VwCqHqWFtDWYUZ9Ej2tjF5SUBBM2Ya36CIhIZWgCQkitsIpVlONWvbBYmrQk0DKymMxBACFaencNU41HpP6D3OeLSH2EAZgLXVuLXZbHDs8CkujQqkDhFjgbaSUrpqZF6XyCxhc3UbEUaUdc9SXSKlQ9Q8TmgQMUXq6Oe7lEoR1BtYWwVzCqlJ05wyLzh8ZIUwjMiyjLKs7td6s44XlsIZao0l4mbM6voODsWxE8dYmJtnrz/i7pVbbN1dw5oCIS15Ibl56y61Ro0nTh1H6RjnDN4bHnroNCdOHOXW7i6KnFNnj3PKetburRLKKlrAGkOR5XjA4AjrNZq+w6g/qCIrdEBmHMNeipCSRhgQBZIIS81BK4TDTTjWlrg8o8zGSOcJwjrSAKIksA6ReEwBsfSshIICw8AqinzqvDEVhTcWVXjfiIAxEV0ke94xsLbabLiqmDO4aQeFqssoBEEtpjU7j0PiLJTG4cIAIyRxXEOFGimre0yrsCr+K4Lq9338wAXKyy+/zIc//OGD9/fFqz/zMz/Dr/3ar/E3/+bfZDKZ8PM///P0+33e97738YUvfOGAgQLwb//tv+UXf/EX+ehHP3oAavuVX/mVH/RXwUkIYggiCILp2y2BCEBowHkYgzae4CjIuLJRBUdA1KeWVScgBduDYldQjqePO+3BClSskUGTzc2cG3cHtFcewCVdBusDhiNJWDtMNh4xSWFQBnRakoVZhZ00uPJqj9cveE7MBtz3eItDpzzdBM7fzuhn1c8XXtDvem6/XgkVO3OCTqQYSkdde3YKxSiLGY8TxvOavZGgt2m5dM1zqyvwkWKUOS7vBex1PdY7cqNR0vHBz9T5wEdKvvw/etYHde70Cq72Cua1Zz4WHO54uqXkWlfz9LmAd7xbUq8p/u1vKYajnLt7gnRccmUg0IFjW3je/Irj2bOCo3W4s+G4seM4cZ/kc88ILl6x/OF5wWMnPEnPkwjBUw+MKPJFPvWenK+pnFoUcuV6zs7EMBdBg5LHHzTc7QaMRcCF6yUX1j0PPRDyzP2aWMJmOfvHnv99+Qlv/8Pboxv/PynUpwuVmFpJvUT4cjo6cAdfIqatfr+/w55ahcRBQVMtkl5O7arCEklB3Qu6ewPyUUo9bnFs+QQ11cF7zaOHz7D88DxvvPoqS2HM7qBL3TomgzFnTtzPp9/7Hv7Nb/06q1t32Ni+wqm5JYJ0TLq9xct/+HlqUhGEiolwlL5EWUtNCZxNuPHKC/zGP/g/Ezdm6N7b5st3uzTKlOVWi/XtDU43z3LprQuce/gciwsLvHbzOg+ffpQyTLh7b49mPeTxZx/lJ/7snyPVns6xJXyosGmOs56o0aYM6zz+vvfRNYK0P6TZmWFhfolyMkGqJvHiAlEYk04S3v3su/krP/0XadcjTt93FEvB3fV7LCwssnbzDuMc2rU5FuZWuB2s8f4f/TT333+CX/3V/xv9fpdBnpHm+bTD8T2FiQMnKlbJvshVSIVzFR1Vyqlob1qlSglCyWlyLuAskiq12lOJnKdS2Op8OsDbSnhJlYZdYDFZwc6dtyi336BhR3hmSYYxaze6bHUHFFnKJNtlZn6xoqCmKT4zaGsIhOP04jwf+shHOPHQUzTmjmNFCE5Wi+iUr+NllS3lnAAh0TJCtxawSyXZpEeZ5RA7cutRmSHSilI7pAdhHQiLVZ7ce8gr4F7dQFzzNKIhM+4OuRNkwqPUWYSCYWnwRY7d2ULLCYqcVqgohABb9Zms8kRRiPaS+c4So94WdW0YW42VFmEttSCg1ezgpSVJMpwRBIqqMFFVVlUEZLagcDmlrfqfEzz3P/wEo1GAEmukfYnxEt32BAIiJZirQV0UlCKgawx7Ych8M4Qgp3QC71W12EcxKgxxrtIiqiiixGGGE6SxBIFknCRoFRBoB6oqfJuNOq3FZfrjjL1hn0DFrKwsM7OwwJtvXufixatsrG9RU5I4VoQ1BXKGeimohS12uiMePHeEoF6j0YiRxnH6+CKT1QWwJXMLbQI03Y11YimIg4jJZExhPa1ajb18wChN8HiajSZtUX3NqMzQOiRUAY1QUYsDQmCmJlioeWZkjsh6RK4kMAWUksRmFKVHl44F74iMJ/UFXhvqQcxcIDHOUEpIM0FaFAcZXqWXDJxiYD1bhaFvPIPC4KRAGFu5GpWcdi+ryAepJDOLC9SbTaTUhFHI3NwMUa2O9YLSWnAS5T1q2nHxziG/V0f4fRw/cIHyoQ996HvcFH/0EELwy7/8y/zyL//y/+zXzM3N/cBQtj/uqHc8nSMQNIEQZOgRAWAEvvCQA14iOx7R8iAFMqTqmHgBObgxuKHHdAV5H7z2qFgc7LyIIrZ2S7773GV04wgrnWVCkbLe90xe7+LT55mbSci9wpSVgOjIIUU022RmpcNHPlBxGjozCaceCHkgTDj/ypjnC4cCIuPRueC5qx4fKGa3JMvac/yIZ7kNyVCz2xVkQrNuJKyWhNLRM4KxF0zGhgDLwzMBIoGtUmMI0ZGjHBp2ViPCsCAtLYuxYGMiqEfQqlUL+VIzwjjFdhZx5IxB5hkPHxV8560QkRmE91gpabc9h2Ys4VDw8nXL65XKlB/6SMB7nxAIK9jb9ly66/jdlwXWOX7ms4pRP+b5C5anHnA8chJ801EkmqWxZKnpOHeorIoJXfDgacNM3RHXBQ+eENzbnuXEyoRWCyYH0kjYd+1UKcbVuZJTDP5B4o7YF0WKaRgcVXvYM92tyooP4TxSODzTfJYpSdZPv18IpjvsSrNQzV/FtM3pAIOyILOCdLtL5BWH5g/zkXd/kGOHz/DSt5+nuHUDO9jjqBly49oVxjvbGOM5unyE/O4VXt+7zqGlNkdPPsub332Fo4uHyQY7THY28DJHashdwVhALiXWe6RzxFGE9SXX33qVMJ5F1+YYywHr63dR953mA5/5FGVu+Ff/8l/yc7/0S7zn2Xdj04LMCj784U9SUy0297Z59MEnqbXaPPf6q1xfv4OLBHlqibVikORE8Qwb213q7YDLty6ztblG0R8x2RtS68zw6DPv4tT99zHfafNjn/wkK50WyWRIMpkwEwfEw4R2xzARkiTL6I322Nwd8Lt/+HskxYjoy5Ib169iygKlNFOkLk54vDNTLk2VFrOfjbN/HTgESD+F0Lv9E1/VKbaKsgBACtSUPlt11qrCxE55J1AJSAvnkELijSadjBnee41s41WifELmPVurE/Z2R+x2x+wNE0yekpqcrdLS9IbIlEy8IJKOk4dX+PjH/xRHH3qCsDGHExFW7lui7ZT/5w8s085Nx4geDBrdWaB59EEGpSXNLKmyZMEQGYB2GustzodY5xEixxlN7jxaWpQUWAReQ80VuOE9UlmB4UR8FG9jRJYjyxFxZLACskKiY0mgJCqsY4I6iQtoakteTshygxYhXvrKMCwlneVF5o8cpru9ychavKoYKFI4tAdFNSq1aHAeRY4OBFF7ARHNs9Q8StIfsLfmEKWjcVggGpWYfW425L4zMWt9y8DBzTRnLhQsaEk+PacCi1bglap2/F6igxpxHNOfZCAEYRRCWEOQ4GyODHSFCAhjtgeVM/Phhx8hUIILFy7xpS9/g821TYrc4p3EhorChUSEqKhk1gcI3WJ9c0zpb3LqzHGCVhuvNGdPLZF0D7O3UxKHDd46/wqRkLRUgLIeEQaMC4Nxjna9Rp7nWO/RtYCmBF9khFIw124TB4pWI6IWBQRC0JYZM2JAxyaEJkNrQRwobF7B7oSTzCvFUaFY8BbtHFZJtBLE0tIJPYm39HIoSl8h8pVgYEOsgzGWkdcMbEnmHL6sxqhCe0JZRU1YKfClJIoCzt5/hjBoooOIuaVZTpw8ilABygcoVfFrlKy4p96bKYX7+x/vwJ8QF8//3FE/KoiOgAjelkD6EiiqnQTFdBjQAF+vxFxVPgW4TOAGHtsHM4Ri7LHlNF8jr0ScTihQh+l2FVnhpoTaAHSDVr3G/Owiaxs75HlC2KjhrSVLC2Y6dcq4zTBwnL+3STLOeeZowZHFnCKB8bjqnCyHnkNKkGlBfUZSx+PHlq6CE87TiKBT96TblppyRGnB4w9CPfYcm/Wsdx1fviLYHXp2xyknlwRnHExcylau2dgN8b834da64Oa9krqETz0gaNcFe2PBJBfEOJCVmHI0jui+mXLjrmAwMpxcENzuSmwMR05YHnlEMBjBt1/2nL/jiBuCM8uws6bwpSPPFTONENFLqdckc22JS3PaqqCpSmwGL16Aug949oxhpmOIFeSlpxbBXNtRporAQTqybO50EUNHYgasfHpfyAr7/ZL9QuEA8npw7e+LXfcFsNNP7XdD2B/cKPYtx/v6FoFHeoc86LhU7ervdX1UyPNq14stUU5wfG6R9zx4jnqzSaM5w87uiBevfJG1G5dZv3ODmjMshgEmzVB5QbPRJrk14uqNSyTaESy2CFod4lGBmljGk5REC4pAkCtPaSUTB46IRmceJSNyYyhdSS8bsTgXUVtoo5QgHEe8+ubrXFpdZ2VmhXQyphHUeOThc7x54TXeeOVN/uKf/hkW4jk+/4UvcurIfXzxi1/hwvZV+oMdarWIYiyRkabRrrG4NM+lV1+mP96in+9Q5BlhIfj4Bz7Fj/zkn+PK1hYljieffJJmu4FU0G7UUTbAbndZyiPqOwWtUvOdC2+w3h/ikNxZvUZ/tAc4lFJIJSidnZYavipQPAcjOrc/7xH24LxVEdFM8e7TEyYOzviUwOvxriou5fQa8M7j3dS9JaZn3lYdjcw7xjs3GN96HbPzFqK07OWOsZTc3UpYXdvE2QIXCkQpKXOJShIaNU2DOhM34sjiLB/6yEc5+8S7sLpZ6aOEx+2jvr2vIHFeUsl5p9eYr5KIEeDDkGjpMLF3FFmJzC1RzYEZkFtPWVaiR+Mt2huUlSg81ljyQFKWHpNWeqpIpIh8A7vbIm1J4tYy5WgXYZOqSAojjAsJC4VvSEwcMC6raz9SJf1Jj0IoaHUwe30iW2ndYmUR5Yhk0MUXJV6CEY5YTfWB0793ZiudSSAglNBozrKTOHZlwowUKBGC0WSjalPkQk+gDTOzgjwKKAvJ7lbG1UEBKqRQitJadCTQoUKEIZkFqTWNdptao8leL0XWQiaTnHzcZZIkeAG1Wg2HZZgVHDl+iiisc/HiJS69cZGt1VXG6YTSGqTQSKlIS0mZeUopkalluz9G10e4qIEclYwu32Z+a4ejp45SrwkOHeowHAR0d4e0ojpmPCJW0NAKH9SphTk7gzF1GXB4ZobS5CA9ARYnLO16m0hGCFMQt6JqL116TJ4QMaEmUkJRUBiDIAThkV4SIViKHEc0zJQl2lWOnAwHSqIChclLMg9OSZQBV0CiBLmuYJjDwpBai/WOaoYogWlXUU3V40FIo9OZFtaiCmlst+m0ZyEIqugCRKUTE46yyBC2us+Mexu2+f0cf6ILFNEQUKvokDgPGZAIfB+8AdogZkCEVfcES5WsOBK4AdihoBx7TAI2E+ioag27VODM1Bm0ohlNMowTTJKSQXcb7RKWWo4wtMweeRCX3yIIC0wpEM7x0luS5eMnCDsB5fgWj8yWFAPHd77muZsIXrjh6URwuiPJxpKJsDx2TCALSb+EWHjCQKACWG4WHI/gwRXP8mHo7Xmi2WoWOd+AVizZ7jv2epaFCB487JmbFfQmBfeuGj6/AzsTUQl2tOBeV5L0JHkmmY0grmvM2DBcy/kX/7JgdcsyNoKmhrWJJ2pIGnXHnW1J5x4cPxJwfKFklDoeeFgyX4f1VUugBa3AE0SKH/9QzNZ6ym9/wfAjT1XBeS8/J1i77YmTktk4Z6Hmee2up/SCpSaoSLB2W7E7ElzdcFzfLVmMHY0R1Dp//Pn304UHDp75U20BIPaLFHFQuHhfiR/3NSb70x0vBPuZLkJWi57101nBVFzppWc/vr5iaUzLG2+RXnD71g3W716n2Wrz7LPvZtjd4Lvf/AMimSJsSl3XkUYQWkkctFmYOcxgOCHPC2brdUaTFJP2+TOf+DR3Vte4uj5hLCXWqylorka7tcCpkw/R7Kxw8crNCr7XEARzY37+b/8fePOVi3zjP/4WSxZWmvPU4jaPnzzLTq/P53/nCzQPzfLGWxcZJSO+89w3eezYAyzMzvDAufs5/52rXL9ynclgB1KDEpLSZ2zs3uTqncsMJ2NU6MhVTiQDIiKy0Yjd9TWeefwRmrMt2p0mu3sbDEvH4XarwuYnhnDi6a/fY0/m7OQJg8jy9S9+nv5wm0AzfQhWhNOqi+CmFvK3E6Lx7uBcWz8tEKHaRft9Rsq0G6KnbWTnpo6r6UXhPU5Muyq2ug4sIKbhedZZsmzIeO8e4xuvUnZvs9lLmNgGg0LSH6cUg8p1MSHHTTJCW8MXHi0M1nqOtTRHFg5z/5NPcPqhJyjjOt47tLdIG77d5XFTqRQOIdzbOilBxcqo+PwIqYg6SzSOnsWNM6KiRJsq6r60CicKnCnxJkaqHGkdxkiMd0QSQqUoJPioQGeG0t7Cixx8gsi6SKVxKEorsEJhjYBEEGlPGCokAfV6jbA2R7Y9ZJhMsMYS+IKacmT9TSZFhsgruJ+fpkArvz8WFRjhsaIEV2JEAEGAcgVLoae7uUZZS5DKEQbVJtJ5EEZiC0uajChNiBAxvh5ye2JR45K5ZlXMqlAgtUApTSgFYb1OGEcIpZGBxkhPrzek3urQ7rRRSHSgCOKA2YUFNla3eOn5r3H5yk2S0RghDKgqj8lJg3cWh8YahTeezBoSU5JaQ2Ys49Jjkgl5luKFxIwmKOFIB2OuvfEmS+2YoMwZjscY6WjPNFiaa1KanOHYUQsDiCttTYjDTLt82kxoADLJGPqCoYswk5RCZfggx+pyWnA7glAhDWjrmQtzlmKoB5aQgERKesIzUYqhd6R4SgFeUT2LvEc4KL2g8KIqIBxIX5GX96fl1k5lE7LavI+SjGuXb7N06BDHTx2hLA15XhJqjZOVBtDZ6tmpwhCb59XY/ID2/f0df6ILFC9FlapoHGIo8CNgAtYI5AKIpq/+qFTFic8rTYrpeuwIXAomAVOy/7TA5WDHkjwBNyOJvcaVCZqCsCbYWL3N4Y6lXZfc//gx6vE8rz5/g3rsqLfbbI9O0Dh8iiuvfIX3nuzy8ZMFtzY8L1y1JKXgmvP0jScKJV0p0SF0NKRScHGvxkIgOTNvGOuMZM9Rjh3PnhYcOlnRaDc3K56BLj2ttuSxh2I2BxkPHhIcX/IMdcjSomKhVmAwJLkmm3hKLSrxWc2zORJ0M8Gpw5ruWsmgZ3jX/Z49ZVhzEAnPk4cdwwTAY6IQ0WjzzJMJCIO4KDkzrznZCrl02ZIkcHjBs7bpuHB5zJiQTzwasPoVy1dfC5gXgrLryY0jDxWTmmDkHLNty3cuFdzVitPzba5eyXljJ6WfO0ItaCEqTIn649uCQrytEakuiOrGmrK9qztLvk0F3f/UvuZE4A9YJ1Dl73jnQeoDy6mU4kCYKXVQpcHiibWmpjShcohRSpImzB1a5M69W+As925eJxY5apzS0S2evP8ZsrHjsQffgUo9c505Sm+5cPl1+tkuefcuZZlzY/UmL16+yEYxxNQExkfUwgr0pmtNnFesbmywPdrjg5/+KFE7pDveo/SS1751np//zF9Cb/dYqUfcXb/F8vwMK/NzPH/rFj/z2R/mWy88T6/b4w++8J+5Pn+0EvPGUKtFpKMJO6sbRMkY4Usy50nTnGJ/Hu0keEWzOcuh9jKn7n+IqN1AR5Xry8iUUpQMh33qGJZnZukcO4RVIbuTIS9dfIObe2vcGexwZ+MOYVAJjl1VGVZjM2EOtD7OTCNzpmIj62x1zvcLlH3E/fdcAgKBcBYnHNJJhJwSVKddN+feZtogBJaqk+GFJ0nHZLu3sduX8P0NNnu73BtIjG8xyA3D4QhKQ4Yjd57AKJwt0Lakrg1HF1s8/NgjRIcfp3H0FDRncb4S53qqsD5vJftgQA9Va56KcOt9lbrupvIpMS2otQ6Jl1cgTxnJDL9rUaaLygusF+BjoKTiuBRVh1hURG1TCHJl0dKB8wRll7q22DxlXBZIrUnwZA4KHVQ2URkQ2Eo9EuqIRmcGI+oEPkJmEAlN6RUTIcmDEBXVERn4orIoB1IinKsiFPAVK6rMyUWJC0Jw1f84bgToMAWqlGcvPNoLgun/veYEkfOUZU7uBLms4cIat7OMVBrq9WLaEfM4V6LCmNZ8m8wXpImgXg9Jx7C4NEdnYQ6havS6k6oINCVf+IOvcPG1N5mMJpXLy1ugAGsqrYUIquwm+Xa8QqRDlNRIrVFxhAe0DmjNzeCFptFZIB9lFEmOLT2bW7vUpScVFhcq6onAx1BXkiLwqCggTwtqyqNx1HAEZYYuCmJb0GwYAlvQncQMs4IkqoTESEMmFVlZIhR4KZHC0RGeemCIdCXKxVkmLqRrPWNnKJ3FekHhHU0BTVV1R5wQWCew1uGtm2q/poV0Wf19Sw8iUHRaTeZmlxAiIAw18wtLSKUZJxO0MwRa44No6kyqOixSaYSUROH/lzUo/391CJC5w3XBroJNQbQF+qhH1Pz+xqwa9VSbBtwAmIDLwGRVdoQKPTqsUoPLMUz6nrSA5qJHasPifIwSKXFokXZMb3tCNxE8u3KCxcUT+CLBj7/OWj5La+Vxzn/lC5xu7zHY6ZM7z16mUDqgn2QYYFaBEp6xh/m25/6jgo1EMN5LwAnGA7hVVFaxIx3BsVOCPSNIM4/TAjGnaIbQamrmVMC9VPHViyXvkCUPHhF8+WVF6DT9kSXvGj5+n6BnPHEAyx2YqVnWbyvurJUUY4ONBcPScWrO0LlPUg8dzchxeV1yZ+jR3jHojxnuWOYaJTs7sDkOcAPLqF+yfFJwvgsX7liSXPDamyVH2jEnFxTdHU1/XEAoOH4aBuMG1qSs9yVehDx9KmBjV1ZUSlXjcGiYlAWFnXIQOk0y9b98mR5Mdw4Wr31/zxRlPm39e6hcH97j7DS1VoqpHVUhZTUqwFeCSolCWjcVWjrqYUgtjjHWIUvPfFhjZb7FKN9kqzC8/9lnObG0wOsvvIjtbjPb0tRCgRxnPHz2HE985Ic4cuQkN77+EldffZW3bl/i7sZNvMqZW2yxsbrNnWSHxiOnqBcDjj98H08+/RRZt8fv/4f/yO3b99jd28ZYQyoKXnzxd1g5dIyHzj3BvVev8KnHPsiHH/wAdm4PO9nipe98if72Ld712T+DX57l7LnT3P/gOfb2NmmUlseffJijJ07ilePK1Yv0u1tYO6EkQwrBOE0qXLzQBHGDX/qFX2Jrt8tP/shP0N8boeZm+PobL3LxlW2OHlvk9OljzMQ1XGDpHOqgwhDjJf5ohxe+e5N//p9+k+1kTO5slVG0P2yTVdaOxeHlNKLAO5wvqmGdo6K6CpDe70tGquwkUelPKouWQLqpE0dUSlmHm2pWHFb6quIxFejLeYvxFXre5GPGu9fJ7r2OG2+zMxqx0Y8ZJ4ZJOWSQDHFmGrQnDViLswLtLcv1ktNHZ3jy3e9j/uzTFOESRHWQIc4bPILSyYqAK6osp/3r1e+36DDVYMv5gzm9cw5jq9otrNXg8BGstGRCE+SSOBfghpUGy1fPMYfHmZyAiv8ytpbCekIPESCtRyVDiAIQklJICuUxIqAWxYQC8BrnYsg1BB7RWKIYT4hEQaAkQVk5ZUon2Es8hzoxXmQoIdFCoAK338TEqapD5YynDB1OOkqnyUxBb2AwqSVoeAgUNnFI63BGIKRjTgpy6ek5wW5hSIucwockPmKYeA5lCZ0iQ6gapsgRWpMmKU4HFEVJENVIJ2PiOObMfSfpDyfcub3Fm2+8yY3rV0lLgyldFULoDIgSfDEdTVT8jv1GqtZBtfAaS71Wo93pUGu2CMOQZhQRhTUmacmlqze4c/UN8nSMDAK29ibgShYaAZ3mLAQaYQ0xDuVKvFOoEKJAQZoTy4Smc7SC/zd5//VkW5bfd2KfZbY7Lr273pS3XV3dXY1uNAmiOXQjYkICMSOGTMRMTEgTUoQe9D9MhF6khxGHowhyaAfgcCgSIggQIFwDjbbo7uqqLl/X1PV50588bru11k8Pa+etAskIAo8dPBVZdW/dzLwnz9l7re/6/r6mYZguGBUtK9qyP63ZXTiOVMJyZjFNzUzBaYidLt7XgMKa7uBlFMGDU4qxV+y7QKs9pXicV1iBkU3oBUMl+kl4YQghAuqzAlY+I1RvwGrFcDjiypVLJGnOaHWJp566gjI2ZkVpjYjQNNGto7TBmIRenhFCwIj7M23xP9UARc2FMFM0D2NuiT0P6VVBZUTq1wGVIBVIBSGGMxIqhSvBeUHHVnRohPZUMT0SpjWYniJdgd6qZ7Ps8fTVQD7SJFKxCBts5+ts7SxRjDZYvnSd7//qb7DbCnv3/gnbm57D05oFgWsbKedC4OHYU88N26mnQLE61KhU2FwNXLmo+PhHwsmpp9SKK8uKaqQ5nMCtBfz+dxVJahhQ89ffSHj/cQFV4Etft2Q6cH3o+FbtePOu52Lfs5l6bj2E+wewpmGUQ88Eaq/Yn8Csgmu9huvbgU8OFJIrsg2DD55+5jmawINjw4NjeDRTjPqB08bzrR8K2z3YmyruH1csL2UkRjOZe8aSMXcB5zzOCT/6KPBzl1KmbQ1G43PHl35G8YN3PZkWNgaeN3+kGFiDVymf7Hpy51jNC7ad4mHZMCmFSgcurJ2lCH82cC06K+Omw5PTNFo9GQ/I2elazr4yznS0llg0FuINqTqdisF0oNYj0qJFSJRie32Z1z/3Kicnhzy4f5/XXn+N1f6Qt779HV5c2WLvdM7xYsqv/oP/ka2lZbZax07WIynnrPYyFtbz6NZPmJnA3qNdyv3HnBzv8mi8T9N6gnNYn0LP8uW//pd46a//VT5xE/RSxkp/AOMppp/yjV/9de79+H0yF8gTxeTgEaeP99n9yS3+y1/8r6gOJvz4rT/mjRdf5ld+7Te5v7/HF9/4PAeP9khX19FG43DM3IQLO+e4/Nw1rl19mr/9t/87fvcPf525rtCqjjHxKuXZF1/H2ow33vgKG+trrC4tY4cF1158Cmt6/NEHH/DMz36VD3dvIcsj/ui73+Nc3uPnv/gGeZLRtBVtqPjRT97iX3z397h98gi8wSiNURoJvgtcU4ROlh6kY7tE8N4RhJjAKRbR8UQeGZCYFKtM1A9J54g5u04AvASMFzwukmkhARStOHyoombFG+aH+8z3PqQ8uUF9dMS4tBzMMk6dZb88pXETGl+hpUWJx4jC+sBy3md7lPPUpWWeefUllq+9gs830aRgTZwi8WkBZQiOT61nEoFTtzE8+SfEssB4DQe8CEZF9og0p7d5LoLousG1Ae8DbZhgEoVqDaItSjuCOLxEobBxUUOXJ0KjweAQNwE7oLIJTfBYq0kSYe5bdJqhrCJBk/RX8ElBKSfYfoHJFFILQWskWELpOD49QnuP8g5nhLR7K+LYDXzonr80BJWiTZ/GwcHt2yyneQQWLkXpjOBKQquwRmMlsGIVF1LF3MXm4oMQaGwPj6cXBL0oMcHgdY1uHHXpmTeBSd3QaNjbO2D/+JSbt+9x684j7n2yy3Q2QxtF2kvABJxrIJz1HhgiA/upbumMwcuyjPXVVS5fusja1hZ50cNaTd7LqFv4+L37/OAPv4Xze2xvrtOkltqmuFlLYhxzrfGJBVdjxWN8SxM0JjMkRuPbGutOWdWaDb1gkJUkmSMJhu084yNjeFQ7iiSml8+ASRBaF1OKjY3sXAhRv+VFKIPmpIV957GJxRtDmlqG2jD0AZvEeY94g/L+T+i3PqUmo55PBUELFEWOtoo0Uywt9+j1M9AJCsOirrFJitGmqwnx0drtY29TaMo/0x7/Uw1Q2rswXwhBFNlTkF8WJO2Qn4usCXUEJlJCWICvoFkIzoHNIelpqIXySJgew6xVpCPYeA6G1zxpf8LW5W0+F5aYTWp8WbKoppAPOb75E4ZbNT3dUKVPcXzvLlsjx/y0QQXF0ihB5wmrm7BzHg7dlCLVZBK4dM6gU02eBR49dogTykCsuu4nvPhczlw5vvmDmsNTh587tgvF6dhxcDrncA9WlzK21g0PDwQVHD0bdU1D61jL4MIVeGsX3rkrvHRF4b3QOoXVMEjheAooYWBAYdhrCraTmtbHOfhcFEpp9ucB2pYP7yjeFXg89xitWdnIKNvAxUszJg88O8MetxYTMgsH+zV+x/GlVw1v3U7ob3iaGnoyZXLiOTzIMWKY1J5DC8tFQn08pVnAuhbWNwy3TxwFFVujORU8cefQ/Tp0/UvKdHR4J3Y8+6/CPOnq6ba26NKxoKzBop+Mb6IeJabMJiZBe8PF8+f4yuufZ3F4zDBJ+Lmf/4vsbG6yf+8Bk/19xss9vvOb/4qwmJDMT0mMYrH7mJU049rWDlc3VsmC5/yVpzlUKb/6O79Fi+d0cUjIhbFtUDZhe/U8p5MTpkazSBMqrcEmjMcTimAYes0bX3iDCyvr/I//r79FvT9h2O9xeHJEkWT83/6P/yee33qaN/d/xLOvPMU//Vf/lMfNhAsvfY7B5ed5/kt/nn/5jW/x9//ur7K3e0TVNHx0/xbfePs7/OTuR/zuH/0boCEzGh0ylAOnEq5dfpkvfvXPsXPxHG+8/irBzdk/3mPqKz786GN+67vfY/j0VUrjebS7x5eff42vPfUsy0UBzYL7dz7hnY8+4v/5//7v+fD2bYIojO1e7BAZKhWig+pT51RcIAXpMmyiiwpx3SikAyHd5+puMY79O6oTOcfdUZRHlMb7yEp48XgVRyl1o2hcxfzxXeo7P8AuDmgWE+4/9jy225xOKqbjx8xVimtLjK9IJIpuM1Fc2Fnl8rkNrl9/htXLT2NX1mmzAlSKUtGxgoSunSEu8CKBEFQEwQg+uDOOrxNiR7bO+6jFiddszKAIIojShCQnWd1icG5BVbe4pib4mtCC9gGdWgIJvumeghJUCzMNtlGdI0PTUKFDCnaErhypNmRJywKhzTzWOnRqsUsFtA39ILheRmoCQVma4MhUTOpt25JMFEZ7PIIL8aTdasiBRCvmRgia6LYygbqZwNFdhlcvQ2b5ZFzT84alvsYQaE0sfNSiWDHC+VSYK6EKCrVUcFpVzCtBqxJTtXiVENQUpQZUjeFgUbK/mLFoSppbd3jrrbcRm4POUBp0EusClASMienT8VqM1nQFiHiUieWdzjfkqeHixW2uPX2NlpSmblksSiYTwZVw44P3mZ/us7WdxpGIb8Fo2uA5rQP3Dg8ZqGWW1/uYEA8C1XzOyUnFkQr025IdPFlRMcoWpFkLJsTRjzEgirkx7LdCz2ZMq0DlhaZ15KLRYqgk4ILB4wgSaHRCK4pWAi4EtNYUqaWnNZlSeKVpgiJgIptson086t66RxdYGGGasKhKjk/GLMsqZVmzv79HkS0RvKL1LXWaRDtxV0VR1SneteA90i6exAT8aR4/3QBlD8JAUbwCyQ5gukOUA8rImsgCZKEIVWRPmlIQq8gGkTkJM6Hch8kplAL9bdh4TjG4HAPcVN5S9Pps1AUm0Zw8eETa7nKyvyA0E8JiTDCGzZ11Th7foK5bNA2Xzzdc2dRsnMtoS0VFoL+yTLkwpEnD4UlFKhm7j2aItSwPDdZWaC+c68HX/9oGfXtI6lJ++Y8mrKbw9dcUX3g1sPmx40al+OhDx0c03B3DKxvwuWuwlUtUy1vNYqEZ9eHxTHhJKTaWFaseTsbw5j24tKoRa0j7hqby3H8UODQprfc00nJxRTi3FPjwWJEo+CvPCWGU8s+/1aKUcGVpwYNpYJAKz22VfFy2zDLNUSOsWsW0ES5eDhxJYGcroZlWNGL51k2P9y3PjKI3Py1LegNN/1JKuWg5HSteu+B5edtyYdVjsoZ/p8FBdaGEWmGswfsAEptuE5NgdALoOD/WuqMuu2Av5Z+0156JGAQhBINCOpGaYjGdcO/ebV559lkub55jcXTCH3zvj9noZ3zjt3+D+48+QaTFlCVLaKRVSFYwVfDBdM6N+ZRBYlivPTOdMV8a8GD3EcYkeIlpjYlOaWyBGRksnsf3dzF/+H2Wd9bZGmSsTGfkPnA6PqLfwAtPPY2+pvmlX/ol3vnjH/C9f/UNkpOaO4fvc//ODX7lf94lyRJGV8+jBhntzip33IxPxgcc3bjBlcvbnFu5zO7BJ/zWD77FysqQiZ/ReMfq5jnqiaN1cdG+9+iE59uEg3nDNDiadk6xvsoP3/2Y9z6+w9K5bWpfs9YveGX7El+6cImNYoDxAecVq4MVfv2f/zq3P7yFTTRB6SfaijNMIWdaIaLF+2zxks4SHlXP+kxx2f32rCbwTOzsO1lRly1yBjpRsR3Wxb4dQkOD4LzGzafMDm5T3voeavoQ1Rtw3A647zy7R4+hqQhorGqwCAaLMjXDfs6zl57mueefZbixwmBpG1Ws4XSCcgGMixkrIk+EvE9YPwEhuopU59oJnZ7myYm9EwqHENVOSOCMHBJRBK8RnWNXtujNZ1AvMMB8cUorAVpFi3T6rAB4lA/4VkGjAE8rcYN2wdH6hrSXoq0mhB6ZQGI1Ou+jU4MoR6scJs+xVtDGY7IM1SjypkWnmtbXFCYCLwlRj6+ViqFqoki9IpiUVgZk0seFQO0aUqPoLa1Q2TlLgw1mNw9Ja0NvCSQP1E4I2mB9YM0K5/uehAy9ucqj04qjg2Ompwu0NWRpnyTrsbGxQa/X56R2XbGdR4yOHUQanK9BgwmWahHixilgrMFg8N4/0QNFvVN8b5Q4BsOMy09dZeFa9o5OONw/oKpL+nnO/GjCyeN7LPUUq4Me00VDvZjH4DuraFzDdGGY+oAzMSAtFcXkaMLDcoHzjhUdKAoIqsH045hGlEK5gAmOxsHcWowYUgyLtiYrNed7K2SN49hXzMSwEB/ZYTQzf9ZbpWmCA6/JWgPG0gZFpaK3pA1C7V13AOjWRgl/QuCltCaIYnf3gLIMiKSMVlZ5cO+ALC1JEkvdNLgg9Pt9jAoxOE/FotUQPP3sSY/En+rxUw1QzAoMXhXMuqLLj4GGyJqU8b9SA43gKkXTxr4eUwhpGiPtm9No+22UYnResf485NsxT0UZEFOT9OYsrbVUUwXDKUfjCYP+EoNRRjMbM57NWFs6x3IvZ+Km2Fyx3FPcO+pzqkYgCfdPFpxUDVXZUo89158acG4955vf9BRZDMZJUsG2CqmhyA6YPXIMEs2VvuF/9bLi/IbjwYfCDz+E/kDRUw3ea55ZUrx2SfH0a3ByKJw81DxaKOhH+thazbQymNSzv4Cbu4r53PNARWHt/T149mLKIDdMp57GNoybwPoQlnqGwxLyXNPvOdY3a954SuMbOL/acu9Qs5hAL4crW4HMG1ZHwq0DuDYK2Mpzvi9oD8ZmTE5aTmYxDfO2zTg/ApkKSZ7hfY2xkKZxQTi3BltrcPzv6KriAmzTBIqcJEniYqJjP4TWJgrZ6EYJgA++E8FF70YIEdCguk2PEBcDBSYElvp9LqwvMxmf8O3vfpeHWztcHI14583vc+/Dn9BWE8R4in5GohXDdMBgtEHT63PgGvrnN/j2D7+NEUf26JBKGZo8pQktGWCVwZmE1gfu7D0mSSwkCd/79d9C/tW/QWthqV+g2gbVetrQEtK44XkU/7+6wZ1MGDae++9/wO7hCRefe5pxOeewHnN0esyFZy7xzd/+n3BeqKctq73zrK+8AJUw6q0wZ8btR/fJBj1euP4s20+/SJqtUJcN569fZL9cYJ+6yNL5NX7vvTcZ9Q2Va9kbT7Fbq5y/cI62XTBSgVfO7bDR60UhKIqybnnw8DEPHu52WuWYgaBCzP9RoWMVOj1G1GL4zr3SCUd95+BRTz6DLpz+yfsmnfxEOkuWdIDmTBAdXMyrCaIJXuHawHyyS/voHeqH75KVM2qTcmo2uXm8x+50xmIxhtCS6YREPEEHeibl/M4Oz77wIk89+wrpaBmHwpsoqA7BxU1ZBEVNOHvaZ+t717ztO3ByNsYKoes1EQjBEUKIxWwiID5el93PJyHG8WMsdjhksHUe0ziUMjFUToQ2lKA1rTFIaLqEbcGbQK0DRTeyqGpNqxNMEjNLlLZYoxjgsCZDSNDBkmQDKirKxQyfBEyWEI5qEhUzNFKEnlboEAs2nYJMosYhiCIocF01h1WCsvGAUOQWndXceXyHwUaP5eCxUtA2joBDGSF4aJzHeUH5wKo1jOsp9+/dpi02UdguTt9ilEGJQmcJSdonz+fo2ZiAw6uo5fF1+cSp50QjXrpcP0EbgzEGay1ibRz9ikTdEQ5CxuMHR/zR73yL1hrmjacqS6xNSDE042MoJ6xt9ukbxWwxoacc2EBIFS5oJrVnb1qzNW/ouZJ507CoSiaLhsp5miSwpBUTo2iagE5iiJ+IItNgtTBzDWgD85a8VZwPlnOLwMDHdviFU0wSg7GBRgyl1xgPaeVQ1kS9EYITxSyAM4ZWmfj/lOAkWtzPAH633EYdngaMxtoE5xqy3LKyskKWDhAUSaYxWcHJ6Zy2rkkzTWI1aZrRH/TI8ozECLuH/37Tw7/v8VMNULJnwWwQkxg90MiTsY5qgAqkjl04TS2oVJH2Y9aJm0Izgek0njiWLsLaC0K6TjyumNjqadopUv8xSTIgWVjyYh1lU/LVNSRbR2cF4zvfxdb7bOxcoDq5x3QKtxeGwfYy4cgzaQx3xj1CYwmJoSpPWL6g+dwXWg4eW+7dqpjMYwPlNGjeO1Z853cUvcrz/k9qrmk4eiD84D3h4DRS2X9uR1hZ1jx6YFgsYG83nlzefRwTXo1VfPELhgKPDprb94V+CoNzwmBJMTqGk2lg1FO4yvHJx4Id5Vy+IPhUmJSazfU+uckZPDrFuJZeDvU88IVrwjATyhJ2x4bDRvPSeUEw7Azhy88HvvSMMMzjRjS0gTv3Ex6eNrz1SWyLFfEcTuYczzQvr6ZMp3PKicchrGeazSFMm8DeWGDt372gtdFkRQa9DJMk2CRBGxsdEgGM0l3visI5R9RRxsKrLn0NAKV0PDGpOO7BaLzzrOxs88XPf47rOzvkxvCv//n/wj/+Z/8EOx1j2hKjA0mSYlsodMHmxiWuPv85rn/+i/zq7/8Orm9RvSVSX7PcGJqmQdKc49bRKt9lCMaxQyuBVITUQaI8rqoxIvhyDm2LQSGhJeiYEeG05c3vfIuhyTifrTJpFvTOb7Ly3FX+0l/4Wf7W3/0f+OjNn7Cqt7n76BZFalnNRxwc3ODddzN6ScK1Ky9wVB0xnp7y0utv8Ev/1f+Z333zbbzps7O6xis/+xof7t+nd22Lo9NTzl+5ymRyxHsfvYXyhpdefInRIGUpKbi6PGS7KLDBgUpoRfjBT97hH/6jf8DDg/2Y3AndMCOClDiS85xRKeoz8OPsLTLm0/bpJ4LazzIn8Q2M1lYF0FUQoKI41sfMmloguApfN8wf3GZ+69sk9WPyNGWepDxsFB++d5fj/VMqtyBFCL4htQGLYmO0xMtffIPLz71AMVpDdIILPgbHPWE9PEHHYKqzxV11o6ozt5mcAeizKVfoBlYSCwuDdB+heyUkWtv9mTYgorUoALaWdLSEnD+HaMG1DcEFgo8iyCbEqgcjgUwFnDe0DWQqgA4EIzjbI0kt4gJNqhj0AwUJVT5CVIaxhnRpA9/USH2MzTOGW2uwv4vxNdak9Id90izgFiU6xBO/7wIQlYAzUBtBZULas5iexTdCaiyDIuHk5DFutIMLNeiGxAZMqkl6Cp2Dn3mqNqLRVAybqWbeOu6fTkBygvYYmxBshiNhNq/IqNGJoSgSFl6jnI/jBemKQo2mdfEdEq2jmLoTglprI4NqU7K0B3gWswm+qhgvjjl+cIBKC2yvR6z+UVjvSV1NL/EUySBmS52eMgxgrMIXKY1zuMZzNKm5tX/CRgbahRi6ZxQ4TSuG4xB4tAicr8CkAbGKBoNOhGGm0M4wcw4jipHzbKmM5aohkYD0DLsEjr3CGEXlDPMabKvYUjkzgRMRnIoAthaoXARBjhh0+e97nFVLCJDnGYNRQVHkbG4usbG+TJaNsNagM8BYltdapG1YX+qT5zlJkpLlKUWvRzWfs/tn2ON/qgGK5ERU91lw0nasSRlVx20tOKcwRQdOtODn0M4V04mi9TC4oFh7QZFthLhvWYU20Lm0oC5RKJbOr3N6aFm7vMl8PmU6K1h96nXSj36CLA7IRs+QpUNee27BzK1i1BSrWkQveOH8iNINULaP7l8jVWP2HpY8uv0+1X7Jjo0ZLBMUx8Hwm39Ysp0pQqno54Fzl4WPPoQTp9jqCe/dURT9jGEVmC8cnyw8+5WiyjXHNfS0ohk7vIdWpSSp5uKFhpB5ntsJ9BLFJw80pTeM+opcCTQV7bTm8gVhXmQ8OkpZ7M6ZjwNX12GUC2LhaCw83oO9ieZoFpidKnKTMD6Bl7YMQQeMDkjSJQkSmB9p9vYUrvXxFK3jiSpRHq1qfuYpw1u3FJPS0KYGZWGQOQ5OhBpN70+88wptNGmRQ79AJwaTJGhj4iLULY5n0W7GasTHTcQhhM46rI3GKBW7JIhlXaIUQQy3p/uc/P43+LmXP89Gz/LBu28xnx0wCC0GjwYKgSWTk+U5y+c2+cYPv8sPb91k3tTc2rvPWqoYBM35wYCmrLCDAY8Wnv26woyWCWnK8eSEfNRnZXmV+XjK7HSMLgyucYj39NKMqm0Qo0lsgfKCswk+Vfj+gLHt8fmvfpEqT/mNG2+zf37AHSlZeuoqwWasL21QHp8g4ih0iqtLrDJQw/2bD6jLwLu377D4l/+cwYWL9HpD+ueWuXV4n73pLv1DzQvL51hNhtzcvYE4zfWrl7m8vsYn77zFcDRkdfAsPYkOqiDw4fsf8t/+t/8P3nr3bbCxbO/TaU20FX8KMc4SejtGi8h4yJPPifoLrW1kR86Ez9CNfLoenScapLNJeWQn0JrgW+azGbOH71Lf/jFptSAkAw5cyu7jKfePTng0mce8C+3InUEb6JmWC9eu8/znvsKFq0/hbUorGu8dvpsxRrDlUIZO6xJzHsLZ9aeIkfuKaNNWCqM1qqNYYniVewLMzp5/lLDE18qHqGWJMK1jh0SBSdDDEUnV0BvP8FWNeM+8naNFcM5StZokGAYITRDmRjCJwjuDyQYUpse8nUKjcPSY68g6JlmKZANakzJc3WL/0QGallQrMu8RUbRK400KbYmSQFCaxBvOgjQ0KlYOWIXq5ZhBgSamjOJhZbDGuedeZq+6hzMCuaC1wyQKY6NFFRODUepJiOM5qUnJ0MExq0pM35KkGUonGBKaRU3VjsFo+v2C47lF4eK4xJ/BYP2EwXqyl3QOljiSMFitSbKC0dKAjY0tcpuwmM44PjqlqgI0i7gSaYPRgVw7cmMYWBhRUrQlbQMqz1CFoZ4JjQrM6zkHswRfBUapJ+9nFE1D5QTEUpc1j33DaQ+KLOYj14BklpWlDHUArTKIGPoGVjH0mriWZv2UA1dx4DXeqcgQNY4tydgKmkMVnXJzFI0XTFBUzuEQGq9o2igPEKTLDZNPbzQVIxmyLKNXZCwvLzHs90lTE2sA0gSnHNpokkGBYRALM8sW2wpl3TBfVNTzxZ9pj/+pBihA3IzaM8ZEEUqJI54m2ohdC6aAZCRor5AZuBlMx0JdKfpbipUXIdkIsc1dAUY4A9sigporRFdkqy1L2TIq3GCQebIJjJYHnL+6Sa9/hdnjRwxeuMiKfpeRP8amPYKx7N89oW4P8B7qWUBaTdvA4cySLRq2t8AbTXKkOdEpXgnPfP4iT20P2Xv7Q5pJRbGsOb+tuf/IkaWKcSWUQTAuYEygGAIZZFZQqWFrVTOiofYRwZ2WnnGZsdoTElvz1S85Xr6u2Dd9XnjZ4+bC3/2fWy6lmrpRPDqA2aLkuAnUPcNUWfZOWi5seVZXFLW3DFXC1kqLGyt+dA9GCDf7KdmdhItbJWUV4+OPx4Zaac6tOK5vW955KExqaMVjBC4OhYujhuSphA8eJUzbhN+6mXJ+M+HSiue0zen9e+aWooWgAmiDSTQqsdEV4TzBB3znmlA2NqqGbgN8coRVMeRPa4vWmta3pGlOYjWjomAnHTAYZnzvm9/gxoc/IaPCaR+tmi52hvR1RkiE9+5/xCd7u7y2OmKjp5mYln5maRYLipUlxm3N49092iSlxBAWjutPP8+Xnr3G2uVzXLr6FCeHR8xPDkhUYProgGThOXz4kJrA4fiItf6Qh7cfsLFznuG1i+w8e5W7D3b5TnmELZaYXVzmOw9vkJ1bw4wz3nv/I47uPWbZpvzFr/8c7793i/l0wbmdS1x/6jrF1pDxj/+IlWeus3L9POefuYq3CVVWkWrNM9ub5KcL9h58RLuxzcHJmGxtiZ1nrvCdb/whcuMeL77wCoNzbbS4Ws1sNuOX/9E/5tbNj0nTJI4/IGosAK8EMaCeBJXxKYOipDtxxDFRUPHj0zkJoKPlO4RYb2A0EVQGhdYGUYInenOdKNqyYXb4iHr/Pfz4Jta0OJtxtEi5P5nw4NE+i9rF0ZQEMiCIYzQs+OKrz3H1lZ8hXzkXY+OJjpQzKyYqaixMByiCCK0PnQ4mgind/aCiBB0MqAStO0blLAdB+U4vEX8b83ieaInjhiEB76QDaGcATkOSYkcD7PISRbmgqR1NGr+4QnAUNK6mlBpEY1zL3Ci0EfpLAZVoEq/R1kCiuw1XEJVCkmOShLaFkIBrNapyGOVoRBOCwjWKloDymlYgM1H4HCR2iScOrNa0KkNJDIUTJZTVjDuP7/G1r/1lJg+OuVuXrBQpfRWTcbUPaAPWwmCgqBrNZBZoUXjnydtALxhoAlmuqIOjbjwDXWBSRa0CSZLQ6/VpG0fbNJg8RUJM2v00iiA+zliuEAJNG0eLNm1p25btnQ1eeP4Znn/2aVpHdOLNZrSt584njzh++JDMl9TTCf2wYFB7ttOWULVR27U0YL23TWUsnzzcYzwtUXlGUIo0EUbDlEk9I609OwLrto9ftJSuxVvHHDhqA63WKOUJQaO8MFAtPT8jCVEvkqCQtuZIpQSbkrcNa8GzLApcgzEpp8pEmz+axmtaYlNx4wUf4n2mtX6SpXNWCUEInSvHoZQiSRLmiwWHh0ekaf0E8InE3Ji2jaPKPM+7fdSDDuAiO/ynffxUAxQVBNUoqIVQgswkMiitoq0E70H3IRvFwK0wEZqFYjqOzEq+CqNnhHRdwIDYzrLYRvQY15b4Z6oQxB2i2vcxzZi8p7D9HYy5xdaVnAFzymyDhw9mtIdD1s8NKcMKi+mcK88Ii9Mp+wfC8cRjjZAtKy6sCb7UJEVB6zU+bTmaJBwtHH015cLmAD+Cm8fw5oeRrs57isNK8KKwFo5U4Pk1YXkoHMxATaEwgYH2rOWQ58LmqOVoprhxL5DdDVzfEOSKImSWS1eEc+cCs8eBwZLmNz9uuDBS/IXnHFlqeOtjz9euwfRU8fFhSuk9Vy4oVq/2MVPH6USIRQ6GJSv4OjArA3vHfa5sLLi7b0nF8/yFObNSmNaK6zua248NT6/mXN2pWO0LRU+41Hc4n/LuJy3LmedkNmU2LxgtOf7EJgVPdjelFaobx521sZzNlYFOlxBPBErHsCCtTSdS7AYH2qKtwTuLSQsuXjjPtZ0tLo2W+MKFbT741m+DqwCHdy3KQSIxFE7nQp0IH+3dxWmo5mO0Ubj5MdN5YGW0xMPpCfOhZbdxNImBlTUuv/wqf+3/8L/nwvkdaqXoraxxNTUsp7BmLWukFLXi4cP7SC/l4PiI2d4xv/wP/ymf+7m/wAOpmOQw3xhRN3DiGlQvo57NqfYP2L9xk8X9x+RNQ2sNb3/0PmUNX/tzf5nlwRLf+f632H7uPF/++p9j9PIz1MsFvm9pQ00T5uS6xxevvkR/Zvnxj9/h7uFjBueWWL68TZPB+tYmL6xepDersc6gXNQAvf3WW/zOH/4elWuiJghi9ghxM6eTi336dnasiVJd/kcc4cQGaXNmzolvZVcxcPY1WncdTNajvCHu7grRgbZ1uNmU2d4N6oP3SJs5WMM8ZBzNT7lzdMzRYcm8qVG+RSmFEVhOhQs7Gzz7+htcfvFzGF3gg8edaWU6dk53zE7oFu8QOlgVBNEKq2LuiVeCcmdATD1JjfUK4sKi4teIi6AEFb/nmZOJbjThBXEdi9KxRkF5lNKYPKNYXYWyZeFaVIgnNKME22Eg7RXBNlRKIZUhzRRZmiNFQjuNwEm1kOYKQw+xGmioK4dyC7TUtJUjhJSFieLznotOqcYaUgnQxjJHpWO2iCiNChrtArSCTnvU3hDaBUocR8cP+eidbyJFxnEIPGwa1lZ7tH6KamLJXBBQWshSRWoCNBFEDBILrcU3HnEerwxt0Pi2JZFAXdccjk8om0W85qwhydIOXHZrQzi7lrqNOHQ6NuL1U5UlglDVDQf7Y95//w6vv/4qV65eYuf8BlevXeXb3/gRv/bL/4yiTZiWEwqp6LUlG7ljWjmOFw0mDawN15HVFQ5PJtS6pnEVpcujc0YbBlnCalPxgjJ8bvMCrjxkNjtAEsWhE/a9ZuY1KgnQCKk1rBvLkhOMb7ACTiKMLlXAek3mhA0LqyrgQ0Brw0PRqODRJsGJ4HzAS2TltBLOgl5DJ0QX759oWpUI9aKkLnss5nP29vaoqoBNehGIhE4AroUsS0BrZtNT0ixjMChYWRrRz1fYG//kT73H/1QDFGmAVqCCMIssigRFW0c0aAeKdCRoJU9SY2enwmIOdqAYXVfkOwIpdPGFiPuUQlYBpLMJysKDC1h9QLFs0RZSew/nfociv45MjkjyS6xfPseJnlGnOad1n5WLHuum9PQdRr5Bnziefm6F809d4N7dIw4ePCY1in7eY+NaxuXG8PGdCZsrntOHt3l40HAyV6SNI+8rrqwI0wUczgWaktUlOL+h2B9HlmB1EHh9oJmUisMT+NrlgDKaWxZ+cD+wWQiDLdi5rvDzBnUinN5PuX8rcPd+i3PCvWPh/XvCf/a653CkuNQP7HnhcNfy472U4xPFqz9XsZM5Ti9pvns78No5jXaOW8fCrQeKT1TL7XuGxBqeutgynnmqGsoaQqNY6Wvy4LmyHlNKHTGEyytYH7VsPOXx4ikXM947WGL7U8nWE5F5ULHbwXmPakAlXR5GR1HKmSlVxUVAGY0y9kmAF+gYLqQMKklJM4OyKYezKYNphluc8P3f/pe8+e1vYrQGr5GgSZRiYFOk8UzbwMFiwbhtWctHrK+tcOPD92nFsb29xXRec+wcxdYGV65e4sLrn2PzhRcYbm6ycu4ceZqxPhiRj1YIvmHgGjaTPr1a2Hu8y2RySqoG7N65yx/85u/y3gfvonY2ma71KfsJppfTT8HvlxTAjbc/4uj+fdrJKcYFmsQwTxPWn3maV599jV/6T3+Rj37yAT98+3sM15bJd0b4tXVmlGxvrtMTz9HhA86vrnDnoxv0/RKbzz+DNTNCXjNa7rNKynMvvsJOY1j2hqzXQxvLJzdv87f/1n/P7uEeTp3pQTrFyBlbcmbhpBPhPTFTffZEq578WysdQUn3/ZSKG7juvokEhVYGq4VGfGRdPMyOHtPc/Qnh9B7LS9BmyyxmNY8PF3z88JjxvKRxoEzANQFtDcuDhGefuc5rr32FwdplWpPj5KwTKAZ4qQ6IxDyWSHF4123IxJyIaCUOmABexwRZqzuXixJ8iP0mBEEphxbf9QLFTf3stYknUh1HPeHMlRLtoAofwYAzKJVillYwjSNtZmTlFGkrRMcIc7GaBtC+jkWIxtGaDFEFSTogmBmichqXQOUoCiE3FnQCjcIi4A3NrKaazrCtIYjCJwmthkXbxvtRoA5gI62F99AoixdD3bT0jaUpA+IUSZqwbA03PnifnWeeQvUSbjxaMMosz6Qmgj6vCKJwLhYCLvcscwInjafIMnrO4J0nWCGpGvZKhyoGmMTQlC1t62iahqqtMUYx6Ke0Lo5xJHRxeRKTU9ECEhNjjRFQhta1hIViMV9wcjTmYP+YWx9/Qm/QY/vcKi+8+Czl2NFWJZmv2FldYmAnpGFBz5YUSYDGUyyEQa/A6T5feO0ZXv3Sl/n93/ht7n9yC8RwWtUkwNUk5Skb0CePSINDFzBu4LBVPKwCx1VD01nSrTIM0fQLR1HE12peQOItizYQFo4rKmF76Ci0UFtFlUQhtk1yEpsStEF8Q+NdbJ/WMbgyBBVT2s8WWTSxnE5wZc306JQsTekPhzR1jSde771sSFEMKHJD3k/JegVZmrK8vIzVmn6vwLuKvT/DHv9TDVCUjx6pMFdRgxIUbRMLqpKlONZRSLQYzxWzE0U1C9gU+jvQ2xF0LkgSqX712Zlb6NhmraCF0HaiSiLgMT2LVqd4dx+ZpejVy/jDCZm0NOY8d9+7yUuvaIqNlzDFKtXN38Ee7yLWk6YpVtUsLY948GDCxlrOaHOd+w+OSa3j8y+u4psWTQ/Xf8S0KrnWg6KAh6eKnhGeXhJWe4pipFlZh2wD6lOFdYHty2CM58bHmv254dnrCZ97JuFw0PLmu8LkVmC/9Hz1KTidCN99O7B7LKhGuD7S9Avh4kjR1oGNoYA1lJUjRWgaz+mp0J4opg2c7gUa59mbCb/wkpA+NNzfD6wOFLOZgazl/kEgNfFU3HhL3ya0k4AkgXiKhKNJoGkUS33Hha2Gx2WgyBXHe5qTRbfRyacyLm01Rb+gznsErdGJQacWZbuCQIG2bQjBxQVdadAWlOno9dBpHUBh0SZD6xiu5YNnd/8BjQR+8v0fMB9PGaokagGspV3ULC2t8fnXv8huM+et738LSBjmfS5euMDe8WPKkwZlElrf4NDsTUv+xn/932Av7bB+dZvlfk5fYCiGpC1xJ3UESiS0bcuN3X2+/eYPGDcLEqu59877fPzRxxwdPuYPvvk7XPnzX+HF577M0d4h64M+f/QH3+bDOw8I84qBtYRiifliRsgsF15+kb/8N/4Gi/sTHj/eZ21zjeX1dexoiF1bY+nKZQZ2gQ41T6+t8dxKQVUrdk8PuXt8hGsPYVNzbWmFbZ1yUXLWexnDXkKGQQeYTib8yi//Ct//4x/E7I0uEVYTk2Cj7VbFsRyfuc/gSV2BiDyZ/cTJjnw6AuqEeip+x85p0AlmVfzAQVtPqU72OLnxXYr5Y3rDAaKHnBzV3L23z6PThkXZ0jRtfH4hMEgTtjfWeO7l17jy/MskvRVqJSBNB2Q/FcLG0U3sCALigSacnTI7FKZUdOecaR0ISFAEFbreJ99BsE79JKFrJo7si4iCznItXSFbF9QT/w7RiOpC3/RZ3oQlWxmSz5eopqf4siT4qAFrDLSSk7QtbShJUo0NsPAphQypZA+VaLwBm48gS1E2Ix2sYnIoTybUtSOkMVzS5ppFo2NdQKvIRWGDwtsY6+8EghhskePzEaP+Oi/+zNfZO5mwOL6BqBSvHfXUUU/G+CsV2gqzYcE70wal4PKKoRdC9/rHa8gYGBaK7WA4Hk/Jmoy+FdpmgUVTWUH8Am3WIiNmDakktMHh25pBv0/tPFXV4l2X2qt017cczhA0oLE2HmYEhfdRK1Q3c+p6zmw+Zu/RA9598z3WR0ts9gyKitEwJW0XIHO0NGQaVvuWDRXQbsqzr/wss94KW+fX+Ov/6/+E997a5ic/eItqMSMJwkh5doqWwkfQbJYtB3gOmoQHZeDUCbWJ7eyhbclS6Pc9gzSORBehpvGBqkkxKPK+ZpgHtHIoqzHikDJa8RsXA95arQja4IOLrF9Xrhldjn/y3hTAe898PmdYj8iyjP6wx2BlmY31dXppD5vk5IMcpT15lpNlGU1ds1iUuKbGh+bPtMf/VAMUaomsUhOpXeeEoCBZigAFJTBThLkwO4b5LEAG+RoMLinUKCCp6gRsZ4sLsRE5rhFxPXARWSoBqQMqeMTlqJFHTirM/C5maZsmVLjj+8wOdxj0C/T4TdryI+zKJmpxxPxwytF4iPMJ1TQwWaQcTBW5XXD+SkJvtMo7795hfdlT9A2Jr9nYNHxyAw4mcD4XBgWEKSylCo/FpwUnvubefUfaBHauaBgoegTOrcKjhaZ42nJpU/ha0ucH70x4cOQIC83VQij6AIbZ44ZnRglXLwvPP+uxWaBpYFNpdmcZ+UgxLAN1IuAUu58E9kvF+3c9qZKYnaGF1SWhqYSdVcfHswSVaH58ACmaC0s5QWcks4bGKR4+Fk695dw6vPSU5/C0x2AkhLZGzaGshduPPD75d996Yyy9QZ9ssIy2aRRjphqdJAQB5zy6LgnB4SUgSmNM0hkhInlurELQKNEoLLlNyK1lyWpePrfBlaURD37r95jUFQsjpKkGL/TShMIYVGY5mM1wIiResGju7T5mWtXkvRGTWUXrAgvfINoyPp3x2s5FksRiGkfwgZDEmvijo2OqpmWQ9bjTeh6cHPGOmjGl5OjWQz78zrcIeyfU1qC1UI1POLl1mw9//GN2b9/GG2Fpe4UVv8x0b8zBZIbJ+rz6M1/m4tPX+fa7H3HOjPg7f/cfsPvgIXq5z2uvPo9fyZg0x6z3DMtJwrXCQEg4cDW36jHL587hVgZkyzmb+Yjzaolz5OQmjibOZK0/+v73+LVf+1Uc/kmqq+LMefLpjP8JYwKfUsfdIqiUeiJcjNlQqhvlnRWMKZQyGCF2LHXaEwW0XmgnJ4zvfUBzcIORPiFZGuD8KoePxzx8fMz93WOmbcOibWOMgFOsFH2uX7nOtZdeZO3CJVS2REUg0RKBRAgxZLRT0zyBVhIFq1E60yWOdv+cadeC0pguwyUoFRmgEEcIce4TcyWCnI0lY1FbvEa7lu0n7p6uaE0E8JFO755RXJsUadqjv7RGeTJlPishBNLgSXTc6F1mEJ+zCA3WKQoM1vQI3mJNjdIFWIvKc0gNepCQ9pdpyhpbJCSpJe8XhDCJQYdK07Oe3AeMUqigqEJAaSj6I5LhFk3SZ9Hv4bOCtr4LzQmYHG0gVDX10TGheRakxotnj4S3pkLlNNdGsUlZxzccQhytDjPFIvOUriHRQqo9xqaU1nDczpkvpgCxV0ZCtL+agqPDCU4c3ntskqKUwrsO6KkoZBbxhBAPTWkaE3Cc008YLKPiBmGUAe8okkCmNcMsI1UeKRtq31JJS+MEYxLyNEVnKdOp48HhEcclnFtbxStL5YXWg3aCTYXRstBTjrYOpOsGdQrTRpiLpkIITUtKglLgVUClAVXEJu/ppKYxKTXQ0xaVeBpVRwbMWPAabXOc17ShpWkbmiYyVMoFnERgJhIxcbxnDQo+1ZF1H9PpFO89OtHYVJNkltFSDy+GFgdtQJqSclrGFOEQcLrFGP9n2uJ/qgGKlJ3w3ylaF1/EZAjJksSSuYVCFkJ1qphPQBlFugyDi5CsEcsplHQ0VrxGpSUunCaejnARORothBZAYQZCvWgwwwSDp5lVqJMHKB+oQo+CPWxvwPxYM1xraU8eMD8ueTwGV87IdUszX2IxTTiaJuTiOXh4wmSR8ODQcXpa8vkvXeSD947oKdjeNPgjx+wkztwnrXC7gp4EVm3Jd29qajKcq0geCK/eEf7CsxBauLZj2V5VpEbItaNIA0sZ/OyleFhtQw9/4ljJhIbAnQNPr4BXvxAbhvfvCXfvCU8/12dna4bOFAu22W+mvH9rwrBQXL5oOL/UBU01Lct5xmCk0as9Do7mTGtosZwPGcdTz5IJbG+0rOEpUsX7jxLaKiczwnTSsqjiYXFWKqoKsrOk+yc7W1STb2xuEYZLKJPilKcVj05jwqNQx+hmMQQXC+iUsXEx8u7JguoBk0Wbci/JWElTXlhf52vXrvLP/v7f4/7HH2ITQIUup0LwopmVM+7fuc0H92+ivGe1N2AwXOLHH76PCw6HJ3QZDgsDzz/7DMPBEn7RMBr1ODg8YjabUFYVrvUcHR1RBc/S+jreKA6aOZOBJuQZJ6niWCuwmjQfsbq6jts75ltv/SrTZsrGlfNceuUZfON58IOPODw5YW3nIk+/+ir55iq3jg/5+HCP8/kIvzjm9Te+TGUV4+Njntq8xAvL6/SHOYn3bNiU+wfHJHnCU194Fptu0lZwMD6gV1hGNqWHJVEKR0yH3H/0iP/pH/19Tk6PCSqc3U48QSBnp2Dpxhjdh5LP/i5+bsz/OEtBjYK9mGCvOgbFPNFmnGmQXKtYjB+xuP1D2pM75FRYPWDSpBwdzrh3cMyDoymzeYvPFWlusK5ifWeTL3zpq2xfeQ7bLxAM3klMGA2eFsEE9+mVp87alcOTnIz4XLtoehXw3RgKBCc8cUIoAyZI18fDkxFl6EZWHWEUwY5Ix9BElkJp6Rq0u1OtxOAxG0tkIsBWQkgCycoy/cU2TetYnAiiWqRtqbWhURk4aFyDIcMMerTGgRZ6GiTJIhtjoK0d9XRMP+2jshydppiJQjcxPVZswCZgdY0NFUoMVmCQ9WmsQC/B4VG+plzU/Pjbv4mbTpFGkMxhTUHWzyiq2IG1hDDWDcdiuFVrxhNhXsHlkWFQdCLkqF7Ch5Y0T2jLGq2EnISgNEMlLHTDvJ6gdYHWGh00RmVIKrSt65Kl/RNm1SQWbQy+rTuAort7PIa3pUlKXbfEYFVLcC2tcxgCRarBL7D02FztU49nzGcNYoWZgrlXnFQNI9tjZWmFtz96gF69wLwe8/jOI3YfPmQ6a2i9Aq8olcf2AisrGq2FReHJx4q6avEyiISZtrhOpO0iaYgToRJh5g0NBms1oKlDSxMCWkXRcNU4Fh4WXYVCEEPwDpyPGqoQR5hBqy7HJxoKRHcThkAcvSEsZiWT8YxiaUHQBueE6cmUouj0S0qhfUwU1sqQZSlJrj/jDPrTPX6qAUpoFJLxKXPSh2Ql3mChgrAQ6ilMT6M2IV0SBucUxTZI0VF6HqALTnIg/ow5iUJZ0ZFFla6qQWeCKQLaCU0JzvWQJuCOHyAmp6xWGI4ajDthcrqFnR2QZJ6jQ8ePbgvXLyWMBjOMNbDb4mvHXLW8e6fhNCjSwTKP9/bY2z2k8prDsWI4Mqxbj57G0q+qUWRDeOPnM377+8KhcxgjHCxg1QpZA+UheA239z37v+K5ckHz5u2KZ1c0v/Q1yArhm9+B072K+jSwuhRYXvXsl5Z7DxXrS4HdceCb7wh9aQkfaL74+RwzMnzv7Qk3HswYiPCfPRfdALNa8fhE8E1gNPQ4bfnS50v29lLq9xqOSk01rdgaRjr+q1+KTr39PeGkFI5OYrzWw8eeIhVWcyiM8MXLilnRzeU/k2qYZRnndrap8z4ejVeByjWxnVZU1/8hOPGgDW2ILErMnIiDAoOJp3TRJKIolDBoG6pHu9yazXn7+98n6Wh47Ry5QE8Z8uGA0B+y/vwzqMNH6Npz8fJV/vP/4m/y9/7O3+H46ACsQfdz5lVFnRrOvfQ8W09dRWU547Li490HPDo+oA4em2QEG/BGMQ5zZvNFbD/VCt04tLWsndthkWT0s5S6bDi8+xgpDJ//S1/npS98jk9u3+XG7Y849ZqrX/oKV596hpAmjMOc4aVNjBHUpGK4OuIX/tJfZTGekqw0PL1zieEopQ2dLbGcsLW8w5GuaY1lUdUwb2kOTsnXNknT6K5QojBOoG1580d/zI/efZNGRcviGZCULnANiJkhHUPyhIc4G4v8CYDy5O4GFVCkTzZ8lH7yawkK74S6rihPDmkevIc6vM1yppDBGpMycP/xAXfvTTguHXMHXmukgaEJXLnyPM9/9WusnL+CR8UQvxAZGxMiMwMx1fVsFAhgzsDDGdsj0fxrJD63NgieKGlQSkXhJRboxjIR9sSbUyKrpOhs1nQgvwNums623IlmXTAEAgaP8V1Sreq+VsUxj7GG4c46wTXgairf0qqAVTG0zrWgjEYM5EkfB6h8FFkp0dgiwyjwc4fJLVIH8DWIZ1D0Ozt/Qg9IlccYIZWo6QpKGGxuc9yOCT6g6gpdtBQ25g00QTNezGjrE3K1iQ89tIr9SJuJpkoUPqQ8CIH7rdCMG1pdcN55tHFoHcAayDRGPGsbQ7LgCCpggidXkOtA5WryPCO1UDmFtRbnmng9ao21lrZto6BTafKiYPXcNqenY+bTKd552rJmzgyXZp2VPObWBBU3dwkO64Sl9WW2csNKmHBUjdk9WjDsK5rcMA2ao0owibBwOfeO5ywxZjI55url8ywvjbhvNa4WgjLseZh7R6s12TBWPAy0YZgkUJnuOcTckmAUMw/zoDFeMRPFWCwlFoyhaj0zb6icBR0oMRyLonQBJy7WJnR6pkSb2N7expJUhYoFit02yBnzyacN4uID+7uPyXoF1WzBPD9lVhSMhkPSQQ9tUzKbYdIerQ84V8VbvGn+hL37P/T4qQYoeMG7+CLavsIsC5J0zMoC2qlmeho3qrQPxZqi2ALpSRdHzadzbg+0n9LNBEFZUFZFFqUFlYBkCpWByhx+Cj4MCVrRugHltKBnTtHaUddgslV8rWnLlgdHGZO64fxyTXmqKbY38TJjOh1jqoYj32Nlc4CxHuej+K+XGu7OApJ61pdgyUDmgTzlz/8NuPp0n97yiN/43bvsngRWLLwyhIsWbj2EYDWpUrRly41PFKPCYBvLB+84HpTCo0PPbiVsp/D0klBkwr1jqCvFb38HdAo7K5pmLlRly/c/tExqz2yvJAtCL4u2y0FfoU3AWoUJmmoR2K88z1/15NQ8fKx4+InnYVrwVy84QivcuAEvXIYig16iGdfCYKQ5aSyPp8IgEXaWwU01C5ewjOruFgAhSSwrSyPa3oAWRe1bdAV10xASRQi2sxl3tpFOvR/d43HOrzptXJEaVpKcbWP56vXrvLC9w2L3MUMPdlGjlSMFRjphKeuzPFplUlf8s3/1GxzXFYPBEnXr+YPf+wbD5RXuHzzGKEvjPVMlJOc2yK6c54Evmd6/iRjHcTnFDXPEaqoQSPOcpq04np0izhGsiUjbapZ21tn+2S8xe7jP44/v8ujeTUYbG1z66muMnrrIh7d3uf2T23id8+f+i7/J9tY5Dg+PaAz0dJ/gFrjTU+zC88yFa3zww49ZM5b9H7+Dnx/wzOdewMiAJMtx3lL0eqxrR+VaKqUoXcWr569yPV+j58KZgxblPPuPH/H3/tE/5GA6RmwE9Vq68r8OgESqWH/m110qbNeYqj4DPM9IMpHYOG10zF+ILSmdsyVovFjq2TGzRzeoD29iykP6WUKS5EzmJYeTKY8PD5hXUZytRNDeszzs8fwLL/LCaz9Db/0CjXi0ajHYTwXWREukDhDExrh08fHJiYoRBJ0uRQWPaIsjsiOqc/CItJ2+JAo+lZJOH/VpIeIZZR5HNSGC53AGn0OnuYp/JqjI+vlOp2PotCzdhoEGZdEqkOYFg9UVXDnHtQtqVxFUBSaK0LXRtEGwSmOTPqcqZaYCvRyUdjRNglIJvdEKeb/PfHZCqntMygVVq3EhgAkolZE4wUhLauPY63QxwUuFkgybKYzy5AiJLnBrBdiEKlSc1hW5zgm+QRBGqeZckmC9RVJhzznGFHzsMk4WitVMU9Cyfq5gtD7k0XsPSIJjzYIJnkxB4gNJUBjVoH1NaiUmSRtDqlMaFygXC5RSMTOpC2tsmoYgwurqGltbGxwfHjCZLvBNxaKtYoKvNtE1hia4huA8Js3YWBpwLp3x7NIpJ27KnZsLplJgtWHiLRMfNUOhMpxOp3j/kM21JXZWB4zHjn6aoqYRg+6LcGuqWel5QgKNUeQJbA8gqRxzneBdiInLndDaVY5aKcYI+3UEJW2nITmoAwepYsUYXMg41oHSh0hidNa4xFiMFyrxYFVXs+CJfQCqy/BR3X0amUIl8Z6cnIzZvfeA4XBIkib0ipywvs5GtgNWI6JxviG42O3WVA20cS390z5+qgGK6w49dtAJYi2EUnXgBGYnEcDYAtJl6G2DHsqnORhnUecOcJEuPjudxTyUTp8C8ZWyCrLIqqR9oT71FGbOYrTN7KChXniGywN8PaHoW6ABtcrB/Ufc3LOsD2Bka0Rt0M6n7O4vmMwWhDSQJQ7VTlmcRIFbNV3QljXiQzx/aRj2FWmrmGhYyuDo4wnsTmgnQlErdjJYVbB/CrfnAkZxeVU4vy40iWI8DVSV5+3HFnEtS314NA/0V1P6hScEwTVClmqyJRhlwmQqbC8HBj3h23cCzgl5ohmlGrGKt45hmgsvX3Ns9OC9H2veua9otWPnpqepFLOFIleOJdvSLBxfe9Hz4JHm/dsZ55/Jubqk+WEVeLgQri3D+a2My6st2jt+fE/BuX/7MpVOlZ/jewUtULaKECqcExQhBkSpuNQnSYJ4hwvhyZhBCSSdmLYvihVjefnKNXaGy8i8ZHEy5urmNs14H0kDRwf7KBJ8UGyfu8jmtav82r/5bXR7Qq8/Ik0Lvv+9H1BZkEEP8pT+YEB/Y5Wt11/kQDtu79+nFchTRX+Qsrw0pHYtbXCYImd8UjJ1JYkysUPIgE1ShoMh/azl5NYDHt9/xGhtkzf+0l+gXM64f2+X+d3HvPGlL1P3UlYubLO6scVgfYmbD+6yvrxBvbvPcmJ46anzrIRlfvj7b/Pac0/xje99n//un/wPvPjCc/zCX/wlfuFv/m9JV1YYUzHQBRdTQ6sD1cjyzOo5loLCqkAwcdShrGHS1tx+vEujY96FAYLv2ACBM0uc1p9hVc42aOjuL/UngAkQf34MrW8ja2AMnpgFUtYl1eSI8v4H+P2b5DT0VkeIM0wmM04mx3zycI/jiaGUDKVLchL6owGvfP5zPPP5N0j6ywgG7aJTKIiPr3dXPighFveFoNGiO5ASAYqWTi+iQhfbEjchtI5SCRF0B8TiD9UJasXEPqIz0W/H2iilSEJkWwTwWoEykWaXgO5ixpWA8YEzp7VwxvDG3qk46tFIIqRLI/rtOk1T0VQtdSsENUOMpxGDwTNdTFge9EmIDeNWZxT5csw7SRNUolAWbD+h9Yr54Qn1+IQcH9NU+wNcpdChiuyQTlDGkKoMjcKaEK3OjWZzvcfy+edR/S2OxzP+8A//NWlbkZsErTTGa/ptn1HdcgHIU8s0TVFZj30XGHtP4YXDgxY/XTD1Q/ysZS6BCyMXs5CMkKmAkRp8QUFKaQWVpbRKkZuUiUyo6hrn2zg+VApC4PDwkCRJKYqctOizXmSkSYr3wvhwTFs33XUqGGJSdZZacqPZShvOD0/ZsAu+V8CH0walLHViUKmhVT0eHU7w4iiSlO3lnFXtSbSw2s9JDi2NRAb94Qk8vaSRhVAaRSNCZqCXKY4XNUEMmdGsBqHXWvzMMsNz0kvZdcLUOQQhiKbxnrIMDENGFTTTyuO6+01pg1WBRFuMKNBRRyhnQFtaJGiUj+CMJBoMdBtdUD4EXF1zsHdAuViQZpZ+r4dWUIyGrBU9AsTywKohNB7fRm3XfzQARQzYUfxQOvbvSC34EhYTcE6hU8H2oVgDMwKxQHe6k88cmNSTBZToQuh8c+qshTsB0m6hIP5eFYr60RzaKaPNc5QHx9iiTzpYpTp5iCtPsUvn2Z30eXx0wleeDoxGmmS4RlUHHhxWeOc58cKlDU2hK0yoGSWORKYMEyHHMdKwZhRp6wlOs2I9B28pUJ6jXcP1oeZEohVZI6iesGY0s6lQJJ5WNMcLzcqKZXwSafl+4vloDJJpHjrL28ea1y5ashSS5RQVat75OEban7sY7ZKfu+w5ONEcjBWXtmFt6DiZw3sPCqazDKkrPn4sPHPOkydQHgjHE01ZKvqJYsXWXFqG8bEwnTkGNuHWm4HR5YxrT2m+/c0jpoee/FSx9HyfucoJWcXWWtQBfEoMRttmP09pUgPO4Y2QpwYvOa0LlE0VA7HCmaX4MxtkAB0ExKFaj9IGnXuO9vb56PCIa6ur/P7v/TZvv/tjXv/yq1S07P/RAU3ZspT1SZKC927eYnd6ikazurLO6198g7t3H1I3JW3tqasZrmn4+i/8Fc59/kXePzwgpAmualDG0JQVM+cJxA134RsmdYm0LUZbVO1RWpMYT2hqHty4z4PbDxhsbvLs66+w5+fc+/G7PL1zif/df/1/4aVXX+VHD29y72CXiysj1i5fQtVThv0hie/xxmvXObr7kB9968eYVLjy4jXW71zl+M1v893v/DHnly/x1/7z/w1V3dBmhgWWUhSpUZxfW2NA3ByDgeCjYLQWx1FTki71CXt0+oi4cX76OLPL/lu0rnz2l/JktnP2aUoZrE2i1RPAx9NYtZhSHt6n3P2AMH1EbiFN+4SQMKtKjo9P2N1bcHiimXsIuiExho3lDa49/TzPffENssFyzEjSseRJiceLjRqPzsWBstECrAUd4sL9JN1WoiZEqS4vwkVGrotE6VxFn2ZLBFERnEjEa+aJWLgTDotGGfXkpGo+g95ExbRjDx37oaIGRX1q4VY6ttRGq7LBY1FFTr6ywrBqqWc1ZSW0VUBpwfmWvDfAFBkmswyKAgFqySiSHJtbrNMoV1GdzqOWK6kxMib4KWlmSUSR2xRjDK0TMFC5gG2FYnlAaGpyFeivDBktbbBy8SXWrj6N7q+xIQNuvHOD2eQuQSXxYnBC4VJGVWCoazYTx31x7J7UHOsIYvom46Q2OJ9yOhNUA6d1Q1Ca5ULHahIUuVGUwZOnCUXwqNQy6PWZTWZYa1FNE11ZznXCY2hDwPvAbDbDGMXycp8szVEKhoMR2ZplMCwAw2w6wzQtPYSBr1mSGYWa0R9UvHZBuPluy9HM4PsGkoxKNM2ipEg1hVH0tSJTDV7VDG3FsO9YlIa8SThdlJyMo22+zQINUKIwaYKtAloJa9ryjCgutIF0DpXq0eQwDS2VRKY4SwxFUKSVwpcxxSfHkiSxH0kHwerA0CgsAbxD0Dijn4y0ohc7WvdRAaUNyuqoh/KR4WyaismpI0kTmrqKCd1JGos2s4wiH1AtKtqyIgShyDSjJ5rC//DjpxqgJEtRc4KCMAepFVJBeQpNl4thMsiWIF0TSM/EefHAE4OVQHWgpfOboS3g4p8BUXCbxdNEXIW6E5SDxZ7GmCOaUyHNltFmgdItJk1QSY6rayr67AyPuLzWYrIBSWa5ceuQ2QxSY8h6hovrsebauJb1AWwNHXd2PRt5YFt5BvXZKFhIfMudm9Fyt1MEVs9pvjNJ6Bk49DA/0jFGPlVM2sDJMThtSEcrTOsxftFwnMPtKRSpR506ZJDQm2eky575pOHo0NN6xbUN2FgWbKpYXxOqWnjrtmWz3zDzgWTNYEvFzUfga8vl9ZbnNgUXAmWrOT0WXhoELj4DgzwCw3ohrC3HuPp79xao44ZkWfHcS/DWrYSHBC5mhmcuB5aKlGmW0Q1mujek2/S8g9CiEayBJDHYICRZStJK7JkILc57Wu+iqp8o/ApAcB4VWqStceWCU+fpD/vMipT3b37A7nif3/vmH1D5kiWTspkP+PobP8vWc8/y3u/+Jk3rWDEFi/GUb337uzhraRrNvGyoMs2lV18ku7RNmyWUVQWNoLzQVJ5ZOcW1DY1zLBazGLPtWrQPeAeujc937BVZ6WmmNYPhCheuX6PWjlu3PuTyuW3+y1/6G3z9xS/gWs/1wQojwM3nbAyGfGFjm/1H+7x88Trnekvst7e4ee8DTK1YzL7If/Lln+fmjfe5N77Naz/3M2ilyXXBVCtmQdG6wLIxrGpDJg7RIZayhcCN+7f5//7rXyPJU/YOD2PPUejEot3tdDa+ALpSvDOQeGYbj/eR0p9+XvzS+F4buhKzoAihpZkcUD26hT/8hLw5xhQ56WgVX7ccHh7x4OEBk9OSvYVi4kGMJg0t1zcv8uwbP0Nv5yq2N0IRsy4CHqMVShKsxI1bOvcMSlBGYVSL1tK5Zoi6Ec5OKVEoq20UEXpCpz3RiLLd9wlxE8QS+2Wj9TgKX6NjovWREtHacEbIxO8d/77QsSlagbFdDD6ue+7RNaN01Ff4TlgLimygUKtCPamZ1S1lW0GoCBIlMDbLIqjJLHW1IDcGX7fY3OCp0FjQKaLnWKPpF8uo/DHGBQaFYpAvkSymoB3KB/JgkbbGppbBQLOsAsvbGcvPvkBYf57KJJGFdAmmyFiceMgtQWsSCbjFgs20QOHR/ZYiaXGLmmqaIUs9kmHO6dzRtI5WFDpJqVXKbiW02lOkhto7xDh02mJMYNQvWASPb2uqugQFxnTvpY+uqeBdl/9xFupoWMwr5rOG4AOpNVSNpuinLC+N0MGB8ixpRdLMsXpGUjtIPc+fNzy/6/nxiec4CGmW0zjwzjPopYx6KaGaE6YO7SbYrKXINa5u2PKObVugq5T5yQKWHAsLxy5QhUCWRHH0RvA8bQOXkwaZBWg17awzioR4zVjvOF8YLtoMP27JBFasoqATZIdAbhJWU4X1gvYaEcsk+CfHuSBn+13AeI/ubtHYQaQxRsV1qnUEF/BtQ9M6aucZT2YMRytkaYFC0VQlEOjliu1Lf3rY8VMNUEzRvZCLCE5CA+VMqGuFMoJJ4ufkywqVyZmTrJuhqyeFcXKWON3l0ZzNdUQJJJF1ERuFtoqoaVCn4O4KrgkkBYTJET5xJNklksEQZaFtJkzbhCtbPc4LWBQ2T5hPp+wdNAz7irIMXNw27CyX3LpfUi0aruwI/aTBzQMbwA4KmoALmhIhaNhYUpy7AP2hYm+icLeg9IpeEosRmxYuLAWCDhx6Q60MD98/JpSOSikeTIQmBHylWBnlLBYVD2/M+crTgbwQ3gua++PYUmwMrGxBsazQE+HiqiNTwuEY0gS2tw2TXc/yquHzl2ryPI7WTmeattW8uCNc3IRSFFkecE5RlQk/umM4Fc3LL3p6fSG7bfjRhy2fLISD7y147RH84lcCv38zFrhp6RJlJb6PRgVEOXw3G07TnFQatPdI65A6OnXEn81V43tglCHVkOpAZoSeOEzb4oPCJZa2XHDt8iUe3PyQcjomNxpTNRjbkhQ5H3z4IR/fuAFBWN1Y46lLVymdY+YaSqvwEhhe2mH9pRf4aH8Xc3rA0cERqUmYHB3jFzWurBEXcM4RgouaheCxorrOFkMQoZnP6ZuUC5evsnz+PPuHB8zHJ1y/fJlrL13jYD5mejpl/OgIbT2DJGGhHOH0mOtLIy7Zgs3BiMd37rMoZwQd+OjjD/knv/w/8Ve/+uf5xV/8Rd55+CGvv/EVJmVFyPscScApYcla1nQaFzVxYCLD4JqGf/Ir/5j/zz/8u2xsbbJYTGPh2ZljRZ9pNT4VxqrPsAKf1ZycafBEPlOuhyBogkkJAcrTA9rTPerHN1HTxxS6IVkaovJ+jLIfH3K0v8/u4Zxpq6haS2p1ZH8ubPO5n/06q9tP4bXBJlnUJYhHS6enCTHAylhLl47TrfQmhqip6ByiYzsivuqSiFUXC05Amdioq7pSyjghjrP4uHZYdFSLYJSODokQY+eV0MXtExts6Vw9IUI1LdHZge5AkU+e5Pmg4nc13d8jqovKVwlJf8Rwc4tKPEECi2OHThqcOIzTJDqhbEu0XpDqHIOm9Q4rmpQa5yu8O0aXbZSVD/rQVOiBQYqGJon220FrkeDw2jMqEs6t9Ti3uczyC09z4paYiaKdOayZYZdX+OIv/DXe/j3L3o0/JtFdt5Z2aD8nz2sG/YalEQwyxcpY+KQKHM9K9uctrRcyDEtWY4MieMWi9NHdkiQYqzFKUK7BmpwiTZmH7jAjkNhoIw5EJqB7N6OmSEXtV3S1xMqMWhpar3n0eI/jkzEZmlWjyDKDEQ+to5o5skKT58IrFy2HITD3Cpvm1G2gn1gyCSwmE5wdUJ3OSXoemxgqF8i052qquW4S+o2mdEAeRb7zVqjaFq0TEgnsWM/lomUza2kKieOVkBKj5+Lpe4hi03hW85q6B2XTsp4bUge5hmA0iVX0lSPTAZ9aSjTTxkdtjtJRAxXiPWx8rOmMQFye3LhGx3VKgtA2DucDTe04PZ7QHwyxxmKMiSy10QwHBrl47k+9x/9UAxRE4UvgDJxMhWreLW8J6EyRDQU76oDG2Zz7bHzTzXI7gXIUniliOq2omCKbELUnZ7O7INBC/bFicUehco13Gq2hOp1Quz2y80t4NWSx2EUWJ6yt5YTNBMHTllM+vjNjd0/Ts4ELy443Xspoy5ry1LGWBS6sadrTwLYT1m2kMhsXuzWqoBhkcP4CXHgFFhXc/0Ax0p4TH5/uxSVhLVOsrgQOa8WJyxm38MrTip31IUlS849+v6WaCFbBqgmMnWdnOcSZYx4B0UsD4akt0H2D2dDo3KNm0O8pktUcTksSIxwfVIQ0Y5kFYS6YFDCK3XFsUP3kWHPoFccLOFe0jHrCvQPh5rRkdegZ5YryVAhlIEnjolw3DVmjCfPARh8qzt6/7k0jJsUq1RWoSTzFitEEo3EGWuVpfEPr4sxZebBeyAJkGIrg6QUYWs1SmtEzKRfPnWOoPCdHx5RlQ2ozaGsKZbmwtcPLX3ydhz/8PnNpyPKEXi/l0oUdesMB/iPhzuKIi6+/TH71EgfVjNPTBd41BO9JjWE+npKnGVlWkA9ykixHlMYT89CT1LDU7zNIUqrpjPv37mF1Aj3L9PQhv/Dnf47zmxd5+8EnLF/aJkjKb/zGH1KojOLCKldeuszs+JCT6QFXnn+JrSsbkQp/fMjjh7uMx6dUoWX/6IAksfzlv/6f8gX3NVa3tpguKkoRFmhmvsS0FaXOGWRFN5aIVXWz+YTvfudbKO/Z39uNM2sfMHx6nwjAZ4DIf+BGfjLqoLMPe6VplaapKhaPbuJ2PyRxE3qFxfQLfN6jHS+Y7R1wfDxjXCoaldKIJ7XQyzWXn7rG81/8WXo7LyIh0M8sos90JDYKAglgheBjgV8cxwtBC6DROkVULL+kEwhKMJ+OrURHIBJi/kvo5G3WRIAiIc73Y66EiXHiRsWRjI4joDOha3f8RcuZwFgjRqHFRHGm8ogWrBi8jiMpHUIHilRM9CS6fyJTqNFZSn99GTEGEYtrPM18DO6E4GqkCeiQMChWGaxewI6WaMo5/aJPCB6ZPSYvekwnuxw9PqIgZWhryipQFAotMX260rExeLGYo+sdjFlloYfUc8P9R3sUA0vaWyeoKSvXrtFU6wQHrVeIaBoHWQJpBjptMD0wSeDiiiKzDenUMu0vc7cc8slBSbaY8+xglf6ixbY1ysOiqhBlqU3AZpo8MZRe8HVD42qGRU6CZ1FLFNCniuB1tNpKFIaeMWEhgPgYo59ahTGxRFGJkBcZ/cSQaocPFU0L1UKwImgb2BgZLqwX7C8GTEKUdi/1cgo8FgMBqqZiWo85OZwSHCzbjIumYtjOyBtFbzNgdnI+OYzaHqwhMQWqnLOWCJvLno1lUBcMM2O4sSfIOB7CA0IeWjaHCUu9QKuFoU5pVUbYrREcvqPqci0UyuCSjKmCTOI9IiGm7UaZg0eJYMSirEElphOxS8f6xf6raFsWWl/jmpamXGCMiU3z2oKxNJUB/iMBKFJF1w4t1DOhXsT7XCed9qQnpCtRK4I+E+3xJL+As7HvE3CiPg1ss4BRSBIdCFFXGwW08lgo70Wti9aKkMfZsGsD/mgfR0bI1lBVIPMV1DDa6JHmDQ/vevYeBNLGYkJga0NImwX37wVkIrx4DnpTT3skXEBoG6GNFRRUARItDAtN3hOyIaxsK37u5z0bP4aPPorsSWYVSQ5tKwwsrFNhVwqKXsqF9YAtPFdWYe8UXl2FldGcW1NNqoWgDTfvQVM5+kNQXvPBkeKTjxUvPZ1yOfHMqxw3S6kD+DLgJDAatnyyByWaL142WAPVTJGgaJ0n9cLiWPHmRJENFfkArm4FvvKSpt/A4ZHi4f3AUOCZTcVLlxSX1j11IxRpS9WR/mehXWfJok6kAy4K5x1VU9K0Nc7VtL6ibhe0TY2vGhKJOQ45ihRDzxiGNmG112dleYncWkQF1jfWMcryygsvI/WCm++/R5EX5L0e/+Jf/DO+fecmYqN46fjkkH/9b/41L7/yOT65f4+jZobWFRupIKWQ6wTdyxGjyfs91s7H3IU0SUmSBJMW6KTAK0XrGrS0pFVJeXTEbHxML8tJk5xmesrF9R5f/9IrXNh+hqcOn+Xmnfuc3D+gb/vMVeC7b/0xG+OPGeqWn3v5ZfpLBU41uLohSw0vPPcMP3z/bVTvOqt2xGhpGXGBizs7aAKq38OkGQf1nPl8yrDfJ0pUz05mgCg+/Ogj7ty9G11RPqBRT05aCsNZ2omc8SFnNEm8a+lksU/Eo3zmTz77Gz+fUD+6hT68yUhOscMMleeIUrhxzWT/lAd7p5ycCnXwMR8jGIa55ulXX+LpL36dwdo5miBom6JNRhCH6soEpdORaAKopAMlUW9iVOzJERXj61Xwn3HVxNyIWFIc3UXKd6yrNngf23MVuhMHR+Gt0rq7bjVBxUwj3Y23lKiYfk/XKNvJYWJWnXrC/qouqCQQT7hy9t48edniZykd27pFgzE5uYUV0+J8jTwK+MWcmW9IQkXfGAaDNXpLF0mWcnzYo5yUSDPGLsaYc9tM5jXHB0doZemrgnS4wcrl5zidPsY2hqCETClyF5hOZjRs8XjviGZ/zHSaUG8Htq+v8PjwEcPTQ/rDNa498xwnjz7COc9xKFCSsFkoNlf6BDOLXVci9FJhNWsJ9TErTcqJgJGGUai4MhpAWJDlmkWhOKpLQrCELpDNN+C9I7Q1Nk3ItCEbjshdzaSa0Trp8pHOmFaJ2pRuxmG0xjhPosG0PgppE41NFI0LjKcLHiKsmmhlbhOhDTpu5EbhGocKwnqvYFBN6IUFoa6prTArawSD+FhW2TOa4TDQU4HBRYU9b+GgwXtN6z1eGpbzlNw48p6gioBJNNYq1F68N1EKm1py12J0g8mFLNNMg2d8umDhoQyKIC0Oj7Y2LqmtiyDMEsVOxMRatKBDZP1UiF1TqTJdMGHkbM5KBVXHPMZ9MtCGyBC3bYvqPs9I8R+RzbhR0CjKqVDOorXRJIJOIelBvqrQS4KYzwAS6OLNeZIgjQIx3chHEUPazBOO9k8unMdQfSSENs6o/dxjVw0NXddG0DA+RDJBTU5BNUgq1Kc9ZrccsvBcNqDTFjuCXgHTjz35IXyhgFENphS0j2wJOoqBqzZ2fPRSgMBirJjcBVkTVtYVX/krcPm8cHIopDn8+EPF23cUy0vg0sCzOzV/vJvTtJqffVZQree6VWwZYeI06yPLrcctkz1HZmJT734w3LlpefvQkyeKfKQZPmu5f5zx6/9mjClyLmxv8dHNR2wXLT9/QXFpU/HoNMfnhtHaglXTkFnBi5CrlP3UMFeBooGnRZMPNRsXBb2c88kNx+eXHK+/ajj/UoMxMBsLs4nhBKBL7oSz5M5A61pacXgM3jnEtSjXEsqSUC4Iizmqbkhrh22FNHRuE2Po95ZYHvRYWV1msNSj388h0dw9esTXfv7nOX3wiOMHD1ntDZieHnGoHfuHuxzPx7GPJ+3TOJg3nlu7B+xOFwzOX2S0dYFF7YGYdpsMeiTDHj7RSGKwie2yGVpEWbRSeO9xZUV7dMzk4IDF7iMKbeilPZbzhP/m//p/R7cTdvIlRtqyYXt8661bDHoD7GbKx/u3cSsCq5al4YD96pjDDw852jvkyy99ga2rW4Rc89pXX+O4LikfnPI73/w9Nq5s8sL6CygVyLIBVluGFay1mu10wLKJtLIOgg+B4/GYf/EvfpXpbIrSRE0FoK2FEBetGFnf3UtnvPC/RaYIZ6MgztBmNw4CULj5CbN7b+MObtLTE7KlBGVzmqpifnrKeL/hcOE5nDRM6hYRhVYJS8OC6y++xDNf+TkGK5fQ4rHKgUljKqbEk94ZhNKAEh31HF3eiYhHiGJUUdL178QyVlHd13QdXSomWmH02RhIP2krPss50bH1BW10J8bvXjP9WUePejLWeRJpr88OU9IdplTXQaQw+Cfx41HL0t0bHQ0kYro+lS4u3lr6Q43fapFqSpXXJP0Boj2ml0DTsjh6xKh/kcFoHd+rkWmFzg3N7DHNomLQS9BVRWlzpLfC+HSB9QorBtEBbNT0tPUCV9eUvo0uRGdpmxNaXWF9wcG9e2RZxfnnnqKafIV9U/KwzSjbhNmihqRhuQdp/CljHUEoqcuKeWvZDoLTKXoxJWkdyylkvRZWPCMXsIuGPXG41kHtSZQmUxarDA5oXUOmNcv9AVXd4JxDqxSNoa4anHdxdKcEi6Kf50gQLDDMM4rMkmhFaBTjScMnbUleO3ZWBZVqjsiZSo4jjS7BJCUpSzbCnPXCUSeGeampKah9hQs1C9dQJw1rV2BpoFErgTKpKBJFaCKAboIDmxCUogqRVc6MULYNi0bRSoo1liwxjLKcYEp8Ag7h1AWOlKe0FmszWqlBK0qglUAZfNfEbbBaR41e6K4xFbOr/NmW6OP1bI1FtI5daJgYYNdto08cfBLbo40SEI/yfwaFLD/lACW0UE5gMYvUqk3BpIokF7JVjV0JkQHpENtn10jRdAujIOYsSvuJuCEWy3F2Iule8RLa20J9GoGIiCCVUD7UsKxovSLNFQFHOrLUK0MSmZImLRIaikSTZo406xhdAZkIwwZGfbosAUXrFK7rnmg1zBsoG+gboVcokkRRTeHoNpTHwnBH6G0pltZiX09TKual4rAUvNG8cAXeeNZz2rZ8dKDZeKC5MtScE8dDp3gw9zy/DLsLxfZAGGQKEuj14X5r6a33KaeetQuwczWwOmi5t2d4PG6Zt4EiUby8IbxyNQZGLU5Ljg5SXj3f0paBuhamrUESTTVzHB8JF4eKK9cDC5exMAl3H3lmtcUFy5s3Nadl4JUve7Kgebxr4Onu/ZF4YgyuZVGVLIymbBxOWYJWSOtRtUNXLZQ1Yb5A6obMgXWQ8P8n789iLcvu807wt4Y9nPmcO9+YI+dkJplJiqQoyZLKgm1V2UA3yv3U7mr7WbAfPDy47ScbBiz4od8aBqrbht0otKGCbBmusixbUomiZYqTkqRIZjKnyMiIjIh7I+505j2ttf79sPa5EbQbbRP1RPggIzPj3jPsvc9ea33r+77/99ckuWXY7zLZGTIZDhhsDUl6GbpjUQb2D69Tryt+43/8R+yalFdee5GTcsbdkyPOlkucAVUKP/XFLzDa3uc733sH1+vz2Tc+w5PEs1I5jVeoPKEzGZAOejQWJDGY1GC0Zph3qBYL3HyOrErmj58w/eSY1dEJflGQ5xnJ9pgHx/eZvPgyN3YPuHHwaXKlqQK8/c473Lv3UdT/ywP8XpedratcPdzn+cGIUZLzte98k93dfT4pl3ztj77N2ZMzzqsVd44e0W0su8MBTVGhdELoaGpjWDeOgRgOxgd0xKK9xyDgA0Zr3n3/Xf71b/0mQsxa2FRBBGmZBgWbSpfLJoFyyZnwFO4/zQBhw87QspwC9cVD6nBBnlak4w4BTTWvKM5mnJ+e8+Tcc1YF1q6JDeo0jIYpr332Ta6/8bNkkxsoawmuijE4IgTtUSoCKS++zYLQ0YfQJtZuiJ7Ngi8hIFrQyoJ2MQ9FRRFls+mJc/EGXIHCxPllk1CtTLyGbMBL7CGklb4sRxYRfNhI+4GWwInXJARQsXHg5me2zaSIJFTbnE9oQdZTM7iogIhD2QSV5/S2t1FNxXSqyTp9rKupyzl1xzEeXaGb96ltn6aYkfoBDWtUtaLjV4y3BywWUJYKZQPNxSPssiQ0GSQ1zjQkmaVoKhoPNUOcbyCJ/ph6YVG2z713vsne4W0OP/+L/Ox//xf4gz/6t7xdf5eTCi5qhWsMz01Shp0GdFTcc2sYpYKxQsekTBeQ+BpL7A7f63lsKtiOoNOacHHBuhE69LCmQwixA3NVVoQQWd+gAokiSq5pDmIo1BovNTpJadYFvTRn0O/SlBWpCYx7hkFqyJ2nms1guqDxJQ9KqIMl5HBk4FxleJXiq4LDQYdRVbDfKzkYeIo85+17c1bdCUsfg9+WonnkA9IRGIMzwmJV0+lGKToPGbXy+FXDuSlYVoGR09ResagD86Cp2zXNaiFPwCnPygtOC4+d4jxkhExhjaJ2jhrFRR3I0OAU2idkImAMrvU1heAixBViWwDvsN5jjG2NspClBq8lJvK62CRSJG5AvI+SbWotOgQSbf7jvcr/38dPNEApFrBMIsmZZpB2InOSTlTMO0kjOGkVAKCdDtsvUom0PG10yolSYNra+E3FAVEPVhX4u4H6iYrVCh6kgaKE2XHAjgXd19Dvof0C2xzRyy2driM1niakVJXQXGg6k7hDck07wehIE/sGqjpQOWLDLQtrgXUDCYpeBnkqpIlGnFCuI4DyEhs/dUYwuAr1XJF+S8gFRgl86pZw8yX43HHD448U794VpIatrubsAiZWkAc1W7ni+euBjlWkCeiu5pU/cUjvMOe731xSPTnj/Amc3iuZnzXMZoru+QNeShUjBat1NFd2beD2jo2tAURamhpcrnhuTzGuFFLF4t+zY8XJUQ2lcG2i2R7WnK4C732UEI49jYdPkmgWbjtCxG9RKXwjrOuGWsArR9k41lVNqBxJE8iDQqLlHIsnT1OGeY/9nW22doZMtgakqSUfdEn6CUJDpz9gWTWsFfzJP/tnee/LX42JsxiwlirUNOIZ5l1u3bjJysG8LDF5xu2bV1g2a86LKWoypHOww3B7G9GxL4VWQuoDHecZOfjkvbs8evdDiuNT5k9OCJUjTXI6/QndbMTuznWu33qBncmI3//213jlxdtc395jf3LIp195gf1ej48fHnPazznLFZP9Cc/tH6DPp/RGu3zp8/8Nk16fo8cPWXcznv/pLzI5ndF8922eG+3xuWSHow8+5uUvvsFaJzxanSMBDgZjJkmCCdAocN6jFSxXS377d3+b+WKKV9IyIBvJRn4knG0DQBTS3uNtIqp6FpRsml21wISnVUDGrenaiqzfAZVSz0tWpzNOp3OOFgUXa8XaR8ElRzGcTHjp81/k5hs/Sz7eJ02y1mPSpS5qAg6Mxqo0dkje1Cpset8AsEmq3UyhKjISm5JekZjhxgYwRLo1hr3GqhwlxColFeUtrduNTmuoVbqlztFt7Ho8b9VWFEV5pvW7qNawa3TLzrYHK4JSSXutNkXdCsRHr8qGyVISw8UsWO3wNgHVZ6ivE5IEd3aOX1zQMYrR1efpXn8FH9pwNaNpbEIwGTZN0aFDVxa43hi3XpOtS9RqTpKUOK/QPn6WKj3YlNqOcSrD+DXr4KGoWJx9iM8HoBKqZsbR2RFXn/8sQRsufOAkQKlzyoWwUsLzWKwUYGOCrrJCVsFIC6aXgKuobQALzjRghCyBLUr80NGsDb5WLAKgM4wySF1RljUe3VZfCTbxDPs9yqJG8HSHPdKsy9Q5xltD0jRFpwlZKOi4grwoGdWevUSzMxxRlIqzZs39E2E56DIbDLlIcwof6GjDzWHO86Hhal6wNajRfc1sKnz7fM66Dug0p5aGu4XmyVRjuhWSKIpIwtLpKbbmHlXUdDEkWWyg2l/H4L7TWnHWJDRWY2iwISYeOwxTr1gExUe14cgZTDdD1THKQBSUVcm41vRQdIMw1Za5MayNwliFU4bSGSTEAoXY38jHvKmWLSTEMnejVGzpILG5o4SAtRFi5DbBIPS66Y/hTfsJByjrQhimirQDWS96MpKBID2QpJ0LuUw2ALg0UhIk7qB0C1SUQmmF6HZ3hDxNz2iEcOSpH4BrBKkVrhIqB+sKCIH6rCbVBrXl0GgSVZDtpnQHAa0DxdTh0oTOxGEzRV2CqYVmHhdwYwTfKGoXw3kkVxRBWK4VeOhYsEawRqFVYJOCEHSgrEBOFYNDTe9aIC+FK1cUFw+FN18IvPg5RWcivPKmcHYCtzuBei14A/cLxaEWQgZhYNmaCKoO2I6mdzvj+TcMaXpGeFTyO2/VnAsok9EVx5tbUR8vamF2Hui+BGlfkyUgvuH4gSVRUV8vGsXWWDFbJxibcE7NVz/xHMxrPn0jICmkw1gV9N5MMAvH+mFgIWBfVOzE022XjhjZfTEvWVhDA5R1jQuOunJQOkzpyZzEICxt6fZz+t0+k9GEG1cOmez26fQTkjRBWYOjYdAboSp4/PiUfDjizS/+NDuS8tHb3+ONlz6FvOc4Oj6KmNbA737ld/A257xckugOd2ePCdt9hts7sN1Huh10N8etVyRVg59NmT464sGjI5aPTpg+eoKsaxKnSZUm6/bpb+/ilKbf6fOX/sL/wIOTR1zdmvC5V1/mwek9fu/rX+HTn/48Dx8+ZiyW3Gqubh3i3YqdfEC5XHF890MGky7jXo8t2yNsXWH9qmExX9P4lOu7t+mWnot7n/DDb3ydN37uc5jnD8FVHB4e0lUmNgJTGqUNztU8np7zP/6T/ye//hu/TpJYgnftQht3SqGNl9UbwBHdJ5f9PPiP1v1L2UdoNwRttQtcggQXNEll8K6kmC5ZlxWL2nNRw1IMOk3oKGFn1OfmZ77Itdd+inRwgE5GkfWQaBo0xqClimyFjj6zpC3xhU1PnLb5H62hNWyoEWkNqG13Yi0x7VWB6JjmufHYaKViJQiRBQmyASMxHl8p3f5RlxIPcKnJxxgUQYd4bdQlgIn5x08BVGRI4rVtr6FuvSpBwGyAXutRaZN8g46LDv2EnvcUyyV6WaN0iatOWc0ek5gO2ipMgNwMsdsdOte3WU4L5h99g9C1QENqNSrpEUwCumxBpqXB4bzj4uyEw1ffpHYF8+P7mODoGEUwHRbiWJ+t6WYZiVaoEPBKyHopSZpwMfe8v65Z+8Bup0OiLShHajXWeYwYAo4yEc6oGfc6dJPWiSNRUuukNVuuZiV1zKlJLc45+v2EzAinReyBo1ScV8N6iVuVpFrRt12ausK4WGLuXU2uoG8gcwWqqulUgSukXMWjO4HyWp+vT9cc6y6rfIyXjOBLxr0B4zxlB9gZCOOBkHTXvLgXeO9sDWWOThIqBQ8k4a0nJV/sa5KuMBfFwmlsKhz4iitYBmmPjrWUoeCkrvEhcNRoPikDJAl9ZehUJbYQmiCsdcqRC3y4Fo5cwGcBbSHRCRbPWMFtDb3GsQyKjklItCbVARMqGqVAp6zbSrIgvi3HdqzXAecMaZpe/vGtcVa84JomVgBp6BlFpmHU/3Fi2n7CAYoYSPtCdxx705guSEbsbEvrjt+YTmgZ1410s5kAlHpK0V5OouqS7lVO4InQ3NO4ut3Ba/CiKYpYR29tnNRSC2pVQBZAezoTTz6J0d9NWdPdNaQHCl8L6kwozyHrKCQyZ1R1rNSUtGVOKoWvhF4CeQqdvJ3rRWGSGEC3ac9ucyHfEkjjgPvM5zRbAi+8KQyvK5QVdvY8P/tFxfIjqFzssPp/flGxKoSPL+BoLaQadAaLCt75csHsyce8+YuG6pOUxCn+xX+oOdgWepnh1a2Gbi68/xCypcKdgioUrgO9XLGcWXoHmrBlefuO5u27satl06zxXjg1mvtnAaPgZ1/yZFrzznHOqy9o5ndqPjj3VCieH8XvRdrvSDA0TrGqhLVoFsWa+XIKIhgnJIVDlzV58PRsTtbp0u102NrdYTSZsHewTX+S4FWDSRLQmkQbRuNtbKF4eOeE9z76iE7RMDs5RjoZD06e8N5HH7WmQ4PJE87KOSoX+td2qXeGPChndEnoDnoxkwWDnhesHzyifPSQ2Ud3mH18j7BYolwg8QGCwdictNvjyq3nGYzHbG1NeOmVl5gtTslTzc9//osME8P21pDKB/7hv/o1Oltb/OJzn+a//fmf4bT2XE80nX7Korpg+PJV0m7gtD7n4yfH1Crjw3uPefLxA7bSAb1Oj/r8EXUz5Z13v8X/5//1/+Av/d/+Oi+/eBj7ndQeFzQkKUppah/4X37n3/GPfu1/wq+W6DYpVdqd00Z0Vm0/mTYLvh2kG5jfopFn5Bw2gIR2kX7WPJdavOmzrrssp8esZjPmZWDhNE2woBV9Y9je3eaFN77IwYtvkg67dPIM0S76RFRsaZF1DJDFcag8ogNW2jC1jWyiXCvn8tRDAgQfj9lszNit12QDqsDEMdkyJYG2s6/yCLrN1VCtyV5tEsZbNkk9PWdj43UI0aCplHlmTlKXm63I+MQofoWKhT+b5ygFKrIoIuB9lJ20ikyiCR6TaBqtMJ0e/f0DEjtDna1geUQ62aGbXaGRgKgG3U3o5leomimiNFMndDNNavvkwwMkXVAXnizV1C2r3AjUznFydJe9m9fZunabxXyOrQuCK+n0++RPuqRBCKua0SAhSQ3DVFM5h9EGZwWX9XngEs4LRxYUmUkY5DnWVygR5uKolaHwK8Ky4ro2TExDJpGx007IqOnrEqcVVbOiLyYaZXuGfrfL6XxJ4wNGZTTrCuUaOnmOqj3lqsKiUI1Di0IrRy+p6NiK2hWYpiKrNWldM+47zK7hUa/DuxcZtTJIgNFoQC/tYPsZ3Tyllyo6qTDZSlitV1yfBN47K5h7IUkTChQ/LAw7p3Aw8Vwg3J85qhJeTC2vOsN4MGJmTjlrhAdLMAPD3ZXmcWh9dUnGTr3moHH0K0VVelaJ4cx71kZBWbbpucIQxcv9LrfNArOqWEkflWQE5RkYT2KFMhi00jjxuEZQyrDpphUkUFUxRNNaS9KGs1kUQVWopIsgZInQI9C1gUFf/9cj8XRHMDpQ2L5CpcSkV9PKOu2A3nRHFR0dPtJKOxtwshncmwF+qS1vDHxzj/tEaKrW8a80TgllGXCNIsmEJiishoSAwqK8YFKNSRwmV1BBOvSYvCHrCM1aCCVQ0VYgwXolOAchjS7rogTlYdiBVEMnbdOGBZyDzlCRduOxdydw8BlFviexGqkDN78gXLklmI6gjSesAS3s3gZbw1SgKcCXARLhyrZiMHAkrUE2tUK55fnhDy3vfBz4wZM1ZyvHR3Ph/qJmkhlyDy9tQblQFMvAt9/VpAPY7oGuhMoEkm0Lo4xXsj7f+/gxi6IBbbBpjgslL008r2wpghNsKZiZp7+Xk101vHscmExyMrOR2zYLncKFwNl8wYXWFFVFVZSEsiRphJ4Tcu8ZdjMmoxGjrRHj7RH5oEs26JD2U1Ta9lRRGm0zgg8U64CfBRwZR4t5lLTuf8zt7S3OmjWF9Rid0E1ztnd2KQIczebsH7zA6IWblL0c6aeUTYVZBdx6ydnRlIuPP6Z6+BB3/IhkuSZF4Y2mTiwhz+jv7/G5X/x5krzPgzuf8Lmf/hK/9Kf/BN/43jeYT+f88OGHNGczXnnhJRJSPvX8S1x94QWyyvK4Kjm+OEOlivNCSPqKvf1xbBJnDY+LdWz/vm4YJR1+5nOfoT8a8uCdH/DBv36Xeer5d7//e1x5/TX+zP/l/0h30KWbdGMmiI6lI+ezU77zzndwyuMltl5QWsXFu1VDN9jk0nSyMX2qzc+eGbhP42J/dLJS4XLcqmyAN8LsYsbZtGR+EaiDUKNITEKvr7l69RY3X/8i27deJe0OSbKkjX3fxMGHyw1HzJuKSaPo1j8mIDoem27Lj+Nxtz1/2vRMaSOnFcRQuVaKEQBNlP+IAFqbWIqq2Wx+NnxsnF82KbFe/GWukgkSDbE6NgeUENkaCbF3M2LjESmeZqSgLgPf4jQWjz1sgEqIzGV4ZpMWlMYrjwbyvEPdG0G4ga7XpNUT5PxjbGrpjrZxohESoCIxBTu7Ez56N6UuIdiMorjAUhGCRlmLNEJQNV4UuRFMvWb55Ij+lRcZH97AnTygqmp6nYR8soeuZjz84DvoYULd1EzSKKEmZUCCpgwV87KiMBZtLJYEvajomNhAs/EOnUJ/NODDIjCrK14c5+zkDnxNCIpUHKlbosoaFWoGeY9eAtvWMA+KocmZFQ01hmnRoNCkJnqU6qKKEptzaJ2gXIORijxt0Lqm9muSTp9uHsjzhuEoI68cRoNIjIUfDPpYm3JWVhzVsQFqz9TMzxoSCVwdaW7sZZzPHFZ3COK46xWjqWZuAy5LOFp4mkJxBeGaqQlPHsKkYj4QPlobnDXcKxQrMoIX1HrOCyrwmrJ0g3BeK3JtEa9wKkF0bHLYl4YDI1xLUg4GCjMSzteOhXNMJJBkiq7SrLWK3suQEqymcYHGPbVO6DbdtGkalNKkOkFrjbWQpBbT9hMaKc8gLegPAj8OQvmJBij9A0i3QEyM4Ma0zMdmZtyAE9X+TqlL8HGZ1bAZwGojHkRdEkCtAv5eoF7Ez4svDxRLRVMp0lQwVmGzCB58E0X7rG/JsgaTRpSJFmwOxrYbJxdxhG7Bhpe4CfWJolCCrwXtFd1E6KbxSLMsmmZjN9LotUl6iq2bMHlBSLeANLJGUoGSQLofmxxSRfOwSJSmbF+R9iRKQ4mQCGQ5XLkGOHBeIMDtA9jbcVQiTOfCTFkmPjAUT896jh3YM7AVnPp4w372EKxRPHkcmwzuOKhFo4sZ17cNRzPPIDO8eTOw7RS9c0VeCHOXcveTqG0++n4FowzloTxZcz8Z8Qpw6aBEqJuSs4tTzpXGNx7rA7psUHXcgWaJoZ8njCcDrt6+znhvgqSBRhyiPDihr1J0k1AVgdPzC6Z6jS81D08WnEzX1BdLep0Bo8GIb3z/ayxdTV+nTLIxz129xcPFlN71qzz3M19kNerxcDWPXUCriuqTJ8wfPOH0/mOq0zPUakXuG1RQ1AJ2OEQNO+zdvMX2jWvI7pAHJzOS/UM+PL3guZMTPv+5L/KNt77JN//ou/zUC69RLGp+6rnXee3WS9QC73z0CV///jtsb2+zPRxx5i6oTxfs7O4zyjsYr/jU/jXAcmoTDj/9GnuTCU+qJXp3QNjfYe+lT/FCd5vTx2uWxxVbO/sxn0NgtZzzzntv8+U/+B3+13/zL1mvV2QSC2tjFazEWGy4XIY3/xe/rlgBcAlI2v9ufq82PhW98WhsYAAE02O1WHD28AkX64bCa4KLu7+tfpedgxvc+uzPsXXzFbSOXXxNkkYgILDpWg0Sy3HlKbzdfIZSmqBibD2tYTUCmSihXGIutQl5lDbLJPZ8FRGUaQGKRKP+JitGIehYIoSIIgQNEqt2aI8hZq6oWPmgNlPRJsZet/+0pa+hbfWj4nFLK5FtJDW1kds211jTNi0UQpsGuuGVrdJxJyyCsRqRE7KLKYaCfrKiN7pOWccSfu89Sapp9vuQ5ASnGI3HzB6fgI/hYY4akQznDUqtEBFc5Tg9PSE/PqI32CUZbrEqS9Kuprs7Zvmowq2WvP/W77PSlq1QM7DCJB9QnjiKpmIaVpyJZ6pz1vkYpTWrOpBqG2UDbZBOzklVcFYFzo4rXhobJlmKFqEUiw8GJ5qVV4SmZJLnDJKGQdMwtoZlZjirIDcpVS0o5WlcQT/XWKNQUmFULC0vGo8WjzYan3eYa02+m9Pt1qTjGneiCcagsdg0pakb8k6Hig6fzAvymQIHAwIuxPJnbTMmRmOnU4xTJDZwJFClhnSYMQ0NqVZs9TyTLaE+DQy3E/Rhyh9+b8WZEk5dShmEpAls0/D5/YTDokYqKMtAr9eDRVxkOkbou4prBF4yhh2TkA8ciRXma4U789hQszNO6fqaVZ5Q5JZVlVA5jXMO55PWixJ7/mx6GklwEHzLsDR459HEfkRp6smTBr1pk/xf+PiJBih0ISRx94Fp9ePNZq0twUNtfhfnR63V0x48elPaKD/ytgqFqjzhvuAuFJinNHS5VFQrwWgVd10GOr12ap6r2EWzm5CPFIlttfhMxQk4KMIaQq0IlWCUoqpj6mujobSCK2Po3KQXJR1LnATTXBGaKAP1xpCPYP91YfQCMcI/bXuDbELmhPimCCoh6tJTTbOIybtKaTp7IEvwDfRGsPuyMLsHywuFdxE07e0KZ0eKz/dBcs1J4jE1DLuQJ2CatnrJGp47hFEvArIbV4VHjxSP39ZMXnbUj0ve2HL8X/+0ZjdxJNrxve8b3vlBgKBRykfds28YbWXQ1LixYTYVdGIuv5f4ELxrqMt1pNyrBnGB1MPQJAx7OYNhh97WgM6VLez+ELXVRWiQ0mFrx0AbdvIuyuecOc/jcsHjxZzZbM2Hdz5mtWywJVzbOqBezpnPZ4hWuKrmc59/jZ/5uV/k//4//SP2b99ksL3NfL3ELwumJyf4h0+oHx4zPXlCU5UkTvCNY51YkvGQ7mjM+OoVhjeukk4mrNYF731wj1dfeB3tc7L+hHufnLDdGzKyY7YPd7HS57vfe5f08yl5kjAeT5genVLWDVvPvch4OKZaB9761vfYndd8+rVX0SqQ5wZf1+QDy2iY0rgC7yoK77jxyqv8iefe4PreLT545w7r4znmZQhZIPiaDz/4Ib/6q3+X9+/8EF+syDeL/4ZN2OCOzTiDZ37wdBxuBp9Sz8KDza/kR16oWhNtsVyzenzBclnGnlvaY5OETpaxe/Umey+9wfjwFknaQcRhkmjY837DVzwjJ4UQafrWX3YZg9SWkkb5JbSMziY0bmM0Va2/JD4/NlqzT6+Dlja+3lwCmkvWqGVk4hTUsoDioxemBUCbzVRQsdIoTk4xfC1eD9B609E4XjuDwunwzIiIjEs8zqcgMDZmjGmgQixuNip6PkQrrOrEth7hBlrN6AwTQm8YmR2doVJDV1mCyqBnWYaEgVcM+iPKszN0VUSWRlkaYjlrog2+jhWWq+mCenqMDppKB7p5D79a00zn+LqhaCo4Okd29hg3K0xd8srBcyyrgCsb1DhnnjS8N294ZzpjKpZaWyTL6GmLV5rzqWO68IjXTElZTuF6EtjKLWIs86BZiOZcBViX5OfCy1sJE1vRVYqeyUlVTmY1MxMoiprEW3KjMNoR6oZ5taYUYY5nUTqSzIGHb08X3Jhk7IwSXNplUZeITjGJZXtnG2PTVgVUfPDolPm5J9Upu1KhOkLZKKoqsCPwijYM+n0KF3hQLXk8cwQ8S52ylwV6iWNyGOgfGuodQAdsAtPGMnfgg2doNbd7lqs7wrYHUQnFhcEpi1l5esowcCXPp57XrWWwUFzcW2EcbN3oc0rgo+WK7WFKYld0ciHRKWuXcTrX9CuFOAMuekxKCZShZVK0QXQMLFUmkCSKVMfgxbqJvca0D2gJ7P9Xk4NC9KFsAMimG9flRlvBpejbasGXuztzaTi51Jul9a2oRpBHgjsTggKjBe+hLmJarTaxH4EgJHmku11BLHFLhGzkUF0D1rfmtYCVNiLYgV/E43NeqGtoaqHUUbpPEfpDRb8P1kJoFDYR0kxRB2E4gdFtxeHnoXtNorQF0UfXhs3hN0UTbbdVFLJUuBLcEsoLyA5h/3mhOod6HV9mU+gOwdcKVwtiY3+Q5iga3K4pTyOw24fRQNoumJpHVri1C9f2AyYVTBCS3GOvKJ4sCvRRzatbkHUDE+vIB0LWV4RvCpUX1stAvy9cHcNgvMamBVUpjK8oTvuWaqzbvhDxXDaUfKoUaQikWtHrZgyTlO3ugNG4z2BnQDruM7yyjeonhETwlcOvKvI6MOylbJmUtVcQDEWtuPvgCecnF6yLkkG3C2cXzB4/5OzoQxQ1GYGhsYyV5s5b32bQ6aJzyzvvvc1sXfLw+CGLR0eY4zPscoWRhkQJVhJqm2C2dzC7u3QnW6TbW9RJysXZBdWi5Llr17m2c435ssF2e3z08IjZ7IxbV64x6A5xznPj9iE2N3z46CGjuuHlF19mXVc8PD3m49Vj0oHmhZdeYHd7h5N6yaIq6IlFeTB5EntoaE2PjO3xhGEyZPTxlO/83tf44Q/u8JkvfpbXfu4zNLqiWhf83u/9O959723KYolSsY/MxqgZYz42vod2MWzNrSJPPRy6lVNU+5xnAYluK1025lDV7vgB1ufnVCfHOGp6JkWllkG3S2+8zeS5VxndeAmb9+O9nthL5iNig8jvBAmIxKo7iGW8HmmzRGj/FaI5PmzYnzjhhvY9lIlEdqzOeQpSorQVS4SjXyQmwkgrbUnbsVlf0jaRLdLattVPgQ1RAioOXdlE3OkYYS8xGEtaiSpe3tiPJWzAEhu5Z8MAczmXQWiPKxYKXIbOPVOl6MnJ+/skzAh5yVnhKaUhH4xomgrVTehlu3SblGvPvcDj9z5AdEqnO8CvF2gMXplY9mxi+4DovwmE9ZJ6ccJwbwcF9DoK7dcYv8L4NYmbE4ynUYr9iUbmNacP3qMfEnp5yXDUkGzBXqXoPmx4UFh8b4zPeyznc6rC4bynm+as65pVIzwohFWpGVeavJuyRjOrAwuJLTaqxwW+bHhjLyXPa0xSxHCPOiEXoWwCOZDZhCTV+FDysKo4LYUzp1g3kDqwVvHIwejeijRR9HTNrFGoLGG8PaQ/6iNeU1drlIKz1YKLwhJOG171lu4ocOoVdem44S2fzgy39ieUXvPts5o/KD1nBqqusECYJqAnik5fCP0GZg02gbpIcKIwytFNYZh6dOJgoKi0sHCKj44W6KzLUAk38HxhBLeDp1oGVmKoCsMHT2q+flFxQkqewCp4cmsoxXHhS1YqIUXohYqJSVE65VwMMwlUCGJiPgviyVQgS6EJDXUTcHVJIzXTdcB2FC//ly3twE86QHmGHYkrWDs8N9Womqfx6K2DfyOaP1siudnlKaVRPiBnAf8k9hdQOi74vlGs5oASkg6IE5RVmFyQKso3JomSU+9WIGQGXcZj2eySvBdcEd8j+NYDEiDkYAQ6osgm0B+DNGBTFcu5UDFtv6voXxX2fwY6V4EsTqzKxfcnAGX8vEAMklNGERaCX8b3rM7BTGDyMqRjSHvttbIgjSLtxvOuS4XONWfvBJjDOggVDaWOlPR2rjl+ong8A9W1dPqe8TWQUsE6+me8F3od6HQ9mY1ZFaEU0quK7ramm0LHampRpFmg2wlkabw2yoPVwt4kUOw0PGETbxW/K6M1/U5OmiRYpRj1O0y6PcbdHqPxkPHOGJ8osk5OniZQ1qhlAStH5iziHYVb8/Bkxfvna3744IiHT47RPtDNFLI8p6MKXHPByfwoas7GsDseMd4e88G9B0y2tzg9O+Ph3btcnJ2znJ5jqpK0rjGqQRlBgiYYhc17ZKMJrtvHDXqUmSWUJePekOFknxtXrtIb9tEDzXQxI7GK8fYWNrXUfsn+9ojtSYdKKqZS88ff+SP+5Be+RLk44/HFEaPxHlu72/T1gEoLR+sLqrqmOllSzNZs7+zSTxYMTIZNM8TX7OzvsJ2PkEKzOqs5fXDO6cMTssOEX/v1/5l//hv/nKap48LfDpVNZUlUM55ZFDegZbMAbsr7ZeOP2Lg2Nt/hUz5ss8w+HdTQ1AWEknEvpZt36AxGDA+voIdX6R88j8n6YGJcvblMAfWxjJdYNeNlw0TQ0tGxe/RT70tkKzYNeS79Z+0kok084rAxm8gzma3tIevLwJJNsFs8n2i0jZyKakPrnu3To+Rp+XFQID60DIhuK4E2kvQmf5+nvcRakU3auWzzC7UBgC1FFNke3crW8boQniboKtGIBIqgQLrYUmiWBbPuHNffoamERmryQUa2c8irX/wSZvqYbpqg9l9mqRR6/oS0KQm49n5Pon/F16Q+sDi74PqbE0aJ0E3W1LpA1IxOF5Ikp/KWUoFWDTZbx/TYakWarsizQJIq9rvw07ll50nJ+6fHfHyRkvQnuCSN4Lto6JaePDgqqVklhlIp3CqwchJ772jwScKTqqaaNgQvvLib0skc1lTkOlD4ik4IjIOnt17S6wpZr2Fg1rzrhNNSc1olhKoh7WiMzvjqBSQfwQuScOxSBvsH2MEQ7x2z0zm51Xhfsm0bHoWK9xaOWoSJQJmnODyHOnCtJ8jJxyg0b97q8e7Dmse1xQfFtBTumsC8MSTBUTooRGO6FqkC2msSpRhr6FtYeyEjcOENd2vF/VLhUmHbVNzswuFAGHiPniiKVeBx0Hw4V9x1KXViyZsAlWXmA0VoOAkNq7Km1zhu5rDjG/yipiMpqfIsM1j7JZWL99tAQboKzIKmbKAONcEGQuNR/r+cPWmXpZ/gh9loX09pZH3Js8YY3kspR8dGWhtZB7jcRVzOOt7DhSBHMSdEaVAhuuHXc0EahY09mdAdsFl0rpMIaS/Sq71bCjUCmzSQCBRx4Q9NlFYIcc6p5lCtFSETvFbkAoN9GO5A8ODKCIIQCCX4Gvo34eDnFck2kNLusJ6egBQK1bSnn6hoJJiCn4M4RfkYnIXRpxXpRBAH5FECEgPGC7qrGNaKeh3lok8eCUbD9h4MdjSrD2CgIKwUmQgHPaFaC0fnmhfmikEe0HnsvOwN9LrC6FBh2knT9iDpCIuHga7S9HOFRTHsKDodhbXQIGSZYr5WdLsSw4vgaYsCwBrN9mhMMhqR5yndbkqWGvq9DoNen95gSJIatCWGjXlB6ZRSGromli4+frzkw3unfHi+4PH0lLKcIeWcolySLhc8t7XLw8cl5/WKkGRkSYeDWy/y9Y/vMnOOeR14fDRjOpshTU3XNxhc24Qu9kbxNoWsQzoaIv0evYM9Bs9dw1voJwnXhjuEVc3Otf3WFHqGVcLuqMdL16/RTRP6iWVv3OdkccZXvvktTuc1Sdrn+/fusJidUVBwe/I8ygfQhoJAqRVLH+h2ehymk9jPRafoToeqrtmdjOl1U1SoGOx0Ge+MoNPh0b37FCdrfuNf/UuOz07ajsOaTbiYbPbjG6/DBuRf5ps883hGwtmAmKdy6ib7pH3K5Vcb/62t0B0Ztvcm9EeHdCfbmOEeIR2js2E7tmP8vDgdZRYtsRQSNnEhUbqRp8eiW5kptIu5SIjtK2TDn7avu/TOyI9sYOIhtlKKqEtwsgFkuo0BN23ZcowVbG23rR9lw4hEH74CHTChrbzZGF3105PQotCio7bfMlW6bTsYQUqsRDJa2vOVTSta9Ka8uK3sESVIm1CrrIkgrtMhNAPq6Tz2NcsCPlSX1UCuAZ0ZeuMeN166SjWrOXjpC5w97rF857vIxSMaGjzglVADddD4xlBPK44fPuD28wcMtnMWrmY46FMqx2ztWVSKkEVwG7RHbEWnk9LrGEwnenOyIGxpjxoZdBDK44L7T0pK3SVRhonX7JicgUmQNOHYrTl1NZVAGQxOQa5itZkLnlMPb50UzCrPrUnCIPeIMajKo5rA0DeMmopJUIzSmutbMEg87rGj9PAkOnlAKR7alN8+K/mgaUiuH9K4QDJfkmRdVOOolgW5anh50kHPPQ+qhO+uhIFzbA0j6B1q4XAXnF7jrTC81eVmrXj3SFg5wWrL0Vpx79SjreAtnFfQWIHUoyrFqArsasE6zbKySE/xwwV8e1aytDmaQC+FiQ30U0+eKZJ+jvcd7q80D85WrLVBJXDqhNW0IQ0Bj8FlFU0jHOSardwzqQ2rqmIn36XT7XDiT/CpsAjgnONKbsmUgqVn6WNPNJVYdJpRux9tb/Gfe/xkA5QNONlMIIEodShi1c5mp7YBJlFIbqnWCG5Cq88qAbUUeCT4IvbOMMR8h3IlNBXoNO6ExEeDqpLYtTcdKLRRpBNID2IfIDwoK0hXIafgi6jLBge+UgQHwQougUQJg6HiyquKpCc0qzhxSSO4hWJ9AtkNYfyGwu4BVmL1gWs9AQGoaYsnBBLQqUJWmnoagUj5RLFeBAafUnT22h2WEO+ANO7uJMT/71wVMq84/q6m/5zQnwhbr8LpHN5+V9CVxgXNTu4YTBQ+U1ysA6GO1VTWgqsV+SDQ34aDV6I5tz6N166ZK8ozTTdps1EKRbcn2DTq7fk4hku5VLAG6uTZlYz22DX9NGc4HNMf9kl7loYa0+8QkoTGKpLE4kONbSd7X9ckxtDr9CnXFffOV7x/dMads3MuylN8fYJeneDOTlmfLflm9QOW6yXBpngXuPnCp6Az4bRY8HC9YHExwy3WJGWF1bTplAqvDF5pXJKgByPs1hZ2Z5fh1atsvXCb7tX9OGCLinK25tUXnuPB0TE6z9ieTOhrwxdffoXjjz+gTC0rqzHhCnfu30e85XBvm7IoUcqTZJZeSHDnS5qsy/j6VebVnL7p0yhPR8NLu9dZTpeMtrdBAkVYsZcP0FLz/sMPuPjwPq9+6kVK7zCdhO+/+23u3L0TZQ4nIAbfyiA6hFjdIHIJNqRdxGUjwW3K+vmPeRGeSrBxZD7DqTwFBwhknQ5bk+fYvn6DtLePySc0ymCTHKUjc6IrFxkJHQi6NcOGS9GDaFAN8bg3x6VieT1A8DFfRJ4BGdLOD6E9p/ibTZ6IbY+5DaVDkGDQmz5e6mmWkmplIdVeE2mTmERvWJWnUQbSRsV7BB/kUroJSl/COyWx51EALjvNKgD9tMfPJgulldRiB28Fyjz1zJi2TLoFMlkr1bm8oOAYkwSsMoQaXC0oq2kkAqjOoEdvb5difQfb0zz/pZ/moTgev7XENpA0JbU0lDqhNhCkpudrnty/jwHWqx7dg20WRcPxo1NWi4BTmnQoVE1rusRjtMNmBmNC7Ewe4ryR47jWC/g9QzdRfLwoqEthPxlxS1tGTcOga1h0DQ9qz1HheRJSLhoo1w7RmsQkFBI4DYFi0fC4ajjoWIaZJ9Gajtb0k8Aor+klNZMe6LEgFtYe3HGNq2HpExptaLqKe2vLbKW57XPGNsEGYXpySlU16KYgDzXPXVHs5SN+6+0Zd7xmUWYstNC3mrl12F0YDi1OO2x/zbVxYHIO3mu6SlO7hI+nDWkPHIGPF5rHRcAry7YIL5SelxpDT8Giozmear5zFvhgZSkksGUqRuIZOI+VhCbRTA28e7Hih6ViniRUjZCgWNSCLxw9b7BG46oSn1gaA7Xx1BrWrKlUQd7N2a0daepZi8aK5koeSPMOu8Mu4egJp3VJVVlKAlmv/2Mt8T/RAOUyWRFiI6PN+qVhM+WJ1k/t7894Ti7Lj2lZ0nWIvpO1xAw3HctQq1IoC2IaYxYlGW1BJyCVwnajtKOskO7HBFuRtl8HtKXEEjedPjIuroxTnnRjcFJmYfe2kA0ElShUKtAIpqtoThQ6Vww/rdB7sV2xCLE5GSA1MYzM00Z2q2iaddCcCqFR1CfC+izQexl6t2JFAr49dxMzUnAxM0IFkJ6grbD3M5q9z4BSgu3DJ3+gyLyiGwJbRphcg85uIM0C1xxQKrIYKxITZUeK3jbke4GkB81F/KMzTbPUJBa+9MtwfGTorT1JAh5FPohA8OCqJqyE5TJ+r+HpV4gWyLH0dEZHJVhtacRRisMmnZh9EDziGoxWDGxCZ5ihMwUu5WQ542w6pyhW9GzA+RWhmOMvzlk/eULqFHmnw7wQLAm72YC/8N//D/zL3/zXfHL8mJPiArdakTeBRAleQy3x5qiDxmUZyfYWo1s3yA92yXe3mBzu09veAmMYpV1kGVDO8PF7HzE+3Ge0u835yWM+/frrhKrgxu4un7pxg7opQFnMldt0dYfj4yN285zP3LxFQHP3k08oj1aM9odsuZxqPUeKkoPeCKscjx8fM+6MmKQ5udaYZIhRmqP1jNN6SW+vx/mj+/zx179F/2DIl7/9ZYKrY86JjxAilquGVkZQl3+inyEyAxFgbMDkZpnl8u9xEHDp4WDDcLavfTYHpb9zwHj/OvloD0xOkHZDoQyulZycUmhcG8YXU1o38AQUmJa/uPRxCOgokKgQWQRR0pINcWEXfJu1swFd8swZ+MiitL1yYkrsM5sgJYjykcCIEOWyFVHAXwK2yARupKU22kAJofXLXXYzji+8TEPYXE5pJaNLeKgEr2I1oFEbgBKbBcaclA3TI4CJvpk4gWKUJWCxeY90sMv65AhchYgn6XRwTUm5OqGvRpg0R/e69IcZiakY5wP8C69x/O7blKuCQjkaLWgt9FNF12qU9hTTCz4Olnt3As+99hJLAnVtSbLYB1cpKF0Grk/homdkHixXg2acN/g2uVSckIvjSl/FtgA2Yb2G63nGaF4xTBp6ds146BgZmCxhUgn3VoozZam8p9cERr6hEkcdYNpo1nXDIBUGSUZfN1wfKm5uGbY70OtCUMLuQPHGVUNHC/oi8L1VSUmGyTKKVFGGlLN1SaeoUY1nPVtQOY9yJaNEGJqaV583fPTI82QaOA8Z50VA2cCj1HFaCYeDQJrDypUMu4bDpKG/hLSqmdiU80Xgw2lAlOXOVDGTnI4EXgglv5AnTGpwTcLSDHl3es692tPYBNNoulIzLGqytWa29iz3u3wQAn80bVgMhpi0SyfUSFPQKUtuodiRBF9pzpTiDMW09HzsPUsFMsxZNgXhfMV+t2FgPbsHW/jKkTUrunnC1vaE4+U5fd/jYeHxKon9zn6Mx080QAFoGdJLShfDZZ6JaIUyus0/gQ1oUT+ySwJVCeGxR5ZE+UbLZd5IuYrD2mbtZwmYNE4yOo8+EQ/k2wq7L+0uBlAKX4NaK6iiZCRE6aYuwCUaEiFPhZ0bQn9XETzYPJCkEJxCC4iF/qdA73rI4m5HF3GSUk6QlYpVOi7OYioHPLgTCAX4lVCcQXIF+s9FcIUneldMSzFvcrV0u15oBVZIRh5JQWUQFprZGez3hJ4WJgdw6xfiy9ZnCl8KOos+XalBp5B1IR8qkomge0I2VqQHoEqY/QC2XhV2Xhf2pjXLO0JxHsu20z5Iqph8BlQhTO/Fa7+ZmGl9BHFnGY+/WKwpdElQljzJUSSYIBgHUq5R2pLrnLAWlqua8smcZLbiulXsOcfdsxOsr5nOK0IZODzcJ+/3uZgtuLp1SEqXt/7D13l472PWqxMUJVY5lAk4BbWBRkfaPRmMGd++zfD5m2RbY7avHeIygzMKUsON0S7LT07wZ0ueu36Tx7MzRtvbPHjwkK5WGCfUxZJP3b7NIE1xKbx/7yNcA2++eItPEsetq9fZ2trn4emcm/u3ePudtxmYjHe//X2ScYdydUHIDDf2Dtk+2GeU90kUWBESY6hFmM5XHOxfoV4d8fb7X+FP/bc/hx6m/M+//y8oyzUqSVoAH0PD4tjZAJR4w2ySTdta4R8ZmrG0dyOntpLIMyzY5bNVeFp91z7y4Ta93dv40LrHg48LuCh88KACbYHEpTlea3Np4N2ot4hcRr9HCaY9jyBtk70Y370hXGUj/7QgJb7uRyUTdMxDQkHQsUx585lKWsCzYWVav8slF+I3Jy9P2SQJLZui2+crFA4tPo7zFoRcXt+4g2qBXvS1xGOPFTtPxweXYER0i3QENom9SLTwBWUIxqKTBGMtosH5BpXmuMqRlwWhN6DyGqMsaWawXWFdLmiUZYVhFeooVVtLN23IAGOFxjSUUjKdz1mi6R1f0N8e4CTgfEOedQHDw9KyWFiWtUKnXVLnOFo7nh/CzjDDNyXeC56YZpopYWQNJjG4ZkWiPbmu6eeQpJrEKlIFGRWuVCSmQ10L46AZWU3Sh4vguAiWC29YO5g1jo6FiQlcG1mGqaHRscpQdKCXB67sCi/nCctzy72lsBZBpQbnPGW9pFxMqUqPq2uMTUnyhBAKtFHsjhyfvaH5pHKEICyDYhk0H1SG7x95UhPl85mCOgiHHcOrPqE7F7AZpyFwb16zRnFcGSoH2wQ+M4JXGkeyEM5ry8lJyZFoCpsyzCx9KXnZ1Lwsge21ppwq1GifGQ1n/pSgYjK0L5eMXMHLvcBriSW/CNQ+ZZp2+GNX8HDeUGjhIYLFkOjATqIIwaCUZX804NH9Y0zHUkjJen6G0p7MWrpiWXhLkvx4kOMnGqBsaNLLgbsBJxuB9xKctBrxpuqASy4FvCecOJjyI8FTeEW1jhKOTYiLuUT5Qqs4Rxir0BrsANLrxMW8fd9QAitwK8EXQABXKOqFEEws5UyUYnwAo8Mo+SgbXysS5/tQQn4D1K5A3u6ufARBOEEqBalAUEgqER0E8OeK5jyCouIUzD6MXo+MTJygBGyLtoiBTpe0u40TszJxoqfThkdV0K00ewcCa7jxc4HRa4JaKWwqFE+i/8WIomyEtBsBSjqI3aWx7Xl1oLyvMSlMXgIdBJVpOnuCaxSdK0Ci6T4nmK5ApsmcglO49BIoAWsoE8sSoS4KynpKnTR0sgmmcaTS0JHYY6K6qJk9fsTFdMWkt8XLn/ocnzm8xfqFOb/3W7/B9975Dr2zI2a+YV6UmOE2N158ndnpY7JG8X/4M3+WL3/9a3z5j/+Ai9Wcyq0R06BM7OTqRFErhXS6DK9c4fC1T8HuNjLq0d0eo3tdnK+x1pB4xzAEjo+PMN5w7+ghdtjh/bt36A567B9c4aOP7/GLL3+Krc4IowXnPFmnT8Uc7+b89OsvYVQaWao0YYXjrJjxvTt3EAd5seb9Oz/gl37+Z8gLYZhZchcI4mNWiA5YrXjp8AYuVLx3/5hkbOlNLG+9821KVaKNogkBa0yUekIEB8G0norAM5U70ZcSkMsQtM3O4XL330oibHBKuwxLq4NsgI9qx3VQlqAtSINrGiS0sgYu+kV0rHyJPXBoGUp/WVWkDZcJ8eFyUNMGNcaSf1EhtosPEYpE33yM8mZzu+n2gEObhaJCzHaAdtxIW/GjWhPs5ix4mqekVNs1mcs29UiMwn/KN8WqphDazYOE2AGWls1pj2dTACBhY5KNjKViE+oWfqQqESILFAJtRVI8HoLCh9BKQzr2rLIWmyRgdGxd4BqCAUFTNjWZzlDZkKKoeO8b36LOD3Ana+x8yZYNaAJeeYKCRBu00WSmIVU1wVc0zrIsF+x0DlgWFevFBbIQ8nGPRy7h4Tr2fUl1D3A8XnpOloGbS+Ggm5LYgAsOHzuXkVCjlGXtPU2qEfHYVGFTRaYCYgMHHaFsUnTj6Q66XAkpO3rJ7jVYp4GPTmvem6Z8sBSeiFCL4Z2VIn/gcKK5MQr0egGdxuvbt3CQCM8ZqFPNkQilUgQlFHXBqlxgyjZSwkPeAXxNXRf0M8+nn4cHTcryTKhXmsoJD4PlOycNW104BFa5UBTCOAiv9AJ2XlO6FNXNOS5qHiWGEzIqEcZKeH0nsN8ITQ5VIShqViIkaUoPxwv9hp8dp9xuHCqH6QLuPznhgdUs0FTnK7QRurrhlT58YctyGISiDlQKkIaOc6jguQgg5NQW+tbRNZZ11ZBJ4LE+oaxKmjxm6CxOjyl9wtw1lGtolGO9/q+om/FmwWpl3rgjod39bNiTjWN/M1PKRnMmhhddBOQiekOiiz5OenUFValQWjBJBCS2LS9GFImNwWmStCBi0JZSKtALRVgFZB0lCkI0mjULaEpF04lAoDeC0a3Ieqi2+dIGfFAp2FKwJ0inPfymBVAQu7gZ4vPyVqrRQjgDdwE4zephQDIYvaJIhhuWqa1MMrKpxoyTVzsRC20J9aYEtAVM9YniYE9IX4kTwdbroLJo5htcUxgjuHPw68jodHuQ9iEbAclmfRDwCeUjRf9a7EzqS4VyAb+E/IrQ21UsHwokCrGC3vQV2XzJ7X+dgmlTMb04JxGPCmuSTOj3e+jUoYjVHaHwuJOS6Udn7KQdcJ4ffPXblFXJnfvvcufudzg9+ZjzaslpmpK/+gLbV65zGhzf+N4fcWt7m2986/f55MkjZs2UUtc4G7BiSCqFdoqQJGTjMeOXb9G/eY2wM8J3U8ZbfTq5YbW+AKPIfcKrOzf5qavPs7hzRKMTeqMBw8mQH979AOcrzs9PeG3vCtt7uzRtKmlRNpydTkmSFCpw6wqVRJPjTt+S1R3+u5//BYLK+eCD+5xPT/nFL/xJ3rjxAmkdSKym0S5KZFoQaVABbHAU6wUH+7u87Wp++99/mf/ld/4NHz16ACpBArgfkUU33+MmxGxTlEtb5rtZFBXaWFDgQmxvsGFgnmUxL/0SP5Ld1MoeIjjvsbKJhGtZhk14iGwqbDZhcKDVRkQJhKBa10f75i3F4Vu2UCuNl/Zo20aGDi5Npptgt3jf6ctjj+cqcTMj4dK8upFnNuTFhmGRTWVO+97BbBSip9LTZXl1COjL691uhIgVSnHcq2eAVGSApX0frdsqN7Ux/LYARp55bYBYehylLMRFKUoblEnQSYbO8rjIK6hLj7WKxjvSIHgTWK5Lzh8/Yv1kRTX0JCtLpylIlAerWJnYV0drQ2ZyjE7QQTGoa0ofqJYFdAeM9S7n0znLOqaqLsVw6oXGaGhKEg22O+ATZ3l0umDfCns9yyRPSMS3JFLcgM5Cw0WSc7g9IOTLeM9ZhTGglWeUNLgc9vIBt/MxIy3Y3gVXtj1bA+h+IlBWqErzoEq4bxJWteZhWfPFfcNLe5ZOR9AqYMqEwTJwo3EsKs/CKWYmQ1RKUzku5lMmtkNOSmYU/SQw0BVZ3lDUa2zSsLOdsxsMczHM1w2r0vOugsHc8KKCpCdMl4FRUBz0a7p7cHKxpkCRiHC+FuYmYFPLMBRMhppRx0OqMeuMH9wzuKmQG8Weanh1ori57bDTQNoPqEnGycLiq1j90+10kKZk2Alc7zl2Bo6hKGgUZRKQ4NkLCuqU8xKmpfDEwSLAmQ50fWDQ1ayaEp8pPjpuOC2hqCqSNMU5R+otWWpZrc2Ps8L/hAOUzaOdNDemNtEKZc3TDBSeMitx99KWEM8D4cQTqqeTAgihjsZYIUo4SkWK1ph2gjVgsziDZNcFM46fISqglwq/ClAqwjoej/fQzKFagMtBZUJ/oNh5PkpD0kTQEFyUlkIdgU+6D9IhZrY0IdK9QkyHVSAOVEdBQtyRrRT1CYgXmmVkkbrPQ7olcZLzKnpXDCgbw+J080wPIktkZjYNJyXq4qoBNxX6B9C76lBdUD1BmggkVAd6VxSVhuKRkB8oerfjQpRsSTT1AojGnUOSKrJJIBRx4vSl0BTQv6EIdSyzNG0EeXBcZkXQ5nCAwQucV2uKqqCnDX0rEeVPCzI7pKMMmemwmJ5x9GTG6WzN+xcPKYoapxUff/JDTmYPaFSJyQzZ1RscvvgCdueAel3x3be+xaxcotMdzhfnzBcX1GWs4bYm9qHxJIROzvDGNYYv3sTsDAnDnM7uGNXv0M8zQlnT63cQZZmYLo/uHzO7f85aKwppCHXB4uEMHQKDTod+t8O169fwqeE79z6gODnj9sE+t6/eYmewRRocJpTcf/AJ/ck2vf4YVTmudoecL1Zc3eqRqCWDniYznjxR+MaRpgnOBkRCa7AM1NWS5WrGu++9w+999Q84+ugu87qiEo2YBKU1Wgn+mVJXvQk9RJDg8ZcLqkbZZ4acaptuqijHbEpkkfBUCVKbZTQGCsaH3nwUqdCqRzEASrcm13a1b6XcQAhtCmzL0kSLR6sZiY9Mh4rvExNYJXaYbt9KtV62zRFI6xF5CkqEjf4ZpC3XJUpHMVmlzTRRqq0SUm1zwJjw6FsNNcpHXFZEtZfgUhaSVrZqA40uZa/LvkDytAJCqbYDuggirZEU9XTzJUTGqpVtVcuuCLF/j2rrizTgvY+Ay6TUAquLKT0SknwH6+Uyul+MpdEJQoe1rchMF91PWHaHUDV4XaI7CYnRGB3nS+WF0FQ4HxAdKNZTju7c4catzzOZ7HB2vkCUwniH9jVKeZwk1CU8XAcyq9GkHBWedFlykCdcGXbJjCOIR5SlyTI+Xjug4IU9y0ALxjtCC6oNnq5RyOqc4At6I89gCHpPkQXBdj3Dnmbn2PPWPHCvbjgNlouyw6MHDW8uhJcnhhuZJlwEugKv5nDYz+ifV+h1w4kYXGJRxmCtIlfCKIXtieaFnX0OJwuK9YqiVKyXDfUadJPS9YLTKUub8YOyYloFtscJzbpmxyhGe0K2LfhRJDGH54ZybagNGFORp4YmeFzforpCkwsPPypYeUM31Bz0YSeLrGHZGLIBMMo51wo3V6Qi2LrALNbsZTDJBVVDYy3Z/oR6kHP85IIkgWu1ZpJaVv0Oqmx4UpWsFUieMBx3uHY1w+oex9+9y6ATM7hc49nrdZkohakDx/J0Tf4vefxkA5S2AkeUujTJigZJzNNOoK0m/YzgHSefQpAnHinU09wUQEKUdlxNG8gmrbTT1hyo1o9iwR4KZn/TOknBEiiAGmQdJ4UgCrcSyrkiZKByoZMotl+FfBeoozYsLlK8uLjTsYcQeoI2Bpx/CsKaeI6RTVERTGhgofBPIoPRLAS3ViTXoXcrToASIhCC6ENRAbS00lLGpsAhgp2ES41aaZAzRTMLdJ9T0QeTbmZ2kCqWX2OEpAuuD/pqDIITJWgbv5+ozGiaY0MyDmgTgVsoFPVUQQqmA82JoDpAHtmT4BTKyOabY3N7e/GUrkR3+wz7Q3bSlL4SxkmXCT26ZWy+tlg67s3mnIWalRWeLJ+wWJ4zq0+RnQ7d3etMrl/HjAf4bo4PFlsEzo+e0M27nC8LSm9YVYCPEdsYoU4U0u0xOLjC1isvoUZ9fKIZb20x3N5FdRNmiwskARpBVYGibjh7MCVYxfjmAatyzaMHx/SV5YUbN0lMQpYmlMrxzqO7vPODP0ZNF/SSN7mxt09YLjhdLOn2uzQ6g3TERQHnx+d09Tk7kxG713a4ddCLpm4d0MagtcUJPLz/CY2vuHH9Kg8efMKDB/eQRPNvf//LvHPvHlLWlBJorEVMhrUJSnxLPqrY4VfHALRNAOGlIVWiv+MSayjVRqy7doHbSDyt7EBckCUogmy69QJowubztCaoDIXHBMemv7hqPSeotk2Eiib4WJnS9s+5jIwPT2UX9TQPRJ522WsD3p52Mb/s00OUQIxq5Zq4xhOMvqwK8sFdApnLyO+WFdE6juVNCkKckzZjoZ2U2gRbuay0iUbiTZNAVAyGJAghhPietBuOZ8YDLbsiPK0Qil9LC4Ta67DpOr2Zy0KI/h5C9KI4Ad84XONI+4BOSLOMJM1wNXS7E04721TNku2DbarGUM66hOkUJXFHnpGhtSDW453DisaKJ5WGgsD05D6D4S4HV0aUVYUCBk3BHoHh/g5Vp8PHD1Ys1kvKypNYiwoGJZb5quLU1QytJTWaNFU4o6kTuFhUPKk9L24ptruaBKEWSyUBp6FE8JQ4VZOOBJWDVzBwwtUmoFKFnWfkp44fzgMzb/jAwfRccTR3/MxA8XK3wzjTdLTn5o7Q27bouzXfPGs4dhbyMUmmyBPNoG94/rldRn5GOV+i8SwIzNeB2QK6pbDVaFxTsa4tDwvP1Bq2PWwZTdWBtGvoWkeyHejYDtvvVOhGgdLkwaGCsGgC507QBdxb1dxrAo3VGKNJMi77TY33Ay4YPpk73p8tWaGxoaFb1ezowPNW011BsVLMgQtb8K3ZAp8EtpOcDE+3rfLaV5qLJhqNGypC4WlOPMezR9zezdi6lnA883zwfsHuwJArw7A0nDXPrsX/+cdPNECRtqxPt71jIjixUdrZPDaqwLMGszLA40BYbeaHpxVAdaWoq7gw22QzUQrKRAnHWIXOQG8pkoNNQqaCZZRlpAHWT3MVXC2UM/BakE6kHYe3oXOzZSmUQmqJs2Cl8Q2YK4LabjleJ5fnoBvAR/0/BNC5RHZFIFwo6nPwldAsQQ+E7vOAIVb6aEVbuh9D2UTAbSSrdvItQXWJRt94gcEr3LnCdDRJR2KFkWmpdqsIq3iNlYdQge5Ddk1aYBjYSFJKNG6uCTVkY8FXcScpdaBZCPnztKWRiuyqQiVxllYuMj/t/pM45cYOyP0spTcZcn20w9gk9AX2BhOGSY/V2ZLTsyccT885KwvunB1z9OSI5fSEYd8wvH2N7NoVzHhCkyeoYcqqWCPLhuGiQS9KUq8p68DxqmAtbapwalG5Jt8a8MoXPo+zKVWaUW7MiAFcUZNrg59XdPo9VAn72Tbr43Oujve5vz7hbD2l8SWDrS63Rvv8wmc+x+n5OR8dP+S9Ox/hfE06HHK4dwXJMhZFwez4jHXd0EVYB1idXvDo4SnNfMnVQZdrO3t0yeh3OrgQcOuGYDQkka15MrtAQsN2uc29T+7z7W+/xXff+QHf/c4f09QNxpjYwdgkaJOhbYJVbfVUW/ki0lzKOEFa0yhPE2AjE9GOiyBIcJiN0TPEBTn42HQQHErb9r02XEwMPlPGEEyKBB9DClt/VcwSaSUeiWPXqhjhrvWmJYKO98xls8D4U9XKvcoraEPVhLjox9V6I1q1fWsiUkLMM7KUegaYPVMNuDHZ+hbZaxMIXrHJThGJqbAglz8LbXLsJdPTjjlFaJNfW3GpBXUbqSh+fgtQ1CXmi2Ckje7fvP9lUcDGO7sBie2fmLYbWok3wThNCArvGiRUKK3xLhpTU2PRSZ/+1ZfoPF4iOZi8j+kN8ctzQu3QTUNt2/MIOrLHXuMah8aTSsAXBecPP2Tv8A2G4x61Vry+69hfl5TNlFVXUXYUqhFqFzOUlIuGYYfipPE8ruOM0MstqQnYLKFJDU/WJfdLz2GWcKULg8yy9oHSCQvvObAp2T7YUYMkCiOQpEK3rxl7uJk0SFfBNOW9heVspTiuFRWK7XXDi8OETrckNw29BF7ZFmxHGB4Z/vC44Wi9YG4s/Y5g+57Tc3j77Ts8P6nYHghVrlmLxlSOF13CC2SExHBnveA9E3gkiic6sJ8kbPmGz1dgOwHpC4Vfk40t+gSS0rOXCFtasV5ozoZC6Gi+fSo8qBPqNKVEWJaeCgdYgoWzqeKtjyoepxl6Enghg5s7iuc7mi2XsPqkYX6uKYPFH25z5GaUoWYZHDuZpq89zq/QKsOqBiUa02j86YrVskSrmk6m6SnPdkdz0rdU2lGIsJbA7mD4LKr+zz5+ogEKmzCjIHHHYQ3K6s0Grk1CkqeITYg9dk4CMm+DytqdhFIK10C1jt4M25bLoqK+q9pUWpWCmSjsFUHpdiezVrGKphFYEDNQVAxXc+sY0iZdUBb6O4rBS0DegqoM1CrueJqZoPYVel9DpsH5dqcJ2nGpi+NiUBytkVXm0EyJGSMzhcqF/DakIyLjoqIZUZmWbRGgicBIp5uJOC4iyrTXtY1QoFRUp6AzicDGtfOpEcTHSiS8gkLwlWB2NCYTpGmbv9WxrEmJIpxrbE67Q9WoIDQXCieQTBSq8YRGk3XacC0vSKnj5KoEpdqdtkBmNVe3thhubbOb9emJoactic6ZrQqezC/46PEnTIsVC6k4K+ZM6xXbtw7pj3JcluJHA5pORnfSZxEqvE5IvOP84WNsgP54zAIorEJSQ9pJyMcjusMR4+0Jz//UGzx49JiLJ2d0hyP2x9u8/sKrFMpzsVqwahJu9Q9Z1wX5uuHJgyNOigXNOGGwc8ju7g4HozFbkjLudBhdvc4HH9/lk9kjbty8zng4xDcND8uC4w8/ZJhvs3ZCMp9zON5ifr5iZ3cfBnvUT86oF4LUBb2tQbxpRGJzLzySaV781Kucnj3ht373d/jmV7/Kt7/1Fg9PH+NCu8gaS5IkkKRYm2O0JbGmLe82sZRd3KWMEkIrsyjV+ik2DMlm4QyI9+gNCxE8IXi8D62s4kE8QVz0frSDWiuLMQlZpwd+sxjH5ypp30MZRAwJMRLAqA1D0ibdbgIM9eaWaY81BHzTRHOt3vhWIvUqvvVutBIwLSNyafbdsLJoRLVZJ5i2T08LynlqxAeeMRLzzMQcq56UilVfQVr2VEVwpGnH9cY/FzUZTDuOJQii9WXY3CXmgOiJCREttdbcp9L2Bs2opxsopUz0JSmFd7EHU6+j6HQMWguJyXCuwbmGLM/xWUo+yMmHPcrCMZpsUw6v4GdTCA06xHwZJ4J3nsZDXQlrF8FlggNq6mZKsZyzv3eV42rO1V24EjRH5wX3Vp7tkKEThaiEtCoYUKG1oySwRDFDWJAwa6KEqWtB6wRUxknjuV/UTJaOrQ4M0gyrNeIawnmD7QTe3NEkBELS+nqsoBMwtZBqYZgq+t2UhWT4NHpFHviKItN0JtBJAnao0X3N9STQdAIytnztoTCvVxSFx1cZk0NL/1O3+PgHdzmeVaixopKMK0b4DIaXJaXXGXAzaxhmNV8uNVPgPGge1PDhSUGWRr/eWoPPFFmiOFx43lCO5xqLMSkX/YazOvDuFNZKYVTAF566FKRnqFea9aljUae89vwrHJ88pLFzdjrCtZ5mv+vJG0eyBa4UQmN4vFzgfcNqXVJ7j7OKrVSR5w2uqhmYeM9lRnGw1yNRa1RqacRTrB1CxqIMnIqh9LASOBzoHwef/HgA5Vd/9Vf5jd/4Dd599106nQ4/+7M/yz/4B/+Al19+mq5fliV/42/8DX7t136Nqqr45V/+Zf7hP/yH7O/vXz7n/v37/Mqv/Apf/vKX6ff7/KW/9Jf41V/9Vaz98fCSCqB8BCeSaFSyiZ1uS4xbGjbuOoDaE049zDcLrVw+P3ihLiLbqUyUQSLQUe0AjuXFeqhIroDYgDiFKtoxXwl+BspFEODrls1YKVwGYiHvK4avRnbjcj52QArhXBE6Qn5TIR3NpvtoMNIyRDEFU4JEGcaq2IeoVISTaMD1bYx+sgv5fmQ10G1VorQ0dVBPd1upxICrzWSoZLOBjeuMhrBU+JWQXQXdNj8Uadmdos2aacDNIvuR7sTXKRvfRKUthd2A0kI6CPhGoxNFmAtNIXSuxPh8vzSEWlC9OFFLaHMmNkFtmztbQWIs+5MJedZBN5600yHPOlyczTg9PeVsPmUVSugaQgG6k7B1uEfa77DQDXmvSzrIqTPF3JeoTpfEdpng+aReMKuWuE6f3Tc+w0GvQ9ZPSVMFNiE4Tb1Y80ff+mP2D6+yu3eAUprntg/5s5/+EhezGb/9h3/A2eOStUxZnC14fL7i0Z177O9uc7B9hcNrz/Pq66/S0Zrpo2P+3//i13njzc/z2utvMpvPGYz7NFJTW4/pZty5f0wnREOmqQp6/S49rTh7+IibV5+nc9hBK8WTx4+4tfUckpi2BldxenpKEQJ0DMdPjvjq1/6Qf/+//T7LixneGoIGaxNEKxrVlrSaTbaIxiYWUQYTdLuAxrHhfOsnUS2/tQEpbIZVZEzU5TDzsftxCLFSxkf/hsZH8NJKkcokGGvodPJWut0AHwfiCD7gtQVlYzfgtuz30oOhNj6RzSBrxRsRfAi4NMcH31YFtUBaTDvmIkPjfcvSKPC4eN66lZcwLXNkUMpcbmRUC8Qvb1SlWgPwhvGJUMuYmNkioomdkOOOQKmAbtmgaIJV7WB00ePT3vuiogcrBtO1lTibsdEm0rYVy3Hxbb+v0MpJXM57UbZWZNFgrwJePL6Z4SqwSY7ORqxdja5SeilYPFlYkvolq+WC7NaA8e0XKNcXrMslvvYYcdQqEKhpfIgbNxQYTaKhQVOXNdOzKTcmtzFOk+pAkjgmPaiKhiwVBhJlnL1kxEGomew1SH/JWRN4+7jhh9OaU59TKE2joGk8IkKKwmA5956zZY3RnsQoumnCGYqLuzVnDl57PmU0bqJpuAkkxH1hx0QDOU2Bc4ayMohXfBQM33iy5Pa1DsNBjep7ghKsMowTz8E4cM1l3DmDdVGxPg/cC4/Yv3mdu3VOsdLYpmaQe64bw03rmDQzwnzKc1sp+Y0hH3y0pPKWwnlOgnBnZun1oK+Fsg/HlaKjNLc7ji9YRX8FXdvjpKm479acBUXaTRlaS17U7BnhygB6c49vDNZmvPziK3zr7JQT73FB8C7QBCFLFf1r4POU+ScNq+WKXYRJpunZlN1uh1Ge0dSesnBUxlB6oaahNi5mghlDVcDFiVC7wHzW8NALCw1ox3BZ/jgKz48HUL7yla/wl//yX+YLX/gCzjn+9t/+2/yZP/NneOedd2JLZ+Cv/bW/xm/+5m/y67/+64xGI/7KX/kr/Pk//+f56le/CkRD1p/7c3+Og4MD/vAP/5CjoyP+4l/8iyRJwt//+3//xzkctG8nHqMgeWqKvcxeaHdzmnazduZhIZHRgEtTrBJFXcfKHaVacNIO+uhni8mmug/pFQU2oJtoasUo1FyQOZE5MTHDxNVCXajo2m9z4obPQbLzlAIPNeg6liSLF7LnFaqvWuOgQiyXvQtEA2XcEaokTr3aKcKFUD7WhHXLYIwU3euxMsJLC+J0C8iMinIPsTJAtZk5ykT2R+UKaYPg8NG468+jB8R0IojBg+6CVNE/QgvOxIPdUZh+vA6h9bhIFo8hVAbTVkeYVOGmgeo8ki+9Q6CjqOcx60Xn7U7Y60ivSyu1beyJAtZaLIpisSZNe2hjqSVwMj1hOZ/h12vW52ecFyvmTcGw22N7d5d1U3C0OKXb6yPWUtQleXeMzboocQx7KcvTxwy7HZKdXbZee4POYIAUS8rzxyTBcH58RnU649b+AT//2hf57id3kDxhURV862vf4Oi9j1g9PqW7rvil136BRb/hN9//CoPuDoe3XiLfmbBYNnxy7xHPH16l19vBbu/w4cU5+uyCGwcH7A76PHr0Pqan8dpjeoFFc8b21jZj06eXNNzamuBNh05HM7wyIDOOpLeFNCVGdfHa4JWiP9rizg9+gFMVv/8f/jf+4CtfYb5atuFeAQlgkFYiCVFgkOg18UFiYrGORlStbWQMWumzVVvijlxJm8Ta+jsuK2F86/mw0ebcAoUISGI1iQR/Kd1gEmxiyDsJynlMHKb4YAhiCCGQYNr6WoU1ujWnbvJanoKFaFaNh+M3E7KYSEoEh4hvb/iETWRpaOUjkXgtfEhAfAQo7bEgkVEx2sa/bkLi2vLrjfdNb8zeIQ5iUQYdw1swtDZVUcTo9Gh43VQTtrxPnIvajYSiZUQD7SCLEs3lZ5pW5trUNYcYLqeE6ENrGZrQssYQS5CNTTFJl85gjJqeoHxF49aYUCNNBWtLk3VRWUrW7WB6iuXqArGB4e4B4eanuDdfUzT30EVskW4zQSlHmkQza2U0XkLMeKoDbr4C1igd54pEApl2DCxgHGm3R9crntM9kvM5B72a/n5DpeHKCG4+hh+cVjwqDVNypj6+z4CGHSNYEQqBlfdUXrN2DTOtmWE5v1Px8NzxqX3N1V0DSUAaIfXQE0U/CJl3LTtl8AZOBL4681z/YM2fuOnpASrVeAXaGrJKYXzAN4FMGfa2d1ksz3n3g0c8Kjzn3qCc5koDtxLDzhi2dEWiFK4TSPcyrj0OPF4FikqxAD6agzKenTar5JOz2Oz0lZ7nuVSwxjGbn1F6zayvqXQ0tw+s5/rY8dldxc1OIFFRHQhlwR//we9DqPHKs5TA3MM0gO4qOjrB5ylhXLA7UoyUxjaCWnmUc9TrOPfvmhyPomnWgOLJVJGsA04c6zquRX0rXNsZcDytuHAalMMr92Ot8T8WQPm3//bf/sjf/+k//afs7e3x1ltv8Qu/8AvMZjP+8T/+x/yzf/bP+KVf+iUA/sk/+Se8+uqrfP3rX+dLX/oSv/3bv80777zD7/7u77K/v8+bb77J3/t7f4+/+Tf/Jn/n7/wd0jT9Tz63qiqqqrr8+3w+B9pF22hUols95plHu5IppQg+YOYBNydKHhuBl0jNBgd1GX+mbFzcW4b3snBEdyC9qmPvGh/dEForwgyYtQBAx0wF18RKoOAFlyikisg0vxmpDAFwoGqFzBTuAvR1UDtxx6QEMJs0yZasbYhSVkZrCARZCM1RnAhdE1NokytgRq1pWMXzJSXu3lRLea8jUyLu6YTbzu+RQfGRAREXy6XtIERGREk0fRLf9xL41cRJdSKR1amJ9GwdopSkNbhw2awxNBBWCrf22DEkA5B1vGbpFWn1gBhE55dcauybw48TfmC+XFI4sENDZ73mYjpndTZlq9Pn9GLB/N4RjRIG20P2bt+guz3h3fsfkE2G6G4f8i6TwZjeYMTjsxW2UZw+fMz69JSh0mSDIY2OpNPyYoGcrKnLiq20x9UXb/DffPGnmeztcff+Q8oyMF9Mee9kxekHd+k6wysH17n4wYcMdg+5PhrzU/+n/46prfn+k3ssZw1PnhyzvlhhUDz/0kus8ZycnjOtC/zJY1yasDUecNgfcat/hfsPThmYIYf9Dt2iZphndCcDvDiyLtTO0wCyquiYLsYonFGkec6tG1e59+gud+98xNn56SVDFsGFwqEwQYFXeBq8X+KMxZoEbRxaOURZgtF4rbEmggHTJjULrVellR6kZSPiDWaACEpEuGQiRCKT4oNHt9kjSim0tXEPbFKU8jF1RECFgMNC8JigYpmpVWgT5RKlTJR6LkuFFVaiFAtCsAbjhSa0pbkqjSyEhHgxgkFI8JtUWfFsOCHxTw23oWV0lNKX9/Slc2VjAFGbIv3o74i2OEPAAq2httWO46mrVl7SEQBKrBwMtJ2Ldey+w8a3YjRa5FJGkzb/RF92hG5Lu9twO1BtflM8B9OCTK1jEbcPCS6tySf7mKSiKU7xZUkoK7RSJFkCuSWIIelMGG5t8/j0Ec1qTmd/l+HBdcbTBbUUBALGOSCQiCGxUKqkDQTzaK0JOE5OHjE8OST0hlSNQjtaOTBmwNhQ0bUpiS/oEEhCSaKjif5ACx2rmXQ1d6eGuwvHQ6/oOPh0J+entvqMxyXnes47JzUfnMFp0FSpxduEe0Xg4bnw/oXiU3cbXprA9hgG3Tj3XzHwWDwXLnDuhUI0ldLclYx/87BiHeBVZ9nqeWwnsFYRQEvlsZViqITy4WM++8qLfPvOEbKqcFlKHeBxoXgUQAYpw+1AJ/c0WpixYL9v6BbCvoarRcAWgccNnAaoS8NRYdgl8OqVhHFWkmnBzhVnlaJaG7zOyBJhYite3oIrW4rEBEwDuVKUa8FXK1xRkUigv9nbY6lmgems4UnpmWdCZwR7NpCsFatpYDnzdA92WSjPuL8FdaB5dJ89k1BOG85Fs9aB/rDDVjdlO1eMR13edQJzRUKgozbBBf9lj/9dHpTZbAbA1tYWAG+99RZN0/Cn/tSfunzOK6+8wo0bN/ja177Gl770Jb72ta/x6U9/+kckn1/+5V/mV37lV3j77bf57Gc/+598zq/+6q/yd//u3/1Pfh60Qmy7a2hZxM1DtdKOhIBeBvyZR9Vxpx9HeAQiEqJG6ppYsaPaIKrYjTROpjqD9ArQD6hwWUtAmANTokzT8qi+jqWx3gveKlwN2RiGnyJWwEgLAGqgFJozkCGYKwZSdalZCyoGTwGqCZHdTtvPUUTqYRGBka+iZ8PsQX4IWIkUS9l+Zpu7gBB9JG2uCo1CTJSPVAqStnq5jztCqeL/Jz2FNhK9L31iKXJozcNB4WoFA8GM1dOEWhd/hyGyMV5FN3kGNLE6xzvI92KTN7+KrFNnH5T1yEojbW8fKlqqnUtTofOOYrWmEMW5Ezxzcg8UBeenU/ZHE57/k3+aD48f8vH6nJUreHS+5sQ4OgeHhKyH7mZknQwaQ0d16KWGs0ffJxXo9XJ62yPSVFEXS8xyhZsuOL3/gKlJ6b8g/PFb3+Xk4oLB1hZGwZ/9hV9knGb8q7unlPM5u7tX+PjeQ2b3HnHl5dvUzZzJ1W3KJwvG+3tkKuH27Zvs9UdYpXjr/bfZG/YZZ0NG/QmdSZdOKoy0Zj49pz5eYrf7FOdzpvOSj6o1Nw+uMLkyRDWB1CQ4r0nTDqFp0Ini+PEj3nn/h9y6eZ0fvP0D/uib32h31YCKJsFNA7vgXQxtVQ2iFd5a0BmRlLeISeJ4SDSSpGgTGQSjbKw221TJtKYTTcuoqCjBRJjSMoKtzCMS+/tIeFpKp9v8Ip1k8XkCPniCiahKeRNj5LWOmT3YS2mn5WwIqn2uhEuQQGsiTVppRHjW+Aobi6wWhQr+MohNpPXYiL+UiZDNa1uvh1LxOFU7f2wYC1FtPknM7TAbaUW1+SdEo7rSHlGKICYWGUtsK+ARgsSqpBhh34IvFaUcLYLSoS3B3jCNghLfdvcwTzNTQrtxIYIf3TLEVml8I9RpglYjNPuIW+EWNWW5Ip3sEZKEsqroZDl255Ctnesk7x0xvzins3sL2xuw/9LzSFZxfjfBr06QeoFvKtYESm/ifC2CC7GXl9SOxw8+offcS8wLTVkYgjbUIZphvfcsmzXTpqSbBXCRFbNAhjCwsNcLhODI0oy9PKe31rwkip3qguvditdeULxeat5/pPnh48AH85oT3zC4MmB+sebB3NHzCde0YQ/PJAlcuaIZjh1eoCkD74eGczGslKHSCe9JTvmk5KOl8OIADrcNdIUFgqqEkbK8vL/NzmyB/+ABWycLbkuD4JllGk/C3arm+6clBxNQVghas140FCuHrzNuqoSfybtsmYxjtebj8xX3vWUmCQe6pDtQZFuKPIekSSiKMcVbRQzn0mtGecW4p/FKqIyhtxNIRymri5STswatK24PNM9vw14e2CbQnAlNo9nZ3qOipFhP6eSBPNV0BglllfF4tmYGFItPWNqEvSzh+W6PN7/4Jb7//gd8887b+BpWboGfxypOT/QbZgj7+scReP53AJQQAn/1r/5Vfu7nfo7XX38dgOPjY9I0ZTwe/8hz9/f3OT4+vnzOs+Bk8/vN7/5/Pf7W3/pb/PW//tcv/z6fz7l+/XrUyK25nPT0M4lPYWMoXQfk1MfFuq1+ARWpV8DVsXKHtiQ2/pZ28AokimRfYSZxAo0NTDXMQ5R12kUfgdAI4qP045XCqRjoNnoV1CgOThPaqr5SwVRwoshvKuhuNKU4wbHp+ugldig2KgKPdsJXC8HNVBswB3YC+dVoZo0VjPH5rVTeJnYqiFEeEfC0VLwIsfuxjd4Y5UASgXXbj9W21zKJnxWqGMZGCVLGDAc7UUhH2kqjllmBqNk3JurhuvW4iI7dojNFNlaR1Vor9FDQo/B0wawVuhNQLiLPRnGZ8xCcp1kVOFEUNHz6tU9zfXePP/zdf890NeX1F16hqhvG4wknD+6w0iXNVo98b49ktEVZ1+QmoS4EI4GOD9hyhTs7Ia09tp8znEyYLRY0y5r0YoU+X/Ha4U3GB/vMizUuOK7u7HP7+m3ee/9Dfuef/xZ1XbM4m5KI5Tvv3OX2rZc5P37EV77+bS6+ccHeG9d56ec+Rz6eoLywLBesTk65snvA7Rs3ufvgEy5OTpmfryFNSVTNc1sjkmXJoPa8vLdFXkN1cUGYNlyEOYkBsxZ6oy5JHaiLJS40JNsDCJ7f/Df/K2+/9zYXZ49ZzGdIiDSr0ptuMZtMkBZlByJb5xuCckCC0ikhCYiJBtFGBYxosGmsFxcbm/BpgzK27dQbH1prtDXxfmgbdiJC8FHm0T6mt1427jQaoyPQCRsTrsR7SYtuydIIRATQyl4CIVG6ZR2Jn9GqTVFqasGD0igTOwdvjkmhkdYwewkufDR8+ss5Ix43YdMqMHY11roFSy1rG1pmI1xqxFzKVKLaTYDSGx0mCj36qW9OSzwGhUKJxovGt317VPuZMd4+giat9WVmSvxIhRLT5tnFVhyaSD9GUBOPR7egSek4H6a+SyOeWhkapVGdHC8KXwnLMKWbpnTTQyrpEPpbmMlONIM6ILWkozG7t16l0/3/tvfusXod5f3vZ2bW5b3td1+997aT2HGcQAgJlJIChp7TSuRAKTq9oUpFKQotag80UCgVLb3QSq1SUH86qtoK0V8rlUqnUFR+KqWNaHuiUCjRCblBKLnfTBw79t72vr/XtWbmOX/MrNd24iSkvx+JTdZX2rL3u2a/a9aatWaeeZ7v833mWTv6HXonD+NH25RujC0s+IICReE13kGWOna2e+TW8vCGR28kNBIDRmOVYoBnR8Box3RLM9PMKHwJBXinEOtItKKRaHJjmc88+6YW2b09pOMHmNKirTA/K7wiCynJPClMpU2ai20ezwr6ClKn2HvBXvLNJ8mGQxbajuVXajqLMP+oY/GI4v6NkkfHwkAlDLXiqGnQL4VDKwULW46lltBoalQJ09bT2NxktxO6KmOpIVw4C3eMPQ8lKSdQbKmUr64MmcoNVy0LNBwDEaxRNJVht7bsb3qWdMJsqSjRHBoqJDGMnGa9KLiwKRStkJZ/bDRi3VpIIM1StB5QOM9OGQoyPjk0HDlact9myaYWpjqahbanmwrtDHIlJG3IMwUqoWFabKxt0LMa1Qhk6m0LT47HbOgSkyZohKnEs3+2hdk+yazbYjZ1DHwKuWFYQK9v6ZcJWgoWjOPl7fyF8aBcf/313HPPPdxyyy3/1a/4rpHnOXn+dIlclYSdS9gMhsuWyU4CVOGRkx4ZgHjBVyqSJkwSthDGoyBclCRQ1fAJsXZCfHtOkyyHyYNq57Qj+O0w4ek0GBDWhh/ipGAlhFimLlake+JOywcDhhGoEtxIk+wVZD6k16gqZh95Jwih3k7FO1EKUo0eCn5TkBKcjbHpWUU6G0MjEr5Dm0mkK/BMguc3eMAt0Ai/q1RBRggdjYNRFsivcefpQ3XiZFZQg0jUjXoK4gLvRU+DdmHiwApSqJDWHEXmlFL4JqhS48dQDkJ9HpOAjDTFjtC4WAVezECjxgSF3Y4go3A/THS9I2BEk3sYjwsuffkBFpeX+MrXbmFjZ50f+z//D06urvPkzjb3rj7OoJOwhWVUDukyRccIqqkY+z7bOyPaaFreko77pP013vLGN3HvocfAGcbHt8hH0BooFpf2c+kll7BtxxQLigOXXIrfHtHxKUnPceThJygMTM/N88pX/yAP3/cocuIkdLt0WrtZ3HcZ05fMsXvvPhKT8fhDj3Lo8XvxY8vS0gXs2rcH1c5ppimMcwa9gtSkNMsWlyzsgu4cDRxb6zv0T67R9Qkq0fQHBW5QMtxpsrGyytbGJvPLixy+724ePXGExx5+iIcfvB+hxFGG6r/eYVSQRhZPlHePi76KnAaCarAOdXYpXVAI1Gg8KdobPA4tSUgX1gZFGkiekReijUElBp0m1SNTnQaUCxHUWJ9j4lExBk20+40OXhmvo5ZKhfBMKAVGhUwYISy4QvDKeFd5cE5xl3Dx0Y2eSI3GKHPKQJMqjCKUYrA2hG2Vrsi6nqpGqYrk3Ekx0si70giWIIZXiYVFvwlS5fobHTyx0aPilaBEx2yhypMZ/tXRy+WjwVWR/zXBeSuRnKI9mIoHRCCeV9ouwcMTryX4Y4JRpTSiksD5yJuU45LCgbUqaLx4ixmWeDtEXJ/GYAovBYkoumnGznhAaqBUITMqb03RvrhNszvF2tE5RpsbjEdbFOMhbtxnNBygjSdxJQahGGmcEx4cZmyuGRLnmM41ncRgTBocxXaEH2l02WKpNyJJLIUrGXpN4VOGkrFVCL7UJJ2cPBmTqwSdKPAOnSqaHWGh67lwpNl1wRTHx2MuOzCDvqBD+dAxRFtM4tA6bFRbU3DgImEq1+zfo3nZCc2txw33nHRsFJ6eShlrYVsnrA+F8cixdzqjmWhyWzDV9+zuJGTlFiYXLr+iwZIuuPkJy+0Dz/ow4/4iwR8uOTFWLM4oRm1F0dAk1jPrLItTnk6xQdaEdKnNPUfHnCgV2xiOjDzLY6GTeoaiuH9txJbXbO/0EKfZEsWqgGonOBGOrcDh1ZQngKQrZL4ks4rMgvGCzYR8XtNyOcfX1lkbDGl0hMRo+n3P4OSIjbFmE4V1Fp9oMtG0xCGjVbaOH2Emt1xwYcL9W46ynTHuw9rAoqxhxngO5J5LOo5Dz8NC+S8ZKO9///u58cYb+Y//+A8uvPDCyefLy8sURcHm5uYZXpSVlRWWl5cnbW6//fYzvm9lZWVy7HnhqRcqk81ZWNjXPNIPXoEqa0bFHYa44DlxZZVGHHdTSp2qQ9OF9AKCLLyA9hp6Hr+tYrZPWIydB2fDd3slIRShFc15aBwgeB6cBBKtC5OjShRqAcyFMdui2m56mczf+LibTeLFGR2uaxv8TgitiANSRWNZwPjgHrFUQeawVRqFNgwjkcOoUHPHqJCOmRG4IxW0Aq+QIZH0oaHhgydmRMhU6CvEBs6JnhFoxmMu3isDkgS3ctjpgcri/RpoPJ6kGVMiHTjvyWdiv8cqqPtOOVQmwVsDmI+lZJgAADCnSURBVFgFRQukKHY1O6hym06SsHXyBGsnV3nwoYcZ2JKN3jaumVG2UwZJimsY2jNTtFsputimdH1O7myTmgadtMloa41k/SQnH3qAxzvbzCws0TJtttZOoNdHLHbm+JV3v4eiLLjz3ntQrZwb/8c/wdDxqsteSTNtsP+Si5F2g6zTxqWKJ7dWkG7O7HSLPbsuYvnKCylbnkSnbK9uYnfGzHVmUVOaZnuGfn9M1gixeD+A8eaAxYU5tlc22B4OWZxO2Th6hBNPbtHyis3xNnsvvIKFC5bp9YYcfeJJesWQBw49zPT2Ov/P//gs9x1+mIGMERFKV6JUxYnQMTzho+Hgwo49eiDC7j0+d1Gp1DobSMsmwVqLSRKssxiToE2K0gk68XjjMUmCSaJxYlR0ScbHK+oUqZhlFMKpURvEe5I0aKMYrUKoER1CRjG8AZH/oQKXo0qplrgpUEIUTwz/ai9BzyPyL6p6PVTve3S8hoQbhfgY+w0v4SlPTDzuUKE2sYfMJxgTpP+10RPpAaN8Veoq8ENin/HxPmsm3J3Ka1NZb6HeUeh7eJ9C8Mn6imxchY3CdVSS94pQQ0dOq+xeKcZWKdDBART1e5UOBo13KK0wSYZOUkzaxDfayHiAHzucHmBTQ5Z3sN6RZQarMpJE0MUWYgcoGojymNTgnCJtzzCznOK7SwglpRuzs7GGbKzg7QhjHYlOyCQhTVK2JGPFN1HK8/igoKk9U4kKXi0FR3sjHts2XNx1XDBraDegLD3bhebRnvDEtiJ1kPaO0W4q2jOCmdJkLcXYgrVCQ2kWpg2DjmFTLCeOnmBnY5N07Dg22GDXrNDoerKOwoslTaHZgGbm2DNleJlPGWRNnugJGwMHpSJtpnRUky4FqRY8nkanxZQW5maEdjIMBV+7jlfMKo57zaFjMLTCsNQ8XCZsrXj2bUNjHlZzhRVLN1fMLgszmcPMpizOtFjYLHlgy1MkKcdGjuNrisXEsDrwHFoRMBmNXOMLS2/dszXUuNSRJgY1TFie7nJsOGRYFIwGDt1QKKtwY8OWUwwKw7ENx+oopF/nyjAqPcnYkEjK8vIyV77qVdx+69fY0Q43srQ8zM9ltObGDLWnvZPR3x7SG3mMTTFjWPCeNBUOdBTzXc13zraWPwOel4EiInzgAx/gC1/4Al/5ylfYv3//Gcdf+9rXkqYpN998M+94xzsAePDBBzl8+DAHDx4E4ODBg9xwww2srq6yuLgIwE033US32+WKK654Pt2ZrOlV34KcfbRQtjyy4XE2LvIxBC067CrKAsoRQOBXSJyzAjE2ZLTk+xQ0YpqyExiA7AS9BJ2CFD4YJwWVvABOFIVAPgWdmJWjRFCBMxYItxqcCGpRn+KDRNe6VLtEX4V2Qr99tUsbeGQzuF3tMHhWkmVP0o3hJx/Td9JgPIhTKKNDvZtxuC4sYeEvFF4TihQawg6xYv8XIW6ojCAJmKYKVZlLQQbRk6FAz4bwlYpbWIk7vEoJU6mQ1VRlMvlRyEAQo8kWFWiwfY+eEsx03BU3YrH6loSwkwnjVO2SFcLJ48f593/+J6yHB269nf2X7KPX2yEv+2wefoyVk6vsFCNGYhl4i2ll9JRi3GyAt1htGY3GSNJiQyX01lbwW+vsHD7Og40x89bToOTJw0dpk/KyV83wp3/2f7Ny4gTLF+0mazd55L5vsGfXbh54cIRFcJli6AqSPGNna4fBYIgerbB5pEU6lXPsngYllixtsnliG1uUNPMEow1FGYjISQaDrT5lH6Q0zE13aKWKthKaWshbTUbDEjO22KLHv9+7RKPbZTAcs7WxxerRJ3ns4UcxxnByc42dYoBXwQjxUcPklAVMtJhV9KCENOLTX6zwewgSOATRIburUkpV2sQMnxiu0DH11hiM0cGDYkwgRlaeTRPaBiJtZTCc8oCOXn5J3PcHPohoCQZUYHQGr4LWkxCFj++Lj3ohSqnAf/LBUyTeE7Vfw7ug4rtSGQqV4aQgEmZQPo2fCWJ94KNA5KnoKLImGG1IEzMRPJTIUQsEXYX2CktQPi6joWJIwvsT+TUiErPVYv0gFzwdzvmQ9eIcosC6oAGjVDDUjQ7GpFchzOpiBlCwqzwmZjShONUvFTw9CoVy1ebMhOfDeXSSodM2kOGLTawF8QXGdEDluMQipkvemaY1M83myiZ+uINupIgyeKVwAlZrkk4L3WyglGZUjrFqivl8GjvukYoJnCZvcUk/7sVCqGqsUpzSFGWYzwtgXTQnS82hgWNhreSCaUVqDJt94ahL6EmGIaEcF0wninbeZKGZIOU2rhRGhVCOgod49cETNBZmmGk26I0STqzu8LgreNlUyu4lh0tK/FBjbShI2Ug8TSOkMsYMLF2bk6Dx3nPRXIuLOjmdYkhTOUxqGPRGFOLQUykzCwn5FLhmySjVLM0KsydTNnLPzFSb3skRx4YlG5tjstLgZjVZnjBOPe3FjNlpcDPC2I1IlCMxGUOBQ+uWpWHCaFux7T3NnYR9ecZg3tB2DS5xBZfmMDfdoL9RsHFS2PAFDaMZCXSaGXNznmbuGA7hkceFB46WFEaTNh2dRlCsSVSDpgWs5eX7l2m1DYeakDpHw8F0Ydk4uUXZtGxnlpWRZsMBXrHXenaPNZIGQ/iyaU2aneKafTd4XgbK9ddfz2c/+1m++MUvMjU1NeGMTE9P02w2mZ6e5j3veQ8f/vCHmZubo9vt8oEPfICDBw/yhje8AYC3vOUtXHHFFbzrXe/ij//4jzl+/Di/+7u/y/XXX3/WMM6zQmJYJqYTh0wVh+l73LoL/IxAvj/lktXgS0UxCkJTxgjaqFgjI4qZZZr0IoVqR9KqFdQApB8yflQaQhgeQh2daOSElH8haSvae0HPAShwYbdVGUfKAtMKOmoyoahTFxT0GKycmlxU9LhYoKdwA3AjhcnBNYV0sdoJCjKOvJNI8gVQyiMuejCiiqzWIFrQiUIyQYymygATTQhHKQk1exKCoTIIXxiMM5CUUJcnlyDvHwgBwa0c+1yRknUmIeSjBXwI7SQtjVIeNzAkiz6Ed1zQd9FtQdLgribeN4kZBx7PyvEn+bcvfnESlw+VYx1VrRZ1+ip8OnGRqJURqc5aDEoUTof4nPLQY8Qjx48R9a7Qorjvm3eER6namsaxevzh+9GBmITHRx6DmpAulQp/D+Cqv5WohhdicUwsZ4IYXWgWiJHhXka3vKgoYxMZEFKloWoqzY8qTFhd/SSsAqf9J0I99fPTXZKnGofgStUXf+qYnOXP4gMb/R4IUvWMp+LsZxN25mbiBcTAiPIkURY/3upoHIVfgunhQx8VeC0hc8wLiejAro48kcozpOLzpCPRtZpLKiJH+K8JfI/EoSNP5/R7Jaqy7uPzHgsQogTB4GIxQCeKMqY8a0ImjZ54e+OzETOPTDT8nAtVrEsRnAt1Z3ysmaOVwiuNU2oSlnZVVpQihqmCxyZweyKHv5prfBibKoytTAg7iYBzZayv1MBKCFX50pE6jy9t4KukGq3aNGemMCfWGfT6tLJ50EFPyrqKGBcyupyHkTOUJsclTZQJnlPnFEViMXpIRzlmsQiabRFK72m2p0NIylpwQQl25DSjUpCekBlhVCiKtEEhGlEZTyr4Rm/MyUM9ju6U7F8QOlNgvTAshbKXoAeOjZ0NdHeKsvCsecUdJyy5KPJuxq6xx657tBJKF8ZPaSETS3voUBuWaacRrWmurpLIFBddfAFGYH1jk9KWrNuSQz1LPqeZMQV4obBCIxMSb2maFovz0+ycGIexloydvmNHW9JE82BZcmhLkUw7ilJzYjRm5D1oR1EKYxs2DDNlwlKeks0oZnSD492EtByyP9HszxXdjufElqMcaxwwnaT01ZisabDakXeE1oJn31SX+1b7DAaetPT4viXXBisF7YGwnCjWDt/L4cP3kMuYGSssKMeeZk7qDWtbjmNNzaFtR19nTGvNvhQuS4QDr7iUgT9JYY7Rt/K0aejZ8LwMlE996lMA/OiP/ugZn3/605/m3e9+NwB/8id/gtaad7zjHWcItVUwxnDjjTfyvve9j4MHD9Jut7nuuuv4gz/4g+fTlYBqhotxHcGjxh5/0iMjorrlxHMawjg+iIOVZXhBTRLe5/DCBu2RbHfwDIgieCNGgvQVWBUX57hoFoAPOiEoTVkKpNC5AMycgkQFAmE1KDp2taEg1cHFXWUfxN1k8MFKUFGNuztJDQoNA4ffFqRUlANIupDNaUzDI6lHFdHMMQJaTQiCOKBUqCy4n3WukEIQE/RdJIl/F93dCqBQ0aPj0WnsY1SRxYTvIgfVCIaOQoVwUhnXlkwhiQSxOAVkCjUMsXHbl2AspQqxGld4Gl3C01hEsass1h9Kwj1V0SVdbbYlOsHDkhOJiZNV+dSzIdU9JezGVPC5x2dCYh2Y2DIaMJMCeFHhznNKi6VaocI6EMbdoyYPWUVePGP1l1N1XohegXBnHapy8is/sShOBSdOe5Wr1NGwtE6+LYQlqmpQ8btQZ96GidPkKVPD02aKOI5POVT1Z9KPifFw6r6dutyqD1Vhgmc82TN+qirDLhbnRMBogxgTPXxqYkxMrjsaLZP9mVKkafDoOO/i8IRiftqHzYk/VbBmcmbUqedIi6JSeg0k1TBGEkmzwRAjvr+VNyJ6MJ3CecIi74XSeZy1gb8FJFqHrB5dKWt6lEoiQVSwzmNd0KFx3iLOBVKxD1wVp06NlxePE8ERSMdKqh1ZyIQRd1rYOIZ6DGE+1EqHNObKg0UJZYFKM9L2bODLqRIaU1gPw9EO6VSG9pAmGc1mg2JchFpJtgxq1i5I9Qf721OWnlHhGRZjinKMVSU4h7bgtKeZeK5sGDZNweaoYNNDkWa0Owkuy+j3x4x7JSSKpHBMWU975OjqEqsEU45xFrbI6ZmcsUk4OhQOPT7i0qOOy3LDnmlNPg3GWvKRYKxibauP+JzZqVme3NnhX08O2fgmXL6iWJqDVg4+EUZAYTVNhCuahsW0RaKFvi4pxaIaBabYojdyOLHMLXbob/T4z9UR24VwyR5Nt2PYyhxrBYydZ9Qv2LjvOFeNPYtZimp2OC4DbndjVp3hCeW4dcUyNpBNK9aU0M80vvTsmsp51bTmKjOks1mQjBocaM+xNRYe2R6Sygi1YBgrOLExJpnSzO5J2TpZ4EQovGZ94DmyoUglYWZWcdmBBba3WhxbHbFxsofraVwhZHmDPBmzuFszPT1kpAz5FmyulexfMrR7I3o7njXnebSRsjJOEJWwO/G8rKXYZcf0Dz+CmknYoGCUZs80FZwVzzvE81xoNBp88pOf5JOf/OQzttm3bx9f+tKXns+pz47oPakKnGoPsu5xvbAQx40EEHlsQDlWVJIqJjnNcNDBW5AsaJJd8TMngbfRD4szRsJCryUYJ1V6sQ6qmk4pmouKZF4gCws8pQQDIRJWJ7rfiYpx+bgYxhVFVX9TuZ5NCNEwdkg/nL/sCSZVyBRkCx4xhEXdckrLpJq8Kw99IsiYsLA04i5bC5KF/ug4p4kOE6CMw86VhNBeCFwQF70VuQSSbSuOhSGkAerYZx1DTL7qjwQCrQQDMdsDJnO4nkY3Y0XoaB356OHBSMwuCgtBt93i8stfwaDfp7AlpbWU4wLnXBT+8sG445QXB+I0LqcvvWex4icL7MTtFHQmIHiSqq17NA+qtS3c5NOMn+rbqwFA0Jh41rB8agkKuV4FzpDIqcV20hU57bf4jGip+n7K66ZO+/309yJ84enf+NQrPv33p3s3TrNqzoKntpenHZHTfjndfvluJqcsz2PmD1HRlWDIErR0ghKrnhDikeAJ8V5iqLHygATZAGUSKkUTjQqy506wRH5aHJ3KDxOHNHY1hFGcizou0WhAQu0fEyzXYMhrkChuJ07hvMcRUqRtUWLL4KIU57Gq8gAxqVGktSFJEozRIcTjPdY5RFwwQlxF0A2hOImVoX189h2C9R7tQ0kACJlSJnrnvAoGdTCk1SmuWXxOlNIoY1F2QO4dWZJT+jFOO6wHLTZsyGyO8yNU2kF0TjEa4vs7wYNUuDAXVlmU3jO2jtHIUw76YC1eLBqLSDC8yDwvzxS7LpqizAqOF2OObBU8sXmEbd3G+iQUIkwMU1rz8laDZTfgonaL5qJw1I64/2TBoV7Juhuz4RQ7YrAYLvGaKTIWtDDXtbCseHIIrSMKv+FxmQc75oRyrGaGO4fCE09oOisl3VSRZxqdeBotaLicixPHXufZt6/J0qvmWJUd7ntkm8dXT7J+wmJbTeY6U5jpDoNxzv+3us19q5Z9C4KehZ1OE2nC6OSYl7uMNy63mC4d3ekuh0Yltplx8/qY44XhG2vCcGyZnXWUuWKgIWmnTE0rupljYVrRzBzjYUG/NWRjYDl2csxUx3FkB7YLS1MSLtqnMErTUU1a2yVqrDmxA40RlGvC7llI3DEO7Oly1aWX8tWvPsSgVyJoEtPCpR4z40gaFrxHJylTDc3yRZp8x8E6HPYpR7ZhXUDpkplMuLBraOIY2g12XMqOVhwdJjSfewqY4PyuxSOn9poIqG2HXwvZLacbJ0oRdJgsjEfgfQjJKB1pIVogCQJn2R4VduxOYOgD78RFfZRxVHmNhfEAMGFNLKwmnRGyJcE3oieicCFsoghGRKJDNpBisuhM9EmqiduFfWcVJycx4fzDQI61vXBu1SEUK2zIROE1GDQhTEVZZfOE82kDvgDVBCmjtZZ5fMbk5AqiFRfcLmJC9tIkdTmSdZVS0FDQDBwVFcMySlRMvQi8FSWEhdv4KD7n8WOFLwzplMaPBbsdhNpUA1A+TJJp8GSpSgU84gd+4Af41F/8BRsbG5w4cYKVlRVWV1fZ3Nyk3+8zLooQr/8uDOmnPEjx37Mt1N9LPJuRcLY+PfWz5zIyzk8szXcAcF6wFe/be8YuZMbkWUKepTE9OHoB5HSPUzSJfKwGblQUXgvvhFaA0UFjxcbaOzE1uPKTVXyS8H46lFiwgrWCcw4TlV09BildtdYHqXjvsGU0Zb3DOotzoX9JtB2t91EwzuHLIFaHEZp5Sq4SfJA+ipyTwKOxNnBNRPvwvnsJei4+1DNy3lO64KUxwsRbCEGkzSlC5WeJCsJaMC6EsEP155DurJ0F5VCZRUwBKMSOwp3xDUzpMUlKozWDUYr+xhpp2kWSHClKxGkK57Gx6rX4AjcukfEI7wtAEG/xvgjXIpq2LVjO+sxcVPKKrmdzIBw+5nns+DaHd+BETzMapVyYphy8cB/J2lHmmwO63QGX7BIuXfYcWlc8uuZ4uA8nB45cNBcvLHFBomjrDTJKuguwsChcdKli+XHPI2vCt78zZE00fa95uHQ8WgrNQYb2JalyTOWGTuq4GMdCZkh0iR+OUKMBey8RGm1H/vCYobM8sFGyeryg2W7RS3LuGxvSsbA4dnQ2E4q2ZbvTIEsd865gT0toDC2uP2bfXM7W7BR3bo04aZo80u9R7igWThjSJowaYFqO7uwM3sK6jNi9KxTL3C5Ljq4OGZMw7nseQFhODN0SXj7fYWt7m6Qw7DEtjtoBOzuODeNZnoXZaUcngVT3WH3iCGZYMCPCrtlZeiiOFI6VbUuvsAwxDPqetna4zNLYo5lf0DQ32gyPlDhvyMoh7SnIOwUzC5qZ3GBsmzseH/CYJDwfpul5baCouM1RXlADwZ0IHBFfLfpVuxi2GI8FW4TdvDEh7U4ZIBF0U5PsVpBFL8bIB52PGL/GhglHe7Dj6LmJC2hZgGoKzSVBNWMRMOuCvgdxoTUq+uNDh5QJO0CJWTth+xZY+9VuWqJ8vxrF+kFDsANCRs4MpF0ilUEC8S1RFZUhcP2cCjVwsmBkSU4I1wyDAUFK8FC4aBCZsPNXUf688sSQEDxGSeioVEZQHmZ7sdEAM1DVL1FGgkeFcP+8hP65PmA8uqnD92sfNGA0wdARH7xL0RPkT/MytdttDhw4wObmJtPT03Q6HTqdDhsbG/T7fYoieFOqBafG+YlMlzGsU0kIRC6FaMrSgnEhSCEhC8a5MhBn40YECdk/1XFxwQjx4kl0SK12MVxSVUcWQqbOKf+axLTnsGsUZ3HW4W2UIVCKIIsfeSaxDpHzwVDw0ePifRk5M4HPkqiQQeMkiKt58YBDSxCBxDusVjg0Fo/GBi0ifBDVw+Odxbu4u/IO8SVeCkRcDA8Hj081z4X+hXMGAm9Qnw16LYHgLkSvh1Yk3pFkoDDkmaIoXAjpNJsoHQTbGq2ENPEkrYT+eo980APtUM4GrpT3+Oi3wgmuLCkoKN0YZS06VrMOTsGMhhf0zgjZ8GSpZtcU5Iljoa05sGN4fAWObBbs0oq03CRVIwwFGkeWCQuLQtqC+VyY3zJ8Z0tRlCkdo8J0Yjx5S5F1wTaEmVTYn0AyZZlppyxtCt9csxza1IxMg1JnlL4E6xhmCSeUougNeKVKaCwY8uYOo/4Au6PoNGHfhaEg4oZWPD5WbCjFiWHBuk4pUs228uxKgpzEyokhXQxZrti1lJINS8ZSwAzMWEWrcKiyYL70XFgIu3NH6RRrY9gsPEcOrTPdUXQ7ICmYlufR3phBJ6NlMrxKGOewMS5oWIvb6dNRnmG/T2tYsmQajGyfxUXDxRdpZmcsaeIpRpaHHjjJ9gnHohdaox5JlnFEwZGeY6rUWGA8dKQJ9CyYXOFzoWgMIW9gyoRcxujM0c88rY5h6CyPDkc8tO1ZyRyveB5zwXltoFR8DT302BUXatqcllIMQd8ERahUPAoLXVKpJpkgOGZSTb6kUJ0Yahm7kLESqxKLjdofGvyQkAUTwy/Oh51TcxHo6kA2jRk4yoWF20dVpEDmVHHnV4WJqxCPBDntKl6VRCPG+ciBgWJLUfQFM6vIF5nw84LxRFjkTTRKYvZltdBLoQNfxEa3dhJ4IDKpzR6NqWiMhRulg3GiBZVE77CWkI0Rs3uCMRK9Qi54ohSRYFuFIioOpwK7pjC5QrfD2Ckv6HYwjlRcXFQSwlZeMdklQ8jYSJKERqNBu91mZmYG7z15njMajSjLcqKlURso5y/6W6uoGAWVmHKrtcYXJUpDI0lOLe4xm0dB8CRG7oXE3yXqhQQyajBYrAvUsBASDF47T/DYVCE8o0ERMmggeEgSo6JhE+vbENL0K46JF49WfrJx8s7jERKtA/kVhVYOpyFRisR7vPIUyuEVZCYhTRK8SUIWkAuhRWOS4LFBUC4UXHTKgw6h0NhFvI+FGaMgnQolnUOGjA9GnhOL9yWJC7pFwWEbYstCmH+8SMjGMYokTVFphjGdSVmCUkEWuVbNbpu8bfG2H951a7ESPDIiFomlRGw5ppQC7wqwjjJqxFBYupLiGyl2nDKyI9KxDZtG0bQzwTfH+LmE1Gj0yLG5vcqiETDB65QYRVMpylQYNz1zFgaSstHXnBxtcvF0hmp7bEyISBsacY5GCxZmFIJjkMNODuPM8GQ/YbPwjFGIThgUPqgXq5RHh2N+IGvRmtM05jyF85Rj0OLoTinm5jWHj2n6Ow5nhbQYI1pR6Iy1ocNrizE5pXNsaU2vZbhwHma7hr6xtE/26RhHp1T80FTC/95S7GoaZHae5lqfrfUB/Z7wmFVIodkSIS0ch3qwXXqyVoNmY4Z2UzO1vsorZ1OmVUk2oygXhNGacHhsyXNNu53i/JDtoWLYU6yftKz1oN3W7F3QJFsDrB2RNwzHh4a+L2k6aAw1JlMMBoLVjqFoVnuAhylKukkCRlgpheG2ZUuEB7cdfd0g5/klwpzXBoo4YOSxKx7XP2WcxHkGExdV76EcBk+BSUIIRyTs+I0BMy3omRCFltJBEUNGqhIlI+zMhiEDyCMYEzw11kE+rzBzKuo6gLIebAybVHT5ikFfkWI5zVEfPSmVCxqtkChCRymogcaNhPEG6KbCzELaEaLgQ/CemJjayylCnJKgd4IjEGRjnRwawTATU03oBGPNEy40BJwnoalQCTn2VkVvS+UNkmDsUIWyYsGcuPcNM2AeybiFohyGe6VbQUAPozAtB7HwnIrnFB12zpVCKJwyUPI8Z2pqCoAsy5ienmY8Hp/hPTm9zH1trJxfeOLQOKizGjNJty2tw3pHI89D1fNYmVcrHYzxKG4mSsdsLSbS6io+QEoJ1odwiy2DZ8KYWDHbB89CJdLmBMS7QGwVF4m7hiw1QZCRkDkzGI3Y6vUZjUuyNKHdyMkSg9FhQVU6i8ZWgo7EMqUgSRTKebzXaBcyMhomJU9TrNI4Ae1iWnISpP1L6yjGRSDNSomIQ4tQloayTChdMSHFehdI2J5Arg16sh68wxeOwju0je9LCJQRqikHJWfnBZcaklRTuhCeThCKckxTa5w2qGaXVqvLfKvPZn9EUbowF0nQLVBecH7MWEYo50i9wzlHSSAAi7OUdoSXnG0Hu/IGzTRkLLmhw3uFGiuMU7SMYzr39KRkgMc1G7QXWjSnRwhFeBaMJ9OKlhEaGpQxPDlyHBoPueiSaWYW+4jrQwFKNBmKhvK0UujmwmwmdIwDX2JLYexUWCRcMDY3koS7vWJudYiZMVzU1WDHjLWiH7NCW6llTlty63FjxbJY1seaHXqYTs6wmVJYhbcpj46H/Md3Cn50b0KWFux4GBaG2TTBDhOuXNLsy3u0m57msuN/2zPDsfs83xoYDvcKjm8JD63DnjlItTA3gL63FHqEsiX7pjS7O46m8YhyzFycMp7J4QmPcoqdkXB4TbOxZcIm33vSaY2xwsxujUvG5HnOrErZfsjREljYgblxyrRpMR6UrNoBJ5Tm6LbQLCyLBTQaOc45jvQFrT3bKI4MFE1jmZfh8wpGn9cGiho73DGH7zHhccRkh0lKMYQQTFEEZVV12q7fGNAtFSoMa4O2QRJffBADC8qzgVfhBwoZByeBjl4RWyqSLqRLKtSMQYcFuQh9CO+pCoZAhYoYJ5UhUc2mnipLRCphq9KhR+C2PKMnQ5gkmYHGrsrbEIyvUNwwSG6LU6Ggnz01aVOCz2MoKFeB7JsRS75Hrkok+2lhoo/gVEgPFh1Ti72E4oOVZ0adxnxQwd2IIm59iWXWmWi5SA/cGLJZBQ0JYatcoBnviwiSSQhhIdGwg4pMpJSaeFCUUqRpSqvVoigKrLW19+T7BFtrTwKgkwRbOsrS4p2Q5hlJllFxTCodEBfT1aRSa44psxNDNRKNvYSwTuCX2PDuGR3KMrhq4pAJd91aT1mUOBfS14z2JCYYHtZaSmvpD/tsbW1QjAsaaUIm0+TtFnmWkqR58NIoUCqJmyfBAGmShGwiSUh8FjyBxpCmCSUq7hGEzCiS4PINmT2NFFtavPOE2KqjLCxFUlC6wC1xpceXIR2/9BanQugl3JSgQzS2JcqXQVbfJEFN14KObtmCgqRUaBMr+tohLknBG1xp8U0DSU6aJKTFDm6UUPoibOzIgiaK9zg3RqRAxKOj3AIEDRZTjhjFsNN3ioJiMGJ3pmkqRZIEjpA4GEuCFYc2CpUa1goYDUeMhgkXktK0wVgcFlCIoiChdBm9EfTLlOFqn7Fa542NjPk8JfMlugGuULgySCEkGqZzxXzm6OgRPaUpJMX6AkFjkhSvE55MDLcVnuFjBZeue3YvGJQWxij6WuML4UIDWQZzKmPXcpMjusc314TjqWXNONZMhnWKkzrlpsf6bG4a9sxokkzYajikDbo/Jus0WdjXoDlVUKQ7zJgGiys5l1+wj//3Ww+QJwkyLpldEV42p2lIycPDbR7oK/xUwiiHbRxNbRAj+IUWfclYvX8dr4S1oeVYT2h0YLELsy3F7nlNVoLNPe094JqaYs2TGce+tuFAqWg7hUGx5Vt8Z8vxpAK1XfIKhH3taZjq8vjgMI9axTBJQDmML3iZFpZMws7zmAvOawNl43CbpBEWtqCSGDN3PJg0VDIVrxj0wZVRzt6GiUsnQTo9bcKgVLG6sAcXEzlHgI0r9ljhRxK4JxoSEVwJzkDe1gwLhSrjUj2OHphqwU71RAQOpULtIKWoKq4qVAjjCKEooCamFQfuid8W/LpiZw2yecUo9VgH9MIi7C0TJUxlQm0eZYIhEU6jgrHkJIhXIZCoUDisCPLZQZBNR80XYEeCronTqCTGyyrS64iQhVS5qSoekFQholNeF3aC21xJkPF365otBdKBoiDwUbSgR8HrglOgQgaEghAuA3qDFs5ZtjbXJzVbrLXYoCIV3PGJnmhK1PbJ+Q1jNP1+j+PHjuI9uNLSzDOcTSiGgVgaeB0h26W0gU+BCkZLlcLrvIvS8EGPoyLSKohk6vCsWOuDgaJCqCPopQi2KBkOR4H3osBoTZYmGKURCYRUVQzppgJJEF8zfoRyBm8Fr0L2TXBMmqg4XYRsrMREAz++S7F2j1UaK8FAURD5HCoW+wsGl/eOorCoWLciZLBZvLd470IKNZH0Ky4YY75A+/C+eFViVIkoG/ZGRImGKiirPIWU6LIMAnSAlU2UbZHolK2tNdqqjTKB7IsYvLchRdp5tLagBCsFoi3KxqrMOmwytCiMUpg0C+XFUPSmFnhkMObJzTG5FpqZ0GmlpISxLZVnmMCIhJ42rI0sR3c8C4fhgtk2jdSjtGdkFOtJwrYxuHYKTcVqkfC1YckD3xBevZSxtEtodQTJwq0fuYSBK1EGulPCnhISk7FVJhS+RPImohKchSSz9JtT3G9Ljm4NWBgQMru0Jm0r2k3NBc2EC6ammB5BO93h8qvmeJkUfP1wycNFhgzDFOtbKTudKe7aHvD4EU8ngWw2IekYbMvy6E7GZdrQynqk3TZla4mX/VCT8WrKrpkZ5mc0UxRclQ953WyK3QajFE+eLCi9YXUoPAisi5A3PL1xwndWPEmrw5LRdJWn14BNa1hDaGeexlTCrukOq9ubTDdz+mLYFM2+PTkH5gytZAwZWJ0ys/cA6488ysAJB9qOyxPD8tQcZmaek49v8gSek06YM8K+luXVc7CQdvn683ChKDkPt5tbW1vMzMzwwf/rneR5BpwWLon/nn4PnukC1VMbno7v4q6EkM1zt/ufQuzH6dIaL9Q5z4B6yuffTR+eOhgyoQic+X3P8V0iChE9kUg/Wz/Pu4e4xjNCIomskr+vPCbfwzM+48dPPfLUXjzTq3LWxk/9g2ebtJ4NZznp2a/g2V+QZ3udn/GOn/Wa5OmbgqfOF8+AyRxabXie5XTPOo+fds6q3Rnt4y+nafE9Y3+qa3nO8z3DMfWUdlVG5iRhU85y7+VUv05/HPTpXxgCjZHwLaeEOKEq8wnEW3nauas2p1/b6Z+d0fezXJxU/XvaH4QN7pnXfSpCUI1odaz67lFp+fP//plJssOz4bw0UB577DEOHDjwYnejRo0aNWrUqPFfwBNPPHFGLb+z4bwM8czNzQFw+PDh57TAapw72N7e5qKLLuKJJ56g2+2+2N2p8V2gHrPzE/W4nX94qYyZiLCzs8OePXues+15aaDoyH6dnp7+vh7I71d0u9163M4z1GN2fqIet/MPL4Ux+24dC/q5m9SoUaNGjRo1arywqA2UGjVq1KhRo8Y5h/PSQMnznN///d8nz5+fKl2NFxf1uJ1/qMfs/EQ9bucf6jF7Os7LLJ4aNWrUqFGjxvc3zksPSo0aNWrUqFHj+xu1gVKjRo0aNWrUOOdQGyg1atSoUaNGjXMOtYFSo0aNGjVq1DjnUBsoNWrUqFGjRo1zDuelgfLJT36Siy++mEajwetf/3puv/32F7tLL1l8/OMf54d+6IeYmppicXGRn/qpn+LBBx88o81oNOL6669nfn6eTqfDO97xDlZWVs5oc/jwYd7+9rfTarVYXFzkIx/5SKhWXON7jk984hMopfjQhz40+awes3MTR48e5ed//ueZn5+n2Wxy1VVXceedd06Oiwi/93u/x+7du2k2m1xzzTU8/PDDZ3zH+vo61157Ld1ul5mZGd7znvfQ6/Ve6Et5ScA5x8c+9jH2799Ps9nkwIED/OEf/iGnJ8/WY/YskPMMn/vc5yTLMvnrv/5ruffee+WXfumXZGZmRlZWVl7srr0k8da3vlU+/elPyz333CN33323/PiP/7js3btXer3epM173/teueiii+Tmm2+WO++8U97whjfIG9/4xslxa61ceeWVcs0118g3v/lN+dKXviQLCwvyW7/1Wy/GJb2kcPvtt8vFF18sr3rVq+SDH/zg5PN6zM49rK+vy759++Td73633HbbbfLYY4/Jv/3bv8kjjzwyafOJT3xCpqen5R//8R/lW9/6lvzET/yE7N+/X4bD4aTNj/3Yj8mrX/1q+frXvy5f+9rX5NJLL5V3vvOdL8Ylfd/jhhtukPn5ebnxxhvl0KFD8vnPf146nY786Z/+6aRNPWbPjPPOQHnd614n119//eR355zs2bNHPv7xj7+IvapRYXV1VQD56le/KiIim5ubkqapfP7zn5+0uf/++wWQW2+9VUREvvSlL4nWWo4fPz5p86lPfUq63a6Mx+MX9gJeQtjZ2ZHLLrtMbrrpJvmRH/mRiYFSj9m5id/8zd+UH/7hH37G4957WV5elv/23/7b5LPNzU3J81z+7u/+TkRE7rvvPgHkjjvumLT5l3/5F1FKydGjR793nX+J4u1vf7v84i/+4hmf/czP/Ixce+21IlKP2XPhvArxFEXBXXfdxTXXXDP5TGvNNddcw6233voi9qxGha2tLeBUxem77rqLsizPGLPLL7+cvXv3Tsbs1ltv5aqrrmJpaWnS5q1vfSvb29vce++9L2DvX1q4/vrrefvb337G2EA9Zucq/umf/omrr76an/3Zn2VxcZHXvOY1/NVf/dXk+KFDhzh+/PgZ4zY9Pc3rX//6M8ZtZmaGq6++etLmmmuuQWvNbbfd9sJdzEsEb3zjG7n55pt56KGHAPjWt77FLbfcwtve9jagHrPnwnlVzfjkyZM4586YFAGWlpZ44IEHXqRe1ajgvedDH/oQb3rTm7jyyisBOH78OFmWMTMzc0bbpaUljh8/PmlztjGtjtX4X4/Pfe5zfOMb3+COO+542rF6zM5NPPbYY3zqU5/iwx/+ML/927/NHXfcwa/+6q+SZRnXXXfd5L6fbVxOH7fFxcUzjidJwtzcXD1u3wN89KMfZXt7m8svvxxjDM45brjhBq699lqAesyeA+eVgVLj3Mb111/PPffcwy233PJid6XGs+CJJ57ggx/8IDfddBONRuPF7k6N7xLee66++mr+6I/+CIDXvOY13HPPPfzFX/wF11133Yvcuxpnw9///d/zmc98hs9+9rO88pWv5O677+ZDH/oQe/bsqcfsu8B5FeJZWFjAGPO0bIKVlRWWl5dfpF7VAHj/+9/PjTfeyL//+79z4YUXTj5fXl6mKAo2NzfPaH/6mC0vL591TKtjNf7X4q677mJ1dZUf/MEfJEkSkiThq1/9Kn/2Z39GkiQsLS3VY3YOYvfu3VxxxRVnfPaKV7yCw4cPA6fu+7PNj8vLy6yurp5x3FrL+vp6PW7fA3zkIx/hox/9KD/3cz/HVVddxbve9S5+7dd+jY9//ONAPWbPhfPKQMmyjNe+9rXcfPPNk8+899x8880cPHjwRezZSxciwvvf/36+8IUv8OUvf5n9+/efcfy1r30taZqeMWYPPvgghw8fnozZwYMH+fa3v33GS3jTTTfR7XafNiHX+J/Hm9/8Zr797W9z9913T36uvvpqrr322sn/6zE79/CmN73paSn8Dz30EPv27QNg//79LC8vnzFu29vb3HbbbWeM2+bmJnfdddekzZe//GW897z+9a9/Aa7ipYXBYIDWZy6zxhi890A9Zs+JF5ul+3zxuc99TvI8l7/5m7+R++67T375l39ZZmZmzsgmqPHC4X3ve59MT0/LV77yFTl27NjkZzAYTNq8973vlb1798qXv/xlufPOO+XgwYNy8ODByfEqZfUtb3mL3H333fKv//qvsmvXrjpl9QXE6Vk8IvWYnYu4/fbbJUkSueGGG+Thhx+Wz3zmM9JqteRv//ZvJ20+8YlPyMzMjHzxi1+U//zP/5Sf/MmfPGvK6mte8xq57bbb5JZbbpHLLrvsJZGy+mLguuuukwsuuGCSZvwP//APsrCwIL/xG78xaVOP2TPjvDNQRET+/M//XPbu3StZlsnrXvc6+frXv/5id+klC+CsP5/+9KcnbYbDofzKr/yKzM7OSqvVkp/+6Z+WY8eOnfE93/nOd+Rtb3ubNJtNWVhYkF//9V+Xsixf4Kt56eKpBko9Zucm/vmf/1muvPJKyfNcLr/8cvnLv/zLM4577+VjH/uYLC0tSZ7n8uY3v1kefPDBM9qsra3JO9/5Tul0OtLtduUXfuEXZGdn54W8jJcMtre35YMf/KDs3btXGo2GXHLJJfI7v/M7Z6Ti12P2zFAip0na1ahRo0aNGjVqnAM4rzgoNWrUqFGjRo2XBmoDpUaNGjVq1KhxzqE2UGrUqFGjRo0a5xxqA6VGjRo1atSocc6hNlBq1KhRo0aNGuccagOlRo0aNWrUqHHOoTZQatSoUaNGjRrnHGoDpUaNGjVq1KhxzqE2UGrUqFGjRo0a5xxqA6VGjRo1atSocc6hNlBq1KhRo0aNGucc/n+3H2sgXwUypgAAAABJRU5ErkJggg==", - "text/plain": [ - "
" + "cell_type": "markdown", + "metadata": { + "id": "vXnB6ETzROvK" + }, + "source": [ + "### Framework Incompatibility\n", + "Practitioners with large codebases written in other frameworks, such as PyTorch, are unable to take advantage of TensorFlow's rich ecosystem of state-of-the-art (SOTA) deployment toolings, as this requires converting their code manually and inaccurately.\n", + "\n", + "[Ivy’s transpiler](https://unify.ai/blog/unifying-with-ivy) allows ML practitioners to dynamically connect libraries, layers and models from different frameworks together. For PyTorch users, the transpiler provides a seamless and accurate way to introduce code written in PyTorch to TensorFlow pipelines.\n", + "\n", + "In this blog post, we’ll go through an example of how the transpiler can be used to convert a model from PyTorch to TensorFlow and train the converted model in TensorFlow." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import numpy as np\n", - "from matplotlib import pyplot as plt\n", - "\n", - "\n", - "def imshow(inp, title=None):\n", - " \"\"\"Display image for Tensor.\"\"\"\n", - " inp = inp.numpy().transpose((1, 2, 0))\n", - " mean = np.array([0.485, 0.456, 0.406])\n", - " std = np.array([0.229, 0.224, 0.225])\n", - " inp = std * inp + mean\n", - " inp = np.clip(inp, 0, 1)\n", - " plt.imshow(inp)\n", - " if title is not None:\n", - " plt.title(title)\n", - " plt.pause(0.001) # pause a bit so that plots are updated\n", - "\n", - "\n", - "# Get a batch of training data\n", - "inputs, classes = next(iter(dataloaders['train']))\n", - "\n", - "# Make a grid from batch\n", - "out = torchvision.utils.make_grid(inputs)\n", - "\n", - "imshow(out, title=[class_names[x] for x in classes])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Load the pre-trained model\n", - "\n", - "We then initialise our ML model through the torchvision API, specifically we’ll be using ResNet18. Note that while we are using a model from the torchvision models API for this demonstration, it would still work with any arbitrary PyTorch model regardless of how it is being loaded. You can load models hosted on different platforms including local models." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ + }, { - "data": { - "text/plain": [ - "ResNet(\n", - " (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n", - " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n", - " (layer1): Sequential(\n", - " (0): BasicBlock(\n", - " (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " (1): BasicBlock(\n", - " (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (layer2): Sequential(\n", - " (0): BasicBlock(\n", - " (conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (downsample): Sequential(\n", - " (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", - " (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (1): BasicBlock(\n", - " (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (layer3): Sequential(\n", - " (0): BasicBlock(\n", - " (conv1): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (downsample): Sequential(\n", - " (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", - " (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (1): BasicBlock(\n", - " (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (layer4): Sequential(\n", - " (0): BasicBlock(\n", - " (conv1): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (downsample): Sequential(\n", - " (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", - " (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (1): BasicBlock(\n", - " (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " (relu): ReLU(inplace=True)\n", - " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", - " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", - " )\n", - " )\n", - " (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))\n", - " (fc): Linear(in_features=512, out_features=1000, bias=True)\n", - ")" + "cell_type": "markdown", + "metadata": { + "id": "vFqmCKCXROvL" + }, + "source": [ + "### Transpiling a PyTorch model to TensorFlow\n", + "\n", + "#### About the transpiled model\n", + "To illustrate a typical transpilation workflow, we’ll be converting a pre-trained ResNet model from PyTorch to TensorFlow, and using the transpiled model to run inference.\n", + "\n", + "ResNet owes its name to its residual blocks with skip connections that enable the model to be extremely deep. Even though including skip connections is a common idea in the community now, it was a revolutionary architectural choice and allowed ResNet to reach up to 152 layers with no vanishing or exploding gradient problems during training.\n", + "\n", + "Architecturally, a ResNet block is similar to a ConvNext block but differs in terms of the specific convolutional layers used, grouped convolution, normalization, activation function, and downsampling. Going through the details of the models is outside the scope of this demo, interested readers might want to go through the [paper](https://arxiv.org/pdf/1512.03385)." ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model = torchvision.models.resnet18(weights='IMAGENET1K_V1')\n", - "model" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Converting the model from TensorFlow to PyTorch\n", - "\n", - "With the model loaded, we can run the transpilation to TensorFlow eagerly. As we explain in our docs, [eager transpilation](https://unify.ai/docs/ivy/demos/learn_the_basics/05_lazy_vs_eager.html) involves manually providing dummy input arguments (`tf.ones(4, 3, 224, 224)` in our example) to use when tracing computational graphs." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:root:Native Numpy does not support GPU placement, consider using Jax instead\n" - ] - } - ], - "source": [ - "transpiled_model = ivy.transpile(model, source=\"torch\", to=\"tensorflow\", args=(inputs,))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The transpiled graph can be used with any deep learning framework as backend and, in this case, adding the `to='tensorflow'` flag sets TensorFlow as the backend framework to use, thereby effectively converting the original PyTorch computational graph into a TensorFlow graph!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Comparing the results\n", - "\n", - "Let’s now try predicting the logits of the same input with the transpiled model" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To compare the logits produced by the original and transpiled models at a more granular level, let’s try an `allclose`" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "source": [ + "#### Installation\n", + "\n", + "Since we want the packages to be available after installing, after running the first cell, the notebook will automatically restart.\n", + "\n", + "You can then do Runtime -> Run all after the notebook has restarted, to run all of the cells.\n", + "\n", + "Make sure you run this demo with GPU enabled!" + ], + "metadata": { + "id": "g-B32lj6RVWy" + } + }, { - "data": { - "text/plain": [ - "True" + "cell_type": "code", + "source": [ + "!pip install -q ivy\n", + "\n", + "!python3 -m pip install torchvision\n", + "!python3 -m pip install astor\n", + "\n", + "exit()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "8eDu_mcjRbVu", + "outputId": "42c7a274-bdfd-4817-a7ff-c281f4c9f27a" + }, + "execution_count": 8, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (0.18.0+cu121)\n", + "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from torchvision) (1.25.2)\n", + "Requirement already satisfied: torch==2.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision) (2.3.0+cu121)\n", + "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision) (9.4.0)\n", + "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (3.15.3)\n", + 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already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (12.1.105)\n", + "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (8.9.2.26)\n", + "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (12.1.3.1)\n", + "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (11.0.2.54)\n", + "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (10.3.2.106)\n", + "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (11.4.5.107)\n", + "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (12.1.0.106)\n", + "Requirement already satisfied: nvidia-nccl-cu12==2.20.5 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (2.20.5)\n", + "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (12.1.105)\n", + "Requirement already satisfied: triton==2.3.0 in /usr/local/lib/python3.10/dist-packages (from torch==2.3.0->torchvision) (2.3.0)\n", + "Requirement already satisfied: nvidia-nvjitlink-cu12 in /usr/local/lib/python3.10/dist-packages (from nvidia-cusolver-cu12==11.4.5.107->torch==2.3.0->torchvision) (12.5.40)\n", + "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch==2.3.0->torchvision) (2.1.5)\n", + "Requirement already satisfied: mpmath<1.4.0,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch==2.3.0->torchvision) (1.3.0)\n", + "Collecting astor\n", + " Downloading astor-0.8.1-py2.py3-none-any.whl (27 kB)\n", + "Installing collected packages: astor\n", + "Successfully installed astor-0.8.1\n" + ] + } ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.eval()\n", - "logits = model(inputs)\n", - "logits_np = logits.detach().numpy()\n", - "\n", - "logits_transpiled = transpiled_model(tf.convert_to_tensor(inputs.numpy()), training=False)\n", - "logits_transpiled_np = logits_transpiled.numpy()\n", - "\n", - "np.allclose(logits_np, logits_transpiled_np, atol=1e-4)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The logits produced by the transpiled model at inference time are close to the ones produced by the original model, the logits are indeed consistent!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Fine-tuning the transpiled model\n", - "\n", - "One of the key benefits of using ivy’s transpiler is that the transpiled model is also trainable. As a result, we can also further train the transpiled model if required. Here’s an example of fine-tuning the transpiled model with a few images sampled from ImageNet using TensorFlow.\n", - "\n", - "Let’s start by writing a general function to train a model." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "import time\n", - "import tensorflow as tf\n", - "\n", - "\n", - "def train_model(model, epochs, train_dataset, val_dataset, optimizer, loss_fn):\n", - " # Prepare the metrics.\n", - " train_acc_metric = tf.keras.metrics.SparseCategoricalAccuracy()\n", - " val_acc_metric = tf.keras.metrics.SparseCategoricalAccuracy()\n", - "\n", - " for epoch in range(epochs):\n", - " print(\"\\nStart of epoch %d\" % (epoch,))\n", - " start_time = time.time()\n", - "\n", - " # Iterate over the batches of the dataset.\n", - " for step, (x_batch_train, y_batch_train) in enumerate(train_dataset):\n", - "\n", - " x_batch_train = tf.convert_to_tensor(x_batch_train.detach().numpy())\n", - " y_batch_train = tf.convert_to_tensor(y_batch_train.detach().numpy())\n", - "\n", - " with tf.GradientTape() as tape:\n", - " logits = model(x_batch_train, training=True)\n", - " loss_value = loss_fn(y_batch_train, logits)\n", - "\n", - " grads = tape.gradient(loss_value, model.trainable_weights)\n", - " optimizer.apply_gradients(zip(grads, model.trainable_weights))\n", - "\n", - " # Update training metric.\n", - " train_acc_metric.update_state(y_batch_train, logits)\n", - "\n", - " # Log every 20 batches.\n", - " if step % 20 == 0:\n", - " print(\n", - " \"Training loss (for one batch) at step %d: %.4f\"\n", - " % (step, float(loss_value))\n", - " )\n", - " print(\"Seen so far: %d samples\" % ((step + 1) * 4))\n", - "\n", - " # Display metrics at the end of each epoch.\n", - " train_acc = train_acc_metric.result()\n", - " print(\"Training acc over epoch: %.4f\" % (float(train_acc),))\n", - "\n", - " # Reset training metrics at the end of each epoch\n", - " train_acc_metric.reset_states()\n", - "\n", - " # Run a validation loop at the end of each epoch.\n", - " for x_batch_val, y_batch_val in val_dataset:\n", - " x_batch_val = tf.convert_to_tensor(x_batch_val.detach().numpy())\n", - " y_batch_val = tf.convert_to_tensor(y_batch_val.detach().numpy())\n", - "\n", - " val_logits = model(x_batch_val, training=False)\n", - "\n", - " # Update val metrics\n", - " val_acc_metric.update_state(y_batch_val, val_logits)\n", - "\n", - " val_acc = val_acc_metric.result()\n", - " val_acc_metric.reset_states()\n", - " print(\"Validation acc: %.4f\" % (float(val_acc),))\n", - " print(\"Time taken: %.2fs\" % (time.time() - start_time))\n", - " \n", - " return model" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# Instantiate an optimizer to train the model.\n", - "optimizer = tf.keras.optimizers.SGD(learning_rate=1e-3)\n", - "\n", - "# Instantiate a loss function.\n", - "loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)\n", - "\n", - "# Prepare the datasets\n", - "train_dataset = dataloaders[\"train\"]\n", - "val_dataset = dataloaders[\"val\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Start of epoch 0\n", - "Training loss (for one batch) at step 0: 9.3121\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 4.2399\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 2.4778\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 1.6033\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.3730\n", - "Validation acc: 0.1634\n", - "Time taken: 39.59s\n", - "\n", - "Start of epoch 1\n", - "Training loss (for one batch) at step 0: 1.0761\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 2.0626\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 1.3433\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.6616\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.7910\n", - "Validation acc: 0.3529\n", - "Time taken: 39.50s\n", - "\n", - "Start of epoch 2\n", - "Training loss (for one batch) at step 0: 0.2815\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.3439\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.3905\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.1333\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8525\n", - "Validation acc: 0.2745\n", - "Time taken: 38.26s\n", - "\n", - "Start of epoch 3\n", - "Training loss (for one batch) at step 0: 0.0913\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.0851\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.1482\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.6250\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8197\n", - "Validation acc: 0.3464\n", - "Time taken: 38.24s\n", - "\n", - "Start of epoch 4\n", - "Training loss (for one batch) at step 0: 0.3456\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.8281\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.6437\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.4446\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8402\n", - "Validation acc: 0.3725\n", - "Time taken: 38.19s\n", - "\n", - "Start of epoch 5\n", - "Training loss (for one batch) at step 0: 0.0307\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.0915\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.4379\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.0393\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8197\n", - "Validation acc: 0.4379\n", - "Time taken: 38.38s\n", - "\n", - "Start of epoch 6\n", - "Training loss (for one batch) at step 0: 0.1792\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 1.0138\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.8425\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.1388\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8197\n", - "Validation acc: 0.4314\n", - "Time taken: 38.74s\n", - "\n", - "Start of epoch 7\n", - "Training loss (for one batch) at step 0: 0.0170\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.2789\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.2099\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 1.1670\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8320\n", - "Validation acc: 0.4706\n", - "Time taken: 39.20s\n", - "\n", - "Start of epoch 8\n", - "Training loss (for one batch) at step 0: 0.2829\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.2262\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.3582\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.4215\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8566\n", - "Validation acc: 0.4967\n", - "Time taken: 38.92s\n", - "\n", - "Start of epoch 9\n", - "Training loss (for one batch) at step 0: 0.2506\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.0339\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.5903\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 1.1273\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8689\n", - "Validation acc: 0.4771\n", - "Time taken: 38.93s\n", - "\n", - "Start of epoch 10\n", - "Training loss (for one batch) at step 0: 0.0745\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.0148\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.0130\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.1275\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8975\n", - "Validation acc: 0.5098\n", - "Time taken: 39.82s\n", - "\n", - "Start of epoch 11\n", - "Training loss (for one batch) at step 0: 0.1808\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.3167\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.3353\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.0544\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8607\n", - "Validation acc: 0.5229\n", - "Time taken: 38.37s\n", - "\n", - "Start of epoch 12\n", - "Training loss (for one batch) at step 0: 0.6601\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.2705\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 1.4662\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.0162\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8443\n", - "Validation acc: 0.5229\n", - "Time taken: 39.60s\n", - "\n", - "Start of epoch 13\n", - "Training loss (for one batch) at step 0: 0.2667\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.5686\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.3593\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.0349\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8115\n", - "Validation acc: 0.4902\n", - "Time taken: 40.25s\n", - "\n", - "Start of epoch 14\n", - "Training loss (for one batch) at step 0: 0.0202\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.1907\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.0127\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.0399\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8197\n", - "Validation acc: 0.5033\n", - "Time taken: 38.17s\n", - "\n", - "Start of epoch 15\n", - "Training loss (for one batch) at step 0: 0.5231\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.3243\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.6539\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.7478\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8811\n", - "Validation acc: 0.4575\n", - "Time taken: 38.08s\n", - "\n", - "Start of epoch 16\n", - "Training loss (for one batch) at step 0: 0.0512\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.3078\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.0097\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.5082\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8607\n", - "Validation acc: 0.5033\n", - "Time taken: 40.78s\n", - "\n", - "Start of epoch 17\n", - "Training loss (for one batch) at step 0: 0.0344\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.6654\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.1881\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.1394\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8934\n", - "Validation acc: 0.5163\n", - "Time taken: 42.20s\n", - "\n", - "Start of epoch 18\n", - "Training loss (for one batch) at step 0: 0.0837\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.1806\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.8223\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 1.4363\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8607\n", - "Validation acc: 0.5425\n", - "Time taken: 44.21s\n", - "\n", - "Start of epoch 19\n", - "Training loss (for one batch) at step 0: 0.1178\n", - "Seen so far: 4 samples\n", - "Training loss (for one batch) at step 20: 0.1384\n", - "Seen so far: 84 samples\n", - "Training loss (for one batch) at step 40: 0.1935\n", - "Seen so far: 164 samples\n", - "Training loss (for one batch) at step 60: 0.0257\n", - "Seen so far: 244 samples\n", - "Training acc over epoch: 0.8934\n", - "Validation acc: 0.6078\n", - "Time taken: 43.48s\n" - ] - } - ], - "source": [ - "# Train the model\n", - "transpiled_model = train_model(\n", - " transpiled_model,\n", - " epochs=20,\n", - " train_dataset=train_dataset,\n", - " val_dataset=val_dataset,\n", - " optimizer=optimizer,\n", - " loss_fn=loss_fn,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And that’s it. we’ve successfully been able to train the transpiled model, we can now plug into any TensorFlow workflow!\n", - "\n", - "Let's now visualize the inference of the trained model on some sample images from the validation step" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "def visualize_model(model, num_images=6):\n", - " was_training = tf.keras.backend.learning_phase() == 1\n", - " images_so_far = 0\n", - " fig = plt.figure()\n", - "\n", - " for i, (inputs, labels) in enumerate(dataloaders['val']):\n", - " inputs = tf.convert_to_tensor(inputs.detach().numpy())\n", - " labels = tf.convert_to_tensor(labels.detach().numpy())\n", - "\n", - " outputs = model(inputs, training=False)\n", - " preds = tf.argmax(outputs, 1)\n", - "\n", - " for j in range(inputs.shape[0]):\n", - " images_so_far += 1\n", - " ax = plt.subplot(num_images//2, 2, images_so_far)\n", - " ax.axis('off')\n", - " try:\n", - " ax.set_title(f'predicted: {class_names[preds[j]]}')\n", - " except:\n", - " continue\n", - " imshow(inputs[j])\n", - "\n", - " if images_so_far == num_images:\n", - " model(inputs, training=was_training)\n", - " return\n", - "\n", - " model(inputs, training=was_training)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "metadata": { + "id": "PllpbYzWROvL" + }, + "source": [ + "#### Setting-up the source model\n", + "\n", + "We import the necessary libraries. We’ll mostly use the PyTorch's Torchvision API to load the model, Ivy to transpile it from PyTorch to TensorFlow, and TensorFlow functions to fine-tune the transpiled model." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "wE3i5RnOROvL" + }, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings(\"ignore\")\n", + "import logging\n", + "import tensorflow as tf\n", + "try:\n", + " tf.config.experimental.set_memory_growth(\n", + " tf.config.list_physical_devices(\"GPU\")[0], True\n", + " )\n", + "except:\n", + " pass\n", + "\n", + "# Filter TensorFlow info and warning messages\n", + "tf.get_logger().setLevel(logging.ERROR)\n", + "import os\n", + "import ivy\n", + "ivy.set_default_device(\"gpu:0\")\n", + "import torch\n", + "import torchvision\n", + "from torchvision import datasets, models, transforms\n", + "\n", + "torch.manual_seed(0)\n", + "tf.random.set_seed(0)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vtRuNOoDROvM" + }, + "source": [ + "#### Load the Data\n", + "\n", + "We will use torchvision and torch.utils.data packages for loading the data.\n", + "\n", + "The problem we’re going to solve today is to train a model to classify ants and bees. We have about 120 training images each for ants and bees. There are 75 validation images for each class. Usually, this is a very small dataset to generalize upon, if trained from scratch. Since we are using transfer learning, we should be able to generalize reasonably well.\n", + "\n", + "This dataset is a very small subset of imagenet." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "h9gY1fYYROvM" + }, + "source": [ + "> **Note:** Download the data from [here](https://download.pytorch.org/tutorial/hymenoptera_data.zip) and extract it to the current directory by running the following cell" + ] + }, + { + "cell_type": "code", + "source": [ + "import requests\n", + "import os\n", + "import zipfile\n", + "\n", + "# URL of the zip file you want to download\n", + "url = 'https://download.pytorch.org/tutorial/hymenoptera_data.zip' # Replace with your URL\n", + "\n", + "# Send a GET request to the URL\n", + "response = requests.get(url)\n", + "\n", + "# Check if the request was successful (status code 200)\n", + "if response.status_code == 200:\n", + " # Get the file name from the URL\n", + " filename = os.path.basename(url)\n", + "\n", + " # Specify where you want to save the zip file (current working directory in Colab)\n", + " zip_save_path = os.path.join(os.getcwd(), filename)\n", + "\n", + " # Write the content to the zip file\n", + " with open(zip_save_path, 'wb') as f:\n", + " f.write(response.content)\n", + "\n", + " print(f\"Zip file downloaded successfully as '{filename}' in the current working directory.\")\n", + "\n", + " # Extract the contents of the zip file\n", + " with zipfile.ZipFile(zip_save_path, 'r') as zip_ref:\n", + " zip_ref.extractall(os.getcwd())\n", + "\n", + " print(\"Zip file contents extracted successfully.\")\n", + "\n", + " # Optionally, you can remove the zip file after extraction\n", + " os.remove(zip_save_path)\n", + " print(f\"Zip file '{filename}' deleted.\")\n", + "\n", + "else:\n", + " print(f\"Failed to download zip file from '{url}'. Status code: {response.status_code}\")\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "nGLczy3_SfNo", + "outputId": "5ed3fa89-8a2b-4c22-f5cc-a096b971dd0d" + }, + "execution_count": 2, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Zip file downloaded successfully as 'hymenoptera_data.zip' in the current working directory.\n", + "Zip file contents extracted successfully.\n", + "Zip file 'hymenoptera_data.zip' deleted.\n" + ] + } + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "id": "v4UyNtcvROvM" + }, + "outputs": [], + "source": [ + "# Data augmentation and normalization for training\n", + "# Just normalization for validation\n", + "data_transforms = {\n", + " 'train': transforms.Compose([\n", + " transforms.RandomResizedCrop(224),\n", + " transforms.RandomHorizontalFlip(),\n", + " transforms.ToTensor(),\n", + " transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n", + " ]),\n", + " 'val': transforms.Compose([\n", + " transforms.Resize(256),\n", + " transforms.CenterCrop(224),\n", + " transforms.ToTensor(),\n", + " transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n", + " ]),\n", + "}\n", + "\n", + "data_dir = 'hymenoptera_data'\n", + "\n", + "image_datasets = {\n", + " x: datasets.ImageFolder(\n", + " os.path.join(data_dir, x), data_transforms[x]\n", + " ) for x in ['train', 'val']\n", + "}\n", + "\n", + "dataloaders = {\n", + " x: torch.utils.data.DataLoader(\n", + " image_datasets[x], batch_size=4,\n", + " shuffle=True,\n", + " num_workers=4\n", + " ) for x in ['train', 'val']\n", + "}\n", + "\n", + "dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}\n", + "class_names = image_datasets['train'].classes\n", + "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "AA6QxUwYROvM" + }, + "source": [ + "#### Visualize a few images\n", + "\n", + "We also load an input tensor to be passed as the input for transpilation" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 207 + }, + "id": "qbA_vGFOROvM", + "outputId": "a2fc361a-22d9-4d12-a405-14199ba85c7f" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ], + "source": [ + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "\n", + "\n", + "def imshow(inp, title=None):\n", + " \"\"\"Display image for Tensor.\"\"\"\n", + " inp = inp.numpy().transpose((1, 2, 0))\n", + " mean = np.array([0.485, 0.456, 0.406])\n", + " std = np.array([0.229, 0.224, 0.225])\n", + " inp = std * inp + mean\n", + " inp = np.clip(inp, 0, 1)\n", + " plt.imshow(inp)\n", + " if title is not None:\n", + " plt.title(title)\n", + " plt.pause(0.001) # pause a bit so that plots are updated\n", + "\n", + "\n", + "# Get a batch of training data\n", + "inputs, classes = next(iter(dataloaders['train']))\n", + "\n", + "# Make a grid from batch\n", + "out = torchvision.utils.make_grid(inputs)\n", + "\n", + "imshow(out, title=[class_names[x] for x in classes])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "hD6Gve8tROvM" + }, + "source": [ + "#### Load the pre-trained model\n", + "\n", + "We then initialise our ML model through the torchvision API, specifically we’ll be using ResNet18. Note that while we are using a model from the torchvision models API for this demonstration, it would still work with any arbitrary PyTorch model regardless of how it is being loaded. You can load models hosted on different platforms including local models." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "CAG07Vh1ROvM", + "outputId": "8fe2345c-63a5-4111-e158-f9d39496eeed" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "ResNet(\n", + " (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)\n", + " (layer1): Sequential(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (layer2): Sequential(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (layer3): Sequential(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (layer4): Sequential(\n", + " (0): BasicBlock(\n", + " (conv1): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (downsample): Sequential(\n", + " (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)\n", + " (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (1): BasicBlock(\n", + " (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " (relu): ReLU(inplace=True)\n", + " (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n", + " (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n", + " )\n", + " )\n", + " (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))\n", + " (fc): Linear(in_features=512, out_features=1000, bias=True)\n", + ")" + ] + }, + "metadata": {}, + "execution_count": 5 + } + ], + "source": [ + "model = torchvision.models.resnet18(weights='IMAGENET1K_V1')\n", + "model" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "qoYzh92RROvM" + }, + "source": [ + "#### Converting the model from TensorFlow to PyTorch\n", + "\n", + "With the model loaded, we can run the transpilation to TensorFlow eagerly. As we explain in our docs, [eager transpilation](https://unify.ai/docs/ivy/demos/learn_the_basics/05_lazy_vs_eager.html) involves manually providing dummy input arguments (`tf.ones(4, 3, 224, 224)` in our example) to use when tracing computational graphs." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "dMoQmxeAROvN", + "outputId": "20dc0dc3-76c0-41ff-883f-b4b030f43517" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "WARNING:root:Native Numpy does not support GPU placement, consider using Jax instead\n" + ] + } + ], + "source": [ + "transpiled_model = ivy.transpile(model, source=\"torch\", to=\"tensorflow\", args=(inputs,))" + ] + }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "markdown", + "metadata": { + "id": "FRqYvPD6ROvN" + }, + "source": [ + "The transpiled graph can be used with any deep learning framework as backend and, in this case, adding the `to='tensorflow'` flag sets TensorFlow as the backend framework to use, thereby effectively converting the original PyTorch computational graph into a TensorFlow graph!" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "markdown", + "metadata": { + "id": "MvsGpOqOROvN" + }, + "source": [ + "#### Comparing the results\n", + "\n", + "Let’s now try predicting the logits of the same input with the transpiled model" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "markdown", + "metadata": { + "id": "4GZIyQNCROvN" + }, + "source": [ + "To compare the logits produced by the original and transpiled models at a more granular level, let’s try an `allclose`" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "image/png": 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FRpatFqp+CKZNpPoMgp30rQZz1QiAQ8UEKwGNCAkhaaqCK7hc/TjspPoq4Y6to+tq6FC1qCpOM+L8ucAC58LtBRzONFhVxcVdmBcR8MU0GGImu2y17vbZidIqaBVWxCFqgrHV5F63ZrFefPWTzAQKTQ0qihZ8cRasiGkk1DScwrm/JGK+qtR/bPFufcnfL3Ndvk8lZkmgOqQiSK4q/9xfsBc6VZxzlKJm66U+2JeYu+0tl6rvtp9ZnFZNt332phVc8aatcoEaMYraiTUrYkKhKufaBcxsOzXNYEGCOz/xrgYWJpGCV8H5erNgKq8afBMuJdTfuXM38uLwSP25r9Hv1qTW82d+ztZVwA6oV0HNy7b3IxQVC4pcxm1/Ucq5hqTeZ1HzK52IRYpiGjNrMQG+5HX5PpUq6gVXvXQHZG8PYnuCQNGyLcHNaNU9dc84f4Tb0wtVw9TNQmmqIw72GnWm0QKeWBTnbAOlRp5F1cxoFQ5xem6bt9eIKBklVEk1v8q+V5HzqK6gaJUWJ0JWreaqailzgarf4s6jva22MkhFK7RQ7+8lQueqBtbtv7d74EwrO2pU6Czq9fULL66D6vBXM2tBImkr0AAUnApOPrVm/f/sunShMkfZNjfUB3AOK2DuqW4jHZFzGymYE16cmF+GmVELkS9MVqnv8dSHTql4jjnSxYGTUj8bKOX8oYWXeFlaTZkXc5Lt++y0F4HAFs+Sc82QRYnVAXdbn09NM20da6/2AVVvXdx3VQieC3+MKly+aqXi7BBKDSC2sINWqALAa6E4QcsWbrCDlii2f6p4qTu6jYjrPXmVGhHWw61CfgUwhUsXKq27F8TCcXF2irb4U64PU7Wcmzcv9QiLEKrf5Rw0dROcWChsYfmFL6CihLq1W0F1CEE82RVcdoxkglYIUUv1M6qPIhcPXUVIVXu4omRXELXrEak+mNpDd/UBXwCQJliiFUdSOdcIImJmpoKxqlSH/wK8VOFcsM7vhRpY1M/1W22F/X37/q1W9LwEnDWFRaFssVLT5vU9Wn3ULaxw2esV0FQmCOqkRmhbQbAb63A1ynPnuNRLVb+6ap5EiNUMeLWNcHIRguPMYRcx32LrUmwfhsOTyTQ4cvXTtNjrtvgNmI9Xil5ERBSS2pNoikEf6i4EWqjO9EvMjHOuaiY1E67bZ2v378WZwFbzHlTPted5IOEsei0Vu9pCEl4cUswsbyNKE7IKhqoi3uEzLzN/pZo/qd+rF7tsGqriPPpq0FTbqEcEgjjDRzAB87K9OTmPercq/BxmECFUwdMtTlMM6NTtw5IL03PhqNuJLjVqcgDOGxiYi2kXVwOBeqDr20imx/B2SfgCaKGQK6bkzx3q7R/ARbqlRlZbOEREtwqjwitateVW2KrWkgoZoIgW1F1kFLYYl6qe71lCCXLxvaJyru2LgHfOfLlSKsiqF3tdhUioAsVLostLXpcPKThHK+4irMXRVCTcMKyyfeS2tS8Jad3WxxJ7QFvM6xw/coY4uxou1Udz/t7iTFOY+2/L43BeKMVSR1osT/jfpmReCp2r1FRRUZRsJtA7u9ZqZtEL83cOkhatZsd8JycFxZ1jV4KlUgwf2+JmppGyABQ8zgBKsAgQzjE6X68XqgsgdiBCDYJQxTtnQlkKQWpKiy3QXG9R62GWix9d5rp88NN5tmfRnNvtRijFOSjuPPrxNVqSl5ouwcxe9TVUtyfTfIRtqidsfyYmOFLTFltVv/VnitSHiIOydVrNzEmpGYCts1xPbtatKct45ykU0JriqD7jecZALoR7C21INTtFnaHYVQAsT2ivdvWBmy9n5syJr37VhTAVrX5R3aBUYRlXnamtH7cFlRHBOccoimZn+cua5jKfTs+1lT2py1+XDyls/YptSEw9kUhVy9XXkq3p2t6wQUsvLcbR6oMgW+dYLkxD1dyu+gdb07d9/faoO7WclzM8wL5ThaxybiJ4SZRmD1HMVAukXAhafSrnLkxOffjbw0PVoKYltAqvnGNujnIOYiJbZ3krXPbd6SXm9fy/rRLd/lzk3OnemlCwwyFa70Mq2Cygpf6p5XxfCmrByLmev9z1iiDqngt1bGrW4XLGOVPXWv2Mc6dyi1lV4XHb9IxcREfbE27OMSD1AVU/a5tzzDWykfOrqX5FdfQt+qolOGyFvCLl9UAYRFC/Wwu5mHZrxZFr6LcV3lzvxyMkLah4E6BzfWmfeR7h1qtKWc30eXcuWK4Iuf59C56qXJS/mM9XzVY1xYbH1U3Yxnc196miFDF/UrU68kVJpYAquZRXRKxekdxfEdsEqQ+4iIK/OJHb/JqrTqtu9T3ned6qObZJ5i2EALaT9lkC1SzqS5AqW+aw68WfVZPhTF25Yo9AXc2nqb4ES3tJ9FSUJIpHiWLQgMEkBj2o20ZT4OS8gulcO3Puv211C2jKxBgRcQT1uBDO65+2FRbmClRtVO8tFcsXejFoIqFITR47cVUL5fNyou395GIHN+UKq1Qw+GV1WJe4XhHzZ7dip+ZiWwCp+FTVOKVozfLLuT+St4JT3+eqUJyjh0j1hSpeU3Nv23cplgfc6grRi/faVwjeWc4vZ0BKjZIufKRSwR3HtoylnAt3KN4KUASy2wrBNp7jHEKxCPQlQG+9wpwTaUyM40jTtoh6O08KUV4Ki1TtVKSmaerhKNs91pcEFyZMWV+ybzWYUb04eFJNdlL7O/rKRICvCPi5DXdNk7w8fPU1PMqi56fT3nfxfqmb46p2aTATlbYOPBc4yxbMvNgarUV1F9ph65sEcYZBiRAs+0ouaimaUqosl/Nkt5aLwjxfFNVMDNA4MUe5bqBuHW/M2d+mkgzd9ufmfiva6oBg1Zd6HlVWfVS05iTtPSZwFTjGqjAShtxrRUnTVpdp1cy69W3t5ypq5tcpmi8O0DZRf9nrFTB/27C+CpczIXpprRTV7Dm5EIWg7txsVquBbdRFSYdXIVEMUERIUgjizk/mxZ8XftnFwzSTJ86qDSxVYt6PL9kwLIOwTftsc2dV/xUxELXJhZGR3rd22hFK3OBCZ7m46oRbZOtMy4mrWksIzuFDQxMuSnskm6EqWs41i5VJ28GK9Z6FC7M/Vh/r3N5va6O2h+k8mDHIwfJ+7hyTKDWZ/apw1JNoFRBMPZSqteSiZnqrWbYP+6Jis6LF5kJX6OEiZFcqoFpPtt9atnMU+Tzoo6Dn+JH5JwZVaMFyaZjgNd60nhV/mnCFgtU81c8yNF7xFCQlWK3MhKQNroysbj2NTPfpJzO62QElTClNA01rBYQlXAjNS/ZKgZwT26K+7T1Qt06K7WfdRrYwzBZszWydDHPOtdYyX5RwmwIca4GPEwfefpdyfW1+FTjqgiVeFast2jqc55n46mjCucZ/SWRnKipxgemUWr6xra+6OJnUCJDzqs1tUODVCu4Mq7qANZqt6cFgBWquDe/PNYRWvNmc5ioEmtGUkKzo8ccpR88yLu+Szu5BHDi++UlkMqcLLdJOoe3p9q7QX3sK2hluekC7ewVpO0P5FYrz5/5X5qIERbYBg1ZXQk0Y/dbgSjFca7sF9X9bn3TrR2yrOi1RXqtFnEXHrQZUs2lj9yoQqm3pSpGLNISw1Ri1BERr+kYuIq1SX2sP1F6b0HOfRYo58RmtwOAWEbekcqmmL20jpgrybX01D+elL1sfaOteizoT9OrEJal+UoFcMhIHdHWP4fQem4/8PPH2R9mcHTFuVmjMLBanDENCk+mObtrRTeeE+TXWSYntnP2H38DkyqP0e9egmXLwwCMQOsJ0Fw0e5xxZpOY+t+Cq3YthbRUs1u2eXfij21XOQ5V6aBBUcnXULdz21hBAIx7JhXjZAmDPRC9VVD9++8wiLJVzdbzFVLZYiohDytaJ15ojvAhmzrWLQngpfED1K84jF3uTuG2jwkXkBRVt32bk63uUCmxWoPC820aVlDIxZ3JJaC4GK8QN+eQ54r3brJ/7AOvf+I+kxRGnJ0f4HNkMA8vFwMlqzXqT0VLo+8D+Tk/WQkxKKsoyO8LsCq7taSa7aL/LdLrD4SOvZf/aQzxw7WG6K9dpdg/pprsUEbTpwAWoh8O7WqhHhSvOXaSLIkJzRbfRn+ldVzUedW+k5hNdUbIWnnxw/zJF4BUwf+cFcqZ9Gq2nrlovK/8t5w9/G81sBWlbtbBtCyjb2h+UXMN0tObDqjNt1aI1bbH1hbbRk9aUTdlGg3oRZhdrHGjVwuycC5ozkgs5J7Rk4hhZnxyzevbDrF58jnJyi+VqyWa1wlPYDJGTIXJnmVmsMzQNj8wazlIhbgZSyqQirCPExQskWrI+zTpCJ57dK4fszzoeeegKh9euMjl8mMMbr6NQmB0+Srj+WprdG2jfk/B4MUzNvwQmOS9WlJdicnbjAW/OvpQqdpbGyeYsmua65HX5OFVOZAngHAHOqxS2UdsWu7IHrbWGqfo7QFIsY1/9L1HItYZ7W0eUqTKzRc+doiWfR0cmnaZ9DDk29DqVYg53LiSNxByhKItSKCWjqUBObOJAipE0rnHrW4xnxxy98EmWNz9Bs1qRhg0xDozFsRgTZ1FYl4aTBG3nKY0noYwiDAhRHaF1bNRRMmRtKWTWw8iNJrJcb7j13IpyepOdF36d1W/8R4LL9P0e7fXXsvPI72fy4BvwDzwJeweI1TKfI/nbpbVyY9vLoNVVQCw/enFg7U+nVnJz2evyo7+caWqnr5WzitWgbxFjtVwaIhQptYLTUgjZWdmJYgJnzZ7W9ZHOO2UsvVA0k0uBVEglo7kwxIFhiAybFWOMaEoUTaQcieOGcRjIw4p1XKFxZDMMpJJwJZn500KTM4txjSuZ3iVu+BXEM47vnHJ6fMxEI6EkSlTWQ2JIiU2BRXGMO3sc7BQihbF41iVzFpVJCBTxpBDACX3XMRG4d++MZRx5+MqczTpytFxCFMJySSvCQm7jbz7H4pkP0l+7wc5r/p8cvOlP0Dz4OrRpqwXYHtUaMb4ENlDDVuxBvyThLGzTQJ/ql13GegWEKoE4ggg4f16hqQqRrV9U8LUNOZdMyRlJmZgyZYykOJomiAMaR1ajaYcUR0qKrMcNmgdW44Y4jmw2a/JmYLFacuf0mMXpKaRo0U1O+ODQFCk5EqTQNC1tPyGEntB43Lg+r9smR3KO9JrYmwqlHZC4IJ4sKYuRZcrM2xpwlEIZExqVNDpijswOW1qvrIaEpEwfHH0bGBGmzjMKzKcB5x2JfTaiHK0yOwEGhU3cwCi4kvEUUj5lPDumvfc88dZvsrn9Ma79P76M2es+hzKd17r52qHttgJmWqmpESR13897EivEoFu/9JLX5SPqJZNjtBtQPW+EHHOGlMlDZFgvies1J6s1q+UJi8Up69Upx6dHbFan5HFDTgM5RnQcGdJAShGXEloKgyoaMzlnisIQI704hlJYjRuCFqYUusahvjChJYhSQqHzHhcU51YUXVFGaGKCWAiNgzyQxhVl3HC0UPK0QEmMyzU+K5RMHgtSCiUlyBmXlb3g6V3CRcOzeuucYhqUoBHnGkILGiaEIEy6QN8FRDN943ApMfOBPCgpJVwRXHHkFDnVNbLOlHHFsF6wuXuTh4clu5/9J5DpFI+z6tcKdm4xOIHz+va0xWK2krQNXl6Bdfk+1SZS8sA6nlBKJsXEOAycnp1xcnKX05N7vHjneTYnJ6xXpwynx5wd38NtBpY5sTubVMQYogoSAt47vPeo85BG1AXSkBDv6IGQIzEPaMy4HAkoS1GWxxsOru2gjGjbEFyHpyFGaL2QWk/bzpC2MB7fYzg5Y708grwhjwOTXvC5sUTumEil0DtlHCJBlXHI5FiQUehdpCNSFg1pWtNHasFAzB5pwVXt3LgWN0S6EAgOpk6QxtG6zKYETpcjgW1PX2GdHI6Be6eZfj3CySnaNDwI7H72n8BP5+C0Wj2HKwm0UGrVqquNpMK2tcuelUfgFUgqX7pQ/dr7/zPHx3e4e3yP49N7rBcL1ps1brlmszjGpZFxtWaTR0IQTo4WROcYVIibiHg5LzHOTmibwMRD2zV4X3Eo8YgUQjatJc5TcsGTEQlEZylgV2CxSTgPPnVoUFa90s2m7Dz4GPPrj7K/c4Wj2y/y4of/E6ent1mnRCeFZcwcD4XVJjFvhQmKlpHkCloKY4F1gvVoDRIul9p9nFiOhoYNWtARGu8gGag6aSGljA+estkw6zrSZgSFIY60jad3yjpGYsw1I5HZqNCTaZqBeRZuf+xXWGw2PF7g6md/MTLbI5WEOCGuzkAzoZ+Tivm4zrcohaxCbcIkqb7M0b+sdelC9a/f++PE9ZLVZuR0syLExCQ4UsqUOKKSLToshTEp65gYG0cujlwSIUOnStcFurZheXSPjSX70KZhsRnpe0/oOopzaCNk5yh4ZiJMFEp0uN4hvsFlO4xJMgRH03oO9neZuoKsTrl3fEzaDLgwwzU7KCuWgzIWz62TTJxlYnSckZl4YQDQgkZYbyAnxXsheE/2FtKnAdQ5likT8IyacMnT9Q6VQl/AOQcOUh6tBzFnSoGSRhNAq30m13SAFmGjkEoh5SVDyXSr/0rWfwihYe+zvoAcR0LbMh6/QDeZE12AtKF0E/AjLkxqiU6FVdhWhVzuunShGp/9BIgjlkyviVwyy+hIKeG9w0kgFmXMMEhBQyDnhCuRrJngHXuTjqZ4luuBLIXghJNNJC8HcEpbHKvVBqcwaQN4QYNjIY4UpszaDhkTk87RhildF3AexCtldcbmdmbmBmZNYjadQJfpUkIXLbLZ5ZQOHwq7bNhvRno3UpKyHiJjyZRR2RQlDmZOuq4WGWbw3hFVGWOhZEF6R4xWm17GgisJDZ5Z5wiijGNtYC1KCI7NWFimQsoFlyxVJMU6g1y2fYtZSSSGYYk8/evMPviLzB98itWwoJ/OWN78CO2Npzg7us18MiEuCt3OFXJvTrw0PXpOYHLZEvAKCNWdzZoRZTNEkG2bkZCzlaTklElJSWrVj6VESlFcibR9w7oozy9HYk60QcilENeRVco0qnROWJZCxKoA5n2g6TzTIIS+4cXTe0zahhuHPdPZhCYUZvOGa5OABJCmxTUzKMq9m7f5+K17jHGg7zwxR7r9PSaLFflkSUG4vYKD1jELmd7DaRZyFoZRGSOsizLFMe2UDqUTYSyZoQiTicdLYVOsfqkkGHJhMya8F7oWUipogUaVSYi0wTGMmZwUoVAytMG4uJIkxqj4YAKKF5ZD5OjWs6xufZxhdUxqG8bjm9xJQh4WsLePSIuUCOsdJHS0e9chNKDbmo7LXZevqUokRYuSzMRlMkpKhYin5EQTaqFYKWgqBIGcCmcn5hPM+oaDacvhdMIwDMRuyt3lmnXKpFysjAAhOEFDYGfe0UTl5p0VKUdy67nphNPjkdycstc13Lg+Z2cS2N/p2J1umO1NufbAVa7d2OcTz9/kzu1jnn9+wfGd5ziY9cz2p+zRcRoHTjaJkxwRLaRk3cEhOVapsMlKRElqFQ9OC0UK06mn6QOrRaKINZTmlEjO41GONpl0lvHArPesUiJ3jiZnhmIm26mxCKa8pUmyPu0hCQHIayW6kcmdm7z4kffhiMRUmHQdp89+gr2rD7K++wLd7hVKTnh3C2lmhGaKzHZr7+Tlr8uHFKi14N4zrgeSZhIBLw6nhSRKzMqQDMWWlPFiJqMUCF5Y50KImTunC7q+xTWFa1emdF3HDM+9wcDNFiVtEouTFUNMaFFuXO1YjwVSZE1G1HEvj8SbSt8EJuEU3wQmrWdv/iI3ru3SieexG7vceOQhPvb0bZ7/jU9y+txtdBxIFNqmWAouC4sxkyOkWMhFyMmaIpyHdVKG0XKZoRVOl5lxVCYea1UXZ/forGR0TLYXGUO8I0LvIEZlRHHJqli1WBTZiDCK1YVt35cGywDceu6jTFvPerXCtztsFiuO79ymcYHJ/gH+uY8znx0yOsG7ltnDryO1PbSXS80Ir0juD0ITEC20+zPGElmOSlwNrGI0Ao1NYpRIzkbMtdHImGql4mhJnOXS0XglqtK6gCg0wQOOmM1Xk6w4UUaE1sG0ERbLzHJQJpNM26qRv2jGDRu6pgXn2Jk0uMaxWI986CM32UTFeeHgYIfGBZ5646MsTteUYcXNF26yPFpSkhK6RPCCeLi3FtZrGIBOAoN3dGUkRkEztItCOxqX1KDQCHStowuCaKZxiWmvlOLI2TIMQ1JMyRtXw5CsXzJiaayxJuiDmnbULHgybWgZFkeoDxwfHbFJLzCs1qib0PlC204JE89kuov4BonKE5Md/GwXt/9bTzX9P7MuXagGZ9WNCizXiXERGYaRiRam3ggh1p0yCx2NOCaTjiLCkDLrGPEOWt8gQBxGcoqoF1brwvEqWXdI9QO8KqFx7ExaZn3PdNYxmfUcJOv2PT4+oZNC6z29c3gfSKlwfLxi4kwgfT+h7xs2y5EPf/RpNiul2e3ZmfTsTBuuHe6wvz/j5OgOm6VjsxzJFLogaAfDAEMsEAvNbsMghXSWubcWfIUU2t7KeScx0TWORjM7jTBrgnUXOesxHBPEogZkFk8s+Zx8d6iZca+VpyIIacx0vZDiimHhGRvPvbMz1suRo7MVqg6cZxJgPp+yPz2jeM9qU0hBuPH4G9nLT8HVN16qDFy6UK3uneDVUXxD9g0udJbAzZEmCD4EQjLKHyWxWK0ZVFAPsy7QNy0xRu6ebYhjNid/LGguNC00kwkTL8SYkZxoJy2H8ymny4HVYk3Jmb7v0KI0PtC1Hk0jkkbWS2XWt7j5BNcKcZk4OV5hHRDQBii9ksYNtxZrTkSY9oGWQt9brXm/07HZFPJZRAR2eiG5QlzB8aJA69GJ4+ZGaaPSeYGFEeJOHezNlGnwTBqlK5kxKW2wKg1fqzhKcMShENQRi0LlktJoKa/WQYyAc7TesxqWpNEaOY5OFpwuIp+4O7JOAe8ifQtXF5HXXFP6SUe88wme/9V/gx/voZsTeP3/xYXqbLMx34XCJm04XVtqZRWzOe+1HXniHC44+gZidow5s1hEhLWV2YIxpjiHeMvuS1FSVJYjpAJOAsuzwtFyYVwNTmgXI9004htHizLmwk7bMDolqKIZJBZG9fiu4WBnB+9bTm4fc3J6xnK5AtfQtAHahjF4jk9PSfci016ZT4VZH2g6cEvl+CTDYDVeJSsMha5TmmlLP20Y15H1oIwxc5qUTRFuXGs4KonpUMjZ6rm29WBtcJScQUyAsjjG2l+Ws1EpbZKQvdKIQ/sJw1jYUBjHkXtnibOzzPHgWSUhZqs3K9lx44qnp1BiJJ4ecffZD9L5AfhzlyoDly5Ui+zY5MyJL5SYGHKpeSmptIdWH7UoGRkyMQeESNYCzll9uphfEcT4CHJxxlNVCrGWd0i2BGrbWD18rrXwK2A5FNzSEspJlc47us6z03huh8ikV3YapW2E1q2hKGOyxLZrPDElyI60icRpC3iGPDKeFE7PMt0k0PTWNHr9IBBL4c5RYRyVRpSShJ0ZPPDAlHGd2CwTp+vMaRw5XWXi7cL1uTD3SuthiErvHMEXI5FVIavVyWfNxGzO+aBKwkG2bEFoHNOuZUAY15HFKnKyHlmUjrEUhtVIDJ6D3X26HRjHAZ10bJznbJNp16cMy09v/O7vZl1+9DdmohTCAEkKrXqSFFwtJYu6ZdGzZHMq+bywLMWBxllf3pC09r5ZXXVoAiVGBMgqFf+CNPpa+QBKMZTdO6bicaIEVym4Y+H2UAghku9ZddfEObrOEZwSvEVagUJolEBiHAoiGXVKO+/QWFgvR5bLTDcUOg/9rGX/oGXSjNw+zqzWytlGSa2Sbq6YBRB1zHthMpmxbAdOF5GTjSM3ym7IbCLMOthtDTkHIWbwzho1mkp4ErLUTmOBAHv7UybTjiSBTdrwwr2Ro5UnOWgnDWlMlKRoWqHZsRkFaAhOGLUwrBPP3z65bBF4BXCqPBKco+mtHnqM2Up/t6CgKgGLcgzTEYLzVkVQHL13OA8xF8ZatamqlJis4hHACU2wpLALwk4XWI2RcYSuq7TVkmmDIw2JXBQXvfXxqXE89V4gFFKGTQYGg0OSCuIscewd9JpwXpj1jrZv6eeOzemAd6A5M6wyTXB47+h7IbWOzVliNQonm0ynib1pAJfxrWN/f85sB46P1iw2G2RiDC2bqPRerPK0tolZI6kgar2II4KFCYIrHt+0NF3H6mzDC/cGbq/B+d746b3n2vU5GnrWyyXL1YjOW4aSmGCg8tFyxf/x/Blfe8kycPmND6GldY4mKBlHxNqsx6KoeFotlJwIqngxoh1XLBUzmZj7PpsGWi+cDIqWygGF4KRBUdraNJIr7ctmFEppcD5TsiMCoRE8jgHwvpBUIAiuMbPTiLG75FQI1Uxq1YAZzzJaBfvZBtBC8Jl5U+hnDU3niF7IObE423B2c02mUCYTZDKlpXC62JCiMXRm79ltGtRB5z3XDna4duOQX/uvn0AWA1dmhuGNo8EVvroCsYDzDnEZKo+V1k7XpnVE8dw+G3nxzprnjyI+TNhIyyZFcjZ/rdspSIlIyGhTanOJRabrzYYPfvTuZYvAK9FMKgSvdK03MtliKQ2AxhXaAFkCUpsltZYIizpcATfpCMGzvz/FbTKnm3JO4EoujKXUykUjUI1ZDWmnEJwni/knU+cqk1+hIeADSIBpCOx30DXQYh3BYypsSiImNYigFCJKIZGcIxliwL1Nwa9H1AmdC9B51m6OxgFSoZEWxgTesz+Z0V+BcdxQsqChZdYrO7sTdg922ODYCYE7yzXTVthprSZKSiXXSJZAbl2hQdFizaxZYBqEK9f3WMTC7WePefa5UwotbiLMJsIkeLLzLJdrchpom4amsUT3MINOBOcLboRu59UAfpJIBCsddkIJQPLEbCXB602mbJlUti1TUjPnRWHMzB454PDKFDlO3FvcI1VfCqzseEsllJ1HRGm9wweHE6VvHX3n8DjGQVmOCmUgoIQgyCTRSKDvPKF1hAK9OubakLOymZvDvRiVdTR/p7jA3CmJGjwAnRsZR8dQrLFgutszNp718ZKdecvVwwlJC8PG6qgcjhALw9nI7c0RcVjRt4nsHPfOFL8Du12C4hhVca2lYkSFobjaFApDErogDFk43hSefeGU05NI8M4S+MnR9FOWiw1Hxwu6ruVq39Bn4axJTFaJtg2INJQmIOPpZYvAK4BTlcKeOK5fP2BdMm0qnB1H4nJN2+ywXi8ow2gdNGxZdZ0VlWGlI9Pes7/bg0bao0Acog0xqjwIXsQa/zrPvA00fcDPZswnE6azCb5kzk5OOX3xLjFFSjEHPo3WDFFiYdY2tI2jnXgC2eiMomNWMH+tyaxTYMywLkDw7HQejcp6TKToaEthWhJZLEx3MTJthGuHHQFls8nMmpYsYjVVFE7O1uS0ZMLIlR7KnnBvCSuESbFmkSBiPYdiA6RiEVIpbJLYZIrsWCW4d7rh9CxRipJDYR0zaRwYcmBx60USVtLcPPIQd05OaFYDkzYznUb2+44hJ27szy5bBC5fqEoRQgv716bMso02uxkWrMYBpCBNQHNEKpvrlmc8ixicoMLR2Zo3PnkVJ8KV3RnDkJBS8EWM7LBtmPQNbRtog9DPJrRNS+cdy5MVw3rDerOhpIJ3xiF6uOOtSiELbefod3r2ru4x6z3Bm88WY2a1ibQFgre+k5gTi2VkucmMObOsVRZFlAjs77eoF6tTL0poPVd3Aut1Yd4GNg66ZJxYZ5uIkOlyZNplDqeevg+0faGMhXWGzpvWHvK23cxyoqlwPhplujslNYH1JltVqguIMzqAdUzQjFYhUnOEOijttQc5PnkOOU0c7EDZLexOGt7yur3LFoHLF6q2gc0mMcTClb05p+uBnb6nbRwpWXpD+o5hiNYypWq1PQhGBlwYFxFVOJi3PPzAjHUqHB8tKWREPI33lphtA03TMo6ZlFbEVeZsnejaQKsjft6AwslyYL3JzKeevvdMpxN2d6a0wfg4c1SGmDhejmwi7Ew80mxLeUElICTikMkKBw/s0k0bA2tzpqgyuoiMI9OmwUmiC8qwySwXiaYNtEFRD4dT4UoT2G0czhXyWjmcKMfZGh/WCRAIQc45tZxgQlMqZtd3HJ9Ejo/NrKsTijOy20iiZbBZfkXoJzOuPfwwN970JB/6d5Eh3uFsOTLGhsNJizSvgtIXQqBQrMJyp2UYR7p5x3w+4/bxEpwndA2h6xjHkRQjXjyildVOlHVWPnHrlDe/7iqHOz3SrvF9SyMFUiY0HgmBVBzD2Ybrey3N1COjs94351nnRNt4FstqOp1wZ1GYDInZnmc5FlZ5Y1yZOTIm2JSCdxCLY3FvwyJG4gChZJRI6D2v2d2h3ek5PU3EBOOg+FCQrEznPYvVyMknTmkaWGyMCOOg7Sk+GO7VNEhnzDFUFpqJc2x8IidLPq8UmqznLW5JhFSEoRj8sM7Kvc1ALIVGBZzigmky7C0439FJ5vDhB7jyyIM8+siDvPjAQyw+eYtlhLEIY3G49CqoUXe+xWnk7umaR24c0E16ujJycDDjbLVhzA71ENoJ0k1wQ+2UwbAoZ50BPPvCkidfc4WhRHwqzGYTVusl/aRHakt6ygO+b1mLEAdhvRxJWnCaSIOZrfWgJBE2Wc1sqXLraMWd05G+D0iKtA5C2+KCY9I33DwdWS8TJ6cD6hxX9jzTyYS9Wc/urOdkMXL3zooSGsK04/RsjYvKbh9IacPxotB4BW8TSwcKfjlQSmHYjKzEM2aLYvtWmTeC8wE9yXhXGBTUedbAOtrgEqfKagNdHyihYRxXRhWpQo8zTKvxaBJc9jZ5tXVM93Zp2pYhFfzunFVsiIykDEnknAbyMtfl+1QOEi3PvbDgTY8X9nqPo2UzJvquZ7UYzNHOhWEzMI4JUiJpNuBPIIlH14mPPX/K9cMpN672fPSZI5reM5n1nJ6sKVlpi1Bc5s6tAfGOIY6VGE/xwVmaqGS896Ta4h5z4ebdFaENeO+Z+kI3bcnDhmnXcLoYORkLw1B7+3Lk+ePEtdwwm/ccLUfOlisImSQWYQ5RmfYdp4uBNCjFG1DpgYmHtIoMUZl3ymZZGFTwradvHK0rtB40Fbqmch4X2OBZjnBvXdCk9GKmcXbQcbKIbGKyfKA4Ri+EIHStZ73KBomUYgzO48DRyTHyQkOMibMUWCVlTMqwisTLt1WXL1QBJTjHOCrHy8jhToeKJwTHzrxnsRgYxoHNcsU4xErXeEFQ5rxAypQ+8MlnTzg4mLA7dTzx8C5NP+GF2wvrk3Mtngw5k1qhax3TnR1KEJrgOdjt8E3gxVsnrIbI7TsLUhrQAmMpJMlMFFbZc7oa0CDESa1QLUrjYayzalUdxbUcr5SQ1jiUyaRBsiWffDchFOHm0ZqJg51pg7oCla0ljgknsMkGuq4GYeoLbV/oPdYN5C3xu4nC0bpwPEQDjJ0waT1jKgwJYlJWm5HNIkKpvDDicb6hJCvRNhrvwiYWjo5OaF68zTAmlqsFlIaT6DnLDUSlja8C85dxaFHikPjE7TNuXJ2TGZl0jt1Zw22vHC9GazR1npKyHU6ppFwipKzIWDjTyDPPHPHotSkPXGsYc4sPa+ZtQ9M7ppNA23ha7/GNUKJQKMx3Oqado5tMCDmR+oZrD+zykY/d5OTeyhhfUmaTQTSRBRo8w1gYKgpetOAbR9GG0FjF5jgUFimx11sfYpsLSTxjSpxG83XmOw3z1uOCMGQgRkqyOWF9yEQ1QlgfHF1Q6z/MphVzEu6NykmCRbSS4iYI6yGTqbUxAVIGCYJujByppELXCqjDOSEnBTelpA3HR6dk9wJHJ8cklEhh43sWG2FnryWX8bJF4BXwqcSjJVGy8MyzRzz60B7z1trfQ+d55JGrrDYjKSdKcTTSWXlL0UqWlnDOppIXCrfvnrEzadibNPRd5jMe2WXSONYVu1quM3eP1pwNyqZYv93+jkVf8/6MTz57l7NlZD5v2Ju2zPqW0+O1heeqBDHzVbxwujbz2XbKpJ/YyNwG2rZBgmMcE8tF5HA+J+cMTcdqlVhsMqshW1GcOkrf0oeAi4VRHE0SZt4mMIwp0XaO4ANOCrhCShnNyjIqxwMs1TGQ8d7Rtp5JaFmMA50TwrSnGwrSePIm41xBS4Ki9H1L6BJpOeD7HdQ5NCmre6csjheEvqFpO8S1nKXCztgSXg1MeqqWn3IKJ0drPvSRO3zWk1fpfKBxBfGZ+eGcs7sLI+ZohFbVum1ywRfwXthpG3ZmLYd7U/Z2JrTBGTenJisZXg4cnUaO1hnnWtykZ4wRP21ZF0dJBd1kzjbK8dnAYjmyv9eyvz8hbjwpZ5brOmatFWJUSrZ/T5ueq4dzBicc312yGUdcq5R1QaRwd5XIm0I/89w+jYQS6UODmwirnJkXj2sCXbC2Am2zMeIBnSs0zpLWRmfkiJXKqJk3sMyURaRrPOCRMGH60AOUW7fIztg/RaBrOqIvBKf4trEPDw7fNLi8sUlivYekRLYjQwLBNyiOzZjZ39/h9Ky5bBF4JYQKinjEW0v1s88ds7fbcLjfI04RrxzuThhOBsZxgGK5Nq/Ga9W2LVev7HDtYML+Ts9s0tJ5JY0jJ8sNJ2cb7myUEpXTTcaJo+uEvhWGMSHVUfa+MG4im5QRL/ggTCcNs9Zz1niWSckpslLFeSs58eKZTQMPPDihax03P3lMXm9g0jMRj2s9vgtohtw2xAS9h3basR4qj0QWxqjMslAaM11Uwv6iyqRxxCQUtdRLxqiOkmuQ+ZzJ3RPGLtD0DasYiK5hduUALUqOxzTOQeuYzx0xJnxRkge84r2j64WN98Q4EkJP8YJzgg+e4AMeDyqcpYY7d1e46auASkgUelc1lneQE7/5zF2m3Q1A0TEx8XB4ZcLtOyMlJqbO03UN+7OW/YMZBwczukZonCcNI/dWG1bDhnvHkcVGWUZBK6Nw1wemwdGWyJXe0baB1TBy52SFeCGXhFelQzjYmbJ/MOdokbhzsramiZxRFbzziINZK6RF5MXFgsViqHyZA6Wbcu3KHBc84gKuEcb1SAiOKDDVwpALvhVrqhgTIXkW65EgMPNWpTFkpXhlo7VrSJUxCTrbZXmU6aYNc2B/f87tTaYkofee8MCDxNsFcSN7XU/Z94Sm4+TeEaH1TNuG3iulDwx9YL0Z0NgQKvF/ccZbZYOZhNB4FuvEjf35ZYvAK+BTlUhO0DTCmCMpFoZ7Ix/9zZs88dAhUgrL1YAUaHxg2gYOD+dc2Zsy6QPTzhK0i/Wa1Zi5d7zhaDGwKmKMKFR23i7QpoLkQieFvZ2JFfIVx/rsNmUx4FvHQRfwnWPWe+bzFt/2ZBwp1coILPR2wMG84YFre6yksLk3UtTbhIjgaNuGccjICN1EKBLQBCHYrNFu0rLJmVnrmTTCam3FipuiTIGlCq3AOsNuj5UAO2uu3QwONw+QI6Ft2A0N08M53QtnLMbEcLbmkc94Lff6QLn1DLN+gmtaZtNdPq4FYmK6M8Gp0jhHNw+MoyIpod60pFNB1JGkMGpGfU9KG5pXQ9t73wU2w0jcsu06h2jm6M6SaWiRoOz0gXa35eq8o+0D81mgbxrQzLBcs1huuH0aWYyZs1ViiCA+UJwiUekboXWFnZ3AdNaxN++Yz3sijuViYGce2JtPIBca37B3MKVpJ7Rd4GgVWS02SC548catqQV1jq4NHO5PWd9dgUJoGpz3zCeeJgTWRZBSkJCNdL9vcUVpM4xFmXjPtG8IvvKJSmbqHbNGbJiTKgXHcsjMvZU5j4OQfEubrDG2VwHfEIIn9IFGhc1yQcmJ+XyHu887QgA36Zk2gb39PZaLBZ5AaBxjGtmZ9oyDdVAXzRQVmjpbOiQIuYAoR4uRB18BJtlLF6pu1iGhJSmUlHDF+DMJDesYefjaLldnUxpveNY6J3QYOF1vWCw2nCwHhkXmNCpp0lHUUVxm2njwDu8zfd9wdeKZ703o+0DTGGFoXg0QI75paLXQTyc89PABO7tzNhvlaLHh6M5thjEaa5+zhy04OvHMJz1+0rNeHKOKVT80E3wvtF3LcojMpi3zeUdMQvYZWWdCF1ifrQkBCJ4cEx5jh2m9JwSrjAiNJw6WBF5kCENmSBjxWlbDxSQQgCZm5pOG4+OB03jK2e0jdh+6xs50yrRv2TvcQ2jI10eeI3G0WLNXOiaThiyObp4oZ8UYjwuQwFd/PqmgWTlaJ04Xm8sWgcsXqtmkI/iRXIRxdJCV4gI7ez3XdyccTBvjSEiRTVQ265HTswVHZwNnG1gNNgjRuUA8iTSt0NbIEYG9ncDV/TnzeWDStiSMEzQPkcVgHJ5G5aw8cmXKo48+wGoYOVksOb59wmYcKKnY7OXgCNlKmbtWOLy2w2KRuHcWAWEymTM72MNtBiQNHOz0zCcdbdcybBLiPUUCKY+0oSEraCkEB75pGGOmaay+vJ8E4pDxKvSThkmnrEokqmd/PiMVy1kKViHR9w07vqWVBbkUOhfJ65HYdEjO7M7mFBw+PEgz6SjP3ISYmTYNSkRkStqskGTTKioRKqIFVzIxKYtl5myVf9vn+XtZlw/SuwaCWLWiJNvEac/BTs/+tKXxSkmJ1RA5WWw4Ol1xchJZjUouVjJbvNA5ZboT6JyQxDPvHftTz/7BnLb1eCfMpi0k5WQ9cjYmcjaW9T549idTDvbmDJuB9emGvFrjiLTeW46vsTptAXrvOdibMTnY4fbH7iBjpgmepmuY7U/gxCpW+0lH03pL2raeSeMYYqGsM83Ew2qkDwFU8Tkh0uA7RyDRB6GUwl7fMW8haGaxhJ29Cd1sxnKT0fXGsgHTlsmkI0wdoevIm5FhGNisV4wY3VBoHWG6Q7MZmE57Dg+u8vQLL7I6WRAT7HSedAj3jjdIKqi39FUsGZxwtjG+0zunrwLwc9YFZrMO55Q0ZnJWxEFcJ47GkeAKeUycLUeOFwPLdSblTCxam1AdbQj0U8/OzgSy0jXC/rzhYK+jbXuGMdK3VkN0tlmzWA6kWEgx0zrHjWsTrh9O8H3LZjUyjskaQbuGyVrZn1vf7+nZmq7LTNuWhx89hKTcPV1RgvFftW2LDBkpIw6IY6LrGlpVdnYmJFXWw5Ku74hDwjWepmmslqlrkOWG6dTjiqfzgvOOnkw3MXxrutNweGUf8S0bRkTMt/RNQ9M2TJue3fmM54fEb378eaa7a2YHPeoK0xDwXcusbSkKu1nZ3zvgueefZ3F6wu3bRxzOJ0y85/a9pWFVbU/nHYPCeLSgbTzP311dtgi8EpBC5upsRtt5gitoTmyGxHodjT4oRm4ebVguR2LMlFJIWQku4BvzyXZmPQe7PbNJw7SrdEHeWRcNQjvpiM5ybcNyYBwLxRUaL+zNPNcfmJE3kVufvIV4R1ZveTP1lNCwuzPjdLFiZ9oQXMP1/SkPPXDAJ58/ZbWJOHW0bYsGh+YVk2DUP1k8qNJOW7o2sDkbmc96o/R2jp3WM+lbnFfyWBiHRN965t4hwbM778jjiGsDu2T2Z4G93V3OVmbm531gb94xmXTszaa03YQrV3c5OluSSmEZ1+SjiDv0kDb48ACdh+IayJH57i77e/ssju9w59oxt05OuXXzDsuYuHlrjR8zY+OYhlp7NTpmfn3ZInD5QnX1cMZu72jIiEY2eSCt1pzcW+NF2KiyGCw1kZ0Aga61DPv+/pR20rA3CVzdn7HXt4S+IZcMyQjS1usNt48G7t1bslxndnrHbNrQhA4NkcM9jx8HFsl6Cc9OEylnBrVhimNJjFqYTDuyNjR4HnrwKkjDzbsL69ppA9IEZEykmPAzEC+kIeLdBOc9m9rM0TUNrW8IEugaxXvPpmT6zji4ph3MWugaT9M6Nusp4pTDHcekbaDtiMXRtA3zrnBlr2cymeF9S+g6rl3Z4blP3GaR1myWa2hbNocT1EPfzxBNNgmicUZo5oSDq4dce+BB3pgTN49P+Le/9F+5d+c3EM3MGgddx3h8DCHwv73uVdD4sNsCOjLkkeXphufunnF8skFzYDJtKSkiWQhdgyal6QPTibA7nXC4Zwj63ryjn7TWMOoLORZWqTBu1nzkw3e4vViiGULbkEsgIexMPYfTQN8E1tG4OpeDcpYK41hItXNGc6HFUZzQiTKbTNi9usOd20vunQ4oDtc2hM4Tc0Z0pFHPqPbAXJ35gmamXaBxDeKFSefpu0AboI0NfeuYTiY4zfSNMqmE/aGFRjLeBXzoiVk52Al0LiES8H1LdjNUA8VD03d0DWyyZ0xWlXGyKMQspBRpfcBt5/iKJaoJDW3Totry+HzKfDbh7Gzg5nP32BSlnJ3ROKVtG7LsXLYIvAL1VMOa1dmaT9465c5x4nSMzLsJh9dndPMJIQ740xW3ziLeOa4dTNidBK4ezJnPAtPeIzQMyYrcdFN48eaSQYTTu0srHwkNQxkxYsOGs01BGTmctSSEzUY5XsJyFLIGXIC+KAPFIIqYiaLMG8+NR67im5bbd++wWkeyKiF4a8YokZmDyW5PHzoWa7Fa8TrEKavVQsWUzGdSR1FofSEETy8OFcfEQwgOzYVJJ4hrQRrAKl6bUMd7SEBdw9mo+JwRD5KgDy2pS6jYFNOiytkqMVltcH2HEBBnM55xjsZ5QmjwKBpaHrzm+X+/4//F/+f/+z4+8IFfpfUjcaO0PpBSd9kicPlC9b7/+gIxJYZs1D2HV2d0XYOIY3E6cmV/yuOPHzK/fYw2gfnBLtemwmTaQa1POttENqpoTNw9W7NYpFp/7fBdxzQ0ZHWMeWSqShM8BWGVPfEMYiycDpwPCVgriBQGrHunFWM9fuD6IVcPd7l375Rbd0/QbO1fSZVNSXQ50U9b5ju7qO8Z88hmHNicreh9i/qC8x7NhY16fMjImGm7Bk32u0Ah+ZZSlH7SW9eOGpOLJZKDTbZILeuo+BHuLlco0Aos1yP93oTVrQ2dJMQ3Voy3Hrl374jJzpy27+hCg7TOCG1dwGWBtkWAZnLIQ/OWr/3KL+fpj34WP/sL/z8+/hu/QQJO86sg+ltEoWmnTGeB6cSTM7jG03c913c7dnf3WbspE79D27V0jeBC4WQobKI1FgyjM9KvoqxTQ9d4imRCzlgTTsKHwIuLJZuc6b2nbxuO18YS7NWjXmix8pmAQlEaX/CihCYzm/TsX9lhTJk7N49ZLtfWWOE8vkR8hMYLB/s93aRnEx1d37LZjKRVZsGaLnhcUpKDvb7nbDkSnEBQnLNiwNZ7XDQiuOXo2IzJxuU6YZ2UeciMo2M1Cosx4hlZrCPB2fT4ooW+b9ibOE5WCc2Jg/0rLOPI2a077I2JvZ0pedKR84TQKh2O7ISg1jSRvafFascevrHHl/+Jz+PH/vclpy+esMqvgm6aw2szhmilJ0NUDvZ3ePjqjP3DA3IzZ8yeSXT43d5m2LnEUJSVFhKZgNB3maSFSc5WqqEJydY+n8nGLdCDhpbl2RmxKDtdRwit5bpEjLSfOmldC7m2gsU68GBnp8eFjuXZgsVqfTE1tBjq7LXQ9S3d7h6ZDooabXbbEbLNyQlijZ5OYRMdqSizPrAZhY2zhtfFBvq24GNglS11sjdxUClLVhRSFs5GGFOD02Lm0UEi04gwITG0gc2tNUPMnJyt6LrEYlgT1egex5iZTJQmwRgVFwLeK14CxAWtSzjd0KSR6XzOH3j96/gvR++vo0cud10+QUcyysC9WcdDjzzI4fWrNH1voCiBrijSKX2BpFVAFHZCYZnTudrvcrQaI024XKCUSi5fcNla5ttpYdE1HJ8tKeroJnOcdzTBIqFCzcybx0LRQnKOVpVZ5y30L1Z16kNHyBHnbApq3wT2dmb08xkSenIuNFLo1LbMiWMk23QqCtGbcGXnWSTTRDihIJToiQLFB9quM9Mujk4cozjWThBfcN7GxDkyjoD3dpBmk4b1MLL8xG1iLixOV7zmtR3Diefo7IxJP6FzDhcTg0R8gbYIjRMKGTYjTV7j0ooUB5xkZqGYJXk1sBM/crDHAw9eZ371Ov3uobVMZUcRQZxpC6+FWBKpGAG9TSxVupytUA9LtYhYOYkkGzJWNNWyW6MfSgrz+YTm3hmL9ZJ549jd2bd5zd7b4GtnxW4hYKwezoZkN07xbBhOj2nFMd+d4DcNY0pMJp7ZvOf69SvMd/ZJpSUFCDkzmVqDZ1TYyYVEofdGzKbF5uwFauWq2JgQEGZOUGnACZ14sjdBd2JTV3WS8Q5yMYokpx51GaeZ1kXUO/aeucWLt+6wibA/daT+Gh9/8Tb3Ts640fUMreBzQZxROgbfUERJJaJxZBg3rDeJvF6wWUf2rj3A02evgjTNH/z8PwZNV8dWmHZwdfRacTXxq5lZPeGKUOrAxpJyJe0YzRfD8lQpJsshaiZQUC1G16yOEaWd7PLMsy8wbhKTa1N839G0jc1kEV8nsHucUzoX6uSuDaujBcdHC2KMPPjAnBKVo+MVvnFc3d9l7+Aaze4VGvV06kk1pM9qoK7giZrovEODUNS4sjpvurGgOL/VbIr3DWCNn43IeenNlqNBdDuBwbSMC46cE15HdiVzZb/nxZswLAe6subqlUfYlIa79+6wWayYTCd4Ubx4O1RNwAdHUxrwDaWZ0XSRpt+hPUhMbryO9Oxzly0Cr0Ca5sbjxl1QlFKKjZut7Hg2ctYG+qliuTc1VN0I0CIuF4bcEoqiJTHkzKxRtEQbX1uncm5QXBEmCGkG4lqeu3mT48Upr73yWtxkYmwyLuCcPTBRpQ2BNKw4OTrm3q3bPPfcHaIWHrm2x3S/p5/0HExmTA/3Odjdw832z6eLNq3WMbilMgKaGXYIwRuxsojgvflMnUDyHrBpoF6MDrxUZL7Uzs9Glb5pGWMm+GCURyqIOGJJhDIyYc0DV3Z5etKyjAOnp2uuP97RdFdpJxNu3nqOnQKzbkbfdUjbIsFZMBF6nNheOfV479mdz+n6Kb9vGC5bBC5fqCbzuY2NBZwKUbPhJXVotSmrYlMfcrKR2qrkEgl0FC10dETN5JToY7bJByUYuUZRSsm0PtCLRVidBGbTCU3bcu/uXZbrBVf3D4wUzIUKWtpU9ZIjm3VkdXSXO598kVu3j5C+YedoxbzpeOy1T7B/7UG8D+TVhux7PIoXoGRUbNZy13o7PFqnywtMETLFGkPFqkmdONrGeNJzUZw3UjZFkdDYoG3v8BLoqPVn4ghiteg4IcYRfOKBB65zsPcix0enLI7PeCoI3e4hk70D1Dvurc64cniNbraHd4520jMJgbbrTXi9I7Qts+kOXd/hu8DVV0OR3mQ2r1ooQS602NRQDQW8+Q9FM01TKMWhalyb1GkQRW2CVqOeEgLRjaRckOxonPF8Ss5Q6YTm1VeJOB57zS4Az92+y971GzSTOQSPbz0tDlJiXI+crZec3LvDveNjVjHT+Akni8RjD8648egTTA6uEzeZJHfxswk5KyiMaURzpm06QK3dvGSC98ZhI0Kj5vo671FxtJVkw3tvFD6+jkoTG/TocLgQiGoC2TljyJM6OKb1gTEZs8zhAw9xcPA0x6drFkOh6wJ+b5cd3xEmMz7wwQ+wWG24cr2hmU6ZTWeGrAfonKef9MwmU5xrEFFrQXs1OOoOG8HqvSUtnThyrZHOXpEho876/p0YTbN3gZwz3ltx3ZgSYI0EPlhPnvrq/KZiGIwo4gPOOTQ4ggZCCLzuydfyax/6KC9+8jkefd2U4Ca06vCdIeurxcjZyT2W94442US8NxbhvcmUq488wM6VQ5pmhnORpr1Bcb6Ot014b5xTpEIpibZpKDmTveCLol5wyUafiQjila4JqAt03tsUae+MyU5qh4s4Wu+sfd031Vx7+qZjSCOh7SBknBPS+gqzWUdwjpwyvhT6+YTChKvtjNe/4bN45jc/wtHZEY8f7jPb2cGLo208Td/SNE2lY7JJ1p33pPIqcNQbXygUozp0Di0O74SYra29OOtHVnGoy7TBG8osNTgvRvfsHPQilAK5zldLanPyREwgG2+15dJWmjwcfTvlM556kg/++ke4d/c2j7/2SZrG/AsiDHFgeXzE8ckCkrC/N2Nvd4fXPvYQjz/xBLPpLiIdoe8YYrRWrxJwbbGZzVrQXOcOFtCYwAkZKDnTNEISh3cOEUWdNyGgFh7mSGi8DSAQIeIIXqxkBiPTxzmatsP1EzRHutYmVHQ7B0x35rTThtA0hNDQND1ZWhpxvPaxx5g0jmeefYarR/d44Pp1fNvRNgEVR87RqLwxhuchpjpo+XLX5ZcTdzOjp8aqIEWVkjLSQJszKY3WIdwY36eQ2SRAkwlTSvjWRvvElBHNOPFkzYgGnGbUW9NELtlosjWgzrpznW/Z2Tvg0Ycf58WbL7A3nzF//HWI9wzLJcPRMYvbR5ytIn7e0+7u8sTDD/DGz/4MDh56GPG7ZDySCtI1aCjkotYO5cF7TEvRoDmRGisbzqXQBTWf0FVMbBy59+ItHnzkAcSZS9AEm2ZR1OZNzyZT87OaplIzCk3boI2jdZ5cHE1oIczYnN3lYH+Pw72OEBxOhK7tzO/zlqr6zM98E+obPvYbH2H/8JDdqw+wSCN5M7JcLigoq/WGcVjTqDDkzBf9obdcqgxcfvS3f2CzhWttugKaC5JAQsG1vc0/rg58LpFWMhIahhhJ6qwVXRWCR1y0GTRqsISqwxu/P945cMEcWoQgFul1bcvjTzyM94XnP3mT2c4+u1cPWSxPObpzm3unJ2SE6XTCg3sznvqMx7n26BPQ7BJCj0NIPkOBKBmJibYPSIFMpmt6mziBMO1MgLrKYVBSoXUwlIw6x97ePhJaKyJwlvAtSXHBGYSQRlQ9EWOIaVtHcg7JBVWY9B3SdpSizPb22Z/O6HwlOXPBfEvNnK425DTywnJtlRH9nF/76MfYeeEmYyp0VRs2kymd9zy0f5X5wT6+fxWUvkzbGaVJUOkUU21+iBniONKixJCIasygJSaCFhvP2maGcSTFRMmpTlNXclMqm4sQfKmU2RnNQhOMxtrID403XbwQ2o6Hn3gN4xi59eItJr3j7O5djm/e5GQ9ULqWSd/zmkcf4uHXv57ZlRtkekTBeaPhTkOiDx6aBsQxxEzjHKKFSWvNshifCOQIOdMFh28cTU6knAh7u4ylQEpIsenr6q1jGRVWY8L7TJeVEmwqvMQFk+kEkWAt7XlDKo5cRuYHB4xDw/PrEz75zLOU4YOcLQb6tmXe90wmHQ8e7nK4t8eHPvRh3Djw+z/zjUz3dujCBGka0+o50/WTc//1Mtflt2jtbDkklTEmOkMx6XNmNfZIyUx0OwNQKWm0uunRxox45xkb49DMKaJiwx2VDCVZZj8ltE4tl5gpIVi7fHAkhVYF7wI7e1Mee+p1/OaHfp1nPvIhljdvc3p0xFjMtLzm8IDPeP3r2b/xEL7fQbIgOeOaQEZoQ0sqRnDrHTjLUJtZFjPrlXoU7RojZKv03FGoHdcdmqINCPDGhueCJ+dMyqNVRAyJhRspKZHHgTEanOJyITm7l935nN15izQzWqfcOTFKpjc8+Qj0B/Rdj3iHC+av5ZLoZ1N+7Vc+wNMf/03e+PvejJ8aog+ChoacM417FfBTNdOeUHkDXLB0ilNjlHONjVSjZt9TKuTU0sZMCgnVhI8tYRxJTUOKI6mJlFGs7WkEX5ShSB23kUlAU6KdfhGc83gsAm2c4/r1Q9ZHV/jkr/4yp88+y+l6Te89V3b2eOObPoNHn3o9873riO/qpFRQB5ILrQtkZyPQMgU3ZoomJtNA1kwqRhlmM4kF3zfYwc+g9mCHlHA543zDOIyshw15iKzWa8bFikImrgdyLgRM2zrnmHaefjsV7GCfnf0rzA73OZ0J+3tzXnzxNveevUvfetx8jjhHiqNxqbYdzrU8cP0B4mcpH/qlX2b/2Wd57Rt2aVwH2wHdauDtZa/LN39NSxGgWJeyOEzDZAjJppVqqQKRMzlmhjTQFaNeTCEytIEcEyk2xBhxIaAxsQkDabDJnq4kNBaURExGohYVeiekECgp4kPAoez1HbfHxAuLM3JOzPspr3vqCR77fW9m96FHkDDDXDgljob6B+eRrsHngnNKVJuE1XY9wcMwjkxEiCWSSzHCj1UkDpFNHEmrFWmMNncvZ+vC2VJfN4G9+Q7d4TWaaY8Xm2Uo3jMMo7E3l4E0DKRx5OzohBQ3LE/vMvGZGw8/wsc++DSnx8ekNNILtr++xYnalAwnBB948KEHuffEEc8+d4vdnU9y/dHXGKEJlgN1rwYmPe9bQq0MUFcnldLiUyK7glQm4JQTbcqkMeNHowCSUkgl0sXIZhhJYyQ0I2007lDnAqML5sCnEecG4rgmZdOISGRY2ybNvUeK+WWaR7xLSFuYl4aHblzlyc98PVceeQLXzkkV9ii13LfGrhCMano9jIw5M8YNcRzQlFmPkbIZKOuRGA3oDcEh3iPO07ctkyt7dI90+NAwnTaEtkclGFoOFKeQCuIFxaFaiGMiLdfEcWC53rBanpJWp5zcO4N4jyvXZjz0xMMc7O/zkY8/yxt+7cM89b9do/HTyjTT4HyDYoHMJAhv/uzP5Jf+48hHPvhxmn7GwY0HaBw0TWcB0SWvyzd/obFBj2KjaxFXifgdwVkFQhYbalRcpg2Ka43JSwRcLuQ4on5DaDNNTAxpgI3Hh4D3AecCg/NQ7KwxbkhxRIdoAKvCWh1RM1Ii946PubeJlNIwnXquP/oIB699nDDfrZOqkvk2KSKjEjcbxjGS4si4ieRohLdxHPDOuKW66YRmMmV6eIXQtYSmoZtYeY/zDgmBxjmc89bP6K2h04kliQMGEIsoznsShrCTC+PewHq5ol1v6OdT1qcTFqd3SKdHLM42zA8OeeoPvZkX3/8rvPh//Bo3Hnsd+489AXi66QxwjJpxCL7r8Nry+s96Ix/9lV/l2WeeYbY7I+weIk7pQnvZIvAKaKrgzKdRG9zjBBtk552ZQjAH2wXU147cFAxURBlypkSPCw2kRMmRfmhYucAYBptxFzzN4IniGLyncY7oHHFjpLSboqhmwnBGXJ5y9+NPc/fFWzgXuH7tOv38gNWqcOv528Z/PiRQjNBWrR0eb4523wfcfIe+6wiNxzeBru0JbWe/dw3ZV/9EBBkTrnHWO1jBzCDG4ymi+GCmXcRoJEMwIUQh5kTJhaZtaNuONI/MxzmLSYu6zGoYGPIAyfH4Qw9xMIzMr8xY3rzL7PBBJtf2cN7hm5Y0jtZzqTaP5ureHuUzX8/TH/oQLzzzCZ54/RTX7tiMwktel8/56QVRz/Zasxo1YbG2PVSFoDaxIYuh6yKCVByq84XsPISA5EzKLb4JSNvQDg3rtqGsVmy84D3glKSRMQmrMqLDwFAKk7Xg8obx6A53bj6L08KjD7+WR97wFG7nKse3ztgMhd39faazDmkavHdM+0BoW3xo8OJsEFKxVqxShSOEQAhNHVVr0IIrNsFC24bOBzRYAtn7YJGqw3oXG0fftsZvWiEGnAmVLx4fatdNCKh2pLG1Co6ouEFZLk7w6w17DzzKzsHDzLqO3Qcfom8DwdeUWB1S3ojQhIYkigue6w8+wHqz4vZvPkO/8zwPv/a1dP5V0PjgReo4EFerOo2dLjgbNVaKkqv/It54wcVhhB6KNef5+oC01CmdhayJsWTimMgxUcbIuBooq0jeZNIqoatEXI9ARn0hphXL0zNKzjz68Gt4/R/8Azz8mW9gow0vfuIFXIHJvOPagXUJU2zUmzSeoMYI47JNWWiDpTqggpjiCGqRbRYHQfA1p0cVFO/MrxHFWO68N8dYhKJKFuOOd5UdTwJ4bPB2VuOICJ1np2no+ynX9q8wxgEtiVBZ84wdZmqaNDRGsySK7xpwjgzoWIzPIbQ8/JpHyZuR28/dpN+Z8+D1G5ctAq8AlwLWbCACojbQCDVEXBEiBY3RaquKsspWnJdyIcZozMQpUrIS04imQsoJoqJpJJSCCy2TibDxgTidMaRIWq3ZLGds1ks0DzQSWZwpMStdP+fhN7yeBz/jKfYfeIgUlTxmTp6/y+bOKcN8zmwyw7vmoiylzsCRxjRp8MHyfVvBwbSrlb6ABGemXrdj5Jw1QYiNeyvbeio1TvfgQMSS7lo7eGyWvVhndLKj6YPHi6eVYKPfvFVxCDZet/HGWuhEUCe1U8egAkl2OD2O1pnw70ymPPj4a3h6PXL7N5+ncw3w1KU+/0sXqpgTRazwTsdELNsRroWcCzElSkqUYuSpWqw8eFv8ptlK35zUdEwIhK7BiWfibIB3I56sylgyLmeGzch6sWB5fMTy6B6b9YKiI21OTNpd+n7O9MEH6PYPEFpCUPavXSOPymZxxuJ0RTffJbQNqI3fsEpNXyd8Wb25VAHC2UOUemBUL4YwBatYMW1m3PmocyZ4ahqqq3Oks5o2lpztOxSjU/Qesbw6Jr5Wveqa2tBaPzu7TAmOUJ18cyPUKg/q4fDBmYkuBrcUCVzbPWD16MPc/NhvcOeZFy5bBC5fqI6Oj/GaKdEEyBWD1yxyNVpFC/qtgtOK1RzaBIoXWicmSI0lUi1Ed+dmQzENqLkQUyHFkU0/0HlvwptsqFAsAT+uaXZntEUJEhhiYlYyoZ0wb3uCeO7e9KR15PRogbvSMul6XPA2pUuM392pTbRqqpAE59g+bueMNE3E4a2cEBFL9pYiIOb4b2OUKg8kMekTrWiR2vjfrIJkqffrbOStCMU7BOP1rHJr0WOtNqVWlaLW7CGCmXNVsni7J2d751rh4NpVxvWGe8/fvGwReAUIOpabCn4ayJmc8U15MdKy4DvryXOeEhzOB6OWFht41IoVt4k3VNymTBoNjxNHptjD8zZyY3Q1AiiF9TjQribEYUMcMtNmCjtz5GyN30TK6Yo42aWb7dK0HU3Xod5zevsuw+madbdkMpkQ2sZqnjDzJio0Ts+rMoFa2izW4uSkaqE6K3rLCe/t0DiMeD+o+Y6Io1MhO+NHLxXd3s6WaYqRlXlvTaeKnPts4g22TKgJuRZrLrEBLHhvGq6IMxdDpE5fBFFfCwuFedfDQzeqKb/cdflFel0wMjHvaWtdkQvearS9R52NoXXe1Q03513gPGJsK2hK7S4xbeZpqrazga0WkpcttUFMTLsJsZ0SwwpipGky3e4BZbpDG1p6F5i4QBsCvu1QN6H1gaLK5u4JeT2wGja0fUfj7FEktXk2XqxRleoHGWwC2dnjFHEIniClmkwbUJlEDP2nOu9ayGLMxEIwHi+FnLPlBgHnvAUydcRtwMzWdnimqlU0IIovnlybJlRK9au2mt1onGxudDm3p1Lxs735HP/oq6Dvb//KodVcVx1s1QO2RKntAqa+0eoLeBMoV+cll3qfDsGLMcFlxBBovPlj3qomg5gjWvrMdJ4oKdIIDOsJcRjI+/v0XYNvWvq9PdrJlLbtCG1rFZreUfQq94qSlhvGszVj19PPrTG1F4cWG3cVnKNOToNSc344vJgWLQoiAXHWyyjVj1IXLGDxQJFqOKGSm2PumP20ReygWBkDSaROobeAoWgxs+zsaKkTfM2BBrW2tCzmrLfiKM7G5EoWRLQWM1odfSuB0L8KIIWm62Bbl401G0gllUVsEkbeRoS1OzarJVN9PanyEsFT23cqRGSTzMWbXyVKcQ3SZqaux3kxFuH5DikOlGztXD5Y4VvXdPh+Qjdp7bskgAq7OzuQC6fcI8XE6mxJ0zbMZjvWO1ey+TtiwG5Wm96AU7piNVKiBpaqmOE0P8wmSnjxqFOQLWoOeGsCKYrtBQ2mnK0e3qK46o+pq8YN8zHVzGmiRn0Ijak4QGiwClWcccNrMSHLUvBqkWgnZra9v2wJeEVq1E1Fi5rT6s9PnglWdpXhpAbGRanCJecOPIYVkreNAYpJlGj1H0xDFDGcSFRs0kFwaNdR5nOSJnLWej1mnoJ3OAk4b21UooLTQNd5ygHEnFkdn5I2kfXZyoRwEvDBgn2vbqtu2brL6q1KNWOaC9l27oiVy4jRIQbniIgllV0dnClWUlPFpRp2CKW85ODVg1VM4Ly3vXRqUZ1DEfU2708wLZYF8dZFVDDsK4mZUUFonOP8nOurwPw5ESurkDp9qhRKFTJxgjqbmSxodSgNYdfzyAmLeqpZ2KLRuVQ/C2o5jQVopfoZIkKrBjm4FpuxVx1gERsyJNv+PzEk2xeHenukk35C3Nsjj4lhtSauB1bLJXSBSejZxnuKq9dbqLCldc/gyOQq/KbFRBSHN0feKS2G0IuzI6UKSDGw0sn5z4qzQ1eqEIgqBLvvDAQBVUdLIYkVFdYdrQfIg4iZPWearaGWuWh9zbbk+/KzNK8M+InUuqD68Jy481ksTW3DBHMw3ZYYQ8xh9VWLqZh5A8N2amBkbkmNuM7R40piBhc9eJ1aQ6eqdY44p1tlZ5rSfm3MvUVxzjOdzyhjNlMRI+NyQ9O2THYCdG3NElQooEZUyanxUtW0CK72+DmlVHNj2sbseOudHR62Js1VznWTxyJCI56ixnyzNfu5ovdbX8yC4oBXIwtR5ytwW85bv7yvQmpogn1HMe0tYj2L+mqI/mqvjDnoalzpWe0mi25NGtagiWMUOfe9HNt8oG79VEtxIHgxH6FW8FpkI3aanRqWpFsU3JmBLGolyHZCt8gS55oKMR9t+z58Q787J+XEZrGAosTlhqUPTL3HN+Y7FWdlPUHFzBQ2V0fU2rQKQocYUl59Hs6zDBYZbpHuInYQXN09IxVxSLG9MBOP2TbZ3oPgvN2Tc0KmkvA6E3Zvp7nWVWk9qNu9Nw1VuAgOLnu9In1/KuYredkOOTS/xzSDCUByRsJh1mfrK5mDWnQb1UjVVqbBspxjksaIJ9RWejN/1d0w76yCi0aAYZ9Q1PitjMOuekX1oSQslJ+3gu7uWpi/WpOTst4MuCYQvCeIr9rWtIqZYtMQOANAg8fMLs6mg2LXZH7XFrq0Vi63lfaaGrKqWRNah/lOkM99SYdWc1/zerLVznKRWoJaEaIVMJaaOrIUktdCpMIaly9Tr4Cmugj0zm28VyFXh9RVzRFKPWFYlLRVw1JJLmSLq6g56lLDanVaMRcTNNG6sdUZVaDFfDGPmcjsTMil+Np2fwEOuhoshO3nBM901qMpMeTEGBMyRuJqzRAc0k2MOcZVj6ooeKWotcFT8VoDanXrzuMqNoUadYfdq/mLW626dZm9CBGqYFow4EsVXPXVVJrJVKykqCDnucOyPYji6jcp4rS6Cybgnlry/WoQKtROY6plrRclVKZ4C1Wb1B63JGZGNBWS53wAj0WPcp7/Mh+qRkoigLNu22oQVDj3p/TcpbeHW6o51mCaQJW68SbYoZpdJ0pGaFxgMptSSqIsVtaFPEY2qzXiHH3vaNSb3+ftppuM1VXVu93mDM17tHSJPXBBsYldWm18wNUBmnZvhUKjFV5xWyyrEnq4iwhTMfPutltSfa3ganqpmFAWEXwlfTNCEQNumi1Idsnr8olkqw+gtQRm+6CpgJ6cq3R78K6aArwjUE91JQVT1fOz7nVrRDhPllL9sy25qpOt5qpZ/K3hqYJu/FGc+zbVOav+hTvXICpC17Tk6YycrJymFCWNibzekH2AzshbUUuzbAsQVY1uzddITupFqljyfOt1uu1hkQqZ1HIYt90vTDvbn2amtSa6UanasArYOap3caiotESCmI+FBT6+sH0Y1X24bAl4JXyqqmG2aQwVqvNNZZ2z3Tx3FtUy9o0WShVEO4kW2elWE6HnJs34Y7iIhrDvKdvIrgrR1vwUJ8YoXK+l2WoqERvIZKqwPlz7T5zQ9C1dnFGyjT/TIsQhIWGDd56mbarzYg67w8yyaDV9NcmrVXeqKK14u341bSFszf92B+3V5z4mZqJcdSHO8b6tFn9J9KFVI1exAi58WCfUdI+eVzPUiOWyReAVSCg7rfOJTY0HNZrERmwjtjbe1Q1V0XNBdDVKqTnk7f9Ms1QzlrFNKlwg7lY9CjVMuHCit4laMWwnV9+JCmJKqRiVOkYuAE3ZotQuwLRHcmajG7TybqVhZC1WBtx4q6Oy+M7VCLZUH6iCu9uyaqyLeVtmbQfBmHCqhwNUX3ArGFWbbqs8RKyAT+QiGmywQ2M5QD3HuFQMgoEaANVD67YCT22+uOT1ivhUZulKFQRA9AITrP5FqT7EVgx8faAZtqinCdv27y85fVnAZSpibKG6qxpDVc8F01dTmOu1bIlzCuXCMRYhUUtQZBtgb6NORwiBZjKhlMw4jpRSyKnghoHBCzoR+qa1h1UgSSVE2yL/cvF5oe6PSu0vrFqEWmVQ4Lxu6zwTUKPH4qpJr6/31Xw5IFEjYEzrq2z1uzn028/Yft/LdNMr0Ph3+ZqqmEMpYqpWVSpsUG+2yPlm5LL1fAzPaTC8ylftk8/9UqHIBQMfUEeQqOkGpfph5riqOVGk+mLBkerubbEZvzWN21ecp0ssABAxX0TUo11LzL2VPicDR0vOxE2i+BHvrDqTbS2V2j0WyjnY66ha04L7+oDtml0qFAehRoyu5hhL9bNUQOUiKyq1qsPVCNYXOR+G6ZxpwlTxeK3JZS2KZCVqqUAqFq0qsHe5HTWi+koA9ffX/53X5WcT76//26/7QnV/Xfq6L1T316Wv+0J1f136ui9U99elr/tCdX9d+rovVPfXpa/7QnV/Xfq6L1T316Wv/z94zgq6VDhDnwAAAABJRU5ErkJggg==", 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" + "cell_type": "code", + "execution_count": 7, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "WUHr4o2kROvN", + "outputId": "8d8f9b13-be13-47f0-a9ef-57ca143701cd" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "True" + ] + }, + "metadata": {}, + "execution_count": 7 + } + ], + "source": [ + "model.eval()\n", + "logits = model(inputs)\n", + "logits_np = logits.detach().numpy()\n", + "\n", + "logits_transpiled = transpiled_model(tf.convert_to_tensor(inputs.numpy()), training=False)\n", + "logits_transpiled_np = logits_transpiled.numpy()\n", + "\n", + "np.allclose(logits_np, logits_transpiled_np, atol=1e-4)" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "image/png": 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FehGpDyNUAWcV0sj0Mpx71NB0kZOTSGoNqTWIKLZIsImhGFvaVmlaJclBEkFTZXZPWTwQsJYkEybncs5fTXGJ486NwL3nDGkWmWw7ohGODwXfCFGgw1F1QtvC6lhZHimaCV4URelamB0F5vsd6+OOEJSjIyg2HeWOkOYwGCt5Cfv7sFr3F2qeG7SBUAX8oibMV+iqgcZjgsVIjpUSY4pP95V+1nbmME2zySm3R4CI2hbtWhRFRMkGFzn/mi9Gl89gBe7uCVdLgysgzTuWSyVLBWtgVUWe/XBgfqgs5kpqIcbepwqnf6IK4JeRp5+ylBuGzSwiFvT0nQUiSeIwiUWSCFbABkSEdiVkeX87UQvlIKOKHXdf6NjZgckYFpUQo2Ak4ruILRQTT69GUaIzpAbW9wLp0FFuBDCBzQubpANhNt/n2Y95JlPHZNMgrmX/buTaWsiHCWmWkZUVfumJQUgyyLaga5TJSFk3UDdKjB3zBXRrKFJFDKS5xVcB9RGXCM2JcnBPGU8ig4FggNgAUfFdh8QFRCEjxQwKxIL7HOxUZ/6K1iVARDUiKBoNXpWmbnA2JxkO2Hn9/8T8zq9BvU9ohVt3A7GSfodKe38jqpBY5flnPMu1MsmFiNA1SmqExCmJExxgBBIn3H1OmG5DksLoYiAuBNSzODpmOe/YexBxVrAiDC9Y4koJQRhejUQVjvY7jh8E2gh3H0RWtTCYCCF0WAtIxORCjIoBBCF0Chl4geO9gDhHUkZEGowUXL5meerDnv39kjJVbCqENjK7Y0mvBkQaXBKJWe8/ZaXDJQU2WWBTJT2BgxPoaljVQrtSiNA2BtMaqv0GmwvBKxhhsYQQHGWhxBioZ0L04BJF2gbj50gI2CgI8n9efWdoZ/6KwS/RGOGTbEhRjLMkgyEGARHK3dcxvvqVrG7877g0UlctyyYQBSLCbKkEVYrMYDplbCFPQRGWtVDmSmrAGiV2UJRQlAFfRw5eMGxdVjYvGQ5vKKEVlvOG+SyiUUlG0LbCCx+LnD8HNhXSCZiBMjkXKTcUj6CqRKvUQTGdIBmQ9FEqHkQsxhqiDdhcSUrLylvu34btDaFd1dy+t2a91yId3HnaM90y0GOCowPD9IJQbgmrY4v3SrdSFovI6HzvJ7lS0KhkS2U5FzKrxBS2tgVCQt0qJ0eGYqz4WnFA10XqRslLIXiYHfVBTGaFuFb8usWtPdFHYmjJyu6sIXD2oFrsfZToAxojRgzGOZwrEJuCcagkiBG2Xvt2Tm5/kNjcpmmV2VxZrqCqFVFhUirSKctjwQfwUZCoJKaPECVRUmPIUhhN4Nw1cGnkZE+586Swew1uPR/Jk0g+6H2wqMJoYEkL5eRIkbmwtSt0N4TReSiLyPUnDM8/1UeIYpRoIc0NYME4IoB0lKOM7XO7tPM9NK6xqWV94mm94juLri2h7ai80rZK1y1oaiUIRA/Hxw0PnrcMtxyJsxA6nBF86+mqBVmpuEyIQyFP4P5cOZgJWxOYDgzPf7TqL9ioLBZKCJCIYq1B1RCD0qyExUzxNWSJ0nVQNBFXK02c40NHaOs/9Pv8o9iZg+rw+f+NppqhAdJsRJZvYNIhzg2xyQSbTsmyIeVgi+lDX83zv/NPCG3EmX477kJkmCnWwOEx7M9gkPSgGOZw1PVX5CATxqlSZkIxhnJDMA62S+GF34dPfAAWc5BMMQHKDAYDy/jqLs1qSb23xB8p1nqyVJitIB85Bhvw0GOwfyBgLMF7lIB1GWpzwNF1DZIkrL2SFgXqG3wHYgEfabwQkppgAi6DkIOViE0FImjob0nBbHL/1pIiqUkzIIIter/RJmCckpaCKZQsF9xKkQi370UWVWQyEMaj/lY8yiEZ9O9XQuD4EBYHkVAJREVdDzzvBdMJfh2p3RqJ7VlD4OxBtT75CCFEXDoC7ZN2SgXdglDtQbqJFpsk2QbbV17Hvck5Vgc3yHOgVmIrpAn4AAdzuLAJ57aE3S0hxIgcC9pBrlAkynQi5NPefzPGkJSGS68Rnv59RYyAifhWoILNx0YUo5L53j4xKC2waMFOYTZTbh9ZJsuM0dRRTApsmhC6FV07A2tQybBJSRoHCILLMtTkxDrg/RLNhygrghO081irmBRcCtYIkoILp6BxDslLDm+t2RzB7ibEoBSj/vyIYBGMVUIUxMGoBGeh84pVyByUpSACiYNioCQl+KpjtQ8pAqokCpmBQSrkOSRF73emqiT1K+D2t1qvmEwvkOabODfCStZHfs0JhI6IxbsCsNg8Z+fqZZqTm3SV0rWKGjAJdJUgUdgdwfltOH8x4gawMxOeelK5fx+Sc9JHSLM+zWCnisZAOTA88YXC8QND1wmzFyJZIRRDg97bIy4DaSbYPJJk0LXQdQZXJGhS4t2IfLBFkif4eh9ZrxGXEiXD5iNQh9CRJBlojQSDKQZINSAxA0K7pm0XvfOsEXFAIthECF0fnRoXIcwR01KkFucC0DvyNu0z+jazeA0ED9b2oDEK2vWAGo4iZWFoa6VZKUkuJKXijDIZC5cuwWoO3QoGBnIHWQHlsPdDnaVPqZyxnb1PtaiYbpe4ZIhIAjaD6Amr24jv+tuEb9FkSGjvIPUedQVHe4CH4Pporm4AC0mujMbgMiVJYDwVhiPhxg24pIp6IbHQzXoPON2A2AjGCdMtqOZCOzQUeYIs5uQusDFWuqq/taQFfRK2KMhHI2yaY/IpyfAciROIFcHvoM6QJQUmSdEIIgnOCBpaGm0JJCSDMSSR7qQlxAKvHkkaJAomcdhMCNoRUDqFKJHhNGG8bTBxjRPQ0PuL0YC4QJJDNuyjwNSdgg1IDQxHQpIqbd1n5KtlX8ZJLRQZ7O7A6gSO7tP7ogJGIbVKloE46X3EM7YzB9X27nVcMu6VVEKDtkv8uqFZBrTap/H7FFmO7xoWx3c4Plhz977yYB8uDgUsWAddUIpEGRaCqtBVvS/il4ZpBmIiXdtnn1ML2aYiRV8PNE558UlDOhQSVSZTS1x7WATcFWWSwiLCyUqRdQ9c8pasHJCU41PgeJrlCd5X2PwqHkenLXQLJDaIBrpQY7XGZEpSTkncBq5WQj0j+D6apW77aFgspAmhCkQNdF2krRp2tjNUa2LX76a+6bPiESEEizWRYmCo6z7CyzPICyhyIcshLRVJBEkE30WateAygzVKnsP2LvgGfCfQB5+IgE0gWKX9HKDqzEG1sfsajM0REpAG8UsEJeAwxUUmecHR/Se5f+8WqKfuDHf2Dd06ogNwESTAViHszZSj+5AFOPaw6mBz5ChHJWU6Z1YFNrv+1pDUhnJDCSJ0a5hsRkgUWsvxDc9WGcgHYAIMtgzTGJmdljXqNmKlI2nmpMMxsT3h5Oh5YjcnHWyTbVzB2gHWGYhjop+h3TFdF8AUpK4iLzYh3cDYSNtOEbvAJiesuggoSgQEBYxRvIf9Ow32XItKn8ysvLJcAwNhPFTWy0g5cGRFR9XCYq7sjIWGPodblFBkwmCsWAdHe8JyDl6VwUhJUmHjnFB1cHwYiVGItsd3lgrRCXV39qg6++RndhWVDA2BGObMT/a59cyH2Nt/QD7IefyxxxiMd8mO7hFjxM+FVCERwTeRgQNdwwBhO+0/pJVRshyWK6WqI4+NYZD3meb7R8L5KdiFkg4FyXvn1Fqlrgz3b3l8C9tTJR8IxgomVSbbwrBWfIQuABZidcRqvyM0NcQGmxuCdqjUfbnJCtYMQVO6OhLVIWZMZI11U2w+wRhP9OdZaSSEY1wCIRdi7PCN9rVMJ3ReKQeChkh7qo+1XitHM4OdCNOLQr1WtBUSa9nYDMTGsK77grSKktdQRkhS7fNopk+SVi2sVsLWLuQDYbwNi8rQdb0bkWZCkSskSvc5kL0785eM6WW65T5Ht/4PVidPc3K0z/HBMScnLZzMyVPDpa0BUQMJQl0FtkvlpIPlGqTrnXRbCnkSmQ76K9GVUCJ47bBuzfltx517gQfHymgIsjS0t2CypRgHROF4L7L2kc4Jx1HYKKAYgCrYkeH81ZTDecSsO5B+NwnzYzCcOsyCuAbVQ4xJAUGkAPXEsEAcuKRAKGk7R9JVaAwYUSwVRiJJmaJW6ZYdoW2hEwiKNX0kpmpww4S6EVrT8uIhJFuOyxo53osc3Y2cv5BCV+O7SNUIoxRCA/USqmOwuQHb71bWnUbODwARrk5hNFLGEwgeXAJ5Di4VXAZjd/aUujMH1fGtD3Djw/8769VNxpOSjc0dxuMh5f37zI/X1IsDjuICjZ6BVS5MI1fHwtGhUq+ErhXmS+WoUkonjM7B5pYgTsg2+sLxnbseTEKagbVCVFCjeC+s1jAYG5LUMZwETrqIeuVwJWwslHxDSBKDE8eF7QxTlty9M8eHBiMO6Rps0keFkgaMa0BmiAzAZARtCPUB0d8lSS+DAeMyTDpCY2A9f452eY9meYJIyXC6Q7s+ZhkOiUuInWIRhpNTP8grtcJaC4J1LLs1y0XAmpTpNqxXkeOjii4qwzFc2VAGGfi1oJ2yOoak7HdpV+rpji9Er5wcwqXrMJpaLoSARkVFsFaxFpwRiuwPl1b6o9iZg+rJ3/pfqao1PipNG2g9XLh4ldGj1zm6/wL1YsVyuSK1ymACuxfAiTLMe+qHc5H5sXDrrnJQCdkABtt92WaQGoKJfOTDga6NjPKeP5RYKPKe3ZDkhi4qbQudyUgIVAH26oi9JwwnyuaFntsUg7I5TZivxxzPlogIWTZBZE2aLJBUwEFiAsSDfrcKAdUFNsmBBuIM7SqasIYoNKuaZl3jOyUpxqRZQWhOMMZgje9Dt6h0nbC/b9jZdTSt0tSBxA64NKppjwPH94RikLBzsUOjErxgUQYlmCDUB7A+gCZA6MCmFkkjRh0mCD60pKqIGFxmGUwiVhQEQuyBpCI4d/Z8qjMHVdOuCRF8B23rqVczQrjHax9/HdceepTD/Vsc7x9j2kBpoRgLApg5OIXplrC5raSpcP+jwmGtXMh6Got1ynhTMCnQKWkK5VgZTWEwgWRsSCcp9azh8LBl715L0ygtSuPh7loY3AIVz9YVsFmCRM/2sKOtczyGwWgH38z6W5x6JAo2sT3zgRpnBUnPEc0GzeoGbX0DdAT2HMaldF5pvYI4vFeq6oi2a/BB0NPQq2mVo2ODuoyHXr/Len5MATjryJzgV/Dc71VkY2XzPEzPCcNCAcGqEteKRigcJDkkFoKPtJ1Qe6FuhBCFNBUkGLrW0HkQB0nS75Q+WiIOJ6+A5GdfS+6vCFUhRGW1nHEyu8uV81e4mBZYeZbqYJ/MKS5XxAr5RGj2en8oLWDrAoxeUA5PIARIc0D7DzErhaZWkqzPKCe5YktwqWJdICnh/DWQVLh1S1gfR7wBo8qtSkgODeNrU7KBQeYRk00YDzsOTlqin9PUcxCQZEDwBpPmlJsPkeYZ1hq6qkC0wDQtUZ+hrY7JhhdRI4QYiMagjWJMQUgSmnaBDz0hsPXC/ZXl5klKIpFrN4+JXY2NgXq5ZD33pE5p6kjXGtoK2krZPt8HGs0a6kOhPYmMMkM+VmIC3VrxjeHgOHD30KGtZRw9q1nAeWhaaJ1Q5P1niDMEKRBz9srOZw4qI4qTPt+UlsJ0mrG5NaQsIo0/psynXLl0jcPYIN0MEwWTwWCzz/zSKmYM5SbsbsFzt+DmDeHRx3t+VmIMZa5USV//y1LFub6cgVFC67EWTA4XHoHty7B/J+HOPVg00LWB2/PIzolhahK8QjIYYOtDbGlZrRdUswUmEdJRiSsGdMGDyUjKq1iX0WlFaCNiC6zNEQ6AI2CMmBZtGpYHNYOtQFZMCPQFaR8D8zrloLLMvcWI4QMfD1yYQkZkeeTRKCQG0J4psZrDYi6sjmFnB3ytrE9gmAnJWHEjkASaWlENaIBl65h1Ay5IhdJi1BOlf/9RYOQUrNC5DXySnjUEPhd8qp7AluWOzXMTNne2GZcj0rQAlBAqbCLsXrmCPgh09ZLM9f7Q5jXwS0GNkg7h4dcK85Vw58XIdCKMyr44Oh7BcmEohwmLhadIAqkINIrJImZgMMVpzgvY3Y3kxnLzhqBlpK4it16YY5MRR/M1Gg+o05LQCaujBe06kg7BhCXOpFiX49tjgt/sy0Gp6+855OQkGJeiOid2Dd36iGZR0y2hdge40mCsOa0SWB6sEo68o0tHWJdyrGsuyBLrFJMr3TLS1n35xJ7SfbpWmR0IzVLRIGQOdi9YkklEjCLJaTRYKzbA5bKlDoajdoA3ymjQEYMSagjOEQWcCCYZ4ZNLZw2BsweVc4LJE6YXdzl3/jJluUmaFLjEYUWgPiS0S0gL0t1L+OM7xPn69IqLpJs9pdNE4eJDMNwUXvyI4d4Lip4TpiNlmgijq3B40vHBZ5UvvHpK+4g9qDUodSu4IgEHpu7QDEbnweYJ8+PIyVHN4kFLMkjYXzTEpsN3gqpHrGIQJLRodwjJkNDA8niBK3Zw2WVcNoUU3GhImm1SLU+oF3toXRG6nt4SqiV+LeAbQheomoST1uHTDdLyIoqi3T7ZKLK5O2W8WnH/mWP8WvEBkJ6Y6HKwKdhESAfKqBDKkcE6IaonIFSVMj+BulIGeeSRUcNhU7A/HzDdWJBnAQw0Niem4LJISAxt+tnron5aDJz1CyaDhOn2ec5dfIzBaBebDnGuwNlAYgTyMVR30HZJdBYjsDyec3LrBGtbJtP+ljZIDTEqm+cseSrc/L2O5V4kt4bQRG7twf2ZMh6nPLvvGRTx9GoHOR0q4RJBxFF1kb09OJw3iPQ+WuKEF+9CMeg4qcFmAVdY7MCQFAaXJETtiF1LaGYoS1wcIjYHDjBhTbt+AGogDEEDeRpoXSCGFbGD2Hja+QlRhfXKcu8kYS0j8o1HcINd1ssDnL9Hq8pyFWmPKpomwmmZRoEkU6a7GZOJI7MdmVNoO5CAj6Ap+AiLE1gegUYhN7BVBtpqydP3NpgOPefPLclSgyZDTDbAuQPUVtTm7CdwnDmoLl1/M6PxLoPRDmk2whqHcxnWeozUWDktyjb36ZoZ6hyjJIdsm2eevs8HnzxGgnBuQxmhjIfKKPfsbkTaFHwT6RSsU3Y3DcOppVlHGhe5NzcMGsWeQCVgk44kiSxnyqpS2qAYZxALXYSjWcSsI8YJNihqIlIKLk9IB7sEr0RqgggudbisQGOkXd+jqhfUfoGYnOAP0abD+rSPNqs+WFHT75oRw/HSsd8UmPFDJOUFOiK+mTNJWxbLjuODOcNQE6LQebC+Z7XWrRDw+A6mQyAVuk76i8ec3iIroWshiYqzSqKCFeXCqOP2esHTtwvSzLOx2ZJKRO0YsQ3OBJz5VGHZ/6t29qB65E8CAets38BowEqCWIuYNSaCswkYwYojuBU+HTC2S970BWOG41s8+bEFd+7MOJdHpkVgMO256/5IWO7DJIHhOdChoW0bzKZjUSUs15HlKpAGoVG4fydgbCDL+74834GGSFaanuocFaUvskZAY0SDgHi6boHIBJtcxOUlLuv5VV17wHJ2E9/O+vS0bZHgCG3HejGnPqkgKslQcIXt27Aqw0FVYiaPMphcJIaGtpmT+TlbG5GmU1IbMafshSqC8YK2SttGHhxDuFEzLAwXNqAcQIiRpBSsCqtVz5oVA2UhpCVkuSEdKpOtFS8eRp67VfD6NFImFVED3o4xJiDyCsio58UAScbY2GBM76RaMQgOY0qEBolLJKbY4WVMO8f4NRiHn99m59wW/+BXj/nKi4YsV7KRYkd9t3CSRtoKOL0yu3mgiYpqpLMgheXoJDK7r4zHBi+GRSWUBEZ5H9JH7ZN+JjPEJhBq0ASM7TPUwUCwgdCsCBqwpUdNBCeoTYmaoAJIRgwQ2zWhhdgKXd2BgWwqIAaX5Iix1CulGIx5YntI1t0kaY+4E2p8GRhlDQOpUG2pltD6fhdVD16hben569EyU6XMlSQT1kuhnveO/GwmBCO4gSfJew5/OVDysWBLyIcNT90zvHgv5+G0Jc0iHVukzJHPQTPpmYPq7tP/liuveSvZ4AIqsU9aikMAUUFMiw0KaoiquDzHtoveIRXPaPkAwVIXBZIuwfbRjVowpTDYVXQPohNmR1B5wSSBWh1Vp8znwsGxcmc/chgc2bDgsqyxJpCkp+AsLGlu8DFQVxAaxbo+ex6tEEKCuBFITgyBpt4jyoKgC9COto79rqYtvgk0FcTWIAq2jKBCDIpJMowr2BhW7GZzzhUfITMVTd0yFWWOg1jhY998Wjfgg1AmMEj7YrcFSlF8EklzyJM+feI9HO0LuhAOTk5LTxNHCAEfBHyf3jEZbA2Uh6XmqVsJrWzx8PgKub1IkJpopmcNgbMH1fNP/jZNfcS1176V0fQxknSKmAQRCwiiNWIs4lYY36JhgSkcjUSQyPRywp/+ExX/7n33+bw/llFXNV0tfVTXAKkgJRzdcNy8Hbi5hDq3hM6QGcvmyDHdDMyWHbJUmtD70k2nYMCF2POVQkCcko57vhZWiQqhi8RVh80qbA6JSxARum6BrlcQI8vjFSIdNulvUWGh+LbnoEfTR35pPiDNJmShIUlaNpOOVFqygeFElcEgwRjLySolVJGui/iu79UbFD3Jrm1AbN82H+gJduoV3/U+YzTa06AfRDYGgfFACAYiik0t1kMZQFLY3oocLTtemDmyec6lyQCfbYMpzxoCn4OUQibMF7e49ey/YWfrOucufiHJ9FFcMkEkQTEQc0y0iFQErQFDVpzDmxxsyZ/+astvfHjG7z7X8ObzMH8SLl9WhmPBDSFRw/FTkdsr4UMnCXs1aFSKxPMFV3IeOTfGZQuStOFgVRE6Qa0hBO11DAgQ6fNHqcWlFqRDovZsBR/owpoQWrwX0tQQJdJqJNZKswqYnH53CCAtaCeEUwdNVTB5Dm1kI6/IFcJKUNNQLy3RJ6y9YyYZB1WOCw6RJYaAkX4nMgJW+qK6s4rH0EkvwFF78KJ09Dz+o1V/q/RERoUh5hmWlHZpyICyiaRFy6VznlW3x/6tp9jO5wy2zkH+B48g+b+EgbN+weF4SlGMaNZrnr73H7j58Q9w4aEneOgNf5pseh1rMjAW7XKcBZONCO0MUJJ8QjCejU3Hn/+/vYkf/19/i61gMEG5fRPe8HnC5etQL4VhLnze9YRP/L7QLjsalKoVfvdOy+TqaxjlKwpuM9GWTjI0AUzHqmqYr099jlxJi0AqSuKUaBShV16JAbqVRyroTCScgiWc7niJGtoqEmJPX1YFH/r2MpemCAMWy0C6bLgy7pi3kaMOjk4CFy5YfPTcuu/56J7y0CTn8tCSNHPa4LHSJ20TgSSDJBW8M8Q0ZekTDteRoAGxwroVou1ojdI5Q+MyWoa8eOiZPb8maGRjZLm0U3BhJ3B5s+XO0T0O7xwwsp/ADc6dNQQ+B6CaXMFEWMz3Wc4X7M33uXHjAUcP7vDaJ76EjctvISnPIy6B0GElwbgM39UIBpNOQCN/7POv8cjDz/DBe3e4ahvuzITDVvmTQ8NkG7ascPvmNsfdAdOhYe6FpTcc1YGbs8BbHruGRM/ML5jVkYwE4wL76wWHqw5zBEhgZ6Rc2VW2xoJYCBpRBBVDiBF8X6/zvm/bF6eYtC/YGqVv1jjdKX3oqTg2HxAa+NjNNR9/vubqsOdwTYcJg0FOdxQ4OVmhK6WtLE+3SuIKtkclxi1xtu/nQ4RohdoIq2Cpu5z7teHOzNM3wRgGqTAqSibDjGTgiIMRtrxAs/I8vf8cN+8dYKNnXEYe37F88etKjEs4mhsuNA0uu3HWEDh7UGX5BvXskLpaEXyLqlJ3LZ/42Ee598KLPPqa9/PaL/wqBuffiDFF/0UwwFoIXY1RQAxZHnnHn36cv/3375PnloM28OTThqWF//tXR/JR4A2vecATN+DXPmoYbF7g6tZDzA9vc7CouHO0piDl2cOOZaMsY+Sx3YJ0OGAzgxACeycrnt2PnNTKm65IHyGaSJYbOgyKB43oaa+eGBDtlW1iiH0qQk+VWlYQA6STnCQbs3/S8XsvrthfQDApo0HBpe2coS65fWtNooGtXHjdJnzsuGNlRzz+0GW6xT66PEYWoU+K1rCqLAfB0NkOm6ZsjHLWXjipOmbRsojbaCxIaDGt0IYlMSSMJhsUq8DJqqMOCSf3KjoV3vDwkI0LGyxteerrnq2dfUbdDdAyMBrXhJjQdDPklM0/O1zwkd/+PQ5u3OONX/o0uw+9iWiHBJuQZgVEj7YNEiFq4E1v3OaL3nSOD/yn25zPImkXubXv+P/8jpCVhseuGf7461P+w/NQbD/Co6/5Im68ULD34ON84Knn+PwLGelowmg64fxwzsbGiHNXB9B57j44ZFG1GCJbZc4LR4E1oL7j4d2ERx7ewmignu/T1queBgXEIH3AAEBPQSH0TnSSQj4pCCblwzeP2KuES5cf4uq24dGNFrs44Ph+TawjSQlZCpdzZTROGG4PeOoAYjPicpEw5ISmWzNbw34w2NKxO82YlCkmMbTBMFspzx/UfOz+A44WBYN0RKwC9w4PmFcdjaaEpGT74jUG44scH9/l9w6eoRwp492EVZVDMT5rCHwu8lTnKQcPM916jAtdy8nshFvPfZTF/VvYtsUGOHz6Hv/HrV/j3MMf5MprrzC9dJ3k0hdiTUrUfTSu0GAQIv/zV1zgd37vPgugFiVPHU/fhWeOYf27lksXr7BkRh6U+cmMk9khi1YY0FBmQy5tC4uq5tKlc+zsjBlOCjQaNs9tc+HiJnfuHLKYzVh1lv01NEG4v1CaxPCmR0ZkxYpuvib4vmVd+hQUQp8jwisugC0ETYVGA8/fXnLzxHL12ut4/ELOw+M94tEhq3WNM4raHqBd6LPu00HkeLnkg8+t8ZKxvzPgC7Z3GY7vMY4daVIw3CwZjxLUwHzd8eB4yZN7NU8ddPgofN4Fy2Zp2F92VE3L/klNg2e0vc3WzlWGwwuk6ZDn53s8u7dgPDykqht2eAVQXySdokFQScgHkcub19jaeYw7z7yfvY/9Lma9wnlIqpbjT9xlces+117zFOfftKB86M3EaJAYESno2iWXdhL+pycS/uX7DY9sO1IXeOYkUEVh2aU8WCeoG3D3zgvsPbiFsUISPJfGCVmZcG5g2Bp1XLy4wdbWFknaR6DluGNjZ4PLl2Yc7e9x79ZdtmYrjpqUm8ucjz3ImZZLLo4NtrSYxqOdEoPQtkLbQVMLGvsI0iYWX2fMjksWbHHpgmVn2HApO6A+3kOrFmMj5rT7OhqhDkrrIek6hqPIpU3Ls8ewt+x4sch4w3TM5fGCkDhs5ojquH3S8ft3Gj5yt+LBoiO1lrdcHvD6C0MiHu87go80XWTZremO9kjSMZMpNG1HiI4784B5YcbVWcWjvAJufxAJsQPJCCrk0jHZvkwxmDBOCk7e/+9JV2tShC4IJ0fK/RtzxP0249WKyfU3gyZEApGUEJXHL1l2PxYY2sCDeaTqHLmFeRu4e/82bfA4iRgRijTnyiRwaXcT43LUK2li+6hOIy4ZkuRj2naOVU+aWpLSkmWWjb375A8O+MStGYujPapzU5auZb6C5UpYrC2rygKGNiQowuZIKFNDkIQmZrgsYyIVGR2Fdjx4UGGjIzGKiZ6gES+KEaVrYF1B13WMmhlXBiWVjxzU8PxMKLMRb7nSKw6uGjg4XPF7N9bcnEWiCA9v5Ty2kXJtZ0hUZbaoqeuOxFnK1NC2HbPjQ2bLFVubh7ikYLma4TRw8wgShOn+8swRcOagmh89SdNUYIaUxYRMphSDi2Sjc1x4/Zcz1IbmY+/DriuiRkSgmcOtp+dckmeRcpvB7jlEPEpK3Voab3FEJhZueEuaOpa1B1WqrkLEkiSW1ML5Qcvrrm4znG6xajpOZguKNKU8XtLVLXe6+6TDc7z47LMsFws6MZzbKCB2HB9Hbu4brIXcGW7cazk8ABj1KQPfUhaGcZEQnaXthFFhWQVhXjvEWPLYMXItuVWiKt5lxFhQ+xYJDc52YFqqJrLueg5UPwy1ZUuUS0XGohPWPufpY+WxcznjLCIqzOuAsQmff61kMCgYpoZxKkSbEiJI4nGmZpgnDDLL3onjxeOG46ri3v0XSNOUwllaUVaqBE2I3Sug7f3w3odZL9c0bSQtJnD9C7i29TjiRsjYMnndl7M2nuaZDyHLJeNMaYJwcBh58SP3CenHyDa3sc5z9/4J/9v/63k+8VzNohGemSkHtSFPLFulIXGQyISmrTFxxdWtgms7Q5JswJ0Hc1aVp25qEumoG+Xeg32i3aSuPoH1Su7WXDuXIO2UbFhw6fKU6eaAh9YVJsCFjRQbG5r1itUyYAYJo8JiXEajQhsdB2vD8dJDDAyywMB4XFCC9jksVdPnE9ShJkHyFJusaY5OqKqOGCFzQiYR07VcGwLO8f5jZSVbnKwPGSSgacJgY8Jrc2VnY0wxHOJchgKd93ivuHVN6z0+Bs5vDhmXOXm24vbRir1loG3WdJpincM511cKwlkj4HMAqrZu6NoGAmi7pK7nGBHUjVCTYccd+aNfTEwd1dMfIK7mWKNMcljVHYu9+9x/7ll+/8aMf/Hvb/LIOfhTjyofeEHZqxPy8YRhOWLgjwnacbTsGZe7Y8PuqEAl495BBRI5OlmB7cG3Pq44qYXXXJtw64VjjmrP688PsdrhYkfhMspBSukihRFMNKR+xXK+JARhPMzJip6j3npYzBtunzS06kitZZxGNgshOxWFRRKs6fNZURXRiIhBTIotMtJRIG2PsQbGed/GXuZKkbS8cSo0dsSeTthfzbmynZOmJecKw2YwKClqBJMmhM7jXErU0CvCBGXRRIrMMhzmPJJlTAYZxYMl905qUGWcJpSpIWrkZP0KkBLyvkWMUAwGDAfbZGlKRJGkREKKcXNkuIlceg3EwPz5jxBXx9gMcifcO6r5f/7TD7O2Ce/4M1e5XC74nX8/Y9YaqqioQiENbdcxazzBN4xSS5n1euG39mdUbSRNEsQk+CjkWQkCmxNhcXwLm8J65nn2/gnNpsMVCUWINOuWqmnwbYMNLevGkwjkiSf6JUYcrRruLJQ7B5G2DSQJTNOOSWYwWLApRhweh8aIRbE26UGFxxhBjKWYjBFpyE3NZOgQqxRlinWBug3c2TvixuopLl8XNN3tpXBixFiHx7Kumr72mOSk2YBYedbHK2pKTtYVR6s1eW4ZFAWbG1NsmpGmJ9w6WFM1NYW1+Jj2/PsztrN31FXIyjHjzUsMR+fIik3UpCQuJRqLdg7JxujoIuUlpVPD/Jn3s15VvO9Gyr+/aXnTa4T/x9uuUuZw/+aavbll3fXLHYQV8+MllVcWbX/7uLw1YmujYFa1nNSeLgoZYK0hTRw2GZLYSGgtdeMZJS2bZd9qH6Lh3kGDuDXbk4LBZEieZezdPWI8LJEY6GqPj5FuDTeOK06alDwrKFPLpFC2CkUIBO/p2r6FPWivCSoiOGP7JKP0t06TJFhTkmeRlBOyIiHNE0gSViv4wK1jntvreM3ugieunesLyiFQrVuiBFzusDalburT/ysOT9Y89eIeR5WhbjxBIQ8Gr4EsEYq0ZGvasWoCs3VH7SM+9HKOZ21n3/iQpoy2HmK6/Rh5uUtiU3AjjDEgFk03e+K9OlQjyZbnIx+6zW9+6JDENfzPb6x49GKkzAKhrdnfr7h9FKi7hDoGlmuliQFrHDHCxZ0R25tjOlLm7eqUVZCTFAVpUjAdTSnzkrqe4UOvQHd5lPH4IxNu3pvjY8ewEHwL82WH5RiLMh3DaJjRdg0hjahm3FsYlj5lODiHY8bQtExLwRpBsRjpdRya2tP5GmMtxqXgCoxLekUbm2Kd7ZX1NMFo0hMFTcL+SeQ/PjPj9241CPDGKynDIsHHyLr2HM5q6iYy3XJYYzk5WVE3Lc896Gh0gGQP89zNj7GZBcrhCFcMqVHmy5rENAzzAQ+dMxwvKhZ1S+0jzdm3/Z09qMrpDtPtRxltPIxNBuTOkeQbYBxWDdHlmJgTM0PdrPidj7T8p7ubfPnnH/GF59dECzEZEkNLU1fcurfgYAGLuqPG0mif1c6ccmE64MrWlLQYsXe4oImCT0qcK0mzAaihbjq2Jzlb29usFsdop5zUJ7QqDIYlWVixqj2TbE07V2aNsL2dURaOtqkx+RhXWtYNrE9qUiekrmUsK8ap9GWcoMRoCUGIwSLGYV0vN6naU2rEOIxNQAwioGGF75Y4owiOo3nLbz254MUjxSt88UXD+Yml9Q0hwHrVcLRoSLIhVRNxTpitPc/cmlP7FEkV6xdkBjbKFM0LJpMdFusF2ra0UQjBsDEZ45wlW1YIgpdXQNv7eOsRJpsPk5fnWM4fkGYpzpV9c5qAiBBRjLE0tWM8nfKuv/gW4v4SrTpSZ2hkynq94vj+MfP9mhgcbQBxhrKY0jYrnERGoyGjccm6aamaDqLFJRkuyam7SAyBGCJ3DvfYiQ3DPGM8mnBCRpdF1gcv4giMC8Nx67gyhLoL3LrnGU4TrBjq4zmTUclwusn1K1Pu3T/EdsekpiUEMESIAQ0e31naaDE27fsBTZ/T8mp7lqFaRJWuaYn1DBca0qHFo9w9aDleQYhwZWz4wqs5qoHFouZkveZ4GTHZkK3pkK7znMwW3Ntf88JBw6AQlsd3Ee04N3DkWYI9bYuTuiIah29qqsQwlIyt6YjpuCQxSuheAUKyw83Xko8vo/WKO8/8ey4//Eam9FwOQcAVsPaI8Wzvnuerv3JANd/naL2NT5ToLd3JjPXyhGc+PkebyEYWOeoylhjWqyVt13F+mjAuDVY9jQ+s6haPxcaUrqvw9ES8mOaoBMaDnNREElpW9Zrz197MYu8umWlJXIFmjlVYMclh77hh/0Aos5RpmVEIyMkeRZJwZSPFx5Jq1dGum76VKvTS1BGHcUkveG8L1GanImMGrwYJEYktcX0AzQEm7ei6lEQyVh20CM4GHt8yjEqhVWE577h5GDhqhN3dDK+Kho7DwxVP36vJ05KHBw13Tc6itYyKCC5FbMq6C7ikpItLmi4yLgw+KMMsxaWRyaAfs3LWdvY71eQamU24f/eDzA6f4frrv/r0ivWISfueIoEQGmwyJMYMkxaIHdCsbrLcX7B/Z8X+/Zb1KpIZ5dGxEvG8WAsiyiAxbAwKyjTBJSmttlibUNcdVTMnzQaoWnzwaIwktqSuanJaUuPZsAt0cZ9Hz+8ynzUY59CupQ6e2X7D798PvOGy5aHdAWmeI4CPjvXJmi7UZGVClgwwRUqsA+ogBA8hwaYZgtKJ7bstxGCMRaUjqofqBKkOGbmOSeIoA9gqEhJohsLNubA3C6zWkWzoqFvlhYOGRcwgXTPNIxup4oOSJWNed2lM0jygyIUX5oKJSpKXmLREXE5XLzHBMyhTisxRtS1FashczyEzvAKSn8Vgh25+i739p+l8R5aOEGP6CRAKGMWYhNAssMlmr4biCnwn3H7+PvP9huWsZ2iG2JPeCgKPD2A3U1YmY62CZoHzGwWIIcFjTmm0MXQsF4Ek77Xb56s51ipqhr0UYVuROWU382T5AK2EJkRC9MwWNc8ces5vlDy+CwNmxKCo3STNM4wbcTxbsrfq2wWKNGE6STChj/585wmxjyiNgFoBDFY8ElpMfUxSH3LeNuwaSyG275oxsDOA12Y5hzvC3S5Sx0jlLYtg0DRyYTjk/CRBvedwXbM/i5zfGJFTY9KM8WTIXmyZrSqu5hPq2KCtJ8SKxERSZ1m0XT/+RCOpM1jppYXO2s6e+mITjhf3WSwOiSHAqVSp2LwPsWNEbYpoQGixRnpBi9igviVNIoXr/S7vBa9KYoWR80xTj9Kyio71sKDMDE3oSSlpmlCoIXMtq3WD1nOaaMjznHGZUyZCqhUWz9ZkymSQICGQ07MGVouW2SJy5VzJWx4eUBYJNnbQzTmZBySfEm3OUXCcmISBAARMWpDnGUYV7yNN1RHagMX05HitoVmSNDOmsWXXBXY2huhJQ4LDZLZ39INhkA5IMphq5HbXsK8pm9OSt4ym+K5jVVXMKs+DWUdnxnzeI48g9R5oQyuBe7MZFyZDZssDVFKyJEM00onQ1IEudGwMchKXMBwk5GWg0VeC6ouvmc/u0ayOsVZIEkevQNd3mYhJsUkJNkGM7ROGuiY2CyyRzAnBKhWnY96CEOhlcPIUEhQXe9F7UPIsoUwSchcIPrLyvfRP5yNGA85A29WczOdcGFnSJGVrPCC3Hav1jDZGmrpiveoYlRlf9MiI0SDt+8xjQlWvqBYr6mXkUEqaaMkHyu7WhIEYxFqC5LQirKMnSEZMPRo6rF8TmyNcdcRV17E7GZLKBiYG7LjspzOEto8Mi4IOJZGUUM2YRMd8Hbg/m/Ng5dmbew67lFCt2ZlMuXxuys6lx2A5xoZbIJ5ze55ieJ7Z4R0yu6SjoWoDdeXpQkBFKDLHoLRkRYlNGtLPwWzaz0GZZsly8YC2XVKUE7A5Kr0vBIoRC0lKK2BjjbFDTAx09RzotTqN6TnfGiD6fiSbt2DyfvKBVTj2De2qZWOScX5riE3heLmmO+poOxgUvRi5c4Ysszjn0BDBpmxNS1IajlYzqjYQNFCWls+7PGI0yMBarE3oWuVglrJoLR99UBHTjnM7Gzy2NWZzaGk6w6KhV3WRFLCchBWL5Zr1aklTrWiqFZfwvHaiJMkaG2vSbIjJMtQ6VDykUzQdYxb3oD0hTSyFQjJb83v3PWtNmGT9WBKTjhmOBmztXkEwrFcnlMxIC8fFUsE21KYjsQYToXCWKmnpgscZ1zM1XK80mKTSN32csZ05qKp2TbU+JoYOMRGNAVEPmvZ5m+ixxpFlG0hsMWlORyB281Pxrn7+n7GA9h0liQjmtA1cCijSyLCuaGjI7RhSYZ20LEXZmYwYl542RoIKsYssFys2ipzZbM54YuhWSusb6qZFxZBJ4NJGwXhgiApODW3TsX/UsWotHz+O7DfCQCNXJynbI0fXdZws216eyDZYVxDqCscS2jV39mfMVi0dyi0P43XHH+sCvvGc21J0cUKSW6xL0cULVOuOeeN5UBsOsoyA5em5J9qCbQfOrClcwXSYE0PFxvYVHtz4GKbZRzNhtm4Jre914guLs4YgBrrAIE3oOs8od4wSS+4Mae4YTwqywSvAp2qqGW0962Wos5QYWkKMOMLpbmUQjSTZGPwxMXp8O6OpVxjbi/PbRMgKJXhIo+CEPrHYQLMCN4TNXFmxxvgKq8LQRmQ6oMOwqBrSLKcLgbYLHC7WeN/Stg2+s5wc7LOqauZVf0uu6sDogmAM/ZQrVWYrYX8VeeYwsL/uSLKUL7x+jqvncpazFfPas79WqrbDpS1dXGPV8+ilETtjh+vW/P78mKM6UofI/7sSKoGrecrJnYpBYQjScVJV7DVwLwj3o2GNkriGJLEUpeHRYSAGZW9VMBpv4ajY2HqI1XrFfP9FBpMhic2oqiMS9RiF8WCEMR1d7CeCmbpllDoGmbAxMIxKR1lkbExHlKNXAPOzreeEbklSDimG22j0aIhEiafhdd/+JEQsHRrmNIt7NFXdRyKuZ0cWeT8LOAPE93OC1w1UlZA4KIcdwoLWl6gr2N0sWXvLyTpgxGGsENQx2pmytSy5s3fM1mRIt97jWACEPM/Z3zvi3DRnVDpyZ4BIXXv2TwzPHAv7bcQaw2uvnOf113do6xW3Hiy5vWjYr3qBi81JyoWtEVmZs7dccbx/wiS1/KnXjJnPl8TQMhlFCpTlKuNjy769Sy1QJpy7nLNdpKRN5P7hmv15y/6hZ7AULnSGmc+JdkRKzSoEvuiRz+fmU79NKgZNJnipOVh2aLsiSQ8YDsckSUpNQjRrNCR0uWNYplzYGTPdnDCZThiOx+TFKwBUzXofNR2DyS7j0XnSbND7UfT1sagBox6JDaoey4L10R26th/UaBCwvbpe5k7n1DVKVQuhgtj1/XVDA0U6p9JIM3iEZDRgpMKgdqyqwGyxYlgOyIqU+ckRl6YZiZ9TpEOctSRlweJkThsjV7cceQYmTWirhpNFxrNHHXu1x4rj0vaAN14Z09ZLnrm94MZxw/OHC9bBszna4JHtCwzGffpisQ7cWXR84uSEL7hY8vh2RtlVDIZQB0GngXQcsCmUo4TBYEg0CVXlmR3XZMOWi4WynhjurQwHTY6aMSasWbWB0XDK3sEhGiGWO4R0ys2956jqQNp4EjlkkCrlcAujApKR2YgHdiZDdncnbOxsMN3YJB+UmFeC5HVVH5EVmwwnlynKbaxxp453RFRPO3gjxiSoJmh9QlPt42w/9aDv7waTCS4qqVOChbRWpDkFlVdChMwoo7QmCQeIDkndEJ9YVuvAxmTI1iRjf++EYQpt0zEdFQzzFGsdEeVktuTctKTM+vC/bVqaWrhxGLi3jKgkTAcFj54b0rUVtx9UPH9Sc3tWU6mQJwXXH7pIllpmdcvhSjmZdxwuPG0FH7tXsfmaKVcGSlPPGG1FElszKaBGaMXjm16pmNozscJww1JF4biK3GoKMBM01ITOo0aZreZ87BPv4+EL1yimlzheHnHveEEugdFgBKzx3nN0eEBUxQzGjPKEYpCzsTFiNJ0wnkwpJxNc1ieiz9rOfqfqTihG5ykHu5hkSOtrTOjVUPq2coOK6YdJSkEXD+iaGSJK1ylt3Y9uldNpWi7pW598gLyDsAKvppff6SBPWsr6HpWv6HTIeOs6izSnLApu37rD4cERRVYwzvvo0+UGa3rZ52UN28MUY6TXWgiBoxncW3U0EYo05aFpRmkT7h/WPH3UcXfeUIdAYixXL15gYzriZF2zblbM52v2ZgsCCdlgwKOP7TC8tEXT7JHNXiQ0c8h6wZHUnKrl1RWmNb2acTag0YRqHXjQGlo7pAgz5l5Ik4TJeIOqbrl48SqJKcjykuX9m6yqlpOqojw3YDMvmC8qYlczKDKKvCQbjtjeGrJzfofhdIdyPMHlJdbYvj3ojO3MQaUEBoNLZNkEtSltsyINLYIhiiImQTWezmixqPZ02KpRmkr62cASSZL+wycRUqsMLbTaR4Ux9D+v2j6nVWSBrDvGtwuCFejOce9IWM8PmQ7AtxVaB8pRhostXRMxAovKsztoeyal9uNE7i4j95aCF8tmEhlbz8mq4e7Ss7f2VL4DEbY2ppw/t0vVKssmMp83zOYrvIeiGPPaqztMNzPuztcc3z7hzZc2SQlIXGENIEoi0FqIeUYnY6qQsF7V3F0k3FptMJZjTNYX4YvJhIevvYknn/99kqSkadfMDm6yrlakRln4jpvHa0aXtigGCdo5stSyOcoYbQ4ZT8ZMNjYZbW6TFEOMtUT0c1Ck+Vx0KKdjsnIHk2SIOLyvid0MIyMwQozxtLNFkNgBgifph043ivjAJ6dtR0M/oswKxRC2UxiNleUS1rWwDtDU0CmUqVIkHc36Hmm9ZHmUcG5sGUwnvHjjiKwwiBdctHShpm4CdbPGDGMPqLZjtQrcWxlaILNwPvd0bcPNtedmpSyCx4thczji6uUruDRhXbfUbcdiVVO3kTTNefyRazx0ZZemaTg4WnFnHlEf+IrHzjGRPaIse2nwIOByOrZY18LyaMn9ueOeuUDS3OPcTklWTFh5z0OP/nFefOGDjPLA7qDkUDsSY04lLy3TkJGljunGkJ1xgbYVhVPK8YByVLIxmZLnOUmS9HMKPxnq6iuApJcNdkmyMSJgJMGKEHxNtL06sQgE+mGIRkE0otKLdpm0nzDVN1RBNIbGCDGeimhkkBc9wI5O4GChdEGgUkxQhgUMXMO2U46zKRuDFO3WXL+UcHgUSFJH3USscaTOMzCBrlVi5+mCMm8T9lctnTouJZ5x7qij53DVcLwOBCuU2YBz27u4NGfd9X7Z0fEJnRqcK3j06lWuPXQFZy3eThhNO8j2ePp4n+27kTdeKki1InaBLqasdciDReT4pGG1VGZ+xOXhPYrdlEuPvInjB0/yhX/sz3LzwR12x8pDo4uMNy5i7uxThTUbxRqfKtuDjFGRsjl0lMOE3OXkmaWLkSzPKAYpWWZJrJ42tDpEhfg5mPh39gXlYgeXlMTQYqxDkxHR5hiF4BuMVQSL14iJkagRa/vp5uoVCXDKxUUEolgaNayrDuOVxCjJKZXGAYiSObARfNWPhc1ixzjxZDYidFhnYWw5XK5JRlOcB0fGxQtj2pMTvPeoWg4XFfM6ECWyu5VTDsfs7VccrGraoBANxciSZil161k1DbO1pw2Gpqs5t7nFhQsXqWOJk4h6GG1dZ+eq5amP/DY3TxqunSsZZ4EQHVUbqcOQBwvPrcWQtNxhFOec393k8de/ids3XmBz4xJgcOv7OLGMszHaLdkeNXgJ7AwNMZQIASuGohSKrBd9kMRRJjmjzS3SYtR/oKHGBIPYSDBFP0LvjO3MQZXmk57hSN+jJq5EzABwBO1OFS06RCMxKkESXD7EZZZoFQ2K+H7mDChi+oSpGsO6DehaMEFRFRzgHP1gRfqMu69AveC6mq7NmQ4iq1rZmhZUdcVqfszKOMpQc2FcwOgCuj5mvWyour5lyRnPdJQTFSqEKgaiWCT2BDtrhKZZMV+saT1kWY4QuLA1IU0CTues1krTGbLMcfHCde7eepb7i1scrSxptkXbQbVe4GkZ5SMeuXKZul4wXzkOzQVuH0d8V3H52hdy9/ZH2djYpLqzT55vcDK7w2TgEZv1TSWh18/SGDHUxGDwUbAux+WO4XQbW/QjMwIBDS029IOP1A7OGgKfA9GzZAh4DAaxCSqWGAPG9AViQoXGSBeWCC2QkqYlLnV46SdICoqJp7NZCYgBlxhiqnivUIOJ/SSoxEGZ9uNcPfQTpAIMTUsrKUrFqAjUVcPm2GEPK4q8H/2qRMzIEUcXWYY96rjCoxSZZTQdsl6smK+qXpuKfljleDpksV7RRs9qvaKuPUk+5PLONsNxSVXXxKpmvmo5XjQU+ZLRaMy5zU2eObrDzQMlM8Bq3nO4kinD7dexrQvYucbe3nOYcoMn7x6zPbxMug6UacLycI9UXK91Wu0hwwTrPEUqODuk85G2XZGmQuIiJhRgDOV4SlqOwVoifXd0FxV8IJGaxLwC8lSSJkiIoH1RNrUJiVG8ejR6hBYl73lH1X0yCZT5kDwb0IpFTQDrIcZ+YqeYns1wOsfGaAARpOvTqVkGRaY4MVQBJFWCQppETuqGzVFOKmvaLlKmGXOt8Ms1+ThBTSA1S0yWcO78Nset48ZqxigVkkTpRFi1kbat6cSyNRizNRlzeDzncD5jVVV47ymqJelOSRcis8WcdV1zcDzneDanzEc8/NAjCIG6WvPcoWM7SxlrSxMMcXydrNmn3LhEDBWPX7tKl2/zicUhMbvChz/x+1ze2iIuHjAcbHFy+CIheo5nno2tHENJDB1Z0jIcOYbDEYeHKxIjuMQw2djGOgdymnwWRyPg+ywyIq+AFi1rUogtWNtre0aPiqA4lH6iuZicQI3WNYldkCQZ5WAb4xpiqJHYMwd6YkNfRdcYENOhVGA80iiikCa90L4xiotApHf6RYlVTZpnrFcJRQGr1jPdHDA76FAfGU2FEDpMt2SYj3no0ga1sWQIThTjLEGkb9xU2JgMsRa62LJarVhVNaqRYdJrMagqVVtxMDvhwYP7nCwWZEnB1uYGoV2y7jyHy8jRyhBMQhw8xIQ1ZZrj8gnrey8weegrObj9DNemCcfzZ2iW93lqvWAjrcmHBbG6R+Ii61nABE+yA+PpiDR3jDYKmrbBd4aNzRKbDhgOC6wzPZNCLSKOiBCl70v0Z4+pzwGobE4INSqBKA7SMUHSvvFBA1EFoxHVgNd+aoHYnHx0AYoWjS0x9jRgo6bX0YwR9S3arVFrUbtEjEe6ftjR6eeFFv0gH05zWblvaHzEOphXAqFjMCyp65yqa0mbyHiagNshS4a4YUqXTlmuOtIBFLSoXQAGawyjQcpidsJiPqepql6AP3qGg5zKe47u3aFpAuvFgsVqie86UOX2vVskyQB1A1bdiuM6YkYXmTiDk47J9mOQOKYPfx6Hd59DNFKmgulW7Fw7x806ZXV0gLcJIQZc7CdfDGxG7gRrWopBP6l+eVQxHI2wiaUYliSZRUzfMa3a5wVVTgcwiSXoKyD5aU1OB/gQ+6E92RC1BaE7nXquSqQlqkdNRowrkISk3O5zN9H3O532gyOtAsETQ0XsCrAGNR5kBaeCqyL9eDfEIiQ4Dfi2Hy2yagw7Q+FoFtiaKjF2bG6UrNeGPHesqkiSHlC4NcN0xPULGxyuh4gpiCXs3Ou4NbuB0PtUaVSyBHxs8Ris9DsYIbJYrjhZLNg7OKLpemFaHzoO9u6QpDnD4ZRQK2vJ2bDCcjVjMn6I4DJ8W1OUDg1LbDohNi1WLG58nmn9PNNL54k2sFSDuAHjrcvs7Oyi4XmwnqwY4FtPW3m2tqfM1y3b51Os8Yj0qmyqQqSnOnM62esVIc4vYomhw3cLrEmxJsW4lNp7op7qj0ffNyWQ4bsWjR6XTXvh+1NQRQ2YGJFTXyzGfnaeGojGg3hEaqz2OWEVMGmGcSXGtoitSI1n3nSYSUaZV9hUSI2laQJZURC1Y1w66jayOFkx3MrI847dvCTalKxJee2jl7hzcsKyapgvKgCi73dSESGx/Rwb1Z5BGpsG37W0IZzm4frpDDZ4IlCmGSKWe8dzNjfOcfP+A6aXn2B1/DwD6TP77XpJbE4otq+zf/tZNEYchrRZMCkKzPARFtkWe6s5Q9ews9UPsFwezQiasFzWuDQlL6SPtPFY0482kdMhSn3p3r0yyjSI6UHQzVFrEe165TljwTgEj6rpq+whoKEBFJuMSXFo9IRwOqMueiR2RG0x0WKNohKJRKIJaHKC6WoIEWP7InQSM6JNUWOISUVXdzQyQLIxTawpCyE3ga4RmqYfajQsLV4T1lWNkxMkV6w0ZDbl+gUDb9ziE7dWTMYjqi5wtKxJs5xlXVOUKYmL1NWczrccL5e0IWIVrDEYAyEowTck1nNhWHJ1NOB+d5778xVXNja5fe+AgcLByRxnHM1qn9FgzHK1Rrsl6wBu9oAygevXv4i1j9w4vsmd+pgnXjekKMcsFicsFg3j6SYnRydc3dnGOovgEToMAWxGEEev1m5O9T5fAcxPOU0haPAEX9HTxHpBMhEhxAaNp29SIsGvQBXrClQSNHSICBp6NgPWno7uMKeA6sXkxQJpBu0JplshweNMILUBTQaoTfHeIZlQe4st+mkIIgGXOhJpIGY0raXIEqw1JHnBulW0q4kSSKxhWgpf/MSA1z7kWKwMlR8wcJGP0fHg2DApEkJX0bYB3zV0nceooijW6OlOEJkWCZdHhoenjosbI557fkFrM9Z2yu3DB+xubrF6cJ/tQUHqleHuVRYvfrBnc5jAeDLl3PmrSOJI/YzXnt+l1THpoGV2fMhyvqQsJyQ2wRjHYDwG64gaToHlMaJgHEYS+uxyX8g+a/scCHQABCIQokdjz2URepBEDWi3JDZLNMx7KoL0vX+GFJUWYg3aELUn7omxqPS0PnFZ3zbuLBJK6AZIc4htD7HaEYwniIVkgAkJw65lvbYMS8GlOUiLTSypU/J0wN6xp45KWaRYmzCejli1AYyA63UO0iJjJ0/YCWBix+t24fMvlnzw+ZTW57g8pe0anBUGgwxbGVKnDLNeX8HimBYFG0UvXnKwGrCRHrEyI6qqnw+z7DqcGpp5xSOXX8fTz38c11QYZymmu2ycexRxlpP7zzDa3iFLa1KzJjOGUTmka5XRZIcH9+4xHA3IBwUY2zeNxICJXU+ANPa0W/xU20JeARn1SOj9DYQQWppuTUI/XcHanBiGqO3AronJJrgtEMFIgVU5zWUFxC8JYU10JcFm9E0TAaLBGoeSQRycZoQtRtdorEhcTpABSAkxYTCt2FvCKE3JyxS/WlE6xVCiHYyHyqpNoIXCKc45RoMtvCoREOvA1BAcahWLYWgDb3n4Aa+/vMnSniO6kuXJMSdHhjsHnjsHLV3VcrKKtAGyNGeUFeS2o8hKEqm5dm6b/WXHUXvMcHiO425B5VsGox1uHSx4cP8Bk0Q5t3uO8WgXEcvs6DZqpReiNUvOnd/pUyTHR4wnmwSUelVz6cIGloD6vkssSoP208wx4sHmp8BKTiPBs7Wzv/31mr2AEENHaNegYKzDuZwYaoLNkHQTa8dIr46GhL4orPaT0YlHgGCSvlVeHKr5aYnHE9T3LeQ2BQ2IrojagdnGmDFWLRL70bkqLU1rGG0Pab0QWbJatYRQsDXNSXzBurGsVpHcteSlI89GKKYfth1OUGPQEDFikTjAWsM0d4xHu4R8Qtgqqc5nbO8tmLxYs38ATVuzbjrUZBSFQV1BVa8oJ5tYga3Ss717iaNa0DV09ZJjW3B0dJfYtKQuZxmFUWfRwwOsBFyRE3XF+QvnmUxyfFshNmW4cYEHd2+RFSXTrSnGmN4hV4ghEmyHhBpru75dzggYg74SdNT1lEqhGEIMdO2yj+gkwTqH9ZZoM4gGkapnKUSL5TRUwkI2AN2BGLBugLjB6XYdT3NdHSY2SOgIpiKqoCY/jW7ynuUQWkKIRAM28wQ7IIpQbk6pDjucrcltSwy9QFs6GNN2Dh8CzXJFmQxIigmYXug1iEUlIhKwIQNJMMkIk40x2RiIhLrl7oMD7h2uybIxk0nC/mrJIB/QxEhoFWcz1iEhT4TJxgSSgtT0Y9nu14Z1tSSEhoBCkVK7AXuLFdYfMEwattMNtnYvU04mRDoOjxacu/QwKo4QhZ1LV8jH5/o8YQyEfnowEYOqJ2qN0QFWTgdMvxKYnyH6l4hfGgJtMyOGPsMOfcu7szmiEIOHqIgkPYU4hv4+bwRc2Tf+SdLvDqe1OpDeP4gN0df9LEHJ8Ens64Ua+5nFrFECTiKDUUbXlhAFNyjIJ1tIl5LqnHrdMLQWMQZJBEdJML3sYVo6jDOnwYH0k0u164c2uQmS7SLZCLE5HSmLkzXPvHjE3gwGo5JyOGU8hrxImS9WLIMSOijLXsXGJAlxdUBWTtnMIsF61iQ02stBis1YLQ6p/F2K3JKkJdm0ZDAtCdpy++YdisGQECMheFw54fxDj5BNxnRhjfEtop5I6DlscBpRN6hmWAnIK6H2p9qhsWcgRI107YLoVxibne5ivaKciO0FO8SdXi2KhI5oLNZaSMo+Y42+tPt9soUetWgwfT1LLBjFnaYpfNegYUY0DUKKFc90e8T9W0KSZHRNJC0ntPOAZGD9ktZHXGEwPTsQl5TYvAQjiM16/wTbz1yLLWS7SDaB0SXIp2jwVKslN2884PbemnUscIWirTIcD4hB6IBGE1wsWHQZGpZ45ylwNOs5vl0xyCOZdgzFImmC903fv5dmVMbCYMBkq6Cujti/vyBLh5SjktliRl5MyIabbJy7hiQWQk30NSbUxNiiGl7SyjKxJcYOq+lpJHi2dvagiqEvBdBncJtmRrU+pHBjovZA+yRIRMxp1+jpddTr7kC0L1FfIJzqLvRirKoRDQE1DrUFkGKsYgME3+K1AiIiFmMcIhmDgcGZFb4VIODsgGJ6HtsdYgeRdd2Xjqw1vSiZNZg0Q4wg1mFIcUhf+6HAZCOsS5B0hBhHaI+p1jV7+0tmraVFoPJMJJJZixHPoJygVY3LhxxVFTZ1NFVDJgHpZiQaEHFkCWxsTKmquh8LN5pwHGHghMvnS7pmzuGqpRwOGG1MUVK8b1gtZpy7comsGKEiWJsRXI73DTHWRN8QQ0fUXoyEUBNt1hNBztjOPvqLHu2TTICh6xqWi9ukxfZppBZPCXinX6D0ibh+KIdBtHcgReMpME1/vOff9n2E6GmqITktjCoaW0LoE6VqFCTpn4fDAOOJZ1U3TDY2MVmOcQ6cwWZDirSmaz0usfS81BaJ8bQEZLA2oY82HOAwzmGStOeLaS8U23VC48E6S9cZ1i1kzmNTJUsKJknBxmSbeeXxKiCOZbfmuJ5juhWJgTITStuL2uaJwWUpk51zjG1ka9wxHgq+XZCkYFJLwNOFSFEknBwt2docY40gLkc1EjTB2JTgM4JZEnyDBA9EgrZIqDD2FZCniqHtdyOxYPsM+Wpxm7LYIBtc60NYkb7pgcj/mdkFjMVES9QWtMP8f9s7tyc5ruPM/zLPOVXdcx9gABKUREkmqYvldVghR/ifWP/nu+HdWIcVjpC8S1nBFQniMpfu6qpzyX3IUw2unwcPCOM8EEAMp7u6KysvX375pfkEsa0VZWu9IgveHBUf/XKDcpcOioQtQYRApbUFpHFyFfj9P/1vfnP2nHQxUEsjjNdIO2NME7a/Z84OoFpfbpmkyyCREPPcQ0WQmNA4EELAmlGb8PLVG1RHrs+M2zdCrsrdfsZInJyMXF4+JcQNp0thlxt3b98grTHnhVyNsUEV437a8/p14cXVhpubLefnhS8+e4pxx/72JSEuEAO1TOymmZNBeXU7cX55wzBGpCyENELaIDagYaCFmVwV1QO1HKh1ptGobaaUDyD8tVaw7iGCjlSEUvbc3v6Rcx1I43NC3HjvzhzZNQmICNIMU99F7JTigklF2or+BkwHRMfO2e9Jed5Tq8sMhjQ4JGFQqagJgnF6MXJ5fdF7jr1f18SpozYwbDc8TN9TKbScSfqWcXvt1yXhXTdDXNNTxFf4NstMDw98/eeXvD00njw55d9f37K7n5mtYO2UT29eYBJJBNJpIuzusbHyenkg9s7ClBe+eTWRl8zT7QDBuH5+ztUVbM/uefvqDSp736aqiYoSVbm9/Z7drvHVb36LqVHrhJYRCRvvu2rCwkCoI1knShjQcqDUGTOj1A9AR722jFhAdaCZohjWKtP8Gnv7R04vMpvNJ6gmr+jcBXWP5F7JUfj1OG0DcFaCT6Z3AdcJqQekzYgIIW1pEoAMLSOmVBGgsI2Ri/MTNmdbXn/3Hc8+/QwwcmlHRePh5AKT7NekQquL87hicHVlUzREVx0W/3ermfv7t3z75p77qfHp9YYfXw/8j6/f8HCYeciZp59OXKUNc8zIXGnzDrGJTVggNV5+e8vLe2eYbmLkrlW2S+Xi6cjNp4JZZruJ1LhBg9J0AD1lKQf2855xe8NwsqEa5DKjyx0pRGQ8wzRhGpE4uIfNI7UcCPlAqZlmj7/y4fE9la25R0OaEKzQ1N9mWe7g7t+peU8cztBwgurgTz66mhRODDaU1F9L/afehQYWWj6gdYe1AxICGrZUHR1uKHjCL7UDfBFV5fLT59Rl4vzyCfuHB1J0sTXGkWBCCAPFZhAhRgVbjbNrbAWXXDSJoIJZoZSFeTqwm3DBj7Bwc33GF/vMv/z5wOu7Hf/9f/4vLk/POBkHzjeREGBpmSCRi9MNL56eo0NgKUYIgZvrLf/wNzf87X+54fR8cGXAlAjhlLwUTLqqy+GOaX/g4jNhnu8YNifoEMl1RvMDKSRkiBD8OzQdUc3UuFDihGT3WI99Hh9Rt4BoIuBUi6Z9EwLq+/xqYz68JdeZkBZi3CBxS9DkwhoAGnz1rQ4dp4odGV6gPriHKrfUeo/RkLRFdIui0KEGacExK+kVpBhXN8/45g9/4Pz61OkoVql5pi0P1FIIAUxa956C0WjLQ9dDHx3+0OReC8UEFyyLiWbCd3eZ1/vCT56e8cnNGVNe+PrlLYfDwnfzaxBlTJHTTeR0CMSYuDgd+OT5E158+oTNOHJxNvJXP9vy5RdXnJ4malVE9kzTHaUIqsLm5Iy87GklE6RxenZgt/uWmDaoJERP0ZoJeSLEvhNHEqj4dxq2SNyi4QHNH0D4Q4IPPGBgBaFXYaJoGBEZnGYs6vmKeu6lYSRoQMRQUUQSKoMzFqxP2dCwtoP8hrq87upwJ7S4AR1cCESCt3Q6FKFtgTojbeZk3JDC1hH+CunkjDiMaJuY77/HjY/u3Xp5EKKHcDr80UfFpS8bCMMpErYMquRayRlevn3gs+sTnj89YzMmvv7LHXdzoZn1nXsN2BJb4dtX95xE48WzS37606f88pfPuX4yEKL3QVsNWL0nxICOA1aFJTvYOT0sXN1s0VDYH74jPGxc/D+MaEgs5cCwBIKOWEggEQmCYkhNqI5onB7dBN4D9UU6sOk5h0l0T6URkaELdgRiGElhS4jnhHSBxsE/rDqRTIiIOKBp5iGPeg/5LXl6ye5wR2EkbC9IYevJuzrMYNFbFNoKVpovpbSMaOL8+Q3T/p7zixsOUyZGo7WGiZLnCR0FYQCUao1BIkh0VF+T3xwN3lcT92y5DR1ULNxPmcNizLlwfTpyerbh1z/b8Kfvbnn9cGBZKq1WdtOBGDznPJQNT56OfPnLp9w8PyPEvnhLB9phoWBISOQFynxAg3GYZoZROb/0Yqfkmf3+FTFu0LBBYnKMrSxI3qMaMQsIfm9af0g0fAC9PwmhN5WD/7fFbmQ9LHbcZ0gbYtoS05aQtmj0No64yoJXe+aqv7RKW+5oh5ccdv+X+/uXPMwTcfuMMx0JcesanU5dcqiitU4AzNA2iFRUE9fPLvjzH/fEzZbWhPF0S943hnGLSuFQJkJw4BSsI9EFUV8o0DR2T9vb5tqoIXHAWaCC8TA1ctlTamG7NC62I5882fLieuDPr/fcTZWgwnaIPLnc8KsvnvD3v/2cTz67QYJ6DxPDanQdCHz71nw4kIJhFVJSzq9OiIOLVhvKnB/Y7b9H0wZNG89VtUCeSJqQFBAZ+/cr3kEIH0Cbho5DgY+9S3hXgnvVBCGNxHhGGs6J6QSNseNBDu8eGYnNm8ct39Gmb5jv/o3bh1e82T9QJHCOG6qGAQmjh0r1pnZQo2qgSgPJ0BLEgTFes7mcmJeFEAOlFNLmBLOJWgNKcpyNft2AkgnqSLv0fE9wrxxj5PT8knE8BXlDjJHlMMPceH13YNgVDicHrs9Gvvpky/XlGXN1Q3h6teV3v7rht7/5CZfPr6lppGKI+bawthhLq0CikTg5cUntZdoxjoHthdOrjV5Gm3GYH9CHl8R4SoiD51AURPY+46cKNjpTQbqQ7yOfRzcqFaeL+HiVep6jCZWEaiCEyJDOSemSOJwT4ohqAukaJKIoCTOhWsXKDMu3TPdf8/buL7yZZ5YmxxUdJhENoxuWBLynXL0ZXc15V3KOWOlJ9RlPX3zOd//nX7m+uSbv7hm2G0wjIQSCxWO16qj/AmRfF9LXoKzbsUQEjQPXT57x4tNP+P0f/sRlUmwT2S2N2oyHVrBDRBP86/fGk+vIz19c8quvPueLn3/Gs6tTzsZG3Yz+BZrRms9N5XzAp0ECdd7757VGGgbOLreMY/QmsXW6gfjmiXnes9+/8R6mblAVclFkmUkSIQaUSPuBx33M8/jhTwNqChq9lUdENaEhEjSS0ilpuCIOl4R0QtCIiHXasfTZfk9SKTvq/JL9/Te82b3h7eJr13xqRgHpPb6AhrE/eWBSHQ7ACDb4qDc9bIXI6cUVm4tnlCUT4kheMoMGYtyyWMDMKc2qiWYTrSy0coWks6OH8r94sXF2fs5XX/yc//ZP/4ztJoazge+n6qL/1Rnit1Mhpsqvn13y97/7BV/+4hecnZ0TbEYpSBrcQ5YZ1DW65iVTKhymBVVFUoTcUN1ydnWKBENadVatqGN9hvcCpzs0nRLiBg0+70c+YCpECaicOtbHhxD+VJEmXZLRZ85UE0FHQtoQhkvieElK5w7IOUe0o1Q+wGfWvAG6/5754Rtud/fczTPZOvrek/i2QgbqFSddLcasb2FXwzRjFkAMkdiNcODmxz/n23/7F85PBvLunhp946dqRO3g3lMjrd2S6x2aJmLLEOoPeN1e1Q7jhl/+4kv+4e++5J9//zVixmcvIujAvvqg66fPLvnrX3/O3/z1z7h5dsW4Pff3ygXtewAN37vsVd9Mq5VaXSs1DBvMMqqxD48malv6d9acatY9qBksy8Ruf0uKJ8S4JYQRaQXyAVEvPkTkQ2F+Stc+WiEDT9IJIzGeMwznhOEEiWPHe+iwuiC9z9eWHXX6C/vpL9xP9zzMO3Kr7sUkIOYYUTVXjXFMa604PR+pAmIJk0iTBGJo/yJFlM32ksvnn7N/9Sc2w4nTc3RAKYS2JQQfOKj5gWA+5Cpt7UK2njt6/hhC4tmPfsx//cd/5He/+4ZSMiEODOPIkAZUhPOLU04vB4ZBEG0+vyjRw7YWkiaXVIqNWhZyO9BqcaPSgATBZmPcnHF5fQ1avKyxpZPvcO6w3wTMMsvhnl3cktIJIfpWL2sVWSYQSMKHsUaEnuu4N8HpJzqS4pY0XHj4C2MvZdcbJEBysHSZqIfXLNP37Oc99/M9c9nDCks4RxTBh01bayANUUVVvR+I79RzNeToVY65cp+qdoxJuXr2I1qeWW6/IRAIaYMuC5IaYRgQaVQXbUCkuGS39AdAVnTde5VpOOP5j/+Kmxc/gbVcF/dSmOutNJtodnD6czduYgIaqkoMiWRGbs2XEphzzrZbz7NMhcsnN6TtCbUcev+h9baV0ehLDcDB4lbYH+5Iw5kvQAoDgyiZBVsMIRE+hGmaH3oqBwoHNHi1F+KJl7tx8Hykm4eIh71aDtTDW5bDW/Y5s1v2zPmhv3ACAmZ9OaPHuWOfUIPXZK1zyQV6waAEiy72oW5s0g1DQ+T6xU+4m1+z3L9CxwvSMNDUqS21vnyXnNuMkD3/W7es9jEnEzl6yxg3DsCG2AN67mP8ipghzah26J8bIHkRIUIMGxoBLYVaCq0Zw+BGN+0XxtMrLq5uEK0+5s9qQbO3sPqwBojPVppheWa3f0NMG2IY3HhlIOeM8MCoH4KnQjtyCyoDKqPH9HhKSI70oqmT8IqHECKtZer8lvlwy74s7JaJebnHWqWSvMTvOYxhfnO70rGbZt9RTOsSRL40qVnyp3ndti56ZEWAEsPA0xefUc4ah3ktBCK0Bat3PaQ2zCZoM2qN2nEkkdZDchcZ6+FHVB3qEBBz+KG5hCBoxlrodB7xgqZ5KIthpMmAMpHnSujI/mFf0DDw5JMfETcjrZaeXneOGZ6HmbhCieslOECjZiyHPbvwhhjGTlwMaFBymWGRPkn5eOc9gJ+KWuo3MBE0EXTjlJQ0ImHoP2tg0W9IbdTDHfPhjqnMTMueebl1JF0GRIym4Zh7mXj4WxNmsdVTxF7R4Ai6+M0V8y9belKvoj5N4s07RJXNyQnpdMv9dEeeXlHrHaLNm8lSaW3G6gPSFn9NtP++dEhkvSaHIlSDt3fMOfjSBoSDb7zX7KAqBkRHziWCJGIKqGwcMA6JVlxA8eLpMy4uz/pb9trXujCJiY9ukameDbybE6BRrTIddoTw+liFD+MJVaAtH0CbRrs3cL5RRHUgxoEYRkLw6urocEXcEy13LNMrDnlizhNL3jkibh5mRHzP8PqLP/x9sK5jtYKmvg7EjF5ZGmJO6qMPTtAbxu5t1PuRYYOGM1JbkEVcwdaSe8RWqZapbUeyiSCb3qDtzWvpbNXj9UmfyAZBMUueEdTRPXSrNGa/HhUaI0WVJNEJdqLe6yvCw27m7PoJzz77kQPJrWEa0CCu9tyNWc0b+GqtFxOrZoIXP7Uu7Pd3/V5s0JBIssX0A9D8VHkXAlQiqiMxDB3ddQqJ4cshac0Navcdh2XPIe/Jee85iAhNlCah5yydqNfWUS78tcx1qqS/d4NjqKPnOkfKsqhf39HwxQdfQyCw9SEH9bFxN+boXk4HjEKre6RNRK59HD8MHkpVj2Coh8HWcS4PsQ5auodpCFZdptIHEgqmA4Yn/RoG0ERtQp4zn/74p1x98tzlkprQtBDMJ2O81dKfIPMMLljxlGAdFnHIHTNjzhP3+1s0bh2/0g1RPwDmp6j2/Cb2HTFOvZUYjzcSEaiZOt+yTG855MqhZHJxETHvo4Mn5p1KLD0p1u5ozLOS0rx5vJY8KzgphHd5jwT3epjfuGOSvBpX7AyHLvShDqh2eqmHGTPnXrXJdSC0FwudqyUSuhOs3WjtnaHhvTnPHwVj25vktfcWYR3zECJXV8+YP/kpvPic4WTrhoerxtCckiPqrx16i6Ydk3bBKFB6zsb62v7zZZ7YTbcMwxmaTlzf8pHPe2ApxA4nJCQM3aB6KwbwWtcoeU+e75hzZq6V3HKvpnq7AfVGqsSeQ0n3POB3z2Uaa6u0mvuMYDeithpWb6eoOs+rG9hKvXE6S6WTv1Cyv2vw7r0P9PTmtESqNleg0eYaEOpGrho7B2xthjdclGSFNnoXQP1Gm420tviolPkgAhahOe9re3rBi8+/Yr+/Y84T1nzaWDEfEu1GLk36yIgRbIO1ThPSRg4RaRxDoPcGXcf+MD+wn24JwymaNo9tAu8j/Dlaa92oQvRcyr2XJ64278mHe/YZ5ppZ6uQ3sBPf3On01oI4x8mbpv4e0nnI63NoVNZi2n1VT5gVpDmo6v/gaLSsXzZKwAjimztVXDVPZMDLNRysNGgUastYq8QVyVdxiGENgauqsvQhCWl+/RLcu2r1ZLlturhbwdzP4CbQEE3EeEJMmaXV/pmCfxctI+YLuE37ZjKcFeva9J4OqC09NZDVgbGCtbUWpsMdcTwlxPGxTeB94FResq+tGY0bJAz+w2a0cugeqrCUmVymXuXJMfc5eqxejq9MzBVS8S+ph0V7t69crHUv9wOP1v9YwdBVgcZZEepT0db1HEJyglsc0TzTmngp1XqSL0puE63eIfaEoFsf1Aix88V+OL9Ib0KvYdDbV+5aDIsVswErmWbQpKuBAyrBmRx1QyyFbIpaxWTBgGCuNNys+oS3ah8A99ytmdGa9dzKoZf1WWuAWmPJe+bDLTFtH9sE3sMwqSbHaDQhaXAv1bGltuxo0yuWYhxKIRcfTV9pL9bpG77O259OE0/Aq9+uH2QJXuVYz9MUei3dDXENfSIdcuB4s9cEXsE5W1a9mgsbxBIaTkEzytK9S/GyHaW2hZxfkeoNQa6c/92xt+Odg45hVVaaDBKw4PKIQfxazTYUy1jLGFDMqM2VZUKMDMOWUgqtb1n1ByvT2ioLHmjaXDS3f85oFbPkxEPz4VFtUFcMrUMhrTYOhwdCvHtsE3gfibrzoUVjn5jp4qVtoSwP5GrMtVLKAQ8TsYN0DSjOVTAHOq0PRNgx1K2nD56iPXh1j4D0ENvLeesegrUX+R99WM/TBERHWjhFaWjcOVmO6NQThm4YHqhK3WP1Aecp0dH6tdJb7bZvqDI7FgYm4jOLFaBS24iUA0KmsgrrVpJ4wh7iliHOtDCxVGj0odYuVmLSQApmBiQs+MMWGoTo0gN6FOlYw731nqFSS2GZ7x/bBN4Hot4TYw2eXwFWF9q8IxfjYJGlze40VL05jAN3JmsyLn5pUntFJb1ZuiZVXuN4aBTeNbzeNVSPSZVF92Ci7hX7z+wHX/I6iaxra+Wo8dAQHZDWN6t2uLIaWDugLIj43B4IFvrMYr9mNyy/0WtLygOpYTYQ2kjU4ZgCVGm9PeMwh4SBmAaGRbC6kMXVBtUaaKVRUEs0HH1f72YIldA21CiIZcDDJGtuhtJMaM3ZDI99Hj9R77Rh6ZhUqxXagaVklmrkMjuzQKQn42vIWA0quAGsA6Yoph2LOoY2O9qPP3X917Ur7raeS6j2G+il/IoZOTTRJ45rb7lodM9o6+BFwCR0ntKI9PLf/amSW2ZTXXpyfWlTcftSev/zGIhxw+phmoi1SujEwCLijASplDZjdXHuliRi3EJMtFwwmxE9oYbmU0OqvijSukS4qhNmUyOYkBq0JlTLiFWvqNuqSCw0cz3Sxz7vZ5rG1DWizMfOW6ks1ZirJ6Wrp+iIEc44eHfjbQUo8Qqq9b7DSo5bsShni4qzFcyOibi7nga1Hls4iDejYX2f9e0EwuDcLh3QVgjqHPXW3Mug1fshRHzvlLK0A7UdGFyI0r2GxI5w++eTzmDore7utTwMqxmh5SPYWuoOs4VaE63l/uAkJG68bxr2vgxKnNQo5gsDpFUavWGOS3+bKSRP2ANGsIY1oVrnW/Xv1Xunj24B72OJZMDhT3Nl4Qa5NnItR9lG+gcSWbVA6chv9zodV5AV7DR9F9mOnm19v25U/WfOZGzH35cVbvffZg2Lx8GF3ruTMHoeGEC6GKtI6727rqcgDaHQRMi1UeqBgYJo80rPfHjV3+X/qz/f2XEHcQkdxws+WiYIrRVKK9SyHN9XdUCGc0LN6DKjEj0rEkFqb1S3brAN1IQYvWsRmhGb0YK4odYuxmRrNBTfs/zI5z14Kjy0mGGWKU2dH9RjlJgdn+L/+Jh4aiS9T+c9vWbGD9kZJjiFRLwZK9K6PJF1Q1qrL+0Y0VohquNBKj9wVP32S+wjXgkxCLp1nEoXx3msj5s17VWlr+VYygPbOjtgKut8dWVlQJis3C9YqT62Up41dKPymUdR15AvrbDUmdEyysavO26Q8RwlQXHjVQnvRvy1HDsK9DEsDerG5Q7bK8BWeyfCEX7p9eljn/fDUe9JcSVRu+F4GJPjTcHEEWazjgW17qB62JCAk9ne+aW15ee9NuvJcG+hdFGv1VfVHoLWLxBZQ9KaoPc/xLzlop7LiQZvLYUAZZ0Makcw1t/DNRqW2tX8uui9+8h+BUfPpEfwce0MrP+vBQ9vxC2WN1i7p7VKKYvnVa36A6GxN4Eb1KVXpPg1NqBTaUyd9tKk9prYF0TF1iiG9xppx16h41qPTycWs/cRVT+e/8zn8c304/lPfz4a1cfz6OejUX08j34+GtXH8+jno1F9PI9+PhrVx/Po56NRfTyPfj4a1cfz6OejUX08j37+H6GyEA36VKBmAAAAAElFTkSuQmCC", - "text/plain": [ - "
" + "cell_type": "markdown", + "metadata": { + "id": "6He3uia-ROvN" + }, + "source": [ + "The logits produced by the transpiled model at inference time are close to the ones produced by the original model, the logits are indeed consistent!" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "image/png": 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", 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" + "cell_type": "markdown", + "metadata": { + "id": "Mk_mnj7JROvN" + }, + "source": [ + "#### Fine-tuning the transpiled model\n", + "\n", + "One of the key benefits of using ivy’s transpiler is that the transpiled model is also trainable. As a result, we can also further train the transpiled model if required. Here’s an example of fine-tuning the transpiled model with a few images sampled from ImageNet using TensorFlow.\n", + "\n", + "Let’s start by writing a general function to train a model." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "id": "3IPJPNMiROvN" + }, + "outputs": [], + "source": [ + "import time\n", + "import tensorflow as tf\n", + "\n", + "\n", + "def train_model(model, epochs, train_dataset, val_dataset, optimizer, loss_fn):\n", + " # Prepare the metrics.\n", + " train_acc_metric = tf.keras.metrics.SparseCategoricalAccuracy()\n", + " val_acc_metric = tf.keras.metrics.SparseCategoricalAccuracy()\n", + "\n", + " for epoch in range(epochs):\n", + " print(\"\\nStart of epoch %d\" % (epoch,))\n", + " start_time = time.time()\n", + "\n", + " # Iterate over the batches of the dataset.\n", + " for step, (x_batch_train, y_batch_train) in enumerate(train_dataset):\n", + "\n", + " x_batch_train = tf.convert_to_tensor(x_batch_train.detach().numpy())\n", + " y_batch_train = tf.convert_to_tensor(y_batch_train.detach().numpy())\n", + "\n", + " with tf.GradientTape() as tape:\n", + " logits = model(x_batch_train, training=True)\n", + " loss_value = loss_fn(y_batch_train, logits)\n", + "\n", + " grads = tape.gradient(loss_value, model.trainable_weights)\n", + " optimizer.apply_gradients(zip(grads, model.trainable_weights))\n", + "\n", + " # Update training metric.\n", + " train_acc_metric.update_state(y_batch_train, logits)\n", + "\n", + " # Log every 20 batches.\n", + " if step % 20 == 0:\n", + " print(\n", + " \"Training loss (for one batch) at step %d: %.4f\"\n", + " % (step, float(loss_value))\n", + " )\n", + " print(\"Seen so far: %d samples\" % ((step + 1) * 4))\n", + "\n", + " # Display metrics at the end of each epoch.\n", + " train_acc = train_acc_metric.result()\n", + " print(\"Training acc over epoch: %.4f\" % (float(train_acc),))\n", + "\n", + " # Reset training metrics at the end of each epoch\n", + " train_acc_metric.reset_states()\n", + "\n", + " # Run a validation loop at the end of each epoch.\n", + " for x_batch_val, y_batch_val in val_dataset:\n", + " x_batch_val = tf.convert_to_tensor(x_batch_val.detach().numpy())\n", + " y_batch_val = tf.convert_to_tensor(y_batch_val.detach().numpy())\n", + "\n", + " val_logits = model(x_batch_val, training=False)\n", + "\n", + " # Update val metrics\n", + " val_acc_metric.update_state(y_batch_val, val_logits)\n", + "\n", + " val_acc = val_acc_metric.result()\n", + " val_acc_metric.reset_states()\n", + " print(\"Validation acc: %.4f\" % (float(val_acc),))\n", + " print(\"Time taken: %.2fs\" % (time.time() - start_time))\n", + "\n", + " return model" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "id": "N0dm7aU8ROvN" + }, + "outputs": [], + "source": [ + "# Instantiate an optimizer to train the model.\n", + "optimizer = tf.keras.optimizers.SGD(learning_rate=1e-3)\n", + "\n", + "# Instantiate a loss function.\n", + "loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)\n", + "\n", + "# Prepare the datasets\n", + "train_dataset = dataloaders[\"train\"]\n", + "val_dataset = dataloaders[\"val\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "hapz3PjPROvN", + "outputId": "ee93e68d-c692-4856-a513-6da98cf2800a" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "Start of epoch 0\n", + "Training loss (for one batch) at step 0: 9.3121\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 4.2126\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 2.4992\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 1.6072\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.3852\n", + "Validation acc: 0.1830\n", + "Time taken: 224.00s\n", + "\n", + "Start of epoch 1\n", + "Training loss (for one batch) at step 0: 1.1015\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 2.1364\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 1.3915\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.7465\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8033\n", + "Validation acc: 0.3333\n", + "Time taken: 214.04s\n", + "\n", + "Start of epoch 2\n", + "Training loss (for one batch) at step 0: 0.2763\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.3526\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.4220\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.1592\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8525\n", + "Validation acc: 0.3660\n", + "Time taken: 214.46s\n", + "\n", + "Start of epoch 3\n", + "Training loss (for one batch) at step 0: 0.1364\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.1085\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.1366\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.4634\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8115\n", + "Validation acc: 0.3987\n", + "Time taken: 224.36s\n", + "\n", + "Start of epoch 4\n", + "Training loss (for one batch) at step 0: 0.3875\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.8096\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.5836\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.4432\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8402\n", + "Validation acc: 0.3529\n", + "Time taken: 218.69s\n", + "\n", + "Start of epoch 5\n", + "Training loss (for one batch) at step 0: 0.0323\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.0982\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.4332\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.0324\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8197\n", + "Validation acc: 0.3464\n", + "Time taken: 228.84s\n", + "\n", + "Start of epoch 6\n", + "Training loss (for one batch) at step 0: 0.1794\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.9244\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.9429\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.1794\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.7951\n", + "Validation acc: 0.3529\n", + "Time taken: 231.99s\n", + "\n", + "Start of epoch 7\n", + "Training loss (for one batch) at step 0: 0.0132\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.4156\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.2132\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 1.1413\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8279\n", + "Validation acc: 0.4183\n", + "Time taken: 224.95s\n", + "\n", + "Start of epoch 8\n", + "Training loss (for one batch) at step 0: 0.3028\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.1461\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.3779\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.4553\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8607\n", + "Validation acc: 0.4444\n", + "Time taken: 223.66s\n", + "\n", + "Start of epoch 9\n", + "Training loss (for one batch) at step 0: 0.2835\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.0436\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.7022\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 1.1335\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8648\n", + "Validation acc: 0.4052\n", + "Time taken: 215.37s\n", + "\n", + "Start of epoch 10\n", + "Training loss (for one batch) at step 0: 0.0863\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.0237\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.0181\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.1331\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8975\n", + "Validation acc: 0.4967\n", + "Time taken: 209.94s\n", + "\n", + "Start of epoch 11\n", + "Training loss (for one batch) at step 0: 0.1050\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.2271\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.3540\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.0588\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8689\n", + "Validation acc: 0.4902\n", + "Time taken: 222.28s\n", + "\n", + "Start of epoch 12\n", + "Training loss (for one batch) at step 0: 0.7880\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.4800\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 1.4741\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.0218\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8197\n", + "Validation acc: 0.5033\n", + "Time taken: 220.61s\n", + "\n", + "Start of epoch 13\n", + "Training loss (for one batch) at step 0: 0.2198\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.6509\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.3352\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.0270\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8197\n", + "Validation acc: 0.4771\n", + "Time taken: 216.12s\n", + "\n", + "Start of epoch 14\n", + "Training loss (for one batch) at step 0: 0.0385\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.1798\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.0143\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.0309\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8197\n", + "Validation acc: 0.5359\n", + "Time taken: 213.23s\n", + "\n", + "Start of epoch 15\n", + "Training loss (for one batch) at step 0: 0.7697\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.3405\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.6033\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.8392\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8770\n", + "Validation acc: 0.5359\n", + "Time taken: 205.21s\n", + "\n", + "Start of epoch 16\n", + "Training loss (for one batch) at step 0: 0.0623\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.4221\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.0138\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.4607\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8648\n", + "Validation acc: 0.5294\n", + "Time taken: 221.65s\n", + "\n", + "Start of epoch 17\n", + "Training loss (for one batch) at step 0: 0.0349\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.6545\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.1935\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.1512\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8852\n", + "Validation acc: 0.5098\n", + "Time taken: 212.37s\n", + "\n", + "Start of epoch 18\n", + "Training loss (for one batch) at step 0: 0.0821\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.1985\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.7769\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 1.3897\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8648\n", + "Validation acc: 0.5359\n", + "Time taken: 204.62s\n", + "\n", + "Start of epoch 19\n", + "Training loss (for one batch) at step 0: 0.1106\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.1354\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.1801\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.0276\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8893\n", + "Validation acc: 0.5621\n", + "Time taken: 214.83s\n", + "\n", + "Start of epoch 20\n", + "Training loss (for one batch) at step 0: 0.1185\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.0447\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 1.2817\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.1006\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8402\n", + "Validation acc: 0.5752\n", + "Time taken: 215.36s\n", + "\n", + "Start of epoch 21\n", + "Training loss (for one batch) at step 0: 0.2220\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.0387\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.1639\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.0080\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.9221\n", + "Validation acc: 0.5686\n", + "Time taken: 214.12s\n", + "\n", + "Start of epoch 22\n", + "Training loss (for one batch) at step 0: 0.0287\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.0115\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.1679\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.7920\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8893\n", + "Validation acc: 0.5621\n", + "Time taken: 208.51s\n", + "\n", + "Start of epoch 23\n", + "Training loss (for one batch) at step 0: 0.0071\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.0790\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.2657\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.0758\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8934\n", + "Validation acc: 0.5686\n", + "Time taken: 210.86s\n", + "\n", + "Start of epoch 24\n", + "Training loss (for one batch) at step 0: 0.2406\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.9193\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.2372\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.9555\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.9139\n", + "Validation acc: 0.5817\n", + "Time taken: 211.98s\n", + "\n", + "Start of epoch 25\n", + "Training loss (for one batch) at step 0: 0.1150\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.0810\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.2205\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.1616\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.9344\n", + "Validation acc: 0.5817\n", + "Time taken: 218.82s\n", + "\n", + "Start of epoch 26\n", + "Training loss (for one batch) at step 0: 0.0200\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.0117\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.2090\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.1444\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8934\n", + "Validation acc: 0.5948\n", + "Time taken: 208.63s\n", + "\n", + "Start of epoch 27\n", + "Training loss (for one batch) at step 0: 0.0482\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.0338\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.5971\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.0368\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8607\n", + "Validation acc: 0.6144\n", + "Time taken: 207.13s\n", + "\n", + "Start of epoch 28\n", + "Training loss (for one batch) at step 0: 0.1593\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.4745\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.0733\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.0434\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8852\n", + "Validation acc: 0.6078\n", + "Time taken: 209.68s\n", + "\n", + "Start of epoch 29\n", + "Training loss (for one batch) at step 0: 0.3923\n", + "Seen so far: 4 samples\n", + "Training loss (for one batch) at step 20: 0.1614\n", + "Seen so far: 84 samples\n", + "Training loss (for one batch) at step 40: 0.3711\n", + "Seen so far: 164 samples\n", + "Training loss (for one batch) at step 60: 0.2719\n", + "Seen so far: 244 samples\n", + "Training acc over epoch: 0.8852\n", + "Validation acc: 0.6275\n", + "Time taken: 209.91s\n" + ] + } + ], + "source": [ + "# Train the model\n", + "transpiled_model = train_model(\n", + " transpiled_model,\n", + " epochs=30,\n", + " train_dataset=train_dataset,\n", + " val_dataset=val_dataset,\n", + " optimizer=optimizer,\n", + " loss_fn=loss_fn,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ojY_R0iSROvN" + }, + "source": [ + "And that’s it. we’ve successfully been able to train the transpiled model, we can now plug into any TensorFlow workflow!\n", + "\n", + "Let's now visualize the inference of the trained model on some sample images from the validation step" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "id": "4uYIZYgVROvN" + }, + "outputs": [], + "source": [ + "def visualize_model(model, num_images=6):\n", + " was_training = tf.keras.backend.learning_phase() == 1\n", + " images_so_far = 0\n", + " fig = plt.figure()\n", + "\n", + " for i, (inputs, labels) in enumerate(dataloaders['val']):\n", + " inputs = tf.convert_to_tensor(inputs.detach().numpy())\n", + " labels = tf.convert_to_tensor(labels.detach().numpy())\n", + "\n", + " outputs = model(inputs, training=False)\n", + " preds = tf.argmax(outputs, 1)\n", + "\n", + " for j in range(inputs.shape[0]):\n", + " images_so_far += 1\n", + " ax = plt.subplot(num_images//2, 2, images_so_far)\n", + " ax.axis('off')\n", + " try:\n", + " ax.set_title(f'predicted: {class_names[preds[j]]}')\n", + " except:\n", + " continue\n", + " imshow(inputs[j])\n", + "\n", + " if images_so_far == num_images:\n", + " model(inputs, training=was_training)\n", + " return\n", + "\n", + " model(inputs, training=was_training)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 923 + }, + "id": "gANn4EEyROvN", + "outputId": "1b5b1e85-b537-48ab-df19-caa58b9ff486" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" 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\n" 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\n" 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\n" 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\n" 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\n" + }, + "metadata": {} + } + ], + "source": [ + "visualize_model(transpiled_model)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zpgEfq8-ROvO" + }, + "source": [ + "### Conclusion\n", + "\n", + "We've just seen how the transpiler can be used to convert a model from PyTorch to TensorFlow and train the converted model in TensorFlow.\n", + "\n", + "Head over to the [tutorials](https://unify.ai/docs/ivy/demos/) section in our documentation if you’d like to explore other demos like this. You can also run demos locally on your own machine by [signing up](https://console.unify.ai/) to get a transpiler API key for local development.\n", + "\n", + "If you have any questions or suggestions for other interesting demos you'd like to see, feel free to ask on our [Discord](https://discord.gg/sXyFF8tDtm) community server, we look forward to seeing you there!" ] - }, - "metadata": {}, - "output_type": "display_data" } - ], - "source": [ - "visualize_model(transpiled_model)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Conclusion\n", - "\n", - "We've just seen how the transpiler can be used to convert a model from PyTorch to TensorFlow and train the converted model in TensorFlow.\n", - "\n", - "Head over to the [tutorials](https://unify.ai/docs/ivy/demos/) section in our documentation if you’d like to explore other demos like this.\n", - "\n", - "If you have any questions or suggestions for other interesting demos you'd like to see, feel free to ask on our [Discord](https://discord.gg/mMnS8Egy) community server, we look forward to seeing you there!" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "tracer-transpiler", - "language": "python", - "name": "python3" + ], + "metadata": { + "kernelspec": { + "display_name": "tracer-transpiler", + "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": "3.10.13" + }, + "colab": { + "provenance": [] + } }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.13" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} + "nbformat": 4, + "nbformat_minor": 0 +} \ No newline at end of file