[
  {
    "path": ".gitignore",
    "content": "models\ntiny-224\ntiny-imagenet-200\ntiny-imagenet-200.zip\n*.zip\n__pycache__\n.*\n!/.gitignore"
  },
  {
    "path": "Makefile",
    "content": ".PHONY: export-req\n\nexport-req:\n\tuv export --no-hashes --format requirements-txt > requirements.txt\n"
  },
  {
    "path": "README.md",
    "content": "# Pytorch-Tiny-ImageNet\r\n\r\n### Installation\r\n\r\nIf you are familiar with [uv](https://docs.astral.sh/uv/getting-started/installation/), you can install dependencies with `uv sync`.\r\nOtherwise, you can install dependencies with requirements.txt\r\n\r\n**Trouble shooting** with OpenCV [here](https://github.com/NVIDIA/nvidia-docker/issues/864#issuecomment-452023152)\r\n\r\n### Dataset\r\n\r\n`python src/util/prepare_dataset.py` will download and preprocess tiny-imagenet dataset.\r\nIn the original dataset, there are 200 classes, and each class has 500 images.\r\nHowever, in test dataset there are no labels, so I split the validation dataset into validation and test dataset. (25 per class)\r\nProbably not the best train(500), val(25), test(25) splitting method, but I think it's good enough for this project to evaluate transfer learning.\r\n\r\nThe dataset is then resized from 64x64 to 224x224.\r\n\r\nIf you don't want to prepare dataset, you can download dataset\r\n- [tiny-imagenet-200](https://github.com/tjmoon0104/pytorch-tiny-imagenet/releases/download/tiny-imagenet-dataset/processed-tiny-imagenet-200.zip)\r\n- [tiny-imagenet-200 resized to 224x224](https://github.com/tjmoon0104/pytorch-tiny-imagenet/releases/download/tiny-imagenet-dataset/tiny-224.zip)\r\n\r\n### Summary\r\n\r\nGoal of this project is to evaluate transfer learning on tiny-imagenet dataset.\r\n\r\nTiny-ImageNet dataset has images of size 64x64, but ImageNet dataset is trained on 224x224 images.\r\nTo match the input size, I resized tiny-imagenet dataset to 224x224 and trained on pretrained weight from ImageNet.\r\n\r\nFinetune few layers, and use pretrained weight from 224x224 trained model to retrain 64x64 image on ResNet18\r\n\r\n### Test Result\r\n\r\n| Model    | Test Result | Input size | pretrained weight |\r\n| -------- | ----------- | ---------- | ----------------- |\r\n| AlexNet  | 35.88%      | 64x64      | ImageNet          |\r\n| ResNet18 | 53.58%      | 64x64      | ImageNet          |\r\n| ResNet18 | 69.62%      | 224x224    | ImageNet          |\r\n| ResNet18 | 69.80%      | 64x64      | Model Above       |\r\n\r\n### Updates\r\n\r\nThis project was done as part of Udacity Machine Learning Engineer Nanodegree Capstone Project in 2018.\r\n\r\nI haven't updated the code since then, but I decided to update this project thanks to a lot of interest and stars from the community.\r\n\r\nSince then, I have been working as Data Engineer, and I have improved my python programming skills.\r\n\r\nThis version includes the following changes:\r\n- uv for dependency management\r\n- Pytorch with M1 Mac GPU support\r\n- Dataset download and preprocessing with python\r\n"
  },
  {
    "path": "notebook/AlexNet.ipynb",
    "content": "{\n \"cells\": [\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 1,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2025-09-16T19:31:05.125375Z\",\n     \"start_time\": \"2025-09-16T19:31:03.945301Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"from pathlib import Path\\n\",\n    \"\\n\",\n    \"import torch\\n\",\n    \"import torch.nn as nn\\n\",\n    \"import torch.optim as optim\\n\",\n    \"import torchvision.datasets as datasets\\n\",\n    \"import torchvision.transforms as transforms\\n\",\n    \"\\n\",\n    \"from src.model.AlexNet import alexnet\\n\",\n    \"from src.test_model import test_model\\n\",\n    \"from src.train_model import train_model\\n\",\n    \"\\n\",\n    \"%matplotlib inline\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 2,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2025-09-16T19:31:05.130298Z\",\n     \"start_time\": \"2025-09-16T19:31:05.128750Z\"\n    },\n    \"collapsed\": false,\n    \"jupyter\": {\n     \"outputs_hidden\": false\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"if torch.cuda.is_available():\\n\",\n    \"    device = \\\"cuda:0\\\"\\n\",\n    \"elif torch.backends.mps.is_built():\\n\",\n    \"    device = torch.device(\\\"mps\\\")\\n\",\n    \"else:\\n\",\n    \"    device = \\\"cpu\\\"\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 3,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2025-09-16T19:31:05.494216Z\",\n     \"start_time\": \"2025-09-16T19:31:05.132664Z\"\n    },\n    \"collapsed\": false,\n    \"jupyter\": {\n     \"outputs_hidden\": false\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"data_transforms = {\\n\",\n    \"    \\\"train\\\": transforms.Compose([transforms.ToTensor()]),\\n\",\n    \"    \\\"val\\\": transforms.Compose([transforms.ToTensor()]),\\n\",\n    \"    \\\"test\\\": transforms.Compose([transforms.ToTensor()]),\\n\",\n    \"}\\n\",\n    \"\\n\",\n    \"data_dir = Path(\\\"../tiny-imagenet-200/\\\")\\n\",\n    \"num_workers = {\\\"train\\\": 2, \\\"val\\\": 0, \\\"test\\\": 0}\\n\",\n    \"image_datasets = {\\n\",\n    \"    x: datasets.ImageFolder(data_dir / x, data_transforms[x]) for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\\n\",\n    \"dataloaders = {\\n\",\n    \"    x: torch.utils.data.DataLoader(image_datasets[x], batch_size=500, shuffle=True, num_workers=num_workers[x])\\n\",\n    \"    for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\\n\",\n    \"dataset_sizes = {x: len(image_datasets[x]) for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]}\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 4,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2025-09-16T19:31:05.734421Z\",\n     \"start_time\": \"2025-09-16T19:31:05.497501Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Load AlexNet\\n\",\n    \"torch.manual_seed(42)\\n\",\n    \"model_ft = alexnet().to(device)\\n\",\n    \"\\n\",\n    \"# Loss Function\\n\",\n    \"criterion = nn.CrossEntropyLoss().to(device)\\n\",\n    \"# Observe that all parameters are being optimized\\n\",\n    \"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 5,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"image/png\": 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     \"text/plain\": [\n       \"<Figure size 1200x800 with 2 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"accuracy\\n\",\n      \"\\ttraining         \\t (min:    0.005, max:    0.005, cur:    0.005)\\n\",\n      \"\\tvalidation       \\t (min:    0.005, max:    0.005, cur:    0.005)\\n\",\n      \"log loss\\n\",\n      \"\\ttraining         \\t (min:    5.298, max:    5.298, cur:    5.298)\\n\",\n      \"\\tvalidation       \\t (min:    5.298, max:    5.298, cur:    5.298)\\n\",\n      \"Training complete in 1m 60s\\n\",\n      \"Best Validation Accuracy: 0.004999999888241291, Epoch: 1\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"text/plain\": [\n       \"1\"\n      ]\n     },\n     \"execution_count\": 5,\n     \"metadata\": {},\n     \"output_type\": \"execute_result\"\n    }\n   ],\n   \"source\": [\n    \"# Train\\n\",\n    \"train_model(\\n\",\n    \"    output_path=\\\"Alex_not_pretrained\\\",\\n\",\n    \"    model=model_ft,\\n\",\n    \"    dataloaders=dataloaders,\\n\",\n    \"    criterion=criterion,\\n\",\n    \"    optimizer=optimizer_ft,\\n\",\n    \"    device=device,\\n\",\n    \"    num_epochs=5,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 6,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"image/png\": 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     \"text/plain\": [\n       \"<Figure size 1200x800 with 2 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"accuracy\\n\",\n      \"\\ttraining         \\t (min:    0.005, max:    0.238, cur:    0.238)\\n\",\n      \"\\tvalidation       \\t (min:    0.006, max:    0.292, cur:    0.292)\\n\",\n      \"log loss\\n\",\n      \"\\ttraining         \\t (min:    3.322, max:    5.298, cur:    3.322)\\n\",\n      \"\\tvalidation       \\t (min:    3.084, max:    5.297, cur:    3.084)\\n\",\n      \"Training complete in 7m 59s\\n\",\n      \"Best Validation Accuracy: 0.29179999232292175, Epoch: 20\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Load AlexNet with pretrained weights\\n\",\n    \"model_ft = alexnet(pretrained=True).to(device)\\n\",\n    \"\\n\",\n    \"# Loss Function\\n\",\n    \"criterion = nn.CrossEntropyLoss()\\n\",\n    \"# Observe that all parameters are being optimized\\n\",\n    \"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\\n\",\n    \"\\n\",\n    \"# Train\\n\",\n    \"best_epoch = train_model(\\n\",\n    \"    output_path=\\\"Alex_pretrained\\\",\\n\",\n    \"    model=model_ft,\\n\",\n    \"    dataloaders=dataloaders,\\n\",\n    \"    criterion=criterion,\\n\",\n    \"    optimizer=optimizer_ft,\\n\",\n    \"    device=device,\\n\",\n    \"    num_epochs=20,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 7,\n   \"metadata\": {\n    \"collapsed\": false,\n    \"jupyter\": {\n     \"outputs_hidden\": false\n    }\n   },\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"Test Loss: 3.1334 Acc: 0.2780\\n\",\n      \"Test complete in 0m 1s\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Test\\n\",\n    \"model_ft.load_state_dict(torch.load(f\\\"models/Alex_pretrained/model_{best_epoch}_epoch.pt\\\"))\\n\",\n    \"test_model(model=model_ft, dataloaders=dataloaders, criterion=criterion, device=device)\"\n   ]\n  }\n ],\n \"metadata\": {\n  \"kernelspec\": {\n   \"display_name\": \"Python 3 (ipykernel)\",\n   \"language\": \"python\",\n   \"name\": \"python3\"\n  },\n  \"language_info\": {\n   \"codemirror_mode\": {\n    \"name\": \"ipython\",\n    \"version\": 3\n   },\n   \"file_extension\": \".py\",\n   \"mimetype\": \"text/x-python\",\n   \"name\": \"python\",\n   \"nbconvert_exporter\": \"python\",\n   \"pygments_lexer\": \"ipython3\",\n   \"version\": \"3.13.7\"\n  }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 4\n}\n"
  },
  {
    "path": "notebook/ResNet18_224.ipynb",
    "content": "{\n \"cells\": [\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 1,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-02T09:10:38.914114Z\",\n     \"start_time\": \"2023-12-02T09:10:37.879698Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"import os\\n\",\n    \"\\n\",\n    \"import torch\\n\",\n    \"import torch.nn as nn\\n\",\n    \"import torch.optim as optim\\n\",\n    \"import torch.utils.data as data\\n\",\n    \"import torchvision.datasets as datasets\\n\",\n    \"import torchvision.models as models\\n\",\n    \"import torchvision.transforms as transforms\\n\",\n    \"\\n\",\n    \"from src.test_model import test_model\\n\",\n    \"from src.train_model import train_model\\n\",\n    \"\\n\",\n    \"%matplotlib inline\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 2,\n   \"outputs\": [],\n   \"source\": [\n    \"if torch.cuda.is_available():\\n\",\n    \"    device = \\\"cuda:0\\\"\\n\",\n    \"elif torch.backends.mps.is_built():\\n\",\n    \"    device = torch.device(\\\"mps\\\")\\n\",\n    \"else:\\n\",\n    \"    device = \\\"cpu\\\"\"\n   ],\n   \"metadata\": {\n    \"collapsed\": false,\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-02T09:10:38.916852Z\",\n     \"start_time\": \"2023-12-02T09:10:38.915071Z\"\n    }\n   }\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 3,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-02T09:10:39.069142Z\",\n     \"start_time\": \"2023-12-02T09:10:38.918664Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"data_dir = \\\"../tiny-224/\\\"\\n\",\n    \"num_workers = {\\\"train\\\": 4, \\\"val\\\": 0, \\\"test\\\": 0}\\n\",\n    \"data_transforms = {\\n\",\n    \"    \\\"train\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.RandomRotation(20),\\n\",\n    \"            transforms.RandomHorizontalFlip(0.5),\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"val\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"test\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"}\\n\",\n    \"image_datasets = {\\n\",\n    \"    x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x]) for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\\n\",\n    \"dataloaders = {\\n\",\n    \"    x: data.DataLoader(image_datasets[x], batch_size=100, shuffle=True, num_workers=num_workers[x])\\n\",\n    \"    for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 4,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-02T09:10:39.291426Z\",\n     \"start_time\": \"2023-12-02T09:10:39.069883Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Load Resnet18\\n\",\n    \"torch.manual_seed(42)\\n\",\n    \"model_ft = models.resnet18(weights=\\\"IMAGENET1K_V1\\\")\\n\",\n    \"# Finetune Final few layers to adjust for tiny imagenet input\\n\",\n    \"model_ft.avgpool = nn.AdaptiveAvgPool2d(1)\\n\",\n    \"num_features = model_ft.fc.in_features\\n\",\n    \"model_ft.fc = nn.Linear(num_features, 200)\\n\",\n    \"model_ft = model_ft.to(device)\\n\",\n    \"\\n\",\n    \"# Loss Function\\n\",\n    \"criterion = nn.CrossEntropyLoss()\\n\",\n    \"# Observe that all parameters are being optimized\\n\",\n    \"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 5,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"text/plain\": \"<Figure size 1200x800 with 2 Axes>\",\n      \"image/png\": 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\"\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"accuracy\\n\",\n      \"\\ttraining         \\t (min:    0.282, max:    0.795, cur:    0.795)\\n\",\n      \"\\tvalidation       \\t (min:    0.522, max:    0.736, cur:    0.736)\\n\",\n      \"log loss\\n\",\n      \"\\ttraining         \\t (min:    0.798, max:    3.693, cur:    0.798)\\n\",\n      \"\\tvalidation       \\t (min:    0.999, max:    2.269, cur:    0.999)\\n\",\n      \"Training complete in 46m 44s\\n\",\n      \"Best Validation Accuracy: 0.7361999750137329, Epoch: 10\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Train\\n\",\n    \"best_epoch = train_model(\\n\",\n    \"    output_path=\\\"RestNet18_224\\\",\\n\",\n    \"    model=model_ft,\\n\",\n    \"    dataloaders=dataloaders,\\n\",\n    \"    criterion=criterion,\\n\",\n    \"    optimizer=optimizer_ft,\\n\",\n    \"    device=device,\\n\",\n    \"    num_epochs=10,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 6,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-02T09:57:31.634999Z\",\n     \"start_time\": \"2023-12-02T09:57:23.582015Z\"\n    }\n   },\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"Test Loss: 0.9919 Acc: 0.7426\\n\",\n      \"Test complete in 0m 8s\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Test\\n\",\n    \"model_ft.load_state_dict(torch.load(f\\\"models/RestNet18_224/model_{best_epoch}_epoch.pt\\\"))\\n\",\n    \"test_model(model=model_ft, dataloaders=dataloaders, criterion=criterion, device=device)\"\n   ]\n  }\n ],\n \"metadata\": {\n  \"kernelspec\": {\n   \"display_name\": \"Python 3\",\n   \"language\": \"python\",\n   \"name\": \"python3\"\n  },\n  \"language_info\": {\n   \"codemirror_mode\": {\n    \"name\": \"ipython\",\n    \"version\": 3\n   },\n   \"file_extension\": \".py\",\n   \"mimetype\": \"text/x-python\",\n   \"name\": \"python\",\n   \"nbconvert_exporter\": \"python\",\n   \"pygments_lexer\": \"ipython3\",\n   \"version\": \"3.6.5\"\n  }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 2\n}\n"
  },
  {
    "path": "notebook/ResNet18_64.ipynb",
    "content": "{\n \"cells\": [\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 1,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T19:46:40.242919Z\",\n     \"start_time\": \"2023-12-01T19:46:37.722294Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"import os\\n\",\n    \"\\n\",\n    \"import torch\\n\",\n    \"import torch.nn as nn\\n\",\n    \"import torch.optim as optim\\n\",\n    \"import torch.utils.data as data\\n\",\n    \"import torchvision.datasets as datasets\\n\",\n    \"import torchvision.models as models\\n\",\n    \"import torchvision.transforms as transforms\\n\",\n    \"\\n\",\n    \"from src.test_model import test_model\\n\",\n    \"from src.train_model import train_model\\n\",\n    \"\\n\",\n    \"%matplotlib inline\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 2,\n   \"outputs\": [],\n   \"source\": [\n    \"if torch.cuda.is_available():\\n\",\n    \"    device = \\\"cuda:0\\\"\\n\",\n    \"elif torch.backends.mps.is_built():\\n\",\n    \"    device = torch.device(\\\"mps\\\")\\n\",\n    \"else:\\n\",\n    \"    device = \\\"cpu\\\"\"\n   ],\n   \"metadata\": {\n    \"collapsed\": false,\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T19:46:40.316312Z\",\n     \"start_time\": \"2023-12-01T19:46:40.264284Z\"\n    }\n   }\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 3,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T19:46:40.607765Z\",\n     \"start_time\": \"2023-12-01T19:46:40.324777Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"data_dir = \\\"../tiny-imagenet-200/\\\"\\n\",\n    \"num_workers = {\\\"train\\\": 2, \\\"val\\\": 0, \\\"test\\\": 0}\\n\",\n    \"data_transforms = {\\n\",\n    \"    \\\"train\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"val\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"}\\n\",\n    \"image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x]) for x in [\\\"train\\\", \\\"val\\\"]}\\n\",\n    \"dataloaders = {\\n\",\n    \"    x: data.DataLoader(image_datasets[x], batch_size=500, shuffle=True, num_workers=num_workers[x])\\n\",\n    \"    for x in [\\\"train\\\", \\\"val\\\"]\\n\",\n    \"}\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 4,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T19:46:41.098285Z\",\n     \"start_time\": \"2023-12-01T19:46:40.604690Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Load Resnet18\\n\",\n    \"torch.manual_seed(42)\\n\",\n    \"model_ft = models.resnet18()\\n\",\n    \"# Finetune Final few layers to adjust for tiny imagenet input\\n\",\n    \"model_ft.avgpool = nn.AdaptiveAvgPool2d(1)\\n\",\n    \"num_features = model_ft.fc.in_features\\n\",\n    \"model_ft.fc = nn.Linear(num_features, 200)\\n\",\n    \"model_ft = model_ft.to(device)\\n\",\n    \"# Loss Function\\n\",\n    \"criterion = nn.CrossEntropyLoss()\\n\",\n    \"# Observe that all parameters are being optimized\\n\",\n    \"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 5,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"text/plain\": \"<Figure size 1200x800 with 2 Axes>\",\n      \"image/png\": 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    },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"accuracy\\n\",\n      \"\\ttraining         \\t (min:    0.010, max:    0.127, cur:    0.127)\\n\",\n      \"\\tvalidation       \\t (min:    0.018, max:    0.107, cur:    0.107)\\n\",\n      \"log loss\\n\",\n      \"\\ttraining         \\t (min:    4.211, max:    5.294, cur:    4.211)\\n\",\n      \"\\tvalidation       \\t (min:    4.293, max:    5.214, cur:    4.293)\\n\",\n      \"Training complete in 6m 40s\\n\",\n      \"Best Validation Accuracy: 0.10719999670982361, Epoch: 10\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"text/plain\": \"10\"\n     },\n     \"execution_count\": 5,\n     \"metadata\": {},\n     \"output_type\": \"execute_result\"\n    }\n   ],\n   \"source\": [\n    \"# Train\\n\",\n    \"train_model(\\n\",\n    \"    output_path=\\\"ResNet18_64_not_pretrained\\\",\\n\",\n    \"    model=model_ft,\\n\",\n    \"    dataloaders=dataloaders,\\n\",\n    \"    criterion=criterion,\\n\",\n    \"    optimizer=optimizer_ft,\\n\",\n    \"    device=device,\\n\",\n    \"    num_epochs=10,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 6,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T19:53:21.359230Z\",\n     \"start_time\": \"2023-12-01T19:53:21.162685Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Load Resnet18\\n\",\n    \"model_ft = models.resnet18(weights=\\\"IMAGENET1K_V1\\\")\\n\",\n    \"# Finetune Final few layers to adjust for tiny imagenet input\\n\",\n    \"model_ft.avgpool = nn.AdaptiveAvgPool2d(1)\\n\",\n    \"num_features = model_ft.fc.in_features\\n\",\n    \"model_ft.fc = nn.Linear(num_features, 200)\\n\",\n    \"model_ft = model_ft.to(device)\\n\",\n    \"# Loss Function\\n\",\n    \"criterion = nn.CrossEntropyLoss()\\n\",\n    \"# Observe that all parameters are being optimized\\n\",\n    \"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 7,\n   \"metadata\": {\n    \"scrolled\": true\n   },\n   \"outputs\": [\n    {\n     \"data\": {\n      \"text/plain\": \"<Figure size 1200x800 with 2 Axes>\",\n      \"image/png\": 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\"\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"accuracy\\n\",\n      \"\\ttraining         \\t (min:    0.068, max:    0.611, cur:    0.611)\\n\",\n      \"\\tvalidation       \\t (min:    0.176, max:    0.506, cur:    0.506)\\n\",\n      \"log loss\\n\",\n      \"\\ttraining         \\t (min:    1.588, max:    4.945, cur:    1.588)\\n\",\n      \"\\tvalidation       \\t (min:    2.006, max:    4.150, cur:    2.006)\\n\",\n      \"Training complete in 6m 15s\\n\",\n      \"Best Validation Accuracy: 0.5062000155448914, Epoch: 10\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"text/plain\": \"10\"\n     },\n     \"execution_count\": 7,\n     \"metadata\": {},\n     \"output_type\": \"execute_result\"\n    }\n   ],\n   \"source\": [\n    \"# Train\\n\",\n    \"train_model(\\n\",\n    \"    output_path=\\\"ResNet18_64_pretrained\\\",\\n\",\n    \"    model=model_ft,\\n\",\n    \"    dataloaders=dataloaders,\\n\",\n    \"    criterion=criterion,\\n\",\n    \"    optimizer=optimizer_ft,\\n\",\n    \"    device=device,\\n\",\n    \"    num_epochs=10,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 8,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T19:59:36.815423Z\",\n     \"start_time\": \"2023-12-01T19:59:36.451755Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Normalized Dataset\\n\",\n    \"data_transforms = {\\n\",\n    \"    \\\"train\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"val\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"test\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"}\\n\",\n    \"image_datasets = {\\n\",\n    \"    x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x]) for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\\n\",\n    \"dataloaders = {\\n\",\n    \"    x: data.DataLoader(image_datasets[x], batch_size=500, shuffle=True, num_workers=num_workers[x])\\n\",\n    \"    for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 9,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T19:59:37.009598Z\",\n     \"start_time\": \"2023-12-01T19:59:36.819465Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Load Resnet18\\n\",\n    \"model_ft = models.resnet18(weights=\\\"IMAGENET1K_V1\\\")\\n\",\n    \"# Finetune Final few layers to adjust for tiny imagenet input\\n\",\n    \"model_ft.avgpool = nn.AdaptiveAvgPool2d(1)\\n\",\n    \"num_features = model_ft.fc.in_features\\n\",\n    \"model_ft.fc = nn.Linear(num_features, 200)\\n\",\n    \"model_ft = model_ft.to(device)\\n\",\n    \"# Loss Function\\n\",\n    \"criterion = nn.CrossEntropyLoss()\\n\",\n    \"# Observe that all parameters are being optimized\\n\",\n    \"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 10,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"text/plain\": \"<Figure size 1200x800 with 2 Axes>\",\n      \"image/png\": 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\"\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"accuracy\\n\",\n      \"\\ttraining         \\t (min:    0.073, max:    0.612, cur:    0.612)\\n\",\n      \"\\tvalidation       \\t (min:    0.183, max:    0.518, cur:    0.518)\\n\",\n      \"log loss\\n\",\n      \"\\ttraining         \\t (min:    1.577, max:    4.918, cur:    1.577)\\n\",\n      \"\\tvalidation       \\t (min:    1.988, max:    4.115, cur:    1.988)\\n\",\n      \"Training complete in 6m 15s\\n\",\n      \"Best Validation Accuracy: 0.5175999999046326, Epoch: 10\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"text/plain\": \"10\"\n     },\n     \"execution_count\": 10,\n     \"metadata\": {},\n     \"output_type\": \"execute_result\"\n    }\n   ],\n   \"source\": [\n    \"# Train\\n\",\n    \"train_model(\\n\",\n    \"    output_path=\\\"ResNet18_64_pretrained_normalized\\\",\\n\",\n    \"    model=model_ft,\\n\",\n    \"    dataloaders=dataloaders,\\n\",\n    \"    criterion=criterion,\\n\",\n    \"    optimizer=optimizer_ft,\\n\",\n    \"    device=device,\\n\",\n    \"    num_epochs=10,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 11,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T20:05:51.969833Z\",\n     \"start_time\": \"2023-12-01T20:05:51.608509Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Normalized & Flipped Dataset\\n\",\n    \"data_transforms = {\\n\",\n    \"    \\\"train\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.RandomHorizontalFlip(0.5),\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"val\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"test\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"}\\n\",\n    \"image_datasets = {\\n\",\n    \"    x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x]) for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\\n\",\n    \"dataloaders = {\\n\",\n    \"    x: data.DataLoader(image_datasets[x], batch_size=500, shuffle=True, num_workers=num_workers[x])\\n\",\n    \"    for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 12,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T20:05:52.170991Z\",\n     \"start_time\": \"2023-12-01T20:05:51.972187Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Load Resnet18\\n\",\n    \"model_ft = models.resnet18(weights=\\\"IMAGENET1K_V1\\\")\\n\",\n    \"# Finetune Final few layers to adjust for tiny imagenet input\\n\",\n    \"model_ft.avgpool = nn.AdaptiveAvgPool2d(1)\\n\",\n    \"num_features = model_ft.fc.in_features\\n\",\n    \"model_ft.fc = nn.Linear(num_features, 200)\\n\",\n    \"model_ft = model_ft.to(device)\\n\",\n    \"# Loss Function\\n\",\n    \"criterion = nn.CrossEntropyLoss()\\n\",\n    \"# Observe that all parameters are being optimized\\n\",\n    \"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 13,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"text/plain\": \"<Figure size 1200x800 with 2 Axes>\",\n      \"image/png\": 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oUStXV1REUFMSCBQuYMmVK4/nZs2dTUlLCxx9/fNx7LrnkEjp37kxQUBAff/wx0dHRXHfdddx///3YbLYTjlNbW0ttbW3j13l5eQwYMKC5ZYqIiIi4XE5ODna73dtlNFtubi4JCQneLkNEREQ6sB97fmrR8r3i4mIcDgexsbFNzsfGxrJz584Tvmfv3r188803zJw5ky+++IL09HR+/etfU19fzx//+McTvmfu3Lk8/PDDx53PyckhLCysJSWLiIiInJGysjISEhIIDQ31diktcrRePT+JiIiIpzX3+anFPaVayul0EhMTw0svvYTNZmP48OHk5eXx+OOPnzSUmjNnDvfcc0/j10e/mbCwMD1UiYiIiFe0tSVwR+vV85OIiIh4y489P7UolIqKisJms1FYWNjkfGFhIXFxcSd8T3x8PL6+vk2W6vXv35+CggLq6urw8/M77j3+/v74+/u3pDQREREREREREWlDWtSt08/Pj+HDh7NkyZLGc06nkyVLljB27NgTvuess84iPT0dp9PZeG737t3Ex8efMJASEREREREREZH2r8VbyNxzzz28/PLLvP766+zYsYNbbrmFyspKbrrpJgBmzZrFnDlzGq+/5ZZbOHToEHfeeSe7d+/m888/5y9/+Qu33nqr674LERERERERERFpU1rcU+qaa67hwIEDPPjggxQUFDBkyBC++uqrxubn2dnZTbb7S0hI4Ouvv+buu+8mOTmZrl27cuedd3L//fe77rsQEREREREREZE2xWIYhuHtIn5MWVkZ4eHhlJaWqlGniIiIeFRbfQ5pq3WLiIhI29fc55AWL98TERERERERERE5UwqlRERERERERETE4xRKiYiIiIiIiIiIxymUEhERERERERERj1MoJSIiIiIiIiIiHqdQSkREREREREREPE6hlIiIiIiIiIiIeJxCKRERERERERER8TiFUiIiIiIiIiIi4nEKpURERERERERExOMUSomIiIi42UMPPYTFYmny0a9fv1O+5/3336dfv34EBAQwePBgvvjiCw9VKyIiIuIZCqVEREREPGDgwIHk5+c3fnz//fcnvXblypXMmDGDn/3sZ2zatIkpU6YwZcoUtm7d6sGKRURERNxLoZSIiIiIB/j4+BAXF9f4ERUVddJrn376aS666CLuu+8++vfvz6OPPsqwYcN47rnnPFixiIiIiHsplBIRERHxgD179tClSxd69uzJzJkzyc7OPum1q1atYtKkSU3OTZ48mVWrVp30PbW1tZSVlTX5EBEREWnNFEqJiIiIuNno0aOZN28eX331Fc8//zz79u1jwoQJlJeXn/D6goICYmNjm5yLjY2loKDgpGPMnTuX8PDwxo+EhASXfg8iIiIirqZQSkRERMTNLr74YqZPn05ycjKTJ0/miy++oKSkhPfee89lY8yZM4fS0tLGj5ycHJfdW0RERMQdfLxdgIiIiEhHExERQZ8+fUhPTz/h63FxcRQWFjY5V1hYSFxc3Env6e/vj7+/v0vrFBEREXEnzZQSERER8bCKigoyMjKIj48/4etjx45lyZIlTc4tWrSIsWPHeqI8EREREY9QKCUiIiLiZvfeey/fffcdmZmZrFy5kiuvvBKbzcaMGTMAmDVrFnPmzGm8/s477+Srr77iiSeeYOfOnTz00EOsX7+e2267zVvfgoiIiIjLafmeiIiIiJvl5uYyY8YMDh48SHR0NOPHj2f16tVER0cDkJ2djdV67HeF48aN46233uL3v/89v/vd7+jduzcfffQRgwYN8ta3ICIiIuJyFsMwDG8X8WPKysoIDw+ntLSUsLAwb5cjIiIiHUhbfQ5pq3WLiIhI29fc5xAt3xMREREREREREY9TKCUiIiIiIiIiIh6nnlIiIiLS5tQ7nCzbfYCFG3PpERXMfZP7ebukDqegtIYn/ruLg5V1vHrjSG+XIyIiIm2QQikRERFpM3bkl7FwQy4fbc6juKIOgKgQf+6e1AcfmyaAe1KAr5X3N+QCUFpVT3iQr5crEhERkbZGoZSIiIi0agcravl4834Wbsxl2/6yxvORwX5MGdqVqcPsCqS8ICLIj+6RQWQdrCItr4QJvaO9XZKIiIi0MQqlREREpNWpa3Dyzc4iFm7M5dudRTQ4zc2CfW0WJvWPZeowO2f3jcZXYZRXJdsjzFAqt1ShlIiIiLSYQikRERFpFQzDYGteGQs35vLx5jwOV9U3vpZsD2facDuXJ3ehU7CfF6uUH0qxh/Np6n5Sc0q8XYqIiIi0QQqlRERExKuKymr4aHMeCzfksauwvPF8TKg/Vw7ryrRhdnrHhnqxQjmZZHsEAKm5JV6tQ0RERNomhVIiIiLicTX1DhbvKGThhly+232AI6vz8POxMnlgHFOHdWV8UpR6RbVyg7qGYbVAYVkthWU1xIYFeLskERERaUMUSomIiIhHGIbBppwSFm7I5dPU/ZTVNDS+NqxbBNOGJ3BpcjzhgdrFra0I8vOhd0wouwrLSc0p4cKBcd4uSURERNoQhVIiIiLiVvml1XywMY+FG3PZe6Cy8XyX8ACuGmbnqmFd6Rkd4sUK5UykJISzq7CctNxShVIiIiLSIgqlRERExOWq6xx8va2AhRtz+T69GOPI8rwAXysXD4pn2nA7Y3tGYrVavFuonLFkewTvrc9VXykRERFpMYVSIiIi4hKGYbA+6zAL1ufy+ZZ8KmqPLc8b1aMz04bbuWRwPCH+evxoT1KONDvfkleKYRhYLAoaRUREpHn0VCgiIiJnJOdQFR9szOODTblkHaxqPJ/QOZCrhtqZOsxOt8ggL1Yo7tQ3LhQ/m5WSqnqyD1XRPTLY2yWJiIhIG6FQSkRERFqssraBL7cWsGBDDqv3Hmo8H+xn45LB5vK8kYmdtTyvA/DzsdK/SxipOSWk5pYqlBIREZFmUyglIiIizeJ0Gqzed5CFG/L4cms+VXUOACwWGNcrkqnD7Fw0KI4gPz1edDQp9nBSc0pIyynhJyldvF2OiIiItBF6ahQREZFTyiyu5IONuSzcmEdeSXXj+R5RwUwd1pUrh9npGhHoxQrF25LtEUAWabml3i5FRERE2hCFUiIiInKcspp6vkjLZ+HGXNZlHm48Hxrgw2XJXZg2vCvDunVSU2sBzJlSYDY7b3A48bFZvVyRiIiItAUKpURERAQAh9NgRXoxCzfm8tXWAmobnABYLTChdzRTh9u5cEAsAb42L1cqrU3P6BCC/WxU1jlIP1BBv7gwb5ckIiIibYBCKRERkQ4uvaiChRtz+XBjHgVlNY3ne8eEMHW4nSuHdiU2LMCLFUprZ7NaGNQ1nDX7DpGWU6pQSkRERJpFoZSIiEgHVFpVzydp+1m4IZfNOSWN58MDfbliSBemDrOTbA/X8jxptiEJEazZd4jU3BKuHpng7XJERESkDVAoJSIi0kE0OJws23OAhRvyWLS9kDqHuTzPZrVwbt9opg6zc17/GPx9tDxPWs5sdo6anYuIiEizKZQSERFp53YVlLNgQw4fbd7PgfLaxvP94kKZNtzOFUO6Eh3q78UKpT1IPtLsfGdBGbUNDoWbIiIi8qMUSomIiLRDtQ0OvtxSwBurs9iQdWz3vMhgP64Y0pWpw7sysEu4FyuU9sbeKZDOwX4cqqxjR345QxIivF2SiIiItHIKpURERNqR3MNVvLUmm3fX5XCwsg4AH6uF8/vHMG14Auf0jcbXZvVyldIeWSwWku3hLN11gLTcEoVSIiIi8qMUSomIiLRxTqfBsj0HeHN1Ft/sLMJpmOfjwwO4blQ3rhmVQEyods8T90u2R7B01wFSc0phrLerERERkdZOoZSIiEgbdbiyjvc35DB/TTZZB6saz49PiuL6Md2Z1D8GH82KEg9KOdJXKjW3xLuFiIiISJugUEpERKSNSc0p4Y3VWXyaup/aBnMHvdAAH6YPT2DmmG70ig7xcoXSUR3dgS/jQAUVtQ2E+OtRU0RERE5OTwoiIiJtQE29g09S9/Pm6izScksbzw/sEsassd25PKULQX76a128KzrUny7hAewvrWFLbilje0V6uyQRERFpxfT0KiIi0oplFlcyf00W763PpbS6HgA/m5XLkuO5fmx3hiZEYLFYvFylyDHJ9gj2lxaQlluiUEpEREROSaGUiIhIK+NwGnyzs4g3VmexbPeBxvP2ToFcP6Y704fbiQzx92KFIieXkhDBV9sKmszoExERETkRhVIiIiKtRHFFLe+uy+GtNdnklVQDYLHAOX2iuWFsd87uE4PNqllR0rqp2bmIiIg0l0IpERERLzIMgw1Zh3ljdRZfbMmn3mEA0CnIl6tHJjBzVHe6RQZ5uUqR5ht0JJTKPVzNwYpazeoTERGRk1IoJSIi4gWVtQ18tDmPN1ZlsbOgvPH8kIQIZo3tziWD4wnwtXmxQpHTExbgS8/oYPYeqCQtr5Rz+8Z4uyQRERFppRRKiYiIeFB6UTlvrs5m4YZcymsbAAjwtXJFSleuH9OdwUdmmYi0ZSn2CDOUylEoJSIiIienUEpERMTN6h1OFm0v5I1VWazae7DxfI+oYK4f051pw+yEB/l6sUIR10q2h/PhpjzS1FdKRERETkGhlIiIiJsUltXw1pps3l6bTVF5LQBWC0zqH8ussYmM6xWJVY3LpR1KtkcAZrNzwzCwWPTnXERERI6nUEpERMSFDMNg1d6DvLk6i6+3FeJwmo3Lo0L8mTEqgRmjutElItDLVYq418AuYfhYLRRX1LG/tIau+jMvIiIiJ6BQSkRExAXKaur5YEMub67JJr2oovH8qB6duWFMdyYPjMPPx+rFCkU8J8DXRp/YULbnl5GWU6JQSkRERE5IoZSIiMgZ2L6/jDfXZPHRpjyq6hwABPvZuHKY2bi8X1yYlysU8Y6UhHC255eRmlvKxYPjvV2OiIiItEIKpURERFqotsHBV1sLeGNVFuuzDjee7x0Twqyx3ZkytCuhAWpcLh1bij2Ct9fmqNm5iIiInJRCKRERkWbKK6nmrTVZvLsuh+KKOgB8rBYmD4rjhjHdGd2jsxo6ixxxtNn5ltxSnE5DTf1FRETkOAqlRERETsHpNFieXswbq7L4ZmchR/qWExcWwHWju3HtyARiwgK8W6RIK9QnNoQAXyvltQ3sO1hJr+gQb5ckIiIirYxCKRERkRMoqarj/fW5vLkmi6yDVY3nz0qK5IYxiUzqH4OPTY3LRU7Gx2ZlYJdwNmQdJi23RKGUiIiIHEehlIiIyA+k5ZbwxqosPkndT22DE4DQAB+mDbczc3R3kmL0g7VIcyXbzVAqNaeUK4favV2OiIiItDIKpUREpMOrqXfwaep+3lydRWpuaeP5AfFhzBrbnZ8M6UKQn/7KFGmplCN9pdTsXERERE5ET9giItJhHaqs483VWfxnVWZj43I/m5VLk+O5YWx3hiZEqHG5yBlItocDsG1/GfUOJ75a8ioiIiI/oFBKREQ6nH3Flbzy/V4WbMilpt5cotclPIAbxiZy9Qg7kSH+Xq5QpH1IjAwmNMCH8poGdhWUM6hruLdLEhERkVZEoZSIiHQIhmGwPuswLy3by+IdhRhHdtEb3DWcn0/owSWD4zWLQ8TFrFYLyfZwVqQfJC23VKGUiIiINKFQSkRE2rUGh5OvtxXy0vK9pOaUNJ4/v18MN0/syegenbVET8SNUuwRR0KpEq4b3c3b5YiIiEgrolBKRETapcraBt5bn8Mr3+8j93A1AH4+VqYO68rPxvfULnoiHpJ8pNn5DzcREBEREQGFUiIi0s4UlNYwb2Umb63JoqymAYDOwX5cP6Y7s8Z2J0r9okQ8KiXBXLK3u7Cc6joHgX42L1ckIiIirYVCKRERaRd25Jfx8vK9fJq6n3qH2TCqR1QwP5/Qg6nD7AT46gdhEW+ICwsgOtSfA+W1bM8vZXj3zt4uSURERFoJhVIiItJmGYbBsj3F/Hv5XpbvKW48PyqxMzdP7Mn5/WKwWtUvSsSbLBYLKfZwFu8oIjVHoZSIiIgco1BKRETanNoGB59s3s8r3+9jZ0E5AFYLXDw4npsn9GRIQoR3CxSRJpLtESzeUURabom3SxEREZFWRKGUiIi0GaVV9by5JovXV2ZSVF4LQJCfjWtGJvDTs3qQ0DnIyxWKyIkk282+Umlqdi4iIiI/oFBKRERaveyDVby6Yh/vrc+hqs4BQGyYPzed1YMZo7oRHujr5QpF5FSO7sC3t7iS0up6/TcrIiIigEIpERFpxTZmH+bfy/fy1dYCnGbvcvrFhfKLiT25LLkLfj5W7xYoIs3SOdiPhM6B5ByqZktuKeN7R3m7JBEREWkFFEqJiEir4nAaLNpeyL+X72V91uHG8xP7RPOLCT05KykSi0XNy0XammR7BDmHqknNLVEoJSIiIoBCKRERaSWq6xws2JDDK9/vI/NgFQC+NgtThnTl5xN60jcu1MsVisiZGGKP4PO0fDU7FxERkUYKpURExKsOlNfyn1WZvLk6i8NV9QCEB/py/ZhuzB6bSExYgJcrFBFXULNzERER+V8KpURExCv2FJbz7+X7+HBTHnUOJwAJnQP5+fieTBtuJ9hff0WJtCeDuoZjtUB+aQ1F5TXEhCpwFhER6ej0xC8iIh5jGAarMg7y0vK9LN11oPH80G4R/GJCTy4cGIfNqn5RIu1RsL8PSTEh7C6sIC2nlEkDFEqJiIh0dAqlRETE7eodTj5Py+elZXvZnl8GgMUCFw6I5RcTezK8e2cvVyginpBsjzBDqdwSJg2I9XY5IiIi4mUKpURExG3Kaup5Z202r63IJL+0BoAAXyvThyfws/E9SIwK9nKFIuJJKfZwFmzIJVV9pURERASFUiIi4gZ5JdW89v0+3lmXQ0VtAwBRIf7cOK47M0d3p1Own5crFBFvSLZHAJCaW4JhGFgsWq4rIiLSkSmUEhERl0nLLeHl5fv4Yks+DqcBQO+YEG6e0JOfDOlCgK/NyxWKiDf1iw/F12ahpKqenEPVdIsM8nZJIiIi4kUKpURE5Iw4nQbf7Czi5eV7WbPvUOP5s5Ii+fmEnpzTJ1qzIUQEAH8fG/3jw0jLLSU1t0ShlIiISAenUEpERE5LTb2DDzfl8fLyvew9UAmAj9XC5Sld+Nn4HgzqGu7lCkWkNUq2h5OWW0pabgmXp3TxdjkiIiLiRQqlRESkRQ5W1PLG6izeWJXFwco6AEL9fbhudDduPCuR+PBAL1coIq1Zij2CN8lWs3MRERFRKCUiIs2TfbCKF5ZlsHBDLrUNTgC6RgRy01mJXDMygdAAXy9XKCJtQUpCBABb80pxOA1sVi3vFRER6agUSomIyCkVltXwzJI9vLsuh4YjzcsHdw3n5ok9uWRQHD42q5crFJG2pFd0CEF+NqrqHGQcqKBPbKi3SxIREREvUSglIiIndLiyjheWZfD6ykxq6s2ZURN6R3HruUmM7tFZzctF5LTYrBYGdQ1n7b5DpOaUKJQSERHpwBRKiYhIE5W1Dbz6/T5eWraX8toGAIZ378R9k/sypmekl6sTkfYgxW6GUmm5pUwfkeDtckRERMRLFEqJiAgAtQ0O5q/O5p/fpjc2MO8XF8pvL+rLuX1jNDNKRFwm2R4BQFpuiVfrEBEREe9SKCUi0sE1OJx8sDGPp5fsIa+kGoDEyCDuvqAPlyd3waomxNKaNNRB5QGoLIKKA1BRCP4hMPBKb1cmLZByJJTanl9GbYMDfx+bdwsSERERr1AoJSLSQTmdBl9tK+CJ/+4i40AlAHFhAdxxfm+mj7Djqwbm4imOhh8ETUc/Cs1zTY4Lofrw8e/vOlyhVBuT0DmQTkG+HK6qZ2d+eeOOfCIiItKxKJQSEelgDMNg2Z5iHv96J1vzygDoFOTLr89J4oax3Qnw1YwFcQGnAyqLjwRKP5jVdDRcOho+VRZB1SHAaP69rT4QHG1+hMRCTH+3fRviHhaLhcH2CJbtPkBabolCKRERkQ5KoZSISAeyIesQf/1qF2v3HQIg2M/Gzyf05OcTehAa4Ovl6qTVczrMAKkxaDrRrKYjQVNlMS0Kmiw2CI6CkBgIjjHDppDopschsebXgZ3Aqpl8bV2KPZxluw+QmlvKDd4uRkRERLxCoZSISAewfX8Zf//vLr7ZWQSAn4+VWWO6c8s5vYgM8fdydeJVTidUHzp+mVxF0Q+Oj3yuKgbD2fx7W6wQdCRoagybfhAuHT0fEguBnRU0dTApanYuIiLS4SmUEhFpx/YVV/KPRbv5JHU/ADarhatH2Ln9vN50iQj0cnXiEaV5kLsWyvY3ncl0NGyqPACGowU3tEBQ5P8ETT8Il4Kjjx0HRYJVy0HlxJITwgFIL6qgsraBYH89loqIiHQ0+ttfRKQdyi+t5pkl6by3PgeH01xCdXlKF+6e1Jue0SFerk7cqiQbMldA5veQ9T0czmze+wI7H79M7kSzmoKiwKbHBzlzMaEBxIcHkF9aw9a8Ukb3jPR2SSIiIuJheqoUEWlHDlXW8fzSdF5flUVdg7nM6ty+0dw7uS8Du4R7uTpxOcMwQ6esIyFU5goozW56jcUG8cnQuefJZzUFR4NNPcXE85Lt4eSX1pCWq1BKRESkI1IoJSLSDlTUNvDv5Xv59/J9VNQ2ADAqsTP3XdSXkYmdvVyduIxhwKG9RwKo780wqiyv6TVWH+gyFLqfBYnjIWE0BIR5p16RH5Fsj+DrbYWkqq+UiIhIh6RQSkSkDaupd/Dm6iz+tTSDQ5V1AAzsEsZ9k/tydp9oLBaLlyuUM2IYULzHXIZ3dCZURUHTa6y+0HU4JJ5lBlEJo8FfSzSlbTjW7LzUu4WIiIiIVyiUEhFpgxocTt7fkMszS/aQX1oDQM+oYH5zYV8uHhSH1aowqk0yDDiw8wczoVaaTcl/yOYH9pHHZkLZR4JfkHfqFTlDg+3msuLsQ1Ucqqyjc7CflysSERERT1IoJSLShjidBp9tyecfi3azr7gSgC7hAdw5qTdTh9nxsVm9XKG0iNMJRduPNSXPWglVB5te4xNgBk+J482PriPAN8A79Yq4WHigLz2igtlXXElabgnn9I3xdkkiIiLiQQqlRETaAMMwWLrrAI9/vYvt+WUAdA7249Zzk5g5uhsBvjYvVyjN4nRA4dZjS/GyV0L14abX+AZBwijofjSEGgY+/t6pV8QDku3hR0KpUoVSIiIiHYxCKRGRVm7tvkM8/vVO1mWa4UWovw83T+zJT8f3IMRf/xtv1RwNUJB2rCl51iqo/Z/eOX4hZh+oxLMgcQLEDwEfLWFqzx577DHmzJnDnXfeyVNPPXXCa+bNm8dNN93U5Jy/vz81NTUeqNCzku0RfLx5P2lqdi4iItLh6KcZEZFWamteKX//7y6W7joAgL+PlRvHJfKrs3vRSX1XWidHPeSnQubyIzOhVkNdedNr/MOg2xhzFlT38RCfAjb9ddxRrFu3jhdffJHk5OQfvTYsLIxdu3Y1ft1eNy4YkmD2lUrNLcUwjHb7fYqIiMjx9BQsItLK7D1QwROLdvN5Wj4APlYL14xM4PbzehMXrl5CrUpDHezfZIZQWSsgew3UVza9JiAcuo07MhNqPMQlg1XLLTuiiooKZs6cycsvv8yf/vSnH73eYrEQFxfngcq8a0B8ODarhQPltRSU1RAfHujtkkRERMRDFEqJiLQS+0uqeXrxHhZszMXhNLBY4IqULtw1qQ+JUcHeLk8AGmohb8Ox3fFy1kJDddNrAjuZO+Md3R0vdqBCKAHg1ltv5dJLL2XSpEnNCqUqKiro3r07TqeTYcOG8Ze//IWBAwee9Pra2lpqa2sbvy4rK3NJ3e4W6GejT2woO/LLSM0pVSglIiLSgSiUEhHxsoMVtfzz2wzeXJ1FncMJwKT+sfzmwj70jw/zcnUdXH015K4zl+JlrTCPG/6np09QFHQfd2x3vOj+YNUuiNLUO++8w8aNG1m3bl2zru/bty+vvvoqycnJlJaW8ve//51x48axbds27Hb7Cd8zd+5cHn74YVeW7TEp9nB25JeRllvCRYPa/+wwERERMSmUEhHxkrKaev69bC+vfL+PyjoHAGN6dua+yf0Y3r2Tl6vroOqqIGeNGUBlroC89eCoa3pNcMyxpXjdx0N0X1APHDmFnJwc7rzzThYtWkRAQPOW4I4dO5axY8c2fj1u3Dj69+/Piy++yKOPPnrC98yZM4d77rmn8euysjISEhLOrHgPSbZH8M66HNJyS3/8YhEREWk3TiuU+uc//8njjz9OQUEBKSkpPPvss4waNeqE13ak3WNERJqjpt7Bf1Zl8q+lGZRU1QPmluj3Te7L+KQoNfn1JKcD9m+G9EWQ8Q3kbQRnfdNrQuOPLcVLHA+RSQqhpEU2bNhAUVERw4YNazzncDhYtmwZzz33HLW1tdhsp17i6evry9ChQ0lPTz/pNf7+/vj7+7usbk9KtpvNztNyS3A6DaxW/TcmIiLSEbQ4lHr33Xe55557eOGFFxg9ejRPPfUUkydPZteuXcTExJzwPR1l9xgRkVOpdzh5b30OzyzZQ2GZ2fclKSaEey/sw+SBcfp/o6dUHDADqPRFkL4Eqg81fT3M/oOZUGdB554KoeSMnH/++WzZsqXJuZtuuol+/fpx//33/2ggBWaItWXLFi655BJ3lelVfeNC8fexUlbTQObBSnpGh3i7JBEREfGAFodSTz75JDfffHPj7KcXXniBzz//nFdffZUHHnjghO/pKLvHiIiciNNp8Gnafp5ctJusg1UAdI0I5O4L+nDl0K7YNCPAvRwNZnPy9EWQvticGYVx7HX/cOh1DiRNgh4TIaK7QihxqdDQUAYNGtTkXHBwMJGRkY3nZ82aRdeuXZk7dy4AjzzyCGPGjCEpKYmSkhIef/xxsrKy+PnPf+7x+j3B12ZlQJcwNmWXkJZbqlBKRESkg2hRKFVXV8eGDRuYM2dO4zmr1cqkSZNYtWrVSd/XUXaPERH5IcMwWLKjiL//dxc7C8oBiArx47Zzk5gxuhv+PtqRzW3KC8xZUOmLIONbqClp+npcMvS+AJIuAPsIsPl6pUyRo7Kzs7H+oEH+4cOHufnmmykoKKBTp04MHz6clStXMmDAAC9W6V4p9gg2ZZeQmlvClKFdvV2OiIiIeECLQqni4mIcDgexsbFNzsfGxrJz584Tvqej7R4jIgKwKuMgj3+9k43ZJQCEBvjwq7N7cdNZiQT5aY8Jl3PUQ85acyZU+iIoaLpUioAI6HWeGUT1Oh9CY094GxFPWbp06Sm//sc//sE//vEPzxXUChzrK6Vm5yIiIh2F238y6mi7x4hIx7Z9fxlzv9zB8j3FAAT4WrnprB78amIvwoM0G8elSvOOhVB7v4PaH86qtUCXoUdmQ02CrsPBqplpIq1ZSkIEANv2l9LgcOJjs576DSIiItLmtSiUioqKwmazUVhY2OR8YWFhs3tGtffdY0SkY6prcPLcN3v459IMHE4DX5uFGaO6cdu5ScSENW8LePkRDXWQsxr2HOkNVbS96etBkeYsqN4XmLOigqO8U6eInJYekcGE+vtQXtvA7sIKBnQJ83ZJIiIi4mYtCqX8/PwYPnw4S5YsYcqUKQA4nU6WLFnCbbfd1qx7tPfdY0Sk49mSW8p9C1Ib+0ZdMjiOORf3J6FzkJcrawdKso+EUEtg33dQV3HsNYsVuo4wZ0L1ngTxQ8GqmRUibZXVamGwPZyVGQdJyy1RKCUiItIBtHj53j333MPs2bMZMWIEo0aN4qmnnqKysrJxN76OvnuMiHQctQ0Onl2SzvPfmbOjIoP9eHTKIC4ZHO/t0tqu+hrIXgl7FpuzoYp3NX09OMYMoZLON2dDBXX2Tp0i4hbJ9ghWZhwkNbeUa0d5uxoRERFxtxaHUtdccw0HDhzgwQcfpKCggCFDhvDVV181Nj/X7jEi0hGk5ZZw7/up7C40Z+5cntKFhy4fQGSIlh632KG95kyoPYsgcznUVx17zWKDhFFHZkNdALGDNRtKpB1LaWx2XuLdQkRERMQjLIZhGN4u4seUlZURHh5OaWkpYWGayi0i3lPb4ODpxXt4cdleHE6DqBA//jRlEBcN0uyoZquvhszvzZlQexbBoYymr4fGmzOhki6AnudAYIQ3qhRp1FafQ9pi3Xkl1Zz12Df4WC1sfXgyAb7aoEBERKQtau5ziPYlFxFpps05Jdz3fip7iszZUVcM6cIfLx9I52A/L1fWyhkGHMwwd8lLX2wGUg01x163+kC3sUeW5U2C2IFgsXivXhHxmi7hAUSF+FFcUce2/WUM797J2yWJiIiIGymUEhH5ETX1Dp5avIeXlmXgNCAqxJ8/XzmIyQObt+toh1RXCfuWm0HUnkVQktX09TC72Zw86QLoMREC2sYsDhFxL4vFQrI9gm92FpGWW6JQSkREpJ1TKCUicgobsw9z3/upZByoBODKoV158LIBdNLsqKYMAw7sMmdCpS+CrJXgqDv2us0Puo87MhvqAojuq9lQInJCyfbwI6FUqbdLERERETdTKCUicgI19Q7+sWg3Ly/fi9OA6FB//nLlYC4YEOvt0lqP2nLY+92RZXlLoDSn6esR3c3m5EmTIHEC+Id4p04RaVNS7BEApKrZuYiISLunUEpE5H9syDrMfQtS2XtkdtRVw8zZURFBHXx2lGFA0XZzOV76YsheBc6GY6/b/CFx/LEgKjJJs6FEpMWSj+zAt/dAJWU19YQF+Hq5IhEREXEXhVIiIkfU1Dt44r+7+Pf3+zAMiAn1Z+5Vgzm/fwefHVWSA2nvQurbcDC96Wude5kBVO8LoPtZ4BfknRpFpN2IDPHH3imQ3MPVbM0tZVxSlLdLEhERETdRKCUiAqzPPMRvF6Sxt9icHTVtuJ0/XDqA8KAO+hv62grY8SmkvmU2LMcwz/sEmo3JkyaZjco79/RqmSLSPqXYI8g9XE2qQikREZF2TaGUiHRo1XUO/v7fXby6wpwdFRvmz2NXJXNuvxhvl+Z5TidkfQ+b34btH0N95bHXEidAygwY8BPwD/VejSLSISTbw/l8Sz5p6islIiLSrimUEpEOa+2+Q/x2QSqZB6sAmD7czu8vG0B4YAebHXUwAza/ZS7R+2Gz8s49IeU6SLkGIrp5rz4R6XCSjzQ71w58IiIi7ZtCKRHpcKrqGnj8613MW5mJYUBcWABzpw7m3L4daHZUdQls+8CcFZW79th5/3AYdKUZRiWMUqNyEfGKwfZwLBbIK6nmQHkt0aH+3i5JRERE3EChlIh0KGv2HuS3C9PIOjI76poRCfzfZf07xu5OjgbI+MbsE7XzC3DUmuctVrNHVMq10PcS8A30bp0i0uGF+PvQKzqE9KIK0nJLtOGEiIhIO6VQSkQ6hKq6Bv72lTk7CiA+PIDHpiZzdp9o7xbmCQVbzZ3z0t6DyqJj52MGwpAZMPhqCNUPfCLSuiTbw0kvqiA1t1ShlIiISDulUEpE2r1VGQe5f2Ea2YfM2VEzRiUw55J2Pjuq4gBsed+cFVWw5dj5oCgYPN0Mo+KStTxPRFqtFHsEH2zMU7NzERGRdkyhlIi0W5W1Dfz1q538Z1UWAF0jApl71WAmttfZUQ21sOtLSH0H0heBs8E8b/WFvheZfaJ6XwC2dhzGiUi7kWwPB8xm54ZhYFGILiIi0u4olBKRdmllejG/XZhG7uFqAK4b3Y05F/cjtL3NjjIMyNtg7p63dSHUlBx7retwSJkBg6ZCUGevlSgicjr6x4fha7NwqLKO3MPVJHQO8nZJIiIi4mIKpUSkXamobeCxL3fw5upswJwd9depyYzvHeXlylysNA/S3jFnRRXvPnY+tAukXGOGUdF9vVefiMgZCvC10S8ujC15paTlliqUEhERaYcUSolIu7EivZjfLkgjr8ScHXX9mG48cHF/Qvzbyf/q6iphx2dmn6i93wGGed4nEAb8xAyiekwEq82rZYqIuEqyPfxIKFXCpcnx3i5HREREXKyd/KQmIh1ZeU09c7/cyVtrzNlR9k6B/G1qMuOS2sHsKKcTslaYu+dt/xjqKo691n282bB8wBXgH+q9GkVE3CTFHsH8Ndmkqtm5iIhIu6RQSkTatOV7DvDAwi2Ns6Nmje3O/Rf1I7itz446mGEuzUt7B0qyj53v1MOcEZVyDXRK9Fp5IiKekJxgNjvfmleGw2lgs6rZuYiISHvSxn9qE5GOqrymnr98sYO31+YAkNA5kL9NTWFsr0gvV3YGakph24ew+W3IWX3svH8YDLzSDKO6jQHtQCUiHURSdAiBvjYqahvYe6CC3rGaFSoiItKeKJQSkTbnu90HmLMwjf2lNQDcOC6R317UlyC/Nvi/NEcD7P3W3D1v1xfQYH5PWKzQ6zwziOp3KfgGerdOEREv8LFZGdQ1jHWZh0nNLVUoJSIi0s60wZ/gRKSjKqup58+f7eDd9ebsqO6RQfx1ajJjerbB2VGF282G5WnvQUXhsfPR/c0+UYOvhjA19RURSbZHsC7zMGm5JUwbbvd2OSIiIuJCCqVEpE34dlcRv/tgC/mlNVgs5uyo+ya3sdlRlcWw5X2zaXl+6rHzgZ1h8HQzjIofouV5IiI/kGw3+0ql5pZ6uRIRERFxtTb005yIdESl1fX86bPtvL8hF4DEyCD+Ni2FUT06e7myZmqog91fmUHUnv+Cs8E8b/WFPpNhyHWQdAH4+Hm3ThGRVirFHgHAjv1l1DU48fOxercgERERcRmFUiLSan2zs5A5H2yhsKwWiwV+elYP7r2wL4F+Nm+XdmqGAfs3mg3Lty6A6sPHXusyFFKug0FTIbgNLjsUEfGw7pFBhAf6Ulpdz66CcgYfmTklIiIibZ9CKRFpdUqr6nnks+0s3GjOjuoRFczj05IZkdjKZ0eVF0DqO2bT8uJdx86HxkPy1WYYFdPPe/WJiLRBFouFZHs4y/cUk5pbolBKRESkHVEoJSKtyuLthfzuwy0UlZuzo34+vge/ubAvAb6tdHZUQx3s/hI2zYf0xWA4zPM+gdD/MnP3vJ7ngLWV1i8i0gak2CNYvqeYtNwSoLu3yxEREREXUSglIq1CSVUdj3y6nQ825QHQM9qcHTW8eyudHZWfBpvnm7vnVR86dj5hjNknauCVEBDmvfpERNqRo83O09TsXEREpF1RKCUiXrfoyOyoA+W1WC1w84Se3H1Bn9Y3O6rqkLl73qY3oSDt2PnQeEi5FobMhKje3qtPRKSdSkmIAGB3YTlVdQ1ta+dVEREROSn9jS4iXnO4so6HP93GR5v3A9ArOpjHp6cwrFsnL1f2A04HZHwDm96AXV+Co848b/ODvpfA0Ouh13lanici4kaxYQHEhvlTWFbL1ryytrMDq4iIiJySQikR8YqvtxXwfx9upbjCnB31i4m9uGtS79YzO6o4HTa/aTYuL88/dj4u2QyiBk+HIP1QJCLiKcn2CBZtLyQtt0ShlIiISDuhUEpEPKq2wcHvPtjauLNeUkwIf5+ewpAjSzO8qrYctn1oNi3PWX3sfGBnSL4Ghs6EuMHeq09EpANLsYezaHshqeorJSIi0m4olBIRjymtrueXb6xn9d5DWC3wq7N7ccf5Xp4d5XRC1gqzafn2j6G+yjxvsULSBWYQ1edi8PHzXo0iIkKyPQLgyA58IiIi0h4olBIRj8gvrebGV9exq7CcEH8fXrxhOGclRXmvoJIcSH3bbFpeknXsfGRvc3leyrUQGue9+kREpImjO/BlHayipKqOiCD9skBERKStUyglIm63q6CcG19bS35pDTGh/sy7aRQDuoR5vpD6atjxmdkrau93gGGe9wuFQVeZYZR9JFgsnq9NREROKSLIj8TIIDIPVpGWW8rEPtHeLklERETOkEIpEXGr1XsPcvN/1lNe00BSTAjzbhqJvVOQ5wowDMjbaAZRWxZC7Q96kfSYCEOuh/6Xg58HaxIRkdOSbI84EkqVKJQSERFpBxRKiYjbfJa2n3veTaXO4WRE9078e/YIzy23qCgyd87bPB8O7Dx2PrwbDLkOhsyATomeqUVERFwi2R7OJ6n71excRESknVAoJSJu8cr3+/jT59sxDLhoYBxPXTvE/Q3NHfWw+2sziNr9NRgO87xPAPT/ibk8L3ECWK3urUNERNwi5chOrWp2LiIi0j4olBIRl3I6DeZ+uYOXl+8DYPbY7jx4+UBsVjf2aSrcBpvmQ9q7UFV87Lx9JAyZafaLCgh33/giIuIRA7uEYbVAYVktBaU1xIUHeLskEREROQMKpUTEZWobHNz7fhqfpu4H4IGL+/HLiT2xuKNxePVh2LLAnBW1f9Ox8yGxkHyNOSsquq/rxxUREa8J8vOhT2woOwvKSc0tIS5cu6SKiIi0ZQqlRMQlSqvr+eUb61m99xA+VguPT0/myqF21w7idMDepbDpTdj5OThqzfNWX+h7kdm0PGkS2PS/NhGR9irZHs7OgnLSckuYPFChlIiISFumn9xE5IwVlNZw42tr2VlQToi/D89fP4wJvV24K9LBDNj8FqS+DWV5x87HDjKX5yVfDcFRrhtPRERarWR7BO+tzyVNzc5FRETaPIVSInJGdheWc+Ora9lfWkN0qD/zbhrJwC4u6N9UWwHbPzJ7RWWvPHY+IMIMoYbMhPgUcMfSQBERabVS7BEApOWWYhiGe5aIi4iIiEcolBKR07Zm70Fu/s96ymoa6BUdzLybRpHQOej0b2gYkL3KDKK2fQj1leZ5ixV6nWcGUX0vAV81thUR6aj6xoXiZ7NSWl1P1sEqEqOCvV2SiIiInCaFUiJyWj5Py+fudzdT53Ayonsn/j17BBFBfqd3s9I8c2ne5vlwaO+x8517mg3LU2ZAWBfXFC4iIm2an4+VAV3C2JxTQmpuiUIpERGRNkyhlIi02Kvf7+PRz7djGDB5YCxPXzuUAF9by25SXwO7PjdnRe39Fgyned4vBAZOMZuWdxuj5XkiInKcFHs4m3NKSMst5YohXb1djoiIiJwmhVIi0mxOp8FjX+3kpWXmbKYbxnTnoZ8MxGZtQXBUeRC+f9LcQa+m5Nj57meZy/MGXAH+Ia4tXERE2pVkewSQRVpuiZcrERERkTOhUEpEmqW2wcF976fxSep+AH57UV9uObtX8xvM1lbA6n/Bimegrtw8F2aHITNgyHXmUj0REZFmSEkwN9TYmldGg8OJj83q5YpERETkdCiUEpEfVVZTz6/e2MDKjIP4WC38bVoyVw2zN+/NDXWw8XX47m9QWWSei0uG834PSZPA2sJlfyIi0roYhseXWveMCiHE34eK2gbSD1TQLy7Mo+OLiIiIayiUEpFTKiit4cbX1rKzoJxgPxsv3DCcCb2jf/yNTids+wC+eRQOZ5rnOvUww6iBV4FVv9UWEWnTDu2DL38LFYXwy2UeHdpqtTCoaxir9x4iNadEoZSIiEgbpVBKRE5qT2E5s19dy/7SGqJD/XntxpEM6hp+6jcZBmQsgcUPQ0GaeS44Bs7+LQybDT6nuUOfiIi0LoGdIH0JGA4oyYaIbh4dPsUeYYZSuaVcM9KjQ4uIiIiLKJQSkRNau+8QP399HWU1DfSMDub1m0aR0Dno1G/K2wCLH4J9R35j7hcKZ90JY25R83IRkfYmMALsIyFntRlOjbjJo8Obzc5Rs3MREZE2TKGUiBzniy353PXuZuoanAzrFsErs0fSKfgUM5yK0+GbR2D7x+bXNj8YeTNM+A0ER3qmaBER8byk84+EUou9EEqZM3d35pdTU+8gwFc9CkVERNoahVIi0sS8Fft4+LPtGAZcOCCWZ2YMPfmDflk+fPcYbHzDXL6BBVJmwLlzPL6MQ0REvKDX+fDtn80Zso56sPl6bGh7p0A6B/txqLKOHfllDO3WyWNji4iIiGsolBIRAJxOg79+tZMXl+0F4IYx3XnoJwOxWU+wo1J1Cax4Cla/AA3V5rk+F8P5D0LsAI/VLCIiXtZliNlbqvow5K6H7mM9NrTFYiHFHs63uw6QlluqUEpERKQNUiglItQ1OLlvQSofb94PwH2T+/Lrc3ph+d8tvuurYe1LsPxJqCkxzyWMhkkPe/QHERERaSWsNuh1HmxdaG5y4eG/C5LtEXy76wCp6islIiLSJimUEungymrqueXNDaxIP4iP1cJjU5OZNtze9CJHA6S+BUsfg7I881x0f3NmVN+L4X/DKxER6Th6nW+GUulL4Lzfe3TolASzr1RabqlHxxURERHXUCgl0oEVltUw+9W17CwoJ9jPxvPXD2din+hjFxgG7PwMljwKxbvMc2F2OPd3kHKt+RtyERHp2HqdZ37evwkqD3p0g4ujO/BlHKigvKae0ADP9bQSERGRM2f1dgEi4h17Csu56l8r2VlQTlSIP+/+cmzTQCrze3jlAnj3ejOQCuwEk/8Ct2+AoTMVSImIiCksHmIGAgbs/dajQ0eF+NM1IhDDgC15mi0lIiLS1iiUEumA1mUeYurzK8krqaZnVDAf/nocg7qaSyAo2AJvToN5l0LuOvANggn3wp2pMPZW8A3wbvEiItL6JJ1vfk5f4vGhk+1awiciItJWafmeSAfz1dZ87nhnM3UNToZ1i+Dfs0fSOdgPDmfCN3+GLe8DBlh9YNhsOPu3EBrn7bJFRKQ1SzofVj5jNjs3DI/2Gky2R/Dl1gLS1OxcRESkzVEoJdKBvL4yk4c+3YZhwKT+sTw7YyiBdYfgi8dh/avgrDcvHHiV2aw2spd3CxYRkbah21hzZm1FIRRuhbjBHhs65chMqdQczZQSERFpaxRKiXQATqfBX7/eyYvf7QVg5uhuPDy5Gz4rH4eVz0JdhXlhz3Nh0h+hy1AvVisiIm2Ojz8kjoc9/zWX8HkwlBp0JJTKK6nmYEUtkSH+HhtbREREzox6Som0c3UNTu55b3NjIHX/BT35U/wKfJ4bBkvnmoFUl6Ew62OY9ZECKREROT29jvSVyvBsX6mwAF96RQcD6islIiLS1mimlEg7Vl5Tz6/e3MCK9IP4Wg3eHJXD6C1zoCTLvKBzLzj/DzBgikf7f4iISDuUNMn8nL0a6irBL9hjQ6fYI8g4UElqbgnn9ovx2LgiIiJyZhRKibRThWU13PjaOnbklzLZbwtPdP6YkM07zBdD4uCc+2HoDWDz9W6hIiLSPkT2gohuUJINmd9Dn8keGzrZHs4Hm/I0U0pERKSNUSgl0g6lF5Uz+9V1xJSmsTDgXYazHUoA/zA4604Yc4tHf4MtIiIdgMViLuHb8BqkL/ZsKJUQAUBabgmGYWDR7F8REZE2QaGUSDuzPvMQj877mD845nOR/zrzpM0fRv8Cxt8DQZ29W6CIiLRfSUdDKc/2lRoQH4aP1UJxRR37S2voGhHo0fFFRETk9CiUEmlHvl27meLPHuIDy1JsNgPDYsUy5Do4Zw6E271dnoiItHc9JoLFBocy4HAmdEr0yLABvjb6xoWybX8ZqTklCqVERETaCO2+J9IeVB1i67w7Gfv5JKZbv8VmMXD0uQTLLavgin8qkBIREc8ICIeE0eaxh2dLJdsjAEjNLfHouCIiInL6FEqJtGV1VTiXPUnNE8kMypxHgKWefcEpNNz4Fbbr3oaYft6uUEREOpqk88zPGd94dNgUezgAaTlqdi4iItJWaPmeSFvkaIBNb2B891es5fkEADucCaQP/g2XTZ2Nxaq8WUREvKTX+fDNn2Dvd+Co99gur0dnSm3NK8XpNLBa1excRESktVMoJdKWGAbs+ASWPAIH07EAuUYU/3BczZgrfsn0kYnerlBERDq6+CEQFAlVByFnLSSe5ZFh+8SGEOBrpby2gb3FlSTFhHhkXBERETl9mk4h0lbsWwb/Ph/emwUH0ym1hPFw/Q1cajzFZTfcrUBKRERaB6sVep5rHmd4rq+Uj83KoC5HlvCpr5SIiEiboFBKpLXLT4U3roLXL4e8DTh9gnjVdjVnVT/Jp4FX8MYvJnBu3xhvVykiInJM0iTzs5eanaflqq+UiIhIW6DleyKt1aF9Zk+OrQvMr62+FPaZwYxdE9hbHUyPqGBev2kU3SKDvFuniIjI/+p1pNl5/maoOAAh0R4ZNiXBnCmlHfhERETaBs2UEmmNMlfA82cdC6QGT+e7C79k4tZL2FsdTEpCBAt+NVaBlIiItE6hsRA72Dze+63Hhj06U2r7/jLqHU6PjSsiIiKnR6GUSGuTvQbmT4f6SkgYA79cxhtdfs+NHxdR2+Dk/H4xvH3zaCJD/L1dqYiIyMklHZkt5cElfImRQYQF+FDb4GRXQbnHxhUREZHTo1BKpDXJXQ9vTjUDqZ7nYNzwIX9L9ecPH2/DMGDGqARevGE4QX5aeSsiIq3c0b5SGd+A0zOzliwWS+NsKS3hExERaf0USom0FnkbzYbmdeWQOIG66fP5zUe7+dfSDADuuaAPf7lyMD42/WcrIiJtQMIY8A2GyiIo3OqxYZPtR3bgy1GzcxERkdZOP92KtAb5qfDGlVBbCt3GUn/NW9z89nY+2JiHzWrhb1OTueP83lgsFm9XKiIi0jw+ftBjgnmcvthjw2qmlIiISNuhUErE2wq3wX+mQE0J2EfBzPd58rv9fLf7AIG+Nv49ewRXj0zwdpUiIiIt1+t883PGNx4b8ugOfHuKKqiuc3hsXBEREWk5hVIi3lS0E17/CVQfgi7D4PoFLM+u4fkjS/aeuDqFc/vGeLlIERFxpcceewyLxcJdd911yuvef/99+vXrR0BAAIMHD+aLL77wTIGulHQklMpeDbUVHhkyLiyA6FB/HE6Dbfu1hE9ERKQ1Uygl4i3Fe+D1y6GqGOJT4IYPOFAfwN3vpgJw3ehuXDI43stFioiIK61bt44XX3yR5OTkU163cuVKZsyYwc9+9jM2bdrElClTmDJlClu3eq43k0t07gmdEsFZD5nLPTKkxWIhpXEJn0IpERGR1kyhlIg3HMwwA6nKIogdDDd8hNM/gnve20xxRS19Y0N58LIB3q5SRERcqKKigpkzZ/Lyyy/TqVOnU1779NNPc9FFF3HffffRv39/Hn30UYYNG8Zzzz3noWpdxGI5toQvfYnHhk052uxcfaVERERaNYVSIp52aJ8ZSJXnQ3R/mPURBHXm5eV7Wb6nmABfK89eN5QAX5u3KxURERe69dZbufTSS5k0adKPXrtq1arjrps8eTKrVq1yV3nuc3QJnyebnSdEAJCmmVIiIiKtmo+3CxDpUEqyzUCqLA+i+sDsTyA4ik3Zh3n8610A/PHygfSJDfVyoSIi4krvvPMOGzduZN26dc26vqCggNjY2CbnYmNjKSgoOOl7amtrqa2tbfy6rKzs9Ip1tcQJYPWBw/vg0F5zSZ+bJXc1Z0rtK66ktLqe8EBft48pIiIiLaeZUiKeUpoL8y6D0hyITILZn0JIDGU19dzxziYanAaXDo7nWu20JyLSruTk5HDnnXcyf/58AgIC3DbO3LlzCQ8Pb/xISGglf58EhEHCaPPYQ0v4OgX70a1zEABbNFtKRESk1VIoJeIJZfvNGVIlWdCphxlIhcZhGAa/+2ALOYeqsXcK5C9XDcZisXi7WhERcaENGzZQVFTEsGHD8PHxwcfHh++++45nnnkGHx8fHA7Hce+Ji4ujsLCwybnCwkLi4uJOOs6cOXMoLS1t/MjJyXH593Laji7hy/jGY0MmH+krlaq+UiIiIq2WQikRdysvNAOpQ3shopsZSIV1AeC99Tl8lpaPzWrhmRlDtbxARKQdOv/889myZQubN29u/BgxYgQzZ85k8+bN2GzH9xAcO3YsS5Y0nVW0aNEixo4de9Jx/P39CQsLa/LRahxtdr5vGTTUeWTIxh34cko8Mp6IiIi0nHpKibhTxQEzkDqYDuEJMPsziDCXU6QXlfPHT7YB8JsL+zCs26l3YhIRkbYpNDSUQYMGNTkXHBxMZGRk4/lZs2bRtWtX5s6dC8Cdd97J2WefzRNPPMGll17KO++8w/r163nppZc8Xr9LxCVDUBRUFUPOGugxwe1DJjfuwKfleyIiIq2VZkqJuEvlQfjPFVC8C0K7mE3NO3UHoKbewW1vbaKm3sn4pCh+NbGXl4sVERFvys7OJj8/v/HrcePG8dZbb/HSSy+RkpLCggUL+Oijj44Lt9oMqxV6nWceZ3imr9SgruFYLVBQVkNRWY1HxhQREZGW0UwpEXeoOgRvXAFF2yAkDm78rMluQ3/+fAc7C8qJCvHjyWtSsFrVR0pEpCNZunTpKb8GmD59OtOnT/dMQZ6QdD5sec9sdj7pIbcPF+zvQ1JMCLsLK0jNLeWCAe5rMi8iIiKnRzOlRFytugTeuBIKtkBwjNlDKvLYTKivtubzxuosAJ64eggxoXpIFhGRDuDoTKmCNKgo8siQR/tKpanZuYiISKukUErElWrK4M2rIH8zBEWaS/ai+zS+nHu4it8uSAPglxN7cnafaC8VKiIi4mEhMWZvKfDYLnzJCREApKqvlIiISKukUErEVWrLYf40yNsAgZ1g1scQ07/x5QaHk7ve2UxZTQMpCRH85sK+XixWRETEC5KO7MKX7pm+UimNzc5LMAzDI2OKiIhI8ymUEnGFukqYf7W5o1BAONzwEcQNbnLJ00v2sD7rMKH+Pjx77VD8fPSfn4iIdDC9joRSGd+A0+n24frFheFns1JSVU/OoWq3jyciIiIto5+KRc5UXRW8dQ1krwT/MLjhQ+gypMklK9OLee7bdAD+ctVgukUGeaFQERERL0sYDX4hUFVs9pZyMz8fK/3jQwHYrL5SIiIirY5CKZEzUV8D71wHmcvBLxSu/wC6Dm9yycGKWu56dzOGAdeMSODylC5eKlZERMTLfPygx0TzOMMzS/iSjzY7zynxyHgiIiLSfAqlRE5XQy28OxP2fgu+wXD9AkgY2eQSwzC49/1UisprSYoJ4Y8/GeClYkVERFqJo7vweaivVHJjXyk1OxcREWltFEqJnI6GOnhvFqQvBp9AmPkedBtz3GWvfL+Pb3cdwM/HynPXDSXIz8cLxYqIiLQiR5ud56wxd611s5QjO/Bt3V+Kw6lm5yIiIq2JQimRlnLUw4KbYPdX4BMA170LieOPu2xLbil//WonAH+4tD/94sI8XamIiEjr07kndOoBzgZz+bub9YoOIcjPRlWdg/SiCrePJyIiIs2nUEqkJRwNsPDnsPMzsPnDtW9Bz7OPu6yitoHb395IvcNg8sBYrh/T3QvFioiItFJJk8zPHljCZ7NaGNTVXMKXqmbnIiIirYpCKZHmcjrgw1/C9o/A5gfXvHlsCcIPGIbB7z/cQubBKrqEB/DXqclYLBbP1ysiItJaHf37M30xGO5fUjfkyBK+NIVSIiIirYpCKZHmcDrgo1/D1gVg9YGr/wN9LjzhpQs35vHR5v3YrBaemTGUiCA/DxcrIiLSyiVOAKsvlGTBob1uH07NzkVERFonhVIiP8bphE/ugLR3wGKDaa9B34tPeGnGgQoe/HgrAHed35sRiZ09WamIiEjb4B9ybIMQDyzhS7FHALAjv4zaBofbxxMREZHmUSglciqGAZ/fDZvfBIsVpv4bBvzkhJfWNji4/a1NVNU5GNszkl+fm+ThYkVERNqQXueZnzPcH0rZOwXSKciXeofBzvxyt48nIiIizaNQSuRkDAO+uA82zAMscOWLMOiqk14+94udbM8vo3OwH09dOwSbVX2kRERETupos/N9y6Gh1q1DWSwWko/MllKzcxERkdZDoZTIiRgGfP07WPcyYIEp/4Lkq096+aLthcxbmQnA36cnExsW4Jk6RURE2qrYQRAcA/WVkL3a7cOlHOkrlZqjvlIiIiKthUIpkf9lGLDoQVj9L/PrnzwDQ6476eX5pdXctyAVgJ+N78F5/WI9UaWIiEjbZrV6dAnf0ZlS2oFPRESk9VAoJfJDhgHfPAornzG/vvRJGDbrpJc7nAZ3vrOZkqp6BnUN47cX9fVQoSIiIu1A0vnm5/Rv3D5UcoI5Uyr9QAUVtQ1uH09ERER+nEIpkR9a+hgsf8I8vvhxGPmzU17+7Dd7WLvvEMF+Np6dMQx/H5sHihQREWknep5rfi7cAuWFbh0qJjSA+PAADAO25mkJn4iISGugUErkqGWPw3ePmceT/wKjf3HKy9fsPcgzS/YA8KcrB9EjKtjdFYqIiLQvIdEQP8Q8zvDAbKkjfaW0hE9ERKR1UCglAvD9U/DNn8zjSQ/D2FtPefnhyjrufGczTgOmDrNz5VC7+2sUERFpjxqX8C12+1ApCREApOZqppSIiEhroFBKZNU/YfEfzePzfg/j7zrl5YZhcN+CNArKaugZFcwjVwx0f40iIiLtVa8jodTeb8HpdOtQKWp2LiIi0qqcVij1z3/+k8TERAICAhg9ejRr165t1vveeecdLBYLU6ZMOZ1hRVxvzYvw9e/M47MfgIn3/ehbXl+ZyeIdhfjZrDwzYyjB/j5uLlJERKQdSxgFfqFQdRDyN7t1qEFdzeV7OYeqOVRZ59axRERE5Me1OJR69913ueeee/jjH//Ixo0bSUlJYfLkyRQVFZ3yfZmZmdx7771MmDDhtIsVcal1r8CXvzWPJ/wGznngR9+ybX8pf/liJwBzLunX+HArIiIip8nmCz0mmscZS9w6VHigLz2P9IDUbCkRERHva3Eo9eSTT3LzzTdz0003MWDAAF544QWCgoJ49dVXT/oeh8PBzJkzefjhh+nZs+cZFSziEhteh8/vMY/H3QHn/QEsllO+pbK2gdvf3kSdw8mk/jHcOC7R/XWKiIh0BI19pTzX7Dw1R32lREREvK1FoVRdXR0bNmxg0qRJx25gtTJp0iRWrVp10vc98sgjxMTE8LOf/axZ49TW1lJWVtbkQ8RlNr8Fn95pHo++BS545EcDKYA/frKNvQcqiQsL4PFpKVia8R4RERFphqOhVM4aqHFvWJSsvlIiIiKtRotCqeLiYhwOB7GxsU3Ox8bGUlBQcML3fP/997zyyiu8/PLLzR5n7ty5hIeHN34kJCS0pEyRk0t7Hz76NWDAyJvhornNCqQ+2pTHgg25WC3w1LVD6BTs5/5aRUREOopOidC5FxgO2LfMrUOlJByZKZVbimEYbh1LRERETs2tu++Vl5dzww038PLLLxMVFdXs982ZM4fS0tLGj5ycHDdWKR3G1g/gw18ABgy/ES7+W7MCqcziSv7vwy0A3H5eb8b0jHRvnSIiIh1R4xI+9/aVGhAfjs1qobiilvzSGreOJSIiIqfWom3DoqKisNlsFBYWNjlfWFhIXFzccddnZGSQmZnJ5Zdf3njOeWSrXx8fH3bt2kWvXr2Oe5+/vz/+/v4tKU3k1LZ/Agt/DoYThl4Pl/4DrD+eydY1OLn97U1U1jkYldiZ289L8kCxIiIiHVDSJFj7ktns3DCa9Yuj0xHoZ6NPbCg78stIyy2hS0SgW8YRERGRH9eimVJ+fn4MHz6cJUuO/QbL6XSyZMkSxo4de9z1/fr1Y8uWLWzevLnx4yc/+Qnnnnsumzdv1rI88YydX8CCm8wlAcnXwuXPNCuQAvjbVzvZkldKRJAvT107BB+bWycXioiIdFyJ48HmByXZcDDDrUOl2I8t4RMRERHvadFMKYB77rmH2bNnM2LECEaNGsVTTz1FZWUlN910EwCzZs2ia9euzJ07l4CAAAYNGtTk/REREQDHnRdxi93/hfdmgbMBBk2DKf8Cq61Zb/12ZxH//n4fAH+bmqzfpIqIiLiTXzB0G2P2lEpfDFHum52ckhDBO+ty1OxcRETEy1ocSl1zzTUcOHCABx98kIKCAoYMGcJXX33V2Pw8OzsbazNnoYi4VfoSePd6cNbDgClw5YvNDqQKy2r4zfupANw4LpELBx6/PFVERERcrNf5ZiiVsQTG/MptwyQfmSmVlluK02lgtWpHXREREW9ocSgFcNttt3Hbbbed8LWlS5ee8r3z5s07nSFFWmbvUnjnOnDUQr/LYOq/wda8P+4Op8Hd727mUGUd/ePDeODifu6tVURERExJ58PiP0Lm99BQCz7u6THaJzYUfx8r5TUNZB6spGd0iFvGERERkVPTlCZpfzK/h7euhYYa6HMxTHsNbL7NfvsL32WwMuMgQX42nrtuKAG+zZtdJSIiImcodhCExEJ9FWSvctswvjYrA7uEAeZsKREREfEOhVLSvmStgvlXQ0M1JF0AV78OPn7NfvuGrEM8uWg3AA//ZCC99JtTERERz7FYzCV8YPaVcqNkewQAm3NK3DqOiIiInJxCKWk/ctbB/GlQXwk9z4Vr3mzRtP/SqnrueHszDqfBlCFdmDbc7sZiRURE5ISSjoZS37h1mJSEo32lStw6joiIiJycQilpH/I2wptXQV0FJE6Aa98C34Bmv90wDO5fmEZeSTXdI4P405WDsVjU9FRERMTjep4LWKBoG5Tlu22YozOltu0vo97hdNs4IiIicnIKpaTty0+FN6ZAbRl0GwfXvQt+QS26xfw12Xy1rQBfm4VnZwwlxP+09gAQERGRMxUcCV2GmMcZ7pst1SMymFB/H2obnOwuLHfbOCIiInJyCqWkbSvYCv+5AmpKIWE0zHwP/IJbdIudBWU88tl2AO6/qF/jb05FRETES5ImmZ8zlrhtCKvVwmD70SV8anYuIiLiDQqlpO0qzTMDqerD0HU4zFwA/qEtukVVXQO3vbWJugYn5/SN5qdn9XBTsSIiItJsR5udZ3wDTofbhjn6iyj1lRIREfEOhVLSdn35W6gqhrjBcP0HEBDW4ls88ul20osqiAn15+/TU7Ba1UdKRETE6+wjwD/M/MXT/s1uG2bIkWbnqTmaKSUiIuINCqWkbdr5Bez8DKw+cOVLEBjR4lt8mrqfd9blYLHAU9cMISqk+Tv1iYiIiBvZfKHHRPPYjUv4js6U2lVYTk29+2ZkiYiIyIkplJK2p7YCvrjPPB57G8QOaPEtcg5V8bsPtgBw6zlJjEuKcmWFIiIicqaSjizhS3dfKBUfHkBUiD8Op8G2/WVuG0dEREROTKGUtD1L50JZLkR0g7Pvb/Hb6x1Obn97E+W1DQzv3om7JvV2Q5EiIiJyRo72lcpdB9UlbhnCYrGQ0tjs3D1jiIiIyMkplJK2pWALrH7ePL7kCfALavEtnvjvbjbnlBAW4MPT1w7Bx6b/DERERFqdTt0hsjcYDtj3nduGObqELzWnxG1jiIiIyInpp3FpO5xO+PQu8+F0wBXQ58IW32LZ7gO88F0GAH+bloy9U8tDLREREfEQDyzhS044OlNKzc5FREQ8TaGUtB0bXoO89eAXChf9tcVvLyqv4Z73NgNw/ZhuXDQo3sUFioiIiEsdXcKX8Q0YhluGSDkyU2pvcSWl1fVuGUNEREROTKGUtA3lhbD4YfP4/D9AWMsCJafT4DfvpVJcUUe/uFB+f2nLm6OLiIiIhyWeBTZ/KM2B4j1uGaJzsB/2ToEAbM3TbCkRERFPUiglbcPXv4PaUogfAiN/3uK3v7R8L8v3FBPga+XZGUMJ8LW5vkYRERFxLb9g6D7WPM5w3xK+o7OlUtXsXERExKMUSknrl74Eti4AixUufwqsLQuUNmUf5u9f7wLgocsH0js21A1FioiIiFscXcKXvthtQyQf3YEvRzOlREREPEmhlLRu9dXw+W/M41G/gC5DW/T2spp6bn97Ew1Og0uT47lmZIIbihQRERG3OdrsPHMF1Ne4ZYiUhAgA0jRTSkRExKMUSknrtvwJOLwPQuPh3P9r0VsNw2DOB1vIPVyNvVMgc68ajMVicVOhIiIi4hYxA8zngIZqyF7pliEGdQ3HYoH9pTUcKK91yxgiIiJyPIVS0nod2AXfP2UeX/xXCAhr0dvfXZfD52n5+FgtPDtjKGEBvq6vUURERNzLYvnBEj739JUK8fchKToE0GwpERERT1IoJa2TYcBn94CzHnpPhv4/adHb9xSW89Cn2wC4d3Jfhnbr5I4qRURExBOSzjM/uymUAkg+2uw8p8RtY4iIiEhTCqWkddr8FmR9Dz6BcMnj5m9Jm6mm3sFtb22ipt7JhN5R/GJCTzcWKiIiIm7X81zAAgd2QGmeW4ZISTCbnafmqtm5iIiIpyiUktan8iD89/fm8TkPQKfuLXr7nz7fzq7CcqJC/Hny6iFYreojJSIi0qYFdYauw8zjjG/cMsTRmVJpuSUYhuGWMURERKQphVLS+ix6EKoPQcxAGHtri9765ZZ83lydDcCTV6cQHervjgpFRETE0472lcpwzxK+/vGh+NosHK6qJ/dwtVvGEBERkaYUSknrkrkCNr9pHl/2D7A1vzl57uEq7l+YBsCvzu7FxD7R7qhQREREvCFpkvk541twOlx+e38fG/3izE1VUtXsXERExCMUSknr0VAHn91tHg+/EbqNbv5bHU7ufGczZTUNDEmI4DcX9nFPjSIiIuIdXYeDfzjUlEDeRrcMkWw3+0qlqa+UiIiIRyiUktZj5dNQvAuCo2HSQy1661OL97Ah6zCh/j48O2Movjb90RYREWlXbD7Q82zz2E1L+FK0A5+IiIhH6Sd3aR0O7YVlfzePJ/8FAjs1+60r04v559J0AOZOHUxC5yB3VCgiIiLelnSkr1S6m0KphAgAtuaV4nCq2bmIiIi7KZQS7zMM+Pw30FADPc+BwdOb/daDFbXc9e5mDAOuHZnAZcld3FeniIiIeNfRZud566H6sMtvnxQTQpCfjco6B3sPVLj8/iIiItKUQinxvq0Lze2dbf5w6ZNgsTTrbYZhcO/7qRSV15IUE8IfLx/o5kJFRETEqyISIKovGE7Y+53Lb2+zWhjUxewrlaq+UiIiIm6nUEq8q7oEvppjHk/4DUT2avZbv91VxLe7DuDvY+W564YS6GdzT40iIiLSejQu4VvsltsfbXauvlIiIiLup1BKvGvJI1BZBJG9YfxdLXrr/NXZANwwpnvjFs4iIiLSzh1dwpfxjdkCwMWSj/SVSsstcfm9RUREpCmFUuI9ueth/avm8WVPgo9/s9+aV1LNt7uKALhudDd3VCciIiKtUfdx5pL/sjw4sMvlt085MlNqR345dQ1Ol99fREREjlEoJd7haIBP7wIMSJkBPSa26O3vrs3GacDYnpH0jA5xS4kiIiLSCvkFmcEUQIbrd+Hr1jmIiCBf6hxOdhaUufz+IiIicoxCKfGONS9A4RYI7AQX/qlFb21wOHl3fQ6gWVIiIiIdUtIk87Mb+kpZLBYGd1WzcxEREU9QKCWeV5ID3/7FPL7gEQiOatHbl+wsorCslshgPyYPjHNDgSIiItKqHW12nrUS6qtdfvsUewQAaWp2LiIi4lYKpcTzvrwf6iuh21gYcn2L3z5/jdngfPqIBPx89EdYRESkw4nuB6FdoKEGsla4/PZHd+BL00wpERERt9JP9OJZOz+HXZ+D1Qcu+wdYW/ZHMOdQFcv3HABgxqgEd1QoIiIirZ3FAknnmcfp37j89kOO7MC3p6icytoGl99fRERETAqlxHNqK+CL35rH4+6AmP4tvsXba7MxDJjQO4rukcEuLlBERETajKN9pdzQ7DwmLIBunYNwGrB4R6HL7y8iIiImhVLiOUvnQlkuRHSHife1+O11DU7eW58LwEw1OBcREenYep4DFisc2AmluS6//ZShXQFYsMH19xYRERGTQinxjPw0WP28eXzpk+Z2zi20aHshxRW1RIf6c37/WBcXKCIiIm1KYCfoOtw8Tnf9bKnpw+0AfJ9eTF6J65upi4iIiEIp8QSnAz67CwwHDLwSek86rdu8tTYLgGtGJOBr0x9dERGRDq/XkV343LCEL6FzEGN6dsYw4APNlhIREXEL/WQv7rf+VcjbAP5hcNFjp3WLfcWVrEg/iMUC16rBuYiIiAAkHQml9i4Fh+sbkl89wnzmeH9DLk6n4fL7i4iIdHQKpcS9ygtgySPm8fkPQmjcad3m7bXZAJzTJxp7p5Yv/RMREZF2qMswCIiAmlLYv9Hlt794UDwh/j5kH6pibeYhl99fRESko1MoJe711RyoLTMfGkf89LRuUdvgaGwyet3o7q6sTkRERNoym4/Z8BwgfbHLbx/oZ+Oy5HgA3l+vJXwiIiKuplBK3Cd9MWz7wNwZ5/KnwGo7rdt8tbWAQ5V1xIcHcG7faNfWKCIiIm3b0SV8bmh2DjB9hNnw/Ist+VTUun6JoIiISEemUErco74aPv+NeTz6VxCfctq3emuNuXTvmpEJ+KjBuYiIiPzQ0Wbn+zdCleuX2A3r1ome0cFU1zv4Ii3f5fcXERHpyPQTvrjHssfhcCaEdYVzf3fat0kvKmfNvkNYLWYoJSIiItJEeFeI7geG02x47mIWi4Vpw83ZUu9vyHH5/UVERDoyhVLiekU7YcUz5vHFfwX/0NO+1VtrzIe/8/rFEh8e6IrqREREpL1JmmR+znDPEr6pw+xYLbAu8zD7iivdMoaIiEhHpFBKXMvphM/uBmc99LkY+l122reqqXewcKPZVHTmmG6uqlBERETam17nmZ/Tl4BhuPz2sWEBTOxj9rVcoNlSIiIiLqNQSlxr83zIXgm+QXDJ38BiOe1bfZ6WT2l1PV0jApnYWw3ORURE5CS6jwOfACjPh6Idbhni6hFmG4GFG/JwOF0ffImIiHRECqXEdSqLYdEfzONz5kDEmc1uemut2eB8xqgEbNbTD7dERESknfMNhO5nmcduWsJ3fv8YIoJ8KSirYfmeA24ZQ0REpKNRKCWu898/QPVhiB0EY245o1vtLChjQ9ZhfKyWxt9MioiIiJxU0pFd+NLdE0r5+9iYMqQrAO9vyHXLGCIiIh2NQilxjX3LIfUtwAKXPQU23zO63VtrzFlSFwyIJSYs4MzrExERkfbtaLPzrJVQV+WWIY7uwrdoWyElVXVuGUNERKQjUSglZ66h1mxuDjDiJkgYeUa3q6pr4MONeQBcN1oNzkVERKQZovpAmB0ctZC1wi1DDOoaTv/4MOocTj5J3e+WMURERDoShVJy5lY8DQf3QHAMnP/HM77dZ6n5lNc20D0yiLN6RbmgQBEREe96/vnnSU5OJiwsjLCwMMaOHcuXX3550uvnzZuHxWJp8hEQoJnDp2SxQNIPduFzk+lHZku9v15L+ERERM6UQik5MwczYNnfzeOL5kJgxBnfcn5jg/NuWNXgXERE2gG73c5jjz3Ghg0bWL9+Peeddx5XXHEF27ZtO+l7wsLCyM/Pb/zIysryYMVtVK8jfaXc1OwcYMrQrvjaLGzJK2VnQZnbxhEREekIFErJ6TMM+Pw35jT5nufCoKlnfMuteaWk5pTga7M09m0QERFp6y6//HIuueQSevfuTZ8+ffjzn/9MSEgIq1evPul7LBYLcXFxjR+xsbEerLiN6nkOWGxQvBtKst0yROdgP87vZ/670GwpERGRM6NQSk7f1oWw91uw+cOlT5jT5s/QW0dmSU0eGEdUiP8Z309ERKS1cTgcvPPOO1RWVjJ27NiTXldRUUH37t1JSEj40VlVckRgBNhHmMfuXMI3wvzF2Yeb8qhrcLptHBERkfZOoZScnuoS+GqOeTzxPojsdca3rKht4ONNZoPzmaO7n/H9REREWpMtW7YQEhKCv78/v/rVr/jwww8ZMGDACa/t27cvr776Kh9//DFvvvkmTqeTcePGkZt78pk5tbW1lJWVNfnokDywhO/sPtFEh/pzqLKOb3YWuW0cERGR9k6hlJyeJQ9DZZG5081Zd7jklh9vzqOyzkHP6GDG9OzsknuKiIi0Fn379mXz5s2sWbOGW265hdmzZ7N9+/YTXjt27FhmzZrFkCFDOPvss/nggw+Ijo7mxRdfPOn9586dS3h4eONHQkKCu76V1i3pSCi1dxk4GtwyhI/NylXDugKwYEOOW8YQERHpCBRKScvlrIP1r5nHl/0DfM58mZ1hGLy1xly6d92oblhcsBRQRESkNfHz8yMpKYnhw4czd+5cUlJSePrpp5v1Xl9fX4YOHUp6evpJr5kzZw6lpaWNHzk5HTQs6TIUAjtBbSnkrXfbMNOHm6Hft7sOUFRe47ZxRERE2jOFUtIyjnr47C7AgCEzIXG8S26bllvKtv1l+PlYmTpMDc5FRKT9czqd1NbWNutah8PBli1biI+PP+k1/v7+hIWFNfnokKw2cwMWcGtfqaSYEIZ2i8DhNPjoSPsBERERaRmFUtIyq5+Hwq0Q2BkueNRltz06S+rSwfF0CvZz2X1FRERagzlz5rBs2TIyMzPZsmULc+bMYenSpcycOROAWbNmMWfOnMbrH3nkEf773/+yd+9eNm7cyPXXX09WVhY///nPvfUttC1Hl/ClL3brMEdnS72/PhfDMNw6loiISHvk4+0CpA0pyYalc83jCx+F4EiX3Laspp5PUvcDcN3obi65p4iISGtSVFTErFmzyM/PJzw8nOTkZL7++msuuOACALKzs7Faj/2u8PDhw9x8880UFBTQqVMnhg8fzsqVK0/aGF3+R6/zzM/7N0HlQZc9s/yvy1LieeSzbewpqiA1t5QhCRFuGUdERKS9UiglzWMY8MVvob4Kup9lLt1zkY825VFd76B3TAgjundy2X1FRERai1deeeWUry9durTJ1//4xz/4xz/+4caK2rmwLhAzAIq2w95vYfA09wwT4MtFA+P4aPN+3lufo1BKRESkhbR8T5pn52ew+0uw+prNzV3UiPyHDc5njlaDcxEREXGRo7OlMr5x6zDTR5hL+D5N3U9NvcOtY4mIiLQ3CqXkx9WWm7OkAM66E6L7uuzWG7MPs7OgnABfK1eqwbmIiIi4StIk83P6EnPGt5uM7RlJ14hAymsa+HpbgdvGERERaY+0fE9+3Ld/gfL90KkHTLzXpbeef2SW1GXJXQgP9HXpvUVE3MnhcFBfX+/tMsQFfH19sdls3i5DXK3bWPAJhIoCKNwGcYPcMozVamHacDtPL9nD++tzuWJIV7eMIyLSHuj5qf1w1fOTQik5tf2bYc0L5vGlT4BvoMtuXVJVx+dp+YC5dE9EpC0wDIOCggJKSkq8XYq4UEREBHFxcVpG3p74BkDieEhfBBlL3BZKAY2h1IqMYvJKquka4brnJRGR9kDPT+2TK56fFErJyTkd8NldYDhh0NRj2yu7yMKNedQ2OOkfH6bGoCLSZhx9oIqJiSEoKEghRhtnGAZVVVUUFRUBEB8f7+WKxKWSzjdDqfQlZgsCN0noHMTYnpGs2nuQhRtyueP83m4bS0SkLdLzU/viyucnhVJycuteMbdS9g+HyXNdemuzwXkWANepwbmItBEOh6PxgSoy0j1bzIvnBQaas1qKioqIiYnRUr72pNeRX6hlr4K6SvALdttQ00fYWbX3IAs25HLbuUlYrXq2EREBPT+1V656flKjczmxsnxY8oh5POlBCI116e3X7jtExoFKgvxsTBnSxaX3FhFxl6M9EIKCgrxcibja0X+n6nPRzkT1hvBu4KiDzO/dOtTFg+IJ8fch+1AVazMPuXUsEZG2RM9P7Zcrnp8USsmJffUA1JVD1xEw/Kcuv/1ba80G51cM6UJogBqci0jbotmd7Y/+nbZTFgsknWcepy9x61CBfjYuSzaXL7y3PsetY4mItEX6u7b9ccW/U4VScrw9i2D7R2CxweVPgdW1f0wOVdbx5RZzy+TrRnV36b1FREREmji6hC/DvaEUmEv4AL7cUkBFbYPbxxMREWnrFEpJU3VV8Pk95vGYWyBusMuHWLAhhzqHk8FdwxlsD3f5/UVExL0SExN56qmnmn390qVLsVgs2nFHvKPn2eYv2g6mw+Estw41rFsnekYHU13v4PO0/W4dS0RE2hY9P52YQilpatnfoCQbwuxwzhyX397pNHh7rTmlfebobi6/v4iInNg555zDXXfd5ZJ7rVu3jl/84hfNvn7cuHHk5+cTHq5fRIgXBISDfaR57ObZUhaLhenDEwB4f32uW8cSERH30/OT+ymUkmMKt8PKZ83jS/4G/iEuH2LV3oPsK64kxN+Hy1PU4FxEpLUwDIOGhuYtN4qOjm5Rs1I/Pz/i4uLUS0K8J2mS+dnNfaUArhrWFasF1mcdZu+BCrePJyIi3qPnpzOnUEpMTqe5bM/ZAH0vhX6XumWYt9aYDc6nDO1CsL+PW8YQEZGmbrzxRr777juefvppLBYLFouFefPmYbFY+PLLLxk+fDj+/v58//33ZGRkcMUVVxAbG0tISAgjR45k8eLFTe73v9PPLRYL//73v7nyyisJCgqid+/efPLJJ42v/+/083nz5hEREcHXX39N//79CQkJ4aKLLiI/P7/xPQ0NDdxxxx1EREQQGRnJ/fffz+zZs5kyZYo7/1FJe3W02fne78Dh3h0WY8MCOLtPNAALNmi2lIhIW6XnJ89QKCWmzW9C9irwDTZnSbnBgfJavt6mBuci0n4YhkFVXYNXPgzDaHadTz/9NGPHjuXmm28mPz+f/Px8EhLMJUYPPPAAjz32GDt27CA5OZmKigouueQSlixZwqZNm7jooou4/PLLyc7OPuUYDz/8MFdffTVpaWlccsklzJw5k0OHDp30+qqqKv7+97/zxhtvsGzZMrKzs7n33nsbX//rX//K/Pnzee2111ixYgVlZWV89NFHzf6eRZqIHwKBnc2dhXPXuX246SPM/74+2JiHw9n8/1ZFRDqKtvAMpecnz9BUFYHKYlj0oHl87u8g3O6WYd7fkEOD02BotwgGdAlzyxgiIp5UXe9gwINfe2Xs7Y9MJsiveX+Nh4eH4+fnR1BQEHFxcQDs3LkTgEceeYQLLrig8drOnTuTkpLS+PWjjz7Khx9+yCeffMJtt9120jFuvPFGZsyYAcBf/vIXnnnmGdauXctFF110wuvr6+t54YUX6NWrFwC33XYbjzzySOPrzz77LHPmzOHKK68E4LnnnuOLL75o1vcrchyrDXqdC1sXmkv4uo9z63Dn948hIsiXgrIalu85wDl9Y9w6nohIW9MWnqH0/OQZmikl8N/fQ/Vhc6e90b9yyxBmg3MzJb5ulBqci4i0FiNGjGjydUVFBffeey/9+/cnIiKCkJAQduzY8aO/6UtOTm48Dg4OJiwsjKKiopNeHxQU1PhABRAfH994fWlpKYWFhYwaNarxdZvNxvDhw1v0vYk0cbSvlJubnQP4+9iYMqQroIbnIiLtkZ6fXEczpTq6fcsg9W3AApc9DTb3/JFYnl5MzqFqQgN8uCxZDc5FpH0I9LWx/ZHJXhvbFYKDg5t8fe+997Jo0SL+/ve/k5SURGBgINOmTaOuru6U9/H19W3ytcViwel0tuj6lixJFGmxXkf6Su3fbM4SD45y63DThtuZtzKTRdsLKamqIyLIz63jiYi0JW39GUrPT66jUKoja6iFz+42j0f+DOzuS1DfWpMFwNRhdgL9XPODlIiIt1kslmYvofM2Pz8/HA7Hj163YsUKbrzxxsZp3xUVFWRmZrq5uqbCw8OJjY1l3bp1TJw4EQCHw8HGjRsZMmSIR2uRdiQ0DmIHQeFWyPgWkqe7dbhBXcMZEB/G9vwyPt68n9njEt06nohIW9JWnqH0/OR+Wr7XkX3/FBxMh5BYOP9Btw1TWFbD4h3mlMKZo7V0T0TEGxITE1mzZg2ZmZkUFxef9LdwvXv35oMPPmDz5s2kpqZy3XXXnfI3du5y++23M3fuXD7++GN27drFnXfeyeHDh9v9tsjiZkdnS3lgCR/A9BFmn873N+R4ZDwREXEtPT+5n0KpjupgBix/wjy+aC4EhLttqHfX5eBwGoxM7ETv2FC3jSMiIid37733YrPZGDBgANHR0SftcfDkk0/SqVMnxo0bx+WXX87kyZMZNmyYh6uF+++/nxkzZjBr1izGjh1LSEgIkydPJiAgwOO1SDuSdL75OX0JeOCHhSuGdMXXZmFrXhk78svcPp6IiLiWnp/cz2K0gQWIZWVlhIeHU1paSliYdm07Y4YB/7kC9n0Hvc6H6xeCm5JTh9Ngwl+/YX9pDU9dM4QpQ7u6ZRwREU+oqalh37599OjRo1X/5d4eOZ1O+vfvz9VXX82jjz7q8vuf6t9tW30Oaat1u1VDLfw1Eeqr4JfLIT75R99ypm55cwNfbi3gp2f14MHLB7h9PBGR1kbPT97TFp6fNFOqI9ryvhlI+QTApU+4LZACWLqriP2lNXQK8uWiQXFuG0dERNqXrKwsXn75ZXbv3s2WLVu45ZZb2LdvH9ddd523S5O2zMcfEieYxx5ewvfR5jzqGjy/lENERDqOtvj8pFCqo6k+DF//zjyeeB907uHW4d5aY05vnDrMToCLdooSEZH2z2q1Mm/ePEaOHMlZZ53Fli1bWLx4Mf379/d2adLW/XAJnwdM7B1NTKg/hyrr+Gbnybf5FhEROVNt8fmp9be7F9da/BBUHoDofjDuDrcOtb+kmm93mQ9fM9TgXEREWiAhIYEVK1Z4uwxpj3odCaWyV0NtBfiHuHU4H5uVK4d15cXv9vL++hzNHBcREbdpi89PminVkWSvgQ3zzOPL/gE+fm4d7p11OTgNGNszkl7R7n3gExEREWmWyF4Q0Q2c9ZD5vUeGnD48AYCluw9QVF7jkTFFRETaAoVSHYWjHj67yzweej10H+fW4RocTt5dZy7du06zpERERKS1sFggaZJ5nL7YI0MmxYQwrFsEDqfBhxvzPDKmiIhIW6BQqqNY9U8o2g5BkXCB67vu/68lO4soLKslMtiPyQM1TV1ERERakaNL+DzU7Bxg+ghzttT7G3JpA5tfi4iIeIRCqY7gcBYsfcw8vvBPENTZ7UMebXA+fUQCfj76YyYiIiKtSI+JYPWBQ3vh0D6PDHlZcjwBvlbSiyrYnFPikTFFRERaO6UF7Z1hwBf3QUO1uQVyygy3D5lzqIplew4AMGNUgtvHExEREWmRgDCwjzKPPTRbKjTAl4sHxQPmbCkRERFRKNX+7f0W9nwNVl+49Emzj4Kbvb02G8OACb2j6B4Z7PbxRERERFos6Tzzc/o3Hhty+nA7AJ9u3k91ncNj44qIiLRWCqXau20fmp+HzYLoPm4frt7h5L315m//rhulBuciIu1FYmIiTz31VOPXFouFjz766KTXZ2ZmYrFY2Lx58xmN66r7iBznaLPzfd9BQ51HhhzTMxJ7p0DKaxv4eluBR8YUERHv0fPTj1Mo1Z45nbD7v+Zx/8s8MuSi7YUUV9QSHerPpAGxHhlTREQ8Lz8/n4svvtil97zxxhuZMmVKk3MJCQnk5+czaNAgl44lQlwKBEVBXQXkrvXIkFarhanDzNlS72/I8ciYIiLSeuj56XgKpdqzglSoKAC/EOh+lkeGnL8mC4BrRiTga9MfLxGR9iouLg5/f3+3j2Oz2YiLi8PHx8ftY0kHY7VCr3PN43TP7cI37cgSvpUZB8k9XOWxcUVExPv0/HQ8pQbt2a6vzM+9zgMf9//BzyyuZEX6QSwWuFYNzkVEWo2XXnqJLl264HQ6m5y/4oor+OlPf0pGRgZXXHEFsbGxhISEMHLkSBYvXnzKe/7v9PO1a9cydOhQAgICGDFiBJs2bWpyvcPh4Gc/+xk9evQgMDCQvn378vTTTze+/tBDD/H666/z8ccfY7FYsFgsLF269ITTz7/77jtGjRqFv78/8fHxPPDAA//f3n3HR1Wlfxz/zEw66aQXCDX0QALSBaWJZXWVouLa3V1FV8Wyomv/KXZdxbWX3VUs2BtdQSlSEnoLPQVSKOmkzvz+uEkgKyAhUzLJ9/163dfc3LlzzjMZlMMz5zyH6urq+udHjhzJ3/72N+69915CQ0OJiorikUceafwvTlq+TqOMRycVOweID/VjSKe22GzweWq20/oVEZHG0fjJOeMnJaVasvTapFTX85zS3UerMgAY2TWcuBA/p/QpIuJSNhtUlrrmsNlOO8yJEydy6NAhfvrpp/prhw8fZu7cuUyZMoWSkhLOP/98Fi1axNq1aznvvPO46KKLyMjIOK32S0pKuPDCC+nRowepqak88sgj3H333Q3usVqtxMXFMXv2bLZs2cJDDz3E/fffz6effgrA3XffzaRJkzjvvPM4cOAABw4cYMiQIb/pKzs7m/PPP58BAwawfv16XnvtNd555x3+7//+r8F9//73v2nTpg0rV67kmWee4bHHHmPBggWn/TuTVqJTbbHzA+uhJM9p3U7sb8yW+iwtE6v19P9bFhFpMdxgDKXxk3PGT81/LpecmaIDcGAdYIIuYx3eXUV1Tf32xlcObO/w/kREmoWqMngyxjV9378fvE5vh9OQkBDGjx/PrFmzGDXKmBny2WefERYWxjnnnIPZbCYpKan+/scff5wvv/ySb775hltvvfV32581axZWq5V33nkHHx8fevbsSVZWFjfffHP9PZ6enjz66KP1P3fo0IEVK1bw6aefMmnSJPz9/fH19aWiooKoqKiT9vWvf/2L+Ph4Zs6ciclkolu3buzfv5+///3vPPTQQ5jNxvdtffr04eGHHwagS5cuzJw5k0WLFjFmzJjT+p1JKxEQCVG9IWcj7PoJkiY7pdvzekbzkPdmMg8fZeWewwzu1NYp/YqINBtuMIbS+Mk54yfNlGqpdswzHuP6g3+4w7ubuymHw6WVRAX6cE6i4/sTEZHGmTJlCp9//jkVFRUAfPjhh1x++eWYzWZKSkq4++676d69O8HBwfj7+7N169bT/qZv69at9OnTBx8fn/prgwcP/s19r776KikpKYSHh+Pv78+bb7552n0c39fgwYMxmUz114YOHUpJSQlZWVn11/r06dPgddHR0eTlOW8mjLgRFyzh8/WycGFSNKCC5yIizZnGT44fP2mmVEu13blL92atNP6jmDwgHg8VOBeR1sLTz/i2zVV9N8JFF12EzWbj+++/Z8CAAfzyyy+8+OKLgDH1e8GCBTz33HN07twZX19fJkyYQGVlpd3C/fjjj7n77rt5/vnnGTx4MAEBATz77LOsXLnSbn0cz9PTs8HPJpPpNzUhRADoPAqWvQS7fjR2LjY7ZxwzISWej1ZlMmdjDo/+oYoAH8/ff5GISEvhJmMojZ8cP35SUqolqjoKuxcb505ISu3MK2blnsOYVeBcRFobk+m0l9C5mo+PD5deeikffvghO3fuJDExkeTkZACWLVvGtddeyx//+EfAqHGwd+/e0267e/fu/Pe//6W8vLz+275ff/21wT3Lli1jyJAh3HLLLfXXdu3a1eAeLy8vampqfrevzz//HJvNVv9t37JlywgICCAuLu60YxapFz8IPNtAaT7kboTopN9/jR0ktwumY3gbdueX8v2GA1x+Vjun9Csi0iy4yRhK4yfH05SWlmjPz1B9FILiIbKnw7ubtdKYdn5ut0iig3wd3p+IiJyZKVOm8P333/Puu+8yZcqU+utdunThiy++YN26daxfv54rr7yyUd+KXXnllZhMJm666Sa2bNnCDz/8wHPPPdfgni5durBmzRrmzZtHeno6Dz74IKtXr25wT0JCAhs2bGD79u0cPHiQqqqq3/R1yy23kJmZyW233ca2bdv4+uuvefjhh5k2bVp9PQSRRvHwgg5nG+c7T71rkj2ZTCYmphhf5tXV5RQRkeZH4yfH0uitJarfdW+ckYF2oPKqGj5PMwZSUwbqGz4Rkebs3HPPJTQ0lO3bt3PllVfWX3/hhRcICQlhyJAhXHTRRYwbN67+W8DT4e/vz7fffsvGjRvp168fDzzwAE8//XSDe/7yl79w6aWXMnnyZAYOHMihQ4cafOsHcNNNN5GYmEj//v0JDw9n2bJlv+krNjaWH374gVWrVpGUlMRf//pXbrjhBv7xj3808rchcpzOtXWldv7o1G4vTY7FbILUfUfYlV/i1L5FROT0aPzkWCabrRF7SrtIUVERQUFBFBYWEhgY6OpwmjebDV7sCUXZMOUz6OLYXYa+SMti2qfriQ325ed7z8FidmwSTETElcrLy9mzZw8dOnRoUJRS3N+pPlt3HYe4a9wucWgXvJIMZg/4+17wDnBa19e/v5oft+Vx88hO/P28bk7rV0TEWTR+arnsMX7STKmWJmejkZDy9IOE4Q7v7sPaAudXnBWvhJSIiIi4p7adICQBrNWw5xendj0xxajl8UVaFjXWZv9dsYiIiF0pKdXSpM8zHjueA56OzUJvzykmdd8RPMwmJvVXgXMRERFxY51ql/DtWuTUbkd1jyTEz5Pcogp+3pHv1L5FRERcTUmpliZ9jvGY6Phd92at3AfAmB6RRARqGqaIiIi4sc6jjUcnFjsH8PIwc3HfWAA+W6OC5yIi0rooKdWSlORBdqpx3mWsQ7sqq6zmi7RsAK5UgXMRERFxdx2GGzWljuw1akw50cT+xhK+BVtyOVJa6dS+RUREXElJqZakbuleTDIERDm0q+/WH6C4opp2oX4M7RTm0L5EREREHM47AOIHGee7nLsLX8+YIHpEB1JZY+XrddlO7VtERMSVlJRqSdLnGo9dHb9078NVdQXO22FWgXMRaWXcYONaaSR9pgJA53ONx53OrSsFx2ZLzU7VEj4RaZn0d23LY4/PVEmplqKqHHb9ZJx3HefQrjZlF7I+swBPi6l+ACUi0hp4enoCUFZW5uJIxN7qPtO6z1haqbpi53t+hmrnLqO7uG8snhYTm/cXsWV/kVP7FhFxJI2fWi57jJ88zuRFr776Ks8++yw5OTkkJSXxyiuvcNZZZ53w3i+++IInn3ySnTt3UlVVRZcuXbjrrrv405/+dMZBywnsWwpVpRAQDdFJDu1qVu0sqXE9owjz93ZoXyIizYnFYiE4OJi8vDwA/Pz8MJk0W9Sd2Ww2ysrKyMvLIzg4GIvF4uqQxJWi+kCbcCjNh8xfocPZTus6tI0XY3pE8sPGHGanZvJwTE+n9S0i4kgaP7U89hw/NTop9cknnzBt2jRef/11Bg4cyEsvvcS4cePYvn07ERERv7k/NDSUBx54gG7duuHl5cV3333HddddR0REBOPGOXZGT6tSV0+q6zhw4H/gJRXVfL1WBc5FpPWKijJq9tUNrKRlCA4Orv9spRUzm6HTubDhE2MJnxOTUgATU+L5YWMOX6/bz/Tx3fHy0KIGEWkZNH5qmewxfmp0UuqFF17gpptu4rrrrgPg9ddf5/vvv+fdd9/lvvvu+839I0eObPDz7bffzr///W+WLl2qpJS92Gywva6e1HiHdvXNuv2UVtbQMawNgzu2dWhfIiLNkclkIjo6moiICKqqqlwdjtiBp6enZkjJMZ1GGUmpXYtgzKNO7Xp4lzAiArzJK67gx225nNcr2qn9i4g4isZPLY+9xk+NSkpVVlaSmprK9OnT66+ZzWZGjx7NihUrfvf1NpuNH3/8ke3bt/P00083Plo5sbytUJgBHj4O/UbPZrPx4cp9gDFLSlMuRaQ1s1gsSmSItESdaoud52yE4lwIiHRa1x4WM5cmx/H6kl3MXpOlpJSItDgaP8n/atSc4IMHD1JTU0NkZMO/nCMjI8nJyTnp6woLC/H398fLy4sLLriAV155hTFjxpz0/oqKCoqKihoccgrpc4zHjiPBy89h3WzIKmTz/iK8PMxclqwC5yIiItIC+Ycfq8+560end1+3iczi9Hzyisqd3r+IiIgzOWWhekBAAOvWrWP16tU88cQTTJs2jcWLF5/0/hkzZhAUFFR/xMfHOyNM93V8PSkHmrXSKHB+fq8oQtp4ObQvEREREZep24Vv1yLndx3uT3K7YGqsNr6oreMpIiLSUjUqKRUWFobFYiE3N7fB9dzc3FMWtzKbzXTu3Jm+ffty1113MWHCBGbMmHHS+6dPn05hYWH9kZmZ2ZgwW5fSg5C5yjjv4rikVFF5Fd+s3w/AlEHtHdaPiIiIiMt1rktK/QhWq9O7n9jf+EJ29ppMbDab0/sXERFxlkYlpby8vEhJSWHRomPfGlmtVhYtWsTgwYNPux2r1UpFRcVJn/f29iYwMLDBISexYwFgM7YwDop1WDdfrc3maFUNXSL86d8+xGH9iIiIiLhc3FngHQhlh2DzF07v/sI+0fh4mtmVX8razAKn9y8iIuIsjV6+N23aNN566y3+/e9/s3XrVm6++WZKS0vrd+O7+uqrGxRCnzFjBgsWLGD37t1s3bqV559/nv/+979cddVV9nsXrVl63a575zmsC5vNVr90TwXORUREpMXz8ILBU43zBQ9BZalTuw/w8eT82iLns9dkObVvERERZ2rU7nsAkydPJj8/n4ceeoicnBz69u3L3Llz64ufZ2RkYDYfy3WVlpZyyy23kJWVha+vL926deODDz5g8uTJ9nsXrVV1JeysnbWW6LikVFpGAdtyivHxNHNpPxU4FxERkVZg6O2w9kNjh+OlL8K5/3Bq9xP6x/HF2my+W7+fhy7sga+XdqsSEZGWx2Rzg4XqRUVFBAUFUVhYqKV8x9u9GP5zMfhHwrRtYHZM3fppn67ji7RsJqTE8dzEJIf0ISIi0ly56zjEXeNuVrZ8A5/+CSzeMHUlhHZwWtdWq42zn/2JrCNHeWlyXy7p57gyDSIiIvZ2uuMQp+y+Jw6yvXbpXpexDktIFZZV8f2GA4CxdE9ERESk1eh+EXQYATUVMO8Bp3ZtNpuYkGLMUJ+dqk1/RESkZVJSyl3ZbJA+xzh3YD2pz9OyqKi20i0qgH7xwQ7rR0RERKTZMZlg/NNgssD272HnQqd2f1mykZRatvMQmYfLnNq3iIiIMygp5a4OpsORvcZ08o4jHdKFzWbjw5X7AJgyqL0KnIuIiEjrE9EdBv7FOJ9zn1HT00niQ/0Y0qktYHxRKCIi0tIoKeWu6nbd6zAcvP0d0sWqPYfZlV+Kn5eFS/rGOKQPERERkWZvxN/BLwwO7YBVbzi164n9jdlSn6VmYbU2+1KwIiIijaKklLuqqyflwKV7s1ZlAPCHpBgCfDwd1o+IiIhIs+YbDKMfNs4XPw3FuU7r+rye0QR4e5B15Ci/7jnktH5FREScQUkpd1R2GDJ/Nc67jnNIF4dLK5mzMQeAKQPbO6QPEREREbfR9yqI6QeVxbDoUad16+tl4cIkY8b6Z2u0hE9ERFoWJaXc0c5FYLNCRE8IdsyOeJ+lZlJZY6V3bBC944Ic0oeIiIiI2zCbYfyzxvm6DyFztdO6rlvC98OmAxSXVzmtXxEREUdTUsod1e26l+iYpXs2m42PVhlbD1850DFJLxERERG3Ez8Akq40zufcA1arU7rtFx9Mp/A2lFdZ+X7DAaf0KSIi4gxKSrmbmqpj2xE7qJ7Uil2H2HOwFH9vD/6QpALnIiIiIvVGPwJeAbB/rTFjyglMJhMT+8cDMDtVS/hERKTlUFLK3WT8CuWFxg4wsSkO6eLDlUaB80v6xdDG28MhfYiIiIi4pYBIGPl343zhI3C0wCndXtovFovZROq+I+zMK3FKnyIiIo6mpJS7Sa/dda/LWDBb7N58fnEF8zYbBc6vPEsFzkVERER+46y/QNsuUHYQljztlC4jAn0Y0TUcgM80W0pERFoIJaXcTV1SykG77s1OzaTaaqNvfDA9YgId0oeIiIiIW/PwgvG1yaiVb0DeNqd0OzHFKHj+RVoW1TXOqWclIiLiSEpKuZODO+HQTjB7Qqdz7d681Wrjo1XG0r0pKnAuIiIicnKdR0HiBWCrgTn3gs3m8C5HdY8kxM+TvOIKftlx0OH9iYiIOJqSUu6kbpZUwlDwsf8spl92HiTz8FECfDy4sI8KnIuIiIic0rgnwOINe5bA1m8d3p2Xh5mL+8YCxux2ERERd6eklDupX7o33iHNz1q5D4DLkuPw9bJ/vSoRERGRFiW0Awy5zTif9wBUHXV4l5Nqd+FbuCWPI6WVDu9PRETEkZSUchdHCyBjhXHugHpSuUXlLNyaB8CVWronIiIicnqGT4PAWCjMgGUvO7y7HjGB9IwJpLLGytfrsh3en4iIiCMpKeUudi0CazWEdzO+lbOzT1ZnUmO1MSAhhK6RAXZvX0RERKRF8moDYx83zpe+AAUZDu+yruD5bO3CJyIibk5JKXeRPs94dMAsqRqrjY9rC5xrlpSIiIhII/W8FNoPg+pymP8Ph3d3cd9YvCxmNu8vYvP+Qof3JyIi4ihKSrmDmmrYMd8473qe3Ztfkp7H/sJygv08Gd8r2u7ti4iIiLRoJhOMfxpMZtjyNexe4tDuQtp4MbpHBACz12i2lIiIuC8lpdxB1mo4egR8QyDuLLs3/+GvxiypCclx+HiqwLmIiIhIo0X1gv43GOdz/m58qehAE1OMgudfr8umstrq0L5EREQcRUkpd5A+x3jsPAYsHnZten/BUX7abhQ4v0JL90RERETO3Dn3g28o5G+F1W87tKvhXcKICPDmSFkVi7bmOrQvERERR1FSyh3U1ZNKtP/SvY9XZ2K1waCOoXQK97d7+yIiIiKthl8ojHrQOP/pSSg96LCuPCxmLk1WwXMREXFvSko1d4f3QP42MHtAp1F2bbq6xsonq42le1MGtrdr2yIiIiKtUvI1ENUbKgph0WMO7WpifyMptXh7HnlF5Q7tS0RExBGUlGru6mZJtRsMvsF2bXrRtjxyiypo28aLcT2j7Nq2iIiISKtktsD4Z43ztP/A/rUO66pTuD8p7UOw2uCLtdkO60dERMRRlJRq7tLnGo8O2HVv1sraAuf94/Dy0B8FEREREbtoPxh6TwRs8MO9YHVcIfKJKcZsqU/XZGKz2RzWj4iIiCMoE9GclRfB3qXGuZ2TUpmHy/h5Rz4AVwxQgXMRERERuxrzGHi2gaxVsPFTh3VzQZ9ofDzN7M4vJS2jwGH9iIiIOIKSUs3Z7p/AWgVtO0NYZ7s2/dGqDGw2Y+eWhLA2dm1bREREpNULjIGz7zbOFzwEFcUO6SbAx5Pze0UD8FlqpkP6EBERcRQlpZqz7Y5ZuldVY+XTNcYuLVeepVlSIiIiIg4xeCqEdoSSXFjyjMO6mVBb8Pzb9Qc4WlnjsH5ERETsTUmp5spaAzvmG+d2Tkot2JLLwZIKwgO8Gd0j0q5ti4iIyG+99tpr9OnTh8DAQAIDAxk8eDBz5sw55Wtmz55Nt27d8PHxoXfv3vzwww9OilbsxsMbznvKOP/1NTi4wyHdDOrQlrgQX0oqqpm7+YBD+hAREXEEJaWaq+xUKDsI3kHQbpBdm/5w5T4AJvePx9OiPwIiIiKOFhcXx1NPPUVqaipr1qzh3HPP5eKLL2bz5s0nvH/58uVcccUV3HDDDaxdu5ZLLrmESy65hE2bNjk5cmmyruOgy1ijJMPc+8ABxcjNZhMTaguez66dDS8iIuIOlJForup23esyGiyedmt278FSlu08hMkEl58Vb7d2RURE5OQuuugizj//fLp06ULXrl154okn8Pf359dffz3h/f/85z8577zzuOeee+jevTuPP/44ycnJzJw508mRi12MmwFmT9i5ENLnOaSLCSlxmEywfNchMg+XOaQPERERe1NSqrmqG7DYeeneR6syABjRNZy4ED+7ti0iIiK/r6amho8//pjS0lIGDx58wntWrFjB6NGjG1wbN24cK1ascEaIYm9hnY36UmDMlqoqt3sXcSF+DOnUFoDP0zRbSkRE3IOSUs1RQQbkbgKTGTqP/v37T1NFdQ2zU41BypSB7e3WroiIiPy+jRs34u/vj7e3N3/961/58ssv6dGjxwnvzcnJITKyYd3HyMhIcnJyTtp+RUUFRUVFDQ5pRs6+G/yj4Mge+PVVh3QxMcWYBT97TRZWq/2XCYqIiNibklLNUd0sqfhB4Bdqt2bnbsrhcGklUYE+nJMYbrd2RURE5PclJiaybt06Vq5cyc0338w111zDli1b7Nb+jBkzCAoKqj/i47VMv1nxDoAxjxnnPz8Hhdl272JczygCvD3ILjjKr7sP2b19ERERe1NSqjmqqyfVdZxdm5210li6N3lAPB4qcC4iIuJUXl5edO7cmZSUFGbMmEFSUhL//Oc/T3hvVFQUubm5Da7l5uYSFRV10vanT59OYWFh/ZGZmWnX+MUO+kyC+IFQVQYLHrJ7875eFi5MigGonx0vIiLSnCkz0dxUlMCen43zxPF2a3ZnXgkr9xzGrALnIiIizYLVaqWiouKEzw0ePJhFixY1uLZgwYKT1qAC8Pb2JjAwsMEhzYzJBOOfAUyw6TPYt9zuXUzsb+zCN2fTAYrKq+zevoiIiD0pKdXc7F4MNZUQkgBhXe3WbN0sqXO7RRId5Gu3dkVEROT3TZ8+nZ9//pm9e/eyceNGpk+fzuLFi5kyZQoAV199NdOnT6+///bbb2fu3Lk8//zzbNu2jUceeYQ1a9Zw6623uuotiL3E9IWUa4zzH+4Fa41dm+8XH0yn8DaUV1n5fsMBu7YtIiJib0pKNTf1S/fGG9+m2UF5VU39LixTBrazS5siIiJy+vLy8rj66qtJTExk1KhRrF69mnnz5jFmzBgAMjIyOHDgWAJhyJAhzJo1izfffJOkpCQ+++wzvvrqK3r16uWqtyD2dO6D4BMEuRsh9X27Nm0ymZjYv67guZZwiohI8+bh6gDkOFbrsSLndqwn9cPGAxQerSI22Jezu6rAuYiIiLO98847p3x+8eLFv7k2ceJEJk6c6KCIxKXahME5/4A598CPj0PPP9p1c5tL+8Xy7LztpGUUsDOvhM4R/nZrW0RExJ40U6o5ObAWSvPAKwDaD7Vbs3VL9644Kx6L2T6zr0RERESkCfpfDxE94OgR+OkJuzYdEejDyNovIj9TwXMREWnGlJRqTupmSXU+Fzy87NLk9pxi1uw7gofZxKT+KnAuIiIi0ixYPGqLngNr3oWcjXZtvq7g+edpWVTXWO3atoiIiL0oKdWcbJ9jPHY9z25NLtpmbCc9oms4EYE+dmtXRERERJqow3Bj6Z7NahQ9t9ns1vS53SIJbeNFfnEFP+/It1u7IiIi9qSkVHNRtB9yNgAm6DLWbs2m7SsAYHCntnZrU0RERETsZMzj4OELGcth0+d2a9bLw8zFfWMAmL1GS/hERKR5UlKquajbdS9ugFH80g5sNhtpGUcA6NcuxC5tioiIiIgdBcfD8GnG+fwHobLUbk1PTDFKNyzcmsvh0kq7tSsiImIvSko1F3X1pBLtt3Rv36EyDpdW4mUx0ys20G7tioiIiIgdDfkbBLeH4v3wywt2a7ZHTCA9YwKpqrHx9bpsu7UrIiJiL0pKNQeVZbB7sXFux3pSqfuMWVK9YgPx9rDYrV0RERERsSNPHxj3pHG+/GU4vNtuTU9MMQqeawmfiIg0R0pKNQd7fobqcghqZ2wNbCd1S/dS2mvpnoiIiEiz1u0C6HgO1FTCvAfs1uzFfWPxspjZcqCIzfsL7dauiIiIPSgp1RzU1ZPqOg5MJrs1WzdTKln1pERERESaN5MJxj8NZg/Y/gPsWGiXZkPaeDGmRySg2VIiItL8KCnlajbbsXpSdly6V1xeRXpuMQDJmiklIiIi0vyFJ8LAvxrnc++DavsUJ5/Q31jC99W6bCqqa+zSpoiIiD0oKeVqORuMopaebSBhmN2aXZ9ZiNUGscG+RAb62K1dEREREXGgEfdCm3A4tANWvm6XJs/uEk5koDcFZVUs2ppnlzZFRETsQUkpV9teu3Sv0zlGkUs7UT0pERERETfkEwSjHzHOlzwNxTlNbtJiNnFpcl3B88wmtyciImIvSkq5Wn09Kfst3YPj60kF27VdEREREXGwpCshNgUqS2Dho3Zpsm4XviXp+eQWldulTRERkaZSUsqVinNgf5px3mWs3Zq1Wm2srZ8pFWq3dkVERETECcxmGP+scb5+FmSuanKTHcP9SWkfgtUGX6RlN7k9ERERe1BSypV2zDceY1MgINJuze7KL6GovBofTzPdogPs1q6IiIiIOElcCvS9yjj/4R6wWpvcZN1sqdmpmdhstia3JyIi0lRKSrnSdscs3aurJ5UUF4ynRR+xiIiIiFsa/TB4B8KBdbDugyY3d0GfaHw9LezOLyUto6DJ7YmIiDSVMhauUlUOu38yzh1VT0pFzkVERETcl38EjLzPOF/4KBwtaFJzAT6ejO8dBajguYiINA9KSrnK3qVQVQYBMRDV265N133zldJOSSkRERERt3bWnyEsEcoOwuKnmtzcxJR4AL7bcICyyuomtyciItIUSkq5Svoc47HrODCZ7NZsQVklO/NKAOinnfdERERE3JvFE8bXJqNWvQl5W5vU3MAOobQL9aOkopoX5qfbIUAREZEzp6SUK9hskD7POE8cb9em12YWANAhrA1t/b3t2raIiIiIuECnc6HbhWCrgTl/N8aSZ8hsNvHghT0AeHvpHhZuybVXlCIiIo2mpJQr5G6Gwkzw8IUOZ9u16bTaelKaJSUiIiLSgox7AizesGcJbP2mSU2N6RHJ9UM7AHDX7PVkFxy1R4QiIiKNpqSUK6TX7rrXcSR4+tq16bqd91JU5FxERESk5QhJgKG3G+fzHoDKsiY1d9/4bvSJC6LwaBV/+2gtVTXWpscoIiLSSEpKuUJdUqrrOLs2W2O1sa62yHmyipyLiIiItCzD7oTAOGPG/fKXm9SUl4eZmVckE+DtQeq+I7ywQPWlRETE+ZSUcraSfMhaY5zbOSm1PaeY0soa/L096BoZYNe2RURERMTFvPxg3P8Z50tfhIKMJjXXrq0fT0/oA8Bri3exeHteUyMUERFpFCWlnG3HfMAG0UkQGGPXpuuW7vWND8Zitt+OfiIiIiLSTPS4BBKGQ3W5sYyvic7vHc2fBrUHYNqn68ktKm9ymyIiIqdLSSlnq1+6d57dm64rcp6selIiIiIiLZPJBOOfBpPFKHi+e3GTm3zggu70iA7kcGklf/toLdWqLyUiIk6ipJQzVVfCrh+Nc0ckpWpnSiVr5z0RERGRliuyJwy40Tifcx/UVDWpOR9PCzOv7EcbLwsr9xzm5R932iFIERGR36eklDPtWwqVJeAfCdF97dr0wZIK9h4ydmHppyLnIiIiIi3bOdPBNxTyt8Lqt5vcXMdwf568tDcAr/y4g2U7Dza5TRERkd+jpJQzpc8zHruOA7N9f/Vra3fd6xLhT5Cvp13bFhEREZFmxjcERj1knP80w9hMp4ku7hvL5QPisdng9o/XkV9c0eQ2RURETkVJKWex2WD7HOPcAUv3UmvrSaWonpSIiIhI65B8tbF5TkUh/PiYXZp8+KKeJEYGcLCkgjs/WUeN1WaXdkVERE5ESSlnyd8OBfvA4g0dR9q9+WP1pJSUEhEREWkVzBYY/4xxnvZfyE5rcpO+XkZ9KV9PC0t3HuS1xaovJSIijqOklLOk186S6nA2eLWxa9NVNVY2ZBUA2nlPREREpFVpNwj6TAZsMOdesDZ957wukQE8dnFPAF5YkM7K3Yea3KaIiMiJKCnlLMfXk7KzrQeKKK+yEuTrSccw+ya8RERERKSZG/0oePlD1mrY8IldmpzYP55Lk2Ox2uBvH6/lUInqS4mIiP0pKeUMZYchc6Vx7sB6UsntgjGbTXZvX0RERESascBoOPse43zhw1BeZJdmH7+4F53C25BbVMFds9djVX0pERGxMyWlnGHHArBZIbIXBMfbvfm02p33VE9KREREpJUadDOEdoKSXPj5Gbs02cbbg5lXJuPtYWbx9nze+mW3XdoVERGpo6SUM6TPNR4dMEsKIE0774mIiIi0bh7eMP5p4/zX1yA/3S7Ndo8O5OGLjPpSz8zbXj9DX0RExB6UlHK0mirYucg4d0BSKqewnOyCo5hNkBQfbPf2RURERMRNdBljjDet1TD3PrDZZ7ndFWfFc1FSDDVWG3/7aC0FZZV2aVdERERJKUfLWAEVheAXBrEpdm8+LcP4tqpbVCBtvD3s3r6IiIiIuJFxT4LFC3YtOjZbv4lMJhNP/rEXCW39yC44yt2zN2CzU8JLRERaNyWlHG173dK9cWC2/6+7bulecvtgu7ctIiIiIm6mbScYfKtxPvc+qCq3S7MBPp7MvDIZL4uZhVtzeW/ZXru0KyIirZuSUo6WflxSygFSM1RPSkRERESOM/wuCIiGI3thxUy7NdsrNogHLugOwIw5W9mQVWC3tkVEpHVSUsqRDu6Aw7vA7AmdzrV78+VVNWzONrb81c57IiIiIgKAtz+Medw4/+V5KMy2W9NXD27PeT2jqKqxceustRSVV9mtbRERaX2UlHKkullSCcPAO8DuzW/eX0hljZUwfy/ahfrZvX0RERERcVO9J0C7wVBVBgsetFuzJpOJpyf0IS7El4zDZdz3uepLiYjImVNSypHS5xmPieMd0nzavgIA+rULwWQyOaQPEREREXFDJhOMfwZMZtj0OexdZremg3yN+lIeZhM/bMzhg5UZdmtbRERaFyWlHOXoEdi33Dh3VD2pfaonJSIiIiInEd0HUq41zufcCzXVdmu6b3ww943vBsDj321h8/5Cu7UtIiKth5JSjrJzEdhqILw7hCTYvXmbzVZf5Fz1pERERETkhM59EHyCIXcTpL1v16ZvGNaBUd0iqKy2cuustZRU2C/pJSIirYOSUo7i4F33so4cJb+4Ag+ziT5xQQ7pQ0RERETcnF8onPsP4/zH/4Oyw3Zr2mQy8dzEJGKCfNhzsJQHvtyo+lIiItIoSko5Qk017FhgnDuqnlTtLKmeMYH4eFoc0oeIiIiItAAp10FkL6O8xI//Z9emQ9p48fIV/bCYTXy9bj+frsm0a/siItKyKSnlCJkrobwAfEMgboBDukirrSfVT0v3RERERORULB4w/mnjPPU9OLDBrs33TwjlrrFdAXj4m81szym2a/siItJyKSnlCHVL97qMBbNjZjGlZRQAKnIuIiIiIqchYRj0ugxsVpjzd7DzMru/nt2Js7uGU15lZeqsNMoqVV9KRER+n5JSjlBfT+o8hzRfVlnNlgNFACQrKSUiIiIip2PMY+DpBxnLYdPndm3abDbxwqQkIgK82ZlXwsNfb7Zr+yIi0jIpKWVvh3bBwXQwe0DnUQ7pYkNWITVWG1GBPsQE+TikDxERERFpYYLiYPg043z+g3Yteg4Q5u/Ny1f0w2yC2alZfJGWZdf2RUSk5VFSyt52zDce2w8BH8fsipdaW08quX0wJpPJIX2IiIiISAs0+DYISYDi/fDueVBg38Lkgzq25fZRRn2pf3y1iZ15JXZtX0REWhYlpext+xzj0UFL9wDW1u68l6wi5yIiIiLSGJ4+cMXHEBgLB7fDO2MgZ5Ndu7j13M4M6dSWssoabp2VRnlVjV3bFxGRlkNJKXsqL4J9y4xzByWlbDZbfZFz1ZMSERERkUaL6A43LICIHlB8AN4bD7uX2K15i9nES5f3Jczfi205xTz23Ra7tS0iIi2LklL2tGsRWKuhbRdo28khXew9VMbh0kq8PMz0jAl0SB8iIiIi0sIFxcJ1c6D9MKgogg8ug42f2a35iAAfXprcD5MJZq3M4Nv1++3WtoiItBxKStlT+jzjses4h3VRV0+qd2wQ3h4Wh/UjIiIiIi2cbzD86Qvo+UewVsHnN8Cyl8Fms0vzw7qEMXVkZwCmf7GRvQdL7dKuiIi0HEpK2Yu15liR88TxDusmrbaeVIqW7omIiIhIU3l4w2XvwqCpxs8LHoS508FqtUvzd4zuwlkJoZRUVHPrR2lUVKu+lIiIHKOklL1krYGyQ8aOe/EDHdZNWt3Oe+2CHdaHiIiIiLQiZjOc9ySMfcL4eeVr8Nl1UFXe5KY9LGb+eUVfQvw82ZRdxIwftjW5TRERaTmUlLKX9LnGY+cxYPF0SBfF5VVszy0GtPOeiIiIiNjZkFvhsnfA4gVbvoIPLoWjR5rcbHSQLy9M6gvA+8v3MnfTgSa3KSIiLYOSUvZSl5Ry0K57AOsyC7DZIC7El4hAH4f1IyIiIiKtVO8JcNUX4B1k7Cr97nlQmNXkZs/pFsFfzu4IwD2fbSDzcFmT2xQREfenpJQ9HNkHeVvAZIHOoxzWTdq+AkD1pERERETEgToMh+vnQEAM5G+Dt8dA7uYmN3v3uET6tQumuLyaWz9aS2W1fepWiYiI+1JSyh7qdt1rNwj8Qh3WTWpGXT0pJaVERERExIEie8KNCyC8OxTvN2ZM7fm5SU16Wsy8ckU/gnw9WZ9ZwLPzVF9KRKS1U1LKHuqX7o1zWBdWq4212nlPRERERJwlKM6YMdV+KFQUwQeXwcbPmtRkXIgfz07oA8Bbv+xh0dZce0QqIiJuSkmppqoohr2/GOddxzusm535JRSXV+PraaFbVIDD+hERERERqecbYtSY6nEJ1FTC5zfA8plNanJszyiuG5oAwF2z17O/4GjT4xQREbekpFRT7V5s/AUd0gHCujism7R9xiyppPggPCz62ERERETESTx9YMJ7MPBm4+f5D8Dc+8F65jWhpo/vTp+4IArKqvjbR2uprlF9KRGR1kjZjabaXrt0L3E8mEwO6yZ1n+pJiYiIiIiLmM1w3gwY+3/Gz7++Cp9fD9UVZ9Scl4eZmVckE+DtwZp9R3hhQbodgxUREXehpFRTWK2wo7bIuQPrSQGkqZ6UiIiIiLiSyQRDboPL3gGzJ2z+Ev57KRwtOKPm2rX146nLjPpS/1q8iyXp+XYMVkRE3IGSUk2xfy2U5oN3ILQb4rBuCsoq2ZVfCkA/zZQSEREREVfqPQGu+twYA+9bauzMV5h1Rk1d0Ceaqwa1A2DaJ+vILSq3Z6QiItLMKSnVFOlzjMdO54KHl8O6WZtRAEDHsDaEtnFcPyIiIiIip6XjCLhuDgREQ/5WeHsM5G4+o6b+cUEPukcHcqi0kts/XkuN1WbnYEVEpLlSUqop0o+rJ+VAdfWkNEtKRERERJqNqF5wwwIIS4Ti/fDueNjzS6Ob8fG08OqV/fDzsvDr7sO8vGiHA4IVEZHmSEmpM1WYBTkbARN0HuPQrlRPSkRERESapeB4uH4utBsMFYXwwaWw6YtGN9Mx3J8n/9gbgJd/3MHynQftHamIiDRDSkqdqfTaAufxZ0Gbtg7rprrGyrrMAgCS2wc7rB8RERERkTPiFwp/+gq6/wFqKuGz62DFq41u5pJ+sUzuH4/NBrd/so784jPb2U9ERNyHklJnqm7pXtfzHNrN9txiyiprCPD2oEtEgEP7EhERERE5I54+MPF9OOsvxs/z7od5Dxi7VTfCI3/oSddIf/KLK5j26Tqsqi8lItKiKSl1JipLYfcS49zBSam02npSfdsFYzGbHNqXiIiIiMgZM1tg/NMw5jHj5xUz4fMboPr0Zzz5ell49cpkfDzN/LLjIK8t2eWgYEVEpDlQUupM7F4CNRUQ3A4iuju0q7TanfeSVeRcRERERJo7kwmG3g6XvgVmT9j8BXxwGRwtOO0mukQG8NjFvQB4fv52Vu057KBgRUTE1ZSUOhPHL90zOXb2Ut3Oe8kqci4iIiIi7qLPJJgyG7wCYO8v8N54KMw+7ZdPTInj0n6xWG3wt4/Wcri00oHBioiIq5xRUurVV18lISEBHx8fBg4cyKpVq05671tvvcXw4cMJCQkhJCSE0aNHn/L+Zs9mO1bk3MFL9/KLK8g4XIbJBH3jgx3al4iIiIiIXXU6B677AfyjIG8LvDMG8rae1ktNJhOPX9KLjuFtyCkq5+7Z61VfSkSkBWp0UuqTTz5h2rRpPPzww6SlpZGUlMS4cePIy8s74f2LFy/miiuu4KeffmLFihXEx8czduxYsrNP/5uSZuXAOijJAc82kDDMoV2lZRizpLpE+BPk6+nQvkRERERE7C66D9y4AMK6QlE2vDsO9i47rZe28fbg1SuT8fIw8+O2PN5eutvBwYqIiLM1Oin1wgsvcNNNN3HdddfRo0cPXn/9dfz8/Hj33XdPeP+HH37ILbfcQt++fenWrRtvv/02VquVRYsWNTl4l6ibJdXpHPDwdmhXdUmpFC3dExERERF3FdwOrp8H8YOgvBD+ewls/vK0Xto9OpCHL+oBwDNzt9ePj0VEpGVoVFKqsrKS1NRURo8efawBs5nRo0ezYsWK02qjrKyMqqoqQkNDGxdpc7F9jvGYON7hXdXtvNdPRc5FRERExJ35hcLVX0G3C6GmEmZfB7++dlovvfKsdlzYJ5pqq43bZq2lsKzKsbGKiIjTNCopdfDgQWpqaoiMjGxwPTIykpycnNNq4+9//zsxMTENElv/q6KigqKiogZHs1B0wFi+hwm6jHVoV5XVVjZkFQKaKSUiIiIiLYCnL0z6Dwy4CbDB3Ptg/j/Aaj3ly0wmEzMu7U37tn5kFxzlns/WY7OpvpSISEvg1N33nnrqKT7++GO+/PJLfHx8TnrfjBkzCAoKqj/i4+OdGOUp7KhduhebAv4RDu1qy4EiKqqtBPt50jGsjUP7EhERERFxCrMFzn8WRj9i/Lz8FfjiJqiuOOXLAnw8jfpSFjPzt+Ty/vK9Dg9VREQcr1FJqbCwMCwWC7m5uQ2u5+bmEhUVdcrXPvfcczz11FPMnz+fPn36nPLe6dOnU1hYWH9kZmY2JkzHcdKue3Bs6V5yuxBMJpPD+xMRERERcQqTCYbdCX98A8wesOkz+HCCUW/qFHrFBnH/+d0AePKHrWzIKnBCsCIi4kiNSkp5eXmRkpLSoEh5XdHywYMHn/R1zzzzDI8//jhz586lf//+v9uPt7c3gYGBDQ6XqzoKuxcb54mOT0qlZtQlpYId3peIiIiIiNMlXQ5TZoOXP+z5Gd47H4r2n/Il1wxJYFzPSKpqbNw6ay1F5aovJSLizhq9fG/atGm89dZb/Pvf/2br1q3cfPPNlJaWct111wFw9dVXM3369Pr7n376aR588EHeffddEhISyMnJIScnh5KSEvu9C2fY8wtUlUFgLET2cnh3a+tmSqmelIiIiIi0VJ3Ohet+AP9IyN0Eb4+BvG0nvd1kMvHMZUnEhfiScbiM6V9sVH0pERE31uik1OTJk3nuued46KGH6Nu3L+vWrWPu3Ln1xc8zMjI4cOBA/f2vvfYalZWVTJgwgejo6Prjueees9+7cIb0ucZj13HGlGMHOlB4lP2F5ZhNkBQX7NC+RERERERcKjoJblgAbbtAURa8Oxb2LT/p7UF+nrxyRT88zCa+33CAWasynBisiIjYk8nmBl8tFBUVERQURGFhoWuW8tls8GIv4y/JK2dDV8fuvPf9hgNMnZVGz5hAvv/bcIf2JSIiIqfm8nHIGXLXuKUVKzsMsyZD1iqweMNlb0GPi096+1s/7+aJH7bi5WHmq1uG0iNGf85FRJqL0x2HOHX3PbeVu8lISHn4QgfHJ4lSjytyLiIiIiLSKviFwjXfQLcLoaYCPr0GVr5x0ttvHN6BUd0iqKy2cuusNEorqp0YrIiI2IOSUqdje+3SvU7ngKevw7tLqy1ynqJ6UiIiIi3CjBkzGDBgAAEBAURERHDJJZewffv2U77m/fffx2QyNTh8fHycFLGIi3j6wqT/QP8bABvMuRfmPwhW629uNZlMPDcxieggH3YfLOUfX21SfSkRETejpNTpOL6elIOVV9Wweb+xHa5mSomIiLQMS5YsYerUqfz6668sWLCAqqoqxo4dS2lp6SlfFxgYyIEDB+qPffv2OSliERcyW+CC5+HcB42fl78MX/4Fqit/c2tIGy9evqIfFrOJL9dmMzs1y8nBiohIU3i4OoBmryQPslON8y6OT0ptyi6kqsZGmL838aGOn5UlIiIijjd37twGP7///vtERESQmprK2WeffdLXmUwmoqKiHB2eSPNjMsHZd0NgDHxzG2z8FEpyYfIH4NOwNsmAhFCmjenKs/O289DXm+gbH0zXyAAXBS4iIo2hmVK/Z8d8wAbRfSEw2uHdHasnFYzJwbv8iYiIiGsUFhqzokNDQ095X0lJCe3btyc+Pp6LL76YzZs3OyM8keaj75Vw5afg5Q97lsB750PRgd/cdvOITgzvEkZ5lZWpH6q+lIiIu1BS6vfUL907zyndqZ6UiIhIy2a1WrnjjjsYOnQovXr1Oul9iYmJvPvuu3z99dd88MEHWK1WhgwZQlbWiZcnVVRUUFRU1OAQaRE6j4Jrv4c2EZC7Ed4ZA/kNa7KZzSZenNyXiABvduSVMOmNFewvOOqigEVE5HQpKXUq1RWw6yfjPNHxSSmbzUbqvgIAkpWUEhERaZGmTp3Kpk2b+Pjjj0953+DBg7n66qvp27cvI0aM4IsvviA8PJw33jjxbmQzZswgKCio/oiPj3dE+CKuEdMXblwAbTtDYSa8Mxb2rWhwS5i/N29e3Z+2bbzYvL+IP8xcSuq+w66JV0RETouSUqeydylUloB/FEQlOby7rCNHOVhSgafFRO/YIIf3JyIiIs5166238t133/HTTz8RFxfXqNd6enrSr18/du7cecLnp0+fTmFhYf2RmZlpj5BFmo+QBLh+PsQNgPIC+O8lsPXbBrf0jQ/m61uH0j06kIMllVz+5q98ukb/LYiINFdKSp3K8bvumR3/q6qrJ9UjJggfT4vD+xMRERHnsNls3HrrrXz55Zf8+OOPdOjQodFt1NTUsHHjRqKjT1zj0tvbm8DAwAaHSIvTpi1c/Q0kng/V5fDJn2Dlmw1uiQvx47O/DmZ8ryiqamzc+9kGHv9uC9U1VhcFLSIiJ6Ok1MnYbK6rJ9VOS/dERERakqlTp/LBBx8wa9YsAgICyMnJIScnh6NHj9W8ufrqq5k+fXr9z4899hjz589n9+7dpKWlcdVVV7Fv3z5uvPFGV7wFkebDyw8m/RdSrgNsMOceWPAwWI8lndp4e/DqlcncMboLAO8s3cN176+msKzKRUGLiMiJKCl1MnlboSADPHyg40indFm/8177YKf0JyIiIs7x2muvUVhYyMiRI4mOjq4/Pvnkk/p7MjIyOHDg2K5iR44c4aabbqJ79+6cf/75FBUVsXz5cnr06OGKtyDSvFg84MIX4dx/GD8vewm++itUV9bfYjabuGN0V16bkoyvp4Vfdhzkkn8tY2deiWtiFhGR3/BwdQDNVt0sqQ5nG9/GOFhpRTXbcooB7bwnIiLS0thstt+9Z/HixQ1+fvHFF3nxxRcdFJFIC2Aywdn3QEAMfHMbbPgESnKNWVQ+x5avju8dTbu2fvz5P6nsOVjKH19dxstX9uOcxAgXBi8iIqCZUifn5KV767MKqLHaiA7yITrI1yl9ioiIiIi4vX5T4MpPwbMN7F4M758PB3c0uKVnTBBf3zqUAQkhFFdUc8P7q3nr592nlTAWERHHUVLqREoPQeYq47zrOKd0uTajAIBkzZISEREREWmcLqPh2u+gTTjkbIR/DYb5/4Dyovpbwvy9+fDGQVw+IB6rDZ74YSt3zV5PeVWNCwMXEWndlJQ6kZ0LABtE9oagxm3XfKbq60mpyLmIiIiISOPFJsONi6DLOLBWwfJX4JUUWPthfRF0Lw8zMy7tzSMX9cBiNvFFWjaXv/kreUXlLg5eRKR1UlLqRLbPMR4TnbN0z2azHdt5TzOlRERERETOTEh7mPIpXDkbQjtBaR58fQu8MxqyUgEwmUxcO7QD/77uLIJ8PVmXWcAfZi5jQ1aBa2MXEWmFlJT6X9WVsOtH49xJ9aR2HyyloKwKbw8zPaIDf/8FIiIiIiJycl3Hwi2/wpjHwMsfslPh7XPhq1ugOBeAYV3C+HrqUDpH+JNTVM7E11fw9bpsFwcuItK6KCn1vzKWQ0WRsR49JtkpXabVLt3rExeEl4c+EhERERGRJvPwgqG3w22pkHSlcW3dh8aSvmUvQ3UlCWFt+PKWIZzbLYKKaiu3f7yOZ+Zuw2pVAXQREWdQBuR/pc8zHruMA7Nzfj11S/dUT0pERERExM4CouCPrxn1pmKSobIYFjwIrw2GHQsI8PHkrav789cRnQD41+Jd/Pm/aygur3Jx4CIiLZ+SUsez2ZxeTwogbV8BoJ33REREREQcJq6/kZi6+F/QJgIO7YQPJ8CHk7Ac2c1947vx0uS+eHmYWbg1j8teW86+Q6WujlpEpEVTUup4B3fAkT1g8YKOI53SZVF5Fel5xYBmSomIiIiIOJTZDP2mGEv6htwGZg/YMQ9eHQgLHuaSHoHM/stgIgK8Sc8t4eJXl7F850FXRy0i0mIpKXW89NpZUgnDwDvAKV2uyyjAZoN2oX6EB3g7pU8RERERkVbNJxDG/h/cvAI6jwZrFSx7CV7pT9KhOXx76xCS4oIoKKviT++u4j8r9mKzqc6UiIi9KSl1vLp6Ul3HO63L1H119aSCndaniIiIiIgA4V1hymdwxScQ0gFKcuCrvxI5+w98epE3f+wXS43VxkNfb+aBrzZRWW11dcQiIi2KklJ1yg5Dxq/GeddxTuu2rsh5iupJiYiIiIg4n8lk1JOduhJGPwKebSBrNd7vjeEF77d4dFQ4JhPMWpnBVe+s5FBJhasjFhFpMZSUqrNzEdhqIKIHhLR3SpdWq411GQUA9FM9KRERERER1/HwhmF3GvWm+lwO2DCt+4Br1lzG/EEbCfaGVXsO84eZy9h6oMjV0YqItAhKStVJn2s8OnGW1I68EoorqvHzstAtyjk1rERERERE5BQCo+HSN+CGBRDdFyqK6LJ2BqtCHmJi0HayC45y2WvLmbspx9WRioi4PSWlAGqqYOcC49yJ9aTqlu4lxQXjYdFHISIiIiLSbMSfBTf9BH+YCX5heBXs5NmKR/k8+BXCqvbz1w9SeXnRDhVAFxFpAmVCADJXQnkh+IZCXH+ndVtX5Fz1pEREREREmiGzGZL/ZCzpGzQVzB6klK/gR597ucfjY15fsIFbZ62lrLLa1ZGKiLglJaUAts8xHruMBbPFad3WzZRKbh/stD5FRERERKSRfIPhvCfh5uXQ6Vw8bFVM9fiGH73vwmPzbCb8aznZBUddHaWIiNtRUgqMZFS/q6DXpU7r8khpJbvzSwHoF6+ZUiIiIiIizV54Ilz1BVw+C0ISiDId4Z9e/+LRw3dx7yv/Yc3ew66OUETErSgpBdBxBFz8qlOLnK/NNGZJdQxvQ0gbL6f1KyIiIiIiTWAyQbcL4JaVMOohrB6+DDCn89/qv7Pz3Rv4eul6V0coIuI2lJRykfp6Uu00S0pERERExO14+sDwuzDflkp1zwmYTTYuN//IOQvOY+7bD1FdWeHqCEVEmj0lpVwkbV8BAMkqci4iIiIi4r6CYvGY+A7Wa+eQ1yaRQFMZ52X9k5xnBlCyZaGroxMRadaUlHKB6hor6zILAO28JyIiIiLSEpgThhBx1wo2Jj/GYVsAcdX78P/0Mkr+PQkO73F1eCIizZKSUi6wLaeYo1U1BPh40Dnc39XhiIiIiIiIPZgt9P7D7eRdu5xPLRdSbTPjv2ceNTPPgkWPQ2WpqyMUEWlWlJRygbQMo55Uv3YhmM0mF0cjIiIiIiL21K1DO869813uDfsXS2t6YrFWwi/PYZs5ADZ+Bjabq0MUEWkWlJRygbTaIufJ7YJdG4iIiIiIiDhEmL83T908me/7vsZfKu8k0xqOqSgbPr8B3jsfDmxwdYgiIi6npJQLpNbOlFI9KRERERGRlsvLw8yTl/ZhyIXXMq76OZ6rmkg53pCxHN4cAd/eAaWHXB2miIjLKCnlZHnF5WQePorJBH3jg10djoiIiIiIOJDJZOKaIQm8df0w/us1iXPKn2O+eSjYrJD6HrzSD1a+ATXVrg5VRMTplJRysrR9BQAkRgYQ4OPp2mBERERERMQphnYO45tbh9Imoj1/LpvKlOqHKQxMhPJCmHMvvDEcdi9xdZgiIk6lpJSTrT2uyLmIiIiIiLQe7du24ctbhnButwiWVSfSL+9B5nX4OzbfUMjbAv/5A3zyJziyz9Whiog4hZJSTpa6T/WkRERERERaqwAfT966uj83j+yEFTN/2ZrE7WFvU5l8I5gssPUbePUs+OlJqCxzdbgiIg6lpJQTVVZb2ZBdCGjnPRERERGR1spiNvH387rxz8v74u1h5psd5Vyw8w/sv3w+JAyH6nJY8jTMHACbvgCbzdUhi4g4hJJSTrR5fyGV1VZC/DzpENbG1eGIiIiIiIgLXdw3lk//MpjIQG925JUw/uPDLBv6Hkz6DwTFQ1EWfHYdvH8h5GxydbgiInanpJQTpWUUAJDcLgSTyeTaYERERERExOWS4oP55tZhJMUHU3i0iqvfW82/C5KwTV0JI6eDhw/sW2oUQv9uGhRkuDpkERG7UVLKidJq60klq56UiIiIiIjUigz04ZM/D+LSfrHUWG08/M1m7v9uF5XD7oVbV0OPS8BmhTXvwEu9jZlT6z6CylJXhy4i0iRKSjlRWu3Oe8naeU9ERERERI7j42nh+UlJTB/fDZMJPlqVyVVvr+SQRyRM+jdc8x10OBswwd5f4Ku/wnNd4atbYO9SsFpd/RZERBpNSSkn2V9wlAOF5VjMJpLig1wdjoiIiIiINDMmk4m/jOjEu9cMIMDbg1V7D/OHmcvYsr8IOgyHa76FOzbAOf+A0I5QWQLrPoT3L4CXk+CnGXB4j6vfhojIaVNSyknqZkl1jw7Az8vDxdGIiIiIiEhzdU63CL6cOoSEtn5kFxzlsteWM3fTAePJ4HYw4h64LQ2unwfJ14B3oFFraslT8HJfeO98WPsBVBS79H2IiPweJaWcJLW2nlSKlu6JiIiIiMjv6BwRwNdThzGscxhHq2r46wdp/HPhDqxWm3GDyQTtBsEfXoa70+Gyd6DTuYAJ9i2Dr6cay/u++AvsXqzlfSLSLCkp5ST1O++pyLmIiIiIiJyGID9P3r9uANcNTQDgxYXpTH5zBZuyCxve6OkLvSfAn76EOzfDqIehbReoKoMNH8N/LoZ/9oFFj8OhXc5/IyIiJ6GklBOUV9WwufYvDhU5FxERERGR0+VhMfPwRT15+rLe+HpaWL33CBfNXMr9X27kcGnlb18QFAvDpxm79t24CPpfDz5BUJgJvzwHryTDO2Mh9X0oL/zt60VEnEhJKSfYmF1ItdVGeIA3cSG+rg5HRERERETczOQB7Vh01wguSorBZoNZKzMY+exP/Hv5XqprTrA0z2SCuP5w4YtwVzpMeA+6jAWTGTJXwre3G8v7PrsBdi4Ea43z35SItHpKSjnB8fWkTCaTi6MRERERERF3FBPsyytX9OOTPw+iW1QAReXVPPzNZi54eSnLdx08+Qs9faDXpTBlNkzbCmMeg/DuUF0Omz6DDy6DF3vBwkcgP91p70dEREkpJ0irTUoltw92bSAiIiIiIuL2BnZsy3e3DePxS3oR7OfJ9txirnxrJVM/TCO74OipXxwQBUNvh1tWwE0/wVl/Bt8QKN4PS1+EVwfAW6Ng9dtw9Ihz3pCItFpKSjmYzWYjLaN2ppSKnIuIiIiIiB14WMz8aVB7frprJH8a1B6zCb7feIBRzy/mnwt3UF71O8vxTCaITYbzn4W7tsOk/0LX8WCyQPYa+P4ueC4RZl8L6fOhptop70tEWheTzWazuTqI31NUVERQUBCFhYUEBga6OpxGyThUxtnP/oSnxcTGR8bh42lxdUgiIiLSCO46DnHXuEXkzGzZX8Qj325m1Z7DAMQG+/Lghd0Z1zOqcSVESvJg42xYNwtyNx277h8JfSZB0pUQ2cPO0YtIS3O64xDNlHKw1AzjL4VesUFKSImIiIiIiEP0iAnkkz8P4pUr+hEd5EN2wVH++kEaV72zkvTc4tNvyD8CBk+Fm5fBX36BgTeDX1soyYXlr8Brg+GNEbDyTSg77Lg3JCKtgpJSDpa2rwCA5HZauiciIiIiIo5jMpm4KCmGRXeN4LZzO+PlYWbZzkOM/+cvPPbtFgqPVjWuweg+MP4pmLYNLp8F3S4EswccWAdz7jF27/vkKtj2A9Q0sm0REZSUcrj6nfdUT0pERERERJzAz8uDu8YmsvDOEYztEUmN1ca7y/Zw7nOL+XhVBjXWRlZw8fCCbhfA5R/CXekw/hmITgJrFWz9Fj6+Ap7vBnOnQ85Gx7wpEWmRVFPKgUorqun9yDysNvh1+iiignxcHZKIiIg0kruOQ9w1bhGxv5/T83n0283syi8FoHdsEI/8oWfTvzjP3WzUntrwKZTmHbse1duoPdV7IviHN60PEXFLqinVDKzPLMBqM4oMKiElIiIiIiKucHbXcObecTb/uKA7Ad4ebMwu5LLXljPtk3XkFZWfecORPWHcEzBtK1z5KfS4GCxexmypedPhhW7w0RXGbKrqSvu9IRFpMTxcHUBLlpZhLN3r1y7YtYGIiIiIiEir5mkxc+PwjlzcN5Zn523j0zVZfLE2m3mbc7htVBeuG5qAt8cZbsxk8YCu44yj7DBs+tyYQbU/Dbb/YBy+ocbMqb5XGkv/GrMjoIi0WJop5UCqJyUiIiIiIs1JeIA3z0xI4qupQ+kbH0xpZQ1PzdnGeS/9wk/b8n6/gd/jFwpn3QR//gluWQlDbwf/KDh6GFa9AW+OgNeGGDv5Fec2vT8RcWtKSjmI1WpjbWYBoJ33RERERESkeekbH8wXNw/huYlJhPl7s+dgKde9v5rr31/NnoOl9ukkohuMeQzu3AxTPodel4HFG/K2wPx/wAvd4cNJsPlLqGrCMkIRcVtavucguw+WUlBWhY+nmR4xKi4qIiIiIiLNi9lsYkJKHON6RvLKjzt5d+keftyWxy878rlhWEduPbcz/t52+CejxQO6jDaOowVGEmrdLMhaBTvmGYdPMHS/ELpdBB1Hgqdq8oq0Bpop5SB19aT6xAbjadGvWUREREREmqcAH0/uP787c+84m7O7hlNVY+P1Jbs497nFfLk2C7tu2O4bDP2vgxsXwK1rYPhdEBgL5QWw9gP4aDI82wk+vQY2fgblhfbrW0SaHWVLHCSttp5UsupJiYiIiIiIG+gc4c+/rxvA21f3p12oH3nFFdz5yXomvL6CjVkOSA6FdYFRD8EdG+Gab+GsPxsJqsoS2PIVfH4DPNMJPrgM1rwHJXaoeSUizYrJZte0t2MUFRURFBREYWEhgYHusRRu7ItLSM8t4c0/pTC2Z5SrwxEREZEz5I7jEHDfuEWkeSivquGdpXuY+eNOjlbVYDLB5QPiuXtsIm39vR3Xsc1m7Nq39TvY9h0cTD/uSRPED6xd5nchhHZwXBwi0iSnOw5RUsoBCo9WkfTofADW/GM0YY78n7aIiIg4lLuNQ+q4a9wi0rwcKDzKU3O28fW6/QAE+HgwbUxXrhrU3jllSvLTYdu3RpJqf1rD5yJ7H0tQRfYEk8nx8YjIaVFSyoWWpOdzzburaN/WjyX3nOPqcERERKQJ3G0cUsdd4xaR5mn13sM8/PVmthwoAqBrpD8PX9SToZ3DnBdEYRZs+8FIUu1dBraaY8+FJBjJqe4XQdxZYFalGhFXOt1xiP5LdYDU2npSKe1UT0pERERERNzfgIRQvr1tGE/8sRchfp6k55Yw5e2V3PxBKpmHy5wTRFAcDPyzUX/qnp1w8b8g8Xzw8IEje2HFTHh3HDyfCN/eDjsWQnWlc2ITkTNih/095X+trd15r5+KnIuIiIiISAthMZuYMrA9F/SO5sUF6fz3133M2ZTDj9vy+OuITvx1RCd8vSzOCcYvFPpNMY7KUti50Fjilz4PSvMg9X3j8A6ELmONZX6dx4C3v3PiE5HTouV7dlZjtZH06HxKKqr54W/D6RHTvOMVERGRU3Onccjx3DVuEXEf23KKeOSbzfy6+zAAscG+PHBBd8b3isLkqvpO1ZWw9xejSPq276Ek99hzFm/odI6xzC/xfGjT1jUxirQCqinlIttyijjvpV9o42VhwyPjsJhVbE9ERMSdudM45HjuGreIuBebzcYPG3N44vst7C8sB2Bwx7Y88oeeJEYFuDY4qxWy18DWb43jyJ5jz5nM0H6okaDqdgEEx7suTpEWSEkpF/lw5T4e+HITQzu35cMbB7k6HBEREWkidxqHHM9d4xYR93S0sobXluzi9SW7qKy2YjGb+NOg9tw5uitBfp6uDg9sNsjbYizx2/Yt5Gxs+Hx039qd/C6C8ETt5CfSRKc7DlFNKTtL21cAQLKKnIuIiIiISCvh62Vh2piuTEyJ44nvtzJ3cw7vL9/L1+uyuWdcNyYPiHftKhKTCSJ7GsfIvxuF0bd9bySpMlbAgXXG8eP/QdvOx3byi0nWTn4iDqSZUnZ2znOL2XOwlPeuG8A5iRGuDkdERESayJ3GIcdz17hFpGVYuuMgj367mR15JQD0jAnk0T/0pH9CqIsjO4GSfNj+g1GHavdiqDlux76AGOh2vpGgaj8ULM1g1peIG9DyPRc4XFpJ8uMLAFj/0NjmMU1VREREmsRdxiH/y13jFpGWo6rGyn9X7OPFhekUl1cDcEnfGO4b352oIB8XR3cS5UWwc4Exg2rHfKgsOfacTzAkjjdmUXU6F7z8XBamSHOn5XsukLbvCACdI/yVkBIRERERkVbN02Lm+mEd+EPfGJ6bt51P1mTy1br9zN+Sy63nduaGYR3w9rC4OsyGfAKh12XGUV0Bu5fA1m9g+xwoOwjrPzIOD1/oPMqYQdV1HPiqfIvImVBSyo7SMoykVHK7YNcGIiIiIiIi0kyE+Xvz1GV9uHJgOx75ZjNpGQU8M3c7n6zO5KELe3ButwhMzbGwuIc3dB1rHNYayPjVWOK39TsozDDOt30HZg9IGFa7k9+FEBjt6shF3IaW79nR5DdWsHLPYZ6+rDeTB7RzdTgiIiJiB+4yDvlf7hq3iLRsVquNr9ZlM2PONvKLKwAYmRjOgxf2oFO4v4ujO002G+RsqN3J7ztjV7/jxfY/tpNfWGfXxCjiYqop5WRVNVb6PDKfo1U1LLjzbLpEBrg6JBEREbEDdxiHnIi7xi0irUNJRTWv/LiDd5fuoarGhqfFxMT+8dwwrIP7JKfqHNp1bAZV1qqGz4V3O1aDKqYveLVxSYgizqaklJNtzCrkoplLCfTxYN1DYzG7crtTERERsRt3GIeciLvGLSKty+78Eh7/bgs/bc+vvzaqWwQ3DO/A4I5tm+eyvlMpzoFt3xtJqj0/g7X62HMmC0T0gLgUiBtgzKgK6wpms+viFXEQFTp3srp6Uv3ahSghJSIiIiIicho6hvvz3nVnsXL3Id76ZQ+LtuWyaFsei7bl0TMmkBuHd+CC3jF4ebhJ4iYgCgbcYBxHC4wd/LZ9D5krofgA5G40jtT3jfu9AyGmH8T1P5ao8g935TsQcSolpewktXbnvZT22nVBRERERESkMQZ2bMvAjm3ZnV/Ce8v2Mjs1k837i7jzk/U8NWcb1wxJYMpZ7d1rl3PfYOgzyTgACrMhew1krYHsVNi/FiqKYM8S46gT3M5ITsX1Nx6jk8DTxyVvQcTRtHzPToY9/SNZR47ywQ0DGdYlzNXhiIiIiJ24wzjkRNw1bhERgCOllcxalcH7y/fWF0T39bQwqX8c1w3tQEJYC6jNVFNtFEnPXgNZqcZj/nbgf/6JbvaEqF4NE1VtO4G7LW2UVkU1pZwor6ics55chNkE6x8eS4CPG2XvRURE5JSa+zjkZNw1bhGR41VU1/Dd+gO89ctutuUUA0YuZkz3SG46uyP924e4X92pUykvNGZQZa0+lqgqzf/tfT7BxxJUcf0hNgX8Qp0ersjJqKaUE9XVk+oaGaCElIiIiIiIiJ14e1i4LCWOS5NjWb7rEG/9spvF2/OZvyWX+VtySYoL4obhHTm/VxQeFjepO3UqPkHQcaRxANhsUJBxbDZV1mo4sB7KC2DnQuOoE9qxNkk1wCimHtkbPLxc8CZETp+SUnagelIiIiIiIiKOYzKZGNo5jKGdw9iRW8y7y/bweVo267MK+dtHa3k62JdrhyQw+ax4AlvSRAGTCULaG0evy4xr1ZWQu8moS5W1xkhYHdoJh3cbx8ZPjfss3hDd59hsqrj+ENxey/6kWdHyPTu47LXlpO47wvMTk7gsJc7V4YiIiIgdNfdxyMm4a9wiIqfrYEkFH/y6j/+u2Meh0koA2nhZmDygHdcNTSA+1M/FETpR2WHYn2YkqeoSVUeP/PY+v7Djlv2lGMv+fIKcH6+0eKop5SQV1TX0fng+lTVWFt89smUU3BMREZF6zXkcciruGreISGOVV9Xw9bps3v5lDzvySgAwm2B8r2huGN6B5HatcEWLzWbMmqqbTZW1GnI2grXqt/eGJR6rSxXXHyJ6gkWLqqRplJRykrSMI1z6r+WEtvEi9R+jW1aRPREREWnW45BTcde4RUTOlM1mY0l6Pu8s3cMvOw7WX09pH8KNwzowtmcUFnMr/vdaVbmRmMo+bjbVkb2/vc/DF2L6NiykHhirZX/SKCp07iRptfWkktu1sF0fRERERERE3IjJZGJkYgQjEyPYllPEO7/s4et1+0ndd4TUfUeID/XluiEdmDQgHn/vVvhPYU8fiB9gHHVKDx5LUGWtgew0qCiEjBXGUcc/6rjZVAMgph94+zv/PUiLo5lSTXTLh6n8sDGHe89L5JaRnV0djoiIiNhZcx6HnIq7xi0iYk95xeX8d8U+Pvh1H0fKjKVrAT4eXHlWO64ZkkBMsK+LI2xmrFajaHp27ZK/rDWQuxlsNQ3vM5khvLtRlyq6L0T2hPBu4BvsiqilGdLyPSew2WwMmrGI3KIKPvnzIAZ2bOvqkERERMTOmus45Pe4a9wiIo5wtLKGz9OyeHfpHnYfLAXAYjZxQe9obhrekd5xKvZ9UpVlcGD9sdlUWWugKOvE9wbGQkR3iOhRe3SH8ETwVPKvtdHyPSfYX1hOblEFHmYTfeKCXR2OiIiIiIiInICvl4WrBrXnyrPa8dP2PN7+ZQ8rdh/im/X7+Wb9fs7qEMqNwzowunsk5tZcd+pEvPyg/WDjqFOcc2zZX+5myN1iJKqKso1j58Jj95rMENIBIo9LVEX0gNBOKqguSko1RWptPakeMYH4ellcHI2IiIiIiIicitlsYlT3SEZ1j2RTdiHvLN3Dt+v3s2rPYVbtOUxCWz9uGNaBy1Li8PPSP5dPKiAKul9oHHXKCyFvG+RtgbytxmPuZjh6GA7vMo6t3x673+Jl7PwX0d04Insaj0HxKqreiui/siY4vsi5iIiIiIiIuI9esUG8OLkvfz+vG+8v38uslfvYe6iMB7/ezPML0pkysB1XD04gMtDH1aG6B58gaDfQOOrYbFCaX5ug2nJcwmorVJVC7kbjOJ5XAER0q01W9Tw2s8o/3LnvR5xCSakmSMuoTUq1V1JKRERERETEHUUF+XDf+G7cdm5nPkvN4t1le9h3qIxXf9rFmz/v5qKkGG4c1pEeMarP12gmE/hHGEfHkceuW61QmFmbpDouUZW/HSqLa4usr27Yll/Yb5cAhncDH30u7kyFzs/Q0coaej8yj2qrjaV/P4e4ED9XhyQiIiIOYI9xyIwZM/jiiy/Ytm0bvr6+DBkyhKeffprExMRTvm727Nk8+OCD7N27ly5duvD0009z/vnnOy1uEZHWqMZqY8GWXN5ZupvVe4/UXx/auS03DuvIiK7hqjvlKDVVcGhXwyWAeVvg8B7gJKmLoHa/XQIY1hU8vJ0aujSkQucOtiGrgGqrjchAb2K1jaiIiIicwpIlS5g6dSoDBgygurqa+++/n7Fjx7JlyxbatGlzwtcsX76cK664ghkzZnDhhRcya9YsLrnkEtLS0ujVq5eT34GISOthMZs4r1cU5/WKYl1mAe8s3cMPGw+wbOchlu08RKfwNtwwrCOXJsfi46nawnZl8axdutet4fXKMji43UhU5W4+NrOqeD8UZhjHjnnH7jdZoG2n3y4BDO0AZn1mzYlmSp2h1xbv4um52xjfK4rXrkpxdTgiIiLiII4Yh+Tn5xMREcGSJUs4++yzT3jP5MmTKS0t5bvvvqu/NmjQIPr27cvrr7/ukrhFRFqrrCNl/Hv5Xj5elUlxRTUAoW28uGpQe/40qD3hAZqV4xJHj9QWVz8uUZW7GcoLTny/hw+EJzZcAhjRHQJjVVzdzjRTysHqdt5LUT0pERERaaTCwkIAQkNDT3rPihUrmDZtWoNr48aN46uvvnJkaCIicgJxIX48cEEP/jaqC5+uyeLdpXvILjjKy4t28PriXVzSL4Ybh3eka2SAq0NtXXxDoP1g46hjs0FxTsNaVXmbjeRV9VE4sN44jucddGwJYESPY7Wr/E7+97TYh5JSZ8Bms7G2tsh5P+28JyIiIo1gtVq54447GDp06CmX4eXk5BAZGdngWmRkJDk5OSe8v6KigoqKivqfi4qK7BOwiIjUC/Dx5IZhHbhmcHvmbc7lrV92sy6zgE/XZPHpmizO7hrOjcM6MLxLGCbNvHENkwkCo42j86hj161WKNh7rFZVbm3S6tAOqCiEzF+N43h+YcYywNBO0LZj7WMnCO0I3kpA2oOSUmdg36EyDpVW4mUx0ytW0+FFRETk9E2dOpVNmzaxdOlSu7Y7Y8YMHn30Ubu2KSIiJ+ZhMXNBn2gu6BNN6r7DvP3LHuZtzuHn9Hx+Ts8nMTKAG4Z34OK+MXh7qIZRs2A2G8mk0I7Q7YJj16sr4dDO/9kJcAsc2QtlB40jc+Vv2/OPNJJUoR1/m7DyOnG9SPktJaXOQFrtLKlesYH6H4yIiIictltvvZXvvvuOn3/+mbi4uFPeGxUVRW5uboNrubm5REVFnfD+6dOnN1juV1RURHx8fNODFhGRU0ppH0pK+1AyDpXx3vI9fLI6k+25xdz72Qaembudqwe358qB7QjzV92pZsnDy1iuF9mj4fWKEji8y9gN8PAuOLT72M9lB6Ek1zgylv+2zYDo2oRVh+NmWnWCkA7g5eec9+UmlJQ6A6onJSIiIo1hs9m47bbb+PLLL1m8eDEdOnT43dcMHjyYRYsWcccdd9RfW7BgAYMHDz7h/d7e3nh76x88IiKu0q6tHw9f1JM7Rnfl41UZvL98LwcKy3lhQTovL9rByMQIJqTEcm63SLw8zK4OV36Ptz9EJxnH/yovrE1W7TaO+sTVLjh6GIoPGMe+E8yKDow9NmPrfxNWnj6Of1/NjJJSZyAtowCAZNWTEhERkdMwdepUZs2axddff01AQEB9XaigoCB8fX0BuPrqq4mNjWXGjBkA3H777YwYMYLnn3+eCy64gI8//pg1a9bw5ptvuux9iIjI7wvy9eQvIzpx/bAO/LDxAO8u28v6zAIWbs1l4dZcQvw8+UNSDBNS4ukVG6jaU+7IJwhik43jfx090nBW1eHjzssLoCjbOPb+8j8vNEFQ3HHJquOWBIYkgEfL/OLJZLPZbK4O4vc0py2NSyqq6fPIPKw2WHn/KCIDW18mU0REpDWxxzjkZP/geO+997j22msBGDlyJAkJCbz//vv1z8+ePZt//OMf7N27ly5duvDMM89w/vnnOy1uERGxjx25xXyWlsVXa7PJLTq2KUXXSH8uS47jj/1iidC/LVu+ssMNZ1Udn7iqOMUGJSZzbcKq028TVsHtjSWIzczpjkOUlGqkZTsPMuXtlcQG+7LsvnNdGouIiIg4XnMahzSGu8YtItKS1VhtLN15kM9Ss5i/OYeKaisAZhOc3TWcy5LjGNMjEh9P1S5uVWw2KDt08oRVZcnJX2uyQHD8cQmrTsdmWwW3A4un897HcU53HKLle42UpnpSIiIiIiIicgYsZhMjuoYzoms4hUer+H7DAT5PyyJ13xEWb89n8fZ8An08uDAphgkpcfSLD9byvtbAZII2YcbRbmDD52w2KM0/QcKqtp5VVamxU+CRvbBrUcPXmj2MxNRvElYdIagdWFyfEnJ9BG4mtXbnveR2wa4NRERERERERNxWkK8nVw5sx5UD27E7v4Qv0rL5Ii2L/YXlzFqZwayVGXQMa8NlKcbyvphgX1eHLK5gMoF/hHG0/5/NTmw2KM5pWLfq+IRV9dFjxdh3Lmj4WrMnXPkJdB7lvPdyAkpKNYLVamNtbZHzlPahrg1GREREREREWoSO4f7cPS6RaWO6smL3IT5PzWLOphx2Hyzl2XnbeW7+doZ2CmNCShzjekbh66XlfYKRsAqMNo6EoQ2fs1qNHQAbFFzffey8pgICol0T93GUlGqE3QdLKDxahY+nmW7RAa4OR0RERERERFoQs9nE0M5hDO0cxmOXVPPDxgN8nprFyj2HWbrzIEt3HsTf24Pze0cxISWeAQkhWt4nJ2Y2Q1CscXQ4u+FzVquxA2BAlGtiO475TF706quvkpCQgI+PDwMHDmTVqlUnvXfz5s1cdtllJCQkYDKZeOmll840VpdL21cAQFJcMJ6WM/rViYiIiIiIiPwuf28PJvWP55O/DObne87hjtFdiA/1paSimk/XZDHpjRWMeHYx/1y4g8zDZa4OV9yJ2WwUR3dREfQGoTT2BZ988gnTpk3j4YcfJi0tjaSkJMaNG0deXt4J7y8rK6Njx4489dRTREW5PgvXFKm1Rc6TVeRcREREREREnKRdWz/uGN2VJXefwyd/HsSk/nG08bKQcbiMFxemM/yZn7j8zRXMXpNJaUW1q8MVOW0mm81ma8wLBg4cyIABA5g5cyYAVquV+Ph4brvtNu67775TvjYhIYE77riDO+64o1FBNpctjce8sIQdeSW8fXV/RveIdFkcIiIi4jzNZRzSWO4at4iInJ6yymrmbc7hs9Qslu86RN2/7P28LJzXK4oJyXEM6tgWs1nL+8T5Tncc0qiaUpWVlaSmpjJ9+vT6a2azmdGjR7NixYozj9YNFJZVsSOvBIB+2nlPREREREREXMjPy4M/9ovjj/3iyC44yldrs/ksNYs9B0trd/LLJjbYl0uTY7ksOY6EsDauDlnkNxqVlDp48CA1NTVERjacJRQZGcm2bdvsFlRFRQUVFRX1PxcVFdmt7TO1NtNYutchrA1t/b1dHI2IiIiIiIiIITbYl6nndOaWkZ1Iyyjgs9Qsvtuwn+yCo7zy405e+XEn/duHcFlKHBf0iSbQx/W1hESgme6+N2PGDB599FFXh9FAWm09Kc2SEhERERERkebIZDKR0j6ElPYhPHxRDxZsyeWz1Cx+2ZHPmn1HWLPvCI98s5lxPaOYkBLH0M5hWLS8T1yoUUmpsLAwLBYLubm5Da7n5ubatYj59OnTmTZtWv3PRUVFxMfH2639M5GWUQBAioqci4iIiIiISDPn42nhoqQYLkqKIbeonC/XZvN5ahY78kr4Zv1+vlm/n6hAHy7pF8uElFg6RwS4OmRphRq1+56XlxcpKSksWrSo/prVamXRokUMHjzYbkF5e3sTGBjY4HClGquNtRm1O++1U1JKRERERERE3EdkoA9/HdGJ+XeezTe3DuXqwe0J9vMkp6ic15fsYvQLP3Pxq8v474q9FJRVujpcaUUavXxv2rRpXHPNNfTv35+zzjqLl156idLSUq677joArr76amJjY5kxYwZgFEffsmVL/Xl2djbr1q3D39+fzp072/GtOE56bjGllTX4e3vQNVLZYxEREREREXE/JpOJPnHB9IkL5oELuvPj1jw+T8vip+35rM8sYH1mAY9/t5XRPSKYkBLH2V3C8bA0ai6LSKM0Oik1efJk8vPzeeihh8jJyaFv377MnTu3vvh5RkYGZvOxP7T79++nX79+9T8/99xzPPfcc4wYMYLFixc3/R04QWptPam+8cFabysiIiIiIiJuz9vDwvje0YzvHU1+cQVfr8vm87Rsth4o4oeNOfywMYcwf28u6RvDhP5xdIty7QomaZlMNpvN5uogfk9RURFBQUEUFha6ZCnftE/X8UVaNn8b1YVpY7o6vX8RERFxHVePQ86Uu8YtIiKutXl/IZ+nZvP1umwOlR5bytczJpAJKXFc3DeW0DZeLoxQ3MHpjkOa5e57zU3dznvJ2nlPREREREREWrCeMUH0jAli+vndWLw9n89Ts1i0LZfN+4vYvH8LT3y/lXO7RXBZShznJEbg5aHlfXLmlJT6HYdKKth7qAyAfipyLiIiIiIiIq2Ap8XMmB6RjOkRyeHSSr5dv5/PUrPYmF3I/C25zN+SS2gbL87vHcWYHlEM6hiKt4fF1WGLm1FS6nekZRQA0CXCnyBfT9cGIyIiIiIiIuJkoW28uGZIAtcMSSA9t5jPU7P4Ym02+cUVfPBrBh/8moG/twcjuoYzpkck5yRGEOSnfz/L71NS6nekZRhL91Laa5aUiIiIiIiItG5dIwOYfn537hmXyNKdB5m3OZeFW3PJL67g+40H+H7jASxmE2clhNbPtIoP9XN12NJMKSn1O1Lr60kpKSUiIiIiIiIC4GExMzIxgpGJETxh7cWG7EIWbMlhwZZc0nNLWLH7ECt2H+Kx77bQLSqAMT0iGd09kt6xQZi1q73UUlLqFKpqrGzIKgAgWTOlRERERERERH7DbDbRNz6YvvHB3DOuG/sOlbJgizGDavXeI2zLKWZbTjGv/LiTyEBvRnePZHSPSIZ0aqs6VK2cklKnsPVAEeVVVoJ8PekY1sbV4YiIiIiIiIg0e+3btuHG4R25cXhHjpRW8tP2PBZuzWXJ9nxyiyr4cGUGH67MoI2XhRGJ4YzuHsm53SII9vNydejiZEpKnUJa/dK9YE0vFBEREREREWmkkDZeXJocx6XJcZRX1bBi9yEW1s6iyi2q4IeNOfywMQeL2UT/9iH1dajat9XEkNZASalTSK3deU/1pERERERERESaxsfTwjmJEZyTGMHjF/di0/5CFmzJZcGWXLblFLNyz2FW7jnM/32/la6R/vV1qJLiNFGkpVJS6hTqZ0qpnpSIiIiIiIiI3ZjNJvrEBdMnLpi7xiaSebisvg7Vyj2HSc8tIT23hFd/2kVEgDejukcypkcEQzqF4eOpOlQthZJSJ5FbVE52wVHMJkiKD3Z1OCIiIiIiIiItVnyoH9cP68D1wzpQWFbFT9vzWFBbhyqvuIKPVmXw0aoM/LwsDO8SxpgeUZzbLYLQNqpD5c6UlDqJullSiVGB+Hvr1yQiIiIiIiLiDEF+nlzSL5ZL+sVSUV3Dr7sP19ehOlBYzrzNuczbnIvZBP3bh9bXoUrQBmVuR9mWk0itTUqltA92bSAiIiIiIiIirZS3h4URXcMZ0TWcxy7uyeb9RcyvrUO19UARq/YeZtXewzzxw1Y6RxyrQ9UvXnWo3IGSUieRllG3857qSYmIiIiIiIi4mslkoldsEL1ig5g2pitZR8pqZ1Dl8evuQ+zMK2FnXgmvLd5FmL83o7tHMLp7JMO6qA5Vc6Wk1AlUVNewKbsIgBQVORcRERERERFpduJC/Lh2aAeuHdqBwqNVLN6ex8KteSzelsfBkgo+Xp3Jx6sz8fE0M7xLOGN6RDKqWwRt/b1dHbrUUlLqBDZlF1FZY6VtGy/ahfq5OhwREREREREROYUgX08u7hvLxX1jqay2snLPIRbWLvPbX1jOgtpzkwlS2oUYy/x6RNIp3N/VobdqSkqdQF2R8+T2IZhMWoMqIiIiIiIi4i68PIyZUcO7hPPIH3qy5UBRfVJq8/4i1uw7wpp9R5gxZxsdw9sYhdK7R9KvXQgW1aFyKiWlTkD1pERERERERETcn8lkomdMED1jgrhjdFf2Fxxl4VYjQfXr7kPszi/ljSW7eWPJbtq28eLcbhGM6RHJ8C7h+HqpDpWjKSn1P2w223E77ykpJSIiIiIiItJSxAT7cvXgBK4enEBReRVLtuezcGsuP27L41BpJbNTs5idmoW3h5lhncMYkWjs/Ne+bRtXh94iKSn1P7ILjpJXXIGH2USfuCBXhyMiIiIiIiIiDhDo48lFSTFclBRDVY2VVXsO1y/zyy44yqJteSzalgdAQls/zu5qJKgGdWxLG2+lU+xBv8X/UTdLqmdMoLaMFBEREREREWkFPC1mhnYOY2jnMB6+qAdbDxSzOD2Pn9PzWbP3CHsPlbF3xT7+s2IfXhYz/RNCGNE1nBGJ4SRGBqge9RlSUup/rM0oAKCf6kmJiIiIiIiItDomk4keMYH0iAnklpGdKS6vYsWuQyxJz2dJej5ZR46yfNchlu86xIw524gM9ObsLkaCaljnMIL9vFz9FtyGklL/Q/WkRERERERERKROgI8nY3tGMbZnFDabjT0HS1mSns/P6fms2H2I3KKK+lpUZhMkxQczoms4Z3cNJykuWDv6nYKSUscpq6xmy4EiAJKVlBIRERERERGR45hMJjqG+9Mx3J/rhnagvKqG1XsPs2R7Pj/vyCc9t4S1GQWszSjgpYU7CPbzNAqm1yapIgN9XP0WmhUlpY6zIauQGquNqEAfYoL0B0VERERERERETs7H08LwLuEM7xIOwP6Co/ycbiSoftlxkIKyKr7bcIDvNhwAoFtUgLGjX5dwUhJC8PZo3bWslZQ6TlqGsXQvuX2wipSJiIiIiIiISKPEBPty+VntuPysdlTXWFmXWcDPtbWoNmQXsi2nmG05xbyxZDd+XhaGdGpbv6tf+7ZtXB2+0ykpdZy02npSySpyLiIiIiIiIiJN4GEx0z8hlP4JoUwbm8ihkgqW7jxYW4/qIAdLKli4NY+FW/MASGjrV7/Mb3Cntvh5tfyUTct/h6fJZrORVrvznupJiYiIiIiIiIg9tfX35uK+sVzcNxar1caWA0X8vCOfJdvzSd13hL2Hyti7Yh//XrEPL4uZAR1C6nf1S4wMaJErupSUqrX3UBmHSyvx8jDTMybQ1eGIiIiIiIiISAtlNpvoFRtEr9ggbhnZmeLyKlbsOsSS2qV+WUeOsmznIZbtPMSMOduIDPSun0U1rHMYwX5ern4LdqGkVK26pXu9Y4NafaExEREREREREXGeAB9PxvaMYmzPKGw2G7sPltbXovp19yFyiyr4dE0Wn67JwmyCvvHB9bWo+sQFYzG75ywqJaVqpdYWOU/R0j0RERERERERcRGTyUSncH86hftz3dAOlFfVsHrvYZZsN5JUO/JKSMsoIC2jgJcW7iDYz5NhncMYUZukigj0cfVbOG1KStU6VuQ82LWBiIiIiIiIiIjU8vG0MLxLOMO7hPMPYH/B0fpZVEt3HqSgrIrvNhzguw0HAOgeHcjZXY0kVf/2oXh5mF37Bk5BSSmguLyK7bnFgHbeExEREREREZHmKybYl8vPasflZ7WjusbKusyC+lpUG7ML2XqgiK0HinhjyW78vCwM6dS2dhZVBO3a+rk6/AaUlALWZxZis0FciK9bTXMTERERERERkdbLw2Kmf0Io/RNCuWtsIodKKli68yBLtufz8458DpZUsnBrHgu35gGbSWjrZySoEsMZ1LEtfl6uTQspKQWk7lM9KRERERERERFxb239vbm4bywX943FarWx5UBR/SyqtH1H2HuojL0r9vHvFft4bUoy43tHuzReJaWA6GAfBiSEMKhjW1eHIiIiIiIiIiLSZGaziV6xQfSKDWLqOZ0pLq9i+a5DLEnPZ9nOgwzpHObqEJWUApjUP55J/eNdHYaIiIiIiIiIiEME+HgyrmcU43pGuTqUes23BLuIiIiIiIiIiLRYSkqJiIiIiIiIiIjTKSklIiIiIiIiIiJOp6SUiIiIiIiIiIg4nZJSIiIiIiIiIiLidEpKiYiIiIiIiIiI0ykpJSIiIiIiIiIiTqeklIiIiIiIiIiIOJ2SUiIiIiIiIiIi4nRKSomIiIiIiIiIiNMpKSUiIiIiIiIiIk6npJSIiIiIiIiIiDidklIiIiIiIiIiIuJ0SkqJiIiIiIiIiIjTKSklIiIiIiIiIiJOp6SUiIiIiIiIiIg4nZJSIiIiIiIiIiLidEpKiYiIiIiIiIiI0ykpJSIiIiIiIiIiTqeklIiIiIiIiIiIOJ2SUiIiIiIiIiIi4nRKSomIiIiIiIiIiNMpKSUiIiIiIiIiIk6npJSIiIiIiIiIiDidklIiIiIiIiIiIuJ0SkqJiIiIiIiIiIjTKSklIiIiIiIiIiJOp6SUiIiIiIiIiIg4nZJSIiIiIiIiIiLidB6uDuB02Gw2AIqKilwciYiIiLQ2deOPuvGIu9D4SURERFzldMdPbpGUKi4uBiA+Pt7FkYiIiEhrVVxcTFBQkKvDOG0aP4mIiIir/d74yWRzg6/9rFYr+/fvJyAgAJPJ5JA+ioqKiI+PJzMzk8DAQIf0Ifanz8096XNzT/rc3Jc+u6ax2WwUFxcTExOD2ew+lQ80fpKT0efmvvTZuSd9bu5Jn1vTnO74yS1mSpnNZuLi4pzSV2BgoP7AuSF9bu5Jn5t70ufmvvTZnTl3miFVR+Mn+T363NyXPjv3pM/NPelzO3OnM35yn6/7RERERERERESkxVBSSkREREREREREnE5JqVre3t48/PDDeHt7uzoUaQR9bu5Jn5t70ufmvvTZiaPoz5Z70ufmvvTZuSd9bu5Jn5tzuEWhcxERERERERERaVk0U0pERERERERERJxOSSkREREREREREXE6JaVERERERERERMTplJQCXn31VRISEvDx8WHgwIGsWrXK1SHJKcyYMYMBAwYQEBBAREQEl1xyCdu3b3d1WNJITz31FCaTiTvuuMPVochpyM7O5qqrrqJt27b4+vrSu3dv1qxZ4+qw5BRqamp48MEH6dChA76+vnTq1InHH38clZIUe9H4yf1oDNUyaAzlPjR+ck8aQzlXq09KffLJJ0ybNo2HH36YtLQ0kpKSGDduHHl5ea4OTU5iyZIlTJ06lV9//ZUFCxZQVVXF2LFjKS0tdXVocppWr17NG2+8QZ8+fVwdipyGI0eOMHToUDw9PZkzZw5btmzh+eefJyQkxNWhySk8/fTTvPbaa8ycOZOtW7fy9NNP88wzz/DKK6+4OjRpATR+ck8aQ7k/jaHch8ZP7ktjKOdq9bvvDRw4kAEDBjBz5kwArFYr8fHx3Hbbbdx3330ujk5OR35+PhERESxZsoSzzz7b1eHI7ygpKSE5OZl//etf/N///R99+/blpZdecnVYcgr33Xcfy5Yt45dffnF1KNIIF154IZGRkbzzzjv11y677DJ8fX354IMPXBiZtAQaP7UMGkO5F42h3IvGT+5LYyjnatUzpSorK0lNTWX06NH118xmM6NHj2bFihUujEwao7CwEIDQ0FAXRyKnY+rUqVxwwQUN/ruT5u2bb76hf//+TJw4kYiICPr168dbb73l6rDkdwwZMoRFixaRnp4OwPr161m6dCnjx493cWTi7jR+ajk0hnIvGkO5F42f3JfGUM7l4eoAXOngwYPU1NQQGRnZ4HpkZCTbtm1zUVTSGFarlTvuuIOhQ4fSq1cvV4cjv+Pjjz8mLS2N1atXuzoUaYTdu3fz2muvMW3aNO6//35Wr17N3/72N7y8vLjmmmtcHZ6cxH333UdRURHdunXDYrFQU1PDE088wZQpU1wdmrg5jZ9aBo2h3IvGUO5H4yf3pTGUc7XqpJS4v6lTp7Jp0yaWLl3q6lDkd2RmZnL77bezYMECfHx8XB2ONILVaqV///48+eSTAPTr149Nmzbx+uuva1DVjH366ad8+OGHzJo1i549e7Ju3TruuOMOYmJi9LmJiMZQbkRjKPek8ZP70hjKuVp1UiosLAyLxUJubm6D67m5uURFRbkoKjldt956K9999x0///wzcXFxrg5Hfkdqaip5eXkkJyfXX6upqeHnn39m5syZVFRUYLFYXBihnEx0dDQ9evRocK179+58/vnnLopITsc999zDfffdx+WXXw5A79692bdvHzNmzNCASppE4yf3pzGUe9EYyj1p/OS+NIZyrlZdU8rLy4uUlBQWLVpUf81qtbJo0SIGDx7swsjkVGw2G7feeitffvklP/74Ix06dHB1SHIaRo0axcaNG1m3bl390b9/f6ZMmcK6des0mGrGhg4d+pstw9PT02nfvr2LIpLTUVZWhtnc8K95i8WC1Wp1UUTSUmj85L40hnJPGkO5J42f3JfGUM7VqmdKAUybNo1rrrmG/v37c9ZZZ/HSSy9RWlrKdddd5+rQ5CSmTp3KrFmz+PrrrwkICCAnJweAoKAgfH19XRydnExAQMBvala0adOGtm3bqpZFM3fnnXcyZMgQnnzySSZNmsSqVat48803efPNN10dmpzCRRddxBNPPEG7du3o2bMna9eu5YUXXuD66693dWjSAmj85J40hnJPGkO5J42f3JfGUM5lstlsNlcH4WozZ87k2WefJScnh759+/Lyyy8zcOBAV4clJ2EymU54/b333uPaa691bjDSJCNHjtR2xm7iu+++Y/r06ezYsYMOHTowbdo0brrpJleHJadQXFzMgw8+yJdffkleXh4xMTFcccUVPPTQQ3h5ebk6PGkBNH5yPxpDtRwaQ7kHjZ/ck8ZQzqWklIiIiIiIiIiIOF2rriklIiIiIiIiIiKuoaSUiIiIiIiIiIg4nZJSIiIiIiIiIiLidEpKiYiIiIiIiIiI0ykpJSIiIiIiIiIiTqeklIiIiIiIiIiIOJ2SUiIiIiIiIiIi4nRKSomIiIiIiIiIiNMpKSUicgKLFy/GZDJRUFDg6lBERERE3IbGUCLSGEpKiYiIiIiIiIiI0ykpJSIiIiIiIiIiTqeklIg0S1arlRkzZtChQwd8fX1JSkris88+A45NC//+++/p06cPPj4+DBo0iE2bNjVo4/PPP6dnz554e3uTkJDA888/3+D5iooK/v73vxMfH4+3tzedO3fmnXfeaXBPamoq/fv3x8/PjyFDhrB9+3bHvnERERGRJtAYSkTciZJSItIszZgxg//85z+8/vrrbN68mTvvvJOrrrqKJUuW1N9zzz338Pzzz7N69WrCw8O56KKLqKqqAoyB0KRJk7j88svZuHEjjzzyCA8++CDvv/9+/euvvvpqPvroI15++WW2bt3KG2+8gb+/f4M4HnjgAZ5//nnWrFmDh4cH119/vVPev4iIiMiZ0BhKRNyJyWaz2VwdhIjI8SoqKggNDWXhwoUMHjy4/vqNN95IWVkZf/7znznnnHP4+OOPmTx5MgCHDx8mLi6O999/n0mTJjFlyhTy8/OZP39+/evvvfdevv/+ezZv3kx6ejqJiYksWLCA0aNH/yaGxYsXc84557Bw4UJGjRoFwA8//MAFF1zA0aNH8fHxcfBvQURERKRxNIYSEXejmVIi0uzs3LmTsrIyxowZg7+/f/3xn//8h127dtXfd/xgKzQ0lMTERLZu3QrA1q1bGTp0aIN2hw4dyo4dO6ipqWHdunVYLBZGjBhxylj69OlTfx4dHQ1AXl5ek9+jiIiIiL1pDCUi7sbD1QGIiPyvkpISAL7//ntiY2MbPOft7d1gUHWmfH19T+s+T0/P+nOTyQQYtRpEREREmhuNoUTE3WimlIg0Oz169MDb25uMjAw6d+7c4IiPj6+/79dff60/P3LkCOnp6XTv3h2A7t27s2zZsgbtLlu2jK5du2KxWOjduzdWq7VBfQURERERd6YxlIi4G82UEpFmJyAggLvvvps777wTq9XKsGHDKCwsZNmyZQQGBtK+fXsAHnvsMdq2bUtkZCQPPPAAYWFhXHLJJQDcddddDBgwgMcff5zJkyezYsUKZs6cyb/+9S8AEhISuOaaa7j++ut5+eWXSUpKYt++feTl5TFp0iRXvXURERGRM6YxlIi4GyWlRKRZevzxxwkPD2fGjBns3r2b4OBgkpOTuf/+++unfj/11FPcfvvt7Nixg759+/Ltt9/i5eUFQHJyMp9++ikPPfQQjz/+ONHR0Tz22GNce+219X289tpr3H///dxyyy0cOnSIdu3acf/997vi7YqIiIjYhcZQIuJOtPueiLidul1djhw5QnBwsKvDEREREXELGkOJSHOjmlIiIiIiIiIiIuJ0SkqJiIiIiIiIiIjTafmeiIiIiIiIiIg4nWZKiYiIiIiIiIiI0ykpJSIiIiIiIiIiTqeklIiIiIiIiIiIOJ2SUiIiIiIiIiIi4nRKSomIiIiIiIiIiNMpKSUiIiIiIiIiIk6npJSIiIiIiIiIiDidklIiIiIiIiIiIuJ0SkqJiIiIiIiIiIjT/T9Pu5Nd5TrchgAAAABJRU5ErkJggg==\"\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"accuracy\\n\",\n      \"\\ttraining         \\t (min:    0.068, max:    0.575, cur:    0.575)\\n\",\n      \"\\tvalidation       \\t (min:    0.172, max:    0.517, cur:    0.517)\\n\",\n      \"log loss\\n\",\n      \"\\ttraining         \\t (min:    1.719, max:    4.949, cur:    1.719)\\n\",\n      \"\\tvalidation       \\t (min:    1.959, max:    4.183, cur:    1.959)\\n\",\n      \"Training complete in 6m 10s\\n\",\n      \"Best Validation Accuracy: 0.5171999931335449, Epoch: 10\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"text/plain\": \"10\"\n     },\n     \"execution_count\": 13,\n     \"metadata\": {},\n     \"output_type\": \"execute_result\"\n    }\n   ],\n   \"source\": [\n    \"# Train\\n\",\n    \"train_model(\\n\",\n    \"    output_path=\\\"ResNet18_64_pretrained_normalized_flipped\\\",\\n\",\n    \"    model=model_ft,\\n\",\n    \"    dataloaders=dataloaders,\\n\",\n    \"    criterion=criterion,\\n\",\n    \"    optimizer=optimizer_ft,\\n\",\n    \"    device=device,\\n\",\n    \"    num_epochs=10,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 14,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T20:12:02.177554Z\",\n     \"start_time\": \"2023-12-01T20:12:02.024327Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Normalized & Rotated Dataset\\n\",\n    \"data_transforms = {\\n\",\n    \"    \\\"train\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.RandomRotation(20),\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"val\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"test\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"}\\n\",\n    \"image_datasets = {\\n\",\n    \"    x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x]) for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\\n\",\n    \"dataloaders = {\\n\",\n    \"    x: data.DataLoader(image_datasets[x], batch_size=500, shuffle=True, num_workers=num_workers[x])\\n\",\n    \"    for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 15,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T20:12:02.370357Z\",\n     \"start_time\": \"2023-12-01T20:12:02.179664Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Load Resnet18\\n\",\n    \"model_ft = models.resnet18(weights=\\\"IMAGENET1K_V1\\\")\\n\",\n    \"# Finetune Final few layers to adjust for tiny imagenet input\\n\",\n    \"model_ft.avgpool = nn.AdaptiveAvgPool2d(1)\\n\",\n    \"num_features = model_ft.fc.in_features\\n\",\n    \"model_ft.fc = nn.Linear(num_features, 200)\\n\",\n    \"model_ft = model_ft.to(device)\\n\",\n    \"# Loss Function\\n\",\n    \"criterion = nn.CrossEntropyLoss()\\n\",\n    \"# Observe that all parameters are being optimized\\n\",\n    \"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 16,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"text/plain\": \"<Figure size 1200x800 with 2 Axes>\",\n      \"image/png\": 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\"\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"accuracy\\n\",\n      \"\\ttraining         \\t (min:    0.046, max:    0.502, cur:    0.502)\\n\",\n      \"\\tvalidation       \\t (min:    0.117, max:    0.496, cur:    0.496)\\n\",\n      \"log loss\\n\",\n      \"\\ttraining         \\t (min:    2.044, max:    5.112, cur:    2.044)\\n\",\n      \"\\tvalidation       \\t (min:    2.071, max:    4.499, cur:    2.071)\\n\",\n      \"Training complete in 6m 22s\\n\",\n      \"Best Validation Accuracy: 0.4957999885082245, Epoch: 10\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"text/plain\": \"10\"\n     },\n     \"execution_count\": 16,\n     \"metadata\": {},\n     \"output_type\": \"execute_result\"\n    }\n   ],\n   \"source\": [\n    \"train_model(\\n\",\n    \"    output_path=\\\"ResNet18_64_pretrained_normalized_rotated\\\",\\n\",\n    \"    model=model_ft,\\n\",\n    \"    dataloaders=dataloaders,\\n\",\n    \"    criterion=criterion,\\n\",\n    \"    optimizer=optimizer_ft,\\n\",\n    \"    device=device,\\n\",\n    \"    num_epochs=10,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 17,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T20:18:25.010395Z\",\n     \"start_time\": \"2023-12-01T20:18:24.617172Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Normalized & Rotated & Flipped Dataset\\n\",\n    \"data_transforms = {\\n\",\n    \"    \\\"train\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.RandomRotation(20),\\n\",\n    \"            transforms.RandomHorizontalFlip(0.5),\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"val\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"test\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"}\\n\",\n    \"image_datasets = {\\n\",\n    \"    x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x]) for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\\n\",\n    \"dataloaders = {\\n\",\n    \"    x: data.DataLoader(image_datasets[x], batch_size=500, shuffle=True, num_workers=num_workers[x])\\n\",\n    \"    for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 18,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T20:18:25.225847Z\",\n     \"start_time\": \"2023-12-01T20:18:25.016778Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"# Load Resnet18\\n\",\n    \"model_ft = models.resnet18(weights=\\\"IMAGENET1K_V1\\\")\\n\",\n    \"# Finetune Final few layers to adjust for tiny imagenet input\\n\",\n    \"model_ft.avgpool = nn.AdaptiveAvgPool2d(1)\\n\",\n    \"num_features = model_ft.fc.in_features\\n\",\n    \"model_ft.fc = nn.Linear(num_features, 200)\\n\",\n    \"model_ft = model_ft.to(device)\\n\",\n    \"# Loss Function\\n\",\n    \"criterion = nn.CrossEntropyLoss()\\n\",\n    \"# Observe that all parameters are being optimized\\n\",\n    \"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 19,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"text/plain\": \"<Figure size 1200x800 with 2 Axes>\",\n      \"image/png\": 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\"\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"accuracy\\n\",\n      \"\\ttraining         \\t (min:    0.050, max:    0.493, cur:    0.493)\\n\",\n      \"\\tvalidation       \\t (min:    0.124, max:    0.501, cur:    0.501)\\n\",\n      \"log loss\\n\",\n      \"\\ttraining         \\t (min:    2.081, max:    5.072, cur:    2.081)\\n\",\n      \"\\tvalidation       \\t (min:    2.045, max:    4.445, cur:    2.045)\\n\",\n      \"Training complete in 6m 12s\\n\",\n      \"Best Validation Accuracy: 0.5012000203132629, Epoch: 10\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Train\\n\",\n    \"best_epoch = train_model(\\n\",\n    \"    output_path=\\\"ResNet18_64_pretrained_normalized_flipped_rotated\\\",\\n\",\n    \"    model=model_ft,\\n\",\n    \"    dataloaders=dataloaders,\\n\",\n    \"    criterion=criterion,\\n\",\n    \"    optimizer=optimizer_ft,\\n\",\n    \"    device=device,\\n\",\n    \"    num_epochs=10,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 21,\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"Iteration: 10/10, Loss: 1019.2914009094238.Test Loss: 2.0974 Acc: 0.4980\\n\",\n      \"Test complete in 0m 2s\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Test\\n\",\n    \"model_ft.load_state_dict(\\n\",\n    \"    torch.load(f\\\"models/ResNet18_64_pretrained_normalized_flipped_rotated/model_{best_epoch}_epoch.pt\\\")\\n\",\n    \")\\n\",\n    \"test_model(model=model_ft, dataloaders=dataloaders, criterion=criterion, device=device)\"\n   ],\n   \"metadata\": {\n    \"collapsed\": false,\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-01T20:26:09.204421Z\",\n     \"start_time\": \"2023-12-01T20:26:07.401797Z\"\n    }\n   }\n  }\n ],\n \"metadata\": {\n  \"kernelspec\": {\n   \"name\": \"python3\",\n   \"language\": \"python\",\n   \"display_name\": \"Python 3 (ipykernel)\"\n  },\n  \"language_info\": {\n   \"codemirror_mode\": {\n    \"name\": \"ipython\",\n    \"version\": 3\n   },\n   \"file_extension\": \".py\",\n   \"mimetype\": \"text/x-python\",\n   \"name\": \"python\",\n   \"nbconvert_exporter\": \"python\",\n   \"pygments_lexer\": \"ipython3\",\n   \"version\": \"3.6.5\"\n  }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 2\n}\n"
  },
  {
    "path": "notebook/ResNet18_FineTune.ipynb",
    "content": "{\n \"cells\": [\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 51,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-02T10:27:04.971887Z\",\n     \"start_time\": \"2023-12-02T10:27:04.962248Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"import os\\n\",\n    \"\\n\",\n    \"import torch\\n\",\n    \"import torch.nn as nn\\n\",\n    \"import torch.optim as optim\\n\",\n    \"import torch.utils.data as data\\n\",\n    \"import torchvision.datasets as datasets\\n\",\n    \"import torchvision.models as models\\n\",\n    \"import torchvision.transforms as transforms\\n\",\n    \"\\n\",\n    \"from src.test_model import test_model\\n\",\n    \"from src.train_model import train_model\\n\",\n    \"\\n\",\n    \"%matplotlib inline\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 52,\n   \"outputs\": [],\n   \"source\": [\n    \"if torch.cuda.is_available():\\n\",\n    \"    device = \\\"cuda:0\\\"\\n\",\n    \"elif torch.backends.mps.is_built():\\n\",\n    \"    device = torch.device(\\\"mps\\\")\\n\",\n    \"else:\\n\",\n    \"    device = \\\"cpu\\\"\"\n   ],\n   \"metadata\": {\n    \"collapsed\": false,\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-02T10:27:12.588753Z\",\n     \"start_time\": \"2023-12-02T10:27:12.586014Z\"\n    }\n   }\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 53,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-02T10:27:12.794915Z\",\n     \"start_time\": \"2023-12-02T10:27:12.589798Z\"\n    }\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"data_dir = \\\"../tiny-imagenet-200/\\\"\\n\",\n    \"num_workers = {\\\"train\\\": 2, \\\"val\\\": 0, \\\"test\\\": 0}\\n\",\n    \"data_transforms = {\\n\",\n    \"    \\\"train\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.RandomRotation(20),\\n\",\n    \"            transforms.RandomHorizontalFlip(0.5),\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"val\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"    \\\"test\\\": transforms.Compose(\\n\",\n    \"        [\\n\",\n    \"            transforms.ToTensor(),\\n\",\n    \"            transforms.Normalize([0.4802, 0.4481, 0.3975], [0.2302, 0.2265, 0.2262]),\\n\",\n    \"        ]\\n\",\n    \"    ),\\n\",\n    \"}\\n\",\n    \"image_datasets = {\\n\",\n    \"    x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x]) for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\\n\",\n    \"dataloaders = {\\n\",\n    \"    x: data.DataLoader(image_datasets[x], batch_size=100, shuffle=True, num_workers=num_workers[x])\\n\",\n    \"    for x in [\\\"train\\\", \\\"val\\\", \\\"test\\\"]\\n\",\n    \"}\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 54,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-02T10:27:12.998747Z\",\n     \"start_time\": \"2023-12-02T10:27:12.797426Z\"\n    }\n   },\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"Skipping conv1.weight due to size mismatch\\n\",\n      \"New Model Size: torch.Size([64, 3, 3, 3])\\n\",\n      \"Pretrained Model Size: torch.Size([64, 3, 7, 7])\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Load Resnet18\\n\",\n    \"torch.manual_seed(42)\\n\",\n    \"model_ft = models.resnet18()\\n\",\n    \"\\n\",\n    \"# Finetune first few layers to adjust for tiny imagenet input (64, 3, 7, 7) -> (64, 3, 3, 3)\\n\",\n    \"model_ft.conv1 = nn.Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\\n\",\n    \"model_ft.maxpool = nn.Sequential()\\n\",\n    \"model_ft.avgpool = nn.AdaptiveAvgPool2d(1)\\n\",\n    \"num_features = model_ft.fc.in_features\\n\",\n    \"model_ft.fc = nn.Linear(num_features, 200)\\n\",\n    \"model_ft = model_ft.to(device)\\n\",\n    \"\\n\",\n    \"# Get resized model_ft weights\\n\",\n    \"model_ft_dict = model_ft.state_dict()\\n\",\n    \"\\n\",\n    \"# Load pretrained weights from 224x224 ResNet18\\n\",\n    \"pretrained_dict = torch.load(\\\"./models/RestNet18_224/model_10_epoch.pt\\\")\\n\",\n    \"\\n\",\n    \"# Update model_ft weights with pretrained model weights if size matches\\n\",\n    \"for new_model, pt_model in zip(model_ft_dict.items(), pretrained_dict.items()):\\n\",\n    \"    new_model_layer, new_model_weights = new_model[0], new_model[1]\\n\",\n    \"    pt_model_layer, pt_model_weights = pt_model[0], pt_model[1]\\n\",\n    \"    if new_model_layer == pt_model_layer:\\n\",\n    \"        # If size matches, update model_ft weights with pretrained model weights\\n\",\n    \"        if new_model_weights.size() == pt_model_weights.size():\\n\",\n    \"            model_ft_dict[new_model_layer] = pt_model_weights\\n\",\n    \"        else:\\n\",\n    \"            print(f\\\"Skipping {new_model_layer} due to size mismatch\\\")\\n\",\n    \"            print(f\\\"New Model Size: {new_model_weights.size()}\\\")\\n\",\n    \"            print(f\\\"Pretrained Model Size: {pt_model_weights.size()}\\\")\\n\",\n    \"    else:\\n\",\n    \"        print(f\\\"Skipping {new_model_layer} due to layer mismatch\\\")\\n\",\n    \"        print(f\\\"New Model Layer: {new_model_layer}\\\")\\n\",\n    \"        print(f\\\"Pretrained Model Layer: {pt_model_layer}\\\")\\n\",\n    \"\\n\",\n    \"# Update model_ft weights with matched pretrained model weights\\n\",\n    \"model_ft.load_state_dict(model_ft_dict)\\n\",\n    \"\\n\",\n    \"# Loss Function\\n\",\n    \"criterion = nn.CrossEntropyLoss()\\n\",\n    \"# Observe that all parameters are being optimized\\n\",\n    \"optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 55,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"text/plain\": \"<Figure size 1200x800 with 2 Axes>\",\n      \"image/png\": 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    },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"accuracy\\n\",\n      \"\\ttraining         \\t (min:    0.599, max:    0.895, cur:    0.895)\\n\",\n      \"\\tvalidation       \\t (min:    0.668, max:    0.729, cur:    0.721)\\n\",\n      \"log loss\\n\",\n      \"\\ttraining         \\t (min:    0.409, max:    1.609, cur:    0.409)\\n\",\n      \"\\tvalidation       \\t (min:    1.054, max:    1.275, cur:    1.103)\\n\",\n      \"Training complete in 121m 9s\\n\",\n      \"Best Validation Accuracy: 0.7289999723434448, Epoch: 17\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Train\\n\",\n    \"best_epoch = train_model(\\n\",\n    \"    output_path=\\\"ResNet18_FineTune\\\",\\n\",\n    \"    model=model_ft,\\n\",\n    \"    dataloaders=dataloaders,\\n\",\n    \"    criterion=criterion,\\n\",\n    \"    optimizer=optimizer_ft,\\n\",\n    \"    device=device,\\n\",\n    \"    num_epochs=20,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 56,\n   \"metadata\": {\n    \"ExecuteTime\": {\n     \"end_time\": \"2023-12-02T12:30:02.310734Z\",\n     \"start_time\": \"2023-12-02T12:29:57.720362Z\"\n    }\n   },\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"Test Loss: 1.0853 Acc: 0.7192\\n\",\n      \"Test complete in 0m 4s\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Test\\n\",\n    \"model_ft.load_state_dict(torch.load(f\\\"models/ResNet18_FineTune/model_{best_epoch}_epoch.pt\\\"))\\n\",\n    \"test_model(model=model_ft, dataloaders=dataloaders, criterion=criterion, device=device)\"\n   ]\n  }\n ],\n \"metadata\": {\n  \"kernelspec\": {\n   \"display_name\": \"Python 3\",\n   \"language\": \"python\",\n   \"name\": \"python3\"\n  },\n  \"language_info\": {\n   \"codemirror_mode\": {\n    \"name\": \"ipython\",\n    \"version\": 3\n   },\n   \"file_extension\": \".py\",\n   \"mimetype\": \"text/x-python\",\n   \"name\": \"python\",\n   \"nbconvert_exporter\": \"python\",\n   \"pygments_lexer\": \"ipython3\",\n   \"version\": \"3.6.5\"\n  }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 2\n}\n"
  },
  {
    "path": "pyproject.toml",
    "content": "[tool.ruff]\nline-length = 119\n\n[project]\nname = \"pytorch-tiny-imagenet\"\nversion = \"0.2.0\"\ndescription = \"\"\nreadme = \"README.md\"\nrequires-python = \">=3.11\"\nauthors = [\n    {name = \"Taejun Moon\", email = \"tjmoon0104@outlook.com\"},\n]\ndependencies = [\n    \"opencv-python>=4.8.1.78,<5.0.0\",\n    \"torch>=2.8.0,<3.0.0\",\n    \"torchvision>=0.16.1,<1.0.0\",\n    \"livelossplot>=0.5.5,<1.0.0\",\n    \"ruff>=0.13.0\",\n]\n\n[dependency-groups]\ndev = [\n    \"ruff>=0.13.0\",\n    \"tqdm>=4.66.1,<5.0.0\",\n    \"notebook>=7.4.5,<8.0.0\",\n]\n"
  },
  {
    "path": "requirements.txt",
    "content": "# This file was autogenerated by uv via the following command:\n#    uv export --no-hashes --format requirements-txt\nanyio==4.10.0\n    # via\n    #   httpx\n    #   jupyter-server\nappnope==0.1.4 ; sys_platform == 'darwin'\n    # via ipykernel\nargon2-cffi==25.1.0\n    # via jupyter-server\nargon2-cffi-bindings==25.1.0\n    # via argon2-cffi\narrow==1.3.0\n    # via isoduration\nasttokens==3.0.0\n    # via stack-data\nasync-lru==2.0.5\n    # via jupyterlab\nattrs==25.3.0\n    # via\n    #   jsonschema\n    #   referencing\nbabel==2.17.0\n    # via jupyterlab-server\nbeautifulsoup4==4.13.5\n    # via nbconvert\nbleach==6.2.0\n    # via nbconvert\nbokeh==3.8.0\n    # via livelossplot\ncertifi==2025.8.3\n    # via\n    #   httpcore\n    #   httpx\n    #   requests\ncffi==2.0.0\n    # via\n    #   argon2-cffi-bindings\n    #   pyzmq\ncharset-normalizer==3.4.3\n    # via requests\ncolorama==0.4.6 ; sys_platform == 'win32'\n    # via\n    #   ipython\n    #   tqdm\ncomm==0.2.3\n    # via ipykernel\ncontourpy==1.3.3\n    # via\n    #   bokeh\n    #   matplotlib\ncycler==0.12.1\n    # via matplotlib\ndebugpy==1.8.16\n    # via ipykernel\ndecorator==5.2.1\n    # via ipython\ndefusedxml==0.7.1\n    # via nbconvert\nexecuting==2.2.1\n    # via stack-data\nfastjsonschema==2.21.2\n    # via nbformat\nfilelock==3.19.1\n    # via torch\nfonttools==4.59.2\n    # via matplotlib\nfqdn==1.5.1\n    # via jsonschema\nfsspec==2025.9.0\n    # via torch\nh11==0.16.0\n    # via httpcore\nhttpcore==1.0.9\n    # via httpx\nhttpx==0.28.1\n    # via jupyterlab\nidna==3.10\n    # via\n    #   anyio\n    #   httpx\n    #   jsonschema\n    #   requests\nipykernel==6.30.1\n    # via jupyterlab\nipython==9.5.0\n    # via ipykernel\nipython-pygments-lexers==1.1.1\n    # via ipython\nisoduration==20.11.0\n    # via jsonschema\njedi==0.19.2\n    # via ipython\njinja2==3.1.6\n    # via\n    #   bokeh\n    #   jupyter-server\n    #   jupyterlab\n    #   jupyterlab-server\n    #   nbconvert\n    #   torch\njson5==0.12.1\n    # via jupyterlab-server\njsonpointer==3.0.0\n    # via jsonschema\njsonschema==4.25.1\n    # via\n    #   jupyter-events\n    #   jupyterlab-server\n    #   nbformat\njsonschema-specifications==2025.9.1\n    # via jsonschema\njupyter-client==8.6.3\n    # via\n    #   ipykernel\n    #   jupyter-server\n    #   nbclient\njupyter-core==5.8.1\n    # via\n    #   ipykernel\n    #   jupyter-client\n    #   jupyter-server\n    #   jupyterlab\n    #   nbclient\n    #   nbconvert\n    #   nbformat\njupyter-events==0.12.0\n    # via jupyter-server\njupyter-lsp==2.3.0\n    # via jupyterlab\njupyter-server==2.17.0\n    # via\n    #   jupyter-lsp\n    #   jupyterlab\n    #   jupyterlab-server\n    #   notebook\n    #   notebook-shim\njupyter-server-terminals==0.5.3\n    # via jupyter-server\njupyterlab==4.4.7\n    # via notebook\njupyterlab-pygments==0.3.0\n    # via nbconvert\njupyterlab-server==2.27.3\n    # via\n    #   jupyterlab\n    #   notebook\nkiwisolver==1.4.9\n    # via matplotlib\nlark==1.2.2\n    # via rfc3987-syntax\nlivelossplot==0.5.6\n    # via pytorch-tiny-imagenet\nmarkupsafe==3.0.2\n    # via\n    #   jinja2\n    #   nbconvert\nmatplotlib==3.10.6\n    # via livelossplot\nmatplotlib-inline==0.1.7\n    # via\n    #   ipykernel\n    #   ipython\nmistune==3.1.4\n    # via nbconvert\nmpmath==1.3.0\n    # via sympy\nnarwhals==2.5.0\n    # via bokeh\nnbclient==0.10.2\n    # via nbconvert\nnbconvert==7.16.6\n    # via jupyter-server\nnbformat==5.10.4\n    # via\n    #   jupyter-server\n    #   nbclient\n    #   nbconvert\nnest-asyncio==1.6.0\n    # via ipykernel\nnetworkx==3.5\n    # via torch\nnotebook==7.4.5\nnotebook-shim==0.2.4\n    # via\n    #   jupyterlab\n    #   notebook\nnumpy==2.2.6\n    # via\n    #   bokeh\n    #   contourpy\n    #   matplotlib\n    #   opencv-python\n    #   pandas\n    #   torchvision\nnvidia-cublas-cu12==12.8.4.1 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via\n    #   nvidia-cudnn-cu12\n    #   nvidia-cusolver-cu12\n    #   torch\nnvidia-cuda-cupti-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nnvidia-cuda-nvrtc-cu12==12.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nnvidia-cuda-runtime-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nnvidia-cudnn-cu12==9.10.2.21 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nnvidia-cufft-cu12==11.3.3.83 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nnvidia-cufile-cu12==1.13.1.3 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nnvidia-curand-cu12==10.3.9.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nnvidia-cusolver-cu12==11.7.3.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nnvidia-cusparse-cu12==12.5.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via\n    #   nvidia-cusolver-cu12\n    #   torch\nnvidia-cusparselt-cu12==0.7.1 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nnvidia-nccl-cu12==2.27.3 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nnvidia-nvjitlink-cu12==12.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via\n    #   nvidia-cufft-cu12\n    #   nvidia-cusolver-cu12\n    #   nvidia-cusparse-cu12\n    #   torch\nnvidia-nvtx-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\nopencv-python==4.12.0.88\n    # via pytorch-tiny-imagenet\noverrides==7.7.0 ; python_full_version < '3.12'\n    # via jupyter-server\npackaging==25.0\n    # via\n    #   bokeh\n    #   ipykernel\n    #   jupyter-events\n    #   jupyter-server\n    #   jupyterlab\n    #   jupyterlab-server\n    #   matplotlib\n    #   nbconvert\npandas==2.3.2\n    # via bokeh\npandocfilters==1.5.1\n    # via nbconvert\nparso==0.8.5\n    # via jedi\npexpect==4.9.0 ; sys_platform != 'emscripten' and sys_platform != 'win32'\n    # via ipython\npillow==11.3.0\n    # via\n    #   bokeh\n    #   matplotlib\n    #   torchvision\nplatformdirs==4.4.0\n    # via jupyter-core\nprometheus-client==0.22.1\n    # via jupyter-server\nprompt-toolkit==3.0.52\n    # via ipython\npsutil==7.0.0\n    # via ipykernel\nptyprocess==0.7.0 ; os_name != 'nt' or (sys_platform != 'emscripten' and sys_platform != 'win32')\n    # via\n    #   pexpect\n    #   terminado\npure-eval==0.2.3\n    # via stack-data\npycparser==2.23 ; implementation_name != 'PyPy'\n    # via cffi\npygments==2.19.2\n    # via\n    #   ipython\n    #   ipython-pygments-lexers\n    #   nbconvert\npyparsing==3.2.4\n    # via matplotlib\npython-dateutil==2.9.0.post0\n    # via\n    #   arrow\n    #   jupyter-client\n    #   matplotlib\n    #   pandas\npython-json-logger==3.3.0\n    # via jupyter-events\npytz==2025.2\n    # via pandas\npywin32==311 ; platform_python_implementation != 'PyPy' and sys_platform == 'win32'\n    # via jupyter-core\npywinpty==3.0.0 ; os_name == 'nt'\n    # via\n    #   jupyter-server\n    #   jupyter-server-terminals\n    #   terminado\npyyaml==6.0.2\n    # via\n    #   bokeh\n    #   jupyter-events\npyzmq==27.1.0\n    # via\n    #   ipykernel\n    #   jupyter-client\n    #   jupyter-server\nreferencing==0.36.2\n    # via\n    #   jsonschema\n    #   jsonschema-specifications\n    #   jupyter-events\nrequests==2.32.5\n    # via jupyterlab-server\nrfc3339-validator==0.1.4\n    # via\n    #   jsonschema\n    #   jupyter-events\nrfc3986-validator==0.1.1\n    # via\n    #   jsonschema\n    #   jupyter-events\nrfc3987-syntax==1.1.0\n    # via jsonschema\nrpds-py==0.27.1\n    # via\n    #   jsonschema\n    #   referencing\nruff==0.13.0\n    # via pytorch-tiny-imagenet\nsend2trash==1.8.3\n    # via jupyter-server\nsetuptools==80.9.0\n    # via\n    #   jupyterlab\n    #   torch\n    #   triton\nsix==1.17.0\n    # via\n    #   python-dateutil\n    #   rfc3339-validator\nsniffio==1.3.1\n    # via anyio\nsoupsieve==2.8\n    # via beautifulsoup4\nstack-data==0.6.3\n    # via ipython\nsympy==1.14.0\n    # via torch\nterminado==0.18.1\n    # via\n    #   jupyter-server\n    #   jupyter-server-terminals\ntinycss2==1.4.0\n    # via bleach\ntorch==2.8.0\n    # via\n    #   pytorch-tiny-imagenet\n    #   torchvision\ntorchvision==0.23.0\n    # via pytorch-tiny-imagenet\ntornado==6.5.2\n    # via\n    #   bokeh\n    #   ipykernel\n    #   jupyter-client\n    #   jupyter-server\n    #   jupyterlab\n    #   notebook\n    #   terminado\ntqdm==4.67.1\ntraitlets==5.14.3\n    # via\n    #   ipykernel\n    #   ipython\n    #   jupyter-client\n    #   jupyter-core\n    #   jupyter-events\n    #   jupyter-server\n    #   jupyterlab\n    #   matplotlib-inline\n    #   nbclient\n    #   nbconvert\n    #   nbformat\ntriton==3.4.0 ; platform_machine == 'x86_64' and sys_platform == 'linux'\n    # via torch\ntypes-python-dateutil==2.9.0.20250822\n    # via arrow\ntyping-extensions==4.15.0\n    # via\n    #   anyio\n    #   beautifulsoup4\n    #   ipython\n    #   referencing\n    #   torch\ntzdata==2025.2\n    # via pandas\nuri-template==1.3.0\n    # via jsonschema\nurllib3==2.5.0\n    # via requests\nwcwidth==0.2.13\n    # via prompt-toolkit\nwebcolors==24.11.1\n    # via jsonschema\nwebencodings==0.5.1\n    # via\n    #   bleach\n    #   tinycss2\nwebsocket-client==1.8.0\n    # via jupyter-server\nxyzservices==2025.4.0\n    # via bokeh\n"
  },
  {
    "path": "src/model/AlexNet.py",
    "content": "import torch.nn as nn\nimport torch.utils.model_zoo as model_zoo\n\n\n__all__ = [\"AlexNet\", \"alexnet\"]\n\n\nmodel_urls = {\n    \"alexnet\": \"https://download.pytorch.org/models/alexnet-owt-4df8aa71.pth\",\n}\n\n\nclass AlexNet(nn.Module):\n    def __init__(self, num_classes=1000):\n        super(AlexNet, self).__init__()\n        self.features = nn.Sequential(\n            nn.Conv2d(3, 64, kernel_size=11, stride=4, padding=2),\n            nn.ReLU(inplace=True),\n            nn.MaxPool2d(kernel_size=3, stride=2),\n            nn.Conv2d(64, 192, kernel_size=5, padding=2),\n            nn.ReLU(inplace=True),\n            nn.MaxPool2d(kernel_size=3, stride=2),\n            nn.Conv2d(192, 384, kernel_size=3, padding=1),\n            nn.ReLU(inplace=True),\n            nn.Conv2d(384, 256, kernel_size=3, padding=1),\n            nn.ReLU(inplace=True),\n            nn.Conv2d(256, 256, kernel_size=3, padding=1),\n            nn.ReLU(inplace=True),\n            nn.MaxPool2d(kernel_size=3, stride=2),\n        )\n        self.classifier = nn.Sequential(\n            nn.Dropout(),\n            nn.Linear(256 * 6 * 6, 4096),\n            nn.ReLU(inplace=True),\n            nn.Dropout(),\n            nn.Linear(4096, 4096),\n            nn.ReLU(inplace=True),\n            nn.Linear(4096, num_classes),\n        )\n\n    def forward(self, x):\n        x = self.features(x)\n        x = x.view(x.size(0), 256 * 1 * 1)\n        x = self.classifier(x)\n        return x\n\n\ndef alexnet(pretrained=False, **kwargs):\n    r\"\"\"AlexNet model architecture from the\n    `\"One weird trick...\" <https://arxiv.org/abs/1404.5997>`_ paper.\n    Args:\n        pretrained (bool): If True, returns a model pre-trained on ImageNet\n    \"\"\"\n    model = AlexNet(**kwargs)\n    if pretrained:\n        model.load_state_dict(model_zoo.load_url(model_urls[\"alexnet\"]))\n    model.classifier[1] = nn.Linear(256 * 1 * 1, 4096)\n    model.classifier[6] = nn.Linear(4096, 200)\n    return model\n"
  },
  {
    "path": "src/test_model.py",
    "content": "import time\n\nimport torch\n\n\ndef test_model(model, dataloaders, criterion, device):\n    since = time.time()\n    phase = \"test\"\n\n    # Each epoch has a training and validation phase\n    model.eval()  # Set model to evaluate mode\n\n    running_loss = 0.0\n    running_corrects = 0\n\n    with torch.no_grad():\n        for i, (inputs, labels) in enumerate(dataloaders[phase]):\n            inputs = inputs.to(device)\n            labels = labels.to(device)\n\n            outputs = model(inputs)\n            _, preds = torch.max(outputs, 1)\n            loss = criterion(outputs, labels)\n\n            # statistics\n            running_loss += loss.item() * inputs.size(0)\n            running_corrects += torch.sum(preds == labels.data)\n\n    epoch_loss = running_loss / len(dataloaders[phase].dataset)\n    epoch_acc = running_corrects.float() / len(dataloaders[phase].dataset)\n\n    time_elapsed = time.time() - since\n    print(\"Test Loss: {:.4f} Acc: {:.4f}\".format(epoch_loss, epoch_acc))\n    print(\"Test complete in {:.0f}m {:.0f}s\".format(time_elapsed // 60, time_elapsed % 60))\n"
  },
  {
    "path": "src/train_model.py",
    "content": "import time\nfrom pathlib import Path\n\nimport torch\nfrom livelossplot import PlotLosses\n\n\ndef train_model(output_path, model, dataloaders, criterion, optimizer, device, num_epochs=5, scheduler=None) -> int:\n    (Path(\"models\") / output_path).mkdir(parents=True, exist_ok=True)\n    since = time.time()\n    liveloss = PlotLosses()\n\n    best_acc = 0.0\n    best = 0\n\n    for epoch in range(num_epochs):\n        logs = {}\n        print(\"Epoch {}/{}\".format(epoch + 1, num_epochs))\n        print(\"-\" * 10)\n\n        # Each epoch has a training and validation phase\n        for phase in [\"train\", \"val\"]:\n            if phase == \"train\":\n                if scheduler:\n                    scheduler.step()\n                model.train()  # Set model to training mode\n            else:\n                model.eval()  # Set model to evaluate mode\n\n            running_loss = 0.0\n            running_corrects = 0\n\n            # Iterate over data.\n            for i, (inputs, labels) in enumerate(dataloaders[phase]):\n                inputs = inputs.to(device)\n                labels = labels.to(device)\n\n                outputs = model(inputs)\n                loss = criterion(outputs, labels)\n\n                if phase == \"train\":\n                    optimizer.zero_grad()\n                    loss.backward()\n                    optimizer.step()\n\n                # statistics\n                _, preds = torch.max(outputs, 1)\n                running_loss += loss.detach() * inputs.size(0)\n                running_corrects += torch.sum(preds == labels.data)\n\n            epoch_loss = running_loss / len(dataloaders[phase].dataset)\n            epoch_acc = running_corrects.float() / len(dataloaders[phase].dataset)\n\n            if phase == \"train\":\n                prefix = \"\"\n            else:\n                prefix = \"val_\"\n\n            # deep copy the model\n            if phase == \"val\" and epoch_acc > best_acc:\n                best_acc = epoch_acc\n                best = epoch + 1\n\n            logs[prefix + \"log loss\"] = epoch_loss.item()\n            logs[prefix + \"accuracy\"] = epoch_acc.item()\n\n        liveloss.update(logs)\n        liveloss.send()\n\n        torch.save(model.state_dict(), f\"./models/{output_path}/model_{epoch + 1}_epoch.pt\")\n    time_elapsed = time.time() - since\n    print(\"Training complete in {:.0f}m {:.0f}s\".format(time_elapsed // 60, time_elapsed % 60))\n    print(\"Best Validation Accuracy: {}, Epoch: {}\".format(best_acc, best))\n    return best\n"
  },
  {
    "path": "src/util/prepare_dataset.py",
    "content": "import random\nimport shutil\nfrom hashlib import md5\nfrom pathlib import Path\nfrom urllib.request import urlretrieve\nfrom zipfile import ZipFile\nimport cv2\n\nfrom tqdm import tqdm\n\nrandom.seed(42)\n\n# DATASET_URL = \"http://cs231n.stanford.edu/tiny-imagenet-200.zip\"\nDATASET_URL = (\n    \"https://github.com/tjmoon0104/pytorch-tiny-imagenet/releases/download/tiny-imagenet-dataset/tiny-imagenet-200.zip\"\n)\nDATASET_ZIP = Path(\"./tiny-imagenet-200.zip\")\nDATASET_MD5_HASH = \"90528d7ca1a48142e341f4ef8d21d0de\"\n\n# Download Dataset if needed\nif not DATASET_ZIP.exists():\n    print(\"Downloading the dataset, this may take a while...\")\n\n    with tqdm(unit=\"B\", unit_scale=True, unit_divisor=1024, miniters=1, desc=DATASET_URL.split(\"/\")[-1]) as t:\n\n        def show_progress(block_num, block_size, total_size):\n            t.total = total_size\n            t.update(block_num * block_size - t.n)\n\n        urlretrieve(url=DATASET_URL, filename=DATASET_ZIP, reporthook=show_progress)\n\n# Check MD5 Hash\nwith DATASET_ZIP.open(\"rb\") as f:\n    assert (\n        md5(f.read()).hexdigest() == DATASET_MD5_HASH\n    ), \"The dataset zip file seems corrupted. Try to download it again.\"\n\n\n# Remove existing data set\nORIGINAL_DATASET_DIR = Path(\"./original\")\nif ORIGINAL_DATASET_DIR.exists():\n    shutil.rmtree(ORIGINAL_DATASET_DIR)\n\nif not ORIGINAL_DATASET_DIR.exists():\n    print(\"Extracting the dataset, this may take a while...\")\n\n    # Unzip the dataset\n    with ZipFile(DATASET_ZIP, \"r\") as zip_ref:\n        for member in tqdm(zip_ref.infolist(), desc=\"Extracting\"):\n            zip_ref.extract(member, ORIGINAL_DATASET_DIR)\n\n# Remove existing data set\nDATASET_DIR = Path(\"./tiny-imagenet-200\")\nif DATASET_DIR.exists():\n    shutil.rmtree(DATASET_DIR)\n\n# Create the dataset directory\nif not DATASET_DIR.exists():\n    print(\"Creating the dataset directory...\")\n    DATASET_DIR.mkdir()\n\n# Move train images to dataset directory\nORIGINAL_TRAIN_DIR = ORIGINAL_DATASET_DIR / \"tiny-imagenet-200\" / \"train\"\nif ORIGINAL_TRAIN_DIR.exists():\n    print(\"Moving train images...\")\n    ORIGINAL_TRAIN_DIR.replace(DATASET_DIR / \"train\")\n\n# Get validation images and annotations\nval_dict = {}\nORIGINAL_VAL_DIR = ORIGINAL_DATASET_DIR / \"tiny-imagenet-200\" / \"val\"\nwith (ORIGINAL_VAL_DIR / \"val_annotations.txt\").open(\"r\") as f:\n    for line in f.readlines():\n        split_line = line.split(\"\\t\")\n        if split_line[1] not in val_dict.keys():\n            val_dict[split_line[1]] = [split_line[0]]\n        else:\n            val_dict[split_line[1]].append(split_line[0])\n\n\ndef split_list_randomly(input_list: list[str], split_ratio=0.5) -> dict[str, list[str]]:\n    # Shuffle the input list in-place\n    random.shuffle(input_list)\n\n    # Calculate the index to split the list\n    split_index = int(len(input_list) * split_ratio)\n\n    # Split the list into two parts\n    return {\"val\": input_list[:split_index], \"test\": input_list[split_index:]}\n\n\n# Sample from validation images randomly into validation and test sets (50/50)\nprint(\"Splitting original dataset images...\")\nwith tqdm(val_dict.items(), desc=\"Splitting images\", unit=\"class\") as t:\n    for image_label, images in t:\n        for split_type, split_images in split_list_randomly(images, split_ratio=0.5).items():\n            for image in split_images:\n                src = ORIGINAL_VAL_DIR / \"images\" / image\n                dest_folder = DATASET_DIR / split_type / image_label / \"images\"\n                dest_folder.mkdir(parents=True, exist_ok=True)\n                src.replace(dest_folder / image)\n        t.update()\n\n# Remove original directory\nshutil.rmtree(ORIGINAL_DATASET_DIR)\n\n# Remove resized data set directory\nRESIZED_DIR = Path(\"./tiny-224\")\nif RESIZED_DIR.exists():\n    shutil.rmtree(RESIZED_DIR)\n\n# Copy processed dataset to tiny-224\nprint(\"Copying processed dataset to tiny-224...\")\nshutil.copytree(DATASET_DIR, RESIZED_DIR)\n\n\n# Resize images to 224x224\ndef resize_img(image_path: Path, size: int = 224) -> None:\n    img = cv2.imread(image_path.as_posix())\n    img = cv2.resize(img, (size, size), interpolation=cv2.INTER_CUBIC)\n    cv2.imwrite(image_path.as_posix(), img)\n\n\nall_images = [*Path(\"tiny-224\").glob(\"**/*.JPEG\")]\nprint(\"Resizing images...\")\nwith tqdm(all_images, desc=\"Resizing images\", unit=\"file\") as t:\n    for image in t:\n        resize_img(image, 224)\n"
  }
]