diff --git a/README.md b/README.md
index 1e0c80fa3..521543b83 100644
--- a/README.md
+++ b/README.md
@@ -45,14 +45,23 @@ For other announcements, updates, and additional materials, you can follow [Ligh
-### Model Training in PyTorch
+### Unit 3. Model Training in PyTorch
- [3.6 Training a Logistic Regression Model in PyTorch](https://github.com/Lightning-AI/dl-fundamentals/tree/main/3.6-logreg-in-pytorch)
- Unit 3 exercises
- [Exercise 1: Banknote Authentication](https://github.com/Lightning-AI/dl-fundamentals/tree/main/exercises/1_banknotes)
- [Exercise 2: Standardization](https://github.com/Lightning-AI/dl-fundamentals/tree/main/exercises/2_standardization)
-### Unit 4. Coming Soon
+### Unit 4. Training Multilayer Neural Networks
+
+- [4.3 Training a Multilayer Perceptron in PyTorch](unit04-multilayer-nets/4.3-mlp-pytorch)
+ - [XOR data](unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part1-2-xor)
+ - [MNIST data](unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist)
+- [4.4 Defining Efficient Data Loaders](unit04-multilayer-nets/4.4-dataloaders)
+- [4.5 Multilayer Neural Networks for Regression](unit04-multilayer-nets/4.5-mlp-regression)
+- Unit 4 exercises
+ - TBA
+
### Unit 5. Coming Soon
diff --git a/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part1-2-xor/4.3-mlp-pytorch-part1-xor.ipynb b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part1-2-xor/4.3-mlp-pytorch-part1-xor.ipynb
new file mode 100644
index 000000000..8f70c250f
--- /dev/null
+++ b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part1-2-xor/4.3-mlp-pytorch-part1-xor.ipynb
@@ -0,0 +1,511 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "d71bce70-9dc3-448b-9f9a-8896e83b6d09",
+ "metadata": {},
+ "source": [
+ "# Unit 4.3: Implementing a Multilayer Perceptron (XOR)\n",
+ "\n",
+ "## Part 1 of 2"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e5b48fc7-4f46-4d5a-8558-cd06892aaa27",
+ "metadata": {},
+ "source": [
+ "## 1) Installing Libraries"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "be1f5a9a-b3ee-424b-ab02-4371f49bd786",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !conda install numpy pandas matplotlib scikit-learn --yes"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "1ea7b3b8-9092-4b37-8b7f-57362be611ad",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !pip install torch torchvision torchaudio"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "79dd2077-ba5c-4ab5-95fc-6ee4d8a9f811",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !conda install watermark --yes"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "bc4fa295-5c62-4888-bcf8-d07d6a7afc47",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Python implementation: CPython\n",
+ "Python version : 3.9.15\n",
+ "IPython version : 8.6.0\n",
+ "\n",
+ "numpy : 1.23.4\n",
+ "pandas : 1.5.2\n",
+ "matplotlib : 3.6.2\n",
+ "torch : 1.13.0\n",
+ "scikit-learn: 1.2.0\n",
+ "\n",
+ "conda environment: dl-fundamentals\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "%load_ext watermark\n",
+ "%watermark -v -p numpy,pandas,matplotlib,torch,scikit-learn --conda"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b9549676-2fa5-41a7-bbb9-ce03f5797c34",
+ "metadata": {},
+ "source": [
+ "## 2) Loading the Dataset"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "f609024c-3eae-4ad5-8cb8-b95b403b7606",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " x1 | \n",
+ " x2 | \n",
+ " class label | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 0 | \n",
+ " 0.781306 | \n",
+ " 1.062984 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 1 | \n",
+ " -1.060524 | \n",
+ " -1.095550 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 2 | \n",
+ " 0.632125 | \n",
+ " 0.674028 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 3 | \n",
+ " -1.424712 | \n",
+ " 0.535203 | \n",
+ " 1 | \n",
+ "
\n",
+ " \n",
+ " | 4 | \n",
+ " 1.383161 | \n",
+ " 1.368510 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ "
\n",
+ " \n",
+ " | 745 | \n",
+ " 0.792484 | \n",
+ " 0.839275 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 746 | \n",
+ " 0.582466 | \n",
+ " -0.749250 | \n",
+ " 1 | \n",
+ "
\n",
+ " \n",
+ " | 747 | \n",
+ " -1.593475 | \n",
+ " 0.671721 | \n",
+ " 1 | \n",
+ "
\n",
+ " \n",
+ " | 748 | \n",
+ " -0.812671 | \n",
+ " -0.268542 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 749 | \n",
+ " -1.286524 | \n",
+ " 0.655459 | \n",
+ " 1 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
750 rows × 3 columns
\n",
+ "
"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.plot(\n",
+ " X_train[y_train == 0, 0],\n",
+ " X_train[y_train == 0, 1],\n",
+ " marker=\"D\",\n",
+ " markersize=10,\n",
+ " linestyle=\"\",\n",
+ " label=\"Class 0\",\n",
+ ")\n",
+ "\n",
+ "plt.plot(\n",
+ " X_train[y_train == 1, 0],\n",
+ " X_train[y_train == 1, 1],\n",
+ " marker=\"^\",\n",
+ " markersize=13,\n",
+ " linestyle=\"\",\n",
+ " label=\"Class 1\",\n",
+ ")\n",
+ "\n",
+ "plt.legend(loc=2)\n",
+ "\n",
+ "plt.xlim([-5, 5])\n",
+ "plt.ylim([-5, 5])\n",
+ "\n",
+ "plt.xlabel(\"Feature $x_1$\", fontsize=12)\n",
+ "plt.ylabel(\"Feature $x_2$\", fontsize=12)\n",
+ "\n",
+ "plt.grid()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "db50db02-3696-4f86-b149-74baabeec6c4",
+ "metadata": {},
+ "source": [
+ "## 4) Implementing the model"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "971389a7-5424-4141-a3ee-9399eebbbb6a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import torch\n",
+ "\n",
+ "\n",
+ "class PyTorchMLP(torch.nn.Module):\n",
+ " def __init__(self, num_features, num_classes):\n",
+ " super().__init__()\n",
+ "\n",
+ " self.all_layers = torch.nn.Sequential(\n",
+ " \n",
+ " # 1st hidden layer\n",
+ " torch.nn.Linear(num_features, 25),\n",
+ " torch.nn.ReLU(),\n",
+ "\n",
+ " # 2nd hidden layer\n",
+ " torch.nn.Linear(25, 15),\n",
+ " torch.nn.ReLU(),\n",
+ "\n",
+ " # output layer\n",
+ " torch.nn.Linear(15, num_classes),\n",
+ " )\n",
+ "\n",
+ " def forward(self, x):\n",
+ " logits = self.all_layers(x)\n",
+ " return logits"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "12068721-daf9-4ea1-9240-5bcc19c75ce9",
+ "metadata": {},
+ "source": [
+ "## 5) Defining a DataLoader"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "133ba03e-5053-4ed1-a2d9-eab0f51cf226",
+ "metadata": {},
+ "source": [
+ "- More details in Unit 4.4"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "f6376d80-e7cf-43b4-96eb-bfd99709b63a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from torch.utils.data import Dataset, DataLoader\n",
+ "\n",
+ "\n",
+ "class MyDataset(Dataset):\n",
+ " def __init__(self, X, y):\n",
+ "\n",
+ " self.features = torch.tensor(X, dtype=torch.float32)\n",
+ " self.labels = torch.tensor(y, dtype=torch.int64)\n",
+ "\n",
+ " def __getitem__(self, index):\n",
+ " x = self.features[index]\n",
+ " y = self.labels[index] \n",
+ " return x, y\n",
+ "\n",
+ " def __len__(self):\n",
+ " return self.labels.shape[0]\n",
+ " \n",
+ "\n",
+ "train_ds = MyDataset(X_train, y_train)\n",
+ "val_ds = MyDataset(X_val, y_val)\n",
+ "test_ds = MyDataset(X_test, y_test)\n",
+ "\n",
+ "train_loader = DataLoader(\n",
+ " dataset=train_ds,\n",
+ " batch_size=32,\n",
+ " shuffle=True,\n",
+ ")\n",
+ "\n",
+ "val_loader = DataLoader(\n",
+ " dataset=val_ds,\n",
+ " batch_size=32,\n",
+ " shuffle=False,\n",
+ ")\n",
+ "\n",
+ "test_loader = DataLoader(\n",
+ " dataset=test_ds,\n",
+ " batch_size=32,\n",
+ " shuffle=False,\n",
+ ")"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part1-2-xor/4.3-mlp-pytorch-part2-xor.ipynb b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part1-2-xor/4.3-mlp-pytorch-part2-xor.ipynb
new file mode 100644
index 000000000..9c6e57a86
--- /dev/null
+++ b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part1-2-xor/4.3-mlp-pytorch-part2-xor.ipynb
@@ -0,0 +1,885 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "d71bce70-9dc3-448b-9f9a-8896e83b6d09",
+ "metadata": {},
+ "source": [
+ "# Unit 4.3: Implementing a Multilayer Perceptron (XOR)\n",
+ "\n",
+ "## Part 2 of 2"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e5b48fc7-4f46-4d5a-8558-cd06892aaa27",
+ "metadata": {},
+ "source": [
+ "## 1) Installing Libraries"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "be1f5a9a-b3ee-424b-ab02-4371f49bd786",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !conda install numpy pandas matplotlib scikit-learn --yes"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "1ea7b3b8-9092-4b37-8b7f-57362be611ad",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !pip install torch torchvision torchaudio"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "79dd2077-ba5c-4ab5-95fc-6ee4d8a9f811",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !conda install watermark"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "bc4fa295-5c62-4888-bcf8-d07d6a7afc47",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Python implementation: CPython\n",
+ "Python version : 3.9.15\n",
+ "IPython version : 8.6.0\n",
+ "\n",
+ "numpy : 1.23.4\n",
+ "pandas : 1.5.2\n",
+ "matplotlib : 3.6.2\n",
+ "torch : 1.13.0\n",
+ "scikit-learn: 1.2.0\n",
+ "\n",
+ "conda environment: dl-fundamentals\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "%load_ext watermark\n",
+ "%watermark -v -p numpy,pandas,matplotlib,torch,scikit-learn --conda"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b9549676-2fa5-41a7-bbb9-ce03f5797c34",
+ "metadata": {},
+ "source": [
+ "## 2) Loading the Dataset"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "f609024c-3eae-4ad5-8cb8-b95b403b7606",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " x1 | \n",
+ " x2 | \n",
+ " class label | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 0 | \n",
+ " 0.781306 | \n",
+ " 1.062984 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 1 | \n",
+ " -1.060524 | \n",
+ " -1.095550 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 2 | \n",
+ " 0.632125 | \n",
+ " 0.674028 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 3 | \n",
+ " -1.424712 | \n",
+ " 0.535203 | \n",
+ " 1 | \n",
+ "
\n",
+ " \n",
+ " | 4 | \n",
+ " 1.383161 | \n",
+ " 1.368510 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ "
\n",
+ " \n",
+ " | 745 | \n",
+ " 0.792484 | \n",
+ " 0.839275 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 746 | \n",
+ " 0.582466 | \n",
+ " -0.749250 | \n",
+ " 1 | \n",
+ "
\n",
+ " \n",
+ " | 747 | \n",
+ " -1.593475 | \n",
+ " 0.671721 | \n",
+ " 1 | \n",
+ "
\n",
+ " \n",
+ " | 748 | \n",
+ " -0.812671 | \n",
+ " -0.268542 | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 749 | \n",
+ " -1.286524 | \n",
+ " 0.655459 | \n",
+ " 1 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
750 rows × 3 columns
\n",
+ "
"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.plot(\n",
+ " X_train[y_train == 0, 0],\n",
+ " X_train[y_train == 0, 1],\n",
+ " marker=\"D\",\n",
+ " markersize=10,\n",
+ " linestyle=\"\",\n",
+ " label=\"Class 0\",\n",
+ ")\n",
+ "\n",
+ "plt.plot(\n",
+ " X_train[y_train == 1, 0],\n",
+ " X_train[y_train == 1, 1],\n",
+ " marker=\"^\",\n",
+ " markersize=13,\n",
+ " linestyle=\"\",\n",
+ " label=\"Class 1\",\n",
+ ")\n",
+ "\n",
+ "plt.legend(loc=2)\n",
+ "\n",
+ "plt.xlim([-5, 5])\n",
+ "plt.ylim([-5, 5])\n",
+ "\n",
+ "plt.xlabel(\"Feature $x_1$\", fontsize=12)\n",
+ "plt.ylabel(\"Feature $x_2$\", fontsize=12)\n",
+ "\n",
+ "plt.grid()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "db50db02-3696-4f86-b149-74baabeec6c4",
+ "metadata": {},
+ "source": [
+ "## 4) Implementing the model"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "971389a7-5424-4141-a3ee-9399eebbbb6a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import torch\n",
+ "\n",
+ "\n",
+ "class PyTorchMLP(torch.nn.Module):\n",
+ " def __init__(self, num_features, num_classes):\n",
+ " super().__init__()\n",
+ "\n",
+ " self.all_layers = torch.nn.Sequential(\n",
+ " \n",
+ " # 1st hidden layer\n",
+ " torch.nn.Linear(num_features, 25),\n",
+ " torch.nn.ReLU(),\n",
+ "\n",
+ " # 2nd hidden layer\n",
+ " torch.nn.Linear(25, 15),\n",
+ " torch.nn.ReLU(),\n",
+ "\n",
+ " # output layer\n",
+ " torch.nn.Linear(15, num_classes),\n",
+ " )\n",
+ "\n",
+ " def forward(self, x):\n",
+ " logits = self.all_layers(x)\n",
+ " return logits"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "12068721-daf9-4ea1-9240-5bcc19c75ce9",
+ "metadata": {},
+ "source": [
+ "## 5) Defining a DataLoader"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "f6376d80-e7cf-43b4-96eb-bfd99709b63a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from torch.utils.data import Dataset, DataLoader\n",
+ "\n",
+ "\n",
+ "class MyDataset(Dataset):\n",
+ " def __init__(self, X, y):\n",
+ "\n",
+ " self.features = torch.tensor(X, dtype=torch.float32)\n",
+ " self.labels = torch.tensor(y, dtype=torch.int64)\n",
+ "\n",
+ " def __getitem__(self, index):\n",
+ " x = self.features[index]\n",
+ " y = self.labels[index] \n",
+ " return x, y\n",
+ "\n",
+ " def __len__(self):\n",
+ " return self.labels.shape[0]\n",
+ " \n",
+ "\n",
+ "train_ds = MyDataset(X_train, y_train)\n",
+ "val_ds = MyDataset(X_val, y_val)\n",
+ "test_ds = MyDataset(X_test, y_test)\n",
+ "\n",
+ "train_loader = DataLoader(\n",
+ " dataset=train_ds,\n",
+ " batch_size=32,\n",
+ " shuffle=True,\n",
+ ")\n",
+ "\n",
+ "val_loader = DataLoader(\n",
+ " dataset=val_ds,\n",
+ " batch_size=32,\n",
+ " shuffle=False,\n",
+ ")\n",
+ "\n",
+ "test_loader = DataLoader(\n",
+ " dataset=test_ds,\n",
+ " batch_size=32,\n",
+ " shuffle=False,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "46bc16a0-ec59-4c54-a209-0a5e22406287",
+ "metadata": {},
+ "source": [
+ "## 6) The training loop"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "8de213fc-48b0-4f7c-af9e-8e2da068e351",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def compute_accuracy(model, dataloader):\n",
+ "\n",
+ " model = model.eval()\n",
+ " \n",
+ " correct = 0.0\n",
+ " total_examples = 0\n",
+ " \n",
+ " for idx, (features, labels) in enumerate(dataloader):\n",
+ " \n",
+ " with torch.inference_mode(): # basically the same as torch.no_grad\n",
+ " logits = model(features)\n",
+ " \n",
+ " predictions = torch.argmax(logits, dim=1)\n",
+ "\n",
+ " compare = labels == predictions\n",
+ " correct += torch.sum(compare)\n",
+ " total_examples += len(compare)\n",
+ "\n",
+ " return correct / total_examples"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "c0dcad3f-5d86-470a-b332-0afe58b4df1f",
+ "metadata": {},
+ "source": [
+ "**Training loop**\n",
+ "\n",
+ "- Similar to Unit 3.6 -- Logistic Regression in PyTorch\n",
+ "- Differences are \n",
+ " - `PytorchMLP` instead of `LogisticRegression` model\n",
+ " - `F.cross_entropy` instead of `F.binary_cross_entropy`\n",
+ " \n",
+ "
\n",
+ "\n",
+ "- Note that F.cross_entropy takes `logits` as inputs, not probabilities\n",
+ " - it does the one-hot encoding and softmax internally"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "3dcaa2b1-4019-4128-9ff5-6a966c3abdf2",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Epoch: 001/010 | Batch 000/018 | Train/Val Loss: 0.68\n",
+ "Epoch: 001/010 | Batch 001/018 | Train/Val Loss: 0.69\n",
+ "Epoch: 001/010 | Batch 002/018 | Train/Val Loss: 0.68\n",
+ "Epoch: 001/010 | Batch 003/018 | Train/Val Loss: 0.67\n",
+ "Epoch: 001/010 | Batch 004/018 | Train/Val Loss: 0.69\n",
+ "Epoch: 001/010 | Batch 005/018 | Train/Val Loss: 0.68\n",
+ "Epoch: 001/010 | Batch 006/018 | Train/Val Loss: 0.66\n",
+ "Epoch: 001/010 | Batch 007/018 | Train/Val Loss: 0.68\n",
+ "Epoch: 001/010 | Batch 008/018 | Train/Val Loss: 0.67\n",
+ "Epoch: 001/010 | Batch 009/018 | Train/Val Loss: 0.68\n",
+ "Epoch: 001/010 | Batch 010/018 | Train/Val Loss: 0.66\n",
+ "Epoch: 001/010 | Batch 011/018 | Train/Val Loss: 0.65\n",
+ "Epoch: 001/010 | Batch 012/018 | Train/Val Loss: 0.67\n",
+ "Epoch: 001/010 | Batch 013/018 | Train/Val Loss: 0.67\n",
+ "Epoch: 001/010 | Batch 014/018 | Train/Val Loss: 0.65\n",
+ "Epoch: 001/010 | Batch 015/018 | Train/Val Loss: 0.67\n",
+ "Epoch: 001/010 | Batch 016/018 | Train/Val Loss: 0.67\n",
+ "Epoch: 001/010 | Batch 017/018 | Train/Val Loss: 0.65\n",
+ "Train Acc 68.41% | Val Acc 65.62%\n",
+ "Epoch: 002/010 | Batch 000/018 | Train/Val Loss: 0.66\n",
+ "Epoch: 002/010 | Batch 001/018 | Train/Val Loss: 0.66\n",
+ "Epoch: 002/010 | Batch 002/018 | Train/Val Loss: 0.66\n",
+ "Epoch: 002/010 | Batch 003/018 | Train/Val Loss: 0.65\n",
+ "Epoch: 002/010 | Batch 004/018 | Train/Val Loss: 0.66\n",
+ "Epoch: 002/010 | Batch 005/018 | Train/Val Loss: 0.65\n",
+ "Epoch: 002/010 | Batch 006/018 | Train/Val Loss: 0.63\n",
+ "Epoch: 002/010 | Batch 007/018 | Train/Val Loss: 0.65\n",
+ "Epoch: 002/010 | Batch 008/018 | Train/Val Loss: 0.66\n",
+ "Epoch: 002/010 | Batch 009/018 | Train/Val Loss: 0.66\n",
+ "Epoch: 002/010 | Batch 010/018 | Train/Val Loss: 0.66\n",
+ "Epoch: 002/010 | Batch 011/018 | Train/Val Loss: 0.63\n",
+ "Epoch: 002/010 | Batch 012/018 | Train/Val Loss: 0.64\n",
+ "Epoch: 002/010 | Batch 013/018 | Train/Val Loss: 0.64\n",
+ "Epoch: 002/010 | Batch 014/018 | Train/Val Loss: 0.65\n",
+ "Epoch: 002/010 | Batch 015/018 | Train/Val Loss: 0.63\n",
+ "Epoch: 002/010 | Batch 016/018 | Train/Val Loss: 0.63\n",
+ "Epoch: 002/010 | Batch 017/018 | Train/Val Loss: 0.62\n",
+ "Train Acc 81.50% | Val Acc 73.44%\n",
+ "Epoch: 003/010 | Batch 000/018 | Train/Val Loss: 0.64\n",
+ "Epoch: 003/010 | Batch 001/018 | Train/Val Loss: 0.63\n",
+ "Epoch: 003/010 | Batch 002/018 | Train/Val Loss: 0.63\n",
+ "Epoch: 003/010 | Batch 003/018 | Train/Val Loss: 0.64\n",
+ "Epoch: 003/010 | Batch 004/018 | Train/Val Loss: 0.62\n",
+ "Epoch: 003/010 | Batch 005/018 | Train/Val Loss: 0.61\n",
+ "Epoch: 003/010 | Batch 006/018 | Train/Val Loss: 0.61\n",
+ "Epoch: 003/010 | Batch 007/018 | Train/Val Loss: 0.64\n",
+ "Epoch: 003/010 | Batch 008/018 | Train/Val Loss: 0.62\n",
+ "Epoch: 003/010 | Batch 009/018 | Train/Val Loss: 0.61\n",
+ "Epoch: 003/010 | Batch 010/018 | Train/Val Loss: 0.61\n",
+ "Epoch: 003/010 | Batch 011/018 | Train/Val Loss: 0.61\n",
+ "Epoch: 003/010 | Batch 012/018 | Train/Val Loss: 0.62\n",
+ "Epoch: 003/010 | Batch 013/018 | Train/Val Loss: 0.60\n",
+ "Epoch: 003/010 | Batch 014/018 | Train/Val Loss: 0.62\n",
+ "Epoch: 003/010 | Batch 015/018 | Train/Val Loss: 0.61\n",
+ "Epoch: 003/010 | Batch 016/018 | Train/Val Loss: 0.60\n",
+ "Epoch: 003/010 | Batch 017/018 | Train/Val Loss: 0.59\n",
+ "Train Acc 89.88% | Val Acc 90.62%\n",
+ "Epoch: 004/010 | Batch 000/018 | Train/Val Loss: 0.59\n",
+ "Epoch: 004/010 | Batch 001/018 | Train/Val Loss: 0.59\n",
+ "Epoch: 004/010 | Batch 002/018 | Train/Val Loss: 0.58\n",
+ "Epoch: 004/010 | Batch 003/018 | Train/Val Loss: 0.59\n",
+ "Epoch: 004/010 | Batch 004/018 | Train/Val Loss: 0.59\n",
+ "Epoch: 004/010 | Batch 005/018 | Train/Val Loss: 0.57\n",
+ "Epoch: 004/010 | Batch 006/018 | Train/Val Loss: 0.55\n",
+ "Epoch: 004/010 | Batch 007/018 | Train/Val Loss: 0.60\n",
+ "Epoch: 004/010 | Batch 008/018 | Train/Val Loss: 0.59\n",
+ "Epoch: 004/010 | Batch 009/018 | Train/Val Loss: 0.57\n",
+ "Epoch: 004/010 | Batch 010/018 | Train/Val Loss: 0.57\n",
+ "Epoch: 004/010 | Batch 011/018 | Train/Val Loss: 0.56\n",
+ "Epoch: 004/010 | Batch 012/018 | Train/Val Loss: 0.58\n",
+ "Epoch: 004/010 | Batch 013/018 | Train/Val Loss: 0.58\n",
+ "Epoch: 004/010 | Batch 014/018 | Train/Val Loss: 0.56\n",
+ "Epoch: 004/010 | Batch 015/018 | Train/Val Loss: 0.57\n",
+ "Epoch: 004/010 | Batch 016/018 | Train/Val Loss: 0.54\n",
+ "Epoch: 004/010 | Batch 017/018 | Train/Val Loss: 0.57\n",
+ "Train Acc 93.19% | Val Acc 90.62%\n",
+ "Epoch: 005/010 | Batch 000/018 | Train/Val Loss: 0.56\n",
+ "Epoch: 005/010 | Batch 001/018 | Train/Val Loss: 0.56\n",
+ "Epoch: 005/010 | Batch 002/018 | Train/Val Loss: 0.54\n",
+ "Epoch: 005/010 | Batch 003/018 | Train/Val Loss: 0.54\n",
+ "Epoch: 005/010 | Batch 004/018 | Train/Val Loss: 0.52\n",
+ "Epoch: 005/010 | Batch 005/018 | Train/Val Loss: 0.54\n",
+ "Epoch: 005/010 | Batch 006/018 | Train/Val Loss: 0.53\n",
+ "Epoch: 005/010 | Batch 007/018 | Train/Val Loss: 0.50\n",
+ "Epoch: 005/010 | Batch 008/018 | Train/Val Loss: 0.54\n",
+ "Epoch: 005/010 | Batch 009/018 | Train/Val Loss: 0.52\n",
+ "Epoch: 005/010 | Batch 010/018 | Train/Val Loss: 0.50\n",
+ "Epoch: 005/010 | Batch 011/018 | Train/Val Loss: 0.54\n",
+ "Epoch: 005/010 | Batch 012/018 | Train/Val Loss: 0.48\n",
+ "Epoch: 005/010 | Batch 013/018 | Train/Val Loss: 0.53\n",
+ "Epoch: 005/010 | Batch 014/018 | Train/Val Loss: 0.50\n",
+ "Epoch: 005/010 | Batch 015/018 | Train/Val Loss: 0.48\n",
+ "Epoch: 005/010 | Batch 016/018 | Train/Val Loss: 0.49\n",
+ "Epoch: 005/010 | Batch 017/018 | Train/Val Loss: 0.51\n",
+ "Train Acc 95.29% | Val Acc 92.19%\n",
+ "Epoch: 006/010 | Batch 000/018 | Train/Val Loss: 0.47\n",
+ "Epoch: 006/010 | Batch 001/018 | Train/Val Loss: 0.50\n",
+ "Epoch: 006/010 | Batch 002/018 | Train/Val Loss: 0.51\n",
+ "Epoch: 006/010 | Batch 003/018 | Train/Val Loss: 0.48\n",
+ "Epoch: 006/010 | Batch 004/018 | Train/Val Loss: 0.43\n",
+ "Epoch: 006/010 | Batch 005/018 | Train/Val Loss: 0.47\n",
+ "Epoch: 006/010 | Batch 006/018 | Train/Val Loss: 0.44\n",
+ "Epoch: 006/010 | Batch 007/018 | Train/Val Loss: 0.52\n",
+ "Epoch: 006/010 | Batch 008/018 | Train/Val Loss: 0.45\n",
+ "Epoch: 006/010 | Batch 009/018 | Train/Val Loss: 0.47\n",
+ "Epoch: 006/010 | Batch 010/018 | Train/Val Loss: 0.44\n",
+ "Epoch: 006/010 | Batch 011/018 | Train/Val Loss: 0.41\n",
+ "Epoch: 006/010 | Batch 012/018 | Train/Val Loss: 0.50\n",
+ "Epoch: 006/010 | Batch 013/018 | Train/Val Loss: 0.44\n",
+ "Epoch: 006/010 | Batch 014/018 | Train/Val Loss: 0.45\n",
+ "Epoch: 006/010 | Batch 015/018 | Train/Val Loss: 0.41\n",
+ "Epoch: 006/010 | Batch 016/018 | Train/Val Loss: 0.47\n",
+ "Epoch: 006/010 | Batch 017/018 | Train/Val Loss: 0.41\n",
+ "Train Acc 94.76% | Val Acc 92.19%\n",
+ "Epoch: 007/010 | Batch 000/018 | Train/Val Loss: 0.43\n",
+ "Epoch: 007/010 | Batch 001/018 | Train/Val Loss: 0.42\n",
+ "Epoch: 007/010 | Batch 002/018 | Train/Val Loss: 0.42\n",
+ "Epoch: 007/010 | Batch 003/018 | Train/Val Loss: 0.41\n",
+ "Epoch: 007/010 | Batch 004/018 | Train/Val Loss: 0.38\n",
+ "Epoch: 007/010 | Batch 005/018 | Train/Val Loss: 0.41\n",
+ "Epoch: 007/010 | Batch 006/018 | Train/Val Loss: 0.38\n",
+ "Epoch: 007/010 | Batch 007/018 | Train/Val Loss: 0.41\n",
+ "Epoch: 007/010 | Batch 008/018 | Train/Val Loss: 0.42\n",
+ "Epoch: 007/010 | Batch 009/018 | Train/Val Loss: 0.39\n",
+ "Epoch: 007/010 | Batch 010/018 | Train/Val Loss: 0.39\n",
+ "Epoch: 007/010 | Batch 011/018 | Train/Val Loss: 0.38\n",
+ "Epoch: 007/010 | Batch 012/018 | Train/Val Loss: 0.35\n",
+ "Epoch: 007/010 | Batch 013/018 | Train/Val Loss: 0.37\n",
+ "Epoch: 007/010 | Batch 014/018 | Train/Val Loss: 0.36\n",
+ "Epoch: 007/010 | Batch 015/018 | Train/Val Loss: 0.38\n",
+ "Epoch: 007/010 | Batch 016/018 | Train/Val Loss: 0.38\n",
+ "Epoch: 007/010 | Batch 017/018 | Train/Val Loss: 0.40\n",
+ "Train Acc 96.86% | Val Acc 98.44%\n",
+ "Epoch: 008/010 | Batch 000/018 | Train/Val Loss: 0.39\n",
+ "Epoch: 008/010 | Batch 001/018 | Train/Val Loss: 0.34\n",
+ "Epoch: 008/010 | Batch 002/018 | Train/Val Loss: 0.33\n",
+ "Epoch: 008/010 | Batch 003/018 | Train/Val Loss: 0.37\n",
+ "Epoch: 008/010 | Batch 004/018 | Train/Val Loss: 0.35\n",
+ "Epoch: 008/010 | Batch 005/018 | Train/Val Loss: 0.35\n",
+ "Epoch: 008/010 | Batch 006/018 | Train/Val Loss: 0.37\n",
+ "Epoch: 008/010 | Batch 007/018 | Train/Val Loss: 0.36\n",
+ "Epoch: 008/010 | Batch 008/018 | Train/Val Loss: 0.30\n",
+ "Epoch: 008/010 | Batch 009/018 | Train/Val Loss: 0.32\n",
+ "Epoch: 008/010 | Batch 010/018 | Train/Val Loss: 0.28\n",
+ "Epoch: 008/010 | Batch 011/018 | Train/Val Loss: 0.35\n",
+ "Epoch: 008/010 | Batch 012/018 | Train/Val Loss: 0.32\n",
+ "Epoch: 008/010 | Batch 013/018 | Train/Val Loss: 0.32\n",
+ "Epoch: 008/010 | Batch 014/018 | Train/Val Loss: 0.32\n",
+ "Epoch: 008/010 | Batch 015/018 | Train/Val Loss: 0.30\n",
+ "Epoch: 008/010 | Batch 016/018 | Train/Val Loss: 0.31\n",
+ "Epoch: 008/010 | Batch 017/018 | Train/Val Loss: 0.31\n",
+ "Train Acc 97.03% | Val Acc 100.00%\n",
+ "Epoch: 009/010 | Batch 000/018 | Train/Val Loss: 0.29\n",
+ "Epoch: 009/010 | Batch 001/018 | Train/Val Loss: 0.28\n",
+ "Epoch: 009/010 | Batch 002/018 | Train/Val Loss: 0.24\n",
+ "Epoch: 009/010 | Batch 003/018 | Train/Val Loss: 0.26\n",
+ "Epoch: 009/010 | Batch 004/018 | Train/Val Loss: 0.25\n",
+ "Epoch: 009/010 | Batch 005/018 | Train/Val Loss: 0.28\n",
+ "Epoch: 009/010 | Batch 006/018 | Train/Val Loss: 0.26\n",
+ "Epoch: 009/010 | Batch 007/018 | Train/Val Loss: 0.32\n",
+ "Epoch: 009/010 | Batch 008/018 | Train/Val Loss: 0.30\n",
+ "Epoch: 009/010 | Batch 009/018 | Train/Val Loss: 0.30\n",
+ "Epoch: 009/010 | Batch 010/018 | Train/Val Loss: 0.28\n",
+ "Epoch: 009/010 | Batch 011/018 | Train/Val Loss: 0.28\n",
+ "Epoch: 009/010 | Batch 012/018 | Train/Val Loss: 0.22\n",
+ "Epoch: 009/010 | Batch 013/018 | Train/Val Loss: 0.33\n",
+ "Epoch: 009/010 | Batch 014/018 | Train/Val Loss: 0.33\n",
+ "Epoch: 009/010 | Batch 015/018 | Train/Val Loss: 0.25\n",
+ "Epoch: 009/010 | Batch 016/018 | Train/Val Loss: 0.27\n",
+ "Epoch: 009/010 | Batch 017/018 | Train/Val Loss: 0.27\n",
+ "Train Acc 98.08% | Val Acc 100.00%\n",
+ "Epoch: 010/010 | Batch 000/018 | Train/Val Loss: 0.26\n",
+ "Epoch: 010/010 | Batch 001/018 | Train/Val Loss: 0.23\n",
+ "Epoch: 010/010 | Batch 002/018 | Train/Val Loss: 0.25\n",
+ "Epoch: 010/010 | Batch 003/018 | Train/Val Loss: 0.22\n",
+ "Epoch: 010/010 | Batch 004/018 | Train/Val Loss: 0.25\n",
+ "Epoch: 010/010 | Batch 005/018 | Train/Val Loss: 0.28\n",
+ "Epoch: 010/010 | Batch 006/018 | Train/Val Loss: 0.22\n",
+ "Epoch: 010/010 | Batch 007/018 | Train/Val Loss: 0.27\n",
+ "Epoch: 010/010 | Batch 008/018 | Train/Val Loss: 0.23\n",
+ "Epoch: 010/010 | Batch 009/018 | Train/Val Loss: 0.19\n",
+ "Epoch: 010/010 | Batch 010/018 | Train/Val Loss: 0.22\n",
+ "Epoch: 010/010 | Batch 011/018 | Train/Val Loss: 0.21\n",
+ "Epoch: 010/010 | Batch 012/018 | Train/Val Loss: 0.21\n",
+ "Epoch: 010/010 | Batch 013/018 | Train/Val Loss: 0.22\n",
+ "Epoch: 010/010 | Batch 014/018 | Train/Val Loss: 0.25\n",
+ "Epoch: 010/010 | Batch 015/018 | Train/Val Loss: 0.28\n",
+ "Epoch: 010/010 | Batch 016/018 | Train/Val Loss: 0.16\n",
+ "Epoch: 010/010 | Batch 017/018 | Train/Val Loss: 0.21\n",
+ "Train Acc 98.25% | Val Acc 100.00%\n"
+ ]
+ }
+ ],
+ "source": [
+ "import torch.nn.functional as F\n",
+ "\n",
+ "\n",
+ "torch.manual_seed(1)\n",
+ "model = PyTorchMLP(num_features=2, num_classes=2)\n",
+ "optimizer = torch.optim.SGD(model.parameters(), lr=0.05) # Stochastic gradient descent\n",
+ "\n",
+ "num_epochs = 10\n",
+ "\n",
+ "for epoch in range(num_epochs):\n",
+ " \n",
+ " model = model.train()\n",
+ " for batch_idx, (features, labels) in enumerate(train_loader):\n",
+ "\n",
+ " logits = model(features)\n",
+ " \n",
+ " loss = F.cross_entropy(logits, labels) # Loss function\n",
+ " \n",
+ " optimizer.zero_grad()\n",
+ " loss.backward()\n",
+ " optimizer.step()\n",
+ " \n",
+ " ### LOGGING\n",
+ " print(f\"Epoch: {epoch+1:03d}/{num_epochs:03d}\"\n",
+ " f\" | Batch {batch_idx:03d}/{len(train_loader):03d}\"\n",
+ " f\" | Train/Val Loss: {loss:.2f}\")\n",
+ " \n",
+ " train_acc = compute_accuracy(model, train_loader)\n",
+ " val_acc = compute_accuracy(model, val_loader)\n",
+ " print(f\"Train Acc {train_acc*100:.2f}% | Val Acc {val_acc*100:.2f}%\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "bb0d5821-7c8d-46b5-9e7d-02e72cac2acc",
+ "metadata": {},
+ "source": [
+ "## 7) Evaluating the results"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "id": "27538c8d-61bc-47b0-8289-b6aab4aa16ed",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Train Acc 98.25%\n",
+ "Val Acc 100.00%\n",
+ "Test Acc 99.12%\n"
+ ]
+ }
+ ],
+ "source": [
+ "train_acc = compute_accuracy(model, train_loader)\n",
+ "val_acc = compute_accuracy(model, val_loader)\n",
+ "test_acc = compute_accuracy(model, test_loader)\n",
+ "\n",
+ "print(f\"Train Acc {train_acc*100:.2f}%\")\n",
+ "print(f\"Val Acc {val_acc*100:.2f}%\")\n",
+ "print(f\"Test Acc {test_acc*100:.2f}%\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "fbcd412a-02c0-4d2c-835e-4b01368f53f8",
+ "metadata": {},
+ "source": [
+ "## 8) Optional: visualizing the decision boundary"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "a76bb67c-358c-4e91-a5c7-5456333827aa",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from matplotlib.colors import ListedColormap\n",
+ "import numpy as np\n",
+ "\n",
+ "\n",
+ "def plot_decision_regions(X, y, classifier, resolution=0.02):\n",
+ "\n",
+ " # setup marker generator and color map\n",
+ " markers = ('D', '^', 'x', 's', 'v')\n",
+ " colors = ('C0', 'C1', 'C2', 'C3', 'C4')\n",
+ " cmap = ListedColormap(colors[:len(np.unique(y))])\n",
+ "\n",
+ " # plot the decision surface\n",
+ " x1_min, x1_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n",
+ " x2_min, x2_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n",
+ " xx1, xx2 = np.meshgrid(np.arange(x1_min, x1_max, resolution),\n",
+ " np.arange(x2_min, x2_max, resolution))\n",
+ " tensor = torch.tensor(np.array([xx1.ravel(), xx2.ravel()]).T).float()\n",
+ " logits = classifier.forward(tensor)\n",
+ " Z = np.argmax(logits.detach().numpy(), axis=1)\n",
+ "\n",
+ " Z = Z.reshape(xx1.shape)\n",
+ " plt.contourf(xx1, xx2, Z, alpha=0.4, cmap=cmap)\n",
+ " plt.xlim(xx1.min(), xx1.max())\n",
+ " plt.ylim(xx2.min(), xx2.max())\n",
+ "\n",
+ " # plot class samples\n",
+ " for idx, cl in enumerate(np.unique(y)):\n",
+ " plt.scatter(x=X[y == cl, 0], y=X[y == cl, 1],\n",
+ " alpha=0.8, color=cmap(idx),\n",
+ " #edgecolor='black',\n",
+ " marker=markers[idx], \n",
+ " label=cl)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "4f70038a-8bd7-4fd7-aa12-b2a4f08aa190",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiIAAAGdCAYAAAAvwBgXAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAC7h0lEQVR4nOz9eZRc13nejT57n1NTzwAxNUCQokRCBDiJlkQp1iyKlBUmtjxRGZfjrGXd6FrXg3y9LH3x52uvq3yKo0SWnZUlRv5urCzlJjLtz6RvxIgUCUkEB8uiaIggCIAAKAzN7kYDTXRVddd0hr3vH+/ZZ6pzqk5VV/WE/Vur2egaztmnqtn7qXd4XiallNBoNBqNRqNZB/h6L0Cj0Wg0Gs21ixYiGo1Go9Fo1g0tRDQajUaj0awbWohoNBqNRqNZN7QQ0Wg0Go1Gs25oIaLRaDQajWbd0EJEo9FoNBrNuqGFiEaj0Wg0mnXDXO8FdEIIgbm5OYyPj4Mxtt7L0Wg0Go1GkwEpJZaXl7F3715w3jnmsaGFyNzcHPbv37/ey9BoNBqNRtMHMzMzuP766zs+ZkMLkfHxcQDAzDf/PSZGS+u8Go1Go+mRY9/AwqVZnM7divkP/Lv1Xo1Gs2Y0aiv4tZ9+t7+Pd2JDCxGVjpkYLWFiTAsRjUazuVhuLOLJ7f8YU+/7JEbWezEazTqQpaxCF6tqNBrNEPl28WPrvQSNZkOjhYhGo9EMgwvPo2W7670KjWbDs6FTMxqNRrMpOfp1XJp/Hadyh/DgO3XBvUbTCR0R0Wg0miFwKncIcx/+k/Vehkaz4dFCRKPRaDQazbqhhYhGo9EMkgvPY3Fhdr1XodFsGrQQ0Wg0mkFx4XksnjyC48ZBnZbRaDKihYhGo9EMkBVzGx696ffXexkazaZBd81oNBrNIPA6Zc7nDuGem7av92o0mk2DFiIajUYzCGpX8FcjD2LqfZ9c75VoNJsKnZrRaDQajUazbmghotFoNKvlwvNYXLHWexUazaZEp2Y0Go1mNYRcVHVaRqPpHR0R0Wg0mlWiXVQ1mv7RQkSj0Wg0Gs26oYWIRqPR9It2UdVoVo0WIhqNRtMny2efwxuY1AZmGs0q0EJEo9FoVsFXbv6qNjDTaFaBFiIajUaj0WjWDd2+q9FoNH2w+Pi/xRuYXO9laDSbHh0R0Wg0ml559kt4A5M6LaPRDAAtRDQajaZHFlcsHC7er0WIRjMAdGpGo9FosnLheVx65WlU+BROX/8LuGe916PRbAG0ENFoNJqsXH3Nd1HVIkSjGQw6NaPRaDQajWbd0EJEo9FoMrJ89dJ6L0Gj2XJoIaLRaDQZWD78RczZY9pFVaMZMFqIaDQaTUZ+Z+qPdKeMRjNgtBDRaDQajUazbmghotFoNF1YPvxF1FrOei9Do9mS6PZdjUaj6cSzX8KcPYavHPgqHtRpGY1m4OiIiEaj0XRBu6hqNMNDCxGNRqPRaDTrhhYiGo1Gk8Ly4S/iUrWFbxc/tt5L0Wi2LLpGRKPRaJK48DzekBP48oGHdG2IRjNEdEREo9FoElg++xxajljvZWg0Wx4tRDQajSaGclH9ys1f1UWqGs2Q0UJEo9FoEtAuqhrN2qCFiEaj0Wg0mnVDCxGNRqMJoV1UNZq1RXfNaDQajeLo17WLqkazxuiIiEaj0YSYN/bq2hCNZg3RQkSj0WgUtSvrvQKN5ppDCxGNRqNB4KL65fHfXu+laDTXFLpGRKPRaLSLqkazbuiIiEaj0Wg0mnVDCxGNRqOZ+b62c9do1gktRDQazbXNs1/CpWoLh4v3624ZjWYdGKoQ+cIXvoB3vvOdGB8fx65du/Dxj38cr7766jBPqdFoND2x3HLxr7b/Gabe98n1XopGc00yVCHy9NNP41d/9Vfx/e9/H08++SRs28b999+PWq02zNNqNBpNJrSLqkaz/gy1a+bxxx+P/Py1r30Nu3btwosvvoj3v//9wzy1RqPRdEa7qGo0G4I1bd+tVCoAgO3bk/+nb7VaaLVa/s/VanVN1qXRaK5NtIuqRrP+rFmxqhACv/Ebv4H3vOc9uP322xMf84UvfAGTk5P+1/79+9dqeRqNRqPRaNaBNRMiv/qrv4rjx4/jG9/4RupjPve5z6FSqfhfMzMza7U8jUZzDbF8+Iu4NP86TuSSPxRpNJq1Y01SM5/+9KfxzW9+E0eOHMH111+f+rhCoYBCobAWS9JsNaQEVhaAsd0AY+u9Gs1G5sLzaNku/u2Bh3VaRqPZAAw1IiKlxKc//Wk88sgj+M53voObbrppmKfTXMtcPgm8+Gf0XaPpwoq5bb2XoNFoPIYaEfnVX/1V/Pf//t/x13/91xgfH8elS5cAAJOTkyiVSsM8teZaQgrgwjNAo0zfd90KMO3Vp0nh6mvaRVWj2UAM9a/1V77yFVQqFXzwgx/E9PS0//Xnf/7nwzyt5lrj8imgOgcUxuj75VPrvSLNRuXZL+HS/OvaRVWj2UAMNSIipRzm4TWaIBoiBZAbAZoVHRXRdOSvRh7ULqoazQZC/6XWbG5UNCQ3Sj/nRnRURKPRaDYRWohoNi/haIiRo9uMHHXQqNs1GsXRr+NStdX9cRqNZk3RQkSzeYlHQxQ6KqKJc/TruDT/+oZNy7hi46SxN9JaNNcGWohoNicqGiIEwE2KgqgvbkajJRsVKYHlS/RdM3RO5Q5tSBFycr6Krzx9Fifn13+kxUZai+baQQsRzfqw2k24MgvUFgEGoFVp/wLo/srswJY8cLT3yZqwkV1UT85X8djL81iq2Xjs5fl1FQAbaS2aa4s1HXqn0fhcPgmc/Gvg4M8Auw/1/vyJaeD2XwCEm/4YbtDjNiLa+2RN+Vfb/wwPvnNjza5SG7/jCmwbyWGl5eCxl+cBAAenJ67ZtWiuPbQQ0aw9g9iEuQnsfOtQlrcmJHmf9CPIrgEcAZhbTKOFN/6xggnGGMYK5roIgI20Fs21yRb731uzKbjWDcji3ie6yyeVJ+fy+Ph3tuHJuXx/Bzj6ddRazmAXtUqSNn4AvgBwXLFmqZGNtBbNtYsWIpq1RW/C2vskI0/O5fH5l8YwUzPw+ZfGehcjnovqX408uGHSMmkbv2ItBcBGWovm2kYLEc3acq1vwtr7JBNKhLQEw/5RFy3BuoqRpPExG6ld1xUSh08toGG5iRu/QgmAhuXi8KmFobTTbqS1aDRaiGjWDr0Ja++TDIRFyI6CAGPAjoLoKEZWncJZAwzOcO+tu1HKG1hpOakjMKSUWGk5KOUN3Hvrbhg8WSRsxLVooaLpBy1ENGtHt0144SS19AqxNf01toL3yZBJEiEAOoqRxBTOBnNRVRv0wekJPHDHNEyDJwoAtfGbBscDd0wPtUh00GvRHiSaftFdM5q1IWkTVqhN+MzjgGsB03cD80f7b+3dqMS9T5JQ3idTG6OmYS1JEyEKJUYWWxyff2kMwAoARFI4iy2Oz/9AYolPYnHiJzdEWubkfBWHTy3g3lt34+D0hL+hP/byPFZajp8aWUsRohjUWlS9ScNydaeNpme0ENGsDd02YSmBlQUSKheeAVx76/lrbHbvkyHiCOCPT4yibHHsH3XbRIhCiZGZmoH/90tjgAQsGU3hLFom/r3zi/jozXdiak2vop20DTpJAKy1CFGsdi3ag0SzWrQQ0awN3Tbh8kXg/DOAwQFrBchvQX+Nze59MkRMDvz6oRo+/9IYFls8MSICkF5dbHHkDYmGw2BwtKdwjBpm7bF13wy7bdBhAbBUt1HKG3jgjmkc2D2+5mtNW0svIkR7kGj6RQsRzdrQaRNWaRvGAGHTbcIGWH7rRUU0qdy31wKwkipGlAhxJQCJNhECAKi/AcexMcEaWPLaToHkzdAVcmCFoPFjZd2g1bpU6gYAvvL0WT+Ns5bE19KPCAGgxYimZ/Rfd836o4pYeY5SMowH33UnyTXFfXst/O5dKyhwicUW90uJ/EgIlygZElZKHYnr2Fji2+BM3NCx7XSQhZXxY/VqEnZwegKf+sDNALDus17UWvoVIQrtQaLpBS1ENOuLX8TqAk4DgAQ4p+9O89pq7dUASBYjiy2OApf43+9awf9+1wqm8iIiVMJU2WTHttNBDneLH+vbr1zqa4M+vbAcSeOs5waepUVXe5BoBokWIpr1JSkaAuioyDVOWIzM1AwUuMTv3rWC+/ZaqVETtFa8buj0jo943cZqNvykYz1zdhErTaenDfr4bCUxjbNRowkbyQ9FszXQQkSzfqhoiOsCdh2ABCQA4X2XArAbQSfNRo2KSNnd9yTLYzQRlODYP+r6IiR+ny9Gam/Abq7AlgYAdBUhq93w1bGalou65aDp0DELBocjBJbqVqYN+sCucTz+yqVNN+tlI/mhaDY/Woho1g/V0gsBCMsz93KDL8C73Q38NTYil08CL/4ZfVfEhUfSYzRduW+vhUc/vBQRIeH7fDHiFHGVbcPlwg0YKZiZRAjQ34YfFiFNx4UrgUrDRtMRmBrJoWgaaDnJYiS8Qd+5bxLHZiuZ0zjHZ1O8Z9aJNDEihOhJhOiUjUZ3zWjWD9XSa7eAN86Qw2o8nM05MD4NGPmN6a+hojqNcrTD5/JJ4ORfkynbrluTH6PJhNnhpfI7bf7WwYIYxUjGSEiYXro84iKE1sfgColKwwZKOUyN5FCuA03HxVLdwraRfJtJ2Mdu34PvvnoZDcvFtpFc1zTO4oqFh1+cAWPAbXsne3j1hkvcg8TkDOWGjZF8uxhMIm72prk20UJEs36olt6FE8Abpzenk6qqcSmEfE/iwkOK9sf0cp3K7G1sd7tQ0+C+vRaquf+Jf2d/AvffEe34CBdWZtnwl+o2Dp9awIHd4201DepYK00HjqA0oXqMkSBGFlckLFdiuWljvJhrixJwxtocTeNIKVGu23CEgMk5vnX8EjhjG2rTVmt55OgslurUfp/lt1S7sWoU+mOZpj8GVfMQjyisdR3Iaq4jPBsmNxJ0+CycoDRSrkjfzzzR/pherlOnddK58DwWH/+3uN18He+6/UDbRjbIwkqDMxzYNQ5HCBoPxNrvJ+FgoVy3MVY08b6bdyBnGliq222piix1FuW6jabjomBy7BjLt6WQNlJag4F08tRIDoyhY6qrl6LhjXSNmuGghYimPwa1OSZFFNaS1VxHfIifGt535gnq+LFqlHZangfMkehjsl7negu1TcCKuQ1fufmrePebr0u8f1CFlSfnqzg2W0HB5OCcUU117FickdZsOi7u3DeJ+2/bgwfumMa20VzisdPWFhchKr0Trhn59iuXevZCGcamrkQFY8Du8QJG8mbHupteiob1IL1rAy1ENL0jXOC1p4D60uo2x7SIQq/H6zeqsZpNPrx2I0e3GTnAsUloCIdeJ2HRv1XxrZHr7TrXW6htETpt+FlESDTFk8dkidI8YTEipYSQAOcMJuc4fXkZrpC+SViadXvS2pJECBBu/XVw5MwVLC5bPRXZDnpTj4sKznlknXFx0UvR8CD9XjQbGy1ENL1z5klg6TyQK6xuc0yLKPR6vH6jGqvZ5ONrB0Dtx57oEK5XzyEBMJqfo4RS1usclFDbwiyffQ4tJ9vrkbThdxIh4ehBPMVTNHmbGBGSNtS8wTBWNCMpntMLyx1FQHhtiytWoghRNB0By5WQEnCEQNOrsei0UQ9jU+/VXbUXs7dHjs7i0aOzG8LgTTN8tBDR9IZwgs3Qtfv3+EiLKPS62fYb1VjNJu+7wQoquCUXLcBq0GsCABChY0nAaZEnipTeczK8boMSaluU5cNfxJw9hq/c/FXcc9P2TM8Jb/hJdRuKpOhBXMiExYgbEiGlWMdIVhFwcHoCP3XbHghImDxZhDRsF5WGDSklDE4y13Ldjhv1IE3cFP24qz772iLqHQpz1eNNzlBrOahZDkbzxob3VNGsHi1ENL1x5inAqgfOp9zsM4qRFFFA75ttv1GN1Wzyyv+EAWhV6KtZAVpl0NaQhASaZaB+lR4LdPZGGZRQ2+L8ztQfZRYhCiUo0uo20oSDSrMkiRGjiwjJKgJu3zeJT7xjP8aKZls9S1iEcEa+f5wxTJTyHWsshuHa2k8R8HvfsgMjhfbrCtOwHCw1bIABk6Vc11SPZmug23evFQbRAqqiIfA+1av5MDzXmz9GUkRBEY4WdDtePKrRrPT+vPAmb9ezPV/5nwg3uK12BXjtMNBaASBAKkWGvnPyQuEcuPE9wNQNADfSvVGyCLXN1uq8gTg4PZHYohsXDspbZOZqHacvL0f8LsKtt3aOI2caqSKk0wRehZrge9veybbW3qYj2kQIYwyTpRxKOXKTjR9brXEQ03GTJhUnvQ7hSEdS6mv/9pHUx/siBMBUKYeRfHR70lN9ty5aiFwrhA22+t3A/GgI/eHzoyJmqbfNMR5RSEJFC6b2px+nU1Sj0zpWu8kr/5MwwgHcFvDj73mCw4zdZwH5UaBRASoXgAP3p4udQQm1Lczy4S+i1nKA0e6PTSNNhDQtF5brwjQ4xgomynUbR85cgcl52wb42MvzWKrbKOW7ixAgfTNVxl4feusu3LZ3MnL85aaNhi0gpISRIkLCx16qUyRHSglXyIGYuKWZjqWJkbT6m7THCyFQbtiApPbfuAhJusY0vxfN5kMLkWuBNPfPXghHQ5iXnAYDICiSYPQQFUmKKMTpFC0IX1OvUY1hbfKMA0vnSKTlx9rvr78BNJaAwkR3sTMoobZVOfp1qg058FU82GNaJo76pB93TJUg23YrZ9DPEnClRMNq37jjm3SvTq4zV+s4NlvBStPBN16YwftubuD+2/ZENm1HSEiX1su8tEVYhAChNEjOACDRtMWqTdyymI4liYtORcBJj69ZLkbyJpj3nkgpUw3e9CC9rYcWItcCSXUUvUZFzj9HxZZgQSsqQBu5a9FGnHVzTIoo9Eq/UQ1/vo0EGldp3fE/eP1s8pVZYOUKvTbNcvSYEt7MHE802U5nsTMIobbFmTf29lwbEkd90j+waxzHZiuJtu0rLQeMAQYHhJSwXAAxMRLewHt1cl1csfDM2UXkOOBKev6RM1cAoE2MuE0HApLmQXbxQlHPURu9OmfSc9I29bQ0lbruMN0iRHHSHh9fd6dUT1o7tGbzoYXIVqffOor4Ma6cBMxCYMwVxq4DozuAt/79tdkcVxPVUJv81XPAzPeB/e+meo0w/WzyE9PA/nuAC8+HjikpCtWqAuefAYwCwExK3VRm08XSIITaVqZ2BcDqagPUJltvOXimukixPe/3yPDMylT3rpSAZAycSbhSwnYB00mOEKgizt6s2xlsQbeZHHAFUsTIHBotat8te7UUI3mzYxsybfQWbFdiIhRF6da63Gt9S/jnrLNjOj2+W6oHAL7y9Fk9o2aLoIXIVqffOoowlVlKLXCTPtnHMUzAaVJKgq/Br9RqUhfcBHbcApz7HkV4yheA6TtpsN5q5rio1IzdCGpALp8Czj1NAo4bFJGyGxQx6bXAVwMgqA358vbfxoN9HiO8yW4fzWNxxYLlhrqQhETcgFSlRKhLJYeiyVM35SxFnMqwzOTU+quKUBljMLhsEyP0RIacyVHKG1hq2L4YcYVMFBQHpycwc7WOI2euQHgTggH4a+9FhADZ6krSioDTSHp8t1SPuk/PqNk6aCGylVltd4hio6UKsq5nfA85rsY7hcKpqvIF4G+/Atzxj4A9t/W/psgxZ2jezMXnKP0DACPXeV4jK57ZGe8cFRkEW21Y3oXn8YacwJcPPNR3bUh8k206AnZYhCCIhKhXTGkSKYFS3oh0qaTVV3Qq4lQixGBoEyFAuxhZXGlhrtKEI6LCYKlh00ybQvKkW2VJXzSpzkV4Q/kaBkMxl5w6GcSk4l7rNpIe3y11kyVdpNk8aCGylRlUC+hGSxVkXc/CifZOoUiqqkQFpFIAp78F7D7YX3QiYk7GqLPoxKNkYgbmdc2oL6+eRjjUcTTMqMggOqW2EPFNFgAqDauT80sbLceFlPTcbkWTaZ/sW57wsQXAQMZkSRu+wSUcARyfq6KUMyI1JyWvq6TcsBPXGb7WqZEcmo6Bct2CKySaQsLg7b9vg5xUPAjiqRugvR1Zt/NuDXRMeKuS5v7Zi7PnZibNcTUszuxmcPvyHAmXfvCPOUIRDwhKZTkt+NtZc4lSMlLQbVKQKFm5km5qthq24rC8me9ntnOPk/RJv+kIuBkPx0Cf3MeLFFnMMp8GSHZyvXXPWFB/gnQLvPDabLc9+lfKm9g9XgBnwGPHOs9zKeUMTI3k/YnBtZaDR4/ORozBBjmpeFCoOT1AZ08UbXS2udFCZKuS5P4Z/gI6O3tudpI6hSKpKjNwOAW8qMjjyRt2p6F6agCg8ObLuLYX3fDERnGKvniOBGBxCihtp+9mgQpch5HS6tdxtt8Bgl3oUz8EPPslXKq2+nJSTbIjb9gulmoJ9U4pcE6+Hd3qK5IIO7neuW8S85UW8kbwp9cVQaGswnGlL1A4AyZK7XbvtC4OgzMsNWj43bHXy51TKwiydCtWuxiJO8cKEX3jsg4JHCSnF5Z7mmmjxcjmQ6dmtiobra5jLUnrFIKIRkOEHX2eiorsuT16e6cUhxoAWJjwoiEy2MSlQ//Oj1LnDEDCQFUfNMrAlVPAW+7t8fq61H6splNqCOmcJ+fy+OMTo/j1QzXctzf75h9mueXiX23/Mzz4zuwt1cojJN7JYnKGpXpySiMNg3Uv8uy0hoPTE3CFxOOvXILjCuwYy6PadLDScrzHAeASnDG/MDbHORwhUDQNFM3k963WslFpOoAE6i0Hf/HiDAzGsWMsKlwatoty3fJs4QHTYLBdiZrl4LFj0bSG+v7I0VksLLcwVcqh1KU7Z1hstHSRZjjoiMhWRdVR7D6U/rXzrWvT5bLWJHUKVWaB0094qSqDRECcpKhIpxRHeACgVaNUjIwF21tVz3/FEyh2M7iPmyRizjzZ4/V1mTbc7xydAaZzVATkybk8Pv/SGGZqBj7/0hienMv3fcxeiA+tU5/0hQSu9ihCAMAREldrVk+bcHgNJ+ervghRn+onSzm/VgUgMeK4tLKiaWCsaOL9t+xEMSVVUq5bKDccSAmM5A20XEo12a5AuW77jw+LEICKcR1PIE2WcnBEciSBgX5llxo2Gpaz5iIE2JjpIs3g0UJEs7UIRwO4GQzmEy5FEQAaPCed5Ocvz0drRTqlOM4/S4WpYF50JSHjL2wSIxJ0X2uZ1iY8R1q/lidlPUA0XdJNLKxmWF6/6ZwYT87l8fHvbMMXj4/g8y+NoSUY9o+6aAnWnxh59ktk556RtKF1qzHAKhgcI4XOJl1pawiPtI+nFuJiRAIwOUfR6xK5/7Y9uHPfJGqWGxEX5bqFmkXRTgYSG/CiHRJKfJCACIsQ/zwSKOUMjOTNtrSGWjtjZLcOAEt1G0JiTUWIIp4u6mbmpgtWNx9aiGhWz5DqCvoiHA1wmkB9MeRxkgNu+Mn2LiIfTs6oZ56gDTue4ghv5lIAr/+QnpYrBc9PQtigQXiSfFgaS9TW61oAGEVMzj/X4ZpCERB1fflRr004FhXpd6pxp2vtARUB+fGygf/86igqFsOOggBjwI6C6F2MHP06LlVbmdMynabdnl5YphqJnq6INncKD2R7ZqRjpWSi7kUTDM4SUwttkREp8bHb9/gzaI7NVmAwhqZD4iIuQiS8Sbyc1qrESN12fQGRdE0N20XDdv20hvLl+OaxOV80jeRNTJVyYKz3122QpIkRLUK2BlqIaFZPt1TBWhHuFGIGRR+ES9+5SX+pF09RB0si3qa7skCbfKcUx+UTwMolAJKEjpq7A3hDAZlXoFqg7+BA6TrghvcAN99PTrRmkfxFzCI517ZFNySd7/wRioCcP0IOrVJQrYddB86EUkmr6ZTqN50TQomQis3gSHInrTkcy7bqcOhPjJzKHeoqQlwhO468/+axOX9my1Qpl/ma1EZvuxK263YthoyvoeUGKqDcsFG3kiM7E0UTpZwBgzO87+YduG3vZORYO8byKJgcddttEyHBa0A/KzGC2P0KVTcjJfmKKKFkcgbLEW2D8ka87hzGsK7FoEliRIuQrcEWLBDQrCmDGKjXdsw+jbjCnUJ+xAH0vXG1vVMm8hnPG+ZnFAAzT5GRNDO480eoJkS4JDqkGz2W2uiFQyJEukBxHHAawPzRIE1TnKRjcpNSQnFfl8sngWN/TlN986NA+SLdbpa8dI9XfKsKbPt1nB2A8V1YhNQdDiGlNz+FYb5hAHAxkZe+GFlscXz+pTEAK30XsCpow56D7dDx09xAhZSek6nEaN7wN/Q0VIcJy+CmGqyDhMNo3kDTEaiEfT4kItbs/s2h+oafObQXd14/hVfmKvjW8WhNScHkaNiBiFTHDQsSV9BcnDTCIsXgDI4rUW7YKJgcJufgsdfPfx7nGCuwdffs6HWmjWZzoIWIZnUMYqBe2zH77NxQnUKuTemV2iJt4FYdGL0OuOWjQOV1sl3nOdps1R9c4dKG/6b3A9tvIqGRluIoX/Q8QuBNIg5FGBinNJCRp2NAAsgDuTGgdQn+wEBmACPe/35Jm74UFP1oVekYudHAl8RphjpzvFTS7kP9d0q1pXMkma/lSpneUyVCmi5D0yXL8hxTm7iEI5LFyEzNwB+fGMWH9lhIbArxWnaRSz/3yfkqHjk6SzUkDF4aId0NVHhlPAZnHcVIWISEJ92O5g2UG05bZ0ZYhJic4fKK5acP1AA9IQEWEyPhT/V37pvEkTNXcHy2ghPzVRRMjm0j1P1Sadg0gA/RKAcLfQ+LEYXXSB64wwL+ZFv6Tr9KlhdO2T6a3CYcfh2H0Zmiuouy0OtMG83GRwsRTf8MYqBe2jH7ibCoTqGFE7SBhyMOrSr9ta5coMc6dcCYpLSIouXQ/bd8BPjh/yd5qB4zvM4XL/0DiSAt463TtaidVzj0mhSnSOTEu3HsJh3fMNvdbi+foo4a3xCtDN8MLU44KtKrA25SOkfNwylOBfenvA9KhLQEw86iQNEg0eFI+uPCGGDyqBgZz0kstjim8gK/fqiWLEIuPI/FFatjbcjJ+Sq+eWyO0h3eTlxtOr6BV5jwJlrKc6/eQySKkTQR0rAclBs2RvJmpDMj3GJaynGUG0FdhopOMG99KhhWadgomhw1y/VFyLHZCqoNG3Nl6qxqOQJNR/hixXtqRHSonxG7XaF+4zijOhIpAReAARJGEsBowcQ7btyGH80sdR3UN4zOFDUFuRdR0etMG83GRteIaPpnAHUFqcfst3OjU9fI2cPA8mUSCsKhzbZZbjd5m/tRuhlcYwnBn3evi8X/OZSScVtB265dB5peZCNYKB2rdgWwGtEaDuFQNERFXQAvkpJSDBwusO2V8utUaAxJ19esAK0yHbNVplOmGN85AvjjE6MoW9wvSJ3IS0yXXHDG4HgbHwOJEVcClxocV5ocBS7xu3d1TsusmNvwph3JhcUqAuF6NR+cMTCGYJ6KHRUX4U30gTv24oE7qdaAM4pyKPxNPUGELDVs/3rCqBZTw/MnCReHuoKEStzBNW9ylBtORIQ0Wg6c0JOFBJZqlj+szr8WIJ5UjHwH0OY7Qt04QUuuqicZzZv42bv3YXGlhXLDQcN217QzJa3DKQtahGwddERE0x+DGqiXdsx+IyydukbqbwA7DlChqartuPG9wNQNweO4AWy7ESiMJ6c4ls4HqR2z4G3YVfj+IcykYzQrgcuqsJM7ilSapln2ZtCANv3zz3nRkB6ERXUOWLoIbH9T9ucAgQBTr0P5ItXA5Ay6/hvfQ6mqBOM7kwO/fqiGz780hsVWVIwArhcZkTBAtSIcQMmQKBrdRUgnEgezeekLQPpiBKAW1bRNdOZqHc+cXYThRUsAwHIEHCGQN5i/mSsRAlA7qytkYp2EI0SiVIx3rTAAkECpYAQixApm0IShVEr7MX0x4qVW4g9pekYuKkoiJSBDw/QkgKLB8bN378PRi0s4PkcCwHbpvQOCWpFhixA9wE6jhYimPwY1UK/TMXs9VjzNIFyKKpiFIOJw5SQJheIUiYXKBeDA/e1CJynFoY5v5CntA9C5AACcilFHdwA7bwV+/F0SK4VxT6jY7cdTME4b/tQN1Nnz2vei0ZCOqPYIlwRWL0JECuDi81RDo1JSF57J9vp4kJhY6ShGbEHOpKOmwGQ+gwjxakPO5w612bknFXEC8CMXcTEipYQrZNsmGm6LdaXEO27chv3bR6j2Ydc4js1WAhdWJUJKuUhdh9o0AZr1YmXwsVcf4luOgMFdvPR6GU3bRcsRiW22nZCgyEfTTj6vn2ICiaGgDoNOlDM4nj59GRevNiLPi4uRYYsQPcBOo1Mzmt4ZxkC91RhxKeJdI7VFoPEGfW9VSJjYDRISQO+ppKT5Pc0lEhpOg2o9nCawcNyLprgUIYpbyccRDlA+T5EfIYDKDHqKhqjPwxee7WyMFieeBjvzVF+ptvv2Wvjdu1ZQ4FT7oT7Bj+ckRkwBzoCcIbOJEI+/GnkQcx/+k8htx2cr+PMfzmClmVzHUMoZmPSKVRmjjbfSsGHydhESbosdzRs4NkuRoU994Gbcf9se34V1qR4VIUB0tolvViYEJks5zysk/bpUagQA6paLWsvpS4Qo0kQIEERJVLsuAN8+fttIDg3bjYiQ8LJtV9I8Hm9Q37BFCKBnxlzLaCGi6Z1hDNTr14grjOoaufMfA3f8IkUXAPp++88H3h1mKdgNRA+iKXz8O/8xcMcn6JjMoO93fALY906gtUKbO89T144fTUjboSRw9TwVnPpryZr/Du1g3YzRIk9LMTATbl9CMEmMLLY4JnMS/7e31vDmMXfV6ZjHX7kEDgZHCCzVrbY6BsATI0XTT12M5k08cGeyCIl7jTz28jxOLyz7x1IRhbAI8e9j1HUTNisbyZskhDpcR8hWBBKA5cqICOm36qFgciSVTAgJf76MEiNCAtWmHalHSTq/7UpIKddEhPjn12LkmmSoqZkjR47gi1/8Il588UXMz8/jkUcewcc//vFhnlKzFgx6oF5ShMU/TijC0q1WRHXNAMCrj1N6g3H6Pv8yRS4KE7S7qM6Q/Hj29E/4+ECoO2ci6Mopn6PvxSmykm+WkVxOGMO1gLNP0eA81+r8WFqM910JBK9f9vIJ4Kb3RV+nJF+WuPBjnIzfilPR0/SQHgunaWZqBqbywhcfv3montwdE8frlkGomSkewSjXbTQdF0t1y29vDS5VwhESo3kTeTM9EpLmNfLYy/OwXYEjZ67AERK7xwvgPHnhnHNMlXJYqtt+F0zR5HTcLi7DkS6aEH0GRtByhDcoj0EgWhzrKiWC8G2x9aScu+kIHL24NBAhogfYadIYqhCp1Wq466678C//5b/Ez/3czw3zVJq1JL4hr5Z+jbjSUMPoIIN5M/M/ok2VmyR4lOuqXadajtee8oYAGt2OTiQV1p5+gr6rzT0/BlgS2HmI1rJwvIPIENS9su/tZHpm17tdZPRHxgAwoDqbbIwW9mVpS4NJzx3W6/DJjQSCpRchCE+MyGX81SsV/Nxtk7hvL6U2MomQo1/HpfnXcSp3CFPv+ySAZPEwNZJDuY42MRIvqkzz+ej0Sbxct/EXL76Og3vG0bQFapaLsUKyNbsvegom1RlbLsYKFBVJmu8CRNtoBwVn5EnSsF24njdIHLdD7idNhCiOz1WpNTmf8f+NFOJTkNe6TVizcRmqEPnYxz6Gj33sY8M8hWYr0EuEJYvr6pmnqACTqT+c3gwZt0VCx3WirqtSAksXaIjdmz+Qbc1thbUlckflOaDgiR/lYWKvgCIWyl4qTGgbcC1q5y1d53mVyODahWoT5nQcVSzbWgZyRc9OntPz4sZocV+W+Npd26stYVEX2jA9CMH7zJfwkfxfg5k/A6C3guVTuUN+bUinCEaSGEkrqsz6SbzpCDQdF0ICJy8t4z1vuQ7H56qJm2Zc9KgOHMeVmBrJYWokj6WaFXm3lQgJY3IGkzO/y6UbaaIhb3JqCa5bbdGObnTTRLfvnVi1CFGEnVGzvK7x91GLkq3JhuqaabVaaLWCboFqVecHrwl6ibAsnOjsuhqJhoRqRIQg4XL7L1AKxHddrZFIEaCOmnhaI4mkwlrhepbvnNI+rQqlOZQTq1pb+8HCi/cKVT2zCiWkpPCS997PBc8uHgBGtgdrgPecuDFaxJflBHDhuWgajJmeeZkXERndQS604dcha6rNe23YKi3/s0QwwmJkccXCWNFMrGfI8kmcptVakJIenzcYjs9V/fba8PPimyWAyGC6pToVgxqctfmCxEmq0+iEerQ/S8arAak2bIwXB//n/IbtJfyTd9040GOmiZFOIqQf0zPN5mFDFat+4QtfwOTkpP+1f3+GMLzm2iH+6T6pgLItGgKvh9EAHAuYPxa4ruZKtEm6Fs2XUfNeupFkiW6t0D9dm46vhu3Bq1FR9uyJeGkVwDNDi3XZqGm/6vOwU6fIh9Py/FASupbOP0N29udD6SNl6rZyJVpobFUpWiSsoPOnOElCRn3tfCsdO+tr06sh3YXnsbhAxc3hCEZa+B4IxIjJOQSCibVJdBolHxYhnJOR2baRPBxX4NhsBXfum0wdtAYgUr9ico6G7eJStZlZZPQqRjiLGq6p+THVpuPfPwhMDqy03KEUjPYywG41pmeazcGGioh87nOfw2c+8xn/52q1qsWIJqDbXJtwNATxOLi3ic//CMiPBB0hKrKgNvVun+KTCmtdKyQepNeu66U56ovwp+XmSl4ExjM/A6izRtWlSNczQWPBucLFBNKl+1wnuD8pjQJQrcjfPkSPKXh/1JWp25veC0xcn/46cwMY30M1K70MHlyFId3y2edw3DiIuQ//CQygp1qCsaKJn7ptD27bO9nxHEmfxJuOaBMhypNEFbAqMXJsthIZtKaOFR5y53i+MupXLykdAwTdKfHf0PBtqmuHrjV0OyOztUrDxmjexKHpCZyYr3rRnKBLpt+WYID8SbaP5ofq65FlgJ02Pbs22FBCpFAooFAorPcyNBuR+CbXKLcXmM79yKutYPBdS9uO48IPBKoJtgD84s9uHSJJhbVSUkRFyKAYtTgJ2C2ASYAXKQ1k5Gm6rxIX4TQI4A3quxJtYW5VgvoNbniigrU/P7LRCyqcrbxOt0eG6wFYOgfc/JHO4qBbCiyJVRrSfXn8t/Gg9+/V1BIA6fUE4eOq7pskEQJEu2mUGDl9eRn33rrbP4bjChihIXfxvT9NDKj24vhtYUYL1PmjjNkYaJ1Fk6Nuu6R5pcRcpQmTczhCwJUA92bt1FpOX104Oc5w3Rj9HQ53r7xl5xjyXaqOe63j6DTATpuebV5+cO4qWvWVzI/fUEJEo0klvslxk2zQzzwJvPWn6LY9twPNv9+e2gBo8597kdIl+dGgcyaMXQcw0v4pPlwg26mwVtmjmwVaJzPI8MzIUcTFjbmlhtMgAP3byFGKBKBzSBd+NEc4FFEx88Hz7QbdPn1X8PF54QRFPlQbqd2kaAyQTRz0M3hwCJb//dQSAN3rCQ5OT8AVEn/+wxkIryYkLkIU4VbS05eX8cn3vQWvXVmJiJBKw+4r+hCOfISfbnjRjIbtIm9QvUpLShRNAwWTo9yk3+9tIzk4QsJyBAomhykYLNdFMUf+Jv0GRATo3EWT+90rB3aN46vPvNaxRqPfOo6kAXZZW63V8zUbh/IzX8Vn6w+jYQk8lPE5QxUiKysrOHv2rP/zuXPn8KMf/Qjbt2/HDTfcMMxTa9aTLJ0tPR0vtsmplIq6/ZaPkDAxi8DN9yavoTwDzP8dbeLWckrNhlfQGt+o4+2vnezfuUFtuwBt/q0VEhRv+kmaYRMnXAQaFzjSpboV4QKzL1IaZnSnJ7y8Tb36OnD6WxRtUa2554+ELOIlCS6zAIqqhNpxd76VIjDx96lbCiyJToZ0lVngwt8AN/5k++/D+eewdPK7uIzteNON7QPuksRINxHy2MvzaFhux43q9n2TmCs38MzZxchcmThJraSqfqWY432LEAVn8Cfy+rdxBiYlhJRY8tIv77/lOrx4YQnlhg0wYFsph1LIbl4JqhxIhPS7JpNTlKXSsNEwGEp5MzQPJ/01zfq6p5FFhCi0GNk4PPzCDP6w/JuR2yZFGXumr0f1ll8A/s2vZjrOUIXID3/4Q3zoQx/yf1b1H7/0S7+Er33ta8M8tWY9iW/cqz5ebJNzmsFAOatOBaoqKpK2hnAkQ7rAj/4bPS5c1CqFN5smH2zUKwu0sXeLDiRtxAyUmnEd4MoJ4K3xFEqMJIGz5w6KcMx8HyhtIxEFHvUDibfmVl4PrUHVqsRqSWqL1K588fno+9RPnUc3QzrXpveiNAnsvj363HPfQ17UMf8Tf4B7dkXnyiiy1BIAvdcT3H/bHuzbVsK3jl/qmv4JF8Lee+tuPHp0FuW6nRrVyIJ6jnq5VJ2JSm9IQd1T4doR5fRaitnNr7Qc2I7w24D7qRExOR2Pg+bztKTEW3YWcWy20vE1HWQdhzY92/j84NxVHHj9LwEAD9UfxmjBxPjN74k+6MafBFYaCc9OZqhC5IMf/GCiDbNmC9NPWD/L8fxBdiqlIr2OETsaFUlbQ7hF+MdPe+mbhO1D2IAwgo36x9+ljbwwRlGVyyeB3bd1XqNfA9LwCksZRTYWTlD6qJ/rTxIGaa25ALX1qnVYNaolOfBR+JEUxmiKcPx96qfOo5MhnSrmlYI6dnYdCqW86L3MSRe3XPwG5ne+BzIsDEN0qiUA+q8nuG3vJDhjHdM/d+6bxHdfvQzOmH+M+MTbTv1Qnf4Cqrdo+wiJi4btotIg+3XOGSaKJpq2iyNnrqBoGolOr4zRLJlll6b/qv04qzhSjxcySAsxBpic48R8FUXTwJQnCuKvKYCB1nFo07ONyQ/OXcX5xRrub34Ln1Xio2AA09cDd//zVR9f14hoBks/Yf1OxDe5sBkZvPoJNWNFmZF1WoOawGsWAHOk/XyqAPTATwHnjtDGzzjNp7HqwOnHgV0Ho+IqsYAVgF0DZdwZnfe1p2gdvQizNGGwcAK4+FxUoChn1/xY1FuEm1SYqyIpAD1/eT76Gu26tb86jyx1M9ykupVIyusU4NqoszFsq76K6SvPYW7X+1NfiqRaAmD19QSd0j/xtMTM1TqOzVbAOUUwalYHEz50ESHedx5qj1F1KstNG+PFHIomx3KTUi2W6wIs13achu1S664nIFRpUC8fAZUzqyOkX+zasKmQt+m4aDoGSjkj8po+cnTW7+wZZB3HaguVNYPhB+euAgDOL9bw0NVfxmiB5ML4RAF472c6PbVntBDRDI5VtG+mEkmpCK+zxDMjU9j1wIwMSF8DGPmI1N/woisJA9hUAenVc1QMC+l9cq+CbNjnKfIQTjEkbcTlixRNETYJA2ZQeiSLMFP1LaM704XBmSeAZjXd2bXTvJ6010gKoDJHnT3hvo5uUZE0Q7pw3UxxMvZewG+1tlgBeYiuUREAmUWIotOmGO7wODg94bujNm2BsWJQGxFOOTxzdhEGY9gxRrbyrmhldkVNQ0ig0qAC1FKONnw1s0ZKiZzBIKQEZxxXlpuYKOV9wSKlxHLThitk4C9SNFFp2oBUniPts2UUJqdBfC3HxWQph+WmjYKpRIiE4d2/3LT9NTFGbrBLjWAy8aDrOPotVNYMhodfmMFDV38Zpvf/x44hiI8wWohoBscq2zcTCW9y/pC5yfZP/GEzsk6j7F/9XzQhdzLuoyEpTVGaAsqvU/RCxLxBGCexcfqJaIohvhFLQWkP1wYgKIIzsoPWnkWYXT4JnHgUuO4ARVvUtUivc8YoBqKjGPpDLFx6TLOcXCSsbNpby8mv0ZknaK3WCiCngk6bHufNBNfR4fcBgLj8KlyvCMIyJzNFRcL0U0/w1MlLOLB7HKcXliNpnpPzVbz0ehkGY3ClxN7JoDYiOqVX+rbypZyB1ipFiEIIGREj4U23lDfxlp1FnJivQkigXLeAkXwkQlFuUL3KVNGk+hHG6HEgORmuGeEMGMkZaHj1KIwB40XqGioYDIs1C0LIUMSGYbwYvL5SSiy3HO/foDV6a0l73fup4+i1UFmzOsKFpx8WZewZsvgIo4WIZjCstn2zW6dNlgm954/AT4PE13DeMzprlIHFU9RdEx5wd+kV4MffAQ5+HLh8PCRCQqiYd1JUJMzlU140xTMyc22KsvTSOlu/CtSeo04gFeFQ1vFmKbCTV5ELniMR5bSAG98LTCV0pXEDGN8NnP5f7a9Ra5lef+F4EaAyiZLwW9HL4MFOvw/njwDVOUgAF8ybsG0kDxcAnEqmqIii13oCgzO0HInDJxfa0i0/vLCEuuVgqpRDw3LbaiOAdlv5hj0YEQLQuxgWI6p1NpweKpgclishhPTFSNHkcIXEWN6EBLm0SikpYjKSR6VB0ZJwmmYkb2KiaMKtW35bsOoa4pyjYBqwPdM8IYGxvNHmrzJeMLHUsNvSMkmv+2rqOLIWKmt6I1xwqnio/jCJj/3vphtu/Mk1W48WIprB0Kl9M0tUpFunTeV1cvoE0if0Vudo48uPAfC6VQzTm/dywVtPIeo/ooTF6W/R5n/iUYooJCE8M7SkqIjCj4Z47bPKRbW1TMPsXJs24k7dN5VZr9JQkrBQ67Eb1PFjLQfrcSxq3QXotRcOULkAHLg/+fgLJ5Lfp/wYiQ+e88zZXODG90QFTdZ5M+o60n4fyhcBt4Umitg2kvfv6icqkrWewGtAwUrT8Qs/t43kUK7bePr0FXowA7XHAm21EQolRi4vC4gBFuKPFUxquxXJrbOUHsqj6QhqGfbESNE0UIw5varXoWhyWCbHilfHwj0d3bBduEKglDfxrpuis3SajkDdis5EqlsO8iaPpIMcITGap6nDrid+hlXH0a1QWZOdh1+YAQA/7bJjLPj/b1CFp/2ghYhm9WSJVnSKimTptGlU6Lg3voc+kas0ivrILgVw5ttAY4nOaTVoAy9O0XRa5asRXs8tHwGunAaO/bm3uUug8Ua3i6VvKws0oG4q5g1SmQ2G3IUf79u9O7RBl1+nDT8cAVLrcm34s2UYo2sGIwEjQR4qRo6EgV0PbOoVaZGLtvdJBGLNMAPr+MJOSiN1EjQdX6IOvw/MoPdCCgiwyH0uzwMyW61ImG71BEqEkPOo9EVGtcmoFsI7Dkc0fQFEazcU1abT83yYTowVTEyWcqHpue2ts+qa1DpUpKPpuLjnpu2RzZmiBxYsh5xWw3EIg8M//rtumsT9t+3B3qkSHn/lUsRp1uBBwWo8ApM0a2fYdRxphcqa7qiOl4eu/jLu5wyFnDGUgtPVoIWIZvV0at9UdArrd+xy8SIWF5+jiEDlAjB1PW3K4ehJeYY2ZAYqinTqFD1olQGbNjiq2gv7jzxJoqFVRVCc2WWDYTwQCY0KYMTmsYztDI7BTYoscJM2YAbA5SSOmktUrxK+BhUNUfb03KDnXz5BxbncAAqTZGw2cl20HTdMWuQisQOp5RWnAv5MHGGvrr6n0++DcCG96zPhwmxdbnv6eO0ipqqnsDR5W9t9aaTVE4RFiOVKvwBTeLUNkaXJ4DdAzWuRMlq7IbxNdlAoEaKOj1Ie1aYFgOHkpWWM5HikPsN/HGjibs5gODZbwf7tIziwe9wvun369BX/N3kkb6CQM0i8SKoJKZoGjs3Se3P68jL2TgY1KGGnWWUxnxSBiYufYddxaBHSGz84dxWfPf0g7vdet0LBxPi9v73Oq0pGCxHN6unUvqlI2xy7ddpcPgm8/HDg5VGZpbRIPHoSXoNqGc0ZtNnmR0EFpy5FJLj36f/c095HYPUnO8OnXCUShAOcfZI+3R/6eLBZv/a9YIAeY3TdUlD6xK7TNbQqwNmnotcABNEQVf+hNp+q18lSnKDbChPt7bhZiLxPgl7H5XkqpIWkbqLCGKVnGOvfnr3T74Nw0XrpYfxF7mdxw8F3JEY9XJ5DZfxA9vN5xOsJDM7aRIjqLBEpEY2wHA2Gx8mgawRA3uCw0tpQeiAsQgDVhmshZ1AtiBErEg2jOmsAYKlu47GX5/DUSQNv3T2OFy8s+Y9jDGg6AoWc4XfFqLbgct3GkTNXwABc8ubVCCkxEbK7zxKB0XUcG4cfnLuKT539JAAqOB3dwOIjjBYimtWT2r7ZpQAV6NxZsetWKjJtVQEwoLSdIhnL89Q5E/7ErtYQaRmdok/mzbJXA7EcFKgyTgWk/SK9Vl6wYLNW54b0Iieg+yG8OTbSS7swwJonQRHu6PGjITLUkWOQ6HGaAPecR/ud4ZLWgaTSUfFupH6jImm/Dx72icfxf43+Izy4e/CTtYNNcQ62QyLTdsku3VAipEttR1yMMFBXCUBRFM5BFjarIG9wTBSDP78N20W5btHcREGzY3IG71iEq9ZjcAbbkVhpWjhSpUiIBA2vk5C+ZftkKYedYwUwRimppuNG3FcdIRJn7oQjMJwxGvx3MFp8qus41ofyM1+N/PzZuNPpGhacrgYtRDTDo1sBardOGwgqMpUgq3RVrCk8IzMpKfJRmgLGp0nshIWNlN7jvWFx5DvZm9OT2pLCA/CKkySIpENiR23WtSu0xvj0X3/CL/Mm6SKIeggn6Ohxbe/+0Br9TVNQ6innmbCtJnUSiUKVKDIDAEWj9/qeXjn6ddRaDtA+VmZgHNg9jqdOGmhYNraN5JAzvQJPKcGkhJsl8BX7uWAwP9VjraJllzPg0PQE5irNSIFouW7RFGCvzbblCDAAZooY6VT/os7jSvJJ4SExAi8Co0RPGOVnEq5FURRNDjvHkTPTO2B0HcfaoApO/7D8mzTXZSI0sX4dC05XgxYimuGQpQC126C00094aQ7v9lY1CPdbKyQIyheBH3wVuOPBdmdQZS0OeO24DP5HWZllM2HUPhtcFLXO5kZILAkZEhNH6CFJjq2tCj1GDeazanRsa4VqPioz9LO/XhnaCUO7RWuZPEQYW51ICL/ualKxFFR7YiT8SeilbbcTz34Jl6ot/NXIg3jwnYOPhigMzvCRg9G2XpRyqDRsPz2TtdY0bzDkTQPlhuObO/lttKGNPwkG2sAlPGHBgPfevAM/dfu0b8QWLhBVOkN1tzRdgSLaxUhYhEBKOFK21b8olGmbEiNK8KiHMEa27q6kc8Z9SoBA9OTM7ikXLUKGg3I5/dTZT/opF+SA8Xs/t84rGwxaiGiGQzer9yyD0lQ7Lje8OLknJrhB97sOCRWnSVEFKaLChue8wtAyCYH8GNVqOE3Pfr0bDLjlo8DYDurIqV+l67Eb7YKo8jqJgbhjq+tEPT9cT1gpfxHp0m6QGw2KaQG6Xf3bP5ZNRa5h/5NeRUI4GqJe59I2ivCMXkfXGxc1vbTtduGvRh7E1Ps+OZBjdSKpeLVXMcIA5E0D77hxG47NVmA5ApwBEyN5VJtOx6JVJUIMg4Mz+M6sx+equPG6Ub+o9MiZK34tioIzgHFG5mkJYkSJEMcVfq2KBPzUk8FIgCh8B1kpI9esRAhjDAYkXLSLkXiXjE65rC2q5uPDogxTdbxsEfERRgsRzeDJYvWeaVCa59uh6izoTvhz01W3iwSlcKyVdmHjb6qMOmmE097umkauCGx/E23SaoaLlHQeyEAQqVRRaQq45X4EnSxeQWhtkV4H5VoaTvNYy0BhiiIsN77Xc3wNFZIWtwF7f4J2DcYpBRUWIr2KhHA0xGkGLc5FrwCW9VgAu4HpJEaEkB17pDgj63JHSPzwwhIgaQhdmtdGnLAIUZGM8WIwmVbNrCmYHJYjInNnVArGNNrFiCrCtWwXlncNjHn/h0iAQ/pD8MJixHGjpmZhEUI/t4uRasOCkze1CFkH9n7n1zDtzvkCZMdtH9g09R79oIWIZvBksXrvNijt3PcAR/VTutFUivQ2gbDXhtMiwzOzEBU2UnqeGznvu+kJEUa3SeEdzwSJHa+Fleeom2R8D/B3/zUQOHbDG7oXEkgqKtKsINLJUp6hzd4w6TlOXS2KjqfqQlR5YfkceZtcPhUUkgqLTMVGr+tc9JuFcBSKGUBriV7/1jJd66DrQcIc/TouVVtAwpzBYZIkRhoGQ0vScDe1WauXVUUnprzUhBACC8stSAlMjeT8eo5u0RTOWUSE0DmC+StqZs1YIbCJD4sQhWkw2K5EyxUwOEcxx9GwSIQAoRQLQusPiRHHEytx1WUknEuJEcd/HBu6CAnP+7lWiRec/lz9YRIfBz1Tvy0sQBRaiGgGS1ar966D0nLAiBeBEE7I6wMAuNdNEktdcCPd3hwAqq8D554BCuOec+j7gCveFNriFK3RyHvr5iRoLv5tELlplr2CWU+wqK4Y1/bW6dKMmp1vDSIVSmzVrgCvHQ7SLW4riNpYddqFaotULxKPJp15nIRMWtFvVsJRqMbVYIqxawX1IYOqBwlz4XksLsyuWVomTnt7qYl3vmkCz//4DeQMjrGCgUrToc6akIcGQJbnU6Ucluo2ua7K9s0/SZMIKTFZSB8GF8ysEQBLFgZAsFFPFE00bQHpiLb5NtJr84mLEVXIWjQNcAY0HBcM1DUkJJ2zfd30q8i9MMvHbt8zNBFycr56zXbZqILT31j+Ij5sn4gWnG4ws7G1QAsRzWBZrdV7eLMM26TniiEdYgL5EZo+q6bwMkbRhzQ3UCVwGLy6kQqJkGaV2mibZW9y7XjwHKdBU31v+zlagxITdpNEEPfcTRm84lWH7OPPPQO85YNRsSUciq4Il9JI554mwSNc4E2eeOIG0KhGXz+z1N4mvNpJxq4dnWIcrg8xcgOrBwmzYm7D6et/AfcM/MjZSGov3b99BN86fgmOKzBZNLHccvzhbwplZ14wOVqhFEq3z/AtR6DpiLbuEwC+TfziioQjBISkWJyKZChoIB2JEGWjXrdFovCJixHX8+8LG5C5QuLxVy6haVHrbjwaoaJD6jk/ddse3LZ3cihRC1Wsq+b9ANmn8262KIoqNFV8/Nzv4yH7BBWccmB8i6ddsqCFiGZwrNbqHchmjlZ9HTj/bLvvBTPSxU5cIKkNnucAY7R9iBxA4ml5nq5j9yESE2O7yBF1+RINkFPFnVLQnJr6IjD3Q+DN749eY9jn5PS3aEZMfgyAFYgnAHjhT6PRJNWuzM3BTTKOTzHmZlAf0sH/Y7MTby+9be8kOGN47OV5OK7AjtE8OA/es/CwvFLeQDMUiQh7jSjU3ii8GotK3UJxotgW6VDHHS0YuOv66/DDC0uoWU4krRIXIZYXCemUEYp38Jict7mgGpz5G39YjMRFiHrOMKIWSoTQ/JygbgboLkY2WxTl4Rdm/LkuYbZ6zUevaCGiGRyrtXoHaFPccSDdCM1P/cjsYicpXRT2I7GW6bvr0IyaXCn5eOp8rWp7cefC8WA43fKl9Om8l71UULi2JGxqFhZLfmEso3U49uqjIqudktwrR7+OS/Ov43zuEO65afvgjtsn8U/S4bRNzXIxVmCJ81IA4NGjs1gOdcqE932DBwWj6gx5s/11DLfemoxh//YR7N8+gkeOzvpiRAqyYVcixBUSltsuQpKKbdXPYwUT40UDHzm4J9UFFSAxoupIkkRIv1GLNMIiRNXPqLqZbucYxnqGwcMvzOAPy78JgNxN91yDqZZe0UJEMzhWY/UeppMRWj9iJx4NkZIKNAFv7L0X05aSZtO4VjT2ro43uS+5G2jnAepyEW4wHyZpOq8U0cepjhtlzAYWjSapwljGQTUpzuqjIqtNnfXI8tVL61YbkpW0OTVJhZpxMQJERYgEMFow/ZbfTkP41Ib6wB3T+Nm795EYaTnKdg9N20UxZ8A0KC0UdoTtlpj4iRumcN+hPanGYypNAwCW6yJvJIuQfqIWaSSJEACZxMgw1jMIfnDuKg68/peR2x6qP0ziY/+76QYd+eiKFiKawdHF2jsT3YzQehU78XSR8CIRqv4EAJhJEQ4h6PYb3xMteFXHS+sGOv2kF+VAIBqW59ujIn40xHucdNt9SJTAUkJEilBVpKCoTb+RCylI8Lg2kBvrL3XWB98ufgwPDuxowyHLvBT177AYMbjXbe6Ji9GCiZ+9e59fg5I2hI+FvEWiYuR11FouXEl1Ju+66ToAwJEzVyLr7ZSiMTmL+JXEOTlfxfdOX8ad+yZxbLYCaSFVhCjBMJo3UFtFJCJNhCg6iZHVRFEGjSoyVai0y46xfHDjJnU3XU+0ELkWyDLzZaPQzQiNGbRxZ7kWKYH5Y8DKlWCDd+32GTPCpePmS0DLSS54TUtpWDXg/NNBlANIjoqEoyGMB9WFjkXiAoj6kKjBfcwETO+PHGN032qm4lbn6PqH7aIKABeeR8te5VCWNSTLvJS4GBEiKgreceM2/zFpQ/hYqK03vKHeuW8SecOAyAVRipdeL4MxBpNzOILSM11G5QAAbCdZNITTG8dmK7hz3yTNjvGuN2nTb9guDcsrmHBc0Vdx6eFTC2hYLraNJA/xAwIxslS3cfjUAg7sHsfpheW+oyiDQhWbRopMPcZ12mUgaCFyLdBt5stGIYsRWi/XcvkkFYbuvweYuJ6Oe+p/AisxIWKYVCOhjM6SNuO0lAYzAMdL86g/sOp7OCpSmSExSBca2k28dJA5QhGQwmQoBSQBp0aCR9WtAORH0k/kYny316bcAEZ3DNdF1asNqfCpodq590ta50WWeSlqw/uLF2fQtAMPkILJcWy2gv3bRxLECA3hC4sQILz5Wjhy5gqKpoGpkRyAYMiekNS1YwqGpkPCLkmLMJB/yUQp5zuihjfppPTGsdmK36KbJkLUnJ5K08FksXcxYnCGe2+NWu6r65dSRv690nJQytM8mzQR4l/vGoiRvd/5NXzWPuEXm+oi0+GghchWJ8vMl/VGRWxqb3Q2QuvlWsKPXToH3OwZhdkNL0XjUNuu67Rbm8c347gRmGPRMYCoVXz4oyrj0ahIo0odOrnRqDOqcIN00Pab6LyqDkZ47rKd6lZ6iVwsnqWo0Bq5qJ7KHcLch/9kaMfvl26dF1lbQ03OwUAzZKZCduiJm6JkYExiNG+0bahNR3izYqh4tOkYfttvOKVjcIaCaaCREGVSIiTsgRKOLggp/VbleDTmW8cvQUrge6cvR6IWSoRIb3JxWIw0LNePWmR5vZLqcJqOoEhLMddmJX9g9zi+8vTZvqIo/bb2hotMFdehosXHGqCFyFanW6pjI6CiHEa+czdH2rUkpZ7ij104AVx8LjAfA6fNvTDZfVNuMwJrAYZnQBQ2VUsapLeyQGmWmefpHPnR9sfE00ET08C+d5K7bM5L86TVrWQlS7TpGqCXzou0qIk6BmfAZNHAikXCIOkT+oHd45SWsF2UchyLNSviVRLZ7DnVmiw3bRRNDsZY5JhCUv1H3uD+jBkgWYSEowsHdo23iZD4eh9/5ZJfM7LSogF/labjz+VhLBict9SwMZo3U6fwphEWI/6wP9Bcm3jHDoDUKEqYeBQl63riRaaH7ON4SBmLqSJTQAuQNUILka3MZth81BrrVwFIoHRd9H4VFVFCIulaLp+KpmuSrvvME/RdunQeHho6J2Xn1yVuBLZ8iVIb03eTk6rrwB9kF+9nMPPA8kJvnT6Mk907NwLztTSjtqxksd0fFJ6TKoyN1VrZS+dFWtQkfAwhJKqeCKk0SJCWckabGLn31t145OgslrzHqMcWTY7lJqU9KOJAjqbjxWgEIPypv5TnyBl0fCVG0kSIaXBfXGRJb6iakR9eWMJSwyaBwxARLtKrtu230iw87E9KKvZ1BUWC7rlpe2qrcZIYibdYd0rLJBWZjhZMjBe86KQJ4ICOfKwXWohsZdZy8+mXy6eAyhz9W7heO23IpEx1c5x5glxQ267lBHDhuWi6Js28TKVLGKfIifQ6aAqTnV+XNiMwL7UxthP4iV/q3sGz7UYqRM3a6TPo920tvUMuPI/Fk0fwBibx6E2/v25OqnF66bxIi5qEiy4NBj8SAgBCyDYxotIFHzywK9i4JSDhPbaUw3iRhvC5nndIWFD4Twl96leeJo+9PI+VpgNHCOQNhqLnWRLenH/qtj1t6ZYkwkLn2GzFTzFKCbCY8yrngclaP3UZJ+erwbA/V8L1hgnmDdZWXxM+dlyMdBIhcSdTNb1WF5luXLQQ2aqstXHVatYoHEANfmuWKfUR/qOpUi9qcB0QXMtpL9IRT8H4aRIZMi9zg84TCfjpGeF0b11NirJcfB54569kex2ztjUP431bY++QFXMbvvKmhzaEgRnQm38FgPaoybFgw7331t34ix/OYMWOpuEkQmLEs4VXaZHHX7lEdSSlHKpNB0LQ73qlYWOyaCLvDeErmoYvKPzjdthwD59awIFd4xG/kvhjlZNqpvRGzgAg4cpgrWHnVcaCyIuUsue6jGhEKp9YI5IkbnrxeSk/81V81hsaF0bXeWxstBDZqqzx5tMXao35MQAjlPpwrfbBdeWLwPlnvMeFyIVs2tX0WxU5YQbZrRcmQwWlXrdKpP/REz+5UucC0LWKLg36fRuE7X5WvE6ZFp9a3XEGSC/+FY8cnW1rrzU4Q7lh4dGjswCAmav1yNC5sLupEiOqhiIpLcIYoy4UT4yox77/lutSDdCSNtxwd4/yK0nyP+k1vaEe67gCE0UT1aYDR9Ck4rAI6bUuI+l9KOUMvxYGQGqEKn4d6jpv2TWGf3b8XwLHg/NMijL2aB+PTYcWIluRtdx8VrtGKQKfDLPYXg/hD6vjFBkIX4vrRH05wvNjpAhN7RVeKkZ6xylE12LkgLfcS0PpkgpA26IU3hq61Zb0+5oM8n0bhO1+RsIuqhshJdOLf4XJGZbqNhgDdo8X/K6RapOKRFcsB9944SIcl94TzgIn1bgYgQRcV+DFC0tt7boq7RJOxzDAt3rP8qlfoQRAN/+TsJNqVqETFiMroWGAvdRlZHkf0mphkiIt02e/gQ/wbXheXI+f5K/jdxb+M9V53Pye6Al15GPToYXIVmQNN5++yfrJP+1aJMhPA/BEh+3tCJ47qjIMEzbA84Dh5d2V6BjdGRyLG8B1bwlacrut1W5SFCU/4E6kYbxvg7Ldz8hGclHt5F8RpmE5VEjq1WhwziPdLDmDwXYl7JAIMTgDk7TJxsUIZ0DDEWCuwB5P1IRRYmS5aVMbqy1w+NQCPvWBmwF0dndNo5P/SdxJtZvQCUcfwsMA+xEhQPb3ISnSoopM/7D8m9RKO5aHM8JhMgGM6sjHVkELka3IGm8+PdPLJ/+0a1HOo/kCGZJxr56i4BWS8hwVlVo16nA58FEAvLvo6LpWQXNqhEOeJEZ+cFGRYbxvg7Dd38R0S00IIVBu2IAEpkZyGMmbsZZaihyEERIwpDdt16ufCIsQ4d03kjMig/TClHIGCgZDzXIjG28Wd9c0OrUah51Uj81WugqdpGGA/YiQpOOlpYiu1izvNRjDctPB25/8haDINAeM3/tZAHrT2oro93QrstE3n14/+cevxU/XGO2+HMwgYcNBqR414h59mnfF1+o6VMcCFgykG1R0aaO/b2mEXFTftCPBJ2Wd6dR5UbNcjORNMFB0o245qHr+GWpjZ4yBMwkRzgpKCYMxX4wIL80iPRHy/lt2tqVa4htvzXK71n+shjQn1bite5bXrdcITbfjxd+H6nIFO2QVv2n+//CBK68AV4BCzsD4vZ/r61yazYUWIpq1Z7Wf/HtJ1xj57h0ncUO08M+RtQrq0qktkgBS0ZZbH1i/6NIGQbmoboTakCS6dV4AND9GRUdMIyoaAC8CAop4CEn/MDjzvDa8wXeeCLn/tj3+83tpPVUMUoTE25XDtu7dWE2EJu14z55ZROvqDKyWgSnUUMYopmDh/7X7Odz33n8I4B+u6hyazYcWIpq1Z7Wf/HtN13TrOInPr4n/rNbq+4hMUq2JiraotI1mQ9PpE74rJHImA1pKi0pfNAgJv3UVCApNlRjhHURIL62ngyJLu/K3jl8CZ2zV9SedKD/z1cTb/0fjYfxg5E78B+cXccXZgSnTwu/ufw33vU0XmV6r6L+ems1HkpBJS9dI2bnjJD6/ZueB5Hk2m8GXZZ1YvnoJwMZyUU0j7RO+wRkeuGMvHjk6i5pFnTJkaR6IENU10vB8P9REXEcE6ZiwCImfc1Apjk700q7c6+C6Tvzg3FWcXwzmLv3G8hfxYWWZHmf6evz03Q+gNOfgj08U8OuHHNy3980Zrk6zVdFCRLM16LfjJD6T5sxTyfNsNoMvy1py4Xng6mt+bcijN28cF9VupH3CVxuyEiOuZ7ne7p9h4l03eR0oTQeulHjfzTsSRUj82INKcSTRS7vyagfFhd1Lzy/WfMt0Hw6MdzERu2+vhQ/tsWBem/pdE0ILEc3WoJ+6k7RZPGDUfaN+VlGSjezLslaELNwBYH6D14akkbbxhsVI3aJJs2n+Gfu3j/gW7rfvm+x6zkEVoaaxmjbZrPzg3FXfMj3sXrqjT8t0LUI0gBYimq0CN4EdB9qn8HYiHuVgnFpzi1P0s4p2nH8uW7Sl/DqZs2U9/2bBEx8A4AjpF6ZuVZQY+eaxOThCphaX9iMshiVCFIMcFAdQnce9zW/7PysBsuPv624WzeDQQkSzdYgXmXYiyS3VaXrfG0B+xHucBK6cBG7/eYqIpME4UD4PnH8WOPTxTZ2mWT78xcjPtZaDU7lDePSm3weADTNDZphkresYtrDoh34GxQEU7Tjw+l/6Px+yj1Odx/T1wPa3BA/skG5xhI5yaHpHCxHN1iBedNotTZLkluraVOzq2hQZsevknro8TyKkk7hYOA6c+ubmS9Mc/Xrkx8WFWThC4l9t/7PgxlHgwXfu33Tpl9WyFnUdwyJLt45yLQWA+5vfwmfrD5Nl+vZQrcv27MPinpzL449PjOLXD9Vw315roNej2dpoIaLZGsSLTjsVj6a5pUpBQgTez5DZ3FOl5y/iWtQyXJnduMWrF54P/j3zfVyqtvBXIyFT9iIw9b5Pbhib9vVm2HUdwyQsRq6stJA3eMS19H5UUPDs5gFgfBXD4p6cy+PzL42hbHF8/qUxACtajGgyo4WIZvOTVnSaJhziHTbCBYT3R1O6CKaGIJt76uUTFDUB82bd2BsvKhJyPw0o4Xe2P4QH37lO84Y2CVlFiCvkhhMsB6cnsP3YV/G4OIRP5r4dcy397EDOoURISzDsH3Wx2NJiRNMbWohoNj/xNEu3ltp4h410g/QLJDD7ItCsAoVxSs90ck9V0RDhUleOFHS8dY6KLB/+Ilp20EHkCOlPxg2jIx+D4eR8dUOkcB5+YQZ/WP7NyG2TKOP/cdMrMH/in2HQrqVhEbKjIMAYsKMgtBjR9IQWIprNTT9GY0mGaHvuoO8LJ4CZ7wMj2+k4Rq6ze6ofDYHXKcNJlKxFVOTC81g++1zbzS3bxRuYxFdujjpbXgtFputBeLBcLyZhq0G5lh6yj0duf0iZiO1/d3BjxhqPXkkSIQC0GNH0jBYims3NII3GehU18WgI4PmDDygqcuF5EkUpXKq2cCp3CF8e/+22+67F4tL1IGmw3KDFSKpr6fT1CY++HnjbP+utjb0P0kSIQosRTS9oIaLZvLQVna7SaKxXUROOhoCFSks4IJzsUZFwAaki5Fp6uHh/8vNGdGHpetJpsNxqxEjYtfTA63/pd7P4dHMtXTiRvY29DxwB/PGJUZQtjv2jbqrWUWJkpmbgj0+MahdVTSpaiGg2L/3auifRq6iRAjh7OKgzEU78gFTounKl8/mf/RIuVVuxIlLisFfT0X6PZr3JMliuVzEyENfSXtvY+8DkwK8fquHzL41hscUTIyIA/S+02OKYygv8+qGaFiGaVLQQ0Wxe+rF1T6NXUVOZpRbfXDHSZBPByAG5Ehb/5r+lhsiVZ0dS58pU91Vr1oFBDZZLci0dLZgYv3cVrqW9tLGvAkqzrKSKESVCClzid+/SaRlNZ7QQ0WxekopO+6VXUTMxDdzxi8DZJ1FfXkp+vASq1Rb+avQTOH39L6Qe9kFdRLpp6Hew3LGZMn5z5d/790+7c5gU5Z5cS7vSaxv7KkkTI1qEaHpFCxGNBuguao5+HahdabuZDMH+Cb5d/FjqU3Xh6Nah22C5qzXadKWUcIQEZwzvcn+E31n6z9TNMrrTe+QYsP2uwXa09NrGPgCSxIgWIZpe0UJEc03jz8ZIKhj1WD77HGotJ+JAKiTAGfDt7R/Dg+/crwtGryEOTk/g9MIyjs9WcLVmoWByMMYwZc3hRtkEA/CGHEeBOfjt4v/Eh8wTGN/Vv2tpJvppYx8QYTEyUzMwlRdahGh6Yk2EyH/6T/8JX/ziF3Hp0iXcdddd+I//8T/innv0Z0TN+qJmY3zS/m+4Rx5LLBglxvCVA1/1fTjC5lUPDtIvQkpMrPwY1bE3b63pvVuIcEHpc/x2/JH907DcHLZjGYwBRmEMi5hAyY8IPADggeEvbJBt7H2gxIieNaPph6ELkT//8z/HZz7zGTz00EN417vehS9/+cv46Ec/ildffRW7du0a9uk1GuDZL2FxJfqH8WnnNvxR66dRlRb+HfsH2Pem38LPvG1f6iGUbB6medXeK8/g7lP/AUdv/S3M7Xr/QI6pWR2dCkp/HsDEXI5mrIjx9UtLDLqNvU/u22vpFl1NXwxdiHzpS1/Cr/zKr+CXf/mXAQAPPfQQHnvsMfyX//Jf8NnPDmbWgUYDtI+vB8hlVHWmvGkHfVqcrzRwfLYC15AomBxVTKJ+eQUn56sdRcUwzauYdHHLxW9gpHkJt1z8BuZ3vgeSGd2fqBkYD78wg99YDn6HshSUDjUtIWU2Y7JBtrGvEi1CNP0wVCFiWRZefPFFfO5zQTsa5xwf+chH8Dd/8zdtj2+1Wmi1Wv7P1Wp1mMvTbDae/VLqXcqL43em/qjtvjftGPU7U07OV3HkzAoMzjBZoq4HKWVXUTEs8yrF9JXnsK36Kpr57dhWfRXTV57TUZEh8/ALM/6/729+Cw/VH+6roHRoaYnLJ7MZk3kdX67rwkjTK1nb2DWadWCoQmRxcRGu62L37t2R23fv3o1Tp061Pf4LX/gC/uAP/mCYS9JsZDoUjC6ePII3MLkql9F+TaiGYV4VRkVDGASs3ARKrcs6KjJgwm6lAPCps5/E/aigkAte3/Hp/gtKB56W6MWYjJt40r5D12doNi0bqmvmc5/7HD7zmcBBsFqtYv9+PaJ8y3PheSyePAJHyNSC0XnjIOY+/Cd9m3z1a0LV7/N6GQnvR0PMSQCAZU7qqMgA2fudX8Nn7RMRt9JCzsD4vYNNDQ80LZHVmExKPP/jq/j8qzejbBt6rotmUzJUIbJjxw4YhoGFhYXI7QsLC9izZ0/b4wuFAgqFwjCXpFkn4mPpwygBEu5MGST9mlC9ZedYX89zhcT3Tl/ONBI+HA0RBv3uu0YBcCo6KtIHD78wgz8s/2bktutQwY5Os1k2Gj0Ykx09dQbTrz2Kn8A/xpnRO/WQOc2mZKhCJJ/P4+1vfzsOHz6Mj3/84wAAIQQOHz6MT3/608M8tWY9Ofp1LF+95P+YNpY+zD03bR+a6Vc3EyqFqhUp5Q3ce+tu5E3e8/MO7BrH469cytxVE4+GKHRUpDs/OHcVHz/3+5HbHrJPUJ3H/ncHN24WAaLIaEz25KyJsdeewy68gX/Cn8TncTt2FNC/GMlaHKvRDJihp2Y+85nP4Jd+6Zfwjne8A/fccw++/OUvo1ar+V00mk1MQvHocsv1zb/CbqPr7S6qxECaqFBiwjQ4Hrhj2n98L8+7c98kjs1WErtqDuweb0vV+NEQ6ULwfKTt0uV5QAodFUnh4Rdm8NDVX4bJGXbsDrddD9k4bNhkNCZ7ci6PJ196Df9PXEQFE7hJzOBu8TJeNO7y24h7FiNZi2M1mgEzdCHyiU98AleuXMHv/d7v4dKlS3jb296Gxx9/vK2AVbOBSSgiVTUdYbdRAIABnD7wC7jnpu0bzm00TVSkiZBenhcWIfGumkePziJnMjxwx97IsaeqpzBeuwgAGGldTlzzeO0ipqqnsDR52zBekk1J+ZmvBh0uWafSbhYyGJM96b4N/8ePRvB58RRMCFTYKApyCQ84T+EovwOC8d7FyBpM7dVo0liTYtVPf/rTOhWzGTn6dVyafz2xgHTeOIi5+5KLRzeyZ26SqOgkQrI8L0mEAFQ7YnCGcsMGWsAjR2cjx6qMH8ALt/1rGMJOXa/Lc6iMHxjY9W929n7n1/Bh+wR5e/Qa+djoqYcMxmTi/DP4j9W/h0P2cbzVuIgqSLAsYzQSFWEM2FEQmKkZ+OMTo907etZoaq9Gk8SG6prRrBMJzqMAFZGeyh3C3If/ZB0WNTzComKpbqOUNzqKkE7PSxMhANCwXVSbDiBp36tZTkSMCJ7Dwo6/N6Sr3Hr84NxV/Aa7hD39Fp5u9NRDBmMyXl/E//amk5CvPglAwGZ5AIDN8mCy5kdFXHAstjim8gK/fqjWWYSs8dRejSaOFiLXEEnOowD8mo6kUfXD6GLZCChRoWbGZPX/CD/vQ2/dhe++ejmxq6Zhu6g0bEgpYRqUxnElULccfPPYXORYmjVgM6QePGMyiOTuMgAAN/Bu5w00c+cxZ4/CkQwmo8iJHxVxX8bjzt3ZrebXYWqvRhNGC5GtxoXngZnvt928uGL5Vudx3nTj6FC7VjYqB6cnEotIe3keZ6ytdiQsQgxOIoSm9TJMFk04Qg58To2mC5sh9cBNYOdbOz9GCuCFP0WRCewoGZhrCBIjkLCRA0cN99mH8TS/E//bXfXstSHrMLVXo1FoIbLZCReSXn3Nr+locyAtdncevRbpVYTEnxevHTE4Q7XptIkQxshSvpQzMlnKawbIVko9hNI3E6KMggmsOHQNDBISDDfgEr5w4BTevbfdq6mNdZ7aq9EAWohsapYPfxG1lhMpJj088iCm3vfJvh1INb3ji5Fj8yg3LAgJ5AwGV6hICHwRArQboPUTlVkNvbi+bgm2Uuohlr4pADhx1cT/OFdCzWYYzUl84s023v3mHd2PtUGm9g6MjV6MrElFC5GNjmd/HifNjXRqDZemCVBi5NGjs1huOXBcCZny2Lhx2lqKgpPz1Z7rYjY1Wy31kJC+uXs3sDiZ92fNvD2rb8gGmto7EDZ6MbImFS1ENhjxgtJay8Gp3CE8etPvtz32Wqzr2MgcnJ7AzNU6nj59xRchSmNUGtSiWzR5pnbhYaDm5mR1fd1ofPzc72PMXertSatJPfTyCXudP437Q/eYBJYzriNjceymmNq7GYqRNaloIbIe9FJQOrr+rqRbjWGlJk7OV/HihSVfhKgzcAYIKVGuWyiaBooZ24UHvTY1vC/u+roZxEj5ma/ifvckdhx8f/bW3dWmHi6fBE48CtzktQt32tg3wKdxkwNY6GEdWYpjNwuboRhZk4oWImuBLijdMPSamsgqWk7OV/Ho0VmsWA4YonuWqhNxBdB0XNxz0/Z1EyFx19fNJEZ2jOV78w9ZTerB/4R9lTb20iSw+/bkY2yUT+MbZR1rzVYqRr5G0UJkyOiC0o1Dr6mJrKIlLEIg4fuGiNAHcFcCnDPkDYZjsxXs3z6yJpt/kggBsGnFSE+sJvVw+RQJFDDAtYDTTwC7DqVETtbo03i39M+1GhXYSsXI1yhaiAwCXVC64ek1NZFVtJycr+KxY/OoWQ6k1y0D0EbPEYgR1TlTNPmadcukiRDFlhcj/aYe1Cds16Z/gwHL88DlE+1RkbX8NN4p/XOtRgW2WjHyNYoWIn2gC0o3F72mJrKKFv9xQmCylEO16URSOVExwoABdMtkTRW5QuLwqYVE19cw691KvCFR0RDpApAUNRFuclRkrT6Nd0u7XKtRAe2DsiXQQiQNXVC6Jeg1NZFFtBzYPQ4AbRs9YwyVhp0oRlwpUW7YmCzleipUVcdyhcTpheXM9S0GZ7j31t1trq9x1rOVeEMSjoYIlzZ79brFoyJr+Wm8U9rlWo0KbDUflGsYLUQUuqB0yxEXFXHiImPmaj11iq563CNHZ5E3qfU2vtErw7KwGAnXiozkTfyDO/dmFiGqRuXArnEcm63AcgTcBHv4tChJ0sTgsBhRImQ9Wok3LPFoiNrAkqIia/VpPCnt8tpTlHbixrUbFdhqPijXMFqIQBeUbkXiqYmmI7DctDFeDBxOgUBkLK5YeObsIkZyHOPF9lQGYwwmZ1hq2Ki1yLjs43fvwwN3TKeKEceVYAyQAEbzJn727n09iZDHXp7HStPBfJl8SRgDtpVycFzhixGg8+C+NDGiRUgCkWiIA4AjcKWLRUV2HVq7T+NxocE4sHQeOPMkcOD+azcqsJV8UK5xrh0hogtKtzzhyEA4NVGu22g6LiQCYzElGNSG7EoJg7FEEQJ403Sb1JorANQsB48dm8cDd04nihHppWKkBEYL/YmQhuXAESLi0FppOjQ4zxV45OgsGNB1iF6SGNlMImTvd34NH7ZPANPXD/dElVlg5Qp1yUgBQKLNHle4wJnDQGF8bT6Nt6VdJOA0QwLjrXQeKShSkpRZ26pRga3kg3KNs2WFiC4ovbZIarVVTqdHzlyBlIDByVgsyeX0fTdvw7HZSmIKIzxNl47DMFE04QiKTDxwR7sYcYXEWN5EzmR44I7e0jFKhLQcEWkBlhIQkKg0HZRMjppNnwSnYlGSbmJkqW6jtA6mav3w8Asz+D/dk9hx2wd68xDphGqDHd0F1C4H7bAT08CbPwic+TZFRdqe59LtjTfIHGYYn8bjLbrxaIjdpDUwDlh1MjDb907g4vPA/ncDUzcMZh0azRqyuYWILijVIL3V9uR8FcdmKyiYHJYrIaTs6HK6f/tIWwojLkI4T56iGxYj4Y2+ly6UTiJEISWtf8Vy/Q+/1aZDwiijGNlss2YKOWNwIgQI2mCn7wbmjwbtsNwEbng3MLozQWAIqg9ZngdKU8DkXsDID25N8bUd/BlKp0TSLgJoLdN3bpAwuvgcMHE9YDeAygVK1Wy1FIxmy7M5hMjM3wIjsf/pdUGpBumttuHC020jeTQdQUWknqAAKNIRdjmNpzBMzlBpOr4IkaCUTrjGJFzsqsTIUycv4SMH9/S00YdFiJUiQhQy9F1FeVZaDnaM5lHr4ntycHri2m7R9dtgl+i7Y0drKNLC/QsngFYVKE5SCmTx7OALQOMtuoXRaPrHdShtxBg9ljGKipQvXHsmZpotxaYQIgsnn8X8yHVtt+uC0mubtFbbct3GkTNXUDA5to3kwRhDKWfAcgRWWk7kGD+8sBRxOVXfv3lsjmo8AL9UgIHES96kT5yq+DXsw/HBA7uQnKhPRxXW1lsOHCEhoObTZHkuPXa8mAPnHGMF1tWg7JoVIUCQ6jAKgLWSbQNfK7OweItuoxpK/3gRmdoikFfdMRKoLwGOBYzsIKEUX9c6D+PTaLKwKYTIb2z7Cv7p+29tu31q7Zei2SAkiRDphTos14WQgOVKNB2BUs5Aw3bRsCmdEY4o0KY9F4kSqM37kaOzEeFiGuTnUa5b/vMrDRsNg6GUN3Fg1zgef+VSz9Ntw4W1DcuhUoQsKgQkQqZG8n6UZrUGZcMaCLghCAsKYQOQVG/Bc12G362BWViS2Jl5Hnjnr9CawhEZ5RViN+g7AxWwJq0r7saqhYlmA7Ipkok/+/Z9670EzQYiSYQ0bBdXVlpoOgITpTxFFAQVpqovKWXi39665eL0wnLktoPTE3jHjdvAGf2d5wz+84WkLwY6R8sR2DtZDKWCguLRk/PVTKLi4PQEHrhjGqW8mTmeEhchwOoMyk7OV/GVp8/i5Hw183M2FUpQMMMr+PS+czPYwOOkmYVJGdyeFSmB5UvRFlt1+4W/oc6WJLGTZNyl6kWUrLZWgvvUuuKpHilImLz4Z1RfF1+HRrNObAohotEowv4g8YJSRwQdMVMjeTBGj19pORCeGIhrAgag5Qg8enQ2sgGrQtfRvOE7p7qCUiEKdSyTc5yYr6JhOZEUkePScf/oqVczbe4Hpyewd7IIJ2M0RBXNKlbjDaLE3VLN9gXURuA3lr/Y/UFZCAsKpwmybuf03WnQJp8kLLKYhWVFiYDLJ2O3v0JRC9dOFjuVmWitSKsC1K8G9SIA+Z4IO7queKpn4QQdr+5NFF54pYcXUKMZHpsiNaPRKOLW5QZnqHoFpaZnhV5p2JgomjA5h+UpB5ZQc2FwBs4Ax5VYsRw8enTWv09FXMaLtDFYrmyrL1HY3jnCqSDGGAzOUG7YQIvSPEB6qsYVEodPLuBERgHAADRt1z9XVhGSlHrpdSDgWrH3O7+G292TGD/w/tUfLBINqQcpGMZpQzfyFJFIsk7PYhYG1jnlkTYrRnq1H2oNUgbPV6IiUisCROpFuAnYNcAsAcwMClnPPwMqbgqles48Qd8BOt+ZJ+hadZeNZp3RQkSz6QjXcCw3bEBS/QZA4sJxyUyMAb44SRMhAD3XdiVqloNvHpsDY0DDEr4ja6Vh+ftDZC8KiRuTRT1KAGqrhfe8muWkipGT81V889gsKg0HQnYuVFVTfGstF5Yr/YLZLCIkyWul14GAa82O3ftW37obFhS+WZkRvJlSUv2FUYyKhF4sxFvL6ZNxgcA6PleMCp7LJ6glGIyiGnYDyJXoOUrsXHwOOPjTwPg0/TKVZyiqww2aJyMFfUdIxFRn6fb8GP1slug8SvyoicILJ4A9t7evV6NZQ7QQ0Ww6XCExc7WOuhVs9FS/wfw6Dgkgb3CYnKFmRT0hwiJEHU+ZlDVtgVLeQDHHsVS3In4enJGPiBDkR+LK4HiMAVzScDtVjwKQyJFSwpVA3RM6ACJC4JGjs6i1HL8zJy5ClDBRe0zLFhgrmrhz3ySOzVYyGZQlea0AaBMhQPpAwE2LEhTSBQQVGtMsGYX3grsWOasqF9KsFuLju4HT/yt9Mm7EOj5UHLvzAHD2sDdcz4tkNMuA2wrebClJePzg/wTu+AUSL2pdV88B549QlEe6wI3v9QzNBJmy1d4IjiFd7zq8c6nZOToqotkAaCGi2VQkbdwAbdQc0tuwGaaKJrXCSnJQbTpklc4Z2kQIYyRCXCH9DT3syKqEgDqHyRlcKf0OHCklJIICViVCwkPvOGNkzR6yYweoTbhuOVAHSwqEMAbkvGM5Ami5Ah+/bR9u3zeJ/dtHuhqUJaVeHj06678eSZN5t5QYURu3a1EUQITqQGpXgIXjwUa8/57AhTSrhfjCifTJuEB0kJ6a6FuZBc48BdTfIIM0ZlBExLU8QbGfhE2zAvz4OyROlMjhJrDjFuDc90hQFKfoccrQ7PIp+tnIA/VFoDBJ6RsA9BumJgrrqIhmY6CFiGbToESIqtWIN4S4asMPOZ8u1W2UCgY4Z6h7lugqehIXISq1AQDHZisomgaajuufS4kR5dDKPPEgZDS1D0RFCGPtbqxhITBVygWeJQm4ApBM+qLofTfvwO37JgF0NyhLSr2M5g0sLLcgJfxCXIV6bYDVtwJvGMKCYs8dwe1SAC/8KWDmg8186Vxv0YFuHiORaIhLBbLCs4q/8Aw9RqVPgEBQTF4PnHvaazV2KIoSSemktRSfAC48B7guIJp0rlYlmJ2j1gwerCUcFemnvVe3BGtWiY7HaTYFJ+erePToLGpWUDDansJo3/BLeQN37ptCIcdRNLgfuaDJuMkiRG3cUyM5r/uGecdH5NwSUU8SJVTSRAgAv4h1peWgbjkYzRuZ/nira33/LTtx/217Ivf1IkIAgHOOyVIOYMBSw0bDe01VC3QjJNj6bQXeFHTyBxnUMVQ0RDhBbQYkpWisGkVCwqjnn3mCulvqb9BzpAjEi3DSW4rPHqb0knQpugIZOrdChqJCoagIkN7Z0/E16OM5Gk0ILUQ0Gx4lQla8mpCcEdR4RIfCSf+7Kt5UdRQNS8AwPDHi5XQ6iRC1cZdyBiZLFDWIRyzChasmpy2GgUROUiQEoDqRcsMGvEhIyw0KXLvt84Ucx/7tI5lfsyQRohjJm5gq0Sa21LBRrluRFui65WyqCb09Mwh/kG7HUILBtenf8EJn4N7PoOJUKbw6DknRG8ciMaKiGMxrM5ZukNJJaymuvwFc/05gdAdgFinSk+hM43XUMNBxX3sqWG99yfu5Q21M/DUIe5VoND2ihYhmQxMXIeHumCQxUq5bKNdtX4S89HrZr43gDDAMjtGCibE8FaaqjfbA7vE2fxKFEiOcsUSxQJ9xGXLe2lSkZLJo+q6uV1ZaqLccEh0S2FbKoZgzsNy0/VSPwVlq1GE0b4CB4fCpha4GaUleK2GUKFJiREqgZrkkyrxi3HLDhpTYmiIEGIw/SKdjVGaBVx+n6ITTQpAWcaOFsm6L5t4of5BmhQpqpQDgbepSkBgJp3Ti5maORfUikFTz0vRcWPNjVLsSh5lkc28USLC0VoDzz3nXUwCWzgNnnsz+GoTrYzSaHtE1IpoNy8n5Kh47No+a5UB6kZAwhle44ReSenUcLVfgHXu34YcXllC3HEx5EQ1VfGlwhruun8Lpy8uRIs+wP0nSBg4keZGoThcJ1xMjjpAoGByOkKhbDqpNh6zhmzYKJofJuW9aNl7ModLwxAgkOKNq2rDYGM0bMDhDweCZUiRxr5XwtTRs12/5LZocLVv4Rbdh99hw2mk92PudX8Ot9gkA1w/+4L34g6TVi3Q7hmtTjceeO6m1N2w+lh8jUSEcqlmZvitI0ZQverUhrdAxQ9+FAziOJx6UJ4hDgsYokBhZWaCaEhWlyU9QGggASttpUN7odcAtHw35qTA6r1qXur5bPkLX0+k1GPYMHs2WR/+2aDYk/qd628VkKQcjtjkr4pERBuDgnnH83cUyCRgAlaZDc2Y8MeIKiWOzFXzorbsin/aVzbppcKy0nEiqZ7lpR87PGaVjOGNgXqREtekajKFUMCAkUG7YfrsvQC6s77hxm3+Oosn91A8VvUoSA6FrrNtu1+hE/LVJupa4A+3iioWm46KY49iu3GO9lNK2EkWQ1sNltfzMV3G7exJ7bvsAcPc/H/wJ4v4g8S8g8Afp5xjNMgkPYZN7qXBoo1diw2lRysTMUzfL7tuoWHTXrVSoqtImYYQLgFM0xchR6uXOT9DX6A7a+Ed3ADe+h0RIuADWbdF39StSnCDfFMbpvGoGzfI8Pde16T6rTmmgNAZRY6PRQEdENOtM2pC18Kd6xxWYKJp+ZCH8eCUWGOhv/aHpCZx/o46a5fgzYsJGY6Wc4UdGvnX8EjhjbWIEQCSaAJAnie0GHTTxNTPGwCHhCgnJgOmJIi5cDYaShVuKj81W/NoVFZ1AiSIjSlCojpws0Ykko7L4tSzVLVguiRyD0evuQiJvMH9CMRjz1xMu+F2P9t0dY/nVG5mlkdUfRLXx9nqM8kXy9wALjMbAALi04bsW0LgKGGYgeKb2hwpbk9YlAenVlQiXRILrddOoYXjNCnXNMB7UqkjpzaTxlmCtkGCxZcgVFl50xwWEl0biBh0/LSqSVh9j13VURNMzWohoMjPoyaxpG6givJEmiRHVmSIBjBZM/MO7pvHEK5dQaznwMhy+QEgSI2ltqfEN3HZlIBA6XE/YdOyV+WWUcga2lXJY9gRNKW/6m/ux2Qr2ThZx8tIyHGFh20geDYOhKVQUxvsQHRIwSYIgyagsLkZmrtbx9OkrACiVpF4zgFqelS19KWegaPKt174bJ6s/SC/HUC2soztpI+YGpUScBgBGKRFFODVi5EjU+G2+4e6aMF7RqlGg5+y6FXj1fwFmIUiN2FdpDUYhlrbxTNwY87xK7PboRWUusLsP29+rqMhbfyq6nCw1NoOaTKzZ8mghoslEN9HQjbiI6baBKtLECLXfeiIkb+Jn76YJzbZD+RkpAcaDDTUiRqSE45mXpdVcqA38yJkrfsqHAcgZHI4QbdejhApnzK//aDkuSnkD4wUTyy3H78Khzd3CifkqOGNoOQKLKxbyJkfRBJr+fJz2duTwa5VlRszJ+Sp+eGEpWKfntTKWN1C3HH9CMQB/bo1iy7fvDpLLJ8niffruYIOOp0TC1u0qNaLETNkbbMc5wPLJITAjB7zlXmBsF9VzNJbo4KXr6P78GEU8bnwPMLmfoi4zf0udNDmv24qx5Jk0Tgtwm/DCd14Qx0sFxaMi8foYobxOzOw1NhpNCC1ENF3JKhqScIXE6YXliIjpdchakhhRXR2jBRIhQkp86/glMK8tNp7GCYuRpYaN0bzZ1RI9bGomvSiC7Yo2MaJEiMEY7FitRrlOn0YlEJlDY7nKcVWiYBpoOS4MF8iZHKW8geWW46dI1PrDTqczV+s4NlvpOCMGoHk8Nc+5VaWvlLjJmxzlutUmRoBoC/SW7ZwZFH4L6xJ9B6MNuVlWD6D0iFkI7osPzGMMuO3nk9tfpaRjjVwH7LgZuHIaqHrvsXC8VuA81Zw4BtWZTF0P/Ph7VKdimIG1PRAIJABYvkTr8++X0a4eMGoxPv8c8OYP0E3x+phwsazhbSnhlJNG0wUtRDQdWc1kVnruHGxH+qmFLBtoNzHSsFyM5U3kTIYH7tgLV0g8/OIMmAR2jhfAvAJSVXMRFiPSEwo5g+HA7vGu11zIcbRcAem12EoZFSOOkN5wPfrZ5EFEJKxJVDFruW75zRCcAROlPAoGw8KySymSvIFS3kQxITqhXqvFFQvPnF3EaN5InRHzzWNzNMgvlKai9UTbkjGSR7luwRUS1YaNokmfYLUI6QGVpjAKFJEoTpEAUF4hjFHKo3412KiB7APzFk5QzcnBn6EIw4VnvGJY7/jNMkVbGAtah08/AVjLwNge4Jb70yMTDMDVC8BrTwY35EbJHl7h1IErJ4Gb3kfHCdfHSEHma8uXqPZEdeJ0q7HRaEJoIaJJRW3ITcuF5bowDZ55/kh4Jowy72paLo6cuYKCyYMCSWSfa6JuU9GVA7vHcXphGY+/cgmQgC0kFlda2DFW8D/Zh8WI41KOpWhQHcTpheXESbhKhBicodqkjhM1vE4gKkaEFOBMiRD6rtphw/hzaEK3bRvJ++uc9Gzel1RkIh/8r+m33BZMNGwXjhAomkbHGTFLNQtNhz5dqzRVUq1M0eR+1Ee1R2sR0oG4nXm4aFPYoF/EOk27LU4FLbh2nTbqAx+F36zYy8C8sGFYZc6LWoS8Sew6iRBmUJqlOkczbFqVoDsm8Xq8AXmqBkVKEh5AoFm5SekdFeEI18csnPCKZWOdOJ1eM40mhhYimkTCIqTpuEFqoZTrKhp8EWI53mRceBNp6X7LlX6BpKIXMaKKJoOUkQPhHdxy28VI2Ss4ZZ4IMQ3elmZSKaQkEdKW3kEgRgzOIiIEoDS/mxRhj/1shV6DEU94xMWIarkV3twcxij6MhWbEROm2nTQ8ESIKthVYiypVqaQ47jnpu2ZJ/le06haEBW98KMheUphwIt+NJco+qEMx7gBOE0aQBdOV7QNzDtJKRi1accNw848ERSchmksBVESlXpRfiad6jUun6JITWEqmMjrtqjOZOqG4HFJEY6sPiLx10yjiaGFiKaNuAgBQBNnVS1BWIwcay+O9EUIgo3Q9os5Kc0Qr0kAsndpxEVIyxGRNEhYjABBoakSIYwhkmaauVrHqwtVtByJhkW+GnERopBgECGfD8fzCFEihLFkEZKEGt436Vmt+2Kkbns1MBLVlkstyl4HaN4zREszXas0bP+46ph5k0ciQ+FamYLBMVIwsX/7SKZJvsNm73d+DR+2TwDTQzAyWy3h6MT5IxQFOO9txGYJKHkRhXBXTOV1YOb7wP53A9tvim7mSRv56cfJfOz2nwd2HYzeX3sDsOaB4javLTiyODrH/I9I8HCTilI7dbGo80NG3VebbjDJN9XQTQIX/oaiJEk+Iupc8YiOLmDVJKB/IzQRlJHYStPxRYjajFXLbKVho+lQNGCpYeGxl+fhCpkqQhDy3VCCQR1HDVhTt2Xp0ugkQhSWK3F5uUkbsDqnVxMYrk1R6aI3VmxY3jXFa0sUQgbdMdStY8Bgoem7iIqQtCB0+HY1/E5dvyskxgom8gZH2RNDUgKcM0yVcsgb3HNyRcR0DYA/H0bBGfzXV5mmqYnDymLCckUkOvSpD9y8biLkB+euDtfIbDX4G68XnShfBL7/FaB8gTZixsjtNFcKpSlAG7rdoO87bon6cbQZgpXo58ZVEiSXT4Tu93xEhEt1KEltNTN/63XSeGFIt9V5fk5Wm3spqQYk7B57+RWKcrh251k9m9UCPumaNUNDCxFNBIMzHNg1DkcIf+x8/H4pJZZqNNMFklIMh08u4JvH5vxN1RchHjxBjAjPsVS5iWapTegkQuIbvyNIOKjbW57QUOtqOsLviHGlhOtFNfImRU0cNzi4KwIvEXWumk0pK5MzcM7aBFHan7Dw7QxeKiU0ZO7tN25DzuDUzCCDTpeRvOmJKLSJkYbtotoMRIgqUA1Hn5QYsV3pW2wVTQPbRnJwXIHHXp7H6YXllFWvDYWcMTwjs9WwoDZei6IfdpNcUZ0W1WUoZacG10lBBaOV2eRNOMkQTITm0KiCU3W/a8Mfguc0ktdoLdPzlRuetULrSXI8TbKoj69frS8+XVddm2vR+cKbdfhc8YhPLwMF1xs9UXhN0UJEE0G1rRZM7m+uMuFTgUQQFWCQeObsImotF1PecLik58XFCAfNWgGyFUiGozVpIiQ1CuH9ba56du+q9gIgky8pJSyXxIjJOQreOF3HMzOLd8Ao8iZHMUeRkV4/Oxk8OPdSw4aQ8B1XXSGDCSPh6/QiOWExsuRNzhXeIosm99+DuBiZKJp+qqqUM/xak7GC6YuRtbZ03/CozhC18ToNRApF61fabd4lqEBTOBTpEE6QxgFC0YgRT2TIwIQMACCA6qzXvSLJQbW0jaIuAKgN2Ai+4uuVoPXajXZhAWS3uS/PtBfLXj5BdvBgdF12I1nERCI62DwW8Hqi8Jqja0Q0PuGprdtG8mg6IjKQTYX2w5tyyxXYMZqHI2y0HIGmzTBZNFFpOpHnKUQoQkEGXjxzl4bBGT701l34Hz+4mBoJSRIDEoDBqHPEFdL39lDHBED27FLCdgGTS5icAybQtEVbdFadezRHw+hsR8B2e5Uh8FMu4ZbiVxeWsdJ0YIdyPBKeH8lI3nc+VbU0Bme0xtBrYQvpT/1Vk32F1zpscor2FE0jUvCatVh40O66m4KF0MbrOjTZNs4dD8KfJQNQyubc02QyZjfpq3yBNuFdtwbRCNfx2m9H2gtQpQDqS0AJJGZ43pvkC1C4DPCrwdvwxEiz7BWvMko1lGfIz2R8Tzab+1Y1llo5AZw9TM9TXUPqHOF6pZUr9LjNaAGflE7SRbZDRQsRjU/S1FY1A0V4n3jUJsxAm+h4MQfOqR13qW75dSVJYkS1z47lTbz9xm19dWncumcCI3kzUguh6CQFKAITiCl1vQB8q3jOGCZKOV8cuV3ERcN2UcoZgROq959uaWVlsy4kILxunrG8iX9w516yY69cSWz/XapZ4JxhokiD+4o5EhVNm7xLqKOGrk+tLSxGHEE1IeFISJhuYmS17rppbGhxo6Ihwg26SoQNiud575JrUYRB2aBLAZz+FuBYgGlR8agUJCLOPwPkRynaAACtMkVVrLSUmIgO0Yv8ZrhU+JT2m69qS258L/08831KMV16KVsHixTAC38aK6Z9giIFpSkSXsKzkL/xvdEum+rrwPlnN58FvJ4ovC7oV1YTIT61VU2HBdAmQpRDJ0Cb2LaRPAomR9Nx0bQFJoumP1U2LEI+fvc+3H/bHjxwxzS2jeZ6ahU1OMPP3r0PxVzwq6vSREnwUHFquNgUoOiMEiFhO3XGGAyGNpfUOEICNcv118A5o2m8HddPgscMbbwFk+PjnkX9Dy8sdawtoYiODcsVYAzYO1nyu3g8GxC/jqduBcWsXjcvTM6wrUPrL2MMo3kDDcvF4VML/uulanOWavZA0zcn56v4ytNn1zYd1EshYjgaIsO/abFw/fkjgcGYn7rwRITTop5uKSkq0qpSNOLG95AJmlkKjsON9g1PusCOA8Bd/wi4/h5g79uBfe8Abr6fvgop/++4Xv1K+QJQPk/RiIvPUZQlS8ohqZh2eZ6uMz9GPxfGKR1TuUCbtZoivHQulKrpUH+y0dAThdcFLUQ0bcTFSMFgftQ1SYQolBgxObmROkJismj6f7qVCFGi4+D0RF9dGgenJ/Dum67ruOGrtQYbrvTWGF4v2kQIADQsB2Wv8DPpHPHbVFHvZCmHyVIuWozKovUr/mq8KAUDMJI34AoZGMB1QYJSRtWGgxPz1UixrD+N2BNe6osz4Pa9E5go5dq6bcLULQcLyy2YXnQs3Cqt3HUHVUsSFzfzlZQizF7IIjKyFiJKAbz2lFcAis4bp+0Nh1OFnJGUhwwiF04LuPA8cN1baPNmPBAwAD0uaemLp4DdtwNv+yfAT/xz4O5/Btz694E9hyjikoSyf6/OUhuxUaDWYiPXfXNNK6ZVBbVpBapA9vqTymz6+YG171xJmyi8mYpsNyk6NaNJJGypXrNcTBRzWKrbAKO0S1yEAPA7X8aKpl902bBcjHpeFkmRj35C8v4cmByP1EckIQStKXyWQAx4oip0PUIIf45NmgjpdD411G6l5YB7nSsuSPGTOJCejwf8qcEfu30a3zo+H0k3dTsPAN9K3hESI575WTyFpshzhrtv2Ia7gUjqLRwZqVsOyg3qhFJPD4uQXiz5u5E0OuD4bAXfzR3CT/d8NA8paZNXduhJof9efC3CZl+MU3RDdqipOH8E2HmAilTj754M1VRUZ2l2izJCs2rRxyW982lTcBtVinowg47NeVQE5UYoFdS4GnJ+rQGi1N3oLNLaK722YQQFquEhfuHZOWEL+DSyWMCvtRGanii8bmghokklPt9lvEDRDcdLaSRNag0XnYYNsgY1Qj66gVFB7dWaFXmMwakOEAj+pIeLOQs5DiHIhMxg1EkDxlA0OWqWC8MTDGmFr3GRoK4q3CabNzjKDQuuCCJI6jGu9wlPTQ0+sHscf/2jub5fEyFJRIzkTZqom7SPCYnHjs3jgTun8cAd021ixBchILM3R0g8enSWUk6h9BaQvbA1jTRxc3m5hS86/xClORP37bW6HyiOarFVn2CTNtmshYj+p2MJFEYpktHtE7HdAC7+LXW4SBGNdDAWGJEVJ2mTlYKiFGrabccko0yegjvzfKjtl6HtzW8sUZeP7/yqDmdHrz9sw67OFW7tda2gmFYVqNoNL5XkHTM86E5ZwPfLWhuhJbUzK/RE4aGjhYimI/H5LkD7J+o0D5CwHftqiVuwhzdGHvv7KwQ86/X2P+o5g8HkHPk8x97JIk7MVyEkCYSGQUZfSc8LExchyrPD9XxRiiZHMcdRtGmGS95gfrcLpES5YWPEEyHKXj5vMqCVfI4sCInEtI5KpU0UTTiCUioP3BEVIwZngQgp5VDyBE34tl4LW9NIEiEA4NYW8Ra5hCWM4/MvjQFY6U2MhFtseS5ZZPRSiBhPLzjxQtEUFl6mTSweDVAipjhJc1vwBtV2cJMs3aUk4WKtRAVMmHhUpDILLF+OTs5tL3MORFRYSAkHsK3g+i+fCqIPhfHotQO0PjMfUvSMXrOwFXwvg+66zZ9Z686V+PudhJ4oPDS0ENF0JUlQhMVIp/bbQUZBLEdEPp3HvUDcUBRETcWN/1l2JeAKgZYtceGNuj/wzRUSTZEcBUljrBC1T2cs6otSzBv+DBf1WjlCYrKUwz+4c6//WhmcpgirGpF+M+LhqI+K3ITreZRgDIuRR4/OkjEdC0SIepyqfal4EaOkmqAslvyKNBECACXZQD6fw67SKBZbrHcxEikqFSQc4iKjUyFifJNLmjBbnQdkpxoeGfh2JL2LzQowuitowc17BmUGjSKA8CINnY4fjopMTHutwM8lPDb02y8FCbS2w3lRkYUTVMSqog9v/+UuqRVBg/Kql7pbwafRKe2yHp0rg0onafpiaELk3/ybf4PHHnsMP/rRj5DP51Eul4d1Ks0aEN5gwimbYQ9JOzlfxWPH5rHUsAAJv+NDiRA1D0YkFLQlpVGEkGj5nTI0FbiYN7BUs3oSAAyBD0rDYGhJiYJpJPqi7N8+Enmtfuq2PW2vlfr5L34440/N7ZckEQK0C4cPvXUXPdZ7HdTEX8aoLTswSUueDZTVkh+Ie9R06toBdhQEZmoG/vjEKD60x4LZbe+Jt9hKQYIhknpIKURM87WIT5htpnxKplUj8lsm7OSHSQeoXYHv8VG7QgZlhvdn2MkguuwG1Ze8+QO03voblHYRThDxyI/Tba1qUBeSVPApHMBu0WvXrAbRh8WznaMP6vUojvcXrUhLu6goSe2N7IJxUITfb82aM7Rkl2VZ+MVf/EV86lOfGtYpNOuI6qzptf22F/xP0EJgqpQDGLDUsFH2nESVCKEZLcnHiP/5lQjPu6HIheV0LniNw7z/VBs2lps2SnkTh6YnYLkCl5dbqFku7tw3GUlRqdfqzn2T+N7py4kdJ66QsEXvIiRp/1e28GnC4YMHduG7r16GKyR2jxd8EaIo5QxMlnJkuCajdvzhY2UxogMCj5pS3ujYtSMlsNjimMoL/PqhWncRAkSjISplINwgKiJFtkLEpC4NtWm6dodCVSX91L87kCsBN38UGN1BBaajO4A7PwHc8QlgZEf3a+U54MrJ6DUB0TU7Tc9tNbyuFNxWyAE2gw37IGzb0+bPqG6mM4/rzpVrjKFFRP7gD/4AAPC1r31tWKfQrDODrAGJkxbGLzds37sjZwTFk5y1d4qESUrTGJyhYBqJ5midkAAM7/w50/A7hBgoJWRyhmOzFezfPhIRI0JKfOv4pciQufDU4sdfuQSDcQj0KIwYfaIIX398n08SDgZnflfUWIG1RSlUOkfViox3qQnqRjiSltS1o0RIgUv87l0Z0zLxaEhwRygqcoLSF90KESGAk/8zmi6ozJJLqGshXWRw2lTtuhfajz8u9Ntn1ygK4lpAaZKiFuAUXUg1NQtflqQoiLJed22vpiQWkXEdoDhFj29WSETlRqKvkfBSNoyRLwjQPfrQS3orcf0paZedB+h7/SpdS+m66PN6OU+3+hPNhmNDlf+2Wi1Uq9XIl2Zjo0SI26XAsxfSRMhI3sRUKed/xlO26jKlwyVMYgeMNyyunz9VjDGU8uE25aC2Q0iJpic2VOTj5HwV3zp+KdGLI3y9O8byZKrWw1pUNGisYHqGaXS91YbVcaBg3C8mHqXwpwHnTYzmTb9bqh8Rokg7p5TAojvamwgBotEQgDZX4dAL4DqU7jh7mMREJ18LZUkeny8yMQ3sv4ds0f05Lx7cJDOyXIEebxZD6R1OX/lxb5MPvaOvv9AeURjb6c2VieNFeNTzC+PAbT9HAqYySwIj6Ze7WabIiNuC/4D8KBXIqq/iJD3fdQAzQ/RhED4baULmzFM02Rjw/Eoc9G2EpgfWbTo2VLHqF77wBT+Sotk8DNL6O0mEhFuFR7wUQrluQ4LEiBq3oTpYsmoiIQGmnpjxOQxAzuBwpcTeyaIvQiyXNmnTs29XVvePvTyPmat1HJutJHpxPHJ01l+3um+yZKLhBBsMib329FN42YxRZ8x4wUC5QXN/8gZ9+u0kHNKiFHHBoR4ziJqgpHNWZQkT3O5NhCjDsfDcE3+TEvQKCQtoLQNv/iBQ2p5+LGVJHu/SYJxcQrkBOF6LrPLq4AYZjKkZMyuXgVe/GSpOEhQlUe8S43TbyqUgDaM24rPf9aIBKahfcmsZyBWpWFRFQxgPaiwA+J4lN7wHyI8Arx2mKIldj07udb26EsbpWEoIpUUfVuuzkSZkrJp3O7zXSibPrwG6d66sdduvZiD0JEQ++9nP4g//8A87PubkyZO49dZb+1rM5z73OXzmM5/xf65Wq9i/X7dKbWSUcEhKN/RKUkFjw3ax3LQxXgzqHZQYWapTykD6G3ZgZZ6EmsAb1hz+374MMADbRmnw3OKKhZOXlpHnDJYXKeAMvj28KySajgtHSBw5cyVxyJzJGZa8tMdUqEWWc46pUs4XW66QyBkMArJ97QhcXQGynC/lTbzrpsnMs3yShEGaeBmU4IwXPI8zF7+742nct/cnsx+kMgu0VmhjlvA6XEIihufovjd/ELjh3YH/Rhw/NSPbuzTU5qvmqnAj+EVyWkD5deDWj3nHcakDJj9G51LGX4CXFuF0bOEE9SZqIz7/NNps4wE6X3GK/i0cEgxXzwfpIul13kR+hz1R9sZp4N2fogF34W4QKcngbOZvKc2THwVgUPSIm9How863UlHt6M4Unw0vYiEy+GykCRlukvAoTpJwcu3k+TXq9ejUuaIH1m1KehIiv/Vbv4V/8S/+RcfHvPnNb+57MYVCAYVCoe/na9aWJHfMx471L0biQ/cMzlD1BueFuzZUyqCY42h5zqqqTCXcuhr+28wQFJn24xgdFiHlug1HCJgJIiR8LY4raSYMKELSdIzARt52UWmS46uUZKrGQi2ySZEfw/MDYYz5XT6cAVPeVN7lpo2caSQaynV7P7J0Qg26JijsUfOL1vdx3+hrAHoQIhPTwB2/6G2ygqzVa4u0sVo1KgS99QHgupvTRQjQoe4hVFuiNn1mBOE3CeD894AD99Hme/F5EhuFce/AkqIxAK3JaXq/fJz8QsyiV1xrAE5KfYhKUSgX01YFWHwVuOkDwNkn2yf2Khjo3MsL7d0gCyeAH3+PoiSGSZEHq0bfjULQxVNbpCjRxeeBG34y2WfDdYLndYpWpBmGSRlEjZwmCQizSIKt19ZgPbBu09KTENm5cyd27tw5rLVoNhFJKRQyxrLw6FGaIdGPGFHPefTorG83bho0UVZ1yrhCkr8S58gVGHIGR6XpwJUSnLPI1NlwygaA740h4x8iuzBaMP3W3JYrPPdVqgcxYiKEzhNEL9R3ZXam/u0/1zNfU/fH01Aq8jNeMDDi+XyUcuR/UvBaiJfqFixX4n03bu/bUC5uXpf0/g26MFmtcf/3Lvb+5HiLbatKn6qNHN3XqgYbXxqd2nrPHqbNXE2Y9dM/XvoAoKjIuWeBsV3tn/btZiBanIZn5S69VIhF0RKzSAWsnWgueef3fq6/QZv92/5p774X6nqtZWBsD3DL/XT7mSeoY2h0B3DLR2mNnJNgaZSpU+f2nw8siwH44m95PhB9adGKNMMw13ttwYKIj5Hvr2V3tYW0mnVjaDUiFy9exNWrV3Hx4kW4rosf/ehHAICbb74ZY2NjwzqtZg1IEiEN2/WiF8CK5axKjADBByZKjUs/wlBu2N7sGoaGJQJPCsYiKRxlNCbVXJeQIGGMgbH0lt8kmrYLBomcaeB9N28LClRd+PNjwmKEMQbmpVJUNGa8GKRffJ8OKSEFCajw/fQakOgaL5heC23Q/RI2S1tcsbwIDW/r1ulVOAyzEyqJH5y7ik+d/SSuQwXY/v7+DtKrR0iYTnUP9TeAN70HuHScNtHcCN3n11p4YZHZF6j4M/JpX0VDvN+A1jJtumS3R8dpLJFbaZrviA8Dbr6XzNAAEhiT13cWWGn4qYtxEgTqdWlVgeIEfWcMGNkOrCzSsLz8qDd1V0Q39LD46yb6kgzDVMeTem0ZA5jZXpyaJaKxmt8BzbozNCHye7/3e/iv//W/+j/ffffdAIDvfve7+OAHPzis02qGTJoIUdGKnEGCoV8xcnK+ikePzqJuOxjJGWg6IrTRB9GFO/dNRRxLiyZHcazgb+SlHIXQVTQBCESIqqco163Mha2coS3t8djL84DlwEoQI8ppNcc5HCFQ9MzOFP76GuRqOhEbJNhLsegzZxf9GpTVDqMDBh/16MSB1/8Se3MrGL/3s/0fJEsR5a6D7S2d3eaLQNJz7QalK4RFj/ULPr3HrywArVr0075wA+t1KemTvpkH4BW6Cps6cfa9A5j5fkiMhF977/hmAZh6E7D9Tf2/RlKSmDgfS12cPwK/pkTddvrxwBberlPURjgx87Ee0yBJhmHlGUrHqNcW8Lp8QmS1VdcD6zY1QxMiX/va17SHyBYjrZg0bC4GUCrFcQM78ayfsJUIWbHIXrzpCD/N4koJzhimitRGemy24rfOLtUt2K7ERMjAS0oJR0iMFmjGiqolmfI2/IbtdqwVUctVQsURss2kDECiGFHPKZoGivnAZyTeleIIidG8Cea9tqo7qFOLbDhtoqYQj+aNgU7GXWvGC+2TnDPTJiYERR6MWNFlmkdIt/ki8Y6b2ReBub+jfzNG7buQwI3vBiZDhZXSDaIIAG3O49P0HD8NspPExczfUDoiP4427Dp12Ezu7f81AqiV9eWHKQ1S8H4nciNA2UuJ+beVQuv2Oo+sFaAwGd3QB5EGGZStuh5Yt+nZUO27mo1NWjFpWIQA8DZU+jxnOQKnF5b9DdEVMuI9Ev63Oi5AZmGuIJ+PUs5Ay3H9tIv0Ih2nLy/j9r0TePbsoj+4DkCbzToAf1aNIyQa3kC3TsEQ4aVyxgo0AE5K4NhsBfceDKzMk8SIioQUTQOFXLvNe1JXijpGt46VcNokzWslIkZWUTi8aYiLiXDxpCq6jHuEqA0p60Z43VuCLpiX/r8AJIX91dRbIw+UL1C9RXij23NH8G9lslV/I0iDNMvUhitcgMtoHYjCMCkCs7wQjQr0YtolBUU+ml4qZsR7XbgZzL0pebcJN2rKxljgKqv8QpT5WKc0CFj39Q3KVl0PrNv0aCGi6Ym0YlKF9Oe4BNEL9ekciE7xDX+6P72wDMsR5N+EoC5EiRGVugjblB/YNY5jsxV/cJ3wClobBpmNhTfyA7vHcXphGY8cncVSw6ZZLKyz5wh1qwSRk7ioCr8ej708D7fpQDIJk3NwHnUqzdKVksWno5MIUQyqcHhTEBETseLJAx8FwNM9QnrdCM88RRNwlW+I8t8wi52jAVICF56nws9cMUhnWItUwFoYo/WHJ9mGSYoKdBoaF+fyKYp8KC8Su0mRD6cZtP8qcWStIFLGrYqrwlGRM091T4MA2de3WvTAuk2PFiKanjmwexw5b2y9KiZljESDkIGvRTh68djLc4CkVI4y8VIiRRl+cUYTYCteyy5HIEaqTYqUuELCNLif7nBcgamRHJqOgXLdgusNtXvXTZORzdfgDAd2jyNvctRa9KfWNBik29mVteXQvWN5A5whMeUR7jYhcVSG7cg2bxX1uKdOXsJHDu5JPUandtssw+MihcM9psc2HWmdM8o6fdet6R4hncL08YiDqpGADDZ0Ca+OokFRkbTjXn6FNmWXphhjdIfnveH5ifA8ALu9XTUt6tGLaZeKhqjIhyqiNfKhYlrQv7mZMHhPApJRtEY4gV+IZEA+JQ2i6k7WylRMD6zb9OiEmSYzysZdja0fLZj+EDklQsKo6IXBGWxHwhECpRxHzXKwYjko5jialosjZ66gYVFaopQ3MemZe6kuEYMzCEEdM1IiIkJURKCUMzA1kofJKS1ybLbSNliO1j2NsYIJsMCVNcv2XLddmJxFrNnDHJyewKc+cDP2bx8BJANjaLNyD0g+ozpGp+hFeHhceAidQtXsCEHeJmBBJGdLkzaM7fKJ9FqGTsRtws8/R4JDFWoKF5BeF4zbok1ahf/j6zr9hNeiKkh4CJeiEcLrnmmVKUIRX1eaVXna0LjE6zhFnS8K5omK+hvemvyFUqooyVQNgq6jWfZM2pp0W5pdfnUOqMxkW59GAx0R0WQkbuOuNstHjs6i1grmrKgP3SpFYnDut82anLWZeKlUjuVKvzhVFZyq9la/Y8b7EPrS62WagRJLS5RyBorePJC0gs1waknVoyQ5rsYRkgbuTZUCcRE/9umFZX9acFLxqIr8dHKhzRK1ODg9gZmrdTxzdhGOsLBtJB8pHBZenUpSemzLpmiSiicrsyQCem3pjEccdh4gHw2jQJ++7Rr9220Gz8mNkM9GWwpFzcIJ0VSi1PuNE968FyWednnO1ElRj166VfxCXVA7rp9jrFHxrWvR83NFSjlJAZgjQWuy9/8FGEJFue+lLp6RneRFUpxqj9ac+TZ5n2hTMU1G9G+GpiuqJmGpZkc+3R+cnsA7btzmP44z2kg5A4SQaNoCrisiIkS5kJoG8z/NMyCo77Apz6vG0DPG4HoiQfmHNO3k2ghAeYSQAGhYLg6fWmgbyHdwegI//ba9/lyarOZmSowkRUa6FY+GIz/pkZJsqG4ZgzG0HIGluoW65bSJkMlSDqW8ibGCuarzbXjSPCRcm0SA8v9QdIuKxCMO55+jCAI3SMRIERUhAEUDzFLUR0NFQ1TkQyGsoF3Vf345GhVJi3pcPkXD4YwC/HRT2rVcPkVizCzS43Ml+ipOklCwayRQChNkXgZBbcSMeaIhNMNGOFQbU50B3vIhKqI9f4Qeu/tQ8MU4vRa9RqA01zRaiGg6Erdxj0+NPTZbaZsWG973m64gkRESIWqTVp/+lZ5IFCNFam8dzZv42Z/Yh4/dPo1S3kicFqvwTb9yHPfeurstyuAKagUuGPTrn9Vh1Y/2NB2YnPlC5/hspWPxaNMRaDpU9KoiP/2Kg/ik3qJpoGkLLNUTRIgXWVJiaMuKkSQPCSmDNIiKNmSZ5JqU4lGuoioaYMSm8KrzNcuxdSVEQ9JQ3SpSkNfH+SPtaSZVp+JadC67mT79Vl2HY5FxmlUPrp8ZVDPitDwPDzt4rrCD1059ASScpEvpp/JMNFqjnjuI6byaaxKdmtGkkvQpP2lq7NRIDkXHQKVhw/E2eca8VlYJrFguGGgoXXyTNjx7c86Z7yRabQRW6I6QmCzl8A/uJB+F7756OdGXQ6FEiJCAmRAxoWuag+3IxIhKJ5RbqvCMyEbzJj701l347quXU4tHVboE3vW70rNyHyv07PmR9H6EJ/VKADwmQsJrHyuYWKrbVFS7AYpX937n1/Bh+wQwfX3/B0nzkPAHwoGiDUmtsUktnUkpnuV5EjOVC16EIMEJVbrA2aeoZVelUJKiIZ1oVoFcAajO0vPzY6BW4XzQrVKZCwSW5Q38S/LwqMwGg/Gg6juUaZjXjssM+jfPAaVtgGNTWmb37eRxEoZ7PihGngqBkwbLaVMxTZ9oIaJJpFOqYTRvYGG5BSnhT5RVG5+yWQfgpwoA+EWtcSt0FZ2YKJpo2RQ5yHntwEleGw3LjZiZJY2uVx4g8VqMk/NVv6ZF0cvcGeV7oiIxeZPj1j0T4IxFfEDUWpqO8M3eVKswZ1Er96xiJO39iE/qLZm8TYQAgUAr5Y3EKNHQkBITKz9GdezNkVqCH5y7it9gl7Dntg8AN/Yw6C5OmoeE9Lw+eI6+v+XehM011tLZySb8zBMkFJgJiJWEhTASLAsngD23Z4+GcAP+nBXOqQ31tcNA/ap37gaJCJYLBJfqvnEswGpQuiVu2jUxDVz/Tlq3qvO44T10zh8fpk6d4gRdD+D5rhQAuIBTTx82JwXwwp+216gobxFtKqbpAy1ENG1086lQm99SwyYvEdCANioWDYa2SUmdLgzAaM5AI2LXzjzzLxIhapMPD3pTfhoA2qb8JomRsAhRXSvhQtEfXlhCzXL82hAAkehNFlwhfaOzB+6YhsFZxCNkpUVpm2rT8efcGN754ikTIFukotv74U/qbdio2S7yloNSPvhfu5NT67DZe+UZ3H3qP+Dorb+FuV3vH/wJejUl60TaJ3rTcxtlZpCqaMOrozjzBG22Zw5njIYwBBN4W8D8MdrcVTTEWvEMzwDYKrWhlIWMRnvCER7GgYXjXirKIIFw+RXPmM0FmKTOnbilOtDZ/CvNUfX8c9pUTNM3WohoImTxqQDgb3RLdRsVL5XCeVSEuEJiLG96fzYlJoum7xGiBr0pEaKiEq6QMDlDKc/bREg8PRS1ebdhcOaLkPBjy3UbT5++4qUu4NepuEJmFiBx3n7jtsRuHGWYBniZAAm4EuA8OWXSLVKR9f3wxUidxGHBez/WU4Qw6eKWi9/ASPMSbrn4DczvfA8ka4/WrIpBeUh0sgkXTrB5pwoRwI+KnHsWaLyR8bzwzuUJi/kfkfDJmxTtcLypv8INBEV+jFIkUpCQUEZo4QjPgorIqMJTCSx7Ra6FcbqmG9+b3UAt/BolRYwSp/NmPK7mmkcLEU2EuI17WndKeJYLA1CzXIwVWOKsFNVqmhckRsKD3sIihDNgwotiQDK/3bWTjXkgRspe3Qcij/ULRUNrp1oP8mTqVYdwBhTM9im3/rH9Fyj8A5A3WGTonXoNu4mEXt4P1dIsEbwf6yVCAGD6ynPYVn0Vzfx2bKu+iukrzw0nKjIIOqV47AaoCKeTCAH8qMjc35GYaMW9YxJ+2aSDyC+K9PxJmhVKkYR/kZT1ul2notn8GNB0E4zQBEVmlHgBvLoVh6Iuo9dRmin+vG50qgFJms47LHqxt9dsCrQQ0bQRTzWkFYRmmZUCINJq6gr4g96atoDJmS9C4lGMI2euoGBy3ycjTFiM/PDCEhA7BhAtFFU1GsIrVlGGaVkI6juAqZE8iiZvS6Wo9AljwFQph2rT8efOFEwOg/PEepYsIqHf96ObXfwwUdEQBgErN4FS6/LwoiKDIC3FU7tCNRtOyyv87PRLw2jCbrNMxzFLVPyZG6OiUscmcTF1I7XQglH7bFhAtKrAzltpKN75I0C+4LUNN6jdlhn0OGuF2nKTCkEj0RDmL42WLry6kh4LSDfSYLle7O01mwItRDSJpG1+nTbQ+OanblOtpuW6jZYr8I4bt/lD4CxHtAkIALBct83oLI4qnL1UbQEM2DNeiKSGlptkiGaGRun6YqTT6N0YQlJkYrKU8wfqhVMpSTUcjDEsN22MFYKoj7Jc7zTYbpDvRze7+GHiR0PMSQCAZU5u7KhIWopHOMD4HkqRLM/Tz/WriAgSxsggjJv0Kf21w+TT4XqiRjqeaCgBTQmYOeDuf9rZlv31vyUBUgjVigChbheLxEm8UBUIoiHMCJYZFlitKjC+G7BldvGwUQbL9WJvr9k0aCGiSSVp8+s0GRaIDrWLb85ToUJTAH43SVyEMMYwUcqjXLd8bxEAifUVNculCAuLpoeY151SadheZw49p9uguzSKJm+b6qs6cZIKScOFu0oswBMj/UYqen0/1qtFNxwNEUYBAOAaBcCp+FGRTUNYoEx703Q7pQYWTtBGzQzArQctso43aC5LJCKeAnFt+lKoQXXNMokRbgQiQApam0olSaAtiiNsEla9REU2ymC5JKM3HRXZ9GghoulIlqmx4ceqKbedXEaXmzaeObsIgzHsGGtPuwCe6BjJ+4PslLdIOOJBpmZAPsdw576ptnZeJVzoGEHBqGW7WLHa/6CqVbAEsdJyXKy0WGTT71ZIGr9u9foVTNY29C4rWd8P1YW0HsSjIYpwVAS4fV3W1hNpgiMtNRAu5nRtAJ55mHS9QXOF7mkM4QKvPRVNgTATyI8CrRUAgkzIcqPe7BtGxarbbyIRUHmdBE84/eU0Qifw0jVS0nGyplQ2wmC5XuztNZsK/e5punJwegIP3DGNbaO5rp/i00SIQkUqchxwhCD/i5Q0CUUhaOqt8hYBoiJEAmhYwi9aNQ0ecV1Vx2AsKBidHMkH6ZoQEiRWOIvuO5wBecNoizyEB9BlcXpVouH//sFbEl/DrB083d6Pk/NVfOXps+vioOpHQ6QLwfOBm6eUcDl1eqj7NzxJQ+fiqYGwW6j6tG7kg9Zd6dL1uxbQuBqkNZIG5AHA+WeBpQv0/PAwOasGQASW66Z3DrsOlM8DO24hsTB5PXDXPwHu/uf0Nf02RIphuUHrcxrd17LRSGsd1vbxmx4dEdFkIkuoP2uradMRcAR5eLRc0bEAs5g3cM9N29v8QpI6bdK8ReLHMDmDmyIaVIEpZwwGJ2dXk3MUUyIPvRaSdjIs66WmI+39UKmiToP1Bkk88jJVPYXx2kUAwEjrcuJzRheP4V8v/gIKxdLqzMyGSVotQlpqIFzMmSsCRRatQ7LrwOgO4JaP0nGS0hhSUBss4/TYAx8FwIHyRSpcNfIkNhij80hJ/y5fDNYRjlxIQc/LFWnzblYBCOCmD1DBrGIztNV2ah3WUZFNjxYimsx0C/VnaTVVnSyqbuPQ9ATmKs2uBZiquHWpbqd22iR5i4RTF/u3j5DPR53ah7eN5GA5ArVYmob+vkuMFfO4c98kTl9eThUIrpB9FZKGSRMP3dIrnYzPwmZu6niDJkk8VcYP4IXb/jUMkWCD7rHt2Fdx104O/MQvDXxNAyNJcOy6NT01EC7mtBIiUYZJdSLFyfRizsunqCC2OEEFpZIBI1M0e4YZnskZAEg6l2rtdVokOOKbsTpeYdITMFVyZb18gkTOZtq4tX38lkYLEc1A6RQhCI+p5wwomgbmKs3EKEZ88w4fN6nTJkmMJAkIZXg2WcphJG9iJA8wZlMxaQhHAHsni7j/tj2492CyJXrSRpylkDR+jCTxMHO13lEAdTpOXJwNQ4ykiSfBc1jY8fc6P5n/JW2KG5W0WgQp0lMDOw+srpgz6ZxnHqeUjHCi3Squ47mphn4nK69HN+N4BMFueGvzTNcun6CZMpuBjdQ6rBkKWohoBk7SpqzmrqgJscqPo1sUI05apw3QLkY+dntQEKrSRo6Q2D1eAOfBH6zJEk0VbjpRV8iTl5bxylwFt+2NFl0CnVMgWT080sSD8lAxOc8kIjrNBRqGGFnryMuak1aLcOaJzqmB1RRzxs+pbOUlgMm9wC33g0r6BA3Tqy1SAStAgsRuJqeQcqO0cVsrAJTdu0vH2HVoc2zcG6V1WDM0tBDRDIXopmzBcmVEhKiOlixRDCAQEk1bdKw/CXeofPfVy7h1zwQMziJpo3CbL0CRGtubISMBv0YkbzB86/glcMYi68myEXer90gTD74TrKRJvQ2r8ybfbQ7NoMXIWkde1py0WoRmFbDmgdJ10ccPIjWQdE41YZebFB0Bp+MvnPBm0YySN4lvWGa0p5BUBMFueGZsHH7h6maKimyU1mHN0NBCRDM0Dk5PYOZqHUfOXIk4kyYNfVNi5KduS25r7cXqPG12S6dIjZQSBo8Op1MRm/gE3ywbcafC3jTxEHaCpbVIWC6AFDGStTg4y2C9LKx15GVdSKxFkGRKJlxKk8hccNcgUgPxc/oRDEbHduzohFvXpkhMYZJadePryI8GEQTlNSIFIkpbuMDZw5sjKrIRWoc1Q0ULEc3QcIXE6cvLMDmHkAITpXyqQ6raKL93+jIOTk8kbpSD6FCJRGpqFloupWOU0Vl8Qm54g80y+6bbRpwmHpQIIUFEt3FIuFLCdgHTaU8BDUKcZWWtIy/rQlotgmsFc16aZRo0F3+ds6QGknxJks6pIhjMS8VIJ5hwu3KF7pNudC1SemZmV2idKoIQ77jx1+IC9Td0kadmQ6CFiGZohDdKxxVtQ98UvWyUq+1QUce48EYNR84sAgBMnixCgGCDXVyx8MzZRYzmjVVtxEniIRqVCQzbKIrEMJESnen0esRf29UMvlvryMu60WnwnZmnaIKRA95yLzC6M/rcLKmBJCO0+DmVEFHuqWqQnutQa+/17wTOPR0YpakJuuWLwMz3gf33kJcIMyj9cv5IrOMmREsbgmk2BlqIaIbKajbKtPbVfjtUFCfnqzg+V4XJGRwh4YhglkySjfxy04YrJQxvo13tRhxff91yICR8kzUlQpKiM0nHHoQ468RaRl7Wlay1CNe9JRpdyEKaL0n8nOEIhl0jAcI9Z9Xleeqi4QZQnKJakcoF4JaP0DHtBrB0zitWPQkc/7/Izl0XeWo2OFqIaIZOPxtlN4OvXjtUwsdVEZpd4wUsrliwXAGDoS1io9aXMw2878btbRbycfqN7OQNA03H9b1VkkRIt2OvVpx1Yy0iL+vOMGsR0ozQ4gZkFzzPEGbQ0DzGSIwIl+bDhAtm/W6ep6LHXjgBXHwOsJaBsT3UcZMW8dBFnpoNgBYimjWhl40yqzto1g6V+HHDdQ47xvJYqttoOS6W6ha2jeS7mqoNaiMOvyYAPDESzMSJi5Bux+5XnGVltZGXH5y7ik+d/SSuQwXY/v6BrGlTkHVGikrTAECrDN+wTNWmACCbd++fRo4iJBeeoeP4/iNPUJdPYdwbwMd1HYhmQ6OFiGbNyLJR9upRkXXKbKeOj20jOZTrJASUGOlmqjaoFEj4mJQmEv5MHKB3gdOrOOuV1URezi/WsDe3gvF7PzvQNW14Os1ICQsElaa5eo7SM/lC4Pth14Pn8ljXTrNMjq1A4D/Cc+TQqgfDaTYBWoho1pROG2W/HhX9ihAFYwxTITGyuGJhrGhmni2z2pRE+DU5sGu8q8tsluMNs1B02JGXLUUvM1K4ScPrzn2PBEghZOne8pxocyPeTd4wQbtO9ztNerzyH2GcbtcW6JpNgBYimjUnaaMclkdFLx0fUyM5LP7/27v/2KjKPY/jn5m2My20BSqFUlsqhSuICHErsFSvlwpXa3ZVclf+xIINawhwL0KMxawhJGvQQKKGS/jxT/1jJciqSMKNUYL8MFF+iMtGfpRNEaS0ikWgpUOZmc45+8fQWsq0dNqZPnOm71cySX+cOfP1RGY+fc7zfJ8WW5bsO7qyRqpfiu0Hcedr0nlfnb6eO94TReM98pI0ot0jJdLxodv79thWeAfflNtv2+2t3uUKr6xpC/zef8QKhbutpmWwMRwSHkEERvQmhLTrTxiJdsVHZnqqyh/Oi9jWvbN4fBB3XQWT6B/y0Y682N3seJy0ot0jpbvjXalSxojwfJD2HXyl8FwQ35VwqGlvUta5/0ig5fbOu4yKILERRGDUQPSoiNeKj3jeAon37ZVY6W19Z35u1v/92qL9nsl6Ps41JYxo90i51/Gdd/CVwl+npEpWIEL/EYVHUtoC4aXAbAyHBEYQgVED1aMiXr027lVHd71QYnFup2gf8Qq0WVofek4ZDan6c37AdFnxF+0eKdEe3/lYX6N0bt/vt3GkcKAJ3pTaWm8fQ88QJCaCCIwbqB4V8e610dW9eqEMBp1vu6WluOQPpeo//zdTUkvyh5Fo+5JEe3znY602KSuPjeHgSAQRJIR4dweN9DrxXPHR214oyazr3B9PsE4Zrlu6ZmUNnjAyUNgYDg5GEEHCGKgRi3hPBo22F0oy6nwNXJKG3vhRqQopNT1TIz2WrvjdhBEAkggiSDADNWIRr8mgfe2Fkky6XoObgZBcLinVmyl5M+WSNNJLGAEQxvRpJJyHxmTrXx4ZoxFD0+LaKGsgQoj0+4qftpClf/zws8783BzT100knVdB9bxBYDiMXA+49f7poWqzBrhQAAmDEREkJKcsX20Xz14oPenPqpx4iLQKKhLblq743RrusfS3yT6l8icRMGjxzx8JK5E+YHvS+1GAcBhpDYS0r+ayQlb/Gnyd+blZmw/WJtwIS/uIVmqKWy3+trsambWHEK/b1n9M47YMMNgRRIB+ah8FyPCkRPzgbdfXXiiRAkv7CMw1XzAhb/d0DiP+NqujSSghBEBXBBEgBu49CtC3ZciRRj26rspJ1Lkn7dckxe3SNTuTEAIgIoIIECPdhZH+hJCuox6nGpoirspJ1DBy41abXnP/l9LlV11gKCEEwF2YrArEUKx6oUTqRfLf39UpELLkTXVrxBBPzHYojqcHL32sf8v4Xvf/07N6/7RLf5tMCAFwJ4IIBo2BWmHS314okVbgWJatW7fXuPrbLN1qs5SRltLxnEQNI5ODJ5U1Mk9/zg+oLC/A6hgAd+FtAYPCQK8w6WsvlEghpDXQppbA73uIWLZ0/WZArcE79xWJ9aqcWCOEAIiEEREkPVP7vkTbCyViCAmG1HSrTS6X1Hn+a3sY0RBPx8hIf3coBgAT+BsFSc30CpNoluh27UXSGgypqTUo27aV4rr7XJYtNbUG1RoMxXxzQAAYKAQRJK3u9n1JxBUmXXuRtAbaOkKI2xW+7eLuEkbcrvAoSFNrUNduBhIuhFz/epsmBU+bLgNAgiOIICn1Zd8X03MqOvfduN4alNUphLRrDybtecTtCtcdCNl6dkpewoSQncfq9JebO5WX7ZUeXWC6HAAJLG5B5MKFC6qsrNS4ceOUkZGh8ePHa82aNQoEWLqH+Ortvi+dw0iitEt/aEy2/nVqvoZ4wtO3LFsd/UhCli2Xy6XhQzwaPsQjSWqzwmHkjxNG6uH8YcbqjmSoN1V6YqXpMgAkuLhNVq2pqZFlWdq6dasmTJigkydPavHixfL5fNqwYUO8XhaDXOe5FiOGpN1z35drN8PNwmzb1q2glRBLX9tfe9f/1MsXaAuHEcuW2+3SsIw0ZaSlyLZtpaemyB+y9McJI/X0w3nG6gWA/ohbECkvL1d5eXnH98XFxTp79qw2b95MEEHcRNr9NVIY6Zjc6XYp0GbJ7VJH47CECyP+NsklZaendoSQFn+b0j0pmvfw/Zpyf2KNhABANAZ0+W5TU5NycnK6/b3f75ff7+/4vrk5cSYTwjkidTftOs8i3IJdshW+tdF5MmuihZF//NCgYJutkGWzOgZA0hmwyaq1tbXauHGjXnnllW6PWbdunYYNG9bxKCwsHKjykGTute9LpBAi9TyZ1YSHxmTr1bkTNe/R+5Wa4ta1m0FHhJAVN9abLgGAQ0QdRKqqquRyuXp81NTU3PGc+vp6lZeXa/78+Vq8eHG35169erWampo6HnV1ddH/FwG3RQojPYWQdokWRlLcrj53ah1oR89fVcneFzUldEZZEx43XQ4AB4j61syqVau0cOHCHo8pLi7u+LqhoUFlZWUqLS3Vtm3benye1+uV1+uNtiSgW3ft+5KWIrlstQYsZfdyMuu+mstRdUiNl2g7tZriTXVr5B+elIpKTZcCwAGiDiK5ubnKzc3t1bH19fUqKytTSUmJqqur5XbTtgQDrz2M7Ku5rDmTRkvqfv5Iu0Rtl54odQBArMRtsmp9fb1mz56toqIibdiwQY2NjR2/y8tjqSEGVqTRhHtNZnXCXAwAcLq4BZG9e/eqtrZWtbW1KigouON3tp1Yu4JicOgcQrpbWUMI6Z8LV3zKbLtmugwADhK3eyULFy6UbdsRH0Ai6G4yKyGkb65/vU1bri7SyEwP80MA9BqTNjCodQ4jTlkam8jysr20dQcQlQFtaAYkoq6TWQkhADBwCCKAnLM0FgCSDbdmgNsIIQAw8AgiAGJicvCk6RIAOBBBBEC/tLd1nxQ8LRX+s+lyADgMc0QA9MuFKz7lp7Uoa85q06UAcCBGRAAAgDEEEQAAYAxBBAAAGEMQAQAAxhBEAPTZzmN12nJ1kekyADgYq2YA9NmKG+vZXwZAvzAiAqB/huaargCAgxFEAACAMQQRAABgDEEEQNTa27pPCZ2RcsabLgeAgzFZFUDUHrz08e227lWmSwHgcIyIAOiTLG+K6RIAJAGCCAAAMIYgAgAAjCGIAAAAYwgiAKKy81id/nJzp+kyACQJggiAXjt6/qreuf4qbd0BxAxBBEBU7lMTIQRAzBBEAACAMQQRAABgDEEEAAAYQxAB0GsPXvrYdAkAkgx7zQDolfyv/qqngqc1ckyB6VIAJBFGRAD0Wt6YAunRBabLAJBECCIAAMAYgggAADCGIALgnnYeq9Ok4GnTZQBIQkxWBdCj619v05abO8Nt3ZkfAiDGGBEBcE/sLQMgXggiAADAGIIIAAAwhiACAACMIYgAAABjWDUDIKKj569qSe2/a5h1XaKtO4A4IYgA6JY31a28P/xJKio1XQqAJMWtGQAAYAxBBAAAGEMQAQAAxhBEAACAMUxWBXCXncfqtOXqIqW6XaZLAZDkCCIA7rLixnr2lwEwILg1AyCyobmmKwAwCBBEAACAMQQRAABgTFyDyPPPP6+xY8cqPT1dY8aM0YIFC9TQ0BDPlwTQT/lf/VWTgqdNlwFgkIhrECkrK9POnTt19uxZffLJJzp37pxefPHFeL4kgH7YeaxOU0JnlPfwn6RHF5guB8AgENdVM6+++mrH10VFRaqqqtK8efMUDAaVlpYWz5cG0EfetBT2lgEwYAZsjsjVq1f14YcfqrS0lBACAAAkDUAQef311zV06FDdd999unjxonbv3t3tsX6/X83NzXc8AABA8or61kxVVZXeeeedHo85c+aMJk2aJEl67bXXVFlZqZ9++klr167VSy+9pD179sjlurtj47p167R27dq7ft7qa4m2TAB9EGz1qflWSHZLq+lSADhYsy/8HmLb9j2Pddm9OaqTxsZG/fbbbz0eU1xcLI/Hc9fPL126pMLCQn3zzTeaNWvWXb/3+/3y+/0d39fX12vy5MnRlAcAABJEXV2dCgoKejwm6hGR3Nxc5eb2reOiZVmSdEfY6Mzr9crr9XZ8n5mZqbq6OmVlZUUcQUFkzc3NKiwsVF1dnbKzs02X42hcy9jgOsYG1zE2uI6x0dN1tG1bN27cUH5+/j3PE7dVM0eOHNGxY8f0xBNPaMSIETp37pzefPNNjR8/PuJoSCRut/ueSQrdy87O5h9ZjHAtY4PrGBtcx9jgOsZGd9dx2LBhvXp+3CarDhkyRJ9++qnmzJmjiRMnqrKyUlOnTtXBgwfvGPUAAACDV9xGRB555BF99dVX8To9AABIAuw1k4S8Xq/WrFnDyFMMcC1jg+sYG1zH2OA6xkasrmPUq2YAAABihRERAABgDEEEAAAYQxABAADGEEQAAIAxBJEkd+HCBVVWVmrcuHHKyMjQ+PHjtWbNGgUCAdOlOc5bb72l0tJSDRkyRMOHDzddjmNs2rRJDzzwgNLT0zVz5kwdPXrUdEmOc+jQIT333HPKz8+Xy+XSZ599ZrokR1q3bp2mT5+urKwsjRo1SvPmzdPZs2dNl+U4mzdv1tSpUzsamc2aNUuff/55n89HEElyNTU1sixLW7du1alTp/Tuu+9qy5YteuONN0yX5jiBQEDz58/XkiVLTJfiGB999JFWrlypNWvW6Pvvv9e0adP0zDPP6NdffzVdmqP4fD5NmzZNmzZtMl2Kox08eFBLly7V4cOHtXfvXgWDQT399NPy+XymS3OUgoICvf322zp+/Li+++47PfXUU3rhhRd06tSpPp2P5buD0Pr167V582b9+OOPpktxpA8++EArVqzQ9evXTZeS8GbOnKnp06fr73//u6TwflOFhYVavny5qqqqDFfnTC6XS7t27dK8efNMl+J4jY2NGjVqlA4ePKgnn3zSdDmOlpOTo/Xr16uysjLq5zIiMgg1NTUpJyfHdBlIcoFAQMePH9fcuXM7fuZ2uzV37lx9++23BisDwpqamiSJ98N+CIVC2rFjh3w+X6/3kesqbi3ekZhqa2u1ceNGbdiwwXQpSHJXrlxRKBTS6NGj7/j56NGjVVNTY6gqIMyyLK1YsUKPP/64pkyZYrocx/nhhx80a9Ys3bp1S5mZmdq1a5cmT57cp3MxIuJQVVVVcrlcPT66vtnX19ervLxc8+fP1+LFiw1Vnlj6ch0BON/SpUt18uRJ7dixw3QpjjRx4kSdOHFCR44c0ZIlS1RRUaHTp0/36VyMiDjUqlWrtHDhwh6PKS4u7vi6oaFBZWVlKi0t1bZt2+JcnXNEex3ReyNHjlRKSoouX758x88vX76svLw8Q1UB0rJly7Rnzx4dOnRIBQUFpstxJI/HowkTJkiSSkpKdOzYMb3//vvaunVr1OciiDhUbm6ucnNze3VsfX29ysrKVFJSourqarndDIS1i+Y6Ijoej0clJSXat29fx8RKy7K0b98+LVu2zGxxGJRs29by5cu1a9cuHThwQOPGjTNdUtKwLEt+v79PzyWIJLn6+nrNnj1bRUVF2rBhgxobGzt+x1+l0bl48aKuXr2qixcvKhQK6cSJE5KkCRMmKDMz02xxCWrlypWqqKjQY489phkzZui9996Tz+fTokWLTJfmKC0tLaqtre34/vz58zpx4oRycnI0duxYg5U5y9KlS7V9+3bt3r1bWVlZ+uWXXyRJw4YNU0ZGhuHqnGP16tV69tlnNXbsWN24cUPbt2/XgQMH9MUXX/TthDaSWnV1tS0p4gPRqaioiHgd9+/fb7q0hLZx40Z77NixtsfjsWfMmGEfPnzYdEmOs3///oj/71VUVJguzVG6ey+srq42XZqjvPzyy3ZRUZHt8Xjs3Nxce86cOfaXX37Z5/PRRwQAABjDZAEAAGAMQQQAABhDEAEAAMYQRAAAgDEEEQAAYAxBBAAAGEMQAQAAxhBEAACAMQQRAABgDEEEAAAYQxABAADGEEQAAIAx/w9M2+Bon861rAAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plot_decision_regions(X_train, y_train, classifier=model)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part1-2-xor/xor.csv b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part1-2-xor/xor.csv
new file mode 100644
index 000000000..03b60e47d
--- /dev/null
+++ b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part1-2-xor/xor.csv
@@ -0,0 +1,751 @@
+x1,x2,class label
+0.7813059935422636,1.062983772073353,0
+-1.060523847336408,-1.0955499996814952,0
+0.6321253589114496,0.6740281575632703,0
+-1.4247121071777453,0.5352029348696286,1
+1.383160687312169,1.368509769346175,0
+0.9454882801858628,-0.049414190613787885,1
+0.9071847956199112,-1.024796266169805,1
+-0.9775608440170122,1.2095844156506257,1
+1.3448815052898297,0.5307284651833483,0
+1.2794368528556557,0.9592831484033915,0
+-0.8571163867454761,-0.8728766354598072,0
+0.9563649003753113,-1.3036108957882326,1
+-0.6998147289874339,-1.0417976454365725,0
+-0.43436958478926,0.917675178188759,1
+-0.4427469473430252,-1.4614165427791346,0
+0.5018481467028711,1.21390413578593,0
+-1.0625616729105598,-2.0263993237880324,0
+1.276296666605733,-0.7594932573014458,1
+-2.0235498822735885,1.250516079238175,1
+-1.1205814403698324,0.5238864585858407,1
+-1.0902972679103282,0.6105447730843874,1
+-1.0382517154008803,0.9241315557811305,1
+-0.6329881656938112,1.016406376149588,1
+-0.6317607586496516,0.6428600469696454,1
+0.826735252855808,-1.0035183082623187,1
+1.0487932331557412,-0.5422159791886876,1
+0.7806465506427813,-1.2019248037048587,1
+1.155596943707103,1.265664971651976,0
+0.5468798251792087,1.1773420691062157,0
+1.292693324711627,-0.6267162121262522,1
+0.7659900001367103,0.8242334828052511,0
+-0.8349900813879935,-0.7872372506079165,0
+-1.4724818968400686,-1.5607724240731318,0
+0.8137657287028192,0.9477621438549008,0
+-0.5718296799612888,-0.9211164664913091,0
+1.0323862288391652,0.5625935449832588,0
+-0.71949198426255,1.0756991196828736,1
+0.7799292922456206,1.3758752269407555,0
+0.6723200909171319,0.8722179839989146,0
+-1.6987339546873883,1.4430208704427052,1
+1.1341347415950727,-0.5806282952022248,1
+0.9247044963517047,-0.9040129077437163,1
+-1.0912351697108318,-0.9877907572481892,0
+0.7362037580496782,-1.3431036728710215,1
+-1.7907319084024294,-0.9007696894530384,0
+1.1241942656180015,-0.7530971295509391,1
+-1.0194581302220747,-1.1687578481153538,0
+-0.7487722287617408,1.2803975864211752,1
+0.7448996308872472,1.635429758483137,0
+0.6335978357239157,-0.8198466041381478,1
+-0.2672276461701196,1.2039554862173458,1
+0.9651509819947908,-0.768225192986879,1
+0.6142811979043002,-0.23915612264220112,1
+-1.1614098712563492,-0.8436949900204538,0
+-0.5335557564773822,0.9875819657739164,1
+-0.8374510375338721,0.9558546381483138,1
+1.063421610540308,-0.368147167909197,1
+1.618500663982209,1.259732287432295,0
+0.5208911504528699,-0.9195898276863576,1
+1.017297225388624,-1.0439789407374438,1
+0.6504812390152527,-0.8576912705777001,1
+0.8712016751340054,-0.5231371376118508,1
+1.0573976656552606,-0.6647678712028865,1
+-0.3236352280750191,0.7210032271655243,1
+-1.0121782680062938,0.7993857961460038,1
+1.2480524637109824,0.6547143744226231,0
+-0.8605359618036672,1.3094797714308755,1
+0.32361720298287316,-1.1774152731449536,1
+0.459636782621324,1.2829872928485506,0
+0.785782665528001,0.8161771761201285,0
+-1.160854690418603,-1.0969967285445847,0
+-1.0376512346141629,0.6660418424714266,1
+0.6557036128196789,1.4935485469759968,0
+-1.2066754041746157,-0.9487551178344364,0
+-0.6131495436565861,1.12212793744,1
+-0.78664415042852,-0.6817897403646818,0
+0.17889893473536647,1.684970607061739,0
+-0.8309359748948544,-0.12557192242890441,0
+0.5333969468017946,1.3142089332834437,0
+-0.917111152640894,0.6457063947806837,1
+-1.2142504683034325,-1.07868101285736,0
+-0.6941865762377388,-0.5794969314826999,0
+-1.0908035766122663,-1.7163297324082474,0
+0.32679644875241803,1.0970213791686672,0
+0.4897807589094453,0.7411051781169696,0
+1.727692691697255,1.4177522928796995,0
+-0.9424989303057096,-1.3921851156740905,0
+1.0338164394906624,-0.7557503519121614,1
+-1.1714704698970855,-0.9513559408032857,0
+-1.0286196927906295,0.796822743802431,1
+1.1285254852774065,-1.5756062058189984,1
+0.694005749993161,1.1754475088380751,0
+0.907597310176984,-1.0518401945221034,1
+1.2396307157730428,0.8355749931044393,0
+1.1958578973005773,-0.8991993598356147,1
+1.4807261549734287,0.1673037625140909,0
+1.050700825900583,-0.09114354349256139,1
+0.8912642218720326,-0.901156879993239,1
+0.6934182211884385,0.781316329532603,0
+-1.4518523887371355,-0.6144638528710337,0
+-0.9650135028938545,0.8273844354364162,1
+0.8396956799628819,-1.230596312631852,1
+-1.0402980895521023,0.6623252233884118,1
+0.9132468095898831,0.8218358547226506,0
+-0.8411103392682209,1.0401063910262036,1
+0.5594035385443009,-0.29375420615256104,1
+-0.5631135741837974,0.7742584643993151,1
+-0.49471481425230757,1.0543349351113798,1
+1.7796453858793517,0.5380390317447831,0
+-1.048174956271411,-1.5016024579037837,0
+0.07804762219059581,-0.9353698330079456,0
+0.3890099708313575,-1.1591080859906107,1
+-0.8343382420838531,-0.7431554395675181,0
+-0.9308633550331028,-0.03431983292354866,0
+-1.6384458424638935,-1.1504641710680774,0
+0.8147035766000041,0.3119247399151989,0
+-1.0900581022867937,-1.4283458437004746,0
+-1.2621286961682971,-0.4518413979985028,0
+0.8879984050420872,1.3016259357960147,0
+1.418676140676506,-1.2623175662399555,1
+-1.1352536924951302,0.762524546843009,1
+1.0305984602696603,-0.38146195090884116,1
+1.0389583754636675,1.4140293905891606,0
+-1.5707667575969215,-0.7777451065960357,0
+0.6139648413902277,-0.8998059047698059,1
+-0.8464805347201027,1.1827909994583985,1
+0.7311479300955186,-0.8989082381957771,1
+1.2452437586271135,0.6881694540122827,0
+0.7406085225369123,0.766338723211945,0
+-0.31511364611476017,1.0658114605577613,1
+0.9943430985279457,0.7796611399385207,0
+-0.863207601223432,0.5683414874302841,1
+-1.0253563071935134,0.2880578366793361,1
+-1.2711241426977602,0.4321712475403908,1
+-1.253256090479728,-1.0639906128312446,0
+-1.1600831254325368,-1.9487302842803431,0
+0.7728617702835741,-0.8697958879805691,1
+-1.1484738634523883,0.7838414882470985,1
+0.6732499800889824,1.4911120661370307,0
+0.6155400042668754,-1.0277792618649881,1
+-0.35632791378795453,-0.2770142273137524,0
+1.1790038932026419,-0.889211864035357,1
+-1.0636104649317153,-1.3338291081319675,0
+1.0678325738924679,0.5235817625220535,0
+-1.2065785791206145,1.1566111460248978,1
+-1.095005360894372,0.7350724379148486,1
+-1.943319175989703,1.3499188938110172,1
+1.2072657786487786,-0.5171823220656748,1
+0.6362330278494853,-1.1033735483588023,1
+1.7670295035534735,0.393282738013247,0
+-1.0853439840864605,0.9586960958150861,1
+0.8757973219329327,-1.0484661792669432,1
+0.9012460053126451,-0.8132653273464086,1
+-1.112963367691989,0.9909106252282261,1
+-1.2486792244998124,0.20667375085152093,1
+-1.0609977804358928,0.9051470845243489,1
+1.2902635392189372,1.749722905046548,0
+1.302488846012434,-1.1497517925494127,1
+0.2987034987621742,1.6432276753710027,0
+0.9476376735699624,-1.5668520500138938,1
+0.6285296748086759,0.2934686098371885,0
+-1.65780118841945,-0.7698916193145307,0
+0.7980923404430058,0.4224338368002385,0
+-0.929959029542513,0.36522426182295703,1
+-0.7334770235018834,0.6562682945112818,1
+-0.13593408749160624,-1.4995483804840182,0
+-1.00703109390309,-0.3509169175417814,0
+0.43085833044494987,-0.4438890875590858,1
+0.9106053833514234,-0.8204904215304887,1
+-0.9263044207500389,-0.5120875901779373,0
+0.9198369992292186,0.6562319066657477,0
+-1.5205781205243412,-1.483723492752824,0
+-0.596012571631922,0.6048634243839283,1
+1.0281697546052113,-0.7155492225822128,1
+0.5435980276358763,-1.2228465514203557,1
+-1.0545535131397086,-1.255346565728821,0
+-0.9977727727598088,-0.7447407847128535,0
+1.0063168736287313,-1.3636371632323292,1
+-0.3044003498613342,0.4071443255252956,1
+1.2047534158664397,0.49071226521171296,0
+0.7940074559250258,-1.565786897510743,1
+-1.1063368595782228,1.2115292350419162,1
+1.159715351120311,0.3390685835440307,0
+1.2143789577575588,0.49257125277746816,0
+-1.0434703580000297,0.4634649773573642,1
+-0.9033883167741588,-1.5163739241326768,0
+-0.5942137433855272,-0.950487043739885,0
+-1.045522568525959,-1.1999256519084747,0
+0.9230291897628462,0.9862180437375159,0
+0.8864345635777892,-0.7948987617100206,1
+0.6804842471752792,0.7951619347894161,0
+-0.46531583501771506,-0.8844267676292805,0
+-0.39215372361805356,-0.7628400693544017,0
+0.7806232498939073,-1.0244703766720407,1
+-1.4255031105711713,1.1110473375345615,1
+1.2688890558585146,1.0441424183535852,0
+-0.7924987934696649,-0.16635766096575114,0
+1.4403906501857622,-1.0194939145516762,1
+-0.5870392609856324,-0.40351781893267075,0
+0.9611454476672272,-0.5636426002370674,1
+1.0384025858864045,-0.603566029049914,1
+-0.8293391231985977,1.4402791159652863,1
+-0.7181896633608805,1.767920274325023,1
+1.077508102361648,-1.560119412798328,1
+0.719637120342898,-1.0211799025641823,1
+0.878614972848381,1.3444705298317507,0
+-0.5606318122017724,1.1136446475218893,1
+0.5981292089583998,1.0691677551929915,0
+-0.3989627776574007,0.9809000703586731,1
+-0.6101606473860837,1.0472033006682449,1
+0.9756885136045358,1.074705778691106,0
+-0.9281899540650402,0.8079445779277378,1
+-0.2448302858381661,0.8993757467814997,1
+0.5478992201989491,-1.4331490841862238,1
+-0.30900642865478845,-0.8479498384163855,0
+-1.6623032311349972,-1.106254625627281,0
+0.4758352935573796,-0.5531077906751792,1
+-0.9987297853360605,-1.3061575030820831,0
+1.2879730997534222,-0.12494244737185843,1
+-1.3802308187716865,0.7119213032288398,1
+-1.316250398666018,0.8852157674906214,1
+-1.2030351627938802,1.250926851128872,1
+-0.0605946551830842,0.9701264324775312,1
+1.0639266357085782,-0.4318336066873725,1
+0.9537450666497236,-0.9022365602382171,1
+-1.2181846031380192,0.39520917533860467,1
+0.8140118122641499,0.962898450543363,0
+-1.2815985539091082,-1.448508912420273,0
+0.6041509079242887,-0.9930656870222448,1
+1.186757233835662,0.9285294072048521,0
+-1.1278984691044742,-0.8091585144227019,0
+0.4985365275889021,1.2578168229356885,0
+1.0289623027945185,-1.2024439991566322,1
+0.8797483845993326,0.8178333749136022,0
+-1.083159604340138,-1.1465901255856328,0
+0.79382433235295,-0.5638827907092553,1
+-1.2004243623199136,-0.704217922345091,0
+-0.5405212144412368,1.1872901008036274,1
+-1.7447289219236444,-0.7608532824626066,0
+-1.1360564220868055,-0.4954867859351637,0
+0.3598119120668703,0.9503671531690275,0
+-0.7763132205220699,-0.9208033888720394,0
+-0.5120564014281737,0.8765477760334695,1
+0.866699846805664,-0.769512216766651,1
+1.0591139165294978,-0.9643136720102373,1
+-1.4430854031154505,1.6327841335506903,1
+-1.327378876739217,0.7261645513450039,1
+1.064552999917614,-0.8383751054694725,1
+1.1749124418733032,0.7580261130378134,0
+-0.844053823400353,-0.9268092118977291,0
+-0.7170120315289539,-0.7470718237804697,0
+-0.5356520072033403,-1.2739194438344703,0
+0.7719944890337044,-1.212893807826029,1
+1.2786359114441719,0.8702447485810498,0
+1.1870982166242572,-1.2977829130929284,1
+0.7941410196361515,0.9846674005858211,0
+-0.32668351336702256,0.8578285239474711,1
+-0.27776914940430547,-0.6569700733337701,0
+-1.21811130320408,0.7356632219989537,1
+1.0761863271273777,-0.09060654393672098,0
+-0.21412394641653076,0.9217208450485945,1
+1.1888451807653344,-1.4572616549466237,1
+1.198535764748661,-0.502769831096309,1
+0.6822347649912776,-0.7882138142356735,1
+1.517022758912243,-1.0031496356086262,1
+-0.013985808380075956,1.1670727843963487,0
+1.4948681843199487,1.4665112747130666,0
+0.8555527982019331,-0.8736581602858895,1
+-0.7955740490172315,-0.5597884517773801,0
+0.8907023110359507,1.0778659852301296,0
+1.3234156722126038,0.7607182410304435,0
+-0.6353293139423802,0.828632064203005,1
+-0.8005285584718431,-0.7173395427670534,0
+1.8617956239037452,-0.2585385376820606,1
+-0.7203765748901196,1.0438331365305686,1
+-0.7877437566734412,-0.769025682807958,0
+-1.1394742064496743,-0.338442943598922,0
+-0.6950774736597871,0.7088636554646702,1
+-1.0004720843090604,-1.0191824422902964,0
+-0.9621199528767871,0.3841240843080645,1
+0.2481841820061832,0.751692507378054,0
+-0.8290726675488991,0.9854950900566882,1
+-1.7146182730307498,1.4111533961339258,1
+0.7082346890527967,0.8398098918901238,0
+-0.828241438063286,-1.2344615896070534,0
+1.3414357591222947,-1.0987095918448266,1
+-1.4518683387618205,0.34617958132183724,1
+0.3328161413569573,0.84905339302559,0
+1.3968692767003905,-0.7248801540760752,1
+-0.3567841865258989,0.49724052277137964,1
+0.6444943734637381,1.125090542024461,0
+-1.2936121397229323,-0.9368124738776434,0
+-0.7739639361577758,1.3570060595716509,1
+-0.27549743482945505,-0.5432157430185786,0
+-0.6399642855143926,1.133805115457157,1
+0.6797928483564895,0.9388294331733273,0
+-0.5719465904502499,1.1761621334663634,1
+-0.7334905704981335,-0.5235486413305603,0
+-0.6220098224950728,-0.8795064581279788,0
+-0.6142469064649998,-0.9062910733384955,0
+-0.9345326288897844,-0.8272908480912693,0
+-1.045966167447599,-1.1216034763517462,0
+-1.2885457216689857,0.5607331616881138,1
+-0.537673673384778,-0.9347686880965549,0
+-0.590277510260216,0.8272522185716316,1
+-0.7077253604951814,0.8049780548041204,1
+1.3675539533805408,1.0434871729649557,0
+-0.79968981311363,0.8765697874816221,1
+0.6368843312382438,-1.2412818084120743,1
+1.0345658017464112,1.150637052471657,0
+0.986041821344405,1.065959520541025,0
+-0.8588439870981954,0.20820924881417094,1
+0.5974148574126997,-0.4264577445906332,1
+0.5570026029252813,-0.29096773023418815,1
+0.42260573437929966,-0.5904736226420924,1
+0.7621565687489907,-0.8107062455431037,1
+0.7456124132991632,-0.93569297586893,1
+-0.7466226798976167,-0.8057845702965349,0
+-1.451263547710405,-1.3525949333665668,0
+0.5893965335217345,-0.837478599334346,1
+1.4463301264408903,-1.0588751076438396,1
+0.40371264415314234,-0.17483251716669554,1
+1.3495954679799127,0.4738705091905488,0
+0.4955919303080284,1.6406015380495071,0
+-0.6147136638516211,-0.40902965492199456,0
+-0.8388172752331248,-1.3518720361355574,0
+1.2724157019116977,-0.9725882872694233,1
+1.4327352765464898,0.6740650828943572,0
+-1.0699042750599168,0.7790450959732548,1
+0.2803789367858287,1.0926723406192205,0
+-1.186886918409184,-0.8360824075031239,0
+-1.451810423687859,0.7610983584198271,1
+-0.5339212863752544,1.1030094754214401,1
+0.9225349614567826,1.0663226377943,0
+0.6879317628473851,0.7358292128275554,0
+1.2690920107888994,-0.739080025499422,1
+1.1770955937675953,1.076714591109277,0
+-0.6717160616919413,-0.003228442762960022,1
+-0.9383840283168531,-0.9087422914909005,0
+0.5209772914975366,0.9462937440607732,0
+-1.1438939956940992,0.6251048263136008,1
+1.2098679264189025,0.9718091610015857,0
+-0.30887012997973645,0.35817248139318025,1
+-0.05319844385965487,1.1497104392755524,0
+-0.6471738755397253,0.789410136014035,1
+-0.53173249898647,1.1470381280742064,1
+1.4784245791472554,1.6230802716616255,0
+1.091691753570131,-0.8426033386853894,1
+0.9184129594015348,1.0843754759793716,0
+1.449959274107483,-0.6197842947205362,1
+1.1835669001998548,1.4050214722519756,0
+-0.7570819895494014,1.1254008199180376,1
+-0.9107146712779243,0.7091838637533904,1
+-0.7505524351852177,-0.8722985683219556,0
+-0.5696056403144383,-1.0064614356737307,0
+-0.992583170420623,-0.9485691866957053,0
+-0.8760874545109949,0.6865104782863674,1
+-0.6008273870980045,-0.48936297677019264,0
+-1.0243825592755231,0.19349298830075512,1
+1.354370777140758,1.3234470808323737,0
+-0.7084320445161557,0.9808500289399399,1
+0.4266603188891261,-0.9234311124909406,1
+-1.6606316881072307,1.1436111373263786,1
+-1.0198837279936233,1.339703662364049,1
+0.9649098548626205,1.1411334027964382,0
+1.6726028196867881,-1.0208401734044432,1
+-1.1387342793702864,-1.317852672673592,0
+-1.6361927670256868,-1.2432946218882022,0
+0.5428136938038672,1.371727350717942,0
+0.6107741926307642,1.62828385659877,0
+-0.3587899215079129,-0.7051924718836433,0
+0.7760731015862018,0.6527726200613706,0
+1.0130394630185808,-0.8342754599215136,1
+0.34424931091093314,1.1512007137706128,0
+-1.2050336537178945,1.5646732898393079,1
+-0.7807105741783934,-0.8560864227138196,0
+-1.509204397476762,-1.2338965441104055,0
+-1.0318087983779833,-0.9939338411314658,0
+-0.8751308541273702,-1.0474097768888049,0
+-1.3408665903494346,0.9444220301262156,1
+0.9478668823189335,-0.5898775994396596,1
+1.1017928306267375,-0.27103467596302855,1
+-0.7500750032505076,-1.579887330534166,0
+-0.5967505320456731,-0.8066008949874582,0
+-1.3525468499129982,-1.3267723635500797,0
+-0.5717200962167428,-0.3898025304153678,0
+0.6072394989763853,0.7146634918868492,0
+-1.6164941333827454,0.8618743001665813,1
+-0.8445460592464822,-0.5110816224406006,0
+-1.1033420691052154,-0.022680472424856782,0
+-1.0866587598085635,1.0636280612149416,1
+1.5452664581787028,-0.7973809399341155,1
+0.9509393206645933,-0.9862459459109737,1
+-0.8456161257195288,-1.5622025151020762,0
+-0.46660305134876595,0.8563576334127342,1
+-1.2130584711870687,0.8463607085206132,1
+-0.9490871503858932,0.7200039426549093,1
+-0.667840832951023,-1.0484601249487482,0
+1.0896655250849645,-1.1281946165116266,1
+0.5050135538161301,-1.0396888923346743,1
+-0.731017526222299,1.0590168823488495,1
+1.6511291118087281,1.0703390298212063,0
+1.1492550819693432,-1.2706429445862024,1
+-0.5403122516754452,-1.1110581944561218,0
+-1.1264898867992328,1.1018848136105357,1
+0.449222027637096,-0.4398174766779579,1
+1.1220639587931536,0.8641746954726975,0
+-0.9663675841498722,-0.7596556032921673,0
+0.9060621939194698,0.8877560331426849,0
+-0.7093688649106793,-1.3797619589879904,0
+0.8136093042903083,-1.216684158532881,1
+-0.6800815830734992,-1.4847717454071263,0
+0.7952837156544562,-0.5174504180795044,1
+-1.4680019124188795,1.476341883343489,1
+-0.5693921995956657,-1.9139031079673776,0
+0.6822375589991169,-0.29084108033907485,1
+1.1007873162688362,0.36322730005058373,0
+0.829947863675562,0.5130795248755328,0
+-0.6330486953352503,0.8792639332772678,1
+1.0121266908137145,-0.39831222527719323,1
+-1.1970236483413927,1.0378237237193462,1
+1.5118875054083893,-1.2002428894673174,1
+-0.6188281640231784,0.48735428318080226,1
+-1.0909684846623753,1.248591911014135,1
+-0.7455014646215111,-1.0441409218981739,0
+0.7866863333823773,0.9617793916706788,0
+0.21376210248603827,0.996441262508026,0
+-1.762830277781928,-0.8159200289022223,0
+1.219207483974514,0.7559340344075557,0
+0.6489426105356153,-0.9266185355848736,1
+0.5800412535697614,0.7766258792161905,0
+-0.43899274611132827,1.1534325103292973,1
+-1.2611565127372826,-0.9737896125342366,0
+0.6878893004050615,0.7836356757372331,0
+-0.5127789990938985,-0.9942088322352807,0
+-0.8265249317320981,1.487287322107542,1
+0.5126894002335396,0.6589310725309434,0
+-0.7081569337764653,-0.9899725200592437,0
+1.3093561943150422,-1.6597568620112597,1
+0.6284491769378041,0.3888562980466557,0
+-1.3385777107425356,-0.6200949530359555,0
+1.2746277963623494,-1.1011838255197235,1
+1.1980699995058308,0.9744917122531893,0
+-1.9524938123167692,0.4909033405153779,1
+0.9820150826005003,1.460973839508322,0
+-0.5929000945478089,1.1603941817105625,1
+-1.1106551126262403,1.3099970568102546,1
+-0.7402360309136596,0.571747515409634,1
+-0.9510320072260303,-0.4062220028143585,0
+-1.591343211099942,-0.7967882247778718,0
+1.15340963068379,-0.4989581711117288,1
+0.858413136736819,0.782205497390509,0
+-1.266404928673709,-0.8208319684770005,0
+1.0862357243553906,1.1756217744417816,0
+-1.7506229328596397,-1.2835714099581526,0
+-0.9561879132623957,-1.2709054952098822,0
+1.0321952640883465,0.8911165706309576,0
+1.1947068921509194,-1.3130840740701857,1
+1.042685696195951,-1.4140949892115968,1
+-1.4042807856604496,1.1257362389084176,1
+-0.9817137320649277,0.7399256954428846,1
+0.004549183270731847,-1.7324371524225852,0
+-0.7487330984502305,-1.2623196180203113,0
+1.4351198726512726,-1.0953850000215999,1
+-0.6106406132322701,1.1062681757695574,1
+1.4581503988837932,-0.7546500843162515,1
+0.9401216149651754,-0.9337976150457739,1
+-1.436869432832388,-1.1248297677391967,0
+-0.8117019984593226,-1.7600679135672628,0
+-0.6323020611557991,-1.5181664246442013,0
+0.44286251387614595,0.7577086594752754,0
+1.0301980277179577,0.6001118237934565,0
+0.5014150274429968,0.8125102720525466,0
+-0.7244164522711057,0.7298113512468151,1
+-0.824962041390704,1.3143213312556568,1
+0.3220816794749135,-1.0572930118312946,1
+-0.7955903028117624,0.8738184650697917,1
+-0.4273109013657134,-0.9454118600139348,0
+0.990372200011917,1.1602498880020995,0
+-0.3760542280635279,-0.5952826767995261,0
+1.1127487677313863,-0.9178484126987668,1
+-0.8689400364187218,0.20012747421012403,1
+0.6858517116040962,-0.5525804904819288,1
+1.6389533522584552,1.470606380422841,0
+0.8794452000378883,1.3227588922090636,0
+-0.7674779646234582,1.3682594261661696,1
+0.6968709320158619,0.7505717829103833,0
+-0.8497316238748789,-1.0497378442107996,0
+1.0057354187393623,1.285645776429627,0
+0.6111299097782208,-0.7877224099887655,1
+-0.48137719859338496,-1.1401904635046254,0
+1.2796833980988342,0.8715856342478392,0
+-0.8789126962046008,0.9763014003796812,1
+0.66295009036419,-1.236243428830224,1
+1.1764588159585683,-1.1679421071520695,1
+-0.511324902859311,-0.4317614009095101,0
+-1.2572767689333149,1.897302991873337,1
+0.6762187239866823,1.5363261679909865,0
+1.0082062283675914,-0.8725470468642962,1
+0.9365986136074377,-0.8717265498129111,1
+-1.1779783024938764,-0.658631554877004,0
+1.0927369785590924,1.0496289810693555,0
+-0.8120313951883846,1.2863535943961493,1
+1.2729474416302318,1.0519381289114949,0
+0.5917198492743875,1.3371748706358537,0
+0.6519636339264823,-0.8961905779909098,1
+-1.208905982297131,-0.5064186009978574,0
+-1.1143788526107994,-0.5078460268015179,0
+0.6473754513403548,-1.234116494027314,1
+-1.0254284587157931,-1.1877592509509145,0
+-1.1042806753650125,-1.207691221894697,0
+-0.9940628746189366,-0.5851414832770954,0
+1.3281672559813955,-1.139996732064192,1
+0.8298482153126988,1.2217075414379261,0
+0.7681204926313586,1.6059651974477949,0
+-1.421802183226005,1.6418780284787475,1
+-0.5008702630508468,-0.7261639236017293,0
+0.9435061703128248,-1.4834397382109161,1
+1.1049366885161183,-0.8537416245543662,1
+-0.8242953201441577,0.7773728726885744,1
+1.4788321952318402,-0.7168758769314242,1
+1.116141313211248,-0.9508989879304731,1
+-1.6911807851466845,-0.8628185531539977,0
+1.3550548834286014,-0.8449116763226764,1
+1.077403263227294,0.6757679819673661,0
+1.1530238076540376,-1.2929918833617216,1
+-1.0561943326294243,-1.358340843673048,0
+-0.965702230707146,-0.8737459174406498,0
+-0.5743928140001433,-0.6945133087210087,0
+-1.367432964049626,-1.0201786520639036,0
+0.945718905591309,0.8584345404951091,0
+-0.024993316321123685,-1.3318211473474952,1
+0.7321746607370372,-0.6714496848230477,1
+0.9884835412348087,-0.3343458030240983,1
+0.542713544357535,-1.3064582992445384,1
+0.9083790967346068,-1.005118893449019,1
+-0.8464306950201751,0.502432142345822,1
+-0.7282664562457437,0.8073615891900732,1
+-0.6386905472492858,-0.5898295923296667,0
+-0.7734945716023172,1.5102564049502432,1
+-0.9138324357304358,-0.6439268959233386,0
+-1.2566689388497017,-0.8155484703358801,0
+-1.2644155668439911,-0.5349100653207077,0
+0.933337725009531,-0.3321966220212984,1
+-0.8583230147498416,0.5774522814477038,1
+0.6748055379778602,0.4814867513901793,0
+1.1111568746959788,0.884526256835086,0
+1.6242586140506001,0.4324154476560846,0
+-1.5610977830451223,-1.386622773422618,0
+-0.980345271415857,0.8779083043069354,1
+-0.6636232409818936,0.9454466018446298,1
+1.060424836408038,1.1865111274086937,0
+-0.7615975754778919,1.1281120828544844,1
+0.9812431054787895,0.8099274656683172,0
+0.8177425391772914,-1.1507273145968042,1
+1.0943367834972717,-0.28560664059217883,1
+0.4762733293142622,1.2370904337161572,0
+1.41814155314871,-0.8328612573648858,1
+1.1548021553176275,-1.400664881221706,1
+1.3349192834354553,1.1676766737727742,0
+1.4805764164452953,0.8518365679014616,0
+0.6269244176385979,-1.4226345771185265,1
+1.7226475999333133,-0.9413602105682292,1
+1.1241567378924615,-0.8178789753703201,1
+1.1990184837530569,-0.9322730745538358,1
+-0.7172709471527682,1.189949058646975,1
+-1.2980043156016,-1.0366896219658206,0
+-0.4198315389405974,1.2603394821173133,1
+-1.2621109217379447,-1.3718757209146997,0
+-0.958457568292384,-1.5178366146419273,0
+1.1064939158808396,0.10465865476416394,1
+-0.6337512458219294,0.7724860370267106,1
+0.8003383045929353,0.9845371304559167,0
+0.9036192325746618,1.5560718829320026,0
+-1.3382843936586404,0.4813678262167632,1
+0.40292196981049916,0.7460594062013014,0
+-1.0961160158206287,0.9280890239054004,1
+0.554050401452824,-1.1293353325533173,1
+0.9866175936785601,1.012373248376607,0
+-1.0833817908217886,0.28689606073752355,1
+0.8924624918065149,0.6835983715431377,0
+0.6898196608594394,-0.7348833677494087,1
+-1.1748043234282985,-1.0148316285874048,0
+-0.174907389489406,-0.9246037783619093,0
+0.7789082727910278,-0.6423357156706754,1
+0.7605946480334953,0.9335613815808135,0
+0.5050661016969862,0.7664320547588231,0
+-0.9493881865260496,-0.8369136369906612,0
+-0.9308539977216596,1.0504884579970735,1
+1.0615836849406486,-0.9613008581145138,1
+-0.9660519742315219,-0.4923076542313845,0
+-0.8499481397057809,-0.29487109827586533,0
+-1.3531114901773942,-0.43051110421488387,0
+-1.196642978147086,0.486213177046464,1
+-1.4646710837807875,0.4600198889841639,1
+0.7746482252368588,-1.3110983560843006,1
+0.6466259996821283,0.3993667262981215,0
+-0.8469525396729647,1.2503595720943346,1
+0.3053656403441962,-0.9495174181371012,1
+1.2835997643222166,-0.42036704667319497,1
+-1.1087715701527388,-1.267538645307201,0
+0.7086047338918401,0.9078490218342311,0
+0.6116063237576477,-1.2382138015662905,1
+1.8089039170649375,1.273840783551944,0
+-0.8413246172390899,1.1220780666819976,1
+-1.0142787353144336,-0.9751315285496134,0
+-0.8810185279128108,1.5057664369098616,1
+0.6125011551156304,-1.4741133287194108,1
+0.4661694772954599,1.212543111941608,0
+-0.5765009532892391,0.8784826928397453,1
+1.5611662374969297,-1.1990001434673148,1
+1.3641378931292758,0.8610991490620612,0
+-0.43050375916367856,-1.2321484838151806,0
+0.5474706010909145,-1.0685536282286687,1
+-0.9859937774001624,-1.204702103562975,0
+-0.6327780411812594,-0.5303517775333125,0
+0.8523968720878948,-1.1571463205029429,1
+-1.2762784286650117,-0.7926720935087358,0
+0.9326981197981947,1.5826950741275208,0
+0.8851831261606999,0.6774682356475118,0
+-0.869064779786902,0.4111981034535513,1
+0.5594460080446417,0.360097093881398,0
+-1.5853928610021886,1.0781360579432255,1
+-1.272363832148868,-1.1993680790273553,0
+0.5415951684863155,0.40589096175996414,0
+-1.105078088251937,-1.2943536229481325,0
+0.8003199481970373,-1.4050301954887998,1
+0.668578240505929,1.2733934054884068,0
+0.7283444968721452,1.0798671153118624,0
+-0.45046749060472807,-0.8305984372339319,0
+-1.0468271888910359,1.669912822460335,1
+-1.0060254155112702,0.8365532583668058,1
+-1.544756340442959,-0.7660725792089078,0
+0.7401827417413357,0.4937636824409651,0
+0.8705948772583297,1.7555338246405146,0
+1.5802761908553415,1.074033238870704,0
+1.4178995530806273,-0.9714446223215958,1
+-1.7927309346592175,-0.591061172385916,0
+-1.1223581481613922,-1.080993578282646,0
+0.7445361754571851,-0.9003963578800479,1
+-0.2499203846404808,1.087424629458508,1
+-1.2151682107174038,-1.3187391381435263,0
+0.5757948249209314,0.8001436623235191,0
+1.1424655998465187,1.0554949001916043,0
+-0.9446571038426428,0.4509085089324277,1
+-0.7647325273882729,0.7409517009298378,1
+1.1652178740469317,0.3335997453509665,0
+-0.26954680892449595,-0.9570507094580002,0
+-0.9082796093731293,1.1512052600773532,1
+1.1842023041702057,1.182170813951833,0
+-1.1191830782327299,-1.6000197629733153,0
+-1.2767578913203104,1.4213104042045794,1
+-1.0859883983921035,1.450653592891141,1
+1.0789077165047178,-0.9791443711835529,1
+-1.3071233832679743,-0.6071407314567091,0
+0.6630742265046075,0.6287151402076722,0
+-0.5991020088089749,-1.8830474217699655,0
+-0.5194815338277325,-1.847648675908253,0
+1.01163573433405,-1.5244397766669338,1
+1.6185003056639304,0.5684101296422983,0
+0.4513749481059829,1.0251731208392052,0
+0.3781065718321696,1.0884352723727215,0
+-1.1406493012809755,0.5051717090224012,1
+2.0998455806563,-0.8386731416830264,1
+-0.26228188768749416,0.7828281751744447,1
+0.7516860305659103,1.1548637336937035,0
+-1.3902371734004833,-1.1231315129159691,0
+1.6118652774915847,-0.9868492759180131,1
+0.846660871784576,-1.2235226019755316,1
+-0.99986154616331,-1.2434031749825412,0
+0.9233336395903314,-0.6067156210640859,1
+1.7631719688412124,0.9116336265813015,0
+1.2649450166069562,1.043588340258926,0
+-1.3589570141192517,0.7434569179743477,1
+1.2079116098034701,-1.106136428454638,1
+-0.5907590702313257,1.4681286273649,1
+1.1850274574719801,0.8685696549703941,0
+0.7787748083825812,-1.2254038961088356,1
+-1.0852419399570574,-0.7602052155885268,0
+1.8869284913670263,-1.0565443598199835,1
+0.6911354695885833,0.11098767825397306,0
+-0.8124826470071282,0.8135801726056864,1
+-1.538519833082797,-1.234553762616796,0
+1.2477139899133278,-1.2036395119532621,1
+1.795425483296153,-1.3777829831646915,1
+-1.1486694584796246,1.2913346410895212,1
+1.1025491137197228,-0.7939091878162176,1
+-0.8972798812815697,1.036892598735037,1
+1.1222908400767069,0.9596028147845934,0
+-0.33238812053709604,1.1649985107480563,1
+-1.2058168859185374,1.0266641560437257,1
+-0.9144681458881756,-0.7147833758587337,0
+0.9533849911713747,1.0381753237450122,0
+1.1212471580357146,0.7157873660599575,0
+0.44632670714273565,1.5358048775413893,0
+-1.0597020095323995,-1.0711553719359779,0
+0.5789177330534968,-0.818504594695706,1
+-1.0950079434689666,1.2707676479885912,1
+-0.634529521237874,-0.7774473990318861,0
+1.1417526090029668,0.8506837693063476,0
+-0.4034043125738989,1.3080178105873563,1
+1.0109750445806884,-0.9406743931056449,1
+-1.4154364777739747,-1.1877890488606924,0
+-0.6877611921161617,0.6954499078436965,1
+-0.3201150665753495,0.6245245539523214,1
+-0.7321470882249363,0.6106278423311224,1
+1.2138388911072187,1.2294336644455999,0
+0.9410403938433625,-1.221775817746629,1
+-0.6175379414384323,-0.6926651598060036,0
+1.3039006047908623,-0.6508985533264043,1
+1.0355912660986184,-0.7566789824133817,1
+1.1837924876753625,-0.6157948114063393,1
+-1.1680459031576926,-0.4318260729416986,0
+0.9059046069981779,-0.44602407401114813,1
+0.9470987631185876,1.1084207427204225,0
+-0.7927494160732377,1.1663983436142682,1
+0.5937597834349564,0.9462131035736212,0
+0.9060578916046758,-1.4341564251115653,1
+-0.7622113762686823,1.0176669038052772,1
+0.7576168486234625,1.103885409968545,0
+0.436085559209496,0.4327977774343893,0
+0.07226696965240828,0.8534332558484382,1
+1.0127955252183902,-1.281454045061258,1
+-1.5020616524026107,1.7507172016143322,1
+-1.0798448713615052,-0.8416689238916703,0
+-0.012427555319766451,0.8496165961958283,1
+0.6537862976669452,0.6237796039291436,0
+1.044434845506311,0.6136273144304405,0
+-0.6168563040101647,-0.88660371705677,0
+-0.8365906086087974,-0.7639499785043806,0
+0.6009656948505112,0.20004272479002375,0
+-0.5629254245559663,1.0100457830215457,1
+-0.903988358310839,-0.6263554727465802,0
+-0.9321558576161968,0.5788149189894478,1
+1.0750638059270754,0.5259087595823828,0
+0.32597478400232316,-0.9328772003960243,1
+0.6945685498918519,0.7939916954552506,0
+0.9143135672794319,0.4983663309779597,0
+-1.3621877494968906,1.080231789243105,1
+0.6608610454143902,0.41934575203891544,0
+-0.892720749220613,1.2125848785881856,1
+-1.409633462120327,-1.6308683905200727,0
+-1.4902201597870228,-0.7550462289681075,0
+-1.065947571052325,0.755178978562288,1
+0.6194702190380585,-1.1252428961145207,1
+0.7924835153586393,0.8392748980347706,0
+0.5824660535553555,-0.7492504204088355,1
+-1.593474742760761,0.6717209606658276,1
+-0.8126713302735353,-0.2685423108377772,0
+-1.2865242319246575,0.6554588884829766,1
\ No newline at end of file
diff --git a/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/4.3-mlp-pytorch-part3-mnist.ipynb b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/4.3-mlp-pytorch-part3-mnist.ipynb
new file mode 100644
index 000000000..74947590d
--- /dev/null
+++ b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/4.3-mlp-pytorch-part3-mnist.ipynb
@@ -0,0 +1,360 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "d71bce70-9dc3-448b-9f9a-8896e83b6d09",
+ "metadata": {},
+ "source": [
+ "# Implementing a Multilayer Perceptron (MNIST)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e5b48fc7-4f46-4d5a-8558-cd06892aaa27",
+ "metadata": {},
+ "source": [
+ "## 1) Installing Libraries"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "be1f5a9a-b3ee-424b-ab02-4371f49bd786",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !conda install numpy pandas matplotlib --yes"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "1ea7b3b8-9092-4b37-8b7f-57362be611ad",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !pip install torch torchvision torchaudio"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "79dd2077-ba5c-4ab5-95fc-6ee4d8a9f811",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !conda install watermark"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "bc4fa295-5c62-4888-bcf8-d07d6a7afc47",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Python implementation: CPython\n",
+ "Python version : 3.9.15\n",
+ "IPython version : 8.6.0\n",
+ "\n",
+ "numpy : 1.23.4\n",
+ "pandas : 1.5.2\n",
+ "matplotlib: 3.6.2\n",
+ "torch : 1.13.0\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "%load_ext watermark\n",
+ "%watermark -v -p numpy,pandas,matplotlib,torch"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b9549676-2fa5-41a7-bbb9-ce03f5797c34",
+ "metadata": {},
+ "source": [
+ "## 2) Loading the dataset"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e002ad95-a1f7-4c33-826a-4a45944f2687",
+ "metadata": {},
+ "source": [
+ "- MNIST website: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "f609024c-3eae-4ad5-8cb8-b95b403b7606",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from torch.utils.data import DataLoader\n",
+ "from torchvision import datasets, transforms\n",
+ "\n",
+ "train_dataset = datasets.MNIST(\n",
+ " root=\"./mnist\", train=True, transform=transforms.ToTensor(), download=True\n",
+ ")\n",
+ "\n",
+ "test_dataset = datasets.MNIST(\n",
+ " root=\"./mnist\", train=False, transform=transforms.ToTensor()\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "6661307a-6220-48d5-b965-4cd36e29e54c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "60000"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(train_dataset)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "78adc94e-5418-4aac-9a82-9a9cbf8fc688",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "10000"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(test_dataset)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "765adcf0-9147-434b-917a-f6d736a7117e",
+ "metadata": {},
+ "source": [
+ "### Create a validation set"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "b39a42a2-cd46-46cf-ba93-d3f2f232f29c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import torch\n",
+ "from torch.utils.data.dataset import random_split\n",
+ "\n",
+ "torch.manual_seed(1)\n",
+ "train_dataset, val_dataset = random_split(train_dataset, lengths=[55000, 5000])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "b30e4a70-55b3-4fb0-b28d-b0fddd193fae",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "train_loader = DataLoader(\n",
+ " dataset=train_dataset,\n",
+ " batch_size=64,\n",
+ " shuffle=True,\n",
+ ")\n",
+ "\n",
+ "val_loader = DataLoader(\n",
+ " dataset=val_dataset,\n",
+ " batch_size=64,\n",
+ " shuffle=False,\n",
+ ")\n",
+ "\n",
+ "test_loader = DataLoader(\n",
+ " dataset=test_dataset,\n",
+ " batch_size=64,\n",
+ " shuffle=False,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1ac5cbfe-fe11-40e7-84a5-40fdfbc9ec2c",
+ "metadata": {},
+ "source": [
+ "### Check label distribution"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "b14d9f95-d7ee-431f-85fa-ee4ec1a9302b",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "Training label distribution:\n",
+ "[(0, 5419), (1, 6185), (2, 5477), (3, 5681), (4, 5349), (5, 4974), (6, 5422), (7, 5710), (8, 5351), (9, 5432)]\n",
+ "\n",
+ "Validation label distribution:\n",
+ "[(0, 504), (1, 557), (2, 481), (3, 450), (4, 493), (5, 447), (6, 496), (7, 555), (8, 500), (9, 517)]\n",
+ "\n",
+ "Test label distribution:\n",
+ "[(0, 980), (1, 1135), (2, 1032), (3, 1010), (4, 982), (5, 892), (6, 958), (7, 1028), (8, 974), (9, 1009)]\n"
+ ]
+ }
+ ],
+ "source": [
+ "from collections import Counter\n",
+ "\n",
+ "train_counter = Counter()\n",
+ "for images, labels in train_loader:\n",
+ " train_counter.update(labels.tolist())\n",
+ " \n",
+ "print(\"\\nTraining label distribution:\")\n",
+ "print(sorted(train_counter.items()))\n",
+ "\n",
+ " \n",
+ "val_counter = Counter()\n",
+ "for images, labels in val_loader:\n",
+ " val_counter.update(labels.tolist())\n",
+ " \n",
+ "print(\"\\nValidation label distribution:\")\n",
+ "print(sorted(val_counter.items()))\n",
+ " \n",
+ "\n",
+ "test_counter = Counter()\n",
+ "for images, labels in test_loader:\n",
+ " test_counter.update(labels.tolist())\n",
+ "\n",
+ "print(\"\\nTest label distribution:\")\n",
+ "print(sorted(test_counter.items()))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "fc4663a6-e8a7-472e-b9b0-c64f546a85e9",
+ "metadata": {},
+ "source": [
+ "## 3) Zero-rule baseline (majority class classifier)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "36a879c3-0c84-4476-a79a-f41d897c696a",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Majority class: 1\n",
+ "Accuracy when always predicting the majority class:\n",
+ "0.11 (11.35%)\n"
+ ]
+ }
+ ],
+ "source": [
+ "majority_class = test_counter.most_common(1)[0]\n",
+ "print(\"Majority class:\", majority_class[0])\n",
+ "\n",
+ "baseline_acc = majority_class[1] / sum(test_counter.values())\n",
+ "print(\"Accuracy when always predicting the majority class:\")\n",
+ "print(f\"{baseline_acc:.2f} ({baseline_acc*100:.2f}%)\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0de2855f-a31b-4739-b1b6-310ed1296ad6",
+ "metadata": {},
+ "source": [
+ "## 4) A quick visual check"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "id": "d1de5f76-7547-4edf-938d-615195fe949f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np\n",
+ "import torchvision\n",
+ "\n",
+ "\n",
+ "for images, labels in train_loader: \n",
+ " break\n",
+ "\n",
+ "plt.figure(figsize=(8, 8))\n",
+ "plt.axis(\"off\")\n",
+ "plt.title(\"Training images\")\n",
+ "plt.imshow(np.transpose(torchvision.utils.make_grid(\n",
+ " images[:64], \n",
+ " padding=1,\n",
+ " pad_value=1.0,\n",
+ " normalize=True),\n",
+ " (1, 2, 0)))\n",
+ "plt.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/4.3-mlp-pytorch-part4-mnist.ipynb b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/4.3-mlp-pytorch-part4-mnist.ipynb
new file mode 100644
index 000000000..6255cc3ce
--- /dev/null
+++ b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/4.3-mlp-pytorch-part4-mnist.ipynb
@@ -0,0 +1,604 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "d71bce70-9dc3-448b-9f9a-8896e83b6d09",
+ "metadata": {},
+ "source": [
+ "# Implementing a Multilayer Perceptron (MNIST)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e5b48fc7-4f46-4d5a-8558-cd06892aaa27",
+ "metadata": {},
+ "source": [
+ "## 1) Installing Libraries"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "be1f5a9a-b3ee-424b-ab02-4371f49bd786",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !conda install numpy pandas matplotlib --yes"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "1ea7b3b8-9092-4b37-8b7f-57362be611ad",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !pip install torch torchvision torchaudio"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "79dd2077-ba5c-4ab5-95fc-6ee4d8a9f811",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !conda install watermark"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "bc4fa295-5c62-4888-bcf8-d07d6a7afc47",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Python implementation: CPython\n",
+ "Python version : 3.9.15\n",
+ "IPython version : 8.6.0\n",
+ "\n",
+ "numpy : 1.23.4\n",
+ "pandas : 1.5.2\n",
+ "matplotlib: 3.6.2\n",
+ "torch : 1.13.0\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "%load_ext watermark\n",
+ "%watermark -v -p numpy,pandas,matplotlib,torch"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b9549676-2fa5-41a7-bbb9-ce03f5797c34",
+ "metadata": {},
+ "source": [
+ "## 2) Loading the dataset"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e002ad95-a1f7-4c33-826a-4a45944f2687",
+ "metadata": {},
+ "source": [
+ "- MNIST website: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "f609024c-3eae-4ad5-8cb8-b95b403b7606",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from torch.utils.data import DataLoader\n",
+ "from torchvision import datasets, transforms\n",
+ "\n",
+ "train_dataset = datasets.MNIST(\n",
+ " root=\"./mnist\", train=True, transform=transforms.ToTensor(), download=True\n",
+ ")\n",
+ "\n",
+ "test_dataset = datasets.MNIST(\n",
+ " root=\"./mnist\", train=False, transform=transforms.ToTensor()\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "6661307a-6220-48d5-b965-4cd36e29e54c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "60000"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(train_dataset)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "78adc94e-5418-4aac-9a82-9a9cbf8fc688",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "10000"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(test_dataset)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "765adcf0-9147-434b-917a-f6d736a7117e",
+ "metadata": {},
+ "source": [
+ "### Create a validation set"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "b39a42a2-cd46-46cf-ba93-d3f2f232f29c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import torch\n",
+ "from torch.utils.data.dataset import random_split\n",
+ "\n",
+ "torch.manual_seed(1)\n",
+ "train_dataset, val_dataset = random_split(train_dataset, lengths=[55000, 5000])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "b30e4a70-55b3-4fb0-b28d-b0fddd193fae",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "train_loader = DataLoader(\n",
+ " dataset=train_dataset,\n",
+ " batch_size=64,\n",
+ " shuffle=True,\n",
+ ")\n",
+ "\n",
+ "val_loader = DataLoader(\n",
+ " dataset=val_dataset,\n",
+ " batch_size=64,\n",
+ " shuffle=False,\n",
+ ")\n",
+ "\n",
+ "test_loader = DataLoader(\n",
+ " dataset=test_dataset,\n",
+ " batch_size=64,\n",
+ " shuffle=False,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1ac5cbfe-fe11-40e7-84a5-40fdfbc9ec2c",
+ "metadata": {},
+ "source": [
+ "### Check label distribution"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "b14d9f95-d7ee-431f-85fa-ee4ec1a9302b",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "Training label distribution:\n",
+ "[(0, 5419), (1, 6185), (2, 5477), (3, 5681), (4, 5349), (5, 4974), (6, 5422), (7, 5710), (8, 5351), (9, 5432)]\n",
+ "\n",
+ "Validation label distribution:\n",
+ "[(0, 504), (1, 557), (2, 481), (3, 450), (4, 493), (5, 447), (6, 496), (7, 555), (8, 500), (9, 517)]\n",
+ "\n",
+ "Test label distribution:\n",
+ "[(0, 980), (1, 1135), (2, 1032), (3, 1010), (4, 982), (5, 892), (6, 958), (7, 1028), (8, 974), (9, 1009)]\n"
+ ]
+ }
+ ],
+ "source": [
+ "from collections import Counter\n",
+ "\n",
+ "train_counter = Counter()\n",
+ "for images, labels in train_loader:\n",
+ " train_counter.update(labels.tolist())\n",
+ " \n",
+ "print(\"\\nTraining label distribution:\")\n",
+ "print(sorted(train_counter.items()))\n",
+ "\n",
+ " \n",
+ "val_counter = Counter()\n",
+ "for images, labels in val_loader:\n",
+ " val_counter.update(labels.tolist())\n",
+ " \n",
+ "print(\"\\nValidation label distribution:\")\n",
+ "print(sorted(val_counter.items()))\n",
+ " \n",
+ "\n",
+ "test_counter = Counter()\n",
+ "for images, labels in test_loader:\n",
+ " test_counter.update(labels.tolist())\n",
+ "\n",
+ "print(\"\\nTest label distribution:\")\n",
+ "print(sorted(test_counter.items()))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "fc4663a6-e8a7-472e-b9b0-c64f546a85e9",
+ "metadata": {},
+ "source": [
+ "## 3) Zero-rule baseline (majority class classifier)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "36a879c3-0c84-4476-a79a-f41d897c696a",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Majority class: 1\n",
+ "Accuracy when always predicting the majority class:\n",
+ "0.11 (11.35%)\n"
+ ]
+ }
+ ],
+ "source": [
+ "majority_class = test_counter.most_common(1)[0]\n",
+ "print(\"Majority class:\", majority_class[0])\n",
+ "\n",
+ "baseline_acc = majority_class[1] / sum(test_counter.values())\n",
+ "print(\"Accuracy when always predicting the majority class:\")\n",
+ "print(f\"{baseline_acc:.2f} ({baseline_acc*100:.2f}%)\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0de2855f-a31b-4739-b1b6-310ed1296ad6",
+ "metadata": {},
+ "source": [
+ "## 4) A quick visual check"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "id": "d1de5f76-7547-4edf-938d-615195fe949f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np\n",
+ "import torchvision\n",
+ "\n",
+ "\n",
+ "for images, labels in train_loader: \n",
+ " break\n",
+ "\n",
+ "plt.figure(figsize=(8, 8))\n",
+ "plt.axis(\"off\")\n",
+ "plt.title(\"Training images\")\n",
+ "plt.imshow(np.transpose(torchvision.utils.make_grid(\n",
+ " images[:64], \n",
+ " padding=1,\n",
+ " pad_value=1.0,\n",
+ " normalize=True),\n",
+ " (1, 2, 0)))\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "db50db02-3696-4f86-b149-74baabeec6c4",
+ "metadata": {},
+ "source": [
+ "## 5) Implementing the model"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "664cd5a8-acb1-47cd-96c7-1f28d4596643",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "torch.Size([64, 1, 28, 28])"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "images.shape # batchsize, channel, height, width"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4308ab97-ec88-4f31-b9a1-42dda1fbdc9a",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "c2ec5abc-1c6a-4c26-9c71-6af6b8eb32a9",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "torch.Size([64, 784])"
+ ]
+ },
+ "execution_count": 14,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import torch\n",
+ "\n",
+ "torch.flatten(images, start_dim=1).shape # batchsize, features"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "971389a7-5424-4141-a3ee-9399eebbbb6a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class PyTorchMLP(torch.nn.Module):\n",
+ " def __init__(self, num_features, num_classes):\n",
+ " super().__init__()\n",
+ "\n",
+ " self.all_layers = torch.nn.Sequential(\n",
+ " # 1st hidden layer\n",
+ " torch.nn.Linear(num_features, 50),\n",
+ " torch.nn.ReLU(),\n",
+ " # 2nd hidden layer\n",
+ " torch.nn.Linear(50, 25),\n",
+ " torch.nn.ReLU(),\n",
+ " # output layer\n",
+ " torch.nn.Linear(25, num_classes),\n",
+ " )\n",
+ "\n",
+ " def forward(self, x):\n",
+ " x = torch.flatten(x, start_dim=1)\n",
+ " logits = self.all_layers(x)\n",
+ " return logits"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "46bc16a0-ec59-4c54-a209-0a5e22406287",
+ "metadata": {},
+ "source": [
+ "## 6) The training loop"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "adf5d12d-af3d-4359-ba13-e15850a3b432",
+ "metadata": {},
+ "source": [
+ "- Exactly the same accuracy function as before"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "8de213fc-48b0-4f7c-af9e-8e2da068e351",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def compute_accuracy(model, dataloader):\n",
+ "\n",
+ " model = model.eval()\n",
+ "\n",
+ " correct = 0.0\n",
+ " total_examples = 0\n",
+ "\n",
+ " for idx, (features, labels) in enumerate(dataloader):\n",
+ "\n",
+ " with torch.inference_mode():\n",
+ " logits = model(features)\n",
+ "\n",
+ " predictions = torch.argmax(logits, dim=1)\n",
+ "\n",
+ " compare = labels == predictions\n",
+ " correct += torch.sum(compare)\n",
+ " total_examples += len(compare)\n",
+ "\n",
+ " return correct / total_examples"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "c718f5fa-0b4e-4258-940f-dc531018cb03",
+ "metadata": {},
+ "source": [
+ "- Exactly the same training loop as before"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "id": "3dcaa2b1-4019-4128-9ff5-6a966c3abdf2",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Epoch: 001/010 | Batch 000/860 | Train Loss: 2.34\n",
+ "Epoch: 001/010 | Batch 250/860 | Train Loss: 0.68\n",
+ "Epoch: 001/010 | Batch 500/860 | Train Loss: 0.29\n",
+ "Epoch: 001/010 | Batch 750/860 | Train Loss: 0.30\n",
+ "Train Acc 88.70% | Val Acc 88.22%\n",
+ "Epoch: 002/010 | Batch 000/860 | Train Loss: 0.36\n",
+ "Epoch: 002/010 | Batch 250/860 | Train Loss: 0.41\n",
+ "Epoch: 002/010 | Batch 500/860 | Train Loss: 0.44\n",
+ "Epoch: 002/010 | Batch 750/860 | Train Loss: 0.25\n",
+ "Train Acc 91.84% | Val Acc 91.12%\n",
+ "Epoch: 003/010 | Batch 000/860 | Train Loss: 0.28\n",
+ "Epoch: 003/010 | Batch 250/860 | Train Loss: 0.20\n",
+ "Epoch: 003/010 | Batch 500/860 | Train Loss: 0.18\n",
+ "Epoch: 003/010 | Batch 750/860 | Train Loss: 0.26\n",
+ "Train Acc 93.71% | Val Acc 92.86%\n",
+ "Epoch: 004/010 | Batch 000/860 | Train Loss: 0.18\n",
+ "Epoch: 004/010 | Batch 250/860 | Train Loss: 0.14\n",
+ "Epoch: 004/010 | Batch 500/860 | Train Loss: 0.25\n",
+ "Epoch: 004/010 | Batch 750/860 | Train Loss: 0.23\n",
+ "Train Acc 94.80% | Val Acc 93.54%\n",
+ "Epoch: 005/010 | Batch 000/860 | Train Loss: 0.13\n",
+ "Epoch: 005/010 | Batch 250/860 | Train Loss: 0.20\n",
+ "Epoch: 005/010 | Batch 500/860 | Train Loss: 0.08\n",
+ "Epoch: 005/010 | Batch 750/860 | Train Loss: 0.18\n",
+ "Train Acc 95.47% | Val Acc 94.36%\n",
+ "Epoch: 006/010 | Batch 000/860 | Train Loss: 0.28\n",
+ "Epoch: 006/010 | Batch 250/860 | Train Loss: 0.31\n",
+ "Epoch: 006/010 | Batch 500/860 | Train Loss: 0.25\n",
+ "Epoch: 006/010 | Batch 750/860 | Train Loss: 0.07\n",
+ "Train Acc 95.72% | Val Acc 94.66%\n",
+ "Epoch: 007/010 | Batch 000/860 | Train Loss: 0.08\n",
+ "Epoch: 007/010 | Batch 250/860 | Train Loss: 0.11\n",
+ "Epoch: 007/010 | Batch 500/860 | Train Loss: 0.11\n",
+ "Epoch: 007/010 | Batch 750/860 | Train Loss: 0.15\n",
+ "Train Acc 96.06% | Val Acc 95.16%\n",
+ "Epoch: 008/010 | Batch 000/860 | Train Loss: 0.12\n",
+ "Epoch: 008/010 | Batch 250/860 | Train Loss: 0.19\n",
+ "Epoch: 008/010 | Batch 500/860 | Train Loss: 0.06\n",
+ "Epoch: 008/010 | Batch 750/860 | Train Loss: 0.14\n",
+ "Train Acc 96.48% | Val Acc 94.96%\n",
+ "Epoch: 009/010 | Batch 000/860 | Train Loss: 0.15\n",
+ "Epoch: 009/010 | Batch 250/860 | Train Loss: 0.08\n",
+ "Epoch: 009/010 | Batch 500/860 | Train Loss: 0.18\n",
+ "Epoch: 009/010 | Batch 750/860 | Train Loss: 0.05\n",
+ "Train Acc 97.01% | Val Acc 95.48%\n",
+ "Epoch: 010/010 | Batch 000/860 | Train Loss: 0.04\n",
+ "Epoch: 010/010 | Batch 250/860 | Train Loss: 0.08\n",
+ "Epoch: 010/010 | Batch 500/860 | Train Loss: 0.18\n",
+ "Epoch: 010/010 | Batch 750/860 | Train Loss: 0.13\n",
+ "Train Acc 97.24% | Val Acc 95.64%\n"
+ ]
+ }
+ ],
+ "source": [
+ "import torch.nn.functional as F\n",
+ "\n",
+ "torch.manual_seed(1)\n",
+ "model = PyTorchMLP(num_features=784, num_classes=10)\n",
+ "\n",
+ "optimizer = torch.optim.SGD(model.parameters(), lr=0.05)\n",
+ "\n",
+ "num_epochs = 10\n",
+ "\n",
+ "loss_list = []\n",
+ "train_acc_list, val_acc_list = [], []\n",
+ "for epoch in range(num_epochs):\n",
+ "\n",
+ " model = model.train()\n",
+ " for batch_idx, (features, labels) in enumerate(train_loader):\n",
+ "\n",
+ " logits = model(features)\n",
+ "\n",
+ " loss = F.cross_entropy(logits, labels)\n",
+ "\n",
+ " optimizer.zero_grad()\n",
+ " loss.backward()\n",
+ " optimizer.step()\n",
+ "\n",
+ " if not batch_idx % 250:\n",
+ " ### LOGGING\n",
+ " print(\n",
+ " f\"Epoch: {epoch+1:03d}/{num_epochs:03d}\"\n",
+ " f\" | Batch {batch_idx:03d}/{len(train_loader):03d}\"\n",
+ " f\" | Train Loss: {loss:.2f}\"\n",
+ " )\n",
+ " loss_list.append(loss.item())\n",
+ "\n",
+ " train_acc = compute_accuracy(model, train_loader)\n",
+ " val_acc = compute_accuracy(model, val_loader)\n",
+ " print(f\"Train Acc {train_acc*100:.2f}% | Val Acc {val_acc*100:.2f}%\")\n",
+ " train_acc_list.append(train_acc)\n",
+ " val_acc_list.append(val_acc)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/4.3-mlp-pytorch-part5-mnist.ipynb b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/4.3-mlp-pytorch-part5-mnist.ipynb
new file mode 100644
index 000000000..ad473f6ba
--- /dev/null
+++ b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/4.3-mlp-pytorch-part5-mnist.ipynb
@@ -0,0 +1,715 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "d71bce70-9dc3-448b-9f9a-8896e83b6d09",
+ "metadata": {},
+ "source": [
+ "# Implementing a Multilayer Perceptron (MNIST)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e5b48fc7-4f46-4d5a-8558-cd06892aaa27",
+ "metadata": {},
+ "source": [
+ "## 1) Installing Libraries"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "be1f5a9a-b3ee-424b-ab02-4371f49bd786",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !conda install numpy pandas matplotlib --yes"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "1ea7b3b8-9092-4b37-8b7f-57362be611ad",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !pip install torch torchvision torchaudio"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "79dd2077-ba5c-4ab5-95fc-6ee4d8a9f811",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !conda install watermark"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "bc4fa295-5c62-4888-bcf8-d07d6a7afc47",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Python implementation: CPython\n",
+ "Python version : 3.9.15\n",
+ "IPython version : 8.6.0\n",
+ "\n",
+ "numpy : 1.23.4\n",
+ "pandas : 1.5.2\n",
+ "matplotlib: 3.6.2\n",
+ "torch : 1.13.0\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "%load_ext watermark\n",
+ "%watermark -v -p numpy,pandas,matplotlib,torch"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b9549676-2fa5-41a7-bbb9-ce03f5797c34",
+ "metadata": {},
+ "source": [
+ "## 2) Loading the dataset"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e002ad95-a1f7-4c33-826a-4a45944f2687",
+ "metadata": {},
+ "source": [
+ "- MNIST website: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "f609024c-3eae-4ad5-8cb8-b95b403b7606",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from torch.utils.data import DataLoader\n",
+ "from torchvision import datasets, transforms\n",
+ "\n",
+ "train_dataset = datasets.MNIST(\n",
+ " root=\"./mnist\", train=True, transform=transforms.ToTensor(), download=True\n",
+ ")\n",
+ "\n",
+ "test_dataset = datasets.MNIST(\n",
+ " root=\"./mnist\", train=False, transform=transforms.ToTensor()\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "6661307a-6220-48d5-b965-4cd36e29e54c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "60000"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(train_dataset)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "78adc94e-5418-4aac-9a82-9a9cbf8fc688",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "10000"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(test_dataset)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "765adcf0-9147-434b-917a-f6d736a7117e",
+ "metadata": {},
+ "source": [
+ "### Create a validation set"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "b39a42a2-cd46-46cf-ba93-d3f2f232f29c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import torch\n",
+ "from torch.utils.data.dataset import random_split\n",
+ "\n",
+ "torch.manual_seed(1)\n",
+ "train_dataset, val_dataset = random_split(train_dataset, lengths=[55000, 5000])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "b30e4a70-55b3-4fb0-b28d-b0fddd193fae",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "train_loader = DataLoader(\n",
+ " dataset=train_dataset,\n",
+ " batch_size=64,\n",
+ " shuffle=True,\n",
+ ")\n",
+ "\n",
+ "val_loader = DataLoader(\n",
+ " dataset=val_dataset,\n",
+ " batch_size=64,\n",
+ " shuffle=False,\n",
+ ")\n",
+ "\n",
+ "test_loader = DataLoader(\n",
+ " dataset=test_dataset,\n",
+ " batch_size=64,\n",
+ " shuffle=False,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1ac5cbfe-fe11-40e7-84a5-40fdfbc9ec2c",
+ "metadata": {},
+ "source": [
+ "### Check label distribution"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "b14d9f95-d7ee-431f-85fa-ee4ec1a9302b",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "Training label distribution:\n",
+ "[(0, 5419), (1, 6185), (2, 5477), (3, 5681), (4, 5349), (5, 4974), (6, 5422), (7, 5710), (8, 5351), (9, 5432)]\n",
+ "\n",
+ "Validation label distribution:\n",
+ "[(0, 504), (1, 557), (2, 481), (3, 450), (4, 493), (5, 447), (6, 496), (7, 555), (8, 500), (9, 517)]\n",
+ "\n",
+ "Test label distribution:\n",
+ "[(0, 980), (1, 1135), (2, 1032), (3, 1010), (4, 982), (5, 892), (6, 958), (7, 1028), (8, 974), (9, 1009)]\n"
+ ]
+ }
+ ],
+ "source": [
+ "from collections import Counter\n",
+ "\n",
+ "train_counter = Counter()\n",
+ "for images, labels in train_loader:\n",
+ " train_counter.update(labels.tolist())\n",
+ " \n",
+ "print(\"\\nTraining label distribution:\")\n",
+ "print(sorted(train_counter.items()))\n",
+ "\n",
+ " \n",
+ "val_counter = Counter()\n",
+ "for images, labels in val_loader:\n",
+ " val_counter.update(labels.tolist())\n",
+ " \n",
+ "print(\"\\nValidation label distribution:\")\n",
+ "print(sorted(val_counter.items()))\n",
+ " \n",
+ "\n",
+ "test_counter = Counter()\n",
+ "for images, labels in test_loader:\n",
+ " test_counter.update(labels.tolist())\n",
+ "\n",
+ "print(\"\\nTest label distribution:\")\n",
+ "print(sorted(test_counter.items()))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "fc4663a6-e8a7-472e-b9b0-c64f546a85e9",
+ "metadata": {},
+ "source": [
+ "## 3) Zero-rule baseline (majority class classifier)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "36a879c3-0c84-4476-a79a-f41d897c696a",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Majority class: 1\n",
+ "Accuracy when always predicting the majority class:\n",
+ "0.11 (11.35%)\n"
+ ]
+ }
+ ],
+ "source": [
+ "majority_class = test_counter.most_common(1)[0]\n",
+ "print(\"Majority class:\", majority_class[0])\n",
+ "\n",
+ "baseline_acc = majority_class[1] / sum(test_counter.values())\n",
+ "print(\"Accuracy when always predicting the majority class:\")\n",
+ "print(f\"{baseline_acc:.2f} ({baseline_acc*100:.2f}%)\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0de2855f-a31b-4739-b1b6-310ed1296ad6",
+ "metadata": {},
+ "source": [
+ "## 4) A quick visual check"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "id": "d1de5f76-7547-4edf-938d-615195fe949f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np\n",
+ "import torchvision\n",
+ "\n",
+ "\n",
+ "for images, labels in train_loader: \n",
+ " break\n",
+ "\n",
+ "plt.figure(figsize=(8, 8))\n",
+ "plt.axis(\"off\")\n",
+ "plt.title(\"Training images\")\n",
+ "plt.imshow(np.transpose(torchvision.utils.make_grid(\n",
+ " images[:64], \n",
+ " padding=1,\n",
+ " pad_value=1.0,\n",
+ " normalize=True),\n",
+ " (1, 2, 0)))\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "db50db02-3696-4f86-b149-74baabeec6c4",
+ "metadata": {},
+ "source": [
+ "## 5) Implementing the model"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "664cd5a8-acb1-47cd-96c7-1f28d4596643",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "torch.Size([64, 1, 28, 28])"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "images.shape # batchsize, channel, height, width"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4308ab97-ec88-4f31-b9a1-42dda1fbdc9a",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "c2ec5abc-1c6a-4c26-9c71-6af6b8eb32a9",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "torch.Size([64, 784])"
+ ]
+ },
+ "execution_count": 14,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import torch\n",
+ "\n",
+ "torch.flatten(images, start_dim=1).shape # batchsize, features"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "971389a7-5424-4141-a3ee-9399eebbbb6a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class PyTorchMLP(torch.nn.Module):\n",
+ " def __init__(self, num_features, num_classes):\n",
+ " super().__init__()\n",
+ "\n",
+ " self.all_layers = torch.nn.Sequential(\n",
+ " # 1st hidden layer\n",
+ " torch.nn.Linear(num_features, 50),\n",
+ " torch.nn.ReLU(),\n",
+ " # 2nd hidden layer\n",
+ " torch.nn.Linear(50, 25),\n",
+ " torch.nn.ReLU(),\n",
+ " # output layer\n",
+ " torch.nn.Linear(25, num_classes),\n",
+ " )\n",
+ "\n",
+ " def forward(self, x):\n",
+ " x = torch.flatten(x, start_dim=1)\n",
+ " logits = self.all_layers(x)\n",
+ " return logits"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "46bc16a0-ec59-4c54-a209-0a5e22406287",
+ "metadata": {},
+ "source": [
+ "## 6) The training loop"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "8de213fc-48b0-4f7c-af9e-8e2da068e351",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def compute_accuracy(model, dataloader):\n",
+ "\n",
+ " model = model.eval()\n",
+ "\n",
+ " correct = 0.0\n",
+ " total_examples = 0\n",
+ "\n",
+ " for idx, (features, labels) in enumerate(dataloader):\n",
+ "\n",
+ " with torch.no_grad():\n",
+ " logits = model(features)\n",
+ "\n",
+ " predictions = torch.argmax(logits, dim=1)\n",
+ "\n",
+ " compare = labels == predictions\n",
+ " correct += torch.sum(compare)\n",
+ " total_examples += len(compare)\n",
+ "\n",
+ " return correct / total_examples"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "id": "3dcaa2b1-4019-4128-9ff5-6a966c3abdf2",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Epoch: 001/010 | Batch 000/860 | Train Loss: 2.34\n",
+ "Epoch: 001/010 | Batch 250/860 | Train Loss: 0.68\n",
+ "Epoch: 001/010 | Batch 500/860 | Train Loss: 0.29\n",
+ "Epoch: 001/010 | Batch 750/860 | Train Loss: 0.30\n",
+ "Train Acc 88.70% | Val Acc 88.22%\n",
+ "Epoch: 002/010 | Batch 000/860 | Train Loss: 0.36\n",
+ "Epoch: 002/010 | Batch 250/860 | Train Loss: 0.41\n",
+ "Epoch: 002/010 | Batch 500/860 | Train Loss: 0.44\n",
+ "Epoch: 002/010 | Batch 750/860 | Train Loss: 0.25\n",
+ "Train Acc 91.84% | Val Acc 91.12%\n",
+ "Epoch: 003/010 | Batch 000/860 | Train Loss: 0.28\n",
+ "Epoch: 003/010 | Batch 250/860 | Train Loss: 0.20\n",
+ "Epoch: 003/010 | Batch 500/860 | Train Loss: 0.18\n",
+ "Epoch: 003/010 | Batch 750/860 | Train Loss: 0.26\n",
+ "Train Acc 93.71% | Val Acc 92.86%\n",
+ "Epoch: 004/010 | Batch 000/860 | Train Loss: 0.18\n",
+ "Epoch: 004/010 | Batch 250/860 | Train Loss: 0.14\n",
+ "Epoch: 004/010 | Batch 500/860 | Train Loss: 0.25\n",
+ "Epoch: 004/010 | Batch 750/860 | Train Loss: 0.23\n",
+ "Train Acc 94.80% | Val Acc 93.54%\n",
+ "Epoch: 005/010 | Batch 000/860 | Train Loss: 0.13\n",
+ "Epoch: 005/010 | Batch 250/860 | Train Loss: 0.20\n",
+ "Epoch: 005/010 | Batch 500/860 | Train Loss: 0.08\n",
+ "Epoch: 005/010 | Batch 750/860 | Train Loss: 0.18\n",
+ "Train Acc 95.47% | Val Acc 94.36%\n",
+ "Epoch: 006/010 | Batch 000/860 | Train Loss: 0.28\n",
+ "Epoch: 006/010 | Batch 250/860 | Train Loss: 0.31\n",
+ "Epoch: 006/010 | Batch 500/860 | Train Loss: 0.25\n",
+ "Epoch: 006/010 | Batch 750/860 | Train Loss: 0.07\n",
+ "Train Acc 95.72% | Val Acc 94.66%\n",
+ "Epoch: 007/010 | Batch 000/860 | Train Loss: 0.08\n",
+ "Epoch: 007/010 | Batch 250/860 | Train Loss: 0.11\n",
+ "Epoch: 007/010 | Batch 500/860 | Train Loss: 0.11\n",
+ "Epoch: 007/010 | Batch 750/860 | Train Loss: 0.15\n",
+ "Train Acc 96.06% | Val Acc 95.16%\n",
+ "Epoch: 008/010 | Batch 000/860 | Train Loss: 0.12\n",
+ "Epoch: 008/010 | Batch 250/860 | Train Loss: 0.19\n",
+ "Epoch: 008/010 | Batch 500/860 | Train Loss: 0.06\n",
+ "Epoch: 008/010 | Batch 750/860 | Train Loss: 0.14\n",
+ "Train Acc 96.48% | Val Acc 94.96%\n",
+ "Epoch: 009/010 | Batch 000/860 | Train Loss: 0.15\n",
+ "Epoch: 009/010 | Batch 250/860 | Train Loss: 0.08\n",
+ "Epoch: 009/010 | Batch 500/860 | Train Loss: 0.18\n",
+ "Epoch: 009/010 | Batch 750/860 | Train Loss: 0.05\n",
+ "Train Acc 97.01% | Val Acc 95.48%\n",
+ "Epoch: 010/010 | Batch 000/860 | Train Loss: 0.04\n",
+ "Epoch: 010/010 | Batch 250/860 | Train Loss: 0.08\n",
+ "Epoch: 010/010 | Batch 500/860 | Train Loss: 0.18\n",
+ "Epoch: 010/010 | Batch 750/860 | Train Loss: 0.13\n",
+ "Train Acc 97.24% | Val Acc 95.64%\n"
+ ]
+ }
+ ],
+ "source": [
+ "import torch.nn.functional as F\n",
+ "\n",
+ "torch.manual_seed(1)\n",
+ "model = PyTorchMLP(num_features=784, num_classes=10)\n",
+ "\n",
+ "optimizer = torch.optim.SGD(model.parameters(), lr=0.05)\n",
+ "\n",
+ "num_epochs = 10\n",
+ "\n",
+ "loss_list = []\n",
+ "train_acc_list, val_acc_list = [], []\n",
+ "for epoch in range(num_epochs):\n",
+ "\n",
+ " model = model.train()\n",
+ " for batch_idx, (features, labels) in enumerate(train_loader):\n",
+ "\n",
+ " logits = model(features)\n",
+ "\n",
+ " loss = F.cross_entropy(logits, labels)\n",
+ "\n",
+ " optimizer.zero_grad()\n",
+ " loss.backward()\n",
+ " optimizer.step()\n",
+ "\n",
+ " if not batch_idx % 250:\n",
+ " ### LOGGING\n",
+ " print(\n",
+ " f\"Epoch: {epoch+1:03d}/{num_epochs:03d}\"\n",
+ " f\" | Batch {batch_idx:03d}/{len(train_loader):03d}\"\n",
+ " f\" | Train Loss: {loss:.2f}\"\n",
+ " )\n",
+ " loss_list.append(loss.item())\n",
+ "\n",
+ " train_acc = compute_accuracy(model, train_loader)\n",
+ " val_acc = compute_accuracy(model, val_loader)\n",
+ " print(f\"Train Acc {train_acc*100:.2f}% | Val Acc {val_acc*100:.2f}%\")\n",
+ " train_acc_list.append(train_acc)\n",
+ " val_acc_list.append(val_acc)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "bb0d5821-7c8d-46b5-9e7d-02e72cac2acc",
+ "metadata": {},
+ "source": [
+ "## 7) Evaluating the results"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "27538c8d-61bc-47b0-8289-b6aab4aa16ed",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Train Acc 97.24%\n",
+ "Val Acc 95.64%\n",
+ "Test Acc 96.46%\n"
+ ]
+ }
+ ],
+ "source": [
+ "train_acc = compute_accuracy(model, train_loader)\n",
+ "val_acc = compute_accuracy(model, val_loader)\n",
+ "test_acc = compute_accuracy(model, test_loader)\n",
+ "\n",
+ "print(f\"Train Acc {train_acc*100:.2f}%\")\n",
+ "print(f\"Val Acc {val_acc*100:.2f}%\")\n",
+ "print(f\"Test Acc {test_acc*100:.2f}%\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "0f1f8499-3191-4f78-b2d4-82daba9b9bc0",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from helper_plotting import plot_training_loss\n",
+ "\n",
+ "plot_training_loss(minibatch_loss_list=loss_list,\n",
+ " num_epochs=num_epochs,\n",
+ " iter_per_epoch=len(loss_list)//num_epochs)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "bf9d4519-b7a2-4382-90d0-a0dce2ee608e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from helper_plotting import plot_accuracy\n",
+ "\n",
+ "plot_accuracy(train_acc_list=train_acc_list, valid_acc_list=val_acc_list)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "9051e410-2ad8-4416-a7a3-28c18c9aa4fe",
+ "metadata": {},
+ "source": [
+ "## 8) Inspecting failure cases"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "id": "b441ce90-6c6b-434d-8e92-5be0c8f16cee",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "from helper_plotting import show_examples\n",
+ "\n",
+ "\n",
+ "class_dict = {0: 'digit 0',\n",
+ " 1: 'digit 1',\n",
+ " 2: 'digit 2',\n",
+ " 3: 'digit 3',\n",
+ " 4: 'digit 4',\n",
+ " 5: 'digit 5',\n",
+ " 6: 'digit 6',\n",
+ " 7: 'digit 7',\n",
+ " 8: 'digit 8',\n",
+ " 9: 'digit 9'}\n",
+ "\n",
+ "show_examples(\n",
+ " model=model, data_loader=test_loader, class_dict=class_dict\n",
+ ")"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/helper_plotting.py b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/helper_plotting.py
new file mode 100644
index 000000000..44dee4ef5
--- /dev/null
+++ b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/helper_plotting.py
@@ -0,0 +1,138 @@
+import os
+
+import matplotlib.pyplot as plt
+import numpy as np
+import torch
+
+
+def plot_training_loss(
+ minibatch_loss_list,
+ num_epochs,
+ iter_per_epoch,
+ results_dir=None,
+ averaging_iterations=100,
+):
+
+ plt.figure()
+ ax1 = plt.subplot(1, 1, 1)
+ ax1.plot(
+ range(len(minibatch_loss_list)), (minibatch_loss_list), label="Minibatch Loss"
+ )
+
+ if len(minibatch_loss_list) > 1000:
+ ax1.set_ylim([0, np.max(minibatch_loss_list[1000:]) * 1.5])
+ ax1.set_xlabel("Iterations")
+ ax1.set_ylabel("Loss")
+
+ ax1.plot(
+ np.convolve(
+ minibatch_loss_list,
+ np.ones(
+ averaging_iterations,
+ )
+ / averaging_iterations,
+ mode="valid",
+ ),
+ label="Running Average",
+ )
+ ax1.legend()
+
+ ###################
+ # Set scond x-axis
+ ax2 = ax1.twiny()
+ newlabel = list(range(num_epochs + 1))
+
+ newpos = [e * iter_per_epoch for e in newlabel]
+
+ ax2.set_xticks(newpos[::10])
+ ax2.set_xticklabels(newlabel[::10])
+
+ ax2.xaxis.set_ticks_position("bottom")
+ ax2.xaxis.set_label_position("bottom")
+ ax2.spines["bottom"].set_position(("outward", 45))
+ ax2.set_xlabel("Epochs")
+ ax2.set_xlim(ax1.get_xlim())
+ ###################
+
+ plt.tight_layout()
+
+ if results_dir is not None:
+ image_path = os.path.join(results_dir, "plot_training_loss.pdf")
+ plt.savefig(image_path)
+
+
+def plot_accuracy(train_acc_list, valid_acc_list, results_dir=None):
+
+ num_epochs = len(train_acc_list)
+
+ plt.plot(np.arange(1, num_epochs + 1), train_acc_list, label="Training")
+ plt.plot(np.arange(1, num_epochs + 1), valid_acc_list, label="Validation")
+
+ plt.xlabel("Epoch")
+ plt.ylabel("Accuracy")
+ plt.legend()
+
+ plt.tight_layout()
+
+ if results_dir is not None:
+ image_path = os.path.join(results_dir, "plot_acc_training_validation.pdf")
+ plt.savefig(image_path)
+
+
+def show_examples(model, data_loader, unnormalizer=None, class_dict=None):
+
+ fail_features, fail_targets, fail_predicted = [], [], []
+ for batch_idx, (features, targets) in enumerate(data_loader):
+
+ with torch.no_grad():
+ logits = model(features)
+ predictions = torch.argmax(logits, dim=1)
+
+ mask = targets != predictions
+
+ fail_features.extend(features[mask])
+ fail_targets.extend(targets[mask])
+ fail_predicted.extend(predictions[mask])
+
+ if len(fail_targets) > 15:
+ break
+
+ fail_features = torch.cat(fail_features)
+ fail_targets = torch.tensor(fail_targets)
+ fail_predicted = torch.tensor(fail_predicted)
+
+ fig, axes = plt.subplots(nrows=3, ncols=5, sharex=True, sharey=True)
+
+ if unnormalizer is not None:
+ for idx in range(fail_features.shape[0]):
+ features[idx] = unnormalizer(fail_features[idx])
+
+ if fail_features.ndim == 4:
+ nhwc_img = np.transpose(fail_features, axes=(0, 2, 3, 1))
+ nhw_img = np.squeeze(nhwc_img.numpy(), axis=3)
+
+ for idx, ax in enumerate(axes.ravel()):
+ ax.imshow(nhw_img[idx], cmap="binary")
+ if class_dict is not None:
+ ax.title.set_text(
+ f"P: {class_dict[fail_predicted[idx].item()]}"
+ f"\nT: {class_dict[fail_targets[idx].item()]}"
+ )
+ else:
+ ax.title.set_text(f"P: {fail_predicted[idx]} | T: {fail_targets[idx]}")
+ ax.axison = False
+
+ else:
+
+ for idx, ax in enumerate(axes.ravel()):
+ ax.imshow(fail_features[idx], cmap="binary")
+ if class_dict is not None:
+ ax.title.set_text(
+ f"P: {class_dict[fail_predicted[idx].item()]}"
+ f"\nT: {class_dict[fail_targets[idx].item()]}"
+ )
+ else:
+ ax.title.set_text(f"P: {fail_predicted[idx]} | T: {targets[idx]}")
+ ax.axison = False
+ plt.tight_layout()
+ plt.show()
diff --git a/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/img/mnist-reshape.key b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/img/mnist-reshape.key
new file mode 100755
index 000000000..e9d52497a
Binary files /dev/null and b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/img/mnist-reshape.key differ
diff --git a/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/img/mnist-reshape.png b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/img/mnist-reshape.png
new file mode 100644
index 000000000..24d65afa0
Binary files /dev/null and b/unit04-multilayer-nets/4.3-mlp-pytorch/4.3-mlp-pytorch-part3-5-mnist/img/mnist-reshape.png differ
diff --git a/unit04-multilayer-nets/4.4-dataloaders/4.4-dataloaders-part3-download-and-prep.ipynb b/unit04-multilayer-nets/4.4-dataloaders/4.4-dataloaders-part3-download-and-prep.ipynb
new file mode 100755
index 000000000..2bb5a3ba4
--- /dev/null
+++ b/unit04-multilayer-nets/4.4-dataloaders/4.4-dataloaders-part3-download-and-prep.ipynb
@@ -0,0 +1,480 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "c6a92b64-ea7a-48f8-b3e9-debf7df1d854",
+ "metadata": {},
+ "source": [
+ "# Unit 4.4: Defining Efficient Data Loaders\n",
+ "\n",
+ "## Part 3 (Code part 1 of 2)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "d4633126-3fb1-4139-ba16-325127a84f60",
+ "metadata": {},
+ "source": [
+ "How to set up a `DataLoader` for a folder containing image files."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4f3f635e",
+ "metadata": {},
+ "source": [
+ "# Obtaining the Dataset"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1b0c13ad",
+ "metadata": {},
+ "source": [
+ "- This downloads the datasets png files:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "d2a3c21f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !pip install gitpython"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "2f2cbd7b-7193-4596-9b34-dde48cf29a2e",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Python implementation: CPython\n",
+ "Python version : 3.9.15\n",
+ "IPython version : 8.6.0\n",
+ "\n",
+ "git : 3.1.29\n",
+ "pandas: 1.5.2\n",
+ "\n",
+ "conda environment: dl-fundamentals\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "%load_ext watermark\n",
+ "%watermark -v -p git,pandas --conda"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "a7888009",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "from git import Repo\n",
+ "\n",
+ "if not os.path.exists(\"mnist-pngs\"):\n",
+ " Repo.clone_from(\"https://github.com/rasbt/mnist-pngs\", \"mnist-pngs\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "027d4a5a",
+ "metadata": {},
+ "source": [
+ "# CSV"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "ff8099b9",
+ "metadata": {},
+ "source": [
+ "- Here, we check the CSV files listing the image names and labels"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "51371d67",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " filepath | \n",
+ " label | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 0 | \n",
+ " train/0/16585.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 1 | \n",
+ " train/0/24537.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 2 | \n",
+ " train/0/25629.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 3 | \n",
+ " train/0/20751.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 4 | \n",
+ " train/0/34730.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " filepath | \n",
+ " label | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 0 | \n",
+ " test/0/66062.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 1 | \n",
+ " test/0/64675.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 2 | \n",
+ " test/0/62204.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 3 | \n",
+ " test/0/60407.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 4 | \n",
+ " test/0/67368.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " filepath | \n",
+ " label | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 29561 | \n",
+ " train/4/38855.png | \n",
+ " 4 | \n",
+ "
\n",
+ " \n",
+ " | 26640 | \n",
+ " train/4/17837.png | \n",
+ " 4 | \n",
+ "
\n",
+ " \n",
+ " | 24498 | \n",
+ " train/3/7672.png | \n",
+ " 3 | \n",
+ "
\n",
+ " \n",
+ " | 24594 | \n",
+ " train/3/17906.png | \n",
+ " 3 | \n",
+ "
\n",
+ " \n",
+ " | 24249 | \n",
+ " train/3/41969.png | \n",
+ " 3 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " filepath | \n",
+ " label | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 8023 | \n",
+ " train/1/9221.png | \n",
+ " 1 | \n",
+ "
\n",
+ " \n",
+ " | 26302 | \n",
+ " train/4/32108.png | \n",
+ " 4 | \n",
+ "
\n",
+ " \n",
+ " | 54489 | \n",
+ " train/9/7053.png | \n",
+ " 9 | \n",
+ "
\n",
+ " \n",
+ " | 2712 | \n",
+ " train/0/32086.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ " | 1463 | \n",
+ " train/0/12095.png | \n",
+ " 0 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "