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| { | |
| "nbformat": 4, | |
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| "metadata": { | |
| "colab": { | |
| "provenance": [], | |
| "collapsed_sections": [ | |
| "8quVg-twgudS", | |
| "LVP1LIY9kF07", | |
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| "authorship_tag": "ABX9TyNOHKBuPJ5+JUGZ1500l4YR", | |
| "include_colab_link": true | |
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| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3" | |
| }, | |
| "language_info": { | |
| "name": "python" | |
| } | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/vukrosic/992685f472d84a39352b0fff756fe19d/master-math-of-a-neuron-road-to-top-0-1-ai-researcher.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "" | |
| ], | |
| "metadata": { | |
| "id": "Llr3q3-q0Wbb" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "**Ilya Sutskever:**\n", | |
| "\n", | |
| "1. Coming up with new ideas is modest, it’s more imprtant to understand the results, existing ideas and what’s going on. Main activity is understanding.\n", | |
| "2. I found that if I read something very slowly, I will eventually uderstand it." | |
| ], | |
| "metadata": { | |
| "id": "u9qbZ8R9orfO" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Master this to be 0.1%\n", | |
| "\n", | |
| "A few dudes just [doubled speed of AI training (and progress)](https://kellerjordan.github.io/posts/muon/)" | |
| ], | |
| "metadata": { | |
| "id": "cfKtDTna_3Po" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Chapter 1: Math is the CORE" | |
| ], | |
| "metadata": { | |
| "id": "8quVg-twgudS" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "## Step 1" | |
| ], | |
| "metadata": { | |
| "id": "e_5pSaDnhYcQ" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### 🔢 Task: Gradient Descent with Squared Loss (One Step)\n", | |
| "\n", | |
| "You are given:\n", | |
| "\n", | |
| "* Input `x = 3`\n", | |
| "* True output `y_true = 10`\n", | |
| "* Initial weight `w = 0.5`\n", | |
| "* Learning rate `η = 0.1`\n", | |
| "* Model:\n", | |
| "\n", | |
| " $$\n", | |
| " y_{\\text{pred}} = w \\cdot x\n", | |
| " $$\n", | |
| "* Loss:\n", | |
| "\n", | |
| " $$\n", | |
| " L = (y_{\\text{pred}} - y_{\\text{true}})^2\n", | |
| " $$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### ✍️ What to Compute:\n", | |
| "\n", | |
| "1. Compute the predicted value: $y_{\\text{pred}}$\n", | |
| "2. Compute the error: $y_{\\text{pred}} - y_{\\text{true}}$\n", | |
| "3. Compute the loss: $L$\n", | |
| "4. Compute the gradient of loss w\\.r.t. weight: $\\frac{dL}{dw}$\n", | |
| "5. Update the weight using gradient descent\n", | |
| "\n", | |
| " $$\n", | |
| " w_{\\text{new}} = w - \\eta \\cdot \\frac{dL}{dw}\n", | |
| " $$\n", | |
| "6. What is the new value of $w$?" | |
| ], | |
| "metadata": { | |
| "id": "Cnl1RCvwgykA" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "## Step 1: Solution" | |
| ], | |
| "metadata": { | |
| "id": "f1oS5qoohbIX" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### Given:\n", | |
| "\n", | |
| "* $x = 3$\n", | |
| "* $y_{\\text{true}} = 10$\n", | |
| "* Initial weight $w = 0.5$\n", | |
| "* Learning rate $\\eta = 0.1$\n", | |
| "* Prediction: $y_{\\text{pred}} = w \\cdot x$\n", | |
| "* Loss: $L = (y_{\\text{pred}} - y_{\\text{true}})^2$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### Step 1: Compute prediction\n", | |
| "\n", | |
| "$$\n", | |
| "y_{\\text{pred}} = w \\cdot x = 0.5 \\cdot 3 = 1.5\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### Step 2: Compute error\n", | |
| "\n", | |
| "$$\n", | |
| "\\text{error} = y_{\\text{pred}} - y_{\\text{true}} = 1.5 - 10 = -8.5\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### Step 3: Compute loss\n", | |
| "\n", | |
| "$$\n", | |
| "L = (-8.5)^2 = 72.25\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### Step 4: Compute gradient of loss w\\.r.t. weight\n", | |
| "\n", | |
| "We’ll use the chain rule:\n", | |
| "\n", | |
| "$$\n", | |
| "\\frac{dL}{dw} = \\frac{dL}{dy_{\\text{pred}}} \\cdot \\frac{dy_{\\text{pred}}}{dw}\n", | |
| "$$\n", | |
| "\n", | |
| "1. $\\frac{dL}{dy_{\\text{pred}}} = 2 (y_{\\text{pred}} - y_{\\text{true}}) = 2 \\cdot (-8.5) = -17$\n", | |
| "2. $\\frac{dy_{\\text{pred}}}{dw} = x = 3$\n", | |
| "\n", | |
| "So:\n", | |
| "\n", | |
| "$$\n", | |
| "\\frac{dL}{dw} = -17 \\cdot 3 = -51\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### Step 5: Gradient descent update\n", | |
| "\n", | |
| "$$\n", | |
| "w_{\\text{new}} = w - \\eta \\cdot \\frac{dL}{dw} = 0.5 - 0.1 \\cdot (-51) = 0.5 + 5.1 = 5.6\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### ✅ Final Answer:\n", | |
| "\n", | |
| "$$\n", | |
| "\\boxed{w = 5.6}\n", | |
| "$$" | |
| ], | |
| "metadata": { | |
| "id": "GVilPRyrhcge" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "## Step 2" | |
| ], | |
| "metadata": { | |
| "id": "kmTpJKU4hq-s" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### 🧠 Next Step Task:\n", | |
| "\n", | |
| "You just updated:\n", | |
| "\n", | |
| "* **Previous weight:** $w = 5.6$\n", | |
| "\n", | |
| "Now, compute the next update using the same setup:\n", | |
| "\n", | |
| "* $x = 3$\n", | |
| "* $y_{\\text{true}} = 10$\n", | |
| "* Learning rate $\\eta = 0.1$\n", | |
| "* Prediction: $y_{\\text{pred}} = w \\cdot x$\n", | |
| "* Loss: $L = (y_{\\text{pred}} - y_{\\text{true}})^2$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "👉 **Your goal:**\n", | |
| "Use the chain rule to calculate the gradient $\\frac{dL}{dw}$, then perform the gradient descent update to get the **new value of $w$**.\n", | |
| "\n", | |
| "Don't forget:\n", | |
| "\n", | |
| "$$\n", | |
| "\\frac{dL}{dw} = 2(y_{\\text{pred}} - y_{\\text{true}}) \\cdot x\n", | |
| "$$" | |
| ], | |
| "metadata": { | |
| "id": "cacX006rhtOL" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "## Step 2: Solution" | |
| ], | |
| "metadata": { | |
| "id": "5o-GAHBxhw__" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Let's solve it step-by-step using the values:\n", | |
| "\n", | |
| "* $w = 5.6$\n", | |
| "* $x = 3$\n", | |
| "* $y_{\\text{true}} = 10$\n", | |
| "* $\\eta = 0.1$ (learning rate)\n", | |
| "* Prediction:\n", | |
| "\n", | |
| " $$\n", | |
| " y_{\\text{pred}} = w \\cdot x = 5.6 \\cdot 3 = 16.8\n", | |
| " $$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### Step 1: Compute the error\n", | |
| "\n", | |
| "$$\n", | |
| "\\text{error} = y_{\\text{pred}} - y_{\\text{true}} = 16.8 - 10 = 6.8\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### Step 2: Compute the gradient\n", | |
| "\n", | |
| "$$\n", | |
| "\\frac{dL}{dw} = 2 \\cdot \\text{error} \\cdot x = 2 \\cdot 6.8 \\cdot 3 = 40.8\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### Step 3: Gradient descent update\n", | |
| "\n", | |
| "$$\n", | |
| "w_{\\text{new}} = w - \\eta \\cdot \\frac{dL}{dw} = 5.6 - 0.1 \\cdot 40.8 = 5.6 - 4.08 = 1.52\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "✅ **New weight:** $w = \\boxed{1.52}$" | |
| ], | |
| "metadata": { | |
| "id": "9CAPQK_uhy0H" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Chapter 2: Let's plot how weight (W) changes" | |
| ], | |
| "metadata": { | |
| "id": "LVP1LIY9kF07" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "# Initialize variables\n", | |
| "w = 0.0\n", | |
| "x = 3\n", | |
| "y_true = 10\n", | |
| "lr = 0.1\n", | |
| "steps = 30\n", | |
| "\n", | |
| "# Record weight values for plotting\n", | |
| "w_history = []\n", | |
| "\n", | |
| "for step in range(steps):\n", | |
| " y_pred = w * x\n", | |
| " error = y_pred - y_true\n", | |
| " grad = 2 * error * x\n", | |
| " w = w - lr * grad\n", | |
| " w_history.append(w)\n", | |
| "\n", | |
| "# Plot\n", | |
| "plt.figure(figsize=(10, 5))\n", | |
| "plt.plot(range(steps), w_history, marker='o')\n", | |
| "plt.axhline(y=10/x, color='r', linestyle='--', label='Target w = {:.2f}'.format(10/x))\n", | |
| "plt.title(\"Convergence of w during Gradient Descent\")\n", | |
| "plt.xlabel(\"Iteration\")\n", | |
| "plt.ylabel(\"w value\")\n", | |
| "plt.grid(True)\n", | |
| "plt.legend()\n", | |
| "plt.tight_layout()\n", | |
| "plt.show()" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 507 | |
| }, | |
| "id": "8d93zzzNjS30", | |
| "outputId": "aec59796-985c-4015-d3d1-24506da9defd" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 1000x500 with 1 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### How can you make it not oscilate above and below the correct W, but converge from one side (why is it oscilating)?" | |
| ], | |
| "metadata": { | |
| "id": "cbPAFVK5kM0e" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Lower learning rate will make it converge from one side\n", | |
| "\n", | |
| "lr = 0.1 -> 0.01" | |
| ], | |
| "metadata": { | |
| "id": "5bQf0xJbkbHo" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "# Initialize variables\n", | |
| "w = 0.0\n", | |
| "x = 3\n", | |
| "y_true = 10\n", | |
| "lr = 0.01\n", | |
| "steps = 30\n", | |
| "\n", | |
| "# Record weight values for plotting\n", | |
| "w_history = []\n", | |
| "\n", | |
| "for step in range(steps):\n", | |
| " y_pred = w * x\n", | |
| " error = y_pred - y_true\n", | |
| " grad = 2 * error * x\n", | |
| " w = w - lr * grad\n", | |
| " w_history.append(w)\n", | |
| "\n", | |
| "# Plot\n", | |
| "plt.figure(figsize=(10, 5))\n", | |
| "plt.plot(range(steps), w_history, marker='o')\n", | |
| "plt.axhline(y=10/x, color='r', linestyle='--', label='Target w = {:.2f}'.format(10/x))\n", | |
| "plt.title(\"Convergence of w during Gradient Descent\")\n", | |
| "plt.xlabel(\"Iteration\")\n", | |
| "plt.ylabel(\"w value\")\n", | |
| "plt.grid(True)\n", | |
| "plt.legend()\n", | |
| "plt.tight_layout()\n", | |
| "plt.show()" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 507 | |
| }, | |
| "id": "ES9PQEBOjjLX", | |
| "outputId": "1aef3190-1171-4d45-ad5e-8827d1679e2c" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 1000x500 with 1 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# 🧨 Exploding Gradients" | |
| ], | |
| "metadata": { | |
| "id": "rP9WFfxxnDh3" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Let's try:\n", | |
| "- x = 9 (w will converge to the correct value)\n", | |
| "- x = 10 (w will stay the same)\n", | |
| "- x = 11 (w will explode, diverge)" | |
| ], | |
| "metadata": { | |
| "id": "GOhUbaHvqqwM" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "# Initialize variables\n", | |
| "w = 0.0\n", | |
| "x = 10 # Try 9, 10, 11\n", | |
| "y_true = 10\n", | |
| "lr = 0.01\n", | |
| "steps = 12\n", | |
| "\n", | |
| "# Record weight values for plotting\n", | |
| "w_history = []\n", | |
| "\n", | |
| "for step in range(steps):\n", | |
| " y_pred = w * x\n", | |
| " error = y_pred - y_true\n", | |
| " grad = 2 * error * x\n", | |
| " w = w - lr * grad\n", | |
| " w_history.append(w)\n", | |
| "\n", | |
| "# Plot\n", | |
| "plt.figure(figsize=(10, 5))\n", | |
| "plt.plot(range(steps), w_history, marker='o')\n", | |
| "plt.axhline(y=10/x, color='r', linestyle='--', label='Target w = {:.2f}'.format(10/x))\n", | |
| "plt.title(\"Convergence of w during Gradient Descent\")\n", | |
| "plt.xlabel(\"Iteration\")\n", | |
| "plt.ylabel(\"w value\")\n", | |
| "plt.grid(True)\n", | |
| "plt.legend()\n", | |
| "plt.tight_layout()\n", | |
| "plt.show()" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 507 | |
| }, | |
| "id": "HDk2eyI3qS_a", | |
| "outputId": "8fa44bad-53c8-4a54-e180-2763265ac284" | |
| }, | |
| "execution_count": 8, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 1000x500 with 1 Axes>" | |
| ], | |
| "image/png": 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\n" | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Reducing learning rate can help with exploding gradients." | |
| ], | |
| "metadata": { | |
| "id": "yNN-59jArQsZ" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "## 🧨 What is Exploding Gradient?\n", | |
| "\n", | |
| "When gradients during backpropagation become **too large**, parameters like $w$ can grow exponentially and diverge (go to infinity or NaN). This usually happens in deep networks or with very steep loss surfaces.\n", | |
| "\n", | |
| "We’ll demonstrate this with a **simple example** where the gradient becomes too large.\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "## 🔢 Setup: Exaggerated Case\n", | |
| "\n", | |
| "Let’s define:\n", | |
| "\n", | |
| "* Input: $x = 100$\n", | |
| "* True label: $y_{\\text{true}} = 200$\n", | |
| "* Prediction: $y_{\\text{pred}} = w \\cdot x$\n", | |
| "* Loss: $L = (y_{\\text{pred}} - y_{\\text{true}})^2$\n", | |
| "* Gradient: $\\frac{dL}{dw} = 2 (w x - y) \\cdot x$\n", | |
| "* Learning rate: $\\eta = 0.01$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "## 🎯 Start with initial weight\n", | |
| "\n", | |
| "Let’s choose $w = 1$\n", | |
| "\n", | |
| "Then:\n", | |
| "\n", | |
| "### 🔁 First iteration\n", | |
| "\n", | |
| "1. Prediction:\n", | |
| "\n", | |
| " $$\n", | |
| " y = w \\cdot x = 1 \\cdot 100 = 100\n", | |
| " $$\n", | |
| "2. Loss:\n", | |
| "\n", | |
| " $$\n", | |
| " L = (100 - 200)^2 = 10000\n", | |
| " $$\n", | |
| "3. Gradient:\n", | |
| "\n", | |
| " $$\n", | |
| " \\frac{dL}{dw} = 2 (100 - 200) \\cdot 100 = -20000\n", | |
| " $$\n", | |
| "4. Update:\n", | |
| "\n", | |
| " $$\n", | |
| " w = w - \\eta \\cdot \\frac{dL}{dw} = 1 - 0.01 \\cdot (-20000) = 1 + 200 = \\boxed{201}\n", | |
| " $$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### 🔁 Second iteration\n", | |
| "\n", | |
| "1. Prediction:\n", | |
| "\n", | |
| " $$\n", | |
| " y = 201 \\cdot 100 = 20100\n", | |
| " $$\n", | |
| "2. Loss:\n", | |
| "\n", | |
| " $$\n", | |
| " L = (20100 - 200)^2 \\approx 3.92 \\times 10^8\n", | |
| " $$\n", | |
| "3. Gradient:\n", | |
| "\n", | |
| " $$\n", | |
| " \\frac{dL}{dw} = 2 (20100 - 200) \\cdot 100 = 3980000\n", | |
| " $$\n", | |
| "4. Update:\n", | |
| "\n", | |
| " $$\n", | |
| " w = 201 - 0.01 \\cdot 3980000 = 201 - 39800 = \\boxed{-39599}\n", | |
| " $$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### 🔁 Third iteration (even worse!)\n", | |
| "\n", | |
| "1. Prediction:\n", | |
| "\n", | |
| " $$\n", | |
| " y = -39599 \\cdot 100 = -3.9599 \\times 10^6\n", | |
| " $$\n", | |
| "2. Loss:\n", | |
| "\n", | |
| " $$\n", | |
| " L = (-3.96 \\times 10^6 - 200)^2 \\gg 10^{13}\n", | |
| " $$\n", | |
| "3. Gradient:\n", | |
| "\n", | |
| " $$\n", | |
| " \\frac{dL}{dw} \\sim 2 \\cdot (-3.96 \\times 10^6 - 200) \\cdot 100 \\sim -7.92 \\times 10^8\n", | |
| " $$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "## 📉 Result: Gradients explode\n", | |
| "\n", | |
| "Every update becomes:\n", | |
| "\n", | |
| "* Hugely overcorrected\n", | |
| "* Worse than before\n", | |
| "* Loss skyrockets\n", | |
| "* Eventually: `NaN` (not-a-number) or overflow\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "## 🛑 How to prevent exploding gradients?\n", | |
| "\n", | |
| "* **Gradient clipping:** clip gradients within a fixed range\n", | |
| "* **Weight initialization:** proper scaling (e.g. Xavier, Kaiming)\n", | |
| "* **Smaller learning rates**\n", | |
| "* **Normalized inputs**\n", | |
| "* **Better architectures** (e.g., residual connections, layer norm)" | |
| ], | |
| "metadata": { | |
| "id": "vVeo21-jnFBr" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "## Optional: Analysis of exploding gradients" | |
| ], | |
| "metadata": { | |
| "id": "d5OJzo2pxDTG" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "I didn't study this in depth for now, if I find it important, I will study it more in a different video." | |
| ], | |
| "metadata": { | |
| "id": "y6Dsuj9exHO_" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Run the code and check plots and explanations below." | |
| ], | |
| "metadata": { | |
| "id": "ZKJugW3WxjRV" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "def gradient_descent(x, y_true=10, lr=0.001, steps=100, w_init=0.0):\n", | |
| " \"\"\"Run gradient descent and return weight history\"\"\"\n", | |
| " w = w_init\n", | |
| " w_history = [w]\n", | |
| "\n", | |
| " for step in range(steps):\n", | |
| " y_pred = w * x\n", | |
| " error = y_pred - y_true\n", | |
| " grad = 2 * error * x\n", | |
| " w = w - lr * grad\n", | |
| " w_history.append(w)\n", | |
| "\n", | |
| " # Stop if values become too large (divergence detection)\n", | |
| " if abs(w) > 1000:\n", | |
| " break\n", | |
| "\n", | |
| " return w_history\n", | |
| "\n", | |
| "# First: Show the original comparison (x=9,10,11 with lr=0.001)\n", | |
| "x_values = [9, 10, 11]\n", | |
| "fig, axes = plt.subplots(1, 3, figsize=(15, 5))\n", | |
| "\n", | |
| "for idx, x in enumerate(x_values):\n", | |
| " w_history = gradient_descent(x, lr=0.001, steps=50)\n", | |
| " target_w = 10/x\n", | |
| "\n", | |
| " ax = axes[idx]\n", | |
| " ax.plot(w_history, marker='o', markersize=4, linewidth=2)\n", | |
| " ax.axhline(y=target_w, color='r', linestyle='--', linewidth=2, label=f'Target w = {target_w:.3f}')\n", | |
| " ax.set_title(f'x = {x}, lr = 0.001', fontsize=12)\n", | |
| " ax.set_xlabel('Iteration')\n", | |
| " ax.set_ylabel('w value')\n", | |
| " ax.grid(True, alpha=0.3)\n", | |
| " ax.legend()\n", | |
| "\n", | |
| " # Add convergence factor (fixed calculation)\n", | |
| " conv_factor = 1 - 2*0.001*x**2\n", | |
| " ax.text(0.05, 0.95, f'Conv factor: {conv_factor:.3f}',\n", | |
| " transform=ax.transAxes, verticalalignment='top',\n", | |
| " bbox=dict(boxstyle='round', facecolor='lightblue', alpha=0.8))\n", | |
| "\n", | |
| "plt.suptitle('Original Comparison: Gradient Descent for x=9,10,11 with lr=0.001', fontsize=14)\n", | |
| "plt.tight_layout()\n", | |
| "plt.show()\n", | |
| "\n", | |
| "# Second: Show effect of different learning rates with x=10\n", | |
| "fig, axes = plt.subplots(2, 3, figsize=(15, 10))\n", | |
| "x_test = 10\n", | |
| "lr_values = [0.001, 0.005, 0.01, 0.011, 0.015, 0.02]\n", | |
| "\n", | |
| "for idx, lr in enumerate(lr_values):\n", | |
| " row = idx // 3\n", | |
| " col = idx % 3\n", | |
| " ax = axes[row, col]\n", | |
| "\n", | |
| " w_history = gradient_descent(x_test, lr=lr, steps=50)\n", | |
| " target_w = 10/x_test\n", | |
| "\n", | |
| " # Determine appropriate y-limits based on the data\n", | |
| " max_w = max(abs(min(w_history)), abs(max(w_history)))\n", | |
| " y_limit = min(max_w * 1.2, 50) # Cap at reasonable value for visualization\n", | |
| "\n", | |
| " ax.plot(w_history, marker='o', markersize=3, linewidth=2)\n", | |
| " ax.axhline(y=target_w, color='r', linestyle='--', linewidth=2, label=f'Target w = {target_w:.1f}')\n", | |
| " ax.set_ylim(-y_limit, y_limit)\n", | |
| "\n", | |
| " # Fixed convergence factor calculation\n", | |
| " conv_factor = 1 - 2*lr*x_test**2\n", | |
| " if abs(conv_factor) < 1:\n", | |
| " stability = \"Stable\"\n", | |
| " color = 'lightgreen'\n", | |
| " elif abs(conv_factor) == 1:\n", | |
| " stability = \"Critical\"\n", | |
| " color = 'yellow'\n", | |
| " else:\n", | |
| " stability = \"Unstable\"\n", | |
| " color = 'lightcoral'\n", | |
| "\n", | |
| " ax.set_title(f'lr = {lr}, Conv factor = {conv_factor:.3f}', fontsize=11)\n", | |
| " ax.set_xlabel('Iteration')\n", | |
| " ax.set_ylabel('w value')\n", | |
| " ax.grid(True, alpha=0.3)\n", | |
| " ax.legend()\n", | |
| "\n", | |
| " # Add stability indicator\n", | |
| " ax.text(0.05, 0.05, f'{stability}',\n", | |
| " transform=ax.transAxes, verticalalignment='bottom',\n", | |
| " bbox=dict(boxstyle='round', facecolor=color, alpha=0.8))\n", | |
| "\n", | |
| "plt.suptitle(f'Effect of Learning Rate on Convergence (x = {x_test})', fontsize=14)\n", | |
| "plt.tight_layout()\n", | |
| "plt.show()\n", | |
| "\n", | |
| "# Third: Show the stability regions\n", | |
| "x_range = np.linspace(1, 20, 100)\n", | |
| "critical_lr = 1 / (2 * x_range**2) # Fixed: critical lr is 1/(2x²), not 1/x²\n", | |
| "\n", | |
| "plt.figure(figsize=(12, 8))\n", | |
| "plt.plot(x_range, critical_lr, 'b-', linewidth=3, label='Critical lr = 1/(2x²)')\n", | |
| "plt.axhline(y=0.001, color='r', linestyle='--', linewidth=2, label='Your lr = 0.001')\n", | |
| "plt.fill_between(x_range, 0, critical_lr, alpha=0.3, color='green', label='Stable region (lr < 1/(2x²))')\n", | |
| "plt.fill_between(x_range, critical_lr, 0.02, alpha=0.3, color='red', label='Unstable region (lr > 1/(2x²))')\n", | |
| "\n", | |
| "plt.xlabel('x value', fontsize=12)\n", | |
| "plt.ylabel('Learning rate', fontsize=12)\n", | |
| "plt.title('Stability Analysis: Critical Learning Rate vs Input Value', fontsize=14)\n", | |
| "plt.legend(fontsize=11)\n", | |
| "plt.grid(True, alpha=0.3)\n", | |
| "plt.xlim(1, 20)\n", | |
| "plt.ylim(0, 0.02)\n", | |
| "\n", | |
| "# Mark the specific x values with correct critical learning rates\n", | |
| "for x in [9, 10, 11]:\n", | |
| " critical = 1/(2*x**2)\n", | |
| " plt.plot(x, critical, 'ko', markersize=10)\n", | |
| " plt.text(x, critical + 0.001, f'x={x}\\nlr<{critical:.4f}',\n", | |
| " ha='center', va='bottom', fontsize=10,\n", | |
| " bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))\n", | |
| "\n", | |
| "plt.show()\n", | |
| "\n", | |
| "# Fourth: Demonstrate the mathematical relationship\n", | |
| "print(\"Mathematical Analysis:\")\n", | |
| "print(\"=\" * 50)\n", | |
| "print(\"Update rule: w_new = w - lr * 2 * (w*x - y_true) * x\")\n", | |
| "print(\"Rearranged: w_new = w(1 - 2*lr*x²) + 2*lr*x*y_true\")\n", | |
| "print()\n", | |
| "print(\"For convergence: |1 - 2*lr*x²| < 1\")\n", | |
| "print(\"This gives us: lr < 1/(2*x²)\")\n", | |
| "print()\n", | |
| "\n", | |
| "for x in [9, 10, 11]:\n", | |
| " critical_lr = 1/(2*x**2)\n", | |
| " current_lr = 0.001\n", | |
| " conv_factor = 1 - 2*current_lr*x**2\n", | |
| " print(f\"x = {x:2d}: Critical lr < {critical_lr:.5f}, Current lr = {current_lr:.3f}\")\n", | |
| " print(f\" Convergence factor = {conv_factor:.3f} ({'Stable' if abs(conv_factor) < 1 else 'Unstable'})\")\n", | |
| " print()" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 1000 | |
| }, | |
| "id": "a1s401g2uri4", | |
| "outputId": "10795a61-a3e9-49e3-aa55-57008e10b40f" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 1500x500 with 3 Axes>" | |
| ], | |
| "image/png": 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| |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 1500x1000 with 6 Axes>" | |
| ], | |
| "image/png": 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sR48eDABr06YNy8zM5DoXY4xdf/31zGazKZKPoRLpp0+fZmazmV111VWq53vrrbcYALZixQrdtlu0aMGsVqtiwsjPfffdxwCwDz/8UNrmT8Q+++yzQcf793311Ve67U6YMIEBYLNnz9Y9Vo7Re8kfR7X727/vrbfekrbl5uayqKgo1rFjR8WxOTk5zG63s86dO0vbKnMv+fvym2++GXT8hg0bGAB2ww03BO07duwYM5vNQYn0Sy65hDmdTlZcXBxk8+uvvzIA7LHHHpO2Gf38/vGPf3Anao36osXq1auD7t9Ajhw5whISElhycjJ78cUXGQA2bNgw3XPL8X8WvD+jR482dH4/eon0Tz75hAFg//rXv1T3+ydrvvjii6B9ixcvDjneEQRBEARx/kHSLgRBEARxATFkyBB8++231Xb+H3/8EQBw4MAB1UVNT506BVEUcfDgQXTv3h3bt28HAAwePLjafNq1axccDgcuvfTSoH1+3fXdu3dXW/tyDhw4gJycHDRs2BDTp08P2n/69GkAwP79+6VtjDHMmzcP8+fPx759+5CXl6fQiPYv/BqI2vX6adOmDWJiYhTbLBYLUlJSkJuby3093bp1C9rml+SQn2fPnj0AIMlQyLnsssuCpFh4+OWXX4K00Nu2bYstW7agfv36Qcfv3r0br7zyCrZs2YJTp07B7XYr9p85c4ZrUdUdO3bA6/WirKxMtY8fOnQIgO8zvO666zTPk5+fj7///hvt2rULkjEBfH1z7ty52L17N+666y7FPt64VzWVvZd4/Y2Pj8cNN9yApUuXYs+ePejUqRMA4NNPP0VZWZkiDpW5l/yo+R+qjzZp0gRNmzbF4cOHpW3FxcXYu3cvGjZsiJdffjnIxt+/1NrnjQfv8zEcXwLx69aHksxKT0/H7NmzMWLECDzzzDNo3Lgx5s6dq3tuOfPnz6/z+uJJSUkAfM8OgiAIgiAuDCiRThAEQRBElXHu3DkA0NVpLioqAgDk5eUBABo1alRtPuXn5wdp2/rxJ07z8/OrrX05/vj89ttv+O233zSP88cHAP75z3/inXfeQZMmTXDDDTcgLS1N0iCePn265sJ+KSkpmuePi4tT3W6xWOD1enWvI9R5/Elx+Xn88fVrUcsxmUyqiW89xo8fj9mzZ4MxhszMTLzxxht47bXXcNttt+H777+H2WyWjv3hhx+kRSwHDx6M1q1bIyYmBoIgSHr/vAsk+j/DrVu3qi4I6kf+Garhj4nW5xSqb/LGXYvU1FQAQEZGhu6xcip7Lxnx96677sLSpUvx8ccfS4n0jz76CGazGaNGjZKOq8y95Ect5qH6qN9GnkjPyckBYwwZGRmqifxQ7fPGIy8vD4Ig6E7whONLINHR0QB8+v2hGDBgAOLi4pCfn49Ro0ZJSeW6Rnx8PICKsSgQf7/wHyfHvzisw+GoJu8IgiAIgog0KJFOEARBEESV4U8QrVixImQ1rh9/1aPRhJ5Rn7Kzs1X3nTp1SjqmJvC3c8stt+Czzz7TPT47OxvvvvsuLrnkEmzbtk2RsDl16lTIpJkgCOE7XEX4r1vtcxBFEWfOnKn0ZIogCGjYsCFeffVVnDp1Ch9//DHefvttPPzww9IxL7zwAsrKyrB58+agiuMff/xRqkY2ci2PPfYY1+KNeufJyspS3V+dfbN3794AgLVr1+K5557jtquJe+nqq69GgwYNsGjRIrz88ss4duwYtmzZgsGDB0sTAPJ2eO8lOWr3Rqg+CgR/Tv7ju3Xrhp9//tlQ+7wkJCRIE0Wh7o+q9KVBgwYAKiYqtLjnnnuQn5+PevXqYdasWRg5cqTqwrxaLFu2zNCbQJ07d+ZawNcorVu3BlDxJkkg/u3+4+T4Y+SPGUEQBEEQ5z+m2naAIAiCIIjzh8suuwwAsG3bNq7j/RILa9as0T3WX2FspGIaALp06YLi4mJJJkHOhg0bAMBQAigc2rVrh7i4OPz8889B0iJq/P3332CMYeDAgUFVj5s3b64uN6scf2WxWgX39u3b4fF4qqSdV155BdHR0Xj++edRUFAgbf/rr7+QlJQUlEQvLi7Gzp07g84Tqq/16NEDgiBw93Et4uLi0KJFC/z555+qE0nV2TevvPJKtGjRAj/88APWr18f8lh5pX5N3EsWiwUjRoxARkYG1q9fj08++QSMMdx5552K44zeS3qE6qMnTpzAsWPHFNtiY2PRrl07/PHHH9Ump8P7fKxKXy6++GKYTCYcOHBA85h3330XK1aswJ133in5NnLkSBQXF3O3s2zZMkyfPp37Z9myZWFdlxatW7dGw4YNsXXr1qCK/aKiImzduhXNmzdXfRPDH6OOHTtWi28EQRAEQUQelEgnCIIgCKLKuPHGG9G0aVPMnDkTmzZtCtrvdruxZcsW6fcbbrgBjRs3xscff4zVq1cHHS9PMPqlA44fP27Ip9GjRwMAJk2apEi4HT9+HDNnzoTFYsEdd9xh6JyVxWKx4B//+AeOHj2Kxx9/XDUBuG/fPqkqNj09HYBPmkSui37ixAlMmjSpRnyuCm688UbExMTg/fffx19//SVt93g8mDJlSpW1k5aWhgkTJuDs2bOYNWuWtD09PR05OTkKCRCv14vHH39c0tKWE6qvpaamYvjw4fjhhx/w6quvgjEWdMxPP/3ElVQcPXo03G43Jk2apDjPr7/+ivnz5yM+Pr5aqnDNZjPeffddmEwmDB8+HOvWrVM9bsWKFbj11lsV/gLVfy/5tdA/+ugjfPTRR3A6nbj55psVxxi9l/To06cPmjZtihUrVgRNkkyZMkV1UuWf//wniouLcd9996nKphw+fBhHjhzhal+NCRMmwGw2Y/LkyTh69KhiH2NMsT5CVfmSkJCASy65BD///LPimeNn3759ePzxx9GiRQv85z//QdeuXfHCCy9g//79irdA9Jg/fz4YY9w/1aWnLggCxo0bh8LCQsyYMUOxb8aMGSgsLMR9992navvTTz/BYrHg8ssvrxbfCIIgCIKIPEjahSAIgiAuIP7880/VBRL9PP3004iKiqr0+e12Oz777DMMHToU/fr1w1VXXYWOHTtCEAQcPXoUmzdvRr169aRF7+x2O5YuXYqrr74aQ4cOxdVXX41OnTohPz8fu3fvRnFxMXbt2gUAuOiii9CwYUMsXrwYdrsdjRs3hiAIeOihh1T1a/3cdddd+OKLL7B8+XJccskluO6661BUVIQlS5bg3LlzeP3119GiRYtKX7OczMxMjBkzRnVf/fr18dprr2H69OnYuXMn3nrrLaxcuRJ9+/ZFcnIyMjIysHfvXuzZswfbtm1DcnIy0tLScMstt+Dzzz9H9+7dMWDAAGRlZeHrr7/GgAEDFEnpSCYhIQEzZ87E/fffj27dumHEiBGIj4/HN998A7vdjoYNG8Jkqpr6jqeeegpz5szBzJkz8dBDDyEhIQEPPfQQ1qxZgz59+mD48OGIiorChg0bkJGRgf79+0vV1H569eqF6OhozJo1Czk5OZJ0w+TJkwEA//nPf3DgwAE8+eST+Oijj9CrVy8kJCTg+PHj+Pnnn3Ho0CFkZmbqaic/+eSTWLlyJT766CP88ccfGDBgALKzs7FkyRJ4PB7MnTsXsbGxVRKXQK6++mp89NFHGDduHAYMGIDu3bujV69eiI2NRVZWFjZs2IC//voLAwcOlGxq6l7q0aMH2rZti4ULF8LtduOuu+6C0+kMOs7IvaSH2WzG7NmzccMNN+Cqq67C7bffjrS0NGzcuBEZGRno1KkTfv31V4XN+PHj8eOPP2LBggXYunUrBg4ciIYNGyIrKwv79+/HTz/9hIULF6JZs2aVikPHjh0xa9Ys/POf/8TFF1+Mm266Cenp6Th16hQ2bdqEa6+9Vpowqkpfbr75ZkydOhU//vijIklcWlqKkSNHwuPxYOHChVLffOyxx7BmzRrMnTsXQ4YMwS233FKp660q3nvvPWnCdu/evdI2/33ep08fjBs3Tjr+ySefxPLly/Hyyy9j165d6Nq1K3bu3Ik1a9agR48eqhMEhYWF+PHHHzFo0CDVvkkQBEEQxHkKIwiCIAjivOfw4cMMgO5PTk6OZDN69GgGgB0+fDjofKH2McbYiRMn2MSJE1nr1q2Z3W5ncXFxrF27dmzcuHFs7dq1Qcf/+eef7N5772WNGzdmVquVJScns/79+7MPP/xQcdyPP/7I+vXrx2JjYyWftXyQ43a72WuvvcY6duzI7HY7i42NZf369WPLly9XPR4A69evn+55A21C/aSnp0vHejweNmfOHNa7d28WFxfH7HY7a9q0Kbv66qvZf//7X1ZYWCgdW1BQwB577DHWrFkzZrfbWevWrdmMGTOYy+VS9bNfv34s1Fe8UNeWnp6u8JMx9c96/fr1DACbOnVq0Dn8fW306NFB+z799FPWpUsXZrfbWXJyMhs3bhw7e/Ysi4mJYZ06ddL0WY6/7fHjx2se89hjjzEAbMqUKdK2zz77jHXt2pU5HA5Wv359Nnz4cPbXX39p9uWVK1eyHj16sOjoaOkzlFNcXMxeeeUV1q1bN+Z0Oll0dDRr3rw5u+mmm9iHH37I3G431/UUFhayKVOmsDZt2jCbzcYSEhLY0KFD2ebNm4OOnTp1KgPA1q9fH7Rv3rx5DACbN28eV7t+Tpw4wZ566inWpUsXFhcXxywWC0tJSWFXX301mzdvHnO5XIrjjdxLoXwK1YcYY+z555+X4r569WpN/43cS3rPLcYYW7duHevTpw+Ljo5mSUlJ7LbbbmPHjh1jHTp0YPHx8ao2S5YsYQMHDmSJiYnMarWyRo0asf79+7PXX3+dnT59Wjqusp/f+vXr2XXXXceSkpKYzWZjjRs3ZrfccgvbunVrpX0JRUZGBrNYLOwf//iHYvsDDzzAALDnn38+yObkyZOsfv36LDExkR07doyrnerC/zlr/ag9m3Jzc9nDDz/MmjRpwqxWK2vatCl77LHHWH5+vmob8+fPZwDYsmXLqvlqCIIgCIKIJATGVN5HJQiCIAiCIIga4M8//0Tr1q0xfPhwLFmypLbdIYggCgoKkJKSgo4dO+Knn36qbXdqhLvuugsrV67E0aNHq+2tiLrMFVdcgaysLPzxxx/SmgoEQRAEQZz/kEY6QRAEQRAEUe3k5OQoFq4EgJKSEjzyyCMAUC1a4ARhhKKiIsUitYBPS/+JJ55ASUnJBdVHn3/+eZSUlODtt9+ubVcijrVr12LLli14+eWXKYlOEARBEBcYpJFOEARBEARBVDsbN27Evffei8GDB6Np06Y4c+YM1q1bhyNHjkia1ARRmxw6dAh9+vTBkCFD0KJFCxQUFGDz5s34/fffcfHFF+Of//xnbbtYY6Snp2PBggXIysqqbVcijry8PLz22mtBC+ASBEEQBHH+Q9IuBEEQBEEQRLVz6NAhTJkyBT/88ANOnz4NAGjVqhVuv/12PP7442EtcksQVcHp06fx5JNPYuPGjcjKyoLH40HTpk1x00034V//+hcSEhJq20WCIAiCIAiiFqFEOkEQBEEQBEEQBEEQBEEQBEGEgDTSCYIgCIIgCIIgCIIgCIIgCCIElEgnCIIgCIIgCIIgCIIgCIIgiBBQIp0gCIIgCIIgCIIgCIIgCIIgQkCJdIIgCIIgCIIgCIIgCIIgCIIIASXSCYIgCIIgCIIgCIIgCIIgCCIElEgnCIIgCIIgCIIgCIIgCIIgiBBQIp0gCIIgCIIgCIIgCIIgCIIgQkCJdIIgCIIgCIIgCIIgCIIgCIIIASXSCYIgCIIgCIIgCIIgCIIgCCIElEgnIoIxY8agQ4cOte0GTp48iVtuuQWxsbFISkrCuHHjkJ+fz2X7/vvvo02bNoiKikKnTp3w9ddfBx2Tl5eHe++9F0lJSYiNjcWtt96KzMxMxTE///wzxo4di3bt2sFkMuG6664L+7r27t2LUaNGoWHDhrDZbEhJScGwYcOwdu3asM9dlbhcLowdOxYNGjSAIAiYNWtWlZ172bJl+M9//lNl56sJePqLGl6vF6+88gouuugiOBwOtGjRAk888QQKCwsVx7lcLjzxxBNITU2F0+nEoEGDcODAgaDz7d+/H4MGDYLT6URqaiqefPJJuFyuKrtOgiDqJjR2VzBt2jQIghD0M3v27EpfF43dF9bYDQArVqxAp06dEBUVhTZt2mDevHlBx9DYTRBEVXAhjOEulwtPPvkk+vbtC6fTCUEQcObMmbD8LSwsxPTp09GhQwc4HA44nU5ceumlmDlzJkpLS8M6d1WzcOFCtG7dGlarFZ07d66y8x45cgTTpk3DyZMnq+yctcHp06cxceJEXHbZZbDb7YiJiTFkX1XfIQHghx9+QK9evRAdHY309HS8/PLLYIxV+tqIaoYRRAQwevRodvHFF9eqDy6Xi3Xo0IF16NCBffXVV2zx4sWscePG7Nprr9W1XbRoERMEgU2ePJmtW7eOjR8/nlksFrZt2zbFcUOGDGGNGzdmS5YsYcuXL2cdOnRgnTp1Ym63Wzpm1qxZrGXLlmzUqFEsPT2dq/1QLFu2jNntdtatWzf2wQcfsI0bN7LPPvuMjRo1iplMJpabmxvW+auSuXPnMrPZzD7++GO2bds2lpmZWWXnjoQ+ZhSe/qLG9OnTmcViYS+99BJbt24de+utt1hMTAwbNWqU4rjx48ez+Ph49v7777Nvv/2WXXHFFaxRo0aKPnHu3DmWlpbG+vbty7799lv2/vvvs/j4ePbAAw9UyzUTBFF3iITnaqSM3VOnTmXR0dFs27Ztip+srKxKXReN3T4ioY8ZpbJj9+bNm5nZbGbjx49n69atY5MnT2aCILBPP/1UcRyN3QRBVAWR8Hyt7jE8JyeHJSQksEGDBrEhQ4YwAOz06dOV9vf06dOsQ4cOLD4+nk2dOpV999137LvvvmPPPfcca9CgAZs1a1alz13VFBQUMLvdzsaMGcO2bNnCfv311yo79/r16xkAtmPHjio7Z22wa9culpyczK677jp2+eWXM6fTyW1bld8hDx06xGJiYtjNN9/Mvv/+ezZz5kxms9nYq6++WmXXSlQtlEgnIgKegby4uLhafVi4cCETBIHt379f2rZ69WoGgP30008hbdu0acNGjhyp2NarVy82dOhQ6fcffviBAWCrV6+Wtu3fv58JgsCWLFkibfN6vdL/+/XrF1YiPTMzk8XFxbEBAwawsrKyoP3r1q1jRUVFlT5/VfPYY4+xJk2aVMu5q/rLYnX3R97+okbbtm3Z6NGjFdueffZZZrfbpUH7+PHjzGw2szlz5kjHnD17ljmdTvbyyy9L21588UXmdDrZ2bNnpW1z5sxhZrOZZWRkhHOJBEHUcWjsrngWT5061dAfYKGgsbuCC2nsHjx4MLv88ssV20aOHMnatWsn/U5jN0EQVcWFMIYzxpgoiowxxubNmxd2Iv22225jDoeD7d27N2jf2bNn2datWyt97qpm7969DABbu3ZtlZ+7qhPppaWlihxITSFv0+j3uKr8Dnn//fez9PR0xXe+SZMmsYSEBFZaWmromoiagaRdiIhk/vz5EAQB27Ztk15LfeKJJ6q1zVWrVuGSSy5B27ZtpW2DBg1CUlISvvnmG027v//+GwcPHsTw4cMV20eMGIG1a9eirKxMOn9CQgIGDRokHdO2bVt07txZcX6Tqepuy7lz5yI/Px9vvPEGbDZb0P4rr7wSDodD+n3OnDlo27Yt7HY7mjVrhueffx6iKEr7/Z/Lrl27MHToUDidTrRu3RoffvihdMy0adOQlJQEt9utaGvfvn0QBAGrV69W9bVZs2Z4/fXXcfz4cemV+CNHjmD//v0YMWIEmjRpAofDgfbt2+P1119X+AUAZWVlmDx5Mlq0aAG73Y7GjRtjzJgxAHyvLi5YsAC//fabdG7/PgD44osv0LlzZ0RFRaFhw4Z49NFHFa/mbdiwAYIgYOXKlbj11lsRFxeH2267Tf8DCAPe/qKG2+1GfHy8Ylt8fLwiZmvWrIEoiorrSEpKwuDBgxXnX7VqFQYOHIikpCRp2/DhwyGKItasWVPp6yMI4vzjQh67qxIau8cAuLDG7rKyMqxfvz7IvxEjRuCPP/7AkSNHANDYTRBE9XE+juEAIAhClfh69OhRfPbZZ5gwYYKqJE5SUhIuv/xy6fe9e/diyJAhcDqdiI+Px6233opjx44pbARBwCuvvIJp06YhJSUF9evXx9ixY1FUVATAJ6EiCAI+++yzoPa6d++OkSNHqvo6bdo0dOzYEQAwYMAACIKAadOmAQCefvppdOzYETExMWjUqBFGjhypKjWycuVK9O7dGw6HA4mJiejfvz927dqFDRs24MorrwQA9OjRQxqf5XG69dZbER8fD6fTiSFDhmDv3r2Kczdr1gwPPvggXnnlFaSnpyM6Ohrnzp1TvZbqpLJ5l6r+Drlq1SrcdNNNiu98I0aMQG5uLrZt21YpH4nqhRLpREQzatQoXHXVVfj6669x1113aR7n9Xrh8XhC/gT+8RbI/v37cdFFFym2CYKAiy66CPv37w9pByDItl27dnC5XDh8+LB0XNu2bYMG83bt2oU8fzhs3LgRDRs2lAbSULz99tuYMGEChgwZghUrVmDMmDGYNm0annzyyaBj77jjDgwePBjLli1Dly5dMGbMGPzxxx8AgJEjRyInJyfoj+5FixYhOTkZAwcOVG3/yy+/xO23347U1FRs27YN27ZtQ1paGjIyMtC2bVv85z//wTfffIP7778fzz33HGbMmKGwv+WWWzBz5kzcc889WLlyJV599VXpS8iUKVNwzTXXoEWLFtK5p0yZAgD46quvcOutt6J9+/ZYtmwZnnzyScyePRt33nlnkI/3338/WrZsiS+//BKPP/64Zix5+qPX6w3xaYTXX8aNG4ePPvoI69atQ2FhIbZv3y59vhaLRTp/cnIyEhMTQ55f7b5ISEhAWlpatfVbgiDqNhfq2F1SUoIGDRrAYrGgffv2mDt3bkjftaCx+8Ibu//66y+43W7V/ug/r/9fGrsJgqhOzqcxvCrZvHkzGGO4+uqrdY89fvw4+vbti7Nnz+Ljjz/G7NmzsXPnTvTr1w8FBQWKY9955x0cOnQICxYswLPPPouFCxdKY2WzZs3Qs2dPLF68WGFz6NAh/PLLLxg1apRq++PGjZMmy999911s27YN48aNAwBkZ2fjmWeewcqVK/Hmm2/iyJEj6NevHzwej2S/ZMkSXH/99UhOTsbChQvxySefoHfv3sjIyEDXrl3x7rvvAgDmzZsnjc8AUFBQICXcZ8+ejY8//hhnz55F3759cfz4cYWPn3/+Ob7++mu8+eabWL58OZxOp+q1MMZ0+5nc95qgKr9DFhUV4fjx40HnuuiiiyAIAo3ZEYqlth0giFBMmDABTz31lO5xLVu2xNGjR0MeM3r0aMyfP19zf05ODhISEoK2JyYmhpwhzcnJAYAgW/8fOX7byp4/HDIyMtC0aVPd47xeL5577jmMGDECb731FgBg8ODBcLlceP311zFp0iTUq1dPOv7BBx/E//3f/wEALr/8cqxcuRKff/45Jk+ejLZt26JLly5YtGiRYqHUxYsX47bbboPZbFb1oUuXLkhNTYXdbkfPnj2l7QMGDMCAAQMA+AbSPn36oLi4GO+88w6mTp0KAPjuu++wcuVKLFy4UDEz7/9/y5Yt0aBBAxw9elRxbsA3Y9+zZ08sXLgQAHD11VfD4XBg/Pjx2Lt3ryKRccMNN+Dll1/WjeeAAQOwcePGkMf069cPGzZs0NwfTn+ZNGkSysrKMHDgQGmRkjvvvFOxABzv+Wuj3xIEUbe5EMfuVq1a4eWXX0aXLl1QWlqKhQsX4v7770deXl7I5K0aNHZfeGN3VfdHGrsJgqgs59MYXpVkZGQAANf4/MYbb8DtdmPNmjXSm0FdunRB+/btMX/+fDz00EPSsWlpafjkk08A+MaynTt34rPPPsO///1vAL4x8amnnkJBQQFiY2MB+Ca5ExMTMWTIENX2GzduLI2D7du3V4yhH3zwgfR/r9eLXr16oXHjxli3bh0GDx4Mxhgef/xxDB48GF9++aV07DXXXCP9v3379gCADh06oHv37tL2efPm4ejRo/jtt9+kieB+/fqhadOmmDVrFl5//XXpWLfbjVWrVmkm0P0sWLAAY8eODXkMABw+fBjNmjXTPa4qqMoxOzc3V/VcNpsNDoeDxuwIhRLpRERz7bXXch23YsUKxStcatSvX78qXKpz8LzOtn//fpw5cyboleLbb78dL730ErZv346hQ4dK2wcPHiz93+l0Ij09HSdOnJC2jRw5Es899xxKSkoQHR2N7du34++//9Z8/SwUpaWleOmll/DJJ5/g2LFjitfOCwsLERMTg7Vr18LhcGDEiBGGzl1YWIjdu3fjtddeU2y//fbbMX78eGzZskXxxzhvf5wzZ05QtUEg/i9C1cE777yDN998E2+88Qa6dOmC3377DVOmTMFDDz0kVRAQBEFUFxfi2B1YCX3ttdfC5XLh+eefx8SJE2G1Wg2dj8Zubc7XsZsgCCISuBDHcCPwjM+bN2/GVVddpZDXuuiii9CpUyds2bJFkUiXy34AviS1vAJ9+PDheOSRR7Bs2TLpDYHFixfjlltuUZV/02PVqlWYMWMGfvvtN+Tn50vbDx48iMGDB+PAgQM4ceKEIunNy+bNm9GhQwcpiQ74JG8GDRqELVu2KI7t37+/bhIdAK6//nrs2LFD97iGDRtq7hNFUfF2hNlsrjLJH+LChBLpRESTkpLCdVz79u2lylst9DSwEhMTkZeXF7Q9JycHTZo0CWkHAHl5eUhNTVXYAZAG0MTExKBXmvzHyQfZqqRRo0ZcrwP5fQ2Mt//3wJlQtRlTuS7piBEj8NRTT2HFihUYPnw4Fi1ahPT0dIVuHC9PPfUU5s6di6lTp6Jbt25ISEjA8uXL8fzzz6O0tBQxMTE4e/Ys0tLSDA+Iubm5YIwFXXd8fDzsdnvQdfP2x1atWun2Rz1fK9tfzp49i8cffxyvvvqq9CWtb9++iIuLw5133omJEyeiTZs2Ifu7/Py8xxEEQfihsdvH8OHD8dlnn+HPP/9U/FGpB43doTkfx255fwy0A5T9kcZugiCqk/NpDK9KGjVqBAA4duwY2rRpE/LYnJwcdO7cOWh7SkoK19gsn6BITU3FlVdeiUWLFuGuu+7Cnj178Mcff1SqOGrHjh244YYbcOONN+Lpp59GcnIyBEFAz549pe8DZ8+eBRA6Ma1FTk6Oav9JSUnBvn37grbxkJSUFLT2lxp++VI17rnnHixYsED6fd68eYo1V4xSld8h/Z9/4H3gcrlQXFxMY3aEQhrpRETD+8dVy5YtYbVaQ/7cc889Ic+hpsXGGMOBAweCNKsC7QAE2e7fvx82mw0tWrSQjjtw4EDQFw41bbiqon///sjIyMBvv/0W8jj/Azo7O1uxPSsrS7GflyZNmqB3795YvHgxRFHE0qVLMWLEiErN/H766acYP348nnrqKQwcOBDdu3cPGijr1auHzMxM3S9zgSQkJEAQhKDrzsvLQ1lZWdB18/o/YMAA3f7of+Vdi8r2l7/++gtlZWVBX966dOki7fefPysrSxrwtc6vdl/k5eUhMzOz2votQRB1Gxq7w4PG7tCcj2O3/15Q64/+8/r/pbGbIIjq5Hwaw6uSvn37hlx8W05SUlLQGAX4xufKJEZHjhyJ77//HmfPnsXixYuRlpaGfv36GT7Pl19+ifj4eCxduhQ33HADevbsqUgEA5Ak4U6ePGn4/Eaum7efLViwQLefWa1WaVFuNaZNm4YdO3ZIP9dff72h6wqkKr9DOp1ONGnSJOhcfjsasyMTSqQT5wUrVqxQPBzVfvwrVWsxdOhQ7NmzB4cOHZK2rV27FmfPnlVoggXSokULtGnTBp9++qli+5IlSzBgwADplauhQ4ciJycHa9eulY45ePAgdu3aFfL84TBu3DjExcXhkUceUbxW7WfDhg0oLi5G27Zt0aBBg6BrWLp0KWw2Gy699FLDbY8cORLffPMNvv76a5w8ebJSr4YDvsXb5K+teb3eoAVXBg4ciOLiYixdulTzPIGVdwAQExODzp07B62E7j9Pnz59KuXznDlzdPvjnDlzQp6jsv0lPT0dALBz507F9l9++QUAJO24wYMHw2Qy4fPPP5eOycnJwZo1axTnHzp0KL7//ntJvw3wJUhMJpNCJoAgCMIo5/vYvXjxYiQkJKBVq1YhjwuExu4KLpSx226348orrwy6piVLlqBdu3Y0dhMEEXHUhTG8KmnatCluvfVW/Pe//8Xvv/8etD83N1dadLNPnz5Yu3atYtLzwIED+PXXXys1Rg0bNgyCIOCzzz7D4sWLcfvtt+tW+6tRUlICq9WqSGL79dn9tG3bFo0bN8a8efM0z+OPb+D43KdPH+zduxcHDhyQtuXk5OD777+v9Njsl3bR+wlVQd+sWTN0795d+pGvH1MZqvo75NChQ7F8+XLFd74lS5YgISGhUm8FEjUAI4gIYPTo0eziiy+Wfp83bx4DwE6fPl1jPrhcLtahQwfWsWNHtmLFCrZkyRLWpEkTdu211yqOu+eee5jZbFZsW7hwIRMEgT377LNs/fr1bMKECcxisbAffvhBcdyQIUNYkyZN2NKlS9lXX33FOnbsyDp16sTcbrd0THZ2Nvv000/Zp59+ytq3b8+6desm/V5UVCQd169fP5aenq57XcuWLWM2m4316NGDzZ8/n23atIl98cUX7O6772Zms5nl5uYyxhh76623GAA2ceJEtnr1ajZ9+nRmNpvZY489Jp1L63Pp1KkTGz16tGJbdnY2s1gsrGHDhqx9+/a6fjLG2MSJE4Ou6bbbbmOJiYls/vz57Ouvv2bXXHMNa968eZAf11xzDXM4HOyFF15g33//PVu6dCkbPny4tH/mzJnMbDazhQsXsh07drDDhw8zxhhbvnw5EwSB3XHHHWzVqlVs1qxZzOFwsFtuuUWyXb9+PQPAduzYwXUdVQVPf/F/TkeOHJG23XTTTSw2Npa99tprbN26deztt99mSUlJbODAgYrzjx8/niUkJLAPPviArV69mvXr1481atRI6hOMMXbu3DmWlpbG+vXrx1avXs0++OADlpCQwB544IHqDwBBEBENjd0Vz+KuXbuyN998k61evZotW7aM3XbbbQwAmzVrluJcNHbT2M2Y+ti9efNmZjab2T/+8Q+2fv169uyzzzJBENjSpUsV56exmyCIquBCGcO/+eYb9umnn7IHHniAAWAffPAB+/TTT9lvv/0mHeO/9vXr14f09/Tp0+ziiy9mCQkJbPr06ez7779n33//PXvhhRdYamqqNOYfO3aMJSQksO7du7Mvv/ySLVq0iLVs2ZI1a9aM5efnS+cDwF599VVFG2+88QZTS9PdcMMNrGHDhgwA2759e0g/GWNs165dQde0cuVKBoA98MAD7Pvvv2czZsxgbdq0CfJj8eLFTBAENmzYMLZs2TK2atUq9uyzz7IVK1ZIcTCbzWzs2LFs27Zt0jibn5/PmjVrxlq2bMkWLVrEvvzyS9a9e3eWkJDAjh07Jp0/PT09YsYjf57ltttuY1FRUdLv8vG5ur9DHjp0iDmdTnbLLbewtWvXslmzZjGbzRbUN4jIgRLpREQQCQM5Y4ydOHGCDRs2jMXExLCEhAR2zz33sLy8vCBf1Qa39957j7Vq1YrZbDbpy0Agubm57J577mEJCQksJiaGDRs2jGVkZCiO8f/hp/bj/wOSMca6d+/OLrvsMq7r2rNnDxs5ciRLTU1lFouFNWjQgN18881s3bp1iuP++9//statWzOr1cqaNm3KZsyYwbxer7TfyB/jjPkGDgBsxowZXH6q/TF+6tQpKTGckpLCnnrqKTZ37twgP0pKStjTTz/NmjZtyqxWK2vcuDG75557pP15eXlsxIgRrF69egyAwt/PPvuMXXLJJcxms7HU1FT28MMPs5KSEml/bf0xztNfpk6dGtQ38vLy2OOPP85atmzJoqKiWPPmzdlDDz3Ezp07p7AtLS1ljz32GEtOTmbR0dFs4MCB7I8//gjy4/fff2cDBgxg0dHRLDk5mT3++OOsrKysWq6ZIIi6A43dFQwfPpw1a9aMRUVFsejoaHbppZeyjz/+OOhcNHbT2M2Y+tjNmG+CoGPHjsxms7FWrVqx999/P+j8NHYTBFEVXChjeHp6uurf1VOnTpWOeeeddxgA9vvvv+v6m5+fz6ZNm8bat2/PoqKimMPhYD169GBvvPGGYgzas2cPGzRoEHM4HCw2NpYNGzZMkZxlzFgifdGiRQwAa9mypa6PjKkn0hlj7OWXX2aNGzdmDoeDDRo0iB08eFDVj6+++opddtllLCoqiiUkJLCrrrqK7dq1S9o/e/Zs1qJFC2axWBT+HjlyhA0bNozFxsZKbfz666+Kc0dSIl0r7zJv3jzpmOr+DskYY1u3bmWXXXYZs9vtrHHjxuyll15ioihW6bUSVYfAmEFhQoIgap2SkhIkJCTgo48+wvDhw2vbHYIgCIIgdKCxmyAIgiAij7vuugtnz57FN998U9uuEARRB9Be2pYgiIhlx44daNGiBW699dbadoUgCIIgCA5o7CYIgiCIyGPr1q34+OOPa9sNgiDqCFSRThAEQRAEQRAEQRAEQRAEQRAhML7UL0EQBEEQBEEQBEEQBEEQBEFcQFAinSAIgiAIgiAIgiAIgiAIgiBCQIl0giAIgiAIgiAIgiAIgiAIgggBJdIJgiAIgiAIgiAIgiAIgiAIIgSW2nYg0hFFESdPnkRsbCwEQahtdwiCIIgLCMYYCgoK0LBhQ5hMNPfNC43dBEEQRG1BY3floLGbIAiCqC2MjN2USNfh5MmTaNKkSW27QRAEQVzAHD9+HI0bN65tN+oMNHYTBEEQtQ2N3cagsZsgCIKobXjGbkqk6xAbGwvAF8y4uLiwziWKIk6fPo0GDRpQdQIHFC9jULz4oVgZg+JljKqMV35+Ppo0aSKNRQQfNHbXHhQvY1C8+KFYGYPiZQwau2sfGrtrD4qXMShe/FCsjEHxMkZtjd2USNfB/1pZXFxclQzopaWliIuLo5uCA4qXMShe/FCsjEHxMkZ1xItecTYGjd21B8XLGBQvfihWxqB4GYPG7tqHxu7ag+JlDIoXPxQrY1C8jFFbYzd9MgRBEARBEARBEARBEARBEAQRAkqkEwRBEARBEARBEARBEARBEEQIKJFOEARBEARBEARBEARBEARBECEgjXSCIAgDiKIIl8tV227UKKIowu12o7S0lLTaODASL6vVCrPZXEOeEQRBXJjQ2E1jtx40dhMEQUQWNHbT2K1HbY3dlEgnCILgxOVy4fDhwxBFsbZdqVEYYxBFEQUFBbRwFgdG45WQkIDU1FSKLUEQRDVAYzeN3TzQ2E0QBBE50NhNYzcPtTV2UyKdIAiCA8YYMjMzYTab0aRJkwtqhpgxBo/HA4vFQgM6B7zxYoyhuLgY2dnZAIC0tLSacpEgCOKCgMZuGrt5obGbIAgiMqCxm8ZuXmpr7KZEOkEQBAcejwfFxcVo2LAhHA5HbbtTo9CAbgwj8YqOjgYAZGdnIzk5mV4VJwiCqEJo7KaxmxcauwmCICIDGrtp7OaltsbuC2dqhyAIIgy8Xi8AwGaz1bInxPmG/wui2+2uZU8IgiDOL2jsJqoLGrsJgiCqBxq7ieqiqsZuSqQTBEEYgGaGiaqG+hRBEET1Qs9ZoqqhPkUQBFG90HOWqGqqqk9RIp0gCIIgCIIgCIIgCIIgCIIgQkCJdIIgCIIgCIIgCIIgCIIgCIIIASXSCYIgzlMEQQj5M23atFr1bdmyZbXWPg+lpaUYM2YMOnbsCIvFgptuuonL7ty5c7j77rsRHx+PhIQE3HvvvSgsLKxeZwmCIIjzAhq7w4PGboIgCKKmobE7POra2G2p9hYIgiCIWiEzM1P6/5IlS/Dss8/iwIED0raYmBhD53O5XLDb7VXmX6Tj9XoRHR2Nf/7zn/j888+57e68806cPHkSa9asgcfjwdixY3H//fdj4cKF1egtQRAEcT5AY3d40NhNEARB1DQ0dodHXRu7qSKdIAjiPCU1NVX6iY+PhyAI0u9FRUW44447kJKSgpiYGPTo0QPff/+9wr5Zs2aYMWMGRo8ejXr16mH8+PEAgLlz56JJkyZwOBy4+eabMXPmTCQkJChsly9fjq5duyIqKgotWrTA9OnT4fF4pPMCwM033wxBEKTfA7n11lvx4IMPSr8//PDDEAQB+/fvB+D7guF0OoP8riqcTif++9//4r777kNqaiqXzR9//IFvv/0Wc+bMwWWXXYY+ffrg7bffxuLFi3Hy5Mlq8ZMgCII4f6CxOzxo7CYIgiBqGhq7w6Oujd2USCcIgrgAKSwsxDXXXIO1a9di165duPrqq3H99dfj2LFjiuNee+01XHLJJdi+fTsmT56MrVu3YsKECZg4cSJ2796NQYMG4YUXXlDYbN68GXfffTcmTpyI33//HXPmzMH8+fOl43bs2AEAmDdvHjIzM6XfA+nXrx82bNgg/b5x40bUr19f2rZjxw643W5cfvnlqvbHjh1DTExMyJ8XX3yxMuHTZNu2bUhISEC3bt2kbQMHDoTJZMJPP/1UpW0RBEEQFxY0dtPYTRAEQdQtaOw+/8ZuknYhCIIIh5kzfT96dO0KfPWVctsNNwA7d+rbPvqo76cK6dSpEzp16iT9PmPGDHz55Zf46quvFLPRV111FR577DF4PB5YLBZMnjwZQ4cOxeOPPw4AaNOmDX744Qd8/fXXks306dPx9NNPY/To0QCAFi1aYMaMGXjyyScxdepUNGjQAACQkJAQcsa5f//+mDhxIk6fPg2LxYLff/8dU6ZMwYYNGzBhwgRs2LABPXr0gMPhULVv2LAhdu/eHTIOSUlJoQNlkFOnTiE5OVmxzWKxICkpCadOnarStgiCIIhKQmM3jd0yaOwmCIKoA9DYTWO3jNocuymRThAEEQ75+UBGhv5xTZoEbzt9ms82P9+4XzoUFhZi2rRpWLlyJTIzM+HxeFBSUhI0M969e3fF7wcOHMDNN9+s2HbppZcqBvQ9e/Zg69atihlzr9eL0tJSFBcXaw7AgXTo0AFJSUnYuHEjbDYbunTpguuuuw7vvvsuAN9Mef/+/TXtLRYLWrVqxdUWQRAEcQFBYzeN3QRBEETdgsZuGrsjBEqkEwRBhENcHNCokf5x5bPBQdt4bOPijPulw+OPP47vvvsOr732Glq1aoXo6GjceuutcLlciuOcTqfhcxcWFmL69OkYNmxY0L6oqCju8wiCgL59+2LDhg2w2+3o378/LrnkEpSVlWHfvn344YcfpBl6NY4dO4b27duHbOOZZ57BM888w+2THqmpqcjOzlZs83g8OHfuHLfeG0EQBFHN0NgdBI3dNHYTBEFENDR2B0Fjd+2M3ZRIJwiCCIdwXv8KfOWsBtm6dSvGjBkjzXIXFhbiyJEjunZt27YN0lYL/L1r1644cOBAyFlpq9UKr9er216/fv0wd+5c2O12vPDCCzCZTOjbty9effVVlJWVoXfv3pq2tfGKWa9evZCbm4udO3fi0ksvBQCsW7cOoijisssuq9K2CIIgiEpCYzeN3TJo7CYIgqgD0NhNY7eM2hy7KZFOEARxAdK6dWt88cUXuP766yEIAqZMmQJRFHXtHnroIfTt2xczZ87E9ddfj3Xr1mHVqlUQBEE65tlnn8V1112Hpk2b4tZbb4XJZMKePXuwb98+PP/88wB8K4ivXbsWvXv3ht1uR2Jiomp7/fv3xyOPPAKbzYY+ffpI2x5//HH06NEj5Mx9Vbxi9vvvv8PlcuHcuXMoKCiQviB07twZALB9+3bcfffdWLt2LRo1aoR27drh6quvxoQJEzB79mx4PB48+OCDGDFiBBo2bBiWLwRBEMSFDY3dfNDYTRAEQUQKNHbzUZfGblO1np0gCIKISGbOnInExERcfvnluP766zFkyBB07dpV1653796YPXs2Zs6ciU6dOuHbb7/FI488onh1bMiQIfj666+xZs0a9OjRAz179sQbb7yB9PR06ZjXX38d3333HZo0aYIuXbpottexY0ckJCSgc+fOiImJAeAb0L1eb0idtqrimmuuQZcuXbBixQps2LABXbp0UfhbXFyMAwcOwO12S9s+/vhjtG3bFgMHDsQ111yDPn364H//+1+1+0oQBEGc39DYzQeN3QRBEESkQGM3H3Vp7BYYY6zaW6nD5OfnIz4+Hnl5eYgLUy9JFEVkZ2cjOTkZJhPNYehB8TIGxYufysSqtLQUhw8fRvPmzQ3pjZ0PMMak1cPlM+B+7rvvPuzfvx+bN2+uBe8iD714BRKqb1XlGHQhQWN37UHxMgbFix8au41BY7cxaOyufWjsrj0oXsagePFDY7cxaOw2Rm2N3STtQhAEQRjitddew6BBg+B0OrFq1SosWLAA//nPf2rbLYIgCIIgNKCxmyAIgiDqFjR2RyaUSCcIgiAMsX37drzyyisoKChAixYt8NZbb2HcuHG17RZBEARBEBrQ2E0QBEEQdQsauyMTSqQTBEEQhli6dGltu0AQBEEQhAFo7CYIgiCIugWN3ZEJCToRBEEQBEEQBEEQBEEQBEEQRAjqVCJ906ZNuP7669GwYUMIgoBly5bp2mzYsAFdu3aF3W5Hq1atMH/+/Gr3kyAIgiAIHzR2EwRBEMT5zUsvvYQePXogNjYWycnJuOmmm3DgwIHadosgCIIgqpw6lUgvKipCp06d8O6773Idf/jwYVx77bW48sorsXv3bjz88MMYN24cVq9eXc2eEgRxvsIYC8ve5RFRWOqGyyMa2ledtnr73V4RRS4v3N7I8itSbfXiFYgo8h1XVzmfx+7MvBL88NcZZOaVVPn+2rKtinP/crzgvLum6vQr0uIVybHWipWeLWOsTo4nNHbXnC2N3eGxceNGPPDAA/jxxx/x3Xffwe12Y/DgwSgqKqpt14LQew5Vpz3Z1o22LzTb2mxbb+wOhd5zPRJta7PtC81Wjaoau+uURvrQoUMxdOhQ7uNnz56N5s2b4/XXXwcAtGvXDlu2bMEbb7yBIUOGVJebBHFekZlXgsNnitC8vhNp8dGG9odjW53nzswrwe7jBehsj0WjRCeXrdVqhSAIOH36NBIS68EtirCazbBZlPORLo8It9erui+32IXs/FIwAAKA5LgoJDhsuvuq05b8qtlrksMYg8vlwunTp2EymWCzqR9X1zlfx+4lO45h0hd7ITLAJAAvDeuI23s0rZL9tWVbtec+eB5eU3X6FRnxqhuxPsht6x+7j588hRKTAxCEiBkTzscxMlL9orG7+vn2228Vv8+fPx/Jycn45Zdf0Ldv31ryKhi951B12pMtxToSbSPRb/nf3Q0aNIAgCEG2Rp7bkWLLY88Yg8fjgcViCbruunjN1W0bKl6Bx1Xl2C2wcMsrawlBEPDll1/ipptu0jymb9++6Nq1K2bNmiVtmzdvHh5++GHk5eWp2pSVlaGsrEz6PT8/H02aNEFuWhriTDoF/F26gC1frvTzxhuBXbuk30VRhEnlPOyRR4BHHqnYUFAA4eKLQ7fnt/3yS6Bbt4oNX38N4f/+T98wJgbs99+V/j75JLB4sb7tNdeAzZ6ttL30UuDUKX1///1vYNSoig0HDkAYNEj12MB4sZ9+AtLSKg743/8gPP+8vr9t2oB9/73S3zvvBDZt0vd33Djg2WeVtk35Bgf24YdA//4VGzZsgHD33Xy2x44pNzz3HIT33tM83isyuD1eiH37IXrpIsU+d/8rgYOHYDEJMJmCHzCiyOARGYqfmoT4iQ9I25d/+wt6jhgK/9MrLsqKKKsJ/qdGiduLwjIPwIA7R76A/jf0QZ9W9eHxijj33gL0fe816VzRNjOsZt9nycDg9jCUur04HZOIG0fPQr+2DdA2JRZekWHoO9PQ7KcNiplHm8UEc7nvHpHB7RHxVft+eOnKe9A+LQ5p8VEQGcMLzwyHtaQIHm/Fo81iFmAqf7B6RQavyPCvIQ9gXatL0SghGolOK1oeO4Apc5+ByHz7/ZhMAvwhK2t3EXIfnYhTDZuBCb5rMQuA01UMZ2mx5mfjx2W24KwjQbGtfnEerF63rm2B3YFCm6PCLyYipfCcrh0AnHXEw2W2Sr9He8qQUFKga8cEAadi6im2xZcWwuEu1bUttdqRExWr2JZcdA5mjlngvKgYlFij4P8UrKIH9Ytyde0A4HRMIryCWbJ1ukoQV6ZfDeUxmXHGmQgAkm1SSR7sHv3PpsgWjQK7U2GbVnBG2m8y+RI3QTAGVr8+HElJSE1N9Q3oAc+IfFFEQmYm8vLyEBcXp+tLpHO+jN2iyJBdWIb3ut+E9y+9Wdoe5yrGmvf+4esHat+uBN8XQQbgvmFTsC+1lbTrqj+344U15VX7IWyLrNEYcJ9y/J20/gPc8MdGXdv1LXtg0pAHFbu+WvAwGhTlSH5p2b/cfyyWte8vbWpx9gQ+WfwvxTVp2d48+g2cciZJm0bu/hb/3LpI1/ZIUiPcOepFyB7nmLXiVVx2bJ+u7ZLOQ/DOFXeAMSbZb3t3tMIvaNg+dv1j2N6sk2Tb89iveGPF61y2fR5cAEEQJNuJWxZixJ7VCls1v39q2gEPX/8EzOXn9jJg4aJn0Pxchq7tW71HYlHnqyXbpIJz+GqB7DtlCNs7RryAv+s1lmyv/W0DJq2fp2t7OiYRN4yeBcA3DgqCgBmr3kb/P3cEByUgXv6xW267es54OFwqlWwBtv6x22/b4dSfmP35jJD9vqzdRch//GFkycZuAIh1FSOmrLJjdy6sXo+ubW2M3aIgIIvGbl1bGrurlz///BOtW7fG3r170aFDB9VjtMbunJycsOMmiqKUhPOP35l5JbjilQ2Qfc2HWQA2PdlftSgnkMy8EvR5eYPiccNrn5lXgj6vbACrRNvh+M1rW9XxOt9jHUnxivRYq8WKx++ioiJkZGSoVhB7GUNWXpnCZwFASrwd5hDJ1Nq0NWKvljOsi9dcU7ZaOVY1HA5HxdgdQH5+PhITE7nG7jpVkW6UU6dOISUlRbEtJSUF+fn5KCkpQXR08IPhpZdewvTp04O2C5mZ6l+mZLhSU3EuO1uxLSkzE7aMij+CzBq2RZmZKJTZCgUFSJHZheJcVhbcMlt7VhYSOWzFmBhkB/gbl5kJB4dtaWYmcgNsG5w8CXNmpq5tflYWSmS2luxs1NdoMzBep7OyIJortjpOnUIch79upxNnA/xNPHkSdg7b4sxMFATYpnJ+NjlZWXDJbG1ZWUjitM0KaNN89AQahLC1lP9s+uUQvvtiJ7o2jkWxS8QPR3Ix8fcjaHNW+7Mxl/+8smIPvsj/DhazgFK3F87T2fix4GzFgQF/v8WW/wCAyevF+1uO4P0tRwAAt+8/idsLz4IHBmDDgdPYcOA0AKDLkZPolnta1y6+tBAA8HtmPn7PzPf5dC4bsWp/jAcQ5XEBADJyS5CRWwLbqVzUz9Np88ctSBv9CyY+vhCl9ihp892/fI3RO7/WbfO35OaYduNTim1vLX8ZrbIP69ou6HodPux2nfS7w1WKFQse1rUDgDdveBK/p7SQfu/7905MXfs/XbsiWxQmlCdK/Dy66WNce2CLru2G5l0xY+D9im2LFk5CclGOru1rV9yJVRf1kX5PP3cSH3z+nK4dAPxr5Es4E5Mo/X7Lr9/j/376TNfucGJDTL1VOWH272/ewsUZv2tYVPBphwGY3es2xba1cyfoO8sYCl59FZ4rrkBubi6A4GeE/ley84+6MHabAaTBl4iTIzIgtYDvuWcLmECL8riQxmFbYAu+/vjSQi7bOJUkXIPCHKRxPKvt7jLF72bRy2UHAAiQSnC4SrhsC+xORRIdAJKK87lsY0qL4BGVxrz+Wjxuha3N4+a29TJA/hdlbFkRl21ScX6FfTn1i3K5bP0JaL+tWRS5/TWLXoVttLuM/3Mtx3/NcSUFXLb+sVtum1x41tDY7bc1e9z6fX/7VnhH78TDF9DY/Q8au3VtaeyuPkRRxMMPP4zevXtrJtEB7bH79OnTKC3Vn/jR8yEvLw+MMSnBsvt4AQKGBXgZsPvPkzA3iVU5i5LdxwuC5ux47XcfL0Bg+aIR28r6zWtb1fE632MdSfGK9FirxYrX77i4OHi93qB2fztVhBnrs4O2TxncDBenBr9tHgm2vPaMMRQUFCAmJkZRYV0Xr7kmbLXipYbJZILJZJLG7kAKCvSLFfyc14n0yjBp0iQ8+uij0u/+mXGWlgamM8thTUtDcnKyYpuQlgbWqJH0u9ZsiSMtDQ65bXS0wi4UiSkpgNw2JYXLVoiJ0fVXC7vatTZsqBsjAIhNSUGs3DYnR7PNwHjVD7zW1FQufy2NGqn7y2EbnZaG6ABb3s8mIcDfszEJKEtJC6oML3F5kVfqliq/Y+wW/FlgRk6RC+eKXdh86AwuPlSCEeUVRmaTAEHw/a0uMqYYwM454vDRz1n46OcsadsdzgTEclT2FNuikVNSUWEVZTIhM6CqSQuvSZlqKrHauWxPy/5w8pMXFctlmxcVE7QtO6YeCjn+GC+1VMxCmgRAtFpxKrZe0JcBABAEQIAABl+sTxW4UeSqqBLLL3Ih71wRRBVjf0UTA3DOWoyMAuWXgeKCMuTnFCmq4P3IP+fs3FKFrbPMjfwc32eqZmsxV/SvzHw3MhwVtll5ZSjILYK/xtATmKkqty+xiUH+nsktQUFukRQPLVtPqTvINvdcIaJL9G1tgglORzQOZvmSLfZ8N3LOFiquS8s2zhGFUkc0DpTbns4r47Its5YiMc4Jt1fEgVO+48/mFnPZMo8YZOu3gwAkx9hV3wQBAFv9+oA8aRzw/GaiCHBMUF7o1PTY7a9IL5BVmgJAq5QYnIlvELJ/+/u/vNIU8D2TTsfXB6DdvwUIKJElAv3kRcVw2SIpKWjf6ZhEhV9a9on14xXbvCYzMmPqcdk2T4nFKdljudgWzWVbnFgPbVNjpPsK8I1xPLa2eono0ChOcV/Kx5VQ93RKcpzC1mWxctu2TY2B1WySbAvsziBbNb/POeIkewA4cKoQZwLGbi3b4vLJFb/tucJzQWOolq1/7PbblvwePHar2crHbv81IylJdewOjJd87Pbb5ibUR2FxcHV4oK187G6bGoMm3gScjq+ve795vCxo7IbIUJBbpGurNna7il1ctmpjt2/8DX2vMjDNsVvvfiu1V37s9pZ5Kj12200mxDijpfvN0NjtjEKpzJbG7rrNAw88gH379mHLltCTN1pjd4MGDaqkIl0QBEUVbGd7LEzCwaAK2M6tGiKZo3K3sz0WwEHFNl77cG0FHAyqGK5K26qO1/kea614hfM5na+xVouV37ay8TLFlODk538F2XZs1US3it4UU4LML/4Kild12/rtMz7/S7Et0F6rgp/HNlS74cQrkmOtFa/KEBUV/DeWFiTtokN+fj7i4+Or5NU8URSRnZ2N5OTksD/kC4G6GC8tXW6vyPDe5r/x72/3gzFf+rJvm/pIctpxPKcIPx/JrTWf1Uh0WOGwmZGRG1wNckXr+oiLtsLrZfj2N6WUjwBgbO9msJoF/G/TYeWrOAIw+Zp2qB9rR0GpB1OW7VPsNwnA2yO7IDkuCjlFLoz/+BdFUtskAAvv6wmTAIz434+Kh6pJAFY81Adp8dE4U1CGq9/cFLR/w+P9AQHo/2rgK2QCtjx9JdLio5GZV4Le/15Xqf0AQtoCPh24Z77YBy9jMAsCXhzWQaH/qrWvOm35zr3XV/knAC+q6NLWnl+RaqsdL6NU5RgUCZxPY/dH245gyvLfpN9fvoX/3tDbH9nPg8r1/7p9TdXpV2TFK7JjXbmxKFLjRWN3pNnS2F0VPPjgg1i+fDk2bdqE5s2bG7KNhLFbj87T1yC3xPdGmVE96CFvbJQKPYza3v3+T9h0yCc9JAjAvw3YPvHpHnz6ywmfLYB/q1yzVrxeW30A76z/U/rdSLw+2nYUU5bvq5QtUHuxHv3+T9ioE2uteD3x2R58+nPoWGvx2poDeGdd7cS6y3NrkFNcuVhfPWsT9p8q0LQNldMZ/cFP2Hiwcv36yc/2YGktxPrjH49i8rIwYj1jDXKKtGMdKl5DZ23CHyFiHYrRH2zHxoO+t+9rMtavrzmAt6sx1lWZMzQyBp3XifSnnnoK33zzDfbu3SttGzVqFM6dOxe0IIoWlEivPSI1XmrJcsYY3t9yGC9884eUKO/SNBE2i4ATOSXIzC0Jej09XOwWExIdNkTbTDh8RlnFJQAY07sZnDYz3l3/V1DCev7YS9E0yYH8UjduenerZvI3sv9ArHt/jAO+/nPkTDGa1XeoLoKqta86bfX2Z+QUYfefJ9G5VUPNxVlrw69ItdWLlxHOtz/Gz6ex+3RBGXq84Ft7o0+revh4XM8g20jto7XV/+vqNVWnX5EYr0iNdThjUXX6FamxprGbxu6ahDGGhx56CF9++SU2bNiA1q1bGz5HTY/dFhPw54vXGjqvPOG4dHxPXNqc781dABg+exu2H/GtkfDvYR0x4lL+5Nu/vtyLT37yrZ81vm9zTLqmPbftgh+OYOpXvsmDwe1T8L+7uwcdoxWvH/46g1FzfwIAtEqOwfeP9uNu90xhGbo/74u1WQD+eqnysV5yf09c1sJArOdsw/bDvli/dHNHjLyMP9aTl+3Fxz+GjrVWvD7cdgTPlk/UDGqXgrmjg2Otxba/zmLk3B8BAC0bOLH2sf7ctvJYmwTgrxev0ZW5kNN1xnc4V+STTlt8f0/0NBDr2+dsw08hYh0qpzNl2T589ONRAMD9VzTHM9fy92v5pNjAdil4r4ZifbawDN3KYy0A+PslY7HuNuM7nA0R61DxGvG/bfjxb3+sO2DkZenc7T67fB8+3OaL9X1XNMe/KhnrARcl4/0xPbhtf/z7LEb8r3KxPlfkQtcZ3wHQjnVtJdLrlLRLYWEh/vyzYjbj8OHD2L17N5KSktC0aVNMmjQJGRkZ+PDDDwEAEyZMwDvvvIMnn3wS99xzD9atW4elS5di5cqVtXUJRB1n4U++WTFRSpYnQGTAn9kFKCyreBWWAdh5TF9PUgsBwB0905Ge5IAgQErQ+zEJwIYnKhbxCJUcbpLkCEru9m3TQDrXS8M6Bu33n/f2Hk3Rt00DzT88Qu0Px7Y6z317j6bo06qe5h9L1ekXAKTFR2u+yhRqX3Xa8pzb3CRW8zW72vQrUm1DxetC43wdu0tcFc/8JKdd9ZhI7qO10f/r8jVVp1+RFq9IjnVlx6Lq9itSY01jtzFbGrsrzwMPPICFCxdi+fLliI2NxalTvrdW4+PjVdc2qS3kY7dHBFweETYLf/KlWGbvtBtLpRS7ZfKZVq2V09SR+202mCyS+2y0rksRr4D1TozYelnNxlredpSt8vGq0VjL+kfgGi+6trJ2RQa4vCLsFv4+VuyqaDvGaKzdVRRrc+VtjUZbHmu3wWrHwM+4zCMaup/l9oZjLbO1G3yGVFW/NorcZ+OxrvicKhPr6qROJdJ//vlnXHnlldLvfk210aNHY/78+cjMzMSxY8ek/c2bN8fKlSvxyCOP4M0330Tjxo3x3nvvYciQITXuO1F38FecN4yPRk6xC7+dzMdvJ/Ox+1iO9CoN4E+W5+qeLz7aipQ4u6T37MckAJ+MuwztG8Zj1d5M/OtL7Urm2CiLZrIbCJ0cDjehHcl/INbFP8YJ4kLjfB27i2Rf7pz2yPhSRxAEQRC1wX//+18AQP/+/RXb582bhzFjxtS8QxrIx27Al+ThTe56vCLKPBXJZKPJpWJZ0VWgH3rIjzfcrsLWaLte1f/z2SrbKnZ5YJOtcxGKcGMtb7uorPKfk/HPOIxYy/uHQZ+DYl3m5U6ke0WGUndFrIvKjPodRqzlfdNou64w4qX4jI21G9gnil1e7uSuV2SKiQfDsQ7jfqy650A4z66ai3V1U6cS6f3790coJZr58+er2uzatasavSLqGlrSLEfOFuOddYfw+c4Mw+dMjYvCqXylnrhJAFY/3BetU3yrTqvJfvRq6VscbsSlTdGvbeWT3UD1VbURBEGEw/k6dsu/DDpsderrFEEQBEFUKXVFLTYwkVPk8iDeYdU4OsDWrUzqGE+CyZOGRpNgYSTfwkjQKhLDYbQL+JJxCQ6NgwPbDYy10QRcGIlSZRK+jiQ6g2LtQaKTb9IisC3jEzXhxDqMeIUxaVEcxkRLYF8sKvMgiTPWJe7gxLARqup+DOs5EM4EouEJj8rHurqhv/yIC4olO45h0hd7fdIsAnD9JWnwiAzbD+fgTGGZ4fOZBOD7R/uhRYMY1US5P4kOVG/lN0EQBFGzyL8MOmyRUR1BEARBEIQ2gYkcIwm4wOR3jVakh5PIqqJK1GK3F4wxbj3ooAStgcRfUKzDSHYar5IOoyI9nArrgEp4UWQwmSoZawN+Bx4bTt8ML0Fbg29LyPwscRuMdRjPgcA+Yby6OwIq0sOYQDQca5WK9EiBEunEBcPvJ/Pw9Od7JQUtxoCv9mTq2o3ulY7rOjVEu7Q4rPz1ZFCyvEWDGADh62MTBEEQdQf5lzmqSCcIgiCIyCecxEw4yUrGmKLKuqQGq37DSQyXyDWKGVDqFhHNWTxQtbHmv2bGmCK+gVXA+m3XUqwD/Cz1eLm/X4YX6/CSlXK/w4t15fum0fsp0M8St5dbhz+cvhl2rOX9upaeA+E8uwCjsa78xGd1Q3/5EeclmXklOHy6CCID9pzIxdo/skLqmcfYLejQKA4//X1OsVSFWRAwoX9LKfkdblU5QRAEcX4g/zJHGukEQRAEEfkESbsYqKANJ6lT5hHhlS0gaViqpMoqUY1WdgdXK/Mn0itffRtOwtHlFRWLdRqtoFXIfoRR6WxcniW4b/In0itf/R/YrhFbl0dULCAZTqyNv3VQNW94+O0rn9zl9ztYy95YrF2yBX+NPwdqSYJH5TlQ+UkLqkgniGqBMYbXvzuId9f9ybV2syAA88b0wBWtG8BsElTlWShZThAEQQQi/yJJFekEQRAEEfkEJoGMJJTUEp28BCXfwlmUMaxFLI1qjQcvYokY4+1KtpyoJTp5CVeCJ7yFKCufhFefqLFz2arp0Ve2XWO24SU6w0mGh5OEV70fYzUODkBNI72y7RqJdWAluHHpoCpaFDZM/X5DsQ7s1wavuTqhv/yI84Ls/FJ8uSsDi3ccw+EzxarHtEmJQVp8NDYfOg2RQUqU92+bLB3DI89CEARBEPIvsKSRThAEQRCRT7BGcc1UpIeTGPbZy5K7YSTB/JXxZk6NYrWK9Mq0a9w2jCR8GIlOX9tVUyXt8ojweEVYzCY+27AmaiovNxJUJW3INrxEZziLWMrj4/KKcHtFWCsb6xqaqAmq/g/jc6rRinTZNbu9DC6PCJuFL9bhPQeoIp0gqpTMvBIcOFWAEzklWPtHFjYe9CXHtXjz9s64sUsjyZZ0zAmCIIhwUGqkUyKdIAiCICKdIL3eGpIbCdRkNmIrikxhb3wBzOAJgNgoK5dtUBVsGBMPRrSVw4q1iiYzL+HGOrA/Fbu9iONM7hYH6XbXUN8My1bpo5FYB64bYDS5q+Z3fHQlY11LfbOm7ifGWFgST0H3lMtrIJFeO7GubiiRTtQ5Zm/8Cy+v2s8l3QL4Ks8vbZEk/U6JcoIgCCJclBrp9HWKIAiCICKdcDTSw6rcDapErXwSPhx9df/vvIn0cK45HBmL2qqSLvV4wWRJhnDeHAB81ctxnLEOelsiDOkgI9ccrJFupMI6jFi7RUWsjVf/B/eR+OhKxrqGFsINkpYK460DI32zzCMqik6NS/AEtx3v4Ix1LT0Hqhv6y4+oMxzKKsDM7w5i1b5TQftS46JwW/fGuKVrY/x0+KyuzjlBEARBhIP8i2C0lSrSCYIgCCLSCUcjvdYSnSryBowxCAKvPEsYms5BidIwZCwMtRtGojOMSYugRLjBWIeT7KxK/f5wKp2N+RxGrFViZSzWYfTNMPTGg++nmkmGV/WaA+HEOqy+WUPPn+qGEulExJKZV4LdxwtgPSPi050n8d3vWZrHzhzeCZe3qg8AaFbfSTrnBEEQRLUi/yJIFekEQRAEEfmEk6CttURnQPLIKzKUeUREcU7ih6XpXGsV6eEkOqtO191orKu04jiciZoaSoYHJTrD0BoXGYzFOgy98eCEduWv2dhzIBxpl6pbc4Ax3xsB0ZzSlFW50DJVpBNENbJ4+zFM+nKv4nUfLcyCgOYNnIptJN9CEARBVCfyL4ZO0kgnCIIgiIgnHL3esLSkw9BIVzu2xOXlSji6vSJcXrHSbYen6Rygn20gCVa17dZMrD1eES5PYKzD0Dk3oDcezjUHx9qAz+FojatowBdzxto/wRFoy912ba2VUIUTU+H262KXhyuRHn6sa+c5UN3wKcQTRA2y+dBpPP1FcBK9QYwdk69th+k3XAxz+WsoJN1CEARB1AaKxUapIp0gCIIgIp6qlFgxVFkZRhWr2rG81ahqiafwqpUjXyM9HMmPsGKtkvgOp7rbkARGODIn4VRJh1GprHYs7/2o9jkZk2mqur4ZnnxPDcnCqMaLr+2wY12Fb6YYXbOgOqG//IiIIbfYhZnfHcRH246q7p85vBOuaNMAADD44hSSbiEIgiBqDfmXOdJIJwiCIIjIpyplLIwlOoPbFUUGk0lfo1gt8RRWEsxIYrkqNdJrKtEZ0G6J20CsVa6PO9ZqieEwkp3hXHNYMidhyOiUuL3wigxmjlirJ2h5+7VaEj6MiZowJi3Ck++pvCxMqVvkj3UYfVN9Mq521kowuiBtdUKJdKLW8YoMi7Yfw2trDiC32K16jFkQ0ColRvqdpFsIgiCI2sT/ZS7KauL6EksQBEEQRO0Slr5xOEl4lWNLPV44bPrpGDUphLASjpzXzBgLlu4wJDcSRvVtGJIhaseWuL1c69moJ2jDqZLm85sxVmtyI+HJHQX7WOL2IqaSsea9H9U+E16/GWNhSgeFI8FTdfJQ/m08sQ6vIl1N7siAPEuA34b06KkinSCCycwrwTd7M7Fo+3H8mV0obXfYzLiidX1893sWRAaYBZB8C0EQBBFR+LUdnRx/BBMEQRAEUfsE6jIbSeqEoyWtlgAqKuNLpKtWSfMmd1VseROOZR5fxavSlxqq3A1aFLbyVdJ+e75EeuUTtKqJYc54ubwqsQ4nuVtDC2+qvy3h4Uyk184EkcsrwhNWrCtfYR2OjI7avVdcxhdrtT7Mez+qtctb/e/yiHB7lbGuqfUOqhv664+oFeZtPYzpK34P2n5T54Z4emg7pMZHISOnCLv/PInOrRqiUaJT5SwEQRAEUTv4v4A67CTrQhAEQRB1gaqsSDeUfFOVDPEAsOvbqup2cybBqlhfvbY0ncORz5DsY3narbyMhWrCMQxZmHCkg8LTSK+89IZvG2esw9JIr1oJHkPPgTBkh4Ilnio/MWWk7ap/DtSMln2wRjol0okLmNX7MlWT6LPv7IqrO6RJv6fFR8PcJBbJVIlOEARBRBj+L6AOK32VIgiCIIi6QHgJWuWxLo8Ij1eExWwy3C7An+zUqvrlIRyNdPVK1Jqpvg2KtVeE2yvCyhPrcPSg1RLDNZBwVE901lAyPOBYt5fB5RFhs/D063C0tytfka5+P4UR6zAmasJJDBuKdRj3YziTB+H0TdX+EcabKUZiXd3of2IEUUV4RYZ31h3CPz7Zqbo/PtpWwx4RBEEQhHG8IkOpWwRAFekEQRAEUReQj91+wpZW4NRHVtftroHq2zASnVqazDyIIgs6NtzqW95rVotrOPIsvIm/qv6ceH1Wj3V4+v28batKhoQjhRNWVXn134vhxlp9vQPO50AY92M4Gumq8eK2rfz1qq3RYCQJX91QGRVRI2Tll+Lhxbux7e+zqvvNgoBm9R017BVBEARBGEf+xZU00gmCIAgi8lFLOhmRG9HSGY6LsurahlOZqVYlHU4lKm8SLJwKWLVYh6ORDvgScPHRHLFWrUjnTe5WPvGnmqwMIwkfzoRHuIn0IpcH8Q6efl21Ouc1IRkSzr1Y6vGCKSW/w9JIB3xxSOBIg4XzHKh6jXTeRWEr3zdL3WJQrI0sclrd0F9/RLWSmVeCL3aewNxNh5Fb4gYAmATgyouSsX5/dvliogItJkoQBEHUGeRfZh02qkgnCIIgiEhHPTnrBWMMgiDo2oclYxGGZIi6tEs42sjVXzGspckcVqy5k9LqizLyEE6sVROd4fQPbumfcGMdRpV0GNru4SxiGY5eeFj3otr1ur0QRQaTST/WVT0BEO79yENVPwfCmpgyEOvqhhLpRLXx8Y9HMWXZPsgnklLjojBrRGf0bFEPmXklOHKmGM3qOyiJThAEQdQZ5F9mKZFOEARBEJGPWiLKKzKUeUREWfXH8rD0xqs4MRxWEiycRGcYCVaRIbxYh5HsDCfJynvN4SU6w5mkCbZlzFfRG83xHVXNnl+/v6onasKp/q/+inQ1/xjzVao7ON5QrfLnQFga6TWQhA+jb2n2a85YVze17wFxXnIwqwCTl+0L2j5vbA+0S4sD4FtMlBLoBEEQRF1D/mXWYaevUgRBEAQR6Wgl6UpcXt3krssjwu1lQdt5E3+qWsGc+sbhaFiHk4RX1UgPI/nm8yecWPNqpKv5Hc7EQzh64ZWXKglH191/Tr1EutsrwuUVg7aHo58dnjxL9Wukq8Y6jHvRv10vuevxinB5gmMdzqRYeBrpYcjC8MZaVXaIVxNe+xkSCYl0WmyUqHKy80tx7/wdqvtyi9017A1BEARBVC3yL5BOqkgnCIIgiIhHK/nDk8jSSmqGU3HMW0GrXonKq28cjkZ65atJtdrgqaDVjnU4lfS1I2dTE4vCasWFp+1QSXgeau+aw0mkq/XrMGPNcV9oTZxxT5iEU90dlkZ6GMlwDTmtyrbrOye//n91Qol0oko5cqYIt8z+AcdzSoL20YKiBEEQxPlAkUIjvfarIgiCIAiCCI1WsownsaOV4AtHA5s3uRtWIiss6Q31yl2vGFwtzttGWLEOK2kYTmI4HBmLyif/S91iWLHm6Zta18YvhVO10kH8i7OGIcGj0m6ZR4RHpTI/2DaMWGvaVn9VeVVP1IQjacUba+2+GRkLjlIinagy9mXk4dbZP+D4OV8SPdFhhX8dAFpQlCAIgjhfkH8hJY10giAIgoh8NCvSORJ/4VSiMsbUJQ7CqUivgUp4raQhj5yEVhvhJHd5koaMsfB0u8PQV6/q6mzfdp4EbeUnHrSrfmsg1mEkd9X7dZix5unXYfRNTbkjzlirV9LzTsaFURlexYssA3yx1uyblEgnzie2/XUWI/73I84UugAAbVNi8e3DfbH16auw6L6e2PL0lbi9R9Na9pIgCIIgwkeRSCeNdIIgCIKIeORjd3y0Vfo/j7SCPKkjt+VJ6pS6RTCmYmtQl1nps3F9Y789d6JTplFs9JqLwoi11ufEk/gr82jE2uA1x0VVfLfjnXhQi3VlZGGqKl48tmo+B55TizKPCFE11saqpOWx5pc5CY5XZaqza7JvasWa5350eSveTlD4rKEjHoharPl18NVibVwjXREvjgmAEs3nD0m7EOcBmXklePP7g7j7/Z9QWP5A656eiKXjeyElLgpp8dHo1bIeVaITBEEQ5w3yL+ukkU4QBEEQkY987K4fY5P+z5PIkidvjNoWabTLX5FekUi3mn2ve1emEtXfdmU0mZV+8yQNNWLNcc1FWu1yTXhoxNqgPEu8wwqb2cTdLqD+OVdmQUfjfVOrXxurkjYaL617wuiin3HRVtgspnJ/jFeVV8TaC8b0pXA048XTN7U+J67qf/V2eSbFtO5Fo3JHsVFW2P2xrsSbKYZjHcb9qPUc4L3m6oYS6USlWbLjGC5/aR3e+P4Q3OUzZFddlIyP7r0M8Q6rjjVBEARB1E3kX+JII50gCIIgIh/52N0g1i79ny9pWHGMYVuNdvk10n1tOGxm6TuH0epbs0lAosOXjHJ5Rbg8HHrQGtfMl6DVirWxxLCiXS4JHo1Yc2s6+9pw2ixw2M1B/vC0bRKAJKcv1m4v44u1Vh8xmNytqn7NNUFUpvU5GdP+d9osUlGKUe1/QQDqOX1te0QGl0Gdc8N9U+OajU48GI51GM8f+XFOuxlOu/8ZYmzCQx5rr8hQxvUMqfrnAEm7EHWazLwSPP35XsjnoQQA025oj2iqziMIgiDOY+Rf4kgjnSAIgiAiH2ViJkr6P1c1qSIhZNRWvV2ehJA8YeW0VyQcjep2O2wVCTSAU8aiTP2ajSccZfEynIQ31m64sS51+2LtsJnhLJ+0MDrh4bRZFLE2ntCuolgb1EhXtGt40sJYrEWRSVr7DnvFBBH/hIcsCW+v+B7O87aE9nOg8n3TeDK8amLNEy9RrNBXd9gs0t8tvAlp/7U5rGbEGJSGCSvWGn2T936sbiiRTlSKZbsyEPgyBwOQkVNaG+4QBEEQRI0h//Io/wJPEARBEERkoi1FYWxBR6UsgzFZmHpOYxIYgRP3/oI1XnmWEimBZlZM/HMt+unWipexiQej8dKShTFa9Ws01vJFVB02ixRroxrp0QGxDide4UisGNVIN/oZy32Tx5on0amMdUW8eLX//Z9JtOwtDYB3wVCNa+aw1eqbXPIsYcn3VByT5LBCEMq38/isEWt+jXR/v7YoCmarW/6nROP5w9tHqhtKpBOG2ZeRh7fWHgrabhYENKvvqAWPCIIgCKLmUP5hS9IuBEEQBBHpKLWRjcoMyJM6xmRO5O3G2C2ItvoTtMbalVeVF7k8XBrF8ippRcLRYKWzIl4GK2gV8TJYJa2MtbEqekWsDU6W+CrSy23dfHrQUpW0PTDW+m2XhNE3i8Lom0VVdE847caS4UUB36MdfrkRtxeiyKG97fZXpAdMWnD1Ta1+HUasee5ljfuJ7+0Q2dpMdgscVv5JHuUzxCKTh+KLtSR3ZDcr1oXie4aox8v4egfGpYOqG0qkE4bIyC3BPfN3oMSt1EQyCwJeHNaBFhUlCIIgznuUGulUkU4QBEEQkY6mDnVYGunGEsMOu1l6k40r0SlPoMlkGRiDJEOiBWMySQdZuz6/+WUsbBYT4qKtQdtDEZamvJYtl/SGLEErj7XBJKk8Gc4Ta7nf8iQ8d9vlx9jMJsTLY20wMWxch7ry90RRWUAy3IA8izzB6pTFizGg1MNv7wiQ0eHTdvcdYzULSHDI+7WxyRaj/VpLL9yo3JHTLpt4MHgvOgOeAyU8FfyyWMsniPikcHzHVCrWYWj/1wRURkVwk1fixth525FdUAYA6No0ATOHd0ZmXima1XdQEp0gCIK4IKCKdIIgCIKoW2gnaI1qpBtdADMwGW4B4DKc6HTYK3S7fT55Qq5N5vKK8JRXnAYnwfgTcE5bYCWqUX3jqlmo1GgCXxlro4lhZcJRN9YeEW4vq2jXrvyceP0OnvAwqnNucKFSrcSwwbclnOXxOlPIm1SWT3hY4JC1V1TmDfnd2uURpUVF5ZXwPr8NxNpmUdxPfBM1VdM3jcc6+G2J0+Cd8AisSJfF2uVRTEQE4vbKYm0z3jfl2uyGY621mG2EaKTTX38EFy6PiAkf/YKDWYUAgGb1HHhvdA8kOW1oVt9Zy94RBEEQRM1BGukEQRAEUbdQVDgalbGQJXUSHTaYBEBknBWdsvNHKzSKjcsyyJO5epIQJQrbQN1u/rblCxQG+qRtK0uCGYy13O+EaCvMJgFekRnWo482qAcdqCUdrUj8eYEYPp+jbWZJeiNwnxbyBR2jrcYkeErc6rE2Gi95rIvdleibVv6FcBV906rsm0b6dXSl+qa/X5uVmt9cGunqzxCjsY6PtsJiEuARmeHqbHnfrMw6C0ZiHXw/VW6x0cBYG9XRNxrrmoCkXQhdGGN46vNfse3vswCAJKcN88deiiTZohIEQRAEcaHg/wIoCECUhRLpBEEQBBHpyMfuRGflF3T0VWj7ZSwqU5Hu+95Q6hbh1dEoLgqqROWvdFbIQVQm4VhWkQRzGKwmVSyOKI81l8xJgB60jV8KRykZUmFb5hHh8YaWZwmUKlFU4eskluW+Oe3mgIp0/gStw24xLsFTph5ro5JF8lgbrpK2V+j3u3hirXjTwhJU/R+yXbf8flL2TSNJ6cD7ie/NlIrzK2LNc09o9E2uiRaNvul7EyJ0rAOfXUbeTNF6dgXu07QvU4+10WuuF2Ms1jUBJdKJkGTmleDRpbvx5a4MAIDdYsJ7o7tTFTpBEARxweL/IzLaaobJJNSyNwRBEARB6CElhq1mxBhMdBYHJP4cdv5K52CNdP6FKIOSb/KEo14SLEiqhL9dxphUoRuc6DRWiRoTVblEp+S3v/rWYKIzKNY6FcfBi2dWLuEYlITXSfwxVlGVbDTRKW872mpGbJSxiuEijVgblQwJSrLqxbpMOxmu1zcDpUqMyI0oYm0PuJ8MJIYrF2v1+9HoPRE4UaPXtnLCw2JIpino2WWgb4Yd6/LrirKaEBtlDdpe25C0C6HJkh3H8PTneyGfJ39zRBd0bZpYaz4RBEEQRG0jf92ZIAiCIIjIp1hW9auUNzCm6VxRkV5mWDIkMOFY4vIqkkTBPgckhg1UdSqTb8p29ZJgpW4RjPl9Ni7pUCRfoNCgzElQFaw0aaH/OZWEqMIvcXkRFzLWgQlaj2yfzoRHYNWvgUSnPNaBieESAxIrgcl/ozI6ylhzfE7ugMRwQHU3d6ztFjjLPKr71G0Dqv8NXHOZRx5r41XS/msObtdg3zRc/R/QNwP6tXyB2kCUEx5mFBvom1r9w2cb+prLPCJEjVgbuWanTDYI4EvC1wRUkU6okplXgqe/UCbRBQHo1CS+1nwiCIIgiEhAWoCL9NEJgiAIok4gr5K2mk2wmX2pEK6qX9kx0TK938osYqmUouBPhgfrDPPLjQTrG/PbVk5fvSLWFrMJNkt5rA1WSQfqnDNmTApHWd2tlwxX2kYbmHgoUvQP5eSB4VhbjVakl1dJ28wwmwTY/bE2uKCj0VgXBy1iaUCeRX7NVqUevbFYG1tsNFAiRekz/3MgMNaVqUh3yKr/dWMdqm8aiHWwpnw4zwEjzy5j/UPumz/WUVZfrEkjnYhoDpwqQOD9zBhw5Exx7ThEEARBEBGCtCgUVaQTBEEQRJ0gcOw2Uunsr0S1mATYzCaputLtZXB5+DWKA5NReslOZSLLmCxDcUAlqtNIEiwoSVq55K7/Wp02A7EuP8afqPS37REZXHp60GXasda75iDJEHm1sk5luLKK3hwgY8Ff9euwG6v69fntl4Xx+euXDDGy8GZgrL0iQ5lOvw6U0ZH7rZfsVOj3282GdOFLFBrpAX3T4MSUkSS87/zqsTYiVWISUB5rX9sig36sQ/RNveru4PUdDMhDuQInHgys0RA0gWhwAd6yiop0+b9UkU5ENN/uOxW0zSwIaFbfUQveEARBEERk4PaK0h/N8i+FBEEQBEFEJvKx2ykld/2JGf5KVIfNDEEQDCU7AxfPdBrRNw7SSDdQuRuYBDPQbuDimUYSnR6vKCUG/dcqVd8aqP73x1qpN27Eb2WsjVSk+6Q7DFSkB0qVGFicVV02iK9decLb76/DwKSFv23VWBvsm0q/9SZ5QiVojUx4GOubylgH9A8dW6/IUOrWiLWBRXSdNosv1pXUOXfaAydq9K45YKKmknr0TrsxeRZlAt9YrEWRSZJY/muVJj45Yl0TUCKdCGLrn2eweMdxxTazIODFYR2QFh9dS14RBEEQRO0TWM1CEARBEERkIx+7owOSYFzVkbJF8wAoE0p6Fcdu5fcGI9IKSi1pY5rOJYFVvwYq4QNlGaIsZghC8D5VW3fw9yR/spNHj16ujQxAOQFgYMHQoFgbsg2c8NCpkg5MhhtYADOw2jjKaqqIta7PyokDX/v8FekloWKt1zfdyr5pRKs8cPFMpea3kQmPwMSwgc/YbobdYoJJ8LfLfx+HE2spMRzG/WhorYSyyvfNkoB2HQZsA9d3kMfayDMzUivS6Z1kQkFesRuPLd0j/T5xQGv0bFEPzeo7KIlOEARBXPAELrxDEARBEERkozZ2+xNZfo1iwZ+9VEGuQy3/17ev8rrMhpJRgbIwBipRo20Wpc8GErQOmxkmk4BoqxnFLi9HUjk4ke7XwC52eyGKDCaTdqzlVdIAlHrjBhOOSukOY9ccbeBzCtTtjjYy0RIQL0EQ4LCaUeTyGrpe/4KMFfr9HLEuCxFrAwlah9WgjI7CbwuibRXn0pcbCWNiqkwl1jYLCss8+rIwcj35gFiXuL3wigzmkP06QFpKPnlg8H40pEfv1u6butX/YayVEPg5yWNt5I2YwGduqVvUjXVNQBXphARjDP9athen8ksBAL1b1cPEAa3Rq2U9SqITBEEQBII1IQmCIAiCiGzUxm5/QosxSJINajDGgqqkjekM+/bbLSaYTYKhBTCLAiYADCXhAytRjciNBFRJy//VXwxSKZ/hbx8oj7VH214ea//npJSE4GtbNdZGZCwCdaiNSG8EaNkbWRS2QsaCr9I5UDbI9y9fglY31px902YxwWI2GZIbCZQqMVL9H6o626jcke9fv2SIgXvRYKx9fgdMWhh5DpRfl81sgtVsUtjqThCVafdNYxNTxhZKDpxA9J+Dq92A9R38vvvRi3VNQIl0QmL57pP4+tdMAEBclAWv3dYp5AwmQRAEQVxoBFazEARBEAQR2QTqOQPKJFioxF+Zx1cBCciSYAb0foNkYYzIIwQs2FeZRKfP1mJoAczARKf8X6NyNP72K/zWblsZ6+DKXd7En2qsDWikO4I00o3oUJuNJTpd2hMP+gnp4O+kvJMHLq8IT6hYc/YRtUSn0YkaZYW1kYmawDcHjC0KC8gXDDWSGA6OdahrdnlEuL2svN1KPAf8SfiAe9Hnd+X7pqFY2wPf8ODvm4ZjrbgXjT8HagJKpBMAgIzcEkxZvk/6/cVhHakKnSAIgiACCFyoiCAIgiCIyCZQogCAQuIglM6warJSJoHBq1UutWutpKZzQMJRv13lNdvMJkkOwUgyXJKxsJqD9qkRqhJVz+8SleSbseSuV+GrItEZjr66QS1pm8UEiz/Wbv6kcnRA3zSmNV75WDsCEp1G2vbHONpAMrzEreybDs57MdCvaJsZNosJVrMQtE/P1p+g9fcVIxrpUrw4+0iJK/gzNlKRLsU64F7Ua9e3X1taSl+PXnnNVrMJNrOJs121t1r4JuMUfdNq/M2UmoAS6QREkeGxpbtRUOrr0Dd3aYTrLmlYy14RBEEQROQR+McSQRAEQRCRjdrYzSu/UaxWHWlIbkSZSFdWovJV0AoCEGU1wZBUScCCjj6NYr5kuOoiluX/lnlEeLzaUjihFhvV81tdeoP/mqUqaZUFHfUqw/3xEgQgymJMbiSwSlretl67avr9/nP4Kpm1Y63QklaZPAhV/R8oGyQ/B8CjN66UKjGyAKZi8sBqdCHc4L7p4J14UHmr1N9XXF4RLk+IWKtMEEVz9k1FEY5K39SXhfFL8CjvRd8+Y5NilX0zRbofud9MUZPT8v3r9rLQsVab8DDw5kFNQIl0AjO/O4Af/z4HAGiUEI3pN15cyx4RBEEQRGSi9mWYIAiCIIjIRT2RxZdwVJUo4JQZ8IpMSpKpJoY5k7tOm8WXCK+EHIS8TX+yUzeprJJwVCSlQyT+1GR0FJXhISctQifhQ12zKMo0vyuThPcnhq2+xVUrUwkPBCc7w9FI12tbEWu7St8MFWsVqRLFhEeIPiKKTOoDFZNLxjXS/QvZ8l6v79zaleH6EjzBb5XyVsMXu/RiHcpW+170+R1ay16Sh1K5F3XXaCireEvDbBICtP+NyEMpJ0x4JxDlNtyxVpmY4o11TUGJ9AucWd8dxDvr/5J+v/aSNMRFWWvRI4IgCIKIXIpVXsElCIIgCCJyKVZZPJO3MlxVqoSzIl1eaRqoNa7Xrs/vgAUKrfIEmrHFM31+82pvq1Skc+p+qyWGeRdnVVs8k1cCQzfWnIvCOgy2CwQmaI1VpBeHqEj37TdYwc/ZN9UWz+Sd8Cj1eMGY32c1jXTetzSCK+F5JzzkbfIuzqo3UROyqlzvORCijyjvRf9kCd9nXOoWpVhXPLuMJMOVb2koYm1kodIA6SBDaw4YfjMleGLKyP1YE1Ai/QLmZG4xZq09pNj2/ubDyMwrqSWPCIIgCCKyIY10giAIgqhbqGuk81aT6mmkc8rC+JNvRjTSpWp2X3sWswl2C59Gsbouc4W0C/Nn51T9DtZId4RR6Rxt47tmNd1uXs1vpc8qyX9d+QzlpIXZJHDHOlC323cei9RuqFirLWLJ2zdLVKqkeTWw5Z9htEqi0/A9wSmVBED2lkZFrKOspnKf+SvSg/u1R6dfByeGedcs0NNI5+6bKusGhH4jRqV/GNJIL69IL7c1mQRuXfhQn7Nev1bXSOebAFCs72A11jdrCkqkX8As3XEiaJuXMRw5U1wL3hAEQRBE5KP2pZIgCIIgiMhFtRK1EnIjTlUZCz7pDSkRZagiXVm5Kz+PvgSG79xWswBbeULYfx6vyOAKpXOuc80hk6zu4AQad/W/auKOr8JamSRVSUjrVpUHx9rJXensO7fFJEiLMfr994oMZSH0oFUX/axE9X/F5AFnglalSlqeVA65boDKGx5GFsItCnjTwucDnxSO/9zyiQ7/eUSGkLFWe6uU/82U0NfM3TdV+nWoBWlDyQYF7g/VtlPRr3nfTPGd2yRAFmvfeRjzVctroSpZxDlBFLi+A8A/GVdTUCL9AqXM48WnvxwP2m4WBDSr76gFjwiCIAgi8lGrZiEIgiAIInJRX6Cw8hWhykSnMekNXm1kl0eUkt3yZF/Fwop8STBFYphz8U21xTOdnNIKehrpvAlH4xI8Kgl8To10t2yhSXmM5JXOoaiY8PAt6urzmy/xV6TWNzklMNQ00nmrflX7JqcUjtqaA047X6w9XlFKdsttpEUsddcNqEjCS7Hm7Jt6Gum8zwHjsVZJhldiskRdIz30Gg3+ZLfDpvYM4Yu1f40GgF+eRfc5EHKSR+25yT8BWRNQIv0C5aNtR5GRW6rYZhYEvDisA9Lio2vJK4IgCIKIbIpUqlkIgiAIgohc1BbP5NUZVtMad/JWpKssVBplNaE8J6UjbxCcGJa3rbtQaZlygUIgUD/bWBWsg7MiVE8jPeTEg05imDvRqRprTqkSu3ziwaLbLiDXoQ5+c8Bnb3CB1SpKhnP3TbVYG5QssltMMPHEWkUiBeCvSPcnaOUx4l6cVfE5qy1iaXCihnNxVrXFM3knS9TatVtMMJcHm3eRU7W+qac1Lk0QqUzkyfer+q33HOCceDD6HKgpqJTqAiSnyIW3yrXRBQGYN6YH7BYzmtV3UBKdIAiCIEKg0KMkjXSCIAiCiHjUktL8GunBWtJymQFebWR/sk8QBDisZhS5vDoJx+BKeLn/JW4vRJHB5M9eBuD3S36dDk5tZcU1q2qkG5OzqUysVSVDeCUwym0EQYDTZkFhmYdfm10WI7/ferEO1KEO9puv+l/tmo1qpPNKYKjpdssTw9z9WhZrR3msQy4KqyGR6I9dqVuEV2RSojgQeUW6dB7ufh38OXPr0avcjw7Fc4CvbwbqugOhE9Jq8fI/QwrKPNyyVHJddf95yjyhY60mC6PwO8T9qHZP8S6Eq7regaJvUkU6UQu8te4Q8kt9nW9Yl8bo3zYZvVrWoyQ6QRAEQeigtmAZQRAEQRCRi9rY7axEwtGpUlkZWt5AIxnOob2tVokaeB6tBC1jTLVKmlduxL8vylpR+cotNyLzqaKC37gevdrnxC3BI2vPn7jkluCRXacieRci1n6/lQlHTimcclt5lTF/1a88WakigRFSgkelStrKl+jU65uhkvBK2aDg6n8gdKz951ZUSXNXd/v22SwmWMq17MN5M6VyGukqb3iEmmjR6JuSFA73s0vrOaB+zfJ+rZwg4rsf/fGQx7oyC+GqLaIbKtY1BSXSLzAOnynCR9uOAvANjE8MaVvLHhEEQRBE3YEWGyUIgiCIuoXq4pmc0htq8hmVSXTKE5z+//PKZ6hppIeyL/OIEJn/ePUqaZ7EslaikzdB61Cpvg2ZoFWJtbJimDfRqRZrvip6zWR4iFh7y4OtkCrhXZzVn4RXJDorMVGjKs/CmYRXi3XI5L963/RfA2+1sVIyRL9tl1eER4q1Vt/kiLXGPcE/UROORrpaRTpnrFWuOeSzS2sij6MKXx5rtYVKA33T8rsysVZf2JUv1jUFJdIvMP696g/phri/b0ukxkfVskcEQRAEUXdQVNLQYqMEQRAEEfGoJZTkY3hIGQuVJKvNYoLVXK5RHFLeIDgxLP8/twyFRiJLy2+lNrt6JWqoZKdq1a9C0oFzcUSVhRVDxVpNqsRmMcFWXtHKr70dHOvQUiUaFekc8hslGlW/vJry/rbV5Hv0bdWq//mqfktUkuHcsdbomzyLs/L0Ta22izUmSxzcyV1vkM88lfBafvNOlqjJQlrNJtgsvlhzTzyoXDO3zyra/6H8LtGc8DDWNzUnPEL1TXdw3+R9M6WmoET6BcSPf5/F6t+yAAANYu0Y37dFLXtEEARBEHUL/xdWk+B7DZcgCIIgiMhGbexWVknzVaTLK3b9msPcFekqSWmXR4TbK6raKvXCjUkryCcO1HwOPH+wfXkSzKqRGOao+hW0Ys252Ki8PUmeJeSEh3q8/HF3eUW4PFqxDpZI8bWrX5Gu1T8cBivptSuG9at+BcGnNhDoA39FuppkCO9io8F+u71MM9aa9xPH/aj2xgJgXPtf7V4E9N5MqejX/lhzy5zoVIaHjLWWjE55P+WOtYr2f6BvSluttzQ4+2aZygQR50K48lhGWYxp2dcU9BfgBYIoMryw8g/p9ycGt6VKOoIgCIIwiP8Lp9NmgSCoL85DEARBEETkoDZ2h7Ogo+//fhkLPukNeVLWwVF9W6SyaGew3+pta1f96l+zV2TSxENldKjleuFSrLm12TWS4X55Fo5EZ2B7PAvDFqlUZ8vbDWWrjLXcVj/JKspjrZGs5NGhdljNUqx5q37VFnb1n0t+btV2Nfumfqy1ZHScHPej1kKlykUs1a9ZFOWa38buRZ/f5YlhWaz5JzzU+6b/+kOulaCjkR6qbb1nV6i2izUm43j6pigy6Q0Rh8ZbGjxviDhsZmmBX15JmZqCEukXCMv3ZGBvRh4A4KLUWNzSrXEte0QQBEEQdQ+1hXcIgiAIgohcJJkBLa1x3gStmoxFGBrpPt+0kuHqUnJOjopjzeQbxzWXqCwWGvj/kBXpKpWo8mrY0NX/GlWwHIuzqi2eGfh/rbY1q345pHCU1cZyW45Ep5sn0clR9SufOLByJuG1dOH9sebWSDem7R5O31S+4WGsbyr7tUb/4FgUVjPWnMlwNc3w0LHWvx8N902u6n+NeHH0zVKPF4yp2Bp8M0Xuc5TFDH/9Ei02StQIh08XYcbXv0u/T762vbQiNEEQBEEQ/EhVbfRWF0EQBEHUCYqk5G7F2G02CZJEQ+UkQ8oTjm4vmD9rFGirmYTnqAjlqL7V0sBW02T2+axf9asn2wHoaaSXV6TblbH2Jx1Da6SrV8H6E3DFLo92rHU00n32+tesVZGulezUrPrlaFdTqoTzbQn/Ncv9NJkEyZ5Xj1411tz9Wks/u/J9U7uaXaNvcvVr/cmSUP1abfFMZaw5K9LVJi3cXoiiVqz170ettos5+qb2mxbyCQ9jfZMr1qH6pr9f2wNibdWfeKgpKJF+nrNkxzFc9foGnCtyAwDapsSgT+v6tewVQRAEQdRNKl7BpYp0giAIgqgLaI3dPIt++hPDNrMJVnNF+sSfGPaKDGWa2tvqCVpFMkqjglZzsVEOaQVtjXR9CYxiHkkZjmplebWu3D5kRXpZRaxtsnVo/NcgMmjHWkcjXe5bULvypLJV/Zq1q/9D67r7jjEaa165keDKXfm5eLT/rWZBEWv/uRgDSt0cmvIGJWm0NdI5Kqy1Evgc2v+a96KVr1/7244OinW5xFPIdQN857WYAmJd3jZjvipuVVuO+5Er1laNvqlxzZoLu/JMTGn4zPN2iNynwGdINMfzuqagRPp5TGZeCSZ9sRfyua1D2YXIzCupNZ8IgiAIoq7iWxTMN6o6A75IEwRBEAQReYQau3kW+/NXe8qrXgE+nWF5gitao4JWU1pBQ6okmqPqV1O3m6Pqt0ijEtXJoUOtiHVAvKRFLDkSjoHyeUq9cf1kuDy+0RwJRy2pEqWms36CVpk01Jcb4UtIa8faVb5QbWUmiCSpEo17AjDeN40mWbU10nlibaxvauq6cyyA6ZYtVOsMirX+M6RiwiPwGaJf3V2k1Tc5rllbI91Yu9EG+6bWmgM8C4Z6vKI0WRb49q//XKSRTlQrh88UIfANEZEBR84U145DBEEQBFGHKdaooiEIgiAIIjJRShSoJ2h5FnTUSsL77DmqYLX0xjmS4Y6wNNLVE8PaSWX1JLzdYoJfHZZvMciAJJg/1hwa6UHJSp7FEcOItVaS1cmRZNXWGueoSNfQzrZbTJIUL1es7ep9M7QOdbBUSeC5uCYANPqmdvU/j0Y6R980/IaHehLeZjbBIsXa2L0ob5tHIz0wMewwPNmiJTuk3ze15I60+yaPRno1xNqtfr3yc5FGOlGtNIyPDtpmFgQ0q++oBW8IgiAIom5TpPEFniAIgiCIyERLDgKoSOSVhNIoVlk8EwjQGdbQVpYnmrQkQ/gSw+oa6TxJVm2NdI6kocxWEATpXHzVs+qVu6VuEV6NWPv9DkxWOrniVflYKyt3NfTVOSZLHAZ1qIs0ErSCIOhWOhe71fuH/BrKPGHG2q1/zYpYcyzOyqeRrl8Jr1WRztM/5NeojDWPz+qxdnlEeLyhpXBCVaTzJLQ1tf81nz9a2v88GumVnyzhirXWorAa/UN+rlCxrikokX4es/3wOcXvZkHAi8M6IE0lwU4QBEEQRGhKNCosCIIgCIKITEKN3YoF+1SSUYwxKUkVmATj0hl2VSThTf5ybvBVoip0uzUrUQ3KWFj1E51aWuNyP3iSynJNZt+5Qk88MMYqKndDxVpHbzzaqoy1MsmqXyVtVCNdq2I4msc2RKz1krta1caB51K7Znmstap+A9tQ+F3uU5S1onI+qF0eCR4tze+wYs0z4aHeN7XvRe03UvUW4WWMacroyO8R7bclfNvlbykEtcsTa02NdP2+6dSINZ+kVaA8S+g3U4o4nj+A9uRBTUF/BZ6nMMbw3pa/pd9n3NQBA9slUxKdIAiCICpJkcbCOwRBEARBRCahxu5AiYNA6YVStwjGgo8FOHWGObSRtRPD6lIlXAlaDd1uua1m1W8IGQun3QIUlHElOrUq0gHftcWEiHUojXS9ZGeodvkkQzSqfnlkdDS0pLUnHkJUOtssAMq4ZIO0kvD+NmKjrIr9ZR5RkgAObRt64iGU3JG2Rrq638pYG6zOthpL7mq9mcKzKGzIay7zIk4l1v63Aiqjke7fHiQLw1X9r/G2hNEFeDU+Jy5JK7t6MpznzQEtKS5APdY1CVWkn6dsOnQGB7MKAQDd0xNxV890SqITBEEQRBhoLbxDEARBEERkoqUXDujrDIeWKuFPKAVXDPMkaNUTSlya3xoLFNosJtjMpnKfjUnK+PwOLTcSqkraqZP4U/gcGC8DEhihY22sCpZLCkcjyWo1m2CzlMfaoJY0UHHNXInhEAlHtb5ZpDFJE3gu7Wplb9Cxgecy2jedXJXw6vejxWyC3R9rrokHdf3+YpcXjAVL4Wjpugf5rXLNWpM0gX7oXXOwtJSxN1O01g3g6Zvy480mAVFWU/kxHM8uo7Hm7Zu1vOAoJdLPU97bXFGNPu6KFrXoCUEQBEGcHxRTRTpBEARB1CnkY7e8chVQToqrJYWKQ0gU6MnCyM9Zmapfv1aw2SRIyW9AmUzi0gvXkmfhqvpV99vtZXB5gjWKQ1VJR+tcc8jFM2Wfm7amM0fCUatyt/zzMwmQErKBPvNUs2vJfnBV/wfalktxeET1WJe4tROOevIboXxWav/rTFoEyffovy3h//yEELGuVFW5P9Yc6xVoSQd5RQaXiva2om8GXrM9dN9UyB1V4jmg9QzhkTnxn1MQICW/A221+mbot0tCr5VQEuI54JDFukztGeLm65tab6bUFJRIPw/5IzMfmw+dAQCk13NgUPuUWvaIIAiCIOo+ipXkA/7IIwiCIAgi8gg1dustnFcUojpbr4LW4xWlRFFwJap+glauYS0IMs1vHgmMEFIU/uvg0+0OoXOuWlWunejUS2iHirVSxiL4mr0iQ6lbVG2XZ3FWfxWs02YxHusQby347bliHSTdodM3QySV9RbfVCaVjfVNr8ikZHVgdbYi1jq63UGx5loIV79vat9PnM8Bg2+m6FX/h0rg6008iKK2vroyqRw61g6r9jOEp/pfS4Of780Ug32TV0aHKtKJqub9LYel/9/Tu7liUQKCIAiCICqH1sI7BEEQBEFEJqHGbj2dYS1NZp9t6KSOIoEfMpkUOhkeVG1s5U/CB/rp+913Pq3K7qIQlah62u4lioRjKBmL0Ilho5WoxSHblcdLp+o3UM+ZR3s7VB/RXZxVTyM9uI0KW75FdNU+p5D9Q2fyQF7xrTVJ47MNPXkQeE9EWczw53q5NPg11izQvp9CVEnrTNQUh5As0qukLwoxMSXvq2qV4YpYh7wXQ1f/B04cRFlNUqwrlQzXmbQIdT/qvZnC3zepIp2oQrLzS7F8dwYAID7aitu6N65ljwiCIAji/EBr4R2CIAiCICIT/kpUtWpS3krU0JWVoaRdtJJgUkV6QLsmkyAleLnkWayBflcsrKimUcxT9avVduhKVD25kcprI/PI0Wi16/NbffFMk0nQrb7lSdAWu7W0t/WT8IFtVPgcIsmqN/EQqupXRyOdNyGtN/EQmGA1mQSpr2pPPISSSamQGxFFvViH8bZEWBrpIZ4DOpXwldL+lxaFVbYrCIL+2xIc+v0l7qqPtdYiywDfIs01BSXSzzMWbDsCt9fXmUdd1jSo0xMEQRAEUTlCfbkjCIIgCCLyUCT+rMaSrKGqpJUaxTpJeIMSKYyximpSlYn7iurb0JW7NosJFrMy5eP3mzFIcihqtmpt68UrVPJNV49eY3FVQF8jPdSbAzzyLP7KX7UiCf8162mk28wmWANi7fdbO9b6WtLyNtR89h1rrOo3VEJaqZGuF2vtz0kr0en//KKtwbGOliXD1fB/BlazIC3kquZLqUclXpz3o66mfOAzRHeCKNRkiU71f5gTRP4Jk8D1HXzb/Pr9ofu1XqzV+kgJ5zWrSuGE0Eh36EwQ1SSUSD+PKHZ58MlPxwD4OvyYy5vVrkMEQRAEcR6h1FmlinSCIAiCiHRCjd16iaxQyXB9uZFQ7YaWG3F5RXjKKz3VCuP0Fvsr1qhEDfRbVfYjhIyFMgkWWiM9WKqEP7kbXImq53OoKunQ1f8ujygVIqoVSVTEOnSVtNr3Qr0KWkWsQ+iN611zUKwNJHdD6narVcIrpDdCyB2p9A+XR5QW8wyszpZv0411iM/J57eOfn+I+1H/zRRjWuW8kyVqfZP3XlSLtdsri7Xqc6DizRQ1tLTZA7dVed8kjfTq4d1330WzZs0QFRWFyy67DNu3b9c8dv78+RAEQfETFRVVg97WLJ//cgK5xW4AwPWdGiIl7vy9VoIgCKLucL6M3VSRThAEQRDqbNq0Cddffz0aNmwIQRCwbNmy2nYJgBGpAIPVt7pJUu3qbLvFJK1jpp9MClUlHVrfWDUJptBl1tMbN5YMV1SihtRIN1b9r0x06iSGA9q1meWx1kl0qiR3K6RddKRKdBKOan6XuEP0TQPXHKpyV18jPVSy0lgS3mY2weKPtcpbGqEqleXb9DTSVRPDemsWhHhbwqmzVkIoyaJoA8nwUBNEuvdiYKwtJljNQnm7OnJH9hATRFrrLGho2Qf6oj+JaKz6P7RGur4kVk1RpxLpS5YswaOPPoqpU6di586d6NSpE4YMGYLs7GxNm7i4OGRmZko/R48erUGPaw6vyBSLjI7r06IWvSEIgiAIH+fT2B1K848gCIIgLmSKiorQqVMnvPvuu7XtioJQi2c6DFSThq5ENZaEF4QK7W2jiU75+co8IrwqGsVSRbpa1a/uQpTech99C0Aq2tVNOPJWolZxRXqIql95rNU+J2UVfXCs/W2XeUR4vCryLKESjgYq0oMkQ4xU/Rrtm5zJXfVFYbUT0vqx1p6k8fni2+bSirXG4pmBvuhO1ISUeArjOWBwokZxL6pW/3Mmww0m4YGK+Lu8ItyhYq02kWfgfjQca86+SRXpBpg5cybuu+8+jB07Fu3bt8fs2bPhcDjwwQcfaNoIgoDU1FTpJyUlpQY9rjnW/pGFI2eLAQC9W9VD+4ZxtewRQRAEQZxfY3exzh+2BEEQBHGhMnToUDz//PO4+eaba9sVBUo9aGPVt/wa6XqVu9rJcLVKVEXlroqWdKiEkigymea3tjYyoJ5w9GtJR1vNMJVXFwf6LD9OTugqaQNa0vYQsdaLVwg5G3Vbbb3wIL8DPmfGmLRNrd1oq572Nm+sVWzd2tesFy9eHXx9/Wu1ePmrynX6hzV031SLtbQAr87nVBKiGj7aapbeUFCzrV6NdKP9WnuCSL5Nb+FftX4das0CxphsMk7l2aWzZoF/W5TVFBRr3UWaQ/RrvcVZa5I681egy+XCL7/8gkmTJknbTCYTBg4ciG3btmnaFRYWIj09HaIoomvXrnjxxRdx8cUXax5fVlaGsrIy6ff8/HwAgCiKEMXgmRojiKIIxljY51Hj3fV/Sv+/t3fzammjpqnOeJ2PULz4oVgZg+JljKqMV12P+fk2diu+lFqEOv/5VAf0vDAGxYsfipUxKF7GoLG75tEau9lFF4GZdOr9unQBW75csUm48UZg1y7f/wE0EEUIJhOeL3ZhSvlCjykf2SE++ijwyCMAgGirCc6yYnz/3j/gmGsGi7YqznlvqQcjyitFk+bbIK5YDnTrBgCIsgi46s/teGH1u7BZTGDP2hS2V7q92FYuu+pYFA/x8CHF/kfWvId+v3wPkyCAvWtX7Ev3ithW6AIAZFx+JcRblij2z3h+LOxnfG/2OT6ygwmyZBUDfsgvBQB8dvtDEMVeFfsOHMCjYwfgftk1MYtJEa+PC8rgFRnG/N87yr78v//hpqnT0b/8muI+sIIFJLpmFLtwR2waRo18EdFWk2Qv3HknLlm/EdsKfZ+3WqzvKfWAXTQAb/YZhWiLzLZpU8QC2JbnuyabxQQ2VRnr/m4veg74J35segmirWaf7YYNEO6+GwCworAMHi/zxfo/ylg39YrA6Lk+v/y2zz0H4b33AABvFbtRWp7cc35oBzMJUrzEK/qCNb/LZ2vz2QoDBwIHDwIAHinz4L5SZaylj2nyZBSVtamwzciAcNll0v4b3V70k2JtAZMlINl33ykqmOO/WAo2dbL0+yVeph7r1FSw7dtRVOaWjm0//QmwzWul32O0Yj1iBNgrr6BQZjvi7sFg3op7WB5roTzWAgDbiy9CHDUKhaU+2w6n/sSz/3cP2KPKPqAWa/bbb0BsLEpcXjAG3Lv9S/zfnK/A/q3sAw+XeTBOHuse3RTPiCKXB3M/fw6XZP8NNk/ZB25we9G3PNaxH1ggPvWE9IwAAG9uHra9OxoAkBxwv3WUxTp6rhnit19LzwgASN38Hba9+2yFX7I+II+11+mEeM9hxVjU/OXp2LbsMwDq99tX5bHe3OZSiE9fpdjXcOAV2Hb4OABf/wqM9ZvlsX7pyrEoLO2PWP+EwIEDwKBB2CrvAwGxnljmwb2lHtww+g0UlrornhP/+x+E55/Hh+XPEJNJCIr19W4vGkclY9TIF1FY5lY8I7BpE6YXu/BM+fM6MNYdvAwTW/bHm31Godjlkf7Oa9C1KwSTCcHv5ihhH34I9O9fsUH2jAAAZmDsrjOJ9DNnzsDr9QZVpaWkpGD//v2qNm3btsUHH3yASy65BHl5eXjttddw+eWX47fffkPjxo1VbV566SVMnz49aPvp06dRWloa1jWIooi8vDwwxmDS+3JggNlbM7DnRJ70+6ET2WifqNeNIp/qitf5CsWLH4qVMShexqjKeBUUFFSRV7XD+TZ25xWVSNsLc8/BVUj3QyD0vDAGxYsfipUxKF7GoLG75tEau4XMTAgqx8txpabiXIBEXFJmJmwZGdLv/pRTkvygQqAwMxOF5bYlBWUQAKQVnlVtJ678x297NisLblm7MaKrwjZXaeso/wEAl1gaJGkXX1JQYRvQZWwA0sr/fy4/J9g27wwS/baFSltBZhvtKlbYWrKzUf9sFmJl1+THH69kv/8CU9g6Tp1CXPYpRKvY+kkCUN/kO6Io9xzc5d+TEk+ehP3USckvNeIAxJYVAQBKi/KRne1LiqaWf6YK21ylrQOAzeNLhHpKi5CdnQ1bVhaSym0byA9WibWEpwzZ2dmIzcyEs9w2Ub4/IF7FJ08Czf2/e5GdnY16GRmwltvGlv8E2gJAwalTKBJ8xlEW4ExWFpJl/Te6/EfN9mx2NvJk21znzkCQ2VoB1Vh7RRGns7NxRmYsnD2tsEWgba7vn+LMTORnZyPrbG6Fj2eyIBQXKWzVYl189ixKs7ORkeU71uZ1I/5ssMSjWqyzs7PBSkqQ4090u4pRL/d0UB8IjLUrM1PxjCgsdaNecR5S8s8A+UrbwFjLnxEAkFdYUnGvBnwWgbEOfEaU5ORp2kJmW+QuQXZ2tmIs8pzODmnrj3VMUT6ysrIgyJLO8VmZms81oCLW0e4yHM88DXOZbz0qS3Y26mdkhLzf/LE2iyJOnj6H7ITyhZFPnUJcRob0DAGgGuv69Xx33ZmcfOkZk3jyJOwZGUHPazlWALGNfX3oXH6RFK+GmZma1yknJysLLtlnI39GANAdd+TUmUR6ZejVqxd69aqYgb388svRrl07zJkzBzNmzFC1mTRpEh599FHp9/z8fDRp0gQNGjRAXFx4cimiKEIQBDRo0KDKvtBm5pVg/o5Tim2vrDuG67q3QFp8tIZV3aA64nU+Q/Hih2JlDIqXMaoyXpGyyGZNEsljt5v9BQCwmAQ0SktRfGElfNDzwhgUL34oVsageBmDxu6aR2vsZmlpuhXp1rQ0JCcr0jUQ0tLAGjWSfhdFESaTCWcLXXB7RQgCkBIXBUdaGhzltkJ0GRiAzJh6iLKakeBQVm3mlbglmYIGsXYkpqQA8najo5EZUw9ms4AGMcrKy6IyDwrKK2Rj6ycE+euOi0dmTD0AQGq8ss+UeUTkFPkq0lm9+kG2J5MaoLS8arN+jA0Wc0W8vCLD6QJfhaw1Lk5pm5ODogapyC/xJSUTHFZElcs0+OOVlV8KxoBoR5TSNjUVZSlpOFfuV4zdgpgoZTrpbKELZ5wJQd+ThIYN4W3YENn5Pr/sVjMSVWJdYHcCABqnNkByfd///Z9pdkEZRJHBbBLQIDY41i6L73xpDZJ8fqekSLbnilxweUTNWPtpkBjrs5X1pfwStyR9US/GBmt5rEVRhJCcKtkmxjiQnJwMoVEjsCJfsq/Y5VWNNQDEpKai5ISv7dhoO+rL/AV8OuH+WDvtFsTKYp2UnAw3zgAAzCYBiWmpyr7PmGqsTampvuszV+SP7KlKW61YR6elISo5GWZ7RXbTlZwKq1tZsKIWa0e9eohLToY91+ezy2xFYf2UINkQtVg3SE4GYmNRds4nY1xgcyAnMTnoXpXHOt5hRXTAM6LUI+KsIx6n4xugfoyywjow1jGyZwQAeASL714VgNQ4Zf9RxtoU9IxwRzml+7xBrD1I6sQfa1e0A02SkxVjUXZCkmQb2H/ksc6NikVCUn3YZfsLG6Qgt9j3/ImJsiAmMNalbhSXeVFitSM6Nh7JyfG+HTk58KQ1lJ4has9Ff6y9JhNs0TEVcS7vS/5niMVsUo31GXuC7xerXbIVGjYEa9QIZ4tccHtEzVj7nxFewYLk8nh509K4xu2EwOd3wD3HRBHgTMrXmUR6/fr1YTabkZWVpdielZWF1NRUDSslVqsVXbp0wZ9//ql5jN1uh91uD9puMpmq5EuoIAhVdi4A2H8qeGrKy4Bj50rRKNFZJW3UJlUdr/Mdihc/FCtjULyMUVXxquvxPt/Gbv8f0w6bGWYzLTaqBT0vjEHx4odiZQyKlzFo7K5ZtMZuYf9+CByT4EFT2StWSP8Vyytvk5OTMXzmJvx9pghxURb8Om2Iwi4myooiuwO9HliA3q3q4ZNxPRWnfPLDn7Hmd993mJ+eGYCUgMTOLx37oFeTbmgQa8eOfw1U7Ju9+gDeKZdf/fjey9AnoF98Meph/LPbHQCA3c8OQoKjIuG0encGJi7eDQB49rr26BBg++Fbn+F/m/4GACwd3wuXNq+o4zyUmY+hb24GAIy8tImyP7Zrh5XfbMeTn/0KAHj+pg64s2e6FK+kevXRc8pqAEC3BolK2wkT8Me1I3DTu1sBAGMub4ZpNyhl94a/tgF/nylCbOD3pIULUebyoNezvnNf3rIeFt6njPVTH/2M1b/5Yh0bZa1o+8QJAMCwf69DRm4J6sfY8fNkZaznrDmAH9f5Yu20W3y2V10l2T4+bzvWHzgNANg1ZRASnRWxXrPnJLDIJwnksJe3O22a7wfAu9/8IcV6yf09cVmLelK8zonRwFtblO2uWyed+5ufj+OJgFj78XpFlP1rla9dmxmmRo0kfwFg//Fc3Fge69G90jH9xg7SPgFA8TcbKmzvvBO4805pv8vlRa9nvwUA9GpRD4vu76m0lelal7z9H8QHTC7c8vI6nMgpQf0YG36ePEhhK9fE3rl6G/q2UdSgK2K9c8ogJERb4MrO9n2PLp/82ZfaCou/+AHjrmihsP3PN39gTkCs/fdrSXly/v1Lb0bh//0TL996icJ21S8n8PinewAAM27qgLt6pku2XpGh1C3ivlueRdemCfji/3orbA+cyMUN7/hifXevdDwnizUAnDXZ0OuBBYi1W7B3+hDFPrfbi15TfLHu2SIJi3v0UOz/pWNvPP/AAgDAtklXBRW7+mNdz2nDL+V93j8Wrbv3SbzVzLfmxIJ7LkW/gFg/MX8H1u33VVhf7WGItlfcrxs/WYWHyvv15GvbBcd61R+Ys9EX61FuseJ+a9cOh3bux5BZmwAAt3dvEhTrb385gcfKY13i9lbYTpgA7/3j0fOZbwAAXZom4MuAWB88kYdR7/jumRKXrN2FCwEAI2ZuxJ/ZhYixW7BPJdZvlsda3m72zp1ITk7WHXuDxgzZMwIAhPx8ID4+5Dn81JlR3mazoVu3bli7tkK/SRRFrF27VlG5Fgqv14u9e/ciLS3US0V1i79PByfSzYKAZvUdKkcTBEEQRM1xvo3dRSEW3iEIgiAIIvIINXbLFw5UXfhOd2HF8sX+ylQW+9NZxFKx6F7Agn2KhUrtwbYKvwMWGlQsjK6y2KhTschggG2Ihf58tvJ4aV+z2uKqURYz/C/yBV6vz5fQiyP646C3sKLaNTsUsQ64Ztl1OHUWsQxclFE31iEWhZXHWq1vyj931XiVaS9yGmU1SbFWjZfcb5X+5T+n2j1RpNM3HbJrCewj/8/efYe5UZ19H/9J2tU2l7Vx7xgDxtjYxAbHNFMMhhBCDTWhJbQH3kAgTwJ5qKEYSAADIUAIwRA6hBJMC5gSigFTDARsU43BBWMbt+0rnfePtbQz0mg0R9pdbfl+rosLr1Yzc3TvrO7VPWfu4xyL5yKWPgtgun7GHsd1/uxSfx+z/ZzKsy2AmZhI43HckiJnrP3j5ff76Lk4q8W56Rdr2/eBrO9dPuemc4Far/cB12LHPq/Z67wuKQor7BPrttShPgmeffbZOu644zRp0iTtuOOOmjlzpqqqqnTCCSdIko499lgNHjxYM2bMkCT94Q9/0A9/+EONGjVKa9eu1R//+Ed99dVX+uUvf1nIl9GiXv5klevrSCikKw4Z2+HbugAAOofOlLsTH1q8/qgEAKAr27hxo+vusS+//FLz589X7969NWzYsIKNy6/gGA6HVB6NqLo+5llwzFqA21QMrG6IyRjjavlWXZel4OhT+HMWxbwLtM5tMxccPYtvJT6F4Tr/Ilh5SeZCp/Mxr4JjOBxSeXFEVfUx7wsPztdc7BWvouQx4psWMmw+rrNAa1cMdxU6vQraAYu72Y6bWqCtyXqRJnOhs2ncmS9ahEIhVUSLtLGuMetFC79Y1zT4x9q7QNu8P2dRVUq94JGtQOt+zc54ZTs3/S5MZTuu94WagLH2OK+rXb/LmX8faxviisWNa9Z00CJ807jtLsb5nZvZ37scx00t4Gd5vc791fhcePC60JKI9YYMsW5LHaqQfsQRR+i7777ThRdeqBUrVmjChAl65plnkouYLVmyxDWd//vvv9dJJ52kFStWqFevXpo4caJef/11jRkzplAvoUV9u75Wr33eVEgfXFmqP/10vEb0qaCIDgBoNzpL7jbG+H5oAQCgK3v77be1xx57JL9O9D8/7rjjNGvWrIKMyZm7vQpRicebCumZC46lxeG03sZSc9HQmKZCmPNCe3WWmZkVPkXpmqxFMJ+ZznkUhl0z0rPN+k05rjEmub9MfyeVlxQ1FdJ9Yl1SFHb1fE8e2zGe2sZYxtnL9rHOMuvXr7jbkKXQ6ThuelHZeVy7n5MxprndoMfPqWk8EW2sa/QsVtrEuqYhljF+ngVt1+zuzPHKtm36BQ//WfSuAr7P74TtTHjnuPOJdbQonOyv7x63+xwpL25+Tk22C0Q+FwCqsxXhneem9Z0WfndpBI+110UeZxtNL+UlEW2oa2RGuq0zzjhDZ5xxhuf3XnrpJdfX1113na677ro2GFVh/Gv+MpmmBXJ12MShmrJFn8IOCAAAD50hd9c3xhXflHMz/XEHAEBXtfvuu8skPpy2E0Fyd7I9i+fsyGxFeHeRtSzDLHOvY/u1OHAWmMqKbQtZWWbA+rWDsBqz+7h1jU0zalOf53Vs79n/mWeiSu44VNWlFtL9W1H4zv7P0lLGb9us8Sr2iXWW47rPJXes62NxNW6KdbZz07N9RvK8zvRzcrfCqShxx95v3L6z/7PNzg7ansVjFr3fuWl13JR41TfG1RDbFGuP30Vp0zm7oS7D7H//WKe+Z5QXN/fvtzo383jN6e2h/O9qcf0u+lzwsP19qm+Mqz4WzzjmpvEUSaoreCG9w/RIR7pH31ua/PdB2w/2eSYAAMhHVZYZFgAAoH0Jkrub+0F7tWXIMjvS1eLAZwZtlhYYqdtma1XiLmRlLgx794MOOJvUY9toJKyiTTPz/WbAehXfnOPxKziWeRRJJf/2G1XZWtL4FFmrs8wM95tB6461VxsLv7Yw/v3Cm2YwhzYdJ7WA739c57hTz62mY8dcz0nfNvdzs8K3R7r/3RJ+Pyd3j/QsM/j9jusRr+JIWNFNs8XT2pxkmQkvNZ+z3i14/O/SqPA7N+stzk3L1xx49n/WGel27wOuWPvciZPp3EwU571i3ZYopHdQn3y7QR8vXy9JGj+0Upv3qSjwiAAA6LyyzXYCAADtS7bZ2VJz4c85o7p5+yxFMJ+2H4ltQ6Gm1jCp/BbAzLZ4pl+P9GwLFPotgJmtgBYKhRwLrPoVHP2LhvWNcTVumnmaPHZdYkZ6gFnSGY4dJNbpr9m/jY6r9YZfodOzuOszIz3Lwq7OcfsVOrOdm/WxuBpSYp0Yd6BYZ4hXKNS0gGz6tn490nM/N7P3SPcpwmc5r53b+54fWWLdEDOqb0yJtc/imU3H9Tk3nbP/PS4wVfheFMvj3MyysKvf72K29R2c+0xtwVOV5SJN07ib9ukV67ZEIb2DeswxG/3gCYMKOBIAADq/bIt3AQCA9iXb4oapjzuLT7G4SRYCM11Ad84MzzS7uyJa5FqE1Ou4qQXamoZsbRmCLTKYtWWI74xQu+JutgUs047tKLLGHbEOMkvaGR/nscuLI56x9muFU+OKV/qx/Vrw2MQ6tagcbFa5d3E3yM+pLMM5Ened19lnSaedm447B8Ie6wb4LmLZkPu5WZXloli5zwWPbGsOSM3nrF8P/cwti7yPbYxJvuaMP+Pi7Odm5lj7zSr3L8L7xTp7H/zMv4tBzs3EPv0WhfVqaSX594VvSxTSO6B43Ojx+cskSZFwSD8eTyEdAIDWlG1BKQAA0L4Eyd2ZWp24FkbMNDvSr8WBxUxUvzYW3otn+rVW8J+JWu7Tt9vVqiRTwbHEu/d2tlYlUmr7DctY+xVokwtvZl5Q1mucUursbq9Z0n5tTrIVHIMdN9u5md42KHvLokwLw9Y2xpLr7GVswRPg3PRbvNfruFL2NjqZzo+mffkXaF396H3OzcyzpDPM/g8wkSbTnSm1DfFkrLMdN3Wczn1lLP4HeP9p2j7bArw+/eiz9v73aXeUpZ2WXx/8bDPSm55fuD7pFNI7oHmL12jp2hpJ0q5b9lGfbiUFHhEAAJ2b+wMiM9IBAGjvguTuigzFzuogxTe/FgeJ4m7GWZnBFlb0XLDPd7E//4JjUSSskqLwpuPY9Qt3Pl5dH3MtLput0Cmltt9o9Px35pmo2VvSZO7N7jP7NlsbHd8WPP4Fx0g4lGw14xvrjBdqEjN3G92xrvM/P5rG431uZmsb1PR49nMzyMUl/yKrf1sY2ws1kXCouVe5ZRFeaj53UmPtuuARYCHc6gzndZALRJlmhmf6OVUEeP9p2j5brO1a4YTDjhZPfhfyst1p0eB+DwlybpZluEDU1iikd0CPbZqNLkkHs8goAACtzv1HODPSAQBo74Lk7vIMbT+CLJ4ZZGZ4oCJ8hlmw0UhY0SKPnt8lPoXOIMXwTLNvA7V2aXo8Fjeqc/Qorg40S9p7xrHz3znNSLeYJZ3e87vp6+JIyDvWPm1ObF5zWlsYi7sl4kauWFflcW4Gm/XrV2S1mJGe1oKn6euicCi54KR7zJlnGwdqGZLpbolAs/+bHjemaSZ5chy2M9IznNdBZqRnWpDWti2V1ByvSDiUvHDmGrPf4qxZeqQ3HXvTeZ3WIz3IeZ0h1gGK8H7vA22JQnoHU9cY05MfNBXSy6MR7T2mf4FHBABA55etNyMAAGhfguTuTH2GXbOkM82OzNDfuL4xroZY00zLzAs6Ogu0KUWwLL3Z/dobBJl9m5y569t7O0CvcteFB+escrvCX5ALHq6e344idEMsrvpNi2lmK7Cmjtn5deYxZy7CB4p1NLGwYi490r1/ztUBCsOZemAHunPA1fO7+ViNsXhygcdAxd0MM8PLot697P0Kw0GK4ZliHahHeqZz09XXPUg7G0ess6x1IKX2SHev0VCXNdZ+PdIbk/v3inU+PdKdY0rt/V8T4D03UyucbGsOSKlth5iRjoBeXPid1tc2nTDTtx3ArDgAANpATYA/KgEAQPsRJHdnaicRbEa6d0uHIAVpdzHJeyZqpuOWFoeVqI2lz4TP3qM4OXM3rR2Es42FXSGrKsCs8iCF4SAzUZ0zaIO8Xv8WPIlWJd7bumOdWnAMUDTMNHPXokd60/YZzs1AvaS9Z6TbnpvuWfQ5XHjYFINMv4slRWGFM8Y6+yzpTLP/A82SzjAz3H2HR5D2LN6/E4FiXZfhdyLTeZ2hIN007ljac5xKisKKbAq278KuWS48+K2zEOh9wPI1+y2E25YopHcwj89fmvz3QbR1AQCgTQRZgAsAALQfQXJ3pnYjrv7XWRbNa3q+92z2YLNJvYvhmY4bCoWSM1n9+htnm2Vd0xBTPO7d5zxzj/RMM51tC7TOXtJB+qt7t8Kx6cmc+nzJ2RbGe9tQKOQohvvNSPcvdtY0xBRzxjpQO5sMd0u4eqRbnpsBWpW4Zv+71g0IcH74LM6anCWd4fX6xdr1+5jljofahrg71oEueAQ4NzP1SM/QCidIG51M7wPB+rpnXpy1ed0An/cQR194J9exM8Q6Ueiua4yrMebdniXQBaKMFx6yn5up731tiUJ6B7KupkFzFqyUJPXpVqKdt9iswCMCAKBrqM6yoBQAAGhfguTuTLM6a/KYkR6oqJxhlrQxJuvimU3j3tTnPEN/47LiSHLGafq4HbM6HbOMbduN2M6SzjgTNcBFi0wz0gPN+s1QfHPFOsNxm/br3TIksa/S4nDmWDvbpDhj3ZC9KJ3p3MznbgnXuRkg1s54BZup7N2CxxiTHLffnZ2J/WaakV5SFFaRR391KfNrrgpwgSjTXQuBZqSXeF94sJ2R7m4tlfv5YYxJnqt+k3+SCwen9Tlv2lfUJ9aui1OOn3NVgIstwe5MsXsfaGsU0juQpz9cnuz/9ZPxgzKe1AAAoGWx2CgAAB1LoBnDGVoFBJklnalHepCiclmG49Y1xmVM+nNSJQpK1Sk9ihN9mf0u+pcVe7ffCNTTOWO8nDPhs8c60+zbzLOkvQt3QRahdMe6+bh1jXElJi5nmr3v3G/qDNjEvvz+LizL9Jpds8rtYm17XufTI935/CCxLs9Q6KyPNc8S9zuvE8fOVEj3P6+941UT6AJAhli7eqQHuePBcdwAv0/O3xV3e6gA50eG11sfi6txU6zLM/wuOseUtlZCQ+KCR/bfidRjB+lznnkh3NzvTGlrVGI7kEffc7Z1GVTAkQAA0LUEud0ZAAC0H8EWzctQVA7UqiRT643shc5oUVjFkVDacavqss/KdO43bUHHLL2Rm8bt3X7D3W4k+2t2tbEI1CM9ewuMILPKXbN+AxRJo0VhRTdNQnT3oc7+ep1jSlsAM0tbmKZxe8e6KsDs28yz/21bhmS6QBRklrTduVkcccQ608WlAAXa9HZH2S9aZDo3A82SzjT7P8BrztSPPkirkkw90qsC/C4WRcKKFnnE2nlcn/cB5+x/Y5pb4TSf1z6xbqFzM9PvY8Z2Wq6LB8xIRxZL19bozS/XSJJG9q3QuME9CzwiAAC6jiCLHAEAgPbDZoFCKXXhuyA9rDMtBhmsHZzX7NsgxSTnfutjcTU4ehRn643sPG7q8RLFuHCoqYWG33Gbts00mzTIhQfbHukB+lAHmBmeqTDsWwzfdOyGmFF9o7MfdJBWJd4XahKzeEOhptYwnsfNMNM5UIE207kZoFWJq+d3pkJngPYsNa6CdLDzOhHLjLH2Kwxn+X30j3WAtjB5XCDKuGBoxjYn2X/GTeNOP6+DtA1yHrsxbpKdL5z78n3vytKSJhSSSosCzP5vyHShxu59oK1RSO8g7n7jq+S/D54wWKGQdw8uAADQ8oIsHAYAANqPQIt+ZigIufurZ5rFmqH/dT5FsKAzdz1mw8fiRrUN8cDHTT12jaMIn6nekGkBzGAzUQO0G8nYt9sR67wKjs7WG3YFR+ex48Ykt/fvQ+3fOsgv1l4/46Zx252becW6IcO5GaD3tu2isE1jSo9XPN7cXz3ojHSv38fy4kjmWGdqzxJoQdncz83MbU4s70zJ+N5ld27G487zOtiMdHe8NhXhiyMKZ1g3INNCuM4LAEHOTXqkw9f9by3RzS99nvw600IWAACgddAjHQCAjsW+l7TdLGlnT+bM7Q0CzJLO0PIjSI905/GcxUPfGcMZF5OMZT1uWYZZv654ZeyRnn2x0YyzpJ2xzjTTOcDMcPfM7mCxdseraZvEBYvU76eNO8NCp4nXHPS4mVqGZG4Lk71AG+y8tj83m89ruzsWUsdU5XleB+uR7rUQrv8dHt7nZpCLcZnvTMn+mp2ztjO1wglyjlRn+l0McEeMc5vaxlhyjQa/Cx5lHj8nqfl8KQt4wSPTugHlGdYsqGBGOoJYvq5G5z36oeuxa/79iZavqynQiAAA6HqCzngCAADtQ6AZoZkKnQH6dkfCoWSrCNvWG1JzQamqvjHZo7g6QJE0dUyJ4wWdieqarexR+PMr/lcEmMEfZFHGqowXLbyPHQ6HkoXSjL3GA8wMd8U64Axrd/uNRHE37vn9TMdtGnf6a/YrVlZ4/IydY5CCxjpTj3TvbcPhkGev8iD9wpu+t2nbhube27kUdxPHrgrwuyhlPjeb2x0Fmwlve6Em0+z/IK2DXLHOUIT3PTcTF4gaYorHE+8hjWnf99zW49wMsr6D5NcSqzH7mDPMSHedIxkXafae/d/WKKS3c1+uqpKj778kKWaMFq+qLsyAAADoghJ/GEYjYRVH+PMJAID2Lpm7izLnbq9iUtO2tm0s7BYqdR47bqS6Tf2ggyyemTbuZMEx+wKFTWPO1GIlQG/kjIuzNu0n6lgAMe24GduN2PUq9zpu6thSJQrOxjTPJq8K0L7HeVzn8dx9qINdtHD+fBJFwKCzs71mpBdHQpljnaEFRtBieOLYGQudAc4RZ6yD3qVR4VFkrcnhgoe7L3yAWdIZ1w1o2o9frMsz3S1hvZhtppnw2eNlTNNs8rTjBriQ13S8xLZBL8b5XxTzP68zteBp2k9ROJRcsDZtzBkuxrU1Pgm2c5v3qUh7LBIKaUSf8gKMBgCArinxRzgLjQIA0DEkc3fAYlLmWeVBFlb0bssQdMZxYhtX0TDAcZ3b2i5y6tymIRZXQ8xkPW7mXuWNaeNKP26mdiPZZ6I6x+113KaxBY11essQ32K4x8xwV2uXgIXhRP/o+sZ4cnFH34s0GXukByhWZrpzwDbWjhjVBL1Q41FkDXpnp9fs7sCzpJ391TeNuyHmiHUObXQCXfDIGOuA52ZJ+uz/wO8DHu8hQYvwXq/Z9gKic6yNsXhygdigsfZswRP162XvPRO+rVFIb+dKUla6jYRCuuKQsRrYs6xAIwIAoOtpvi2U/ugAAHQEQXJ3SVFYiZqNbS9pqbkfuLv1RvZF8yTvfuPBe6SnF4YDFys92n44W5UE75GePls5U29jqSnW4WSsMxUcA8ySztAv3LeXdB4FWs+Co7OQ7vOaPWPt6n8d8PxwvebsrUqikXBybb2MhfRAM9Kds42D9khPj3Xgc7PYq7gb7HexrDj9gkfQ30X3nSnpM8P9jhuNhFWUjLX3BSLfeBUnzmvv2f+B++h7vWbrbYMV4b3OTeddGr7vXZnuTEle+Mx83Ka7i0Ku4xYChfR27pVPv0v++4DtBurVc/fQETsMK+CIAADoemocsyQAAED7FyR3h0IhR3uWDIUsv0JpYkZ6Q0yxTT2KqwIsntn0PY+CY+Ae6ekF7aCtSrx6pDsL6f6zpDPMKq9LzEjPfFxXrOsyFMMDFKVrG+LJWOfUMsSrQBu0p7NHMTz4IpbpF0sCnx8eF2qyxdrzwoOzGO4T60Qs6xrjatw0ozvouem1+GYu52ZVcoZ10FYl/kX44G1O0tvCZHsPae5znqlHevbFN+tdsQ7Y+99j9n9V4B7p6a/ZvZCt3bmZz/nhHEO2u38T5y090pHRS4uaC+lHTR7GTHQAANpY3JjkLAsK6QAAtH+u3O1TTJLkKII5Wys0z0QNh73bDEgpLQ4a0meE+s+S9iiCBS7u+s9ID7LwpnMb52zSoP2NEwVO44i1X/FNan5NXjPSy4qzxLok/TUH7dvtNZO+Kmjhz3HcGo8Z6UGLu1Wes7ODtQxJnBfGmECzpJvGtan3trMIn+gXXhxJzlj3PLbzHGnwahkS7Nz0+p0IfG4mLvLU51AY9vgZB57Z7Tivk3e1ZH0P8VoroWk/pcXhHGKdS2uXRLxyufCQPiPd726JfN67nD+HxPlhjGle7DjL3b/ORZoLhUJ6OxaPG738SVMhvVtJkSYN713gEQEA0PXUNcaTC3/7feABAADtgyt3+8y8lZoLM85iclWANgNN3882C9au33jQ3sjeRbDci+G1AQvDztebKHDWNgT/OylZ3PVoN+JXYE0/tmW8PGJd3RC0MJxehA/aI92rh7V7Fn2wNieJMbv/Jg160cJR3G1IFIbzjHXQHume7UYC3i3h0YInaGG4psGrqGz3c6prjCtuHWuP8zrg74TUfKGjJuAFIq+LYlU5vA94vYfY9kjPJdaJGen1sea7TLLG2mP2f1ujkN6OfbB0ndZU1UuSdh61WcZVggEAQOuprg92uzMAAGgfbHJ3olWAu31GsFm/Xn2GXYWsgDMzvXqkB18w1Ku/sd3Cis54+c1ELY6EFY2EN43ZbqZy0749irsBFnRM/X6y7Uedcwat3ez/6sA90j1m/ztn8AfskZ6cRR9wlnRRJJysAXm93mwF2mTBsT4ms6n6npyRHnA2u/OYQX/OZVkuLuXTI913lrRHj/Sgs6Qj4ZBKErGu81pzIPgFomSsE3da2LyHeMbLr1e5V1/4HN4Hkj9j+3UDvM5Nv+NGwiGVFoc3jTW9LUzWOy0cM9ITsW5rVGbbsRcXrkz+e4+t+xVwJAAAdF21jY5ZR8xIBwCg3bPJ3YlCe30srvpN2yUXz8w6EzW9z3CikFUUDiWLzp7H9WqxErCg5N2HOoeWIYkZsA3O2aR2M51dY87SAiNRcGyImeZY19lftEgtdjoLoX7HdY47aJG1wqNoGLSnvFe7kaB3LDiP7bmgbMB2I41xo/pY4rzOvgBv074z3/EQDski1vm0s7Hrke4es93dIZLjzhTLwrDz+7G4UV3yvA42I93vNYdCShadvcfsf6Em8LmZfP8J1lPeqwify4UH77Yw/tsmLnzGjZLvIW2NQno79tInzf3Rp27dt4AjAQCg63L/YciMdAAA2rugLQqklJ7O9TE1Ogrq2Xoj+xXDy6IRhUI+vZE9ivCuhSh9jl3mddyALUPcfd3TFxsNWgxPFt8aghXfmvbtLvw5C49BZ6I2beuecVyeJdZePdIDL+xa4j4/pJR4BW7B41VwDHZues6wztayKOVuiVjcJFvSBD1u07Hdi1hWRIv8z2uvdiNBF8/0WJw16MWDCo+LFlUWM53LfS5aBJ39n9guHjfJi1PZFs/0bDsUONbpxfAaV8siu3PTtciy5eKsVQHff5z7rvG40JLtPaTCY0Hatsa0qnZq9cY6ffDNWknS6AHdWWQUAIACCfphCQAAtA/O3F1WbFEEa2hUKOz9PS9lPrNvbYpvXgWloIUs2wJtWXF6Udn9t45dESxoq5LUfVfXx1yLMGa7aFHm0fYjMYagC286t3G2Zwm6EGWiIFzTECzWpUX+FzyC9uCv8ZyRHrwYXt0QU7FjFrlV7/8Gdw/s7D9jjwUwXa1wgrUMqU4pKqd+P1VpcVihkGRM+phTx+V3bO+FN4PfmVJd3+iasR/090naVIyuaB6/ze9TjceM9OAtnhLxCnYhr6SoOda2712S42KcZQ/99HE3Kur77NbBjPR26j+ffpdcRGJ32roAAFAwQW/fBQAA7YNN7k5tv2HVr9ezz/CmWdIWM1E9C0oBe29XWRZow+FQc194r0JnwNec6FFs0z4jtchqMzvba4FV5yxp3+N69kjPpad8ouAYbJJFOBxKm+kctPVG07ibF8KNx03gWfRp465rDPx6U/ed2vs/2wUPr9ZBQS+2eC42GvAcCYVCyd+Z1N/FpnEHex9IzCi3uasl9c6UKouLJV6xrk62hbFpd2T3PuB1wcMm1ml3ptj0798Uz5qGpjslcj43CzQjnUJ6O/XSoua2LrvT1gUAgIJxf7hkRjoAAO2dTe5ObXFQZVMYTmkz0FRYtp+R3lxkbfp/SVFYRb791dNbYFRZFFkTrzlZfHNeeAhYDDdGqm2Iu2fAWhQcq+pilotnutuNOGNtc9EitUAbLQqrOGCsk0X4HC7U2BY6m47dtG9jpNrGlAJttteccm66eo3bFMNT+o3nUuhMbBt1LKDqvW3m46bu23vc7j7nVn27Ha+5piGW0iPd7tx0X/AI3u4oPdbB+ro7t0mcZ8WRUJZYe1zIy2UxW8+FSi3uEGmwOze92lq1NQrp7VAsbvSfTf3Ru5cUaeLwXgUeEQAAXZfN7c4AAKDwbHJ36ox0VzsIq5mojaprjCsWb7q1PGt7A8+FSoPN+i3LNiM9YHG3JtkCw9kjPfjM8Kr6RldPZrsLD+4Z6dnj5S6g1cfiatwUa5t2EM0LlSZms9v0dU9fnDVogda797bl3RIWPdJTZ6TnsnhmYtv6xrgaYmbTmHO4QBTwgodrlrTXXRoBfx+rUi5MpY4r27FTz02bmeFpM9IDrjkgJdZoMKpPxDprvNLfB5K92bP8nMp8fk6p+/Ycd0nKjPSAbWG8ju2+uGTx/uP4+bYlplW1Q+9/s1bfVzdIknbZso/v1VEAANC6qusppAMA0JHY5G5Xn+GGRjnadlv263UX4bMV37wXDN3UGzlLkbSkKKxIOKRY3Hj2KA76mpM9vxuDF4bLUgp/Vj3SHa+rpj6monBzrSN7j3T3TOeaHF5v4riJfTR9z/+40UhzrJtb4Vj0lE+20bHvJZ067qALb6ZuW12f2iPdrr96TY5jbm6FsynWWc7raFFYReGQGuMmuYitzQz+xLnpPSM9j1hbzQyPuXukZ3nNqRfFaly9+4PPhG9esyDYnQNNd2KE1BAzaT8nKfv5lTivc+uR7rxQkxprmx78MUmZF2NtLVRo2yHaugAA0H7UOj5cZvuQBwAACs8md6f2Gc65qFPXmPNM1OqUth/ZZqKGQs29t6tSZpOGQu5FLr3H3fT9usa4GmNx14z0bBcAUttv5NJ6IzHeqhxnoja14LFpZeMx+z9gwdEZ62qPxVmzXfRIHDsRa1c7m2znSMrsf7se6e7XbNOqJPXctOk1nlpUbvp/Yt2A7H9Hp8badaEmW6w3bds0gz5uNUvad/a/xczw1HPT6n2gPuZe38Hmd7HOfcdDkMk/5SkXHpw/5+zn9aZYx+Kqb4zbnZsl+ZybtHaBh5cXrUz+m4VGAQAoLGakAwDQsdjk7tQ+wzY90t2FTncR3rY3snOBwyBrsiTGVp3S37i8OKJw2H+Wpus1N7iLd9lnOrsLjrn2SK9O6yVtWejMtVVJopd9ogVGgOJu88KK7sVZy6PZY+06dkM+s29TL9TYtcKxWTwz9dy0mRVennKhxRjTvFBpgL+jm1uGuGeklxVHFMkW65Qivl3f7pRiuM2aAz7nplXroLpGV//9rLFOeb1NsU5cjAtyXrvvTEn8PgaKdeqdKTYXxaJ5nJsei6S2NaZVtTOrNtbp/W/WSZK2GdhD/XuUFnhEAAB0bTUWf9ACAIDCs8ndqUXWUKi5gGTV09myHURqmxP3LPogs0m9e2/bzPpNHNvZTiLrLNgSv23tCn/OYp1Nj/SahpQe1hbF/+r6mGob4jImMeYAsU72OXfPSLe54CElWoZYXKjxaR2UvUe6+zU7Wwbb/E6ktjmx6eteUx9TXcwkYx0kXs3ntbtlSJDfiYrU89rm9zHl3KxuCF4YTu357WrtYjMjvSGm2obg7wPOWeOJNRqaYx3kvN60VkIi1g3B7tJIHVt1Q6O7rVXWHul5vG+mXLwsBGaktzOJRUYl2roAANAeuBeUYkY6AADtnU3uTiuG5zzTudFq26JIWNFNBbeq1F7jxQEKjo7irjHN/bttWjokju1qVWJRNExvyxC8R3p16oKO2S5aOGJSldJuJNuYI+FQsrhZldqCJ1C83LFuLqQH37b52MF7SZelzv63alWSMtPZasZwSgseVx98/+O6Ym3Zy77pOc3tRprO602zpANsm9e5mfa7bL+gbGLcuS8KG3PNSA9yXpcWh5PHtWmR4jx24s6BxGvOdgFRcr9HpZ6bVjPS8zg3qwu02CiF9HbmRUd/9D1o6wIAQMG5ehXSIx0AgHbPJnen9hmuspkdmVbotFtXpSJZoE3pNR5oRnrT/hvjRvWxePLYNgU0yd1OoigcUjTiXyaqSGmtYNWqJGU2aZVNy5CSzIVOm5YhTRdLgv+Mnc+JxY3qG+PNi2dazGZPHnvTa3YWnDOP2a+4G/wCUWox3OoujbrUPvgWsa5rtGob5Dx2LG5U19jcUz7b7P3U5zgXsQwU65S1Emza6KT1o7dqVeIu/rt7pNu1HbL5XXQ+J26aevgn28IEOW7qubnp2OGQssY6ba2EXM/NBmakd3mxuNErnzYV0ruXFukHwyoLOyAAAGC16A8AACg8m9yd1tIhxx7pqcVwm9m3ab3GAxXQmve/vqZR9Y3xtMczjzt1gcPmwrCztY33mFMKjjaLZ6bMJrXpkZ7ah9qmCO8cd1offMuWIetrG1UXM5u2tSvuVjlec7BYZ16c1WahUtsLNamLs9osntk07uYZ/NWWf0c7j72htqldiXOfvsdN6e2eiJdtrNMv1Ngtzlpts3hm2vuPZTE8cWdK6h0LlhceNtQ2qtbqTovUtRKai/DZYp3aj97m3CxPiXUhMK2qHZn/9VqtrW6QJO26ZR8VZbkSDAAAWp9ztkOQ20oBAEBh2eTu1KKOswaUbSZqaVFEoZBkTG5FsETRqKa+UTUNdrN+nQWl1VV1jjFbzkh3tHYJVBh2PCe1R3r2hV3dx42Em2se2X5OpcXh5lg3xFJ6Mtu1Z7HpySy5Y7q6qj5tn/7HdffATvb8trxYUpMy4zhbvPLpkV5S1Bzrpl7jljPSHe1ZahtsZ/837995XttetHD2SLfu+V0fc72HZHsfKEv5fXLOyM52bpYUhRUONc0Kr66PqbbR7k5YZ6xd53WQ34mSDO8htuemo0d6oOP6LDZqd2cKM9K7vJcWrUz+e3faugAA0C7U1LPYKAAAHYlN7nb3VU5t++FfFAqHQ8kF/6rTejJn/5sh0W+6uiGmDbW59e2WpO82OIpgWXoyp25bXd+YjFf+fahtFxkMPhM1FAolX1t1Wq/x4O1Zqutj2mjRO1tyx9QVa8ufk3PWcJBtXbGuSyk42vTetrxbIhQKOVqGpPZIDz7umoaYNlr8PqU+xxnrMsvz2nluBrloUZYy+981qzzLsVNn/7vOzSzrHYRCIce52ahq13uXXayt30PyOK9Tz0271lIpd6bk3L+fHuld3kuO/ui7b8VCowAAtAc1m2aGlBaHFQn736oIAAAKzyZ3p7YbsW2P4GzPYrN4ZtP+m55jjLTGOdPZcma4qwhm0V9dkjbWNSZnlVv3oXbMJi0pChLr1NYbwdtnSM1xSV0UNljLEMdM542Ws28dsV7l2DbYmN09+KstZu662340F4ZLisJZOxiktcKxaFUiOWbwp/VIt+uf/X1N8F7jTcf1Pq+DzM52txuxjHVKX/jEuRkNEOvUFjz26x003y1RYzmD3/nzsD2vnXGxjXXquWmz2HGFqwVP87kZjYRdd05kG3MNM9K7tu821OnDpeskSdsO6qF+PUoLPCIAACDJcVsos9EBAOgIErnbutCZR3uW1N7btjMz3QVau9m3tsVdZyFrXU2DNrX8tp4xXOW48GBb6EzvJR282JnWtzufWFu2onBuG6xA23zctTX1isVN2niCHNd5bgaJdZnfjHSLIn5Tb3bLliGO17ZmU/tiyf7cdMXaskC7rqZBjVax9i6G2/4uVtc12q93kIh1Xepio/m8D9idm7axdj5nXU2DGhLrBtjOSHcW4YOcW8Xu34lCoJDeTjw+f2ny37tvzWx0AADaixqLhXcAAEDhJXJ3kDYU0UhYRZtmUtekzSa1axlSk2MRXpJWbXT23rYrsrq2tSx0OrfNqUe6RR/qaFFYxZGmWFc3NMq6V7kr1rnN+pXsY+2eke6IVx4/J9tCZ42jkB6kzUm0KKzoptm9qX2oA7U6KU7070/pR2/ZP3tNdW4L8Er252ambW1/F5396IOcH8URd6xd6x1YnJs1DTFXId32zhT3+4DdRUTreGWKdR490oOcW0WRsKJFiVjT2qXLemDeEl325ILk14krlAAAoPCqLW53BgAAhWeTu0OhULLgXuUooIVCci0amEmiKFTXGNf6mgbH43ZFVvve2xlau2Tpyex33CAXHtL7UAcvpEvNBdrquuaLFqFQUxueoMeub4xrnSvWecQrSD/oDL2kg8Ur03EtZ6Q7WqwEKc46x1ftmFUeNNaJY9TH4lpbbVdkdfYbX13VMr8Ttj3SXa1KAvVIT10rIXirEqm5gFxd756RXloUfNwNMaP1ln3Oy/J5D8nYI73t3rucLbGC/D5JzRdqnOtZtCUK6QW2fF2NznvkQ9djf/3PF1q+rqZAIwIAAAmxuFFd46bbQgN+aAEAAIWTS+5OFNqq62KuBQpDoexro2SccZxHP+hgM1Ez9Te2PG4eLWU21Db3Vw/aAq+5ZUhze5bAsc40+9ZylrRt4c8V6zx6pFsXHB2vd2Od3SzppvFtukBU19hcGC6OBDyvc5/p7Iz1akdrF9tWOPbndR4/Y+e6AbWNyYtxQV6vc3tnW5jyaEThAOsrOWPtipdFuyPJ/uJBeYZ1FgLFOtMaDZbte1ztoYJetHAs0lwITK0qsC9XVSl1AnrcSItXVWtgz7LCDAoAAEhSyoI/FNIBAGjvnLk76N1kiQJfVX2jEjXGoHk/c59hu4KjfY/0PI6bV0sZR//rKrsLB03bN88mjWwKdvBY594XvjzTgqH5tAyxLAzbHtc5CzunWDsWZ00s4hi4MJyhV3mgc9NxDGdrF9sLD/bndcvE+vvqeplNdbrgxd3Eed2YbPMS/OKSdysc237j1j3lC/TeVVoUUSjUtMiyM9ZB4+WMdSEwI73ANu9TodTrU5FQSCP6lBdkPAAAoJl7ESzmHwAA0N45c3fQVgHJHsX1zTPSA7d0yLQQpWULDOe2ti1WrBcKdLR/WWU5czcSDiVb3rjGHKClTNMxmmeTVln0V5fccWmpeNm2DLGNV8bjBox1og1LbrF2tBuptzuvncfIJ9ZrLGdY5/X7VJx7rMPhUHJ72+M6n1fd4J6RHoQz1s545fc+YNu/3/a9K1Ossx8371iXNL+HxE3bt8amkF5gA3uW6QfDeyW/DoekKw4Zy2x0AADagSrX4krMSAcAoL3LJXcnik6NcaMNyUK63Wx2SVq9adZwNBJOzgD2U+GxrWQ/E9W5bbCWIc5Cp92Cjs7nrc5jRnosbrS+tmHTY3btM5zHLo6EkosP+m+bIdaWM9LXVOe+KKz7Z2x3x0M+sY4bJXvK5zJLOnHsonAoOdvaf8zN267NY7FR93ltNyM9p1hves22x3U+zxhpbTLWdseVmuPlvGDle9wMr9l20U/rWGf4Odm+57rHbNeyyJimtSnaGlOr2oE1jjelOedM1fDNKgo8IgAAIDXNTEsI+scdAAAonFxyt7P4k2zpYNlf3blt0N7s5R7bBt3eOT7ntkEKw15jbhpP8ALtmqrUbe2K8M5jB29Vkv6abQudzm2lYIW/jLG2LO7mEq/ykohW5xprj9dsW+h0blsete+v7pwvnM+5adsjPadYR4sk1VsfN/V5zed1Dudm8rFgsfZ672p6PPdzM1iP9AyxtmgdtGqj/e+i5P451zS0fSGdGekFtmpjnb5cVSVJGj+0kiI6AADtSOI2WEmule0BAED7lEvu9ir+5FKgTQjamz1T4ch2Rrr78QA9iovD8qrRBR+312u2L4I1P9b6x81UHAxS+MsY6wAFx5KisLzWm8zlQk3zY3mc1zlcXEo+lkN/ddexLe+WcG+b/dglRWFFPIJtO4Pf9riZnpdL7//mx3I/rmQ/Iz3IPp2ikbCKvGKdw4Uam+OmPo9Cehf0zlffJ/89ydHiBQAAFF41M9IBAOhQcsndXgX3XHqkJwTtzZ7pebZ9u92PZ3/NoVDI8zXnM+584tU2sfaOS36xzr5tKBTy/JkE6SXd9Lw84uV1Xge8uOR13HxjbdsKJ8jjTpnPa7ue8rbHzXfblv59koL9nPO5GBcKhfI6R/KJl/PCiPP9vq1QSC+wdx2F9IkU0gEAaFeqHAuW0SMdAID2L5fc7TXTNpce6S1x3LLiiMJeU5jTjpF7EUzyvsiQSxsLv/15HreFZqI2jyX3Gdalxd4zmNO39T5G8FnDeZwjXvEKGmvPn1Pu52Y+d1pkmi2eKtO5EDjWLfz72CZ3pnjeOZD772K0KKyiAL3sMx0jvztT8rhokUNLrA43I722tralxtFlve0opP+AQjoAoJWRu+3UNDAjHQDQ8XTlfJ9L7vYsdObReiN48S3342aa+ZlPYTm/omHuhb+8Cvh5tJIIWvTLFOvgM2hb+BzJowifV6Ezn1jn8bsoWRSWC/T76H1xqTAtZQK3V8kwaz3wuPO5UNNC52aHKKTH43FdeumlGjx4sLp166YvvvhCknTBBRfo9ttvb/EBdma1DTF9+M06SdLmfSrUp1tJgUcEAOiMyN25q6pzfBinRzoAoB0j3zfJJXe3dKEzeG/k3I8bLQqrOJI+w7ctCsstXYQP3g6iMDNgo0VhRT1m+OZTHA5eoM29LUw+hc68Zv/nccGjOBJWtMgj1vm85jb4ffQ6h9tizYF8xlwUCavEI9b5xKutL9Q4L5y2FetC+mWXXaZZs2bp6quvVjQaTT4+duxY/e1vf2vRwXV2Hy1bp/pY09UT2roAAFoLuTt31Y4Fy4J+4AEAoBDI901yyd1efbLzKUjnMxM+6HG9jh0OybMwFvTY+fTAzqencz7Ft8BFeK8Ca3Hwuw1TjxPKM9b59M/OZ8Zx0NfsdYy26KHv9dxQqKkNT6BtPV5fPnd55FNUzq9feOv30Pd6bigklRa1QW93zwse9hdqOsSM9Lvuukt//etfdcwxxygSaR78+PHjtXDhwhYdXGf39mL6owMAWh+5O3euBcsC/nEHAEAhkO+b5JK782oZkkdPZq+Cu00RLPU4FdEihULZ+1BnOnbwdja590j3nkHb+kV4717j+cQ6EjzWecwazifW+fyMPbdtg1nSXtuXF1vEOq8CbYEuEOVx3HzWK2g6Tnqsg6zRILXC+0AOd0tU13eAQvrSpUs1atSotMfj8bgaGhpaZFBdhbM/+iQK6QCAVkLuzp3zwzgz0gEA7Rn5vkkuuTu/RSzzaAfhMWM46HGl9KJVPoVhyaI9Sx5FVs8LD4FbhuRefPOMtUVxNy3WNoVhz4stbdCPvqUL+Hmd17nPkrYpDLd0u5G2ODe9Yh30uKVFEaVeYwh6fjQdJ/dY5/U+0EI/p9rGDtDaZcyYMXrllVfSHn/44Ye1/fbbt8igugJjjN7dVEjvWVasLfp2K/CIAACdFbk7d84P42UWt/8CANDWyPdNcsnd+S1imfu2kXAoreiYT1sGq8JwHjPD8ymyFmpGejjPWKe+5nxa8EjB2354nZv5tLPJp81J0G3D4VB6MTyPixY2heF82v/kc27m0yM9nxnp4XAorYWPVaxTZ6Tn8Tthc+z8eqQ3P68QM9KtPxFeeOGFOu6447R06VLF43E98sgjWrRoke666y7Nnj27NcbYKS1eXa3VVfWSpB8Mqwx86wQAALbI3bmrqqNHOgCgYyDfN8kld3sV3PMqCFnOvnUumGdXBHMfJ2jB0GvbaCSkYo8FNYNsm+kxL959lVt/oVKp6Xxwxzr4tqnHyeeCR3Ek5Lmgpvdx85i56zEz3Gu2uJd827OURyMpbZYs4lWcel7n/jthF+uWvUAU+IJHHms0NB2nSFW5xjqfCx4pzy0KB491XovCOi48dIge6QceeKCeeOIJPf/886qoqNCFF16oBQsW6IknntDee+/dGmPslN5evCb570kjehdwJACAzo7cnbtcP9gCANDWyPdNcsnd3q037Is6zdvazL7NZ5Z06szdfI6b52z2wG0s8mkHkfvPqWn71FY4efTtzmvWr81xc79Q43luBu6vnl9xN6/XnHJsq59xi7fgaYse6bkX8CWPeFldyGu52f/5vHdJFuem4zjO9/u2ktMnwl133VXPPfdcS4+lS3l3CQuNAgDaDrk7N1V1uc3uAACgEMj37tydT4/0oEXWkqKwwiEpbpz7y6MY3mY90vPYNp+e33ksjlhSFFYkHFLMEWy7hRVbrkBrU6z0Wqg08HFbuOd30HMzGgmrKBxSoyPWdq2DWu41213waNlYB148M48e6Z6xzqMYnk8R3irWab8TuZ8fmR7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\n" | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
| "<Figure size 1200x800 with 1 Axes>" | |
| ], | |
| "image/png": 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| |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Mathematical Analysis:\n", | |
| "==================================================\n", | |
| "Update rule: w_new = w - lr * 2 * (w*x - y_true) * x\n", | |
| "Rearranged: w_new = w(1 - 2*lr*x²) + 2*lr*x*y_true\n", | |
| "\n", | |
| "For convergence: |1 - 2*lr*x²| < 1\n", | |
| "This gives us: lr < 1/(2*x²)\n", | |
| "\n", | |
| "x = 9: Critical lr < 0.00617, Current lr = 0.001\n", | |
| " Convergence factor = 0.838 (Stable)\n", | |
| "\n", | |
| "x = 10: Critical lr < 0.00500, Current lr = 0.001\n", | |
| " Convergence factor = 0.800 (Stable)\n", | |
| "\n", | |
| "x = 11: Critical lr < 0.00413, Current lr = 0.001\n", | |
| " Convergence factor = 0.758 (Stable)\n", | |
| "\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Let me explain what's happening in this gradient descent analysis step by step.\n", | |
| "\n", | |
| "### The Problem Setup\n", | |
| "\n", | |
| "We're trying to learn a single weight `w` in the equation `y = w * x` to predict a target value `y_true = 10`. The loss function is mean squared error: `loss = (w*x - y_true)²`.\n", | |
| "\n", | |
| "### The Mathematics Behind Convergence\n", | |
| "\n", | |
| "The gradient descent update rule is:\n", | |
| "```\n", | |
| "w_new = w - lr * gradient\n", | |
| "gradient = 2 * (w*x - y_true) * x\n", | |
| "```\n", | |
| "\n", | |
| "This can be rearranged into a linear recurrence relation:\n", | |
| "```\n", | |
| "w_new = w(1 - 2*lr*x²) + 2*lr*x*y_true\n", | |
| "```\n", | |
| "\n", | |
| "This is the key insight! The term `(1 - 2*lr*x²)` acts as a **contraction factor** that determines whether the algorithm converges or diverges.\n", | |
| "\n", | |
| "### Stability Analysis\n", | |
| "\n", | |
| "For the algorithm to converge, we need the contraction factor to have absolute value less than 1:\n", | |
| "```\n", | |
| "|1 - 2*lr*x²| < 1\n", | |
| "```\n", | |
| "\n", | |
| "This gives us the critical condition: **lr < 1/(2x²)**\n", | |
| "\n", | |
| "Let's see what this means for different scenarios:\n", | |
| "\n", | |
| "#### Case 1: Stable Convergence (lr = 0.001, x = 9,10,11)\n", | |
| "\n", | |
| "- **x = 9**: Convergence factor = 1 - 2(0.001)(81) = 0.838\n", | |
| "- **x = 10**: Convergence factor = 1 - 2(0.001)(100) = 0.800 \n", | |
| "- **x = 11**: Convergence factor = 1 - 2(0.001)(121) = 0.758\n", | |
| "\n", | |
| "All factors are between -1 and 1, so all converge! Notice that x=11 has the smallest factor (closest to 0), so it actually converges **fastest**.\n", | |
| "\n", | |
| "#### Case 2: What Happens with Different Learning Rates (x = 10)\n", | |
| "\n", | |
| "- **lr = 0.001**: Factor = 0.800 → Smooth exponential convergence\n", | |
| "- **lr = 0.005**: Factor = 0.000 → Converges in exactly one step!\n", | |
| "- **lr = 0.01**: Factor = -1.000 → Critical case, oscillates between two values\n", | |
| "- **lr = 0.011**: Factor = -1.200 → Unstable oscillation with growing amplitude\n", | |
| "- **lr = 0.015**: Factor = -2.000 → Strong divergent oscillation\n", | |
| "- **lr = 0.02**: Factor = -3.000 → Explosive divergence\n", | |
| "\n", | |
| "### Why This Behavior Occurs\n", | |
| "\n", | |
| "1. **Positive convergence factor (0 < factor < 1)**: The weight approaches the target from one side in a smooth exponential decay.\n", | |
| "\n", | |
| "2. **Zero convergence factor**: The algorithm finds the exact solution in one step because the update perfectly cancels the current error.\n", | |
| "\n", | |
| "3. **Negative convergence factor (-1 < factor < 0)**: The weight oscillates around the target but still converges, with the oscillation amplitude decreasing each iteration.\n", | |
| "\n", | |
| "4. **Factor = -1**: Perfect oscillation - the weight bounces between two values forever.\n", | |
| "\n", | |
| "5. **Factor < -1 or factor > 1**: The oscillations or deviations grow larger each iteration, leading to divergence.\n", | |
| "\n", | |
| "### The Geometric Interpretation\n", | |
| "\n", | |
| "Think of the loss function as a parabola. The gradient descent is trying to slide down to the bottom:\n", | |
| "\n", | |
| "- **Small learning rate**: Takes tiny steps, always moves toward the minimum\n", | |
| "- **Optimal learning rate**: Takes the perfect step size to reach the minimum quickly\n", | |
| "- **Too large learning rate**: Overshoots the minimum and bounces back and forth with increasing magnitude\n", | |
| "\n", | |
| "### Practical Implications\n", | |
| "\n", | |
| "1. **The \"sweet spot\"**: For each input value x, there's an optimal learning rate around `lr = 1/(4x²)` that gives fastest convergence.\n", | |
| "\n", | |
| "2. **Input magnitude matters**: Larger input values require smaller learning rates. This is why feature scaling is important in machine learning!\n", | |
| "\n", | |
| "3. **The trade-off**: There's always a tension between convergence speed and stability. You want the largest learning rate that still guarantees convergence.\n", | |
| "\n", | |
| "### Why x=11 Converges Fastest\n", | |
| "\n", | |
| "This might seem counterintuitive, but with lr=0.001:\n", | |
| "- x=11 has convergence factor 0.758 (closest to 0)\n", | |
| "- x=10 has convergence factor 0.800 \n", | |
| "- x=9 has convergence factor 0.838 (farthest from 0)\n", | |
| "\n", | |
| "The closer the convergence factor is to 0, the faster each iteration reduces the error. It's like having a stronger \"pull\" toward the correct answer.\n", | |
| "\n", | |
| "This analysis reveals the fundamental relationship between learning rate, input scale, and convergence behavior in gradient descent - principles that apply to much more complex neural networks as well!" | |
| ], | |
| "metadata": { | |
| "id": "a-o5FgWFxNMp" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Vectors" | |
| ], | |
| "metadata": { | |
| "id": "WLAAyvatwApL" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "* $\\vec{x} = \\begin{bmatrix} 1 \\\\ 2 \\end{bmatrix}$\n", | |
| "* $\\vec{w} = \\begin{bmatrix} 1 \\\\ 1 \\end{bmatrix}$\n", | |
| "* $y_{\\text{true}} = 10$\n", | |
| "* Learning rate $\\eta = 0.1$\n", | |
| "\n", | |
| "We’re using a **single linear neuron without activation**, predicting:\n", | |
| "\n", | |
| "$$\n", | |
| "y_{\\text{pred}} = \\vec{w}^\\top \\vec{x}\n", | |
| "$$\n", | |
| "\n", | |
| "Loss:\n", | |
| "\n", | |
| "$$\n", | |
| "L = (y_{\\text{pred}} - y_{\\text{true}})^2\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### ✅ Step 1: Forward pass\n", | |
| "\n", | |
| "$$\n", | |
| "y_{\\text{pred}} = \\vec{w}^\\top \\vec{x} =\n", | |
| "\\begin{bmatrix} 1 & 1 \\end{bmatrix}\n", | |
| "\\begin{bmatrix} 1 \\\\ 2 \\end{bmatrix}\n", | |
| "= 1 \\cdot 1 + 1 \\cdot 2 = 3\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### ✅ Step 2: Compute error\n", | |
| "\n", | |
| "$$\n", | |
| "\\text{error} = y_{\\text{pred}} - y_{\\text{true}} = 3 - 10 = -7\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### ✅ Step 3: Compute gradient of loss w\\.r.t. weights\n", | |
| "\n", | |
| "The loss function:\n", | |
| "\n", | |
| "$$\n", | |
| "L = (y_{\\text{pred}} - y_{\\text{true}})^2\n", | |
| "= (\\vec{w}^\\top \\vec{x} - y_{\\text{true}})^2\n", | |
| "$$\n", | |
| "\n", | |
| "Use the chain rule:\n", | |
| "\n", | |
| "$$\n", | |
| "\\frac{dL}{d\\vec{w}} = 2 \\cdot \\text{error} \\cdot \\vec{x}\n", | |
| "= 2 \\cdot (-7) \\cdot \\begin{bmatrix} 1 \\\\ 2 \\end{bmatrix}\n", | |
| "= \\begin{bmatrix} -14 \\\\ -28 \\end{bmatrix}\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### ✅ Step 4: Weight update using gradient descent\n", | |
| "\n", | |
| "$$\n", | |
| "\\vec{w}_{\\text{new}} = \\vec{w} - \\eta \\cdot \\frac{dL}{d\\vec{w}}\n", | |
| "= \\begin{bmatrix} 1 \\\\ 1 \\end{bmatrix}\n", | |
| "- 0.1 \\cdot \\begin{bmatrix} -14 \\\\ -28 \\end{bmatrix}\n", | |
| "= \\begin{bmatrix} 1 + 1.4 \\\\ 1 + 2.8 \\end{bmatrix}\n", | |
| "= \\begin{bmatrix} 2.4 \\\\ 3.8 \\end{bmatrix}\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### ✅ Final Answer: Updated weights\n", | |
| "\n", | |
| "$$\n", | |
| "\\vec{w}_{\\text{new}} = \\boxed{\\begin{bmatrix} 2.4 \\\\ 3.8 \\end{bmatrix}}\n", | |
| "$$\n", | |
| "\n", | |
| "---\n", | |
| "\n", | |
| "### 🧪 Optional: Sanity check (new prediction)\n", | |
| "\n", | |
| "$$\n", | |
| "y_{\\text{pred,new}} = \\vec{w}_{\\text{new}}^\\top \\vec{x}\n", | |
| "= 2.4 \\cdot 1 + 3.8 \\cdot 2 = 2.4 + 7.6 = 10\n", | |
| "$$\n", | |
| "\n", | |
| "🎯 Now it matches the target exactly — perfect prediction after 1 update!" | |
| ], | |
| "metadata": { | |
| "id": "ML46NHafwD2V" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "I ranomly choose these X and W values and they luckly converge in one step! 😂" | |
| ], | |
| "metadata": { | |
| "id": "KMnI9lRswXGu" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Code to play with" | |
| ], | |
| "metadata": { | |
| "id": "5LwqXb63gtyn" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "id": "05v_YXg23jC1" | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "# Input data (x values)\n", | |
| "# x = np.linspace(-5, 5, 100) # shape (100,)\n", | |
| "x = 5\n", | |
| "# True outputs (ground truth)\n", | |
| "y_true = 12" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "What values should w and b learn to have?" | |
| ], | |
| "metadata": { | |
| "id": "tl-riMnx4sCS" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Initialize weights and bias\n", | |
| "w = np.random.randn()\n", | |
| "\n", | |
| "# Forward pass\n", | |
| "def predict(x):\n", | |
| " return w * x\n" | |
| ], | |
| "metadata": { | |
| "id": "0sGcfIAH3v8b" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Loss: mean squared error" | |
| ], | |
| "metadata": { | |
| "id": "l82yCS3519SJ" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "def loss(y_pred, y_true):\n", | |
| " # return np.mean((y_pred - y_true) ** 2)\n", | |
| " return np.mean((y_pred - y_true) ** 2)" | |
| ], | |
| "metadata": { | |
| "id": "UBlQyI-q6TJK" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Loss: mean error" | |
| ], | |
| "metadata": { | |
| "id": "2gzvOCHk_e--" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "def loss(y_pred, y_true):\n", | |
| " # return np.mean((y_pred - y_true) ** 2)\n", | |
| " return np.mean(y_pred - y_true)\n", | |
| "\n" | |
| ], | |
| "metadata": { | |
| "id": "-vQBBZtC_gza" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "w = np.random.randn()\n", | |
| "b = np.random.randn()\n", | |
| "\n", | |
| "lr = 0.01 # learning rate\n", | |
| "for epoch in range(100000):\n", | |
| " y_pred = predict(x)\n", | |
| "\n", | |
| " if epoch % 50 == 0:\n", | |
| " error = y_pred - y_true\n", | |
| " print(f\"Error: {error}\")\n", | |
| "\n", | |
| " error_times_x = error * x\n", | |
| "\n", | |
| " sum_gradient = np.sum(error_times_x)\n", | |
| "\n", | |
| " # Update weights\n", | |
| " grad_w = 2 * sum_gradient\n", | |
| "\n", | |
| " # Print progress\n", | |
| " if epoch % 50 == 0:\n", | |
| " print(f\"Epoch {epoch}, w={w:.4f}\")\n", | |
| "\n", | |
| " # Exit if w ≈ 2 and b ≈ 3\n", | |
| " if np.isclose(w, 2.0, atol=1e-2):\n", | |
| " print(f\"Stopped early at epoch {epoch}: w ≈ 2\")\n", | |
| " break" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "99uo5dlx6nDi", | |
| "outputId": "8a846dd6-be08-42e1-fbbf-741f004022c6" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Error: -6.279040142500316\n", | |
| "Epoch 0, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 50, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 1950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 2950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 3950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 4900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 5000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 5650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 5900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 6000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 6950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 7950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 8950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 9950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 10950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 11950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 12950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 13950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 14950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 15000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 15050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 20650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 20700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 20850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 20950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 21400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 21500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 21950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 22950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 23950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 24950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 25000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 25050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 25100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 25150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 25200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 25250, w=0.7442\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 35000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 35050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 35100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 35150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 35200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 35250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 35300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 35350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 35400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 39300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 39900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 40000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 40050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 40200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 40250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 40500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 40550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 40650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 40700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 40800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 40850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 40900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 40950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
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| "Error: -6.279040142500316\n", | |
| "Epoch 41200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 41950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 42950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 43950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 44950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 45950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 46950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47200, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47250, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47300, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47350, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47400, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47450, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47500, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47550, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47600, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47650, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47700, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47750, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47800, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47850, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47900, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 47950, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 48000, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 48050, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 48100, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 48150, w=0.7442\n", | |
| "Error: -6.279040142500316\n", | |
| "Epoch 48200, w=0.7442\n", | |
| "Error: -6.27904014250031 |
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