Deep_Learning_Well_Log.ipynb

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    "colab": {
      "name": "Deep Learning Well Log (1).ipynb",
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      "include_colab_link": true
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/prateekvyas1996/gpg/blob/master/Deep_Learning_Well_Log.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5AS2lCS9RxRg",
        "colab_type": "text"
      },
      "source": [
        "## Introduction\n",
        "Well logs are the data that are collected in the oil and gas wells or experimental wells called wildcat wells. These data are actually reading of different sensors which are collected by dropping the sensors in the well and continously collect and save the data. There are 100's of types of data collected from well including Resistivity, Spontaneous potential, Gamma ray, Neutron porosity, Bulk density and many more. \n",
        "\n",
        "### Why use deep learning for well log\n",
        "when we take the data from the wells using sensors, sometimes due to malfunctioning or due to some man made errors, the sensor is not able to detect the data for some section of depth. But for a particular depth for which some data are missing, some other data could be available. We can use the data to predict the messing datas or we can correct some erroneous data also, we will see how to do it later in notebook.\n",
        "\n",
        "To do so we have to use available data to train a deep learning model and then use that model to predict the missing and erroneous data.\n",
        "\n",
        "### How to build deep learning model\n",
        "\n",
        "We are going to use PyTorch, a deep learning framework (A framework is a collection of prebuild codes that we  can use without knowing what is happening under the hood) maintained by Facebook A.I. and is opensource. We can use it free of cost and can share it with anyone. You can modify and use the same codes for your own applications. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wegytsv7RxRg",
        "colab_type": "text"
      },
      "source": [
        "## Exploratory The Data\n",
        "To begin with the project, first import libraries and define functions for plotting the data using `matplotlib`. You can also use seaborn."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_kg_hide-input": false,
        "trusted": true,
        "id": "YIOZuiRYRxRh",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from mpl_toolkits.mplot3d import Axes3D\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "import matplotlib.pyplot as plt # plotting\n",
        "import numpy as np # linear algebra\n",
        "import os # accessing directory structure\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UzlXkgyjRxRl",
        "colab_type": "text"
      },
      "source": [
        "There is 1 csv file in the current version of the dataset: The below code will tell all the available dataset\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_kg_hide-input": false,
        "trusted": true,
        "id": "0KBQAF1rRxRm",
        "colab_type": "code",
        "colab": {},
        "outputId": "1c0a5f21-9204-4062-b1b1-d3105f970bf7"
      },
      "source": [
        "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
        "    for filename in filenames:\n",
        "        print(os.path.join(dirname, filename))\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/kaggle/input/log.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eaYLKKXaRxRr",
        "colab_type": "text"
      },
      "source": [
        "The next hidden code cells define functions for plotting data. Click on the \"Code\" button in the published kernel to reveal the hidden code."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_kg_hide-input": true,
        "trusted": true,
        "id": "YegiebfHRxRr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Distribution graphs (histogram/bar graph) of column data\n",
        "def plotPerColumnDistribution(df, nGraphShown, nGraphPerRow):\n",
        "    nunique = df.nunique()\n",
        "    df = df[[col for col in df if nunique[col] > 1 and nunique[col] < 50]] # For displaying purposes, pick columns that have between 1 and 50 unique values\n",
        "    nRow, nCol = df.shape\n",
        "    columnNames = list(df)\n",
        "    nGraphRow = (nCol + nGraphPerRow - 1) / nGraphPerRow\n",
        "    plt.figure(num = None, figsize = (6 * nGraphPerRow, 8 * nGraphRow), dpi = 80, facecolor = 'w', edgecolor = 'k')\n",
        "    for i in range(min(nCol, nGraphShown)):\n",
        "        plt.subplot(nGraphRow, nGraphPerRow, i + 1)\n",
        "        columnDf = df.iloc[:, i]\n",
        "        if (not np.issubdtype(type(columnDf.iloc[0]), np.number)):\n",
        "            valueCounts = columnDf.value_counts()\n",
        "            valueCounts.plot.bar()\n",
        "        else:\n",
        "            columnDf.hist()\n",
        "        plt.ylabel('counts')\n",
        "        plt.xticks(rotation = 90)\n",
        "        plt.title(f'{columnNames[i]} (column {i})')\n",
        "    plt.tight_layout(pad = 1.0, w_pad = 1.0, h_pad = 1.0)\n",
        "    plt.show()\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "_kg_hide-input": true,
        "trusted": true,
        "id": "hCpthcJuRxRu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Correlation matrix\n",
        "def plotCorrelationMatrix(df, graphWidth):\n",
        "    filename = df.dataframeName\n",
        "    df = df.dropna('columns') # drop columns with NaN\n",
        "    df = df[[col for col in df if df[col].nunique() > 1]] # keep columns where there are more than 1 unique values\n",
        "    if df.shape[1] < 2:\n",
        "        print(f'No correlation plots shown: The number of non-NaN or constant columns ({df.shape[1]}) is less than 2')\n",
        "        return\n",
        "    corr = df.corr()\n",
        "    plt.figure(num=None, figsize=(graphWidth, graphWidth), dpi=80, facecolor='w', edgecolor='k')\n",
        "    corrMat = plt.matshow(corr, fignum = 1)\n",
        "    plt.xticks(range(len(corr.columns)), corr.columns, rotation=90)\n",
        "    plt.yticks(range(len(corr.columns)), corr.columns)\n",
        "    plt.gca().xaxis.tick_bottom()\n",
        "    plt.colorbar(corrMat)\n",
        "    plt.title(f'Correlation Matrix for {filename}', fontsize=15)\n",
        "    plt.show()\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "_kg_hide-input": true,
        "trusted": true,
        "id": "t74ADyVBRxR1",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Scatter and density plots\n",
        "def plotScatterMatrix(df, plotSize, textSize):\n",
        "    df = df.select_dtypes(include =[np.number]) # keep only numerical columns\n",
        "    # Remove rows and columns that would lead to df being singular\n",
        "    df = df.dropna('columns')\n",
        "    df = df[[col for col in df if df[col].nunique() > 1]] # keep columns where there are more than 1 unique values\n",
        "    columnNames = list(df)\n",
        "    if len(columnNames) > 10: # reduce the number of columns for matrix inversion of kernel density plots\n",
        "        columnNames = columnNames[:10]\n",
        "    df = df[columnNames]\n",
        "    ax = pd.plotting.scatter_matrix(df, alpha=0.75, figsize=[plotSize, plotSize], diagonal='kde')\n",
        "    corrs = df.corr().values\n",
        "    for i, j in zip(*plt.np.triu_indices_from(ax, k = 1)):\n",
        "        ax[i, j].annotate('Corr. coef = %.3f' % corrs[i, j], (0.8, 0.2), xycoords='axes fraction', ha='center', va='center', size=textSize)\n",
        "    plt.suptitle('Scatter and Density Plot')\n",
        "    plt.show()\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ogCh-ptRRxR7",
        "colab_type": "text"
      },
      "source": [
        "Now you're ready to read in the data and use the plotting functions to visualize the data."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xCazevIdRxR8",
        "colab_type": "text"
      },
      "source": [
        "### Plot first 1000 data of file /kaggle/input/log.csv"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_kg_hide-input": false,
        "trusted": true,
        "id": "MKznVhSzRxR9",
        "colab_type": "code",
        "colab": {},
        "outputId": "9f7ba1c5-4a9a-4c99-faad-f41cc8bab872"
      },
      "source": [
        "nRowsRead = 1000 # specify 'None' if want to read whole file\n",
        "# log.csv may have more rows in reality, but we are only loading/previewing the first 1000 rows\n",
        "df1 = pd.read_csv('/kaggle/input/log.csv', delimiter=',', nrows = nRowsRead)\n",
        "df1.dataframeName = 'log.csv'\n",
        "nRow, nCol = df1.shape\n",
        "print(f'There are {nRow} rows and {nCol} columns')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "There are 1000 rows and 14 columns\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xX5bhSavRxSB",
        "colab_type": "text"
      },
      "source": [
        "Let's take a quick look at what the data looks like:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_kg_hide-input": false,
        "trusted": true,
        "id": "0J7uTF0jRxSC",
        "colab_type": "code",
        "colab": {},
        "outputId": "e2784aa2-a580-4144-fdc1-51efd57d2f86"
      },
      "source": [
        "df1.head(5)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Depth     RxoRt    RLL3       SP      RILD      MN      MI    MCAL    DCAL  \\\n",
              "0  195.0  226.0848  0.4076  69.8953  132.5052 -0.3548  0.1863  5.1090  1.8878   \n",
              "1  195.5  223.5031  0.4063  69.2303  123.6225 -0.3619  0.1867  5.1031  1.8882   \n",
              "2  196.0  221.4560  0.4047  68.4478  116.9258 -0.3668  0.1860  5.0872  1.8878   \n",
              "3  196.5  219.8248  0.4033  67.4843  111.7925 -0.3613  0.1867  5.0881  1.8884   \n",
              "4  197.0  218.1438  0.4023  66.3013  106.7821 -0.3569  0.1870  5.0972  1.8883   \n",
              "\n",
              "     RHOB    RHOC     DPOR     CNLS       GR  \n",
              "0  1.6973 -0.6303  59.2216  30.0657  60.4576  \n",
              "1  1.6791 -0.6409  60.2877  26.7625  54.1495  \n",
              "2  1.6585 -0.6539  61.4914  27.6017  51.9944  \n",
              "3  1.6435 -0.6649  62.3711  31.5870  52.9645  \n",
              "4  1.6390 -0.6705  62.6343  35.8251  54.9659  "
            ],
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Depth</th>\n",
              "      <th>RxoRt</th>\n",
              "      <th>RLL3</th>\n",
              "      <th>SP</th>\n",
              "      <th>RILD</th>\n",
              "      <th>MN</th>\n",
              "      <th>MI</th>\n",
              "      <th>MCAL</th>\n",
              "      <th>DCAL</th>\n",
              "      <th>RHOB</th>\n",
              "      <th>RHOC</th>\n",
              "      <th>DPOR</th>\n",
              "      <th>CNLS</th>\n",
              "      <th>GR</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>195.0</td>\n",
              "      <td>226.0848</td>\n",
              "      <td>0.4076</td>\n",
              "      <td>69.8953</td>\n",
              "      <td>132.5052</td>\n",
              "      <td>-0.3548</td>\n",
              "      <td>0.1863</td>\n",
              "      <td>5.1090</td>\n",
              "      <td>1.8878</td>\n",
              "      <td>1.6973</td>\n",
              "      <td>-0.6303</td>\n",
              "      <td>59.2216</td>\n",
              "      <td>30.0657</td>\n",
              "      <td>60.4576</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>195.5</td>\n",
              "      <td>223.5031</td>\n",
              "      <td>0.4063</td>\n",
              "      <td>69.2303</td>\n",
              "      <td>123.6225</td>\n",
              "      <td>-0.3619</td>\n",
              "      <td>0.1867</td>\n",
              "      <td>5.1031</td>\n",
              "      <td>1.8882</td>\n",
              "      <td>1.6791</td>\n",
              "      <td>-0.6409</td>\n",
              "      <td>60.2877</td>\n",
              "      <td>26.7625</td>\n",
              "      <td>54.1495</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>196.0</td>\n",
              "      <td>221.4560</td>\n",
              "      <td>0.4047</td>\n",
              "      <td>68.4478</td>\n",
              "      <td>116.9258</td>\n",
              "      <td>-0.3668</td>\n",
              "      <td>0.1860</td>\n",
              "      <td>5.0872</td>\n",
              "      <td>1.8878</td>\n",
              "      <td>1.6585</td>\n",
              "      <td>-0.6539</td>\n",
              "      <td>61.4914</td>\n",
              "      <td>27.6017</td>\n",
              "      <td>51.9944</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>196.5</td>\n",
              "      <td>219.8248</td>\n",
              "      <td>0.4033</td>\n",
              "      <td>67.4843</td>\n",
              "      <td>111.7925</td>\n",
              "      <td>-0.3613</td>\n",
              "      <td>0.1867</td>\n",
              "      <td>5.0881</td>\n",
              "      <td>1.8884</td>\n",
              "      <td>1.6435</td>\n",
              "      <td>-0.6649</td>\n",
              "      <td>62.3711</td>\n",
              "      <td>31.5870</td>\n",
              "      <td>52.9645</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>197.0</td>\n",
              "      <td>218.1438</td>\n",
              "      <td>0.4023</td>\n",
              "      <td>66.3013</td>\n",
              "      <td>106.7821</td>\n",
              "      <td>-0.3569</td>\n",
              "      <td>0.1870</td>\n",
              "      <td>5.0972</td>\n",
              "      <td>1.8883</td>\n",
              "      <td>1.6390</td>\n",
              "      <td>-0.6705</td>\n",
              "      <td>62.6343</td>\n",
              "      <td>35.8251</td>\n",
              "      <td>54.9659</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KbR1Jeb0RxSF",
        "colab_type": "text"
      },
      "source": [
        "Distribution graphs (histogram/bar graph) of sampled columns:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_kg_hide-input": false,
        "trusted": true,
        "id": "dPnkqlLnRxSG",
        "colab_type": "code",
        "colab": {},
        "outputId": "ff96ffd0-dab7-4c1b-da3d-4cfd998a4a5b"
      },
      "source": [
        "plotPerColumnDistribution(df1, 10, 5)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2400x512 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kQ4LsGSSRxSJ",
        "colab_type": "text"
      },
      "source": [
        "* Correlation matrix: This matrix will tell you how every parameter is related to another parameter, The color with value 1 are highly correlated while the color with negative numbers are negatively correlated (means when one parameter go up other parameter go down).\n",
        "\n",
        "It is a best practice to watch this data beacause it will help us to decide the input features for the specific model."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_kg_hide-input": false,
        "trusted": true,
        "id": "QBnYAUfcRxSK",
        "colab_type": "code",
        "colab": {},
        "outputId": "ee464f25-57ad-4da4-9762-91c993574c86"
      },
      "source": [
        "plotCorrelationMatrix(df1, 8)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x640 with 2 Axes>"
            ],
            "image/png": 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jcYIgQBTFErN7VqxYgcLCQqN9xWXKkyUovp8n73f9+vXIy8ur0v2a8t5776FPnz6Ij48vs0zxD+Mn73vZsmUlylbkvk1ZsWIF1q5diy+//BJbtmxBTk5OlX4odunSBampqUhJSTHav2bNGgiCgE6dOlW1yhWO1aFDB9y5cwfbt283KvfNN9+UK84rr7yCPXv2PLUL8XFOTk4YMGAAxo8fj5s3bxotSDdkyBA4ODhg1apVWLVqFRo2bIju3buX67qknEdv0ZV2swTMhDzn2rVrhyVLliAmJgYtW7bEuHHj0LRpU+Tn5+O///0vli9fjqCgIPTp0wdqtRpjxozBF198ASsrK7zyyiuG2TGNGjXCu+++W6W6LFu2DK+88gp69OiByMhINGzYEDdv3sTZs2eRkpKC7777rtTz6tSpg/bt22Pu3LlwcXGBSqXCzz//jMTExBILcwUFBQEAli9fjtq1a8PBwQE+Pj6ldqV069YNPXr0wOTJk3H79m289NJLhtkxwcHBGD58eJXu92m6d+9u8geNRqNBkyZNEBcXB1EUUbduXXz//ff497//XaJss2bNAAALFizAiBEjYGtrC7VaXWbDriynT5/GhAkTMGLECEPDIzExEQMGDMDnn39eqRVQ3333XaxZswa9evXCjBkz4O3tjR9++AGLFy/GuHHjyj1WxZyxRowYgfnz52PYsGGYOXMmfH19sX37dvz4448AYDTTa82aNYiKikJSUhLeeOMNAI9WuN2+fTvat2+PDz/8EM2aNUNOTg527NiB2NhYaDQa9OnTB0FBQWjVqhVcXV1x+fJlfP755/D29jaa8ePk5IT+/ftj1apVyMnJwcSJE43iEz3TlBwVS9XHyZMnxREjRoheXl6inZ2dWKtWLTE4OFj829/+Jl6/ft1QrrCwUPz0009Ff39/0dbWVnRxcRGHDRsmZmZmGl2vQ4cOYtOmTUvEKZ7hMHfu3FLrcerUKXHQoEGim5ubaGtrKzZo0EDs3LmzuHTpUkOZ0mbH6PV6MSIiQnR2dhZr164thoWFiWfOnCl1dsfnn38u+vj4iNbW1kYzHZ6cHSOKj2a4TJ48WfT29hZtbW1Fd3d3cdy4ceKff/5pVK60WR/Fz6FDhw6l3uvj8P+zY56mtBkuqampYrdu3cTatWuLzs7O4sCBA8WMjAwRgPjRRx8Znf/BBx+IHh4eopWVldHzK6vuxceKn19ubq6o0WjEwMBAMS8vz6jc+PHjRVtb2xKzTkq7XmmxLl++LL7++utivXr1RFtbW1GtVotz5841zIgSRdPfO6bqX5FYoiiKGRkZ4quvvio6OjqKtWvXFiMiIsRt27aVmHm0cuXKUmfMZGZmilFRUWKDBg1EW1tb0cPDQxw0aJD4+++/i6Ioip999pkYGhoquri4iHZ2dqKXl5c4atQoUafTlbiPnTt3inj0y7X422+/lfv+STkNGliJGfoGkm6WMDtGEEULGd1CRCSxWbNmYerUqcjIyDA5hoqeb+7u1jh63E3SGO3aWpsce1TdsTuGiKgUX375JYBH3V75+fnYvXs3Fi5ciGHDhrEBQuVSyF/xTWIjhIioFDVr1sT8+fOh0+nw4MEDeHl5YfLkyZg6darSVSOyGOyOISIiMjN3d2v855i03THtX3z2u2M4xJqIiIgUwe4YIiIiMxMBFKLyC+s9L5gJISIiIkUwE0JERCSBIo64NImNECIiIgmwO8Y0dscQERGRIpgJISIiMjMOTC0fZkKIiIhIEcyEEBERmZ2AIlHqTMizP/KVmRAiIiJSBDMhREREEpB+TAgzIURERESVwkwIERGRBAol/z2/SOLrS4+ZECIiIlIEMyFERERmJgIyzI559jETQkRERIpgJoSIiEgCXDHVNGZCiIiISBHMhBAREUmgUOTv+abwCREREZEimAkhIiIyMxECivh7vkl8QkRERKQIZkKIiIgkwNkxpllMI8TeToCri7Vs8a7nOMoWq5ggyvuyItFK3n9ASozhsqlRIGs8UebFiwry5fs3UaxejVxZ493Mk//fIuzkXS5b7u8bIV+BH5628v3/VnA7D2K+vP/2qXQW0whxdbFGRoqPbPFCY8fKFquY3Z1CWePdqyvvt8c9N/n/42scflHWePcKbGWNl3bKU9Z4ALC+/wJZ4w1b9q6s8QBAaJsja7x79+xkjWd/uqas8QCgKOSObLEujflMljicHWManxAREREpwmIyIURERNVJEceEmMRMCBERESmCmRAiIiIzEwEU8vd8k/iEiIiISBHMhBAREUmAs2NM4xMiIiKyYBcuXEBoaCj8/f3Rpk0bpKamliizZs0aaLVaw+bi4oJXX30VAKDT6WBjY2N0/OJF8yxvwEwIERGR2VWfd8dER0djzJgxiIyMRHJyMkaNGoVDhw4ZlXnjjTfwxhtvGD43a9YMQ4cONXx2cnLCyZMnzV63cj0hlUoFjUaDFi1awM/PD3379sXBgwerFHjTpk04evSo4fPevXvRqlWrKl2TiIiI/uf69etISUnBsGHDAAARERFIT0+HTqcr85yjR4/i999/R3h4uOT1K3czLTk5GadOncKFCxcQFRWFnj174siRI5UO/GQjhIiIyFKIIlAoCpJu5ZGZmQkPDw/Y2Dzq+BAEAV5eXsjIyCjznMTERAwfPhy2tv9b4fn27dto3bo1QkJCMGPGDBQWmmcF70rlivr27YuYmBjMmzcP+fn5iIuLQ5s2baDVajF48GDk5Dxa0jgyMhJvvvkmunTpAo1Gg8jISDx48ADbtm3Dli1bMHv2bGi1WqxYsQIAUFBQgJiYGLRo0QJNmzbF8ePHzXKTREREciuElaRbbm4uPD09DVtCQkKp9RAE4waL+JT3kN29exfffvstRo0aZdjn7u4OvV6PY8eOYdeuXdi/fz8++8w8S99XusOqdevW+PXXXzF37lw4Ojri6NGjOHnyJJo2bYqPPvrIUO7IkSPYvHkzfv31V9y8eRMLFixAz549ER4ejri4OJw8eRKjR48GAPz666+IiorCqVOn8NZbb2HKlClVv0MiIiIL5OjoCL1eb9hiY2NLlGnUqBH0ej0KCh69sE8URWRmZsLLy6vUayYnJyMgIACBgYGGffb29nBzcwMA1K1bF1FRUdi/f79Z7qHSjZDiltSmTZuwdu1aw4jZdevW4dKlS4Zyr732GhwdHWFtbY2oqCjs2rWrzGuq1WrDuJB27do9dfRtQkKCUQswN1feN8wSERE9TZFoJelWHm5ubggODsbatWsBAOvXr4dKpYJKpSq1fFJSklEWBHg0riQ/Px8A8ODBA2zYsAHBwcGVfzCPqfTsmGPHjiEoKAjp6elYvHgxOnfuXK7znkwLPc7BwcHwtbW1taHlVprY2FijVp+nByf6EBERPWnZsmWIjIzErFmzUKdOHaxevRoAMHr0aISHhxsGoF68eBEnTpzA999/b3T+gQMH8Le//c3wc7lz585m66mo1E/uzZs3Y8mSJdixYwf+/e9/IyEhAS+++CJq1qyJu3fvIj09HU2bNgUAfPfdd3jnnXfg4OCAlStXomvXrgCAOnXq4NatW2a5CSIiouqkOi3brlarS0zJBWAYj1msSZMmuHPnTolyr776qmHNEHMr9xMaMGAAWrRoAV9fXyQmJmLbtm148cUXERcXB61Wi7Zt26J58+Z48cUXjeYSt2/fHv369UPTpk3h7OyMt956CwAwfPhwfP3110YDU4mIiOj5Ua5MyNPmE9va2mLmzJmYOXNmqcf9/f2xcOHCEvuLB7Y+7vHZMEFBQU+NS0REVJ2Vdxrt86x65IqIiIjouSPpaM5Vq1ZJeXkiIqJqqvos216d8QkRERGRIjivlYiISAKF5VzL43nGJ0RERESKYCaEiIjIzEQAReDsGFOYCSEiIiJFMBNCREQkAY4JMc1iGiHXcxwRGjtWtngHE5bKFquY5qsYWePti5ora7zRlyJkjQcAObNLf5OkVG4G2MoaD15F8sYDMGLBu/IGtJc3HAB4xebJGu+3j+1kjXfPs1DWeADg8oOjbLGE++wmqS4sphFCRERUnVSXd8dUZ3xCREREpAhmQoiIiMxOQBHfHWMSMyFERESkCGZCiIiIzEwEx4SUB58QERERKYKZECIiIgkUcZ0Qk/iEiIiISBHMhBAREUmgkO+OMYmZECIiIlJEuRshKpUKGo0GWq0WarUas2fPrnRQnU4HGxsbaLVatGjRAi1atMAPP/xgOL53717s3Lmz0tcnIiJSkohHY0Kk3CxBhbpjkpOTERQUhCtXriAwMBCdO3dGmzZtKhXYyckJJ0+eBABs27YNgwcPxp9//glra2vs3bsXubm56N69e6WuTURERNVfpZpSHh4eUKvVuHz5Mv75z3+iVatWePDgAURRRJ8+ffDpp58CAHbs2IGQkBA0b94cHTp0QGpqaqnX69SpE+7cuYObN2/i5MmTWLp0KdasWQOtVosZM2ZU/u6IiIgUUghB0s0SVGpg6rlz55CdnY2OHTvC1dUV+/btw3vvvQdvb28UFhZi0qRJuH79OoYNG4Y9e/agWbNm+Oc//4lBgwbhzJkzJa733XffoXPnznB1dYWrqyvGjh2L3NxczJs3r8o3SERERNVThRohAwYMgCAIOH/+PObPnw9XV1cAwMKFC9GmTRts2bIFKSkpEAQBR44cgVarRbNmzQAAQ4cOxfjx43H16lUAQE5ODrRaLW7evIns7Gzs3r27QhVPSEhAQkKC4XNRwYMKnU9ERCQdwWLGbUipQk8oOTkZZ8+exc6dOxEXF4fTp08DAK5fv44///wTRUVFyMnJAQCIoghBKJkuKt5XPCbk8uXLiIuLw+DBg3H//v1y1yU2NhZ6vd6wWdnYV+RWiIiIpCMChaKVpJslqNRddO3aFePGjcPUqVNRUFCA1157DX//+98xb948DBw4EA8ePEC7du1w8uRJnD17FgDwzTffwNPTEw0aNDC6liAIiI+Ph4uLC5YsWQIAqFOnDm7dulXFWyMiIqLqrNJNqfj4eBw4cADdunWDWq3GiBEjMHjwYLRt2xbvvPMOXF1d8Y9//ANDhw5FixYtsGTJEvzrX/8q9VqCIOCzzz7Dp59+irt376J///44fvw4B6YSEdEzSQRQBEHSzRKUe0yITqcz+uzs7IwbN26UKLd06VLD12FhYQgLCytRRqVSITs722hfhw4dcO3aNQCAj48P/vvf/5a3akRERPQM4rLtREREErCUcRtS4hMiIiIiRTATQkREJIEi0TLGbUiJmRAiIiJSBDMhREREZiZCQCF/zzeJT4iIiIgUwUwIERGRBDgmxDRmQoiIiEgRzIQQERFJoIi/55tkMY0QQRRhd6dQtniar2Jki1Xs3JuLZY0XsOx9WePddy+QNR4AOLSR95+A/U1ZwynC6aK8f4/ZkXmyxgMA657yvrW75saassa7o5X/reQ2923lCybKF4qezmIaIURERNVJIceEmMRcERERESmCmRAiIiIzE8HZMeXBTAgREREpgpkQIiIiCRTxLbom8QkRERGRIpgJISIikkAhOCbEFGZCiIiISBHMhBAREZmdwNkx5VDlTIhKpYJGo4FWq4Varcbs2bMBADqdDi4uLqWeIwgCcnNzS+zv3r07mjdvDq1Wi5dffhknT56savWIiIiomjJLJiQ5ORlBQUG4cuUKAgMD0blzZ7i5uVX4Ov/617/g5OQEANi0aROioqKQkpJijioSERHJirNjTDPrE/Lw8IBarcbly5crdX5xAwQAbt26BSsr/gUSERFZKrOOCTl37hyys7PRsWNH5OVV7qVSb7zxBvbs2QMA2LFjhzmrR0REJAsRQBFnx5hkllTDgAEDEBAQgMDAQEyYMAGurq6VvtaaNWuQmZmJmTNn4v33y36La0JCAjw9PQ1bYcHDSsckIiKyVBcuXEBoaCj8/f3Rpk0bpKamliizd+9e1KxZE1qt1rDdu3fPcHzr1q3QaDTw9fVFREREqeM6K8MsjZDk5GScPXsWO3fuRFxcHE6fPl3la44YMQJ79uzBjRs3Sj0eGxsLvV5v2Kxt7Kock4iIyFwKRUHSrbyio6MxZswY/Pbbb5g0aRJGjRpVarnAwECcPJOcIdIAACAASURBVHnSsNWoUQMAkJubi1GjRmHTpk1IS0uDu7s7Pv74Y7M8I7MOuujatSvGjRuHqVOnVvjc27dv48qVK4bPGzduRL169VC3bl1zVpGIiOi5cf36daSkpGDYsGEAgIiICKSnp0On05X7Gtu3b0erVq2g0WgAADExMVi3bp1Z6mf2dULi4+Ph6+uLGzdu4M8//4Snp6fhWKNGjXDo0CEAgFqthiD8ryV36NAhRERE4N69e7CysoKrqyu2bt1qVIaIiOiZIFaP2TGZmZnw8PCAjc2jH/eCIMDLywsZGRlQqVRGZc+fP4+QkBBYW1tj5MiRiImJAQBkZGTA29vbUE6lUiErKwtFRUVVnkBS5UbIk60pZ2dnQxdKYWFhqeeIoljq/qNHj1a1OkRERNWC1IuV5ebmGv2iHxsbi9jY2BLlnvxlvrSfwSEhIdDr9XjhhReg1+vRs2dPuLi4YNCgQaVew1y4YioREdEzyNHREXq9/qllGjVqBL1ej4KCAtjY2EAURWRmZsLLy8uoXJ06dQxfe3p6YsiQIdi/fz8GDRoELy8v7N6923Bcp9OhYcOGZllGQ/lcERERkYUpnqIr5VYebm5uCA4Oxtq1awEA69evh0qlKtEVc/XqVRQVFQEA7ty5g61btyI4OBgAEBYWhmPHjuHcuXMAgMWLF2Pw4MFmeU7MhBAREVmwZcuWITIyErNmzUKdOnWwevVqAMDo0aMRHh6O8PBwrF+/HkuWLIGNjQ0KCgowcOBAjBw5EgBQu3ZtrFixAv369UNBQQGaNWtmuEZVsRFCRERkdtXnBXZqtdowKeRxK1asMHz917/+FX/961/LvEZxY8Xc2B1DREREimAmhIiISALVYYpudccnRERERIpgJoSIiEgC1WVMSHXGTAgREREpwmIyIaKVgHt15budfVFzZYtVLGBZ2W8VlsLZ6MWyxmt5YpCs8QCg9vcvyBovu5mtrPGU+EUsx1fe/1bsfpL37xAACn56IGs867mlv8hTKuIV+Z9poa2M36wyhCpeJ4SejpkQIiIiUoTFZEKIiIiqE44JMY2ZECIiIlIEMyFEREQSYCbENGZCiIiISBHMhBAREUmAmRDTmAkhIiIiRTATQkREJAFmQkxjJoSIiIgUwUwIERGRmXHF1PJRLBOyYcMGtGzZElqtFgEBAejSpQuKiorQsWNHNG7cGFqtFhqNBlOnTlWqikRERCQhRTIh165dw9ixY3Hs2DF4e3sDAFJSUiAIj1qNCxcuRO/evZGTk4Pg4GC0bdsWffr0UaKqREREFScKHBNSDopkQq5evQobGxvUq1fPsC8kJMTQCCnm5OSE1q1b4/z583JXkYiIiCSmSCOkRYsWaNeuHby8vNC/f3/MnTsXWVlZJcrp9XocOHAALVu2VKCWRERElVf0/9kQqTZLoEgjxMrKCuvXr8fBgwcRFhaG//znP2jatCnS0tIAABMmTIBWq0X//v0RHx+PTp06lbhGQkICPD09DVtRvryv1iYiIqKqUXR2jEajgUajQXR0NMLCwrBlyxYA/xsT8jSxsbGIjY01fLar5SRpXYmIiCrCUrIVUlIkE5KVlYX//Oc/hs9//vkn0tPT0aRJEyWqQ0RERApQJBNSUFCAGTNmID09HTVr1kRBQQFGjBiBvn37Yv78+UpUiYiIyGxEMBNSHoo0Qry9vfHjjz+Wemzv3r3yVoaIiIgUwRVTiYiIJCAyE2ISGyFEREQS4LLtpvEFdkRERKQIZkKIiIgkwIGppjETQkRERIpgJoSIiEgCHJhqGjMhREREpAhmQoiIiCTAMSGmWUwjRLQC7rnJ9xc++lKEbLGK3XcvkDVeyxODZI13ouW/ZI0HAM2axsgar6CGrOEgiPLGA4B8R3njFdaT/yYz+7rJGi/3ar6s8azuyZ8kz/OQ7/9v0Vq2UGSCxTRCiIiIqgsRAseElAPHhBAREZEimAkhIiIyN5FjQsqDmRAiIiJSBDMhREREEhAVGBj+rGEmhIiIiBTBTAgREZEE+BZd05gJISIiIkUwE0JERCQBrhNiGjMhREREpAizNEJUKhU0Gg20Wi3UajVmz54NANDpdHBxcTEqd+bMmRLnd+zYEY0bN4ZWq4Wfnx+6deuGH374wRxVIyIiUkSRKEi6WQKzdcckJycjKCgIV65cQWBgIDp37gw3t/K/X2HhwoXo3bs3AGDfvn147bXX8OWXXyIiQv53tBAREZH0zN4d4+HhAbVajcuXL1f6Gu3bt8f06dMNGRUiIqJnjShKu1kCszdCzp07h+zsbHTs2LFK12ndujV+/fVX81SKiIiIqh2zdccMGDAAgiDg/PnzmD9/PlxdXZGXl1fp64kmmnkJCQlISEgwfC56+KDSsYiIiMxJBGfHlIfZMiHJyck4e/Ysdu7cibi4OJw+fbpK1zt27BiCgoLKPB4bGwu9Xm/YrOzsqxSPiIiI5GX27piuXbti3LhxmDp1aqWvsX//fkybNg2TJ082Y82IiIjkI4qCpJslkGSxsvj4ePj6+uLGjRsljnXt2hU2Nv8Le/jwYQDAhAkTMHXqVOTl5cHb2xtfffWVYbYMERERWR6zNEJ0Op3RZ2dnZ0MDJDs7u8xyxfbu3WuOahAREVUblrKWh5S4YioREZEFu3DhAkJDQ+Hv7482bdogNTW1RJndu3ejbdu2CAwMRFBQEKZMmWKYIKLT6WBjYwOtVmvYLl68aJa68d0xREREEqgua3lER0djzJgxiIyMRHJyMkaNGoVDhw4ZlXF2dsa6devQuHFj3L9/H127dsW6devw+uuvAwCcnJxw8uRJs9eNmRAiIiILdf36daSkpGDYsGEAgIiICKSnp5cYHhEcHIzGjRsDABwcHKDVanHp0iXJ68dGCBERkbmJ1WN2TGZmJjw8PAwTQgRBgJeXFzIyMso859q1a0hOTkbPnj0N+27fvo3WrVsjJCQEM2bMQGFhYdWez/9jI4SIiMjspG2AiKKA3NxceHp6GrbHF/A0qolg3GB52mKgt2/fRp8+fTBp0iSEhIQAANzd3aHX63Hs2DHs2rUL+/fvx2effWaWp8QxIURERM8gR0dH6PX6p5Zp1KgR9Ho9CgoKYGNjA1EUkZmZCS8vrxJl79y5g7CwMISHhyM2Ntaw397e3vBC2rp16yIqKgpff/01Jk2aVOV7YCaEiIhIAqLEW3m4ubkhODgYa9euBQCsX78eKpUKKpXKqFxubi7CwsLQo0cPxMfHGx27fv068vPzAQAPHjzAhg0bEBwcXO7n8DRshBAREVmwZcuWYdmyZfD398fs2bORmJgIABg9ejS2bNkCAFiwYAGOHj2KjRs3GqbhfvzxxwCAAwcOIDg4GC1atEBISAgaNGiAKVOmmKVu7I4hIiKSQHVZWl2tVpeYkgsAK1asMHw9ZcqUMhsWr776Kl599VVJ6mYxjRCbGgVoHG6exVPKI2d2yf40qTm0kfevq/b3L8gar1nTGFnjAcDpdxbLGu/og3xZ4w3Z+Jas8QCgqNkdWePV2u0oazwAeCEiS9Z4Dg/kfUFn7nEXWeMBgGtX+Z7pxRXmmdlBVWcxjRAiIqJqpZosVladcUwIERERKYKZECIiIjMTUX3GhFRnzIQQERGRIpgJISIikkB1eYFddcZMCBERESmCmRAiIiIJcEyIacyEEBERkSKYCSEiIpICMyEmyZIJUalUcHNzM7wABwB2794NQRAwceJE7N27F4IgYObMmYbjZ86cKfGCHSIiIrIcsnXHeHl5GV6UAwBJSUlo1aqV4bO7uzsWLFiA7OxsuapEREQkGVGUdrMEsjVCoqKikJSUBAC4desWDh8+jLCwMMNxDw8PDB06FH//+9/lqhIREREpSLZGSPv27XHp0iVkZWVh3bp1GDhwIKytrY3KTJ06FV9//TXS09PlqhYREZH5iTJsFkDW2THDhw/H6tWrkZSUhKioqBLHXVxc8Pbbb2Pq1Kkmr5WQkABPT0/DVnBX3reTEhERUdXIOjsmMjISISEh8Pf3h5+fX6llYmNj4efnZ9RVU1a52NhYw+cabvK/zpuIiKgsXCfENFkbIR4eHvjkk0+g0WjKLFOzZk3Ex8fjb3/7m4w1IyIiIrnJvljZyJEj0a5du6eWGT16NOzs7GSqERERkQQ4JsQkWTIhOp2u1P3Tpk0zfH38+HHD1zY2Njh//rzEtSIiIiIlccVUIiIiCXBMiGl8dwwREREpgpkQIiIiKVjIuA0pMRNCREREimAmhIiISBIcE2IKMyFERESkCGZCiIiIpMAxISaxEUJERCQFNkJMYncMERERKcJiMiGiKOBega1s8W4GyBermP1NeeNlN5P3HgtqyBoOAHD0gbxvX25jL/P3jQLj4uztCmSNZ5cr/6+buov1ZY2n9s+SNd69ey6yxgMA/R/OssUqLJLp928uVmYSMyFERESkCIvJhBAREVUnIseEmMRMCBERESmCmRAiIiIpMBNiEjMhREREpAhmQoiIiMxNFDg7phyYCSEiIiJFMBNCREQkAYFjQkxiJoSIiIgUwUwIERGRFJgJMUmxTIhKpYKbmxvy8/+3bPbu3bshCAImTpyIvXv3olWrVkpVj4iIiCSmaHeMl5cXtmzZYviclJTEhgcREVmG4hkyUm0WQNFGSFRUFJKSkgAAt27dwuHDhxEWFqZklYiIiEgmijZC2rdvj0uXLiErKwvr1q3DwIEDYW1trWSViIiIzEOUeLMAis+OGT58OFavXo2kpCRERUWV+7yEhAR4enoatsJ7DyWsJREREZmb4o2QyMhILFy4EA4ODvDz8yv3ebGxsdDr9YbNuoadhLUkIiKqIGZCTFJ8iq6Hhwc++eQTaDQapatCREREMlK8EQIAI0eOVLoKRERE5mUh2QopKdYI0el0pe6fNm2a4evjx4/LUxkiIiKSXbXIhBAREVkcC1nLQ0qKD0wlIiKi5xMzIURERBLgW3RNYyaEiIiIFMFMCBERkblZ0FoeUmImhIiIyIJduHABoaGh8Pf3R5s2bZCamlpqucTERPj5+aFJkyYYM2YMCgoKDMe2bt0KjUYDX19fREREIDc31yx1YyOEiIjIgkVHR2PMmDH47bffMGnSJIwaNapEmfT0dMTHx+PAgQNIS0vDtWvXkJiYCADIzc3FqFGjsGnTJqSlpcHd3R0ff/yxWerGRggREZGFun79OlJSUjBs2DAAQEREBNLT00us1ZWcnIz+/fujfv36EAQBY8eOxbp16wAA27dvR6tWrQwrm8fExBiOVZXFjAkpyLdG2ilP+QJ6FckXSyFyT3FXYiT5kI1vyRtQ5md68bWl8gYE0OSbsbLGy20pazgAgNVdeX9/u3CykazxBDcF/n+76iBfrEJ5/iFWh9kxmZmZ8PDwgI3Nox/3giDAy8sLGRkZUKlUhnIZGRnw9vY2fFapVMjIyCjzWFZWFoqKimBlVbV/C8yEEBERSUEUJN1yc3ON3iafkJBQajUEwbjRJYqlt44eL/dkmSevYS4WkwkhIiJ6njg6OkKv1z+1TKNGjaDX61FQUAAbGxuIoojMzEx4eXkZlfPy8jLqorl8+bKhjJeXF3bv3m04ptPp0LBhwypnQQBmQoiIiKQhSryVg5ubG4KDg7F27VoAwPr166FSqYy6YoBHY0U2btyI33//HaIoYunSpRg8eDAAICwsDMeOHcO5c+cAAIsXLzYcqyo2QoiIiCzYsmXLsGzZMvj7+2P27NmGWS+jR4/Gli1bAACNGzfG9OnT8dJLL6FJkyZwc3MzzKKpXbs2VqxYgX79+sHX1xdZWVn48MMPzVI3dscQERFJoRoMTAUAtVqNQ4cOldi/YsUKo89vvvkm3nzzzVKvER4ejvDwcLPXjZkQIiIiUgQzIURERBKoDlN0qztmQoiIiEgRzIQQERFJgZkQk5gJISIiIkVUuBGiUqng5uaG/Px8w77du3dDEARMnDgRAHDx4kUMHDgQPj4+aNasGUJCQkqMwn3jjTdQp04d3L17t8T1z5w5U5l7ISIiqj6qwToh1V2lMiFeXl6GucUAkJSUhFatWgEArl27hr/85S/o3r070tPTcfr0aezatcvolcC3b9/G999/j2bNmuG7776r4i0QERHRs6hSjZCoqCgkJSUBAG7duoXDhw8jLCwMALBo0SK8/PLLRnON69ati7Fj//dSq6+//hpdu3bFe++9Z1g0hYiIyJIIorSbJahUI6R9+/a4dOkSsrKysG7dOgwcOBDW1tYAgBMnTqBdu3ZPPT8xMRFRUVHo06cPzp8/j99++60y1SAiIqJnWKUHpg4fPhyrV69GUlISoqKiyn3e6dOncfXqVXTv3h22trYYPny4IatSEQkJCUZvDyx68KDC1yAiIpKECMnfomsJKt0IiYyMxMKFC+Hg4AA/Pz/D/pYtW5a6PGyxFStWIDc3F02aNIFKpcK6deuwevVqozEj5REbGwu9Xm/YrOztK3srREREpIBKN0I8PDzwySef4NNPPzXaHxMTg59//hkrV6407Lt58yY+//xzPHjwAP/85z9x+PBh6HQ66HQ6ZGVloWHDhti2bVvl74KIiKi64ewYk6q0TsjIkSNLjP9wd3fHgQMHsHXrVvj4+KB58+bo1q0b6tSpg02bNsHb2xsajcbonOHDhxtN4e3atatRV4ter69KNYmIiKgaEkRRtIj2lI2TExpNi5cv4HOwzJvcXY6KjPYukjmezM/04mtL5Q0IoMk3Y00XMiclusYt4n/NslnKzIuyZEz/OwpyciSNYfOCE3w++EjSGPe+/OyZ/yX9OfhRSkRERNUR3x1DREQkBQvPKJkDMyFERESkCGZCiIiIzEyA5Y+tMQdmQoiIiEgRzIQQERFJgZkQk5gJISIiIkUwE0JERCQFZkJMYiaEiIiIFGExmZB6NXKxvv8C2eKNWPCubLGKOV2s2Ev+qirHV95vj3xHWcMBAIqa3ZE1nr2dvH+Hsq9eCuDiYHlXaW28MVrWeACAQnnDWd+V9/fFWlfkX4Y2r6HlpQ04O8Y0ZkKIiIhIEWyEEBERkSIspjuGiIioWmF3jEnMhBAREZEimAkhIiIyN5EDU8uDmRAiIiJSBDMhREREUmAmxCRmQoiIiEgRzIQQERFJgZkQk5gJISIiIkVUqhGiUqmg0WjQokUL+Pn5oW/fvjh48KDh+IkTJxAWFobGjRsjKCgI7dq1w6ZNm4yu0b59e/j5+UEUjZuKgiAgNze3MtUiIiKqNgRR2s0SVLo7Jjk5GUFBQQCAzZs3o2fPnvjxxx/h6OiIHj16YOXKlejTpw8AICsrC7t27TKce+HCBVy4cAHOzs7Yt28fOnToUMXbICIiomeNWcaE9O3bFzExMZg3bx4cHBwQFRVlaIAAQMOGDTFixAjD58TERAwbNgzu7u5ITExkI4SIiCyPhWQrpGS2MSGtW7fGr7/+ihMnTqBdu3ZllisoKMCaNWsQFRWF4cOHY8uWLbh165a5qkFERETPCLM1Qp4c21GWbdu2wdvbGwEBAXB1dUXXrl2xbt26CsdLSEiAp6enYbubV1ThaxAREUmFY0JMM1sj5NixYwgKCkLLli1x6NChMsslJibiwoULUKlUUKlU2L9/PxITEyscLzY2Fnq93rDVrMWJPkRERM8Ss4wJ2bx5M5YsWYIdO3agVq1a6NSpEzp06IBevXoBAPR6PbZt24bw8HD89NNP0Ov1cHJyAgAUFhaiYcOG+OWXX9C8eXNzVIeIiEh5FpKtkFKlGyEDBgyAvb098vLyEBgYiG3btuHFF18EAGzfvh1TpkzBW2+9hVq1aqFOnTqYPHkyVq9ejR49ehgaIABgbW2NIUOGYMWKFVi4cCEAQK1WQxAEQxm9Xl/ZahIREVE1ValGiE6ne+rx1q1bY+fOnSX2h4eHl1p+/vz5hq/LO7aEiIioWuOPM5M4kIKIiIgUwXfHEBERScBSZrBIiZkQIiIiUgQzIUREROYmgmNCyoGZECIiIlIEMyFERERSYCbEJGZCiIiISBHMhBAREUmAs2NMs5hGyM08Rwxb9q58Ae3lC1UsOzJP1nh2P70ga7zCevL/i62121HWeHa58t5jbktZwwEAGm+MljXepf7LZI0HAD7bRssar/GEI7LGy5gWKms8ALDLEUwXMhOB7zutNiymEUJERFStMBNiEseEEBERPafu3r2LIUOGwNfXF/7+/tiwYUOp5a5cuYIePXpArVajefPmGDRoEG7evGk4rlKpoNFooNVqodVq8e2335YrPjMhREREEngWxoTMmzcP9vb2SEtLQ3p6Otq1a4dOnTrB2dnZqJy1tTXi4+Pxl7/8BQDw/vvvIy4uDsuXLzeUSU5ORlBQUIXiMxNCRET0nPr2228xfvx4AICPjw/at2+PzZs3lyhXv359QwMEANq2bYtLly5VOT4bIURERFIQJd7MICMjA97e3obPKpUKGRkZTz2nsLAQixYtQp8+fYz2Dx06FM2aNcPo0aPxxx9/lCs+GyFERERSkLgRkpubC09PT8OWkJBQogovv/wyXFxcSt0yMzMBAILwv5lJovj01o0oioiJiYGTkxPeeustw/59+/bh1KlTSElJQb169TBixIhyPSKOCSEiInoGOTo6Qq/XP7XM/v37n3rcy8sLOp0Orq6uAIDLly+jZ8+eZZafMGECMjMzsWnTJlhZ/S+P4eXlBQCwtbXFO++8A39//3LdAzMhREREEhAk3sxh4MCBWLRoEQAgPT0dP//8M8LDw0stO2HCBKSlpWHjxo2ws7Mz7M/Ly0NOTo7h87p16xAcHFyu+MyEEBERPafef/99REVFwdfXF1ZWVli0aBHq1q0LAFi6dCmuXLmCGTNm4D//+Q+++OILaDQatG3bFsCjgawbN27E77//joiICBQWFkIURTRu3Bhr1qwpV3w2QoiIiKTwDEzRrVWrVplreowdO9bw9UsvvVTmeJHGjRvjv//9b6Xil7s75vGFSNRqNWbPng0A0Ol0cHFxKVFeEATk5uYCeDSQZc6cOdBoNAgICIBarcacOXOMbkgQBDRv3hxarRYajQZvvfUWCgsLK3VTREREVP1VKBNSvBDJlStXEBgYiM6dO8PNzc3keVOmTMG+fftw4MABuLi4IDs7G/369UNOTg5mzZplKHfw4EE4OjoiPz8frVu3xo4dO9CrV6+K3xUREZGCBDwbi5UprVIDUz08PKBWq3H58mWTZXNzc5GQkIDly5cbMiYuLi5Yvnw55s+fj7y8ki9lu3v3Lu7fv19ixTYiIiKyHJUaE3Lu3DlkZ2ejY8eOhlGxWq221LKpqamwt7dHYGCg0f7AwEDY2dkhNTUVrVu3BgCEhoZCEASkpaUhIiICoaHyv8mRiIioysy4oJglq1AjZMCAARAEAefPn8f8+fPh6uqKvLw8ODk54eTJk0ZlH1/85PGvn6a4O+bu3buIiIjAF198YbQYyuMSEhKMFmYpevigIrdCRERECqtQd0xycjLOnj2LnTt3Ii4uDqdPnzZ5TmBgIO7fv4/U1FSj/ampqXj48GGJDAkA1KxZE3369MGOHTvKvG5sbCz0er1hs7Kzr8itEBERSesZWLZdaZUaE9K1a1eMGzcOU6dONVnW0dERb7/9NqKjo5GdnQ0AuHHjBqKjo/H222+jVq1aJc4pLCzE3r17oVarK1M9IiIiegZUep2Q+Ph4+Pr64saNGybLfvLJJ5gzZw5CQ0NhbW2NwsJCjBw5EpMnTzYqFxoaCisrKzx8+BAtWrTARx99VNnqERERKYqzY0wrdyNEp9MZfXZ2djY0QIozHI97fA0QKysrxMXFIS4urszrm3ppDhEREVkWrphKREQkBf5ubRJfYEdERESKYCaEiIhIAhwTYhozIURERKQIZkKIiIikwEyIScyEEBERkSKYCSEiIpIAx4SYxkwIERERKYKZECIiIikwE2KS5TRC7IogtM2RLZxXbJ5ssYpZ95T3TcEFP8kbL7Ovm6zxAOCFiCxZ4+ku1pc1ntVdBZKdhfKG89k2Wt6AANJ7rpA1nmZ6jKzxHtQvkDUeAMCmSLZQog1bB9WF5TRCiIiIqhO2dUzimBAiIiJSBDMhREREEuDsGNOYCSEiIiJFMBNCRERkbiI4JqQcmAkhIiIiRTATQkREJAFBZCrEFDZCiIiIpMA2iEnsjiEiIiJFlLsRolKpoNFooNVqoVarMXv2bACATqeDi4tLifKCICA3NxcAIIoi5syZA41Gg4CAAKjVasyZMwfiY6mq3NxcvPPOO/D19UVQUBACAgIwceJE5OfnV/UeiYiIZCeI0m6WoELdMcnJyQgKCsKVK1cQGBiIzp07w83N9FLbU6ZMwb59+3DgwAG4uLggOzsb/fr1Q05ODmbNmgVRFNG7d2/4+fnh9OnTqFGjBh4+fIikpCQ8ePAAtra2lb5BIiIiqp4qNSbEw8MDarUaly9fNtkIyc3NRUJCAlJSUgwZExcXFyxfvhwtW7bElClTcPjwYaSlpWHnzp2ws7MDANjZ2WHs2LGVqR4REZHyLCRbIaVKNULOnTuH7OxsdOzYEXl5ecjJyYFWqy21bGpqKuzt7REYGGi0PzAwEHZ2dkhNTcWJEyfQsmVLQwOEiIiILF+FGiEDBgyAIAg4f/485s+fD1dXV+Tl5cHJyQknT540KisIQqlfm0tCQgISEhIMn4vuPTR7DCIiosqylHEbUqrQ7Jjk5GScPXsWO3fuRFxcHE6fPm3ynMDAQNy/fx+pqalG+1NTU/Hw4UMEBgaiZcuWSElJwcOH5W9IxMbGQq/XGzarGsyiEBERPUsqNUW3a9euGDduHKZOnWqyrKOjI95++21ER0cjOzsbAHDjxg1ER0fj7bffRq1atdC5c2f4+PhgwoQJuH//PgCgoKAACQkJhhk2REREzxRR4s0CVHqdkPj4eBw4cAA3btwwWfaTTz5Br169uHKisAAAIABJREFUEBoaioCAALRr1w49e/bErFmzADzqrvnhhx9gZ2eHpk2bIigoCC1atMC1a9fg4OBQ2SoSERFRNVbuMSE6nc7os7Ozs6EBUpzheNzja4BYWVkhLi4OcXFxZV6/du3aWLhwIRYuXFjeKhEREVVbHBNiGldMJSIiIkXw3TFERERSYCbEJGZCiIiISBHMhBAREZmbBb3fRUrMhBAREZEimAkhIiKSgshUiCnMhBAREZEimAkhIiIyMwEcE1IezIQQERGRIiwmEyKKAu7dk+8ldr99LP8L82purClrPOu5ppfkN6fcq/myxgMAhwf2ssZT+2fJGu/CyUayxgMA67vy/m7TeMIRWeMBgGZ6jKzxzr25WNZ4PttHyxoPAKzsC2WPKTlmQkxiJoSIiIgUYTGZECIioupEKFK6BtUfMyFERESkCGZCiIiIpMAxISYxE0JERESKYCaEiIhIAlwnxDRmQoiIiJ5Td+/exZAhQ+Dr6wt/f39s2LChzLKCIKB58+bQarXQarXYv3+/4diFCxcQGhoKf39/tGnTBqmpqeWKz0wIERGRFJ6Bd8fMmzcP9vb2SEtLQ3p6Otq1a4dOnTrB2dm51PIHDx6Eo6Njif3R0dEYM2YMIiMjkZycjFGjRuHQoUMm4zMTQkRE9Jz69ttvMX78eACAj48P2rdvj82bN1foGtevX0dKSgqGDRsGAIiIiEB6ejp0Op3Jc9kIISIiMjfx0ZgQKTdzyMjIgLe3t+GzSqVCRkZGmeU7duyIFi1aIDY2Fnl5eQCAzMxMeHh4wMbmUeeKIAjw8vJ66nWKVagRolKpoNFo0KJFC/j5+aFv3744ePAgAGDVqlVwcnKCVqtFUFAQXnnlFaMKrFq1Cs2aNUNAQAB8fX0xefJkPHz4sMS1tVot1Gr1/7V393E13///wB+npFRMLkexIkVldbSkuZFcrZnEB5uL+YjcQjNzMZfhJtNHaJnPZ2EWtdkyy+VGftvMxIcWEVIyWReSGZWLLqSL8/ujb+9PR5fq/X4fnR732+3cbjvvc3o/3lnnnNd5vq4QGBj4IpdGRET0clFJe8vLy4OZmZlwCw4OrnIJgwYNQocOHaq93b59G0B5o0G45Fq6kNLT0xEXF4dz587h/v37WLJkifBY5XPUdZ7KXnhMyP79+2FnZwcAOHLkCEaNGoWffvoJADB8+HDs378fALBw4UIsXLgQBw4cwM6dO7FlyxZERUXBwsICBQUFmDZtGry8vBAREVHl3FlZWbCxscHQoUPRv3//F71EIiIirWdsbIzMzMxan1N58Gh1unfvjrS0NHTs2BFAeUNj1KhRNT4XAIyMjODr6wsfHx8AQLdu3ZCZmYmSkhK0aNECKpUKt2/fFp5fm0Z1x3h6esLX1xdBQUFVHhsxYgRu3LgBAPjkk0/w6aefwsLCAgBgaGiInTt34vDhw0hJSanys127doW1tTXS09Mbc3lEREQa0xS6YyZOnIiQkBAAQGpqKqKjozFmzJgqz8vNzUVBQQEAoKysDPv27YNSqQQAdOrUCUqlEt988w0A4MCBAzA3N4e5uXmd+Y0eE+Lk5ITExES1Y6WlpYiMjISjoyP+/vtvZGZmwsXFRe057du3R69evRAfH1/lnMnJyXjw4AGGDBnS2MsjIiKiGixZsgSFhYWwtLTEW2+9hZCQELRr1w4AsGPHDqxZswZA+efygAEDYG9vj759+yI7OxufffaZcJ4vvvgCX3zxBaysrBAYGIhdu3bVK7/RU3Qr9/ucOHECDg4OAIB+/frh008/RVlZzTv4PN9nNGHCBCgUCty4cQNbtmwRykPVCQ4OVuv/Knta1NBfgYiISHxNYIqukZER9u3bV+1jc+bMEf7bxcUFV69erfE81tbW9ZqS+7xGN0IuXLggjBGpPCakMlNTU8TExKj1M2VnZyMlJUUo5wD/GxNy4sQJeHh4YOjQoejbt2+1uYsWLcKiRYv+94u0f6WxvwoRERHJqFHdMUeOHMH27dvVGgPV8fPzw+LFi5GamgqgfIU2Hx8fjBkzBpaWllWeP3z4cMydOxerVq1qzOURERFpTFMYE6JpL1wJmTBhAvT19ZGfnw8bGxtERUVhwIABSE5OrvFn5s6dCz09PXh4eKC0tBTPnj3DP/7xD6xfv77Gn1m9ejUsLS1x8eJFODo6vuhlEhER0UvuhRohta1+5uXlBS8vrxofnzVrFmbNmlXvc5uYmCA7O/tFLo+IiOjloSXVCilxxVQiIiLSCG5gR0REJAFtGbchJVZCiIiISCNYCSEiIhKdCihjKaQurIQQERGRRrASQkREJLaK3W6pVqyEEBERkUawEkJERCQBzo6pm9Y0QhTFCugnGMqWV2hWKltWhScO8m7Sp8qSdz8enUL5C3N5cR1kzSsslDdP0anmDSSlYpSlkDUvY+2bsuYBQFHnElnzLI7XvNCjFFLfDpU1DwB6fjen7ieJpUzev1GqmdY0QoiIiF4qTWAXXU3jmBAiIiLSCFZCiIiIJMAxIXVjJYSIiIg0gpUQIiIiKbASUidWQoiIiEgjWAkhIiISmQKAgrNj6sRKCBEREWkEKyFERERSkH+twCaHlRAiIiLSiAY3QkpKSrBu3Tr07t0btra26N27N3x8fHD58mUoFArMmvW/ZYbz8vKgUPxvmdwhQ4bg6NGjVc6ZkJCAoUOHwt7eHnZ2dnBycsK1a9caeolEREQao1CpJL1pgwZ3x3h7eyMnJwcxMTEwMTFBWVkZDhw4gDZt2sDY2BhHjx5FUlISbGxs6n3OKVOmICAgAGPGjAEA3L59G/r6+g29RCIiInqJNagSkpKSgsjISISFhcHExKT8RDo6mDhxInR0dKCvr4/ly5djxYoVL3TejIwMmJmZCfe7deuGTp06NeQSiYiINEclw00LNKgRcunSJfTq1QsdOtS8I6ivry8SEhJw9uzZep93zZo1GDx4MIYNGwY/Pz/Ex8c35PKIiIg0T6WS9qYFJBuY2rJlS6xbtw5Lly6t988sXrwYt27dwqxZs5CTk4NBgwZh37591T43ODgYZmZmwq3smbzb3BMREVHjNKgR0q9fP9y8eRPZ2dm1Pm/q1KkoKCjAkSNH6n3uzp07Y/Lkydi+fTtWrVqFb7/9ttrnLVq0CJmZmcJNpyXHjhAR0ctDoZL2pg0a1AixtLTE+PHj4e3tjYcPHwIAVCoVvv76a5SWlgrPUygU2LBhA1atWlWv8x46dAjFxcUAymffXL16FT179mzIJRIREdFLrsHdMbt374a9vT2cnZ1ha2sLW1tbnDt3Dk+ePFF7nru7O3r06FHl5728vNS6U2JiYnDw4EHY2dnh9ddfh729PfT19eHv79/QSyQiItIcjgmpU4On6Orp6cHf37/aRsKDBw/U7v/6669q90+dOlXtOV1cXBp6OURERNTEcNl2IiIiCSi4bHuduGw7ERERaQQrIURERFLQknEbUmIlhIiIiDSClRAiIiIpsBBSJ1ZCiIiISCNYCSEiIpKAgmNC6sRKCBEREWkEKyFERERiU4GzY+pBexoheiqU9XtS9/NE0uGYsWxZFVo81ZM1r1RPIWtefld58wCg4/A7suZl3jeRNQ93DeTNA5BvKu8bb8uH8v/doIW8q1Dp6JfW/SQR9fxujqx5AHBr0g7ZsrpvypMti2qnPY0QIiKilwlXTK0Tx4QQERGRRrASQkREJDoVZ8fUAyshREREpBGshBAREUmBlZA6sRJCREREGsFKCBERkRRYCakTKyFERESkEayEEBERSYHrhNRJ1kpIcXEx/P390bt3b9ja2kKpVGLs2LG4fPkyTp06BUNDQzg4OMDe3h7Ozs74/fff5bw8IiIikpGslZAZM2YgLy8PMTExMDEpX776xx9/RGJiIkxNTWFjY4O4uDgAwLZt2zBz5kwkJSXJeYlERESi4DohdZOtEnLz5k0cOnQIu3fvFhogAODh4YGpU6dWeb6bmxvS09PlujwiIqJmp6CgAJMnT4alpSWsrKxw8ODBap+XlJQEBwcH4WZubo527doJj5ubm6N3797C4/v27atXvmyVkPj4eFhaWqpddG3279+PSZMmSXxVREREEmkClZCgoCDo6+sjJSUFqampcHFxgZubm1qxAABsbGxw+fJl4f68efOgUKhvHrl//37Y2dm9UL6s3TGVL/jWrVsYP348CgsLMXjwYEydOlVoaf31118oKSlBbGxsjecKDg5GcHCwcL/saZGk105ERKRt9u3bh/DwcACAhYUFBg8ejCNHjsDLy6vGnykqKkJERAROnjzZ6HzZumOUSiVu3ryJ3NxcAEDPnj1x+fJlrFixQjhW0dK6ffs2xo0bh6lTp0JVQ0ty0aJFyMzMFG46Bvpy/SpERES1U6G8EiLlTQQZGRl47bXXhPvm5ubIyMio9WcOHjwICwsLODg4qB2fOnUq+vbti1mzZuH+/fv1ypetEdKrVy94enrC29sbDx8+FI7n5+dXea6enh62bt2KzMxMHD58WK5LJCIiEo/EjZC8vDyYmZkJt8q9AxUGDRqEDh06VHu7ffs2APVeipq++Fe2e/dueHt7qx07ffo0rly5gkuXLqF9+/aYPn16vf6JZO2OCQ8PR0BAAJydnaGrqwsTExN06tQJy5cvR2FhodpzDQ0NERAQgLVr12Ls2LFV+p6IiIiaM2NjY2RmZtb6nDNnztT6ePfu3ZGWloaOHTsCANLT0zFq1Kgan5+eno5z584hMjKyynmA8iLCggULYGVlVZ9fQd5GSMuWLeHv7w9/f/9qH6+Ynlth+vTp9W5NERERvVSawGJlEydOREhICMLDw5Gamoro6Gjs2LGjxueHhYVh3LhxaNu2rXAsPz8fxcXFwrG9e/dCqVTWK58rphIRETVTS5YswcyZM2FpaQkdHR2EhIQIs1h37NiBrKwsrFu3DkB5V014eDjCwsLUznHv3j2MHz8epaWlUKlU6NGjB77++ut65bMRQkREJIGmsFiZkZFRjWt6zJkzR+2+QqFAWlpalef16NED8fHxDcrnBnZERESkEayEEBERSaEJVEI0jZUQIiIi0ghWQoiIiESnAspYCakLKyFERESkEayEEBERSYFjQurESggRERFphNZUQnTyniL/o50v/HN5eXkwNjZ+4Z+ruuONtHmNIXdmU8p7vEf+TOaJm9nQ/bOb0r9pqQYy5c7rHiRf3v1s3RcPe1EVG9hRrbSmEVJU1LC3IjMzszrX3heT3HmayNT2PE1kanueJjK1PU8TmdqeR+LTmkYIERHRS4WVkDpxTAgRERFphO7atWvXavoiNM3FxUWr8zSRqe15msjU9jxNZGp7niYytT2vvtav2wCLNo7/NzZEmtvfpdewaNEiOX8t0SlUKtaLiIiIxGTQojXcus+WNCPh2XdNfkwMx4QQERFJQVWm6St46XFMCBEREWkEKyFERERS4GiHOrESQkRERBrBSgg12rFjx3Djxg04OjrC1dVV05dDIsrKykLXrl01fRlETRN30a0TKyEyWL9+fb2OSSU3N1eyc69evRoffvghYmNjMWXKFOzc+eJL59PLa8CAAbJndu/eXfZMsZWWlqKgoKDK8YKCApSVyT9YMT4+XvRzJiUl4cGDB8L9yMhIjB07FosXL0ZeXp7oeTU5cuQIlEqlbHkkrmbZCLl06RLc3d1hZWWFHj16CDepHDx4sF7HxHDlyhU4Ojqif//+uH79Ot555x2Ympqie/fuuHr1quh5Bw4cQHx8PPbt24fY2Fjs2rVL9IznHTp0CP3794exsTGMjY0xYMAAHD58WLI8CwsLtb+TyreePXuKnufk5IT+/fvXeJOTJmbwS5GpUqlw/Phx/P777wCAkJAQeHh44OOPP8aTJ09Ez1uxYgW++eabKse/+OILrFy5UvS8CnFxcThw4ACys7MBAImJiRg7dixGjhwpetaMGTOE7TIuX74Mb29vuLi44K+//sJHH30kel5sbCxsbW3RunVr+Pj4IDU1FS4uLvjwww+xcOFC0fMaT1U+JkTKmxZolt0x06dPx7x58+Di4gJdXek2Mvrll1/w888/IysrC0uXLhWOP3r0SLLM+fPnY82aNXj48CHc3d2xfv16HDt2DIcOHcLHH3+Mn3/+WdQ8AwMDvPLKKwDK93EoLi4W9fzPi4qKwgcffAB/f384OTlBpVLh/Pnz8PX1hb6+Pt5++23RM48ePVrlWHx8PNasWQM9PT3R84KCGrCTl0QUCoVWZC5YsACnT59GUVER+vfvj7///hseHh44deoU5syZg2+//VbUvGPHjuHKlStVjn/44YdQKpUIDAwUNQ8ANm7ciMDAQFhbW2P58uWYP38+li1bBl9fX4SHh4ueV1BQAFNTUwDA/v378f7772PZsmUoKSmRpDKxYMECzJs3D25uboiMjISzszPGjRuHkydPolWrVqLnkTyaZSNEV1cXs2dLu4gMALRs2RLGxsZQKBQwMjISjnfp0gUrVqyQJPPx48fw9PQEUN5VMm3aNADAuHHj4O/vL3reo0ePEBUVpZZf+f6oUaNEzdu6dSv27duHQYMGCceUSiVsbGzwySefSNIIsbW1Ff47PT0dfn5+iI6OxurVq+Ht7S163rFjx2p9XOxxN0lJSTU+VlJSImpWheq6KipIUQn55ZdfkJCQgLy8PJiZmeH+/fswMDCAj48P7O3tRc/T1dVFixZV315btGghWcMuPDwcSUlJ6NKlC5KTk2FnZ4effvoJw4YNkySv8u8XGxuLWbNmCcel+HJXWFiIuXPnAih/b9u2bRu2bdsm6RfJRuEuuvXSLBshAwcORHx8vOT9iK6urnB1dcXYsWOrvNE9ffpUkszKb+Bubm41PiaWbt26YfPmzWr3g4KCoFKpoFAoRG+EpKWlqTVAKgwaNAjp6emiZlWWk5ODdevWISIiAh999BG+/PJLyb59BQUFwcnJCe7u7tDRkb7H9J133qnxMX19fUkyKxrnlf8mK+5L8SGtr68PXV1dvPLKK+jZsycMDAwAlDcWpKhmFRYWoqioqMq/X1FRUa0NsMYwMDBAly5dAAC9e/eGlZWVZA0QAGjXrh2OHTsGU1NT/P7774iIiABQ3nCV4v3t+ddCly5dXt4GCNVbs2qEODk5QaFQoLi4GKGhobC2thbejADg/PnzomeqVCqYmZkJ9589e4Zt27Zh06ZNyMrKEj2vc+fOePz4Mdq0aYOvvvpKOH737l2131Usv/32m9qHxq1bt/DDDz/A0tISHh4eoudVrii9yGON8a9//Qtbt27F1KlTkZycjHbt2kmSU+HEiRMICwtDREQE3n33XcycOVOSsScVUlNTJTt3TeQenKlSqVBYWCjkFhYWCg0gKRrno0ePxvz58xESEiJUDEpKSrBw4cJaG32NUVRUhOvXr6v9PpXv29jYiJq3detWTJkyBbdv34a/vz86duwIoLz7UoqxSzdu3FA7b8X9ioarFO/fjSZ1JUT+3lLRNau9Y6Kjo2t9XOwyd1RUFCZPnoy8vDwMHToUAQEBeO+999CxY0cEBQVh8ODBoubV5smTJ3j8+LHQhyuWESNGYPPmzXBwcEBWVhbs7Ozg7OyMtLQ0eHl5YdmyZaLm9ezZE59//nm1Hxzz589HSkqKqHlA+TewLl26oGvXrmoNLqnf/B4/foy9e/ciLCwMrVq1QmBgIJydnSXJel5ZWRmioqIQGhoq6aDf5127dg2hoaH47LPPRD2vjo5OrZWX0tJSUfPy8/Pxzjvv4M8//4SjoyOA8gHxFhYWOHbsmCQNZnNz8xqrSAqFAn/++afomTWJjY0V/W9V7vfvxjLQNYbbqzMkzUhQHOLeMU1JxR/p7t27MXPmTLXHdu/eLfofsZ+fH7777ju4ubnh+++/x9ChQ7Fs2TKsXr1a1Jz6aN26NWxtbZGRkSHqee/cuQMHBwcAQEREBFxdXXHo0CHk5ubC1dVV9EZI9+7dsWnTpmof69atm6hZFX777TdJzluXNm3aYMyYMcjJycG///1vJCcnS94ISUlJwa5du/D111/D1NQU77//vqR5QHkDee/evdi1axcyMjIwZcoU0TPkrrwYGRnh1KlT+PXXX3Hp0iUA5YNShw4dKllmWlqaZOd+URMnThT9vcbExASJiYmYPHkyAGD27NnC8gNLliwRNUs0Uv/daUFvVLNqhFT4/PPPqzRCqjvWWCqVShgo+c9//hOrV6/WSAOk8vWIrXIXz7lz54QxICYmJtUOzGus2hoEUnRvAfIPFC0tLcUPP/yAXbt2ITU1FdOmTcOlS5eE/n6xPX36FJGRkQgNDcUff/yB999/Hzo6OpKXt8+cOYPQ0FD8+OOPGDZsGDIyMnDnzh1Jx8EUFhYiKSkJCoUCNjY2knRRVvbmm2+ibdu2AMTvDqnJn3/+KawL0q9fP1hYWMiSW5kU7zVr165VGwgeHR2NFStWID8/H4GBgThw4IDomY3WfDoaGqxZNULi4uIQGxuLBw8eYNu2bcLxR48e4dmzZ6LnPf9m2r59e9EzXoQUA/50dHSQmZkJExMTREdHq009lGoAXk0GDBgg+rcvQP6BohXrusycOVPossvNzRW+9Yn9Yda5c2e8/vrrWLx4MUaPHo0WLVpI/oZubW0NPT09zJo1C59++ik6dOgACwsLSf99/fz8sGXLFrRs2RIAUFxcjAULFiAgIEDSPH19fahUKsnziouL4eXlhcOHD6NXr15QqVRISUnB2LFjER4eLskA3JpI8V6Tnp6uNp6mVatWmD59OgBg7969oueRPJpVI+TOnTuIi4tDfn4+Lly4IBxv06aNJPPoExIS0KlTJ+F+bm4uOnXqJPRD//3336Jnyj31ceXKlXB0dISenh7c3NxgZWUFoLwqYm5uLnpebaQa3iT3QFEDAwPcv38fGzduxKZNm6qMYxC7b9/T0xNHjx7F3r17YWhoiBEjRoh6/up07twZKSkpuHv3LnJyctChQwdJ1yTZvHkzTp8+jYsXL6JPnz4Ayqcmz5kzB5s2bVJbx6cp5gHAmjVrUFRUhNu3bwuDp7OzszF79mysXr1a9LVJKk/Ff54Us2Oe/6JYuaEs5arQjcJKSJ2a1cDUCsePH5dkPYnn1TVl9LXXXhM9s7YBeIA0feP37t3D3bt3YW9vL3yQZGVloaSkRNYluLt37y5JJaSCJgeKSu3JkyeIiIjArl27cPfuXeTn5yM2Nha9evWSLLPy+BNzc3PcvHkTt27dQuvWrUXP6tOnD86ePVtlZlN2djYGDhyI5OTkJp0HAFZWVrh69WqVLqaCggLY29vj5s2bouY9vwTA88QeS9WnTx/ExsaiTZs2ascfPXoEZ2dnSf5NG8NA1xhuHaZJmpGg9yMHpjZFw4cPR1BQEE6cOAGFQoERI0Zg3rx5QplWLM83Mu7duweFQqFWHRGbJval6Ny5Mzp37qx2TKpNzzSxsFYFTQwUlUvr1q0xe/ZszJ49GwkJCQgNDcWbb74Jc3NztaqhmCwtLbFhwwasX78eUVFR2LVrF7p27Qp3d3dERkaKmqWjo1Pt1Or27dtLstaE3HkAoKenV+0YF0NDQ9Hf2wD5B2xPmjQJXl5eCAsLE1ZpfvToEby9vTFp0iRZr6XeuIFdnZplI2T27NnIzs4WVt8LCwtDYmKiZPueXL9+He+++67QYu3WrRu+//579O7dW5K8mgwcOBBnz56VNVNsta2xINUgQ7kHimpa3759sXXrVmzevFmW6bm6urrw8PCAh4cH7t27p7a+jVjKysqQm5sLExMTtePZ2dmSNF7lzgPK/x0zMjKqVB/T0tJkGcskNT8/P3h5ecHMzAyWlpZQKBS4efMmPD09sWrVKk1fHjVQs2yExMTECCPkgfKFhfr27StZnq+vL1asWCFMPfzuu+8wd+5c2b9JSNlVIRdNLKwl90BRue3evRslJSXw8fFRO759+3bhG6fYfvjhBzx69EjYVqDycSn+PWfMmAFPT098+eWXsLa2BgAkJydj9uzZkiy9L3ceACxatAhvv/02goODhd2PY2JisHjxYixevFj0vIqu3wqVV7tVKBSiN7ZatGiBb775BikpKcLsH6VSCUtLS1FzxKRSyV+Zbmqa5ZiQ4cOH48cffxSW3S4sLISnp6fom7tVcHBwwOXLl9WOKZVKSbbXro3UYya0VeVFoKobbyPnIlBSeOONN3DixAlhKmmFnJwcvPXWW5J0xwwcOBD79++vUk26c+cOJk2ahDNnzoieuXLlSmzZsgUGBgZQKBR4+vQpPvroI2zYsEH0LE3kAcDOnTuxfv16ZGZmQqFQwNTUFCtXrsScOXNEz8rPz69y7MiRI1i1ahV69OiBEydOiJ7ZlBjoGmOIifhr3lR2zSCqyY8JaZaNEB8fH5w/fx7vvfceACAyMhKDBw8WZnb4+vqKmufo6Ig9e/YI3/Bu3LiBKVOm4OLFi6Lm1EUbGiEdO3asdhaFlDOOtJ29vX21O74C1TegxfD666/j6tWrL3w9jZWfny+MK7KxsZFsqX9N5VW4f/8+AAhLqUstJiYGS5cuRUFBATZs2ICRI0fKkvsyM9AxwpC2EjdCDI83+UZIs+yOKS4uhlKpxB9//AGg/E3v0aNHuHDhgiTTBAMCAuDq6gqlUgmFQoHLly9jz549oucAtX9IP3z4UJJMOcXFxdX4WE5OjoxXoj3y8vJqfOzJkyeSZNY2lby6b9hi5SkUCrVdkSuOGxoaNuk8AMjMzMTChQtx48YNvPHGGwgKChI943nJyclYvnw5EhISsG7dOkydOlXyTNIuzbIREhYWJmueu7s7kpKSEBsbC5VKBRcXF3To0EGSLG3/kH7ttdcQFxeH9PR0DBkyBO3bt0diYiL8/Pxw9uxZ4Rsg1Z+jo2O1Wxl89dVXku003atXL0RFRVXZZfn48eOSrMFSedfe6sYxiL3an9VhAAAGbUlEQVR3jNx5QPmAe2tra8ycORORkZFYunQpQkNDRc+p4OPjg6NHj2L58uXYv3+/JCskN3nNr6PhhTXL7pjHjx9jzZo1SEtLw+HDh5GUlIQrV64IexKIbfPmzWp7G1SsnBgSEiJJnjZ/SG/cuBGBgYGwtrZGdnY25s+fj2XLlsHX1xerVq2qMq6B6nbr1i0MGjQIgwcPhouLC4DyxeZOnz6N//73v5I0Ci5evAh3d3d4e3urZYaFheH48ePCpm9SkHs8llx5ffv2RUJCAoDyGV1OTk7CvjVS0NHRgbGxMfT19attaDX3rlEDHSMMeUWaz5QK14z+H7tjmqI5c+bAxsZGGDhlYWGBKVOmSNYIOXPmDKKjo7Fnzx7k5uZiwoQJwuh1sVX+kF6+fLnah7QUq8LKLTw8HElJSejSpQuSk5NhZ2eHn376CcOGDdP0pTVZPXv2RHx8PEJCQvDzzz9DoVDA0dERW7duxauvvipJpqOjI06dOoWNGzfCz89POHby5EnY2dlJkllBypVZNZlXeVl2qdYiqSw+Ph5t2rSpMv23tLRUsm68JkcD6zY1Nc2yEZKcnIyIiAhh2d9WrVpJtuQ3UD7tMCgoCEqlEmVlZQgKCsK7774rSZa2f0gbGBgIMyp69+4NKysrrfndNKXyEuIVg6cLCwsRHBwMADXuWtxYBQUFePr0qfDaKyoqQmFhoSRZlcld/JUrLzU1VXhfUalUavcB4Pvvvxc1b/v27RgxYgTGjx+vdnzPnj2IiYlR25+LqCbNshHy/OqBhYWFkr5RFBcXIz09HW3btkVubq4km+VV0PYP6aKiIly/fl3t/1fl+019zQ5NqLxBn66uriwfmjExMRg1ahQ++OADTJkyBSqVChcuXMBbb72F48ePS7oSrbZWQj777DO1zNGjR0uad/r0aezYsaPK8WnTpmHjxo2SZjcZzW+0wwtrlo0QNzc3BAQEoKioCKdOnUJwcDDGjh0rWd6bb76JN954A+fPn8e9e/cwadIknDp1SpJBY9r+IV1QUFBlMGPFfW1Ys0MT5N6gDyivrnz11VcYM2aMcGzcuHFwdnbGhg0bRF+ptfKssYqNJAHpxi/InQcA06dPx4ULF7B582ZhWrCdnR0WLVqE/v37i55XW5eP3A09arqa5cDUkpIStSWpPTw8sHz5cslGd0dERAirpQLlfaYjR47Er7/+KnpW5YW1nscPaaqNnBv0WVtb48aNG9U+ZmVlJUyfF0ttm0nm5OSIPgtI7jzgf9UlX19fODk5CdWlHTt2SFJdamobysnNQMcIroYTJM1IbPsrB6Y2NRcuXEBQUBCuXbsGoHxE+ciRIyVrgMTFxUFfXx/Z2dlqM1VqWqipsdLS0iQ5L2k/OTfoq1ituDpSrKEh99RuTUwll7u6NHnyZEybNg3h4eHCHjm5ubkv94Zy9NJp+rsavYCYmBiMHDkSlpaWCAgIwPr169GjRw+4u7sjNjZW9LyNGzdixIgR2Lx5MwYMGID//Oc/cHJygqWlpejbahM1VGlpKQ4dOoTRo0dj+PDhUCgUuHTpEqZPny5Z5rNnz3D9+nUkJSVVuUkxZkru16ImXvtJSUlqDZAKnp6ete4+3VB+fn5o27YtunXrBqVSCaVSiW7duqF169ZYvXq16HlNkkol7U0LNKvumHHjxmHGjBlVXqhHjhxBWFiY6N8U+vTpg5MnT2rtTBXSDq+++mqVDfoqk2IckdzdhnK/FjXx2q9tiX2plt8HyteZqViPpF+/fpKPJ2oqDHSM4NpqfN1PbIREk5NNvjumWTVC5O6Hfn6RIhsbG0m+kRA1hrZv0AfI/1rUxGvfxsYGBw4cqHZ204QJE/jeIzMDhRFcDf4haUZi+9+afCOkWY0JkbsfWttnqpB2aA7jiOR+LWritV/dzLEKnK1CL6tmVQmR+5sCZ6oQvRzkfi3ytU8GCkO46o+TNCOxQzQrIU2J3N8UmsM3TKKmQO7XIl/7RPXTrBohfGMgIiK5qMqaTUdDgzWrKbpERET08mhWlRAiIiLZqLiLbl1YCSEiIiKNYCWEiIhIAhwTUjdWQoiIiEgjWAkhIiKSAseE1ImNECIiIpH1fcMW1+/GSJrRpUsXSc8vh2a1YioRERG9PDgmhIiIiDSCjRAiIiLSCDZCiIiISCPYCCEiIiKNYCOEiIiINIKNECIiItKI/w+CpQC9TnmyFQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "acG89GbARxSM",
        "colab_type": "text"
      },
      "source": [
        "****As we can see above, if I am building a model for SP, then we can see that SP is highly correlated with RxoRt and it is highly neagatively related with RHOC. So, it is very must for us to include these datasets as an input while building a model for SP. ****\n",
        "\n",
        "> **Before making a model decide a threshold of correlation to decide which parameters to take as an input for making models**."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WCiyL2ATRxSN",
        "colab_type": "text"
      },
      "source": [
        "We can also make a scatter plot to visualize the same data\n",
        "\n",
        "Scatter and density plots:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "_kg_hide-input": false,
        "trusted": true,
        "id": "sVHdFUzhRxSN",
        "colab_type": "code",
        "colab": {},
        "outputId": "0b992efb-fdc9-4754-b0b3-b79ebabaf334"
      },
      "source": [
        "plotScatterMatrix(df1, 20, 10)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x1440 with 100 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xBLaAkx5RxSQ",
        "colab_type": "text"
      },
      "source": [
        "## Import Deep learning Dependencies and libray Pytorch"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "w1_VqRYsRxSR",
        "colab_type": "code",
        "colab": {},
        "outputId": "56b5b532-0506-41a6-dcc2-0657eea1ad6c"
      },
      "source": [
        "!conda install pytorch torchvision cudatoolkit=10.2 -c pytorch"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting package metadata (current_repodata.json): done\n",
            "Solving environment: - ^C\n",
            "failed with initial frozen solve. Retrying with flexible solve.\n",
            "\n",
            "CondaError: KeyboardInterrupt\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "hXwysbfmRxST",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import torch\n",
        "import torchvision\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "from torchvision.transforms import ToTensor\n",
        "from torchvision.utils import make_grid\n",
        "from torch.utils.data.dataloader import DataLoader\n",
        "from torch.utils.data import random_split, TensorDataset\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H7cPNGmbRxSW",
        "colab_type": "text"
      },
      "source": [
        "Now we are going to build our own model class WellLogModel, which is build over nn.modules of PyTorch. I will tell you later, What this code do. But first run the below code. We will come back here to see what it will do."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "_zhbG7DhRxSW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class WellLogModel(nn.Module):\n",
        "    \"\"\"Model to create Neural Network\"\"\"\n",
        "    def __init__(self, in_dim,H,out_dim):\n",
        "        super(WellLogModel, self).__init__()\n",
        "        self.input_layer= nn.Linear(in_dim,H//2)\n",
        "        self.hidden_1 = nn.Linear(H//2,H)\n",
        "        self.hidden_2 = nn.Linear(H,H//2)\n",
        "        self.output_layer = nn.Linear(H//2,out_dim)\n",
        "    def forward(self, x):\n",
        "        h_relu = self.input_layer(x)\n",
        "        h_relu = F.relu(h_relu) # First activation\n",
        "        h_relu = self.hidden_1(h_relu)\n",
        "        h_relu = F.relu(h_relu) # Second activation\n",
        "        h_relu = self.hidden_2(h_relu)\n",
        "        h_relu = F.relu(h_relu) # Third activation\n",
        "        y_pred = self.output_layer(h_relu)\n",
        "        return y_pred\n",
        "        \n",
        "    def training_step(self, batch):\n",
        "        inputs, targets = batch \n",
        "        out = self(inputs)                  # Generate predictions\n",
        "        loss = F.l1_loss(out, targets)        # Calculate loss\n",
        "        return loss\n",
        "    \n",
        "    def validation_step(self, batch):\n",
        "        inputs, targets = batch \n",
        "        out = self(inputs)                    # Generate predictions\n",
        "        loss = F.l1_loss(out, targets)          # Calculate loss\n",
        "        return {'val_loss': loss.detach()}\n",
        "        \n",
        "    def validation_epoch_end(self, outputs):\n",
        "        batch_losses = [x['val_loss'] for x in outputs]\n",
        "        epoch_loss = torch.stack(batch_losses).mean()   # Combine losses\n",
        "        return {'val_loss': epoch_loss.item()}\n",
        "    \n",
        "    def epoch_end(self, epoch, result, num_epochs):\n",
        "        if (epoch+1) % 100 == 0 or epoch == num_epochs-1:\n",
        "            print(\"Epoch [{}], val_loss: {:.4f}\".format(epoch+1, result['val_loss']))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "8SBLRkydRxSa",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# evaluation and fitting code, This will evaluate our model performance and cost function\n",
        "def evaluate(model, val_loader):\n",
        "    outputs = [model.validation_step(batch) for batch in val_loader]\n",
        "    return model.validation_epoch_end(outputs)\n",
        "\n",
        "## change SGD to change the optimizer\n",
        "def fit(epochs, lr, model, train_loader, val_loader, opt_func=torch.optim.SGD):\n",
        "    val_hist = []\n",
        "    train_hist = []\n",
        "    optimizer = opt_func(model.parameters(), lr)\n",
        "    for epoch in range(epochs):\n",
        "        # Training Phase \n",
        "        for batch in train_loader:\n",
        "            loss = model.training_step(batch)\n",
        "            loss.backward()\n",
        "            optimizer.step()\n",
        "            optimizer.zero_grad()\n",
        "            train_hist.append(loss.item())\n",
        "        # Validation phase\n",
        "        result = evaluate(model, val_loader)\n",
        "        model.epoch_end(epoch, result, epochs)\n",
        "        val_hist.append(result)\n",
        "    return val_hist,train_hist"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bTMZBNijRxSe",
        "colab_type": "text"
      },
      "source": [
        "## Import data and convert into tensors"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "9oY80iw2RxSf",
        "colab_type": "code",
        "colab": {},
        "outputId": "d0200850-db44-42b2-da82-e0f3dd40eeca"
      },
      "source": [
        "DATA_FILENAME = \"/kaggle/input/log.csv\"\n",
        "dataframe = pd.read_csv(DATA_FILENAME)\n",
        "dataframe.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Depth     RxoRt    RLL3       SP      RILD      MN      MI    MCAL    DCAL  \\\n",
              "0  195.0  226.0848  0.4076  69.8953  132.5052 -0.3548  0.1863  5.1090  1.8878   \n",
              "1  195.5  223.5031  0.4063  69.2303  123.6225 -0.3619  0.1867  5.1031  1.8882   \n",
              "2  196.0  221.4560  0.4047  68.4478  116.9258 -0.3668  0.1860  5.0872  1.8878   \n",
              "3  196.5  219.8248  0.4033  67.4843  111.7925 -0.3613  0.1867  5.0881  1.8884   \n",
              "4  197.0  218.1438  0.4023  66.3013  106.7821 -0.3569  0.1870  5.0972  1.8883   \n",
              "\n",
              "     RHOB    RHOC     DPOR     CNLS       GR  \n",
              "0  1.6973 -0.6303  59.2216  30.0657  60.4576  \n",
              "1  1.6791 -0.6409  60.2877  26.7625  54.1495  \n",
              "2  1.6585 -0.6539  61.4914  27.6017  51.9944  \n",
              "3  1.6435 -0.6649  62.3711  31.5870  52.9645  \n",
              "4  1.6390 -0.6705  62.6343  35.8251  54.9659  "
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Depth</th>\n",
              "      <th>RxoRt</th>\n",
              "      <th>RLL3</th>\n",
              "      <th>SP</th>\n",
              "      <th>RILD</th>\n",
              "      <th>MN</th>\n",
              "      <th>MI</th>\n",
              "      <th>MCAL</th>\n",
              "      <th>DCAL</th>\n",
              "      <th>RHOB</th>\n",
              "      <th>RHOC</th>\n",
              "      <th>DPOR</th>\n",
              "      <th>CNLS</th>\n",
              "      <th>GR</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>195.0</td>\n",
              "      <td>226.0848</td>\n",
              "      <td>0.4076</td>\n",
              "      <td>69.8953</td>\n",
              "      <td>132.5052</td>\n",
              "      <td>-0.3548</td>\n",
              "      <td>0.1863</td>\n",
              "      <td>5.1090</td>\n",
              "      <td>1.8878</td>\n",
              "      <td>1.6973</td>\n",
              "      <td>-0.6303</td>\n",
              "      <td>59.2216</td>\n",
              "      <td>30.0657</td>\n",
              "      <td>60.4576</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>195.5</td>\n",
              "      <td>223.5031</td>\n",
              "      <td>0.4063</td>\n",
              "      <td>69.2303</td>\n",
              "      <td>123.6225</td>\n",
              "      <td>-0.3619</td>\n",
              "      <td>0.1867</td>\n",
              "      <td>5.1031</td>\n",
              "      <td>1.8882</td>\n",
              "      <td>1.6791</td>\n",
              "      <td>-0.6409</td>\n",
              "      <td>60.2877</td>\n",
              "      <td>26.7625</td>\n",
              "      <td>54.1495</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>196.0</td>\n",
              "      <td>221.4560</td>\n",
              "      <td>0.4047</td>\n",
              "      <td>68.4478</td>\n",
              "      <td>116.9258</td>\n",
              "      <td>-0.3668</td>\n",
              "      <td>0.1860</td>\n",
              "      <td>5.0872</td>\n",
              "      <td>1.8878</td>\n",
              "      <td>1.6585</td>\n",
              "      <td>-0.6539</td>\n",
              "      <td>61.4914</td>\n",
              "      <td>27.6017</td>\n",
              "      <td>51.9944</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>196.5</td>\n",
              "      <td>219.8248</td>\n",
              "      <td>0.4033</td>\n",
              "      <td>67.4843</td>\n",
              "      <td>111.7925</td>\n",
              "      <td>-0.3613</td>\n",
              "      <td>0.1867</td>\n",
              "      <td>5.0881</td>\n",
              "      <td>1.8884</td>\n",
              "      <td>1.6435</td>\n",
              "      <td>-0.6649</td>\n",
              "      <td>62.3711</td>\n",
              "      <td>31.5870</td>\n",
              "      <td>52.9645</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>197.0</td>\n",
              "      <td>218.1438</td>\n",
              "      <td>0.4023</td>\n",
              "      <td>66.3013</td>\n",
              "      <td>106.7821</td>\n",
              "      <td>-0.3569</td>\n",
              "      <td>0.1870</td>\n",
              "      <td>5.0972</td>\n",
              "      <td>1.8883</td>\n",
              "      <td>1.6390</td>\n",
              "      <td>-0.6705</td>\n",
              "      <td>62.6343</td>\n",
              "      <td>35.8251</td>\n",
              "      <td>54.9659</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 252
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "GoFb7i7ZRxSi",
        "colab_type": "code",
        "colab": {},
        "outputId": "7fb84ea7-75cf-4d75-d0d4-74b094ff4361"
      },
      "source": [
        "# Get Number of Rows and Number of Colums\n",
        "num_rows, num_cols = dataframe.shape\n",
        "print(\"Number of Rows : \",num_rows)\n",
        "print(\"Number of Colums : \",num_cols)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Number of Rows :  8739\n",
            "Number of Colums :  14\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uEA9m-7rRxSk",
        "colab_type": "text"
      },
      "source": [
        "## Decide Input data and output data\n",
        "\n",
        "I am going to train a model for Density porosity DPOR, so my output will be DPOR. To know what should be the Input we have to see the Correlation plot to see how DPOR is related to other parameter.\n",
        "\n",
        "But actually there is no need to do it here, because our neural network is so big that it will automatically discards all the parameters which has no relation with RHOB. But it always adviced to choose best correlated data to make algorithm faster and give less load to the algorithm. Deep learning algorithms are computationaly very expensive specialy for big datas."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "kUmaWjaTRxSk",
        "colab_type": "code",
        "colab": {},
        "outputId": "6c0d4361-8635-45d8-b55f-22027c7da926"
      },
      "source": [
        "# I am using all the parameter as input except DPOR, which is ouput\n",
        "output_cols = [dataframe.DPOR.name]             # modify DPOR.name to your model.\n",
        "print(f'Output feature are : {output_cols}')\n",
        "input_cols = [cols for cols in dataframe]\n",
        "input_cols.remove(output_cols[0])               # input data = all data - output data.\n",
        "print(f'Input layers are {input_cols}')\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Output feature are : ['DPOR']\n",
            "Input layers are ['Depth', 'RxoRt', 'RLL3', 'SP', 'RILD', 'MN', 'MI', 'MCAL', 'DCAL', 'RHOB', 'RHOC', 'CNLS', 'GR']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SEACdqBMRxSn",
        "colab_type": "text"
      },
      "source": [
        "### Convert dataframe into input and output array\n",
        "\n",
        "I am using input_cols and output_cols to extract data from dataframe and then convert them to numpy. To do this I am making a function called dataframe2array()"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "sQjXngZHRxSn",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def dataframe2arrays(dataframe):\n",
        "    # Extract and convert required data to array\n",
        "    dataframe1 = dataframe.copy(deep=True)\n",
        "    inputs_array = dataframe1[input_cols].to_numpy()\n",
        "    targets_array = dataframe1[output_cols].to_numpy()\n",
        "    return inputs_array, targets_array"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "rQ13PGGDRxSq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# call dataframe2array to extract data in input_array and target_array\n",
        "inputs_array, targets_array = dataframe2arrays(dataframe)\n",
        "inputs_array, targets_array\n",
        "\n",
        "# convert array into tensors using torch.tensor()\n",
        "inputs = torch.tensor(inputs_array, dtype=torch.float32)\n",
        "targets = torch.tensor(targets_array, dtype=torch.float32)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "00F305jERxSt",
        "colab_type": "code",
        "colab": {},
        "outputId": "0f6bb59b-4132-4bfc-a4a4-d9dbf5cd4597"
      },
      "source": [
        "# print some values\n",
        "print(f'Input {inputs[0:2]},\\n output {targets[0:2]}')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Input tensor([[ 1.9500e+02,  2.2608e+02,  4.0760e-01,  6.9895e+01,  1.3251e+02,\n",
            "         -3.5480e-01,  1.8630e-01,  5.1090e+00,  1.8878e+00,  1.6973e+00,\n",
            "         -6.3030e-01,  3.0066e+01,  6.0458e+01],\n",
            "        [ 1.9550e+02,  2.2350e+02,  4.0630e-01,  6.9230e+01,  1.2362e+02,\n",
            "         -3.6190e-01,  1.8670e-01,  5.1031e+00,  1.8882e+00,  1.6791e+00,\n",
            "         -6.4090e-01,  2.6763e+01,  5.4150e+01]]),\n",
            " output tensor([[59.2216],\n",
            "        [60.2877]])\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BqeJcjb4RxSw",
        "colab_type": "text"
      },
      "source": [
        "## Divide Dataset into Train, Validation and Test Data.\n",
        "\n",
        "Now to go further we have to divide our data set into 3 parts\n",
        "1. Training dataset : It is the data which we use to train the model. Generally 60-70% of data go for training.\n",
        "2. Validation dataset : This data is used to test the performance of our model and to visualize the error and cost function of model. It is also used to see how our algorithm performs by changing our hyperparameters(i.e Learning rate, momentum etc.)\n",
        "3. Test dataset : This is the final testing dataset to use for testing purpose. The difference between testing data and validation data is, we do not take any decision on the basis of tesitng data performance. If our algorithm does not perform well on the testing data then, either there is something wrong with the model preparation or something wrong with hyperparameters and optimization choosing.\n",
        "\n",
        "As a common practice 15% is devoted to validation and 15% data is devoted to testing. I have done the same."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "rRExMi8bRxSw",
        "colab_type": "code",
        "colab": {},
        "outputId": "a6eb5781-04ee-42cf-b25a-1403dbd8ea2b"
      },
      "source": [
        "# First combine our input and targets into one dataset\n",
        "dataset = TensorDataset(inputs, targets)\n",
        "# print some dataset\n",
        "print(f'Dataset {dataset[0:2]}')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Dataset (tensor([[ 1.9500e+02,  2.2608e+02,  4.0760e-01,  6.9895e+01,  1.3251e+02,\n",
            "         -3.5480e-01,  1.8630e-01,  5.1090e+00,  1.8878e+00,  1.6973e+00,\n",
            "         -6.3030e-01,  3.0066e+01,  6.0458e+01],\n",
            "        [ 1.9550e+02,  2.2350e+02,  4.0630e-01,  6.9230e+01,  1.2362e+02,\n",
            "         -3.6190e-01,  1.8670e-01,  5.1031e+00,  1.8882e+00,  1.6791e+00,\n",
            "         -6.4090e-01,  2.6763e+01,  5.4150e+01]]), tensor([[59.2216],\n",
            "        [60.2877]]))\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-Qm9_BvDRxSy",
        "colab_type": "text"
      },
      "source": [
        "The dataset is a collection of inputs and targets zip together into a one set. we do this, to easily divide both data together, other wise it is long code to divide then individually and other problems such as indexing."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7pIgNQD5RxS2",
        "colab_type": "text"
      },
      "source": [
        "#### Define the percentage of data we want to extract."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "1jvAvSB1RxS3",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "## training and validation spliting\n",
        "def split_ds(dataset, val_percent):\n",
        "    val_size = int(len(dataset) * val_percent)\n",
        "    train_size = len(dataset) - val_size\n",
        "    train_ds, val_ds = random_split(dataset, [train_size, val_size]) # Use the random_split function to split dataset into 2 parts of the desired length\n",
        "    return train_ds, val_ds"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "hgek2ucwRxS9",
        "colab_type": "code",
        "colab": {},
        "outputId": "e2210ba1-ff25-4120-997e-bd6ad60dfacd"
      },
      "source": [
        "val_percent = 0.30 # between 0.2 and 0.3\n",
        "train_ds, val_ds = split_ds(dataset, val_percent)\n",
        "print(f'Train dataset {train_ds[0:3]}\\n')\n",
        "print(f'Validation dataset{val_ds[0:3]}')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train dataset (tensor([[ 4.3230e+03, -2.0521e+00,  1.9216e+02, -1.1633e+02,  2.0713e+02,\n",
            "          1.5942e+02,  1.6811e+02,  7.9637e+00,  7.7627e+00,  2.6905e+00,\n",
            "          1.8200e-02,  2.5927e+00,  4.2111e+01],\n",
            "        [ 2.9635e+03, -2.2523e+01,  1.6554e+01, -5.3847e+01,  9.1812e+00,\n",
            "          1.0518e+00,  2.5280e-01,  5.0897e+00,  2.0210e+00,  1.6930e+00,\n",
            "          1.3380e-01,  9.1260e+00,  5.6320e+01],\n",
            "        [ 1.6585e+03, -8.5337e+01,  5.8981e+00, -1.5570e+02,  3.6750e+00,\n",
            "          3.4758e+00,  3.4651e+00,  5.0930e+00,  1.9196e+00,  1.4215e+00,\n",
            "          2.7100e-02,  1.1616e+01,  5.1755e+01]]), tensor([[ 1.1376],\n",
            "        [59.4716],\n",
            "        [75.3505]]))\n",
            "\n",
            "Validation dataset(tensor([[ 2.9370e+03, -3.2024e+01,  7.7704e+00, -6.1047e+01,  3.5307e+00,\n",
            "          3.0210e-01,  7.8900e-02,  5.1076e+00,  1.9773e+00,  1.7430e+00,\n",
            "          1.5170e-01,  1.8539e+01,  6.5221e+01],\n",
            "        [ 4.4950e+03, -1.7971e+01,  7.7800e+01, -8.8573e+01,  4.8683e+01,\n",
            "          5.2799e+01,  6.0395e+01,  7.9828e+00,  8.0245e+00,  2.6782e+00,\n",
            "          1.5200e-02,  4.0884e+00,  4.2946e+01],\n",
            "        [ 2.1220e+03, -2.0526e+01,  7.8529e+00, -7.7377e+01,  4.8615e+00,\n",
            "          2.0860e-01, -1.9340e-01,  5.0970e+00,  1.9325e+00,  2.0146e+00,\n",
            "          2.5770e-01,  1.3816e+01,  9.0732e+01]]), tensor([[56.5497],\n",
            "        [ 1.8572],\n",
            "        [40.6651]]))\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Aqm1dbTuRxS_",
        "colab_type": "text"
      },
      "source": [
        "The validation data contain 30% of data, now I extract 15% for training data and 15% for val_ds"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "7x-YnyPTRxS_",
        "colab_type": "code",
        "colab": {},
        "outputId": "a2341cc3-7c3d-4a6f-8396-1f1d63a76db7"
      },
      "source": [
        "test_percent = 0.5\n",
        "test_ds, val_ds = split_ds(val_ds, test_percent)\n",
        "print(f'Train dataset size is {len(train_ds)}\\n')\n",
        "print(f'Test dataset size is {len(test_ds)}\\n')\n",
        "print(f'Validation dataset size is {len(val_ds)}')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train dataset size is 6118\n",
            "\n",
            "Test dataset size is 1311\n",
            "\n",
            "Validation dataset size is 1310\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ixugVz1dRxTB",
        "colab_type": "text"
      },
      "source": [
        "#### Make the batches of dataset, dataloader and GPU config\n",
        "Here my dataset is not that big but in general the datasets are very big in 10-100 millions. In that case we need to run the algorithm in the batches. I divide dataset into dataloader with 64 element in each batch.\n",
        "\n",
        "I also configure my dataloader for GPU's. If GPU is available then our algorithm will work on CUDA.\n",
        "\n",
        "I also shuffle the train loader to make algorithm more random and powerfull."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "tnUFpUPjRxTC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "batch_size = 64\n",
        "# Dataloaders\n",
        "train_loader = DataLoader(train_ds, batch_size, shuffle=True, num_workers=4, pin_memory=True)\n",
        "val_loader = DataLoader(val_ds, batch_size*2, num_workers=4, pin_memory=True)\n",
        "test_loader = DataLoader(test_ds, batch_size*2, num_workers=4, pin_memory=True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "7vniORYtRxTD",
        "colab_type": "code",
        "colab": {},
        "outputId": "05ff3235-dcda-48ec-8bbd-89d0caa82a9c"
      },
      "source": [
        "# To print loaders we have to use for loop\n",
        "for X,Y in train_loader:\n",
        "    print(f'Input of train loader {X}')\n",
        "    print(f'Targets of train loader {X}')\n",
        "    break # it only print one element"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Input of train loader tensor([[ 3.7095e+03, -1.5628e+01,  1.4406e+01, -3.8928e+01,  1.0923e+01,\n",
            "          9.4168e+00,  1.6517e+01,  8.0497e+00,  8.0254e+00,  2.5966e+00,\n",
            "          4.2600e-02,  1.9946e+01,  9.2314e+01],\n",
            "        [ 1.1205e+03,  1.4955e+01,  1.1535e+01, -1.2200e+02,  1.5675e+01,\n",
            "          3.9370e-01,  1.8050e-01,  5.0955e+00,  1.8975e+00,  1.9157e+00,\n",
            "          2.2580e-01,  3.8856e+01,  7.2840e+01],\n",
            "        [ 3.5730e+03, -1.6704e+01,  5.9436e+00, -4.2643e+01,  3.9063e+00,\n",
            "          5.1490e-01,  1.6410e-01,  5.0991e+00,  8.9010e+00,  2.4097e+00,\n",
            "          1.4650e-01,  3.1357e+01,  1.3123e+02],\n",
            "        [ 3.4020e+03, -2.0689e+01,  1.7308e+01, -3.9713e+01,  9.9077e+00,\n",
            "          1.2287e+00,  2.9530e-01,  5.0982e+00,  2.0446e+00,  2.0604e+00,\n",
            "          2.8680e-01,  6.3007e+00,  4.3837e+01],\n",
            "        [ 1.6475e+03, -2.3133e+01,  8.1271e+00, -1.3822e+02,  3.7086e+00,\n",
            "          1.7258e+00,  1.3562e+00,  5.0841e+00,  1.9190e+00,  1.4346e+00,\n",
            "          3.4800e-02,  4.2579e+01,  6.3431e+01],\n",
            "        [ 2.1925e+03,  1.6000e-03,  1.3454e+01, -9.2565e+01,  1.2480e+01,\n",
            "          1.4700e-02, -2.6250e-01,  5.0982e+00,  1.9337e+00,  2.0838e+00,\n",
            "          2.7480e-01,  1.0754e+01,  8.4245e+01],\n",
            "        [ 1.5180e+03, -3.0759e+00,  6.7421e+00, -1.3365e+02,  6.2963e+00,\n",
            "          4.4625e+00,  6.4039e+00,  5.1074e+00,  1.9253e+00,  2.1399e+00,\n",
            "          2.8640e-01,  2.1786e+01,  1.0290e+02],\n",
            "        [ 3.2330e+03, -6.3508e+01,  1.6220e+01, -6.4083e+01,  4.3239e+00,\n",
            "          9.7980e-01,  2.2360e-01,  5.0893e+00,  2.0206e+00,  1.6975e+00,\n",
            "          1.3610e-01,  1.0789e+01,  5.0133e+01],\n",
            "        [ 2.4460e+03, -5.2706e+01,  1.4796e+01, -6.1157e+01,  3.8535e+00,\n",
            "          1.7290e-01, -1.2200e-01,  5.0929e+00,  1.9330e+00,  1.3651e+00,\n",
            "          9.5000e-03,  1.0694e+01,  6.4569e+01],\n",
            "        [ 3.2505e+03, -8.0629e+00,  4.1636e+00, -3.3754e+01,  3.3843e+00,\n",
            "          2.8100e-01,  9.0600e-02,  5.1015e+00,  2.0205e+00,  2.2270e+00,\n",
            "          3.0380e-01,  2.4859e+01,  7.8888e+01],\n",
            "        [ 2.6550e+02, -2.1859e+00,  2.0027e+01, -1.4152e+02,  1.8632e+01,\n",
            "          1.0168e+00,  4.8130e-01,  5.0846e+00,  1.8879e+00,  2.1971e+00,\n",
            "          6.4500e-02,  3.3697e+01,  8.3768e+01],\n",
            "        [ 1.4625e+03, -1.0841e+01,  4.2235e+00, -1.4781e+02,  3.2943e+00,\n",
            "          3.6265e+00,  4.5880e+00,  5.1079e+00,  1.9258e+00,  1.9029e+00,\n",
            "          2.2830e-01,  3.0863e+01,  1.0357e+02],\n",
            "        [ 2.6195e+03, -7.2695e+00,  3.2194e+00, -5.4759e+01,  2.8745e+00,\n",
            "          1.3400e-01,  1.4300e-02,  5.1072e+00,  1.9756e+00,  2.3980e+00,\n",
            "          2.5830e-01,  2.0245e+01,  7.3436e+01],\n",
            "        [ 6.3650e+02, -1.6451e+01,  4.4550e+00, -1.3512e+02,  2.9432e+00,\n",
            "          1.5104e+00,  1.7385e+00,  5.0897e+00,  1.9020e+00,  1.7383e+00,\n",
            "          1.7340e-01,  3.1689e+01,  1.0569e+02],\n",
            "        [ 3.3205e+03, -9.8630e+00,  5.8597e+00, -4.1759e+01,  4.5635e+00,\n",
            "          2.6260e-01,  9.0400e-02,  5.0859e+00,  2.0356e+00,  1.9492e+00,\n",
            "          2.3730e-01,  1.5927e+01,  8.7959e+01],\n",
            "        [ 3.1240e+03, -4.7084e+01,  7.3989e+00, -7.3120e+01,  2.3804e+00,\n",
            "          6.9880e-01,  1.5950e-01,  5.1085e+00,  2.0171e+00,  1.5222e+00,\n",
            "          5.9000e-02,  2.4150e+01,  2.5726e+01],\n",
            "        [ 2.6385e+03, -1.8546e+01,  2.5265e+00, -5.9072e+01,  1.6782e+00,\n",
            "          8.2800e-02,  1.2300e-02,  5.0868e+00,  1.9792e+00,  1.7403e+00,\n",
            "          1.6220e-01,  3.3596e+01,  8.4914e+01],\n",
            "        [ 7.9100e+02, -4.6745e+00,  1.3380e+01, -1.3613e+02,  1.1323e+01,\n",
            "          1.4403e+00,  6.6300e-01,  5.0888e+00,  1.9036e+00,  1.6319e+00,\n",
            "          1.0780e-01,  3.0169e+01,  7.5997e+01],\n",
            "        [ 3.3180e+03, -7.8358e+00,  6.2716e+00, -3.7968e+01,  5.1839e+00,\n",
            "          2.6740e-01,  8.7600e-02,  5.0979e+00,  2.0350e+00,  1.9646e+00,\n",
            "          2.3980e-01,  1.8423e+01,  9.4009e+01],\n",
            "        [ 3.8395e+03, -3.9591e+01,  3.5706e+01, -7.8295e+01,  1.2721e+01,\n",
            "          4.2332e+01,  5.4783e+01,  7.9712e+00,  8.0255e+00,  2.6407e+00,\n",
            "          6.4000e-03,  7.8269e+00,  5.1386e+01],\n",
            "        [ 2.1520e+03, -3.7011e+00,  2.3104e+01, -9.5447e+01,  1.9607e+01,\n",
            "          6.6000e-03, -2.4870e-01,  5.0944e+00,  1.9353e+00,  1.9181e+00,\n",
            "          2.1460e-01,  3.8856e+00,  6.3899e+01],\n",
            "        [ 4.0480e+03, -4.5645e+01,  1.1482e+02, -1.0205e+02,  3.5057e+01,\n",
            "          1.6360e+01,  1.2601e+01,  7.7431e+00,  7.9973e+00,  2.6300e+00,\n",
            "          5.6500e-02,  4.9596e+00,  3.6733e+01],\n",
            "        [ 1.5905e+03, -3.5607e+00,  6.7678e+00, -1.3692e+02,  6.1896e+00,\n",
            "          3.5090e+00,  2.7596e+00,  5.1015e+00,  1.9265e+00,  1.6048e+00,\n",
            "          9.4600e-02,  2.4356e+01,  1.0368e+02],\n",
            "        [ 1.3210e+03, -8.9241e+00,  3.8347e+00, -1.3103e+02,  3.0711e+00,\n",
            "          6.2460e-01,  6.6850e-01,  5.0911e+00,  1.9240e+00,  1.4596e+00,\n",
            "          4.4900e-02,  3.2778e+01,  7.3985e+01],\n",
            "        [ 4.6510e+03, -8.1941e+01,  3.3571e+02, -9.0392e+01,  3.9055e+01,\n",
            "          3.9009e+01,  4.4750e+01,  7.9241e+00,  7.8797e+00,  2.6803e+00,\n",
            "          2.0300e-02,  3.0049e+00,  6.6697e+01],\n",
            "        [ 2.6670e+03, -3.9684e+01,  2.7204e+01, -4.4237e+01,  7.6780e+00,\n",
            "          5.3900e-01,  5.8800e-02,  5.1039e+00,  1.9800e+00,  2.0765e+00,\n",
            "          2.7660e-01,  6.6696e+00,  3.9078e+01],\n",
            "        [ 3.4205e+03, -4.1409e+01,  6.7325e+01, -4.6058e+01,  2.1662e+01,\n",
            "          1.1328e+00,  2.6210e-01,  5.1074e+00,  2.0424e+00,  1.9632e+00,\n",
            "          2.4020e-01,  4.1645e+00,  4.2112e+01],\n",
            "        [ 4.1360e+03, -4.5001e+01,  2.7231e+02, -9.4006e+01,  8.5319e+01,\n",
            "          6.8609e+01,  9.7603e+01,  7.9288e+00,  7.9381e+00,  2.6680e+00,\n",
            "          1.4300e-02,  2.3598e+00,  3.1392e+01],\n",
            "        [ 2.7325e+03, -2.5740e+01,  1.1649e+01, -4.0997e+01,  5.9964e+00,\n",
            "          2.8720e-01,  5.1700e-02,  5.1001e+00,  1.9787e+00,  2.0254e+00,\n",
            "          2.4740e-01,  2.2066e+01,  7.0952e+01],\n",
            "        [ 1.2725e+03, -2.0160e+01,  6.7412e+00, -1.3385e+02,  4.1359e+00,\n",
            "          3.9260e-01,  1.7540e-01,  5.0979e+00,  1.9244e+00,  1.5604e+00,\n",
            "          8.4800e-02,  2.9651e+01,  8.7983e+01],\n",
            "        [ 7.8250e+02,  7.8105e+00,  1.3518e+01, -1.2860e+02,  1.7847e+01,\n",
            "          1.6193e+00,  9.2150e-01,  5.0911e+00,  1.9004e+00,  1.6435e+00,\n",
            "          1.1430e-01,  3.0128e+01,  7.7966e+01],\n",
            "        [ 4.0010e+03, -4.7776e+01,  6.0706e+01, -9.9167e+01,  1.5531e+01,\n",
            "          1.1805e+01,  8.8380e+00,  7.7721e+00,  7.7193e+00,  2.5781e+00,\n",
            "          5.2000e-02,  7.3929e+00,  2.7229e+01],\n",
            "        [ 2.2035e+03,  1.5364e+01,  1.6786e+01, -9.7228e+01,  2.4284e+01,\n",
            "          6.0000e-04, -2.5670e-01,  5.0981e+00,  1.9336e+00,  2.0897e+00,\n",
            "          2.6430e-01,  9.6884e+00,  8.1914e+01],\n",
            "        [ 3.9560e+03, -4.4666e+01,  1.1203e+01, -1.1437e+02,  4.0376e+00,\n",
            "          8.4137e+00,  6.5072e+00,  7.7738e+00,  7.8936e+00,  2.4867e+00,\n",
            "          6.8400e-02,  1.5474e+01,  6.4025e+01],\n",
            "        [ 3.4925e+03, -5.3725e+01,  2.1518e+01, -6.1762e+01,  6.1712e+00,\n",
            "          1.0824e+00,  2.5080e-01,  5.1023e+00,  2.0584e+00,  2.0289e+00,\n",
            "          2.6480e-01,  1.5085e+01,  3.7561e+01],\n",
            "        [ 3.4850e+03, -1.6575e+01,  8.2595e+00, -3.6074e+01,  5.2458e+00,\n",
            "          9.9910e-01,  2.8140e-01,  5.1080e+00,  2.0477e+00,  1.9552e+00,\n",
            "          2.4780e-01,  2.0726e+01,  8.4766e+01],\n",
            "        [ 8.1250e+02, -9.6044e+00,  1.0756e+01, -1.3980e+02,  8.1638e+00,\n",
            "          1.4881e+00,  8.5690e-01,  5.1015e+00,  1.8979e+00,  1.5256e+00,\n",
            "          7.3400e-02,  3.7665e+01,  1.1876e+02],\n",
            "        [ 3.2785e+03, -2.3687e+01,  7.3829e+00, -4.4604e+01,  6.4245e+00,\n",
            "          9.7260e-01,  2.3780e-01,  5.0947e+00,  2.0227e+00,  1.6918e+00,\n",
            "          1.3600e-01,  8.6526e+00,  3.5038e+01],\n",
            "        [ 4.8750e+02,  1.8015e+01,  1.7484e+01, -1.1807e+02,  3.1880e+01,\n",
            "          4.7960e-01,  2.8440e-01,  5.0858e+00,  1.8992e+00,  2.2391e+00,\n",
            "          1.0320e-01,  3.6099e+01,  3.0090e+01],\n",
            "        [ 1.5400e+03,  6.8910e-01,  5.7038e+00, -1.3568e+02,  5.8436e+00,\n",
            "          1.1039e+00,  1.0936e+00,  5.0852e+00,  1.9257e+00,  1.5098e+00,\n",
            "          6.0100e-02,  3.0153e+01,  9.2254e+01],\n",
            "        [ 2.6865e+03, -2.6826e+01,  1.0965e+01, -5.0591e+01,  4.5416e+00,\n",
            "          3.6550e-01,  4.6000e-02,  5.0869e+00,  1.9766e+00,  2.2609e+00,\n",
            "          3.2230e-01,  2.4028e+01,  6.7386e+01],\n",
            "        [ 1.3715e+03, -7.7125e+00,  6.2889e+00, -1.3436e+02,  5.1746e+00,\n",
            "          5.1286e+00,  7.0797e+00,  5.1063e+00,  1.9250e+00,  2.1022e+00,\n",
            "          2.8320e-01,  3.0726e+01,  1.0253e+02],\n",
            "        [ 3.1860e+03, -4.0021e+01,  7.2209e+00, -5.7839e+01,  2.3736e+00,\n",
            "          8.4540e-01,  2.2680e-01,  5.0971e+00,  2.0214e+00,  1.4718e+00,\n",
            "          4.5100e-02,  2.2858e+01,  6.8340e+01],\n",
            "        [ 1.1270e+03, -1.5702e+01,  5.6761e+00, -1.3633e+02,  3.8375e+00,\n",
            "          2.9750e-01,  1.6350e-01,  5.0984e+00,  1.9012e+00,  1.7915e+00,\n",
            "          1.8350e-01,  3.3733e+01,  9.5920e+01],\n",
            "        [ 3.8110e+03, -4.5929e+01,  4.2831e+01, -7.7464e+01,  1.1924e+01,\n",
            "          3.7900e+01,  4.7888e+01,  7.9994e+00,  8.0243e+00,  2.5136e+00,\n",
            "          2.2300e-02,  1.0244e+01,  6.8967e+01],\n",
            "        [ 2.1055e+03, -2.1764e+01,  4.0977e+00, -7.5182e+01,  2.4666e+00,\n",
            "          1.7000e-01, -1.9350e-01,  5.0904e+00,  1.9331e+00,  1.8924e+00,\n",
            "          2.1230e-01,  2.2299e+01,  1.0134e+02],\n",
            "        [ 2.9000e+03, -7.4002e+00,  4.1896e+00, -4.6596e+01,  3.5547e+00,\n",
            "          1.5120e-01,  5.5900e-02,  5.0887e+00,  1.9786e+00,  1.5703e+00,\n",
            "          8.9900e-02,  2.2248e+01,  1.0317e+02],\n",
            "        [ 7.2150e+02, -9.9835e+00,  7.5707e+00, -1.3841e+02,  5.6896e+00,\n",
            "          9.9500e-01,  4.4150e-01,  5.0968e+00,  1.8994e+00,  1.7446e+00,\n",
            "          1.7070e-01,  3.5305e+01,  1.0489e+02],\n",
            "        [ 2.4300e+03, -4.3864e+01,  6.5193e+00, -7.0766e+01,  2.2420e+00,\n",
            "          2.5320e-01, -2.0990e-01,  5.0841e+00,  1.9340e+00,  1.4857e+00,\n",
            "          4.3500e-02,  1.8783e+01,  8.1415e+01],\n",
            "        [ 3.5645e+03, -3.1265e+01,  1.1503e+01, -4.2005e+01,  4.7673e+00,\n",
            "          2.1380e+00,  1.0378e+00,  5.0969e+00,  2.1090e+00,  1.9832e+00,\n",
            "          2.5350e-01,  2.1342e+01,  1.1299e+02],\n",
            "        [ 4.0270e+03, -2.1986e+01,  1.1120e+01, -1.1241e+02,  5.9569e+00,\n",
            "          1.1910e+01,  1.1466e+01,  7.7707e+00,  7.8936e+00,  2.4611e+00,\n",
            "          5.6300e-02,  2.2357e+01,  4.8590e+01],\n",
            "        [ 6.3150e+02, -1.1943e+01,  4.3079e+00, -1.3528e+02,  3.2178e+00,\n",
            "          1.2204e+00,  1.0304e+00,  5.1032e+00,  1.9027e+00,  1.9063e+00,\n",
            "          2.2940e-01,  2.8628e+01,  1.0906e+02],\n",
            "        [ 2.4785e+03, -2.4724e+01,  2.9669e+00, -4.9547e+01,  1.6244e+00,\n",
            "          1.4050e-01, -3.4600e-02,  5.1026e+00,  1.9335e+00,  2.0449e+00,\n",
            "          2.6330e-01,  2.6680e+01,  1.1232e+02],\n",
            "        [ 3.4975e+03, -1.5355e+01,  4.5815e+00, -4.1482e+01,  3.7841e+00,\n",
            "          3.5250e-01,  1.0090e-01,  5.0938e+00,  2.0537e+00,  1.7500e+00,\n",
            "          1.6340e-01,  3.3305e+01,  1.2430e+02],\n",
            "        [ 3.2240e+03, -1.6656e+01,  6.8899e+00, -3.7278e+01,  4.1398e+00,\n",
            "          8.7590e-01,  2.2300e-01,  5.1019e+00,  2.0213e+00,  1.6729e+00,\n",
            "          1.2310e-01,  1.9330e+01,  9.1629e+01],\n",
            "        [ 2.4525e+03, -6.5339e+01,  1.2100e+01, -6.0221e+01,  2.3134e+00,\n",
            "          1.2710e-01, -5.7600e-02,  5.0974e+00,  1.9352e+00,  1.3743e+00,\n",
            "          9.7000e-03,  1.4782e+01,  7.3165e+01],\n",
            "        [ 5.2800e+02, -4.4992e+00,  1.2069e+01, -1.4353e+02,  1.0627e+01,\n",
            "          7.0790e-01,  3.3660e-01,  5.0885e+00,  1.8992e+00,  2.3116e+00,\n",
            "          7.3800e-02,  2.8415e+01,  1.1324e+02],\n",
            "        [ 2.1150e+03, -1.0457e+01,  4.5501e+00, -7.6561e+01,  3.9824e+00,\n",
            "          1.2200e-01, -2.0060e-01,  5.0925e+00,  1.9334e+00,  1.9389e+00,\n",
            "          2.2870e-01,  1.8875e+01,  1.0266e+02],\n",
            "        [ 1.1585e+03, -5.1679e+00,  1.2891e+01, -1.2934e+02,  1.0767e+01,\n",
            "          4.1390e-01,  1.7910e-01,  5.1008e+00,  1.8996e+00,  1.9742e+00,\n",
            "          2.4800e-01,  3.2977e+01,  7.5354e+01],\n",
            "        [ 2.4585e+03, -5.5992e+01,  7.9409e+00, -5.9071e+01,  1.8532e+00,\n",
            "          2.1670e-01, -2.5600e-02,  5.1053e+00,  1.9326e+00,  1.5752e+00,\n",
            "          8.3200e-02,  2.1045e+01,  7.4670e+01],\n",
            "        [ 3.3750e+02, -4.9930e+00,  2.2818e+01, -1.1698e+02,  2.0330e+01,\n",
            "          6.9680e-01,  3.4060e-01,  5.1070e+00,  1.8897e+00,  2.1373e+00,\n",
            "          1.5420e-01,  4.1186e+01,  1.1979e+02],\n",
            "        [ 1.9905e+03, -8.0962e+01,  2.7054e+00, -8.8653e+01,  3.3920e-01,\n",
            "          5.1460e-01, -8.0800e-02,  5.0934e+00,  1.9340e+00,  1.7699e+00,\n",
            "          1.7200e-01,  2.5124e+01,  4.7956e+01],\n",
            "        [ 9.7200e+02, -7.1711e+00,  1.3267e+01, -1.2974e+02,  9.4493e+00,\n",
            "          9.5700e-01,  4.5700e-01,  5.1018e+00,  1.8980e+00,  1.7639e+00,\n",
            "          1.7380e-01,  3.7102e+01,  1.0368e+02],\n",
            "        [ 5.1850e+02,  5.2585e+00,  1.0906e+01, -1.4491e+02,  1.2446e+01,\n",
            "          6.1930e-01,  3.2810e-01,  5.0873e+00,  1.9008e+00,  2.2891e+00,\n",
            "          5.3600e-02,  2.6266e+01,  9.0310e+01]])\n",
            "Targets of train loader tensor([[ 3.7095e+03, -1.5628e+01,  1.4406e+01, -3.8928e+01,  1.0923e+01,\n",
            "          9.4168e+00,  1.6517e+01,  8.0497e+00,  8.0254e+00,  2.5966e+00,\n",
            "          4.2600e-02,  1.9946e+01,  9.2314e+01],\n",
            "        [ 1.1205e+03,  1.4955e+01,  1.1535e+01, -1.2200e+02,  1.5675e+01,\n",
            "          3.9370e-01,  1.8050e-01,  5.0955e+00,  1.8975e+00,  1.9157e+00,\n",
            "          2.2580e-01,  3.8856e+01,  7.2840e+01],\n",
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            "          8.3200e-02,  2.1045e+01,  7.4670e+01],\n",
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            "          1.5420e-01,  4.1186e+01,  1.1979e+02],\n",
            "        [ 1.9905e+03, -8.0962e+01,  2.7054e+00, -8.8653e+01,  3.3920e-01,\n",
            "          5.1460e-01, -8.0800e-02,  5.0934e+00,  1.9340e+00,  1.7699e+00,\n",
            "          1.7200e-01,  2.5124e+01,  4.7956e+01],\n",
            "        [ 9.7200e+02, -7.1711e+00,  1.3267e+01, -1.2974e+02,  9.4493e+00,\n",
            "          9.5700e-01,  4.5700e-01,  5.1018e+00,  1.8980e+00,  1.7639e+00,\n",
            "          1.7380e-01,  3.7102e+01,  1.0368e+02],\n",
            "        [ 5.1850e+02,  5.2585e+00,  1.0906e+01, -1.4491e+02,  1.2446e+01,\n",
            "          6.1930e-01,  3.2810e-01,  5.0873e+00,  1.9008e+00,  2.2891e+00,\n",
            "          5.3600e-02,  2.6266e+01,  9.0310e+01]])\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hDKY2Ah0RxTF",
        "colab_type": "text"
      },
      "source": [
        "# Build the network\n",
        "\n",
        "This is how our neural network look like\n",
        "* It has 13 input features with one bias(not shown here)\n",
        "* It has 18 neurons in first hidden layer\n",
        "* 36 neurons in 2nd hidden layer\n",
        "* 18 neurons in 3rd hidden layer\n",
        "* and 1 output layer (here RHOB)\n",
        "![](https://i.imgur.com/EyoxGX2.png)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "DhD-tpWpRxTG",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "in_dim, H, out_dim = len(input_cols), 36 , len(output_cols) # see the WellLogModel class for reference"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "4ZC7zkIqRxTJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# call the WellLogModel in model variable\n",
        "model = WellLogModel(in_dim,H,out_dim)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "zVVJLUUGRxTM",
        "colab_type": "code",
        "colab": {},
        "outputId": "9479b978-7e8f-4d46-fc74-17dcfd01aba3"
      },
      "source": [
        "# see the model\n",
        "model"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "WellLogModel(\n",
              "  (input_layer): Linear(in_features=13, out_features=18, bias=True)\n",
              "  (hidden_1): Linear(in_features=18, out_features=36, bias=True)\n",
              "  (hidden_2): Linear(in_features=36, out_features=18, bias=True)\n",
              "  (output_layer): Linear(in_features=18, out_features=1, bias=True)\n",
              ")"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 266
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QT8-tqf9RxTO",
        "colab_type": "text"
      },
      "source": [
        "## Set the GPU device\n",
        "\n",
        "we set our device to fastest hardware, if gpu is available we switch our algorithm to GPU otherwise it will work on CPU."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "Ub4cDwpmRxTO",
        "colab_type": "code",
        "colab": {},
        "outputId": "ee129f38-e9d8-45db-f045-8621e947c57f"
      },
      "source": [
        "# see wheather GPU is availabel or not\n",
        "torch.cuda.is_available()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 267
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "Zb_vC4JrRxTQ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# This will pick the gpu details if you have (Don't go in details, just run and use it)\n",
        "def get_default_device():\n",
        "    \"\"\"Pick GPU if available, else CPU\"\"\"\n",
        "    if torch.cuda.is_available():\n",
        "        return torch.device('cuda')\n",
        "    else:\n",
        "        return torch.device('cpu')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "OavyAnSIRxTS",
        "colab_type": "code",
        "colab": {},
        "outputId": "f587b771-bbbe-47a4-b031-472476bf3934"
      },
      "source": [
        "device = get_default_device()\n",
        "device"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "device(type='cuda')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 269
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "gFb5VIRqRxTU",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# move our data and model to device GPU or CPU whichever is availabel\n",
        "def to_device(data, device):\n",
        "    if isinstance(data, (list,tuple)):\n",
        "        return [to_device(x, device) for x in data]\n",
        "    return data.to(device, non_blocking=True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MtaOIugZRxTX",
        "colab_type": "text"
      },
      "source": [
        "Now we have to create new dataloader for device, because the previous dataloader will only work on CPU's."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "9Mik72QeRxTX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class DeviceDataLoader():\n",
        "    \"\"\"Wrap a dataloader to move data to a device\"\"\"\n",
        "    def __init__(self, dl, device):\n",
        "        self.dl = dl\n",
        "        self.device = device\n",
        "        \n",
        "    def __iter__(self):\n",
        "        \"\"\"Yield a batch of data after moving it to device\"\"\"\n",
        "        for b in self.dl: \n",
        "            yield to_device(b, self.device)\n",
        "\n",
        "    def __len__(self):\n",
        "        \"\"\"Number of batches\"\"\"\n",
        "        return len(self.dl)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "H1gDatTERxTZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "train_loader = DeviceDataLoader(train_loader, device)\n",
        "val_loader = DeviceDataLoader(val_loader, device)\n",
        "test_loader = DeviceDataLoader(test_loader, device)\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "2Xr_S_1URxTb",
        "colab_type": "code",
        "colab": {},
        "outputId": "d32cd3e4-b536-400a-eb56-bd404e8008c2"
      },
      "source": [
        "for xb, yb in val_loader:\n",
        "    print('xb.device:', xb.device)\n",
        "    print('yb:', yb)\n",
        "    break"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "xb.device: cuda:0\n",
            "yb: tensor([[23.6992],\n",
            "        [53.8483],\n",
            "        [15.1834],\n",
            "        [ 9.4153],\n",
            "        [55.9741],\n",
            "        [49.8511],\n",
            "        [55.6100],\n",
            "        [29.5685],\n",
            "        [62.5438],\n",
            "        [27.8088],\n",
            "        [27.8128],\n",
            "        [13.4314],\n",
            "        [ 6.9251],\n",
            "        [74.4966],\n",
            "        [41.0792],\n",
            "        [85.8226],\n",
            "        [ 5.0954],\n",
            "        [10.7903],\n",
            "        [42.0002],\n",
            "        [58.3532],\n",
            "        [73.1666],\n",
            "        [50.2112],\n",
            "        [72.7853],\n",
            "        [69.1467],\n",
            "        [88.4891],\n",
            "        [64.0314],\n",
            "        [52.6521],\n",
            "        [30.1660],\n",
            "        [42.9240],\n",
            "        [36.3901],\n",
            "        [36.3033],\n",
            "        [ 2.7276],\n",
            "        [40.0057],\n",
            "        [53.3297],\n",
            "        [ 2.8930],\n",
            "        [57.5651],\n",
            "        [74.7233],\n",
            "        [62.9930],\n",
            "        [82.4945],\n",
            "        [77.4242],\n",
            "        [ 5.3925],\n",
            "        [49.2495],\n",
            "        [45.6287],\n",
            "        [37.6810],\n",
            "        [64.3983],\n",
            "        [29.1728],\n",
            "        [39.9308],\n",
            "        [20.3713],\n",
            "        [29.0208],\n",
            "        [55.6067],\n",
            "        [28.4879],\n",
            "        [12.5081],\n",
            "        [35.4455],\n",
            "        [ 0.6725],\n",
            "        [31.5985],\n",
            "        [50.9151],\n",
            "        [73.5126],\n",
            "        [ 5.1077],\n",
            "        [49.8224],\n",
            "        [16.3912],\n",
            "        [40.3180],\n",
            "        [39.7301],\n",
            "        [42.6379],\n",
            "        [48.3904],\n",
            "        [43.5318],\n",
            "        [87.1964],\n",
            "        [29.5751],\n",
            "        [54.9216],\n",
            "        [70.8830],\n",
            "        [62.9504],\n",
            "        [35.8664],\n",
            "        [ 1.1293],\n",
            "        [41.6393],\n",
            "        [41.8781],\n",
            "        [63.6375],\n",
            "        [70.5174],\n",
            "        [32.3245],\n",
            "        [13.1512],\n",
            "        [ 9.4149],\n",
            "        [55.1450],\n",
            "        [47.8733],\n",
            "        [68.9489],\n",
            "        [86.1376],\n",
            "        [53.0757],\n",
            "        [47.9832],\n",
            "        [43.2959],\n",
            "        [17.0034],\n",
            "        [63.3193],\n",
            "        [27.9287],\n",
            "        [65.8629],\n",
            "        [47.0692],\n",
            "        [46.2415],\n",
            "        [ 8.0611],\n",
            "        [77.1802],\n",
            "        [72.7425],\n",
            "        [19.6687],\n",
            "        [ 3.8300],\n",
            "        [78.1146],\n",
            "        [68.6786],\n",
            "        [59.4898],\n",
            "        [ 0.1367],\n",
            "        [64.4200],\n",
            "        [59.7059],\n",
            "        [38.0687],\n",
            "        [19.2034],\n",
            "        [38.8713],\n",
            "        [72.2136],\n",
            "        [65.4835],\n",
            "        [23.4569],\n",
            "        [63.4491],\n",
            "        [78.4021],\n",
            "        [69.9528],\n",
            "        [36.4261],\n",
            "        [46.9944],\n",
            "        [40.6657],\n",
            "        [80.8022],\n",
            "        [61.0714],\n",
            "        [38.3107],\n",
            "        [56.2221],\n",
            "        [59.7662],\n",
            "        [25.9014],\n",
            "        [22.2462],\n",
            "        [ 7.2476],\n",
            "        [42.3421],\n",
            "        [57.9215],\n",
            "        [54.2391],\n",
            "        [73.9594],\n",
            "        [11.4447]], device='cuda:0')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "NfDDU7VeRxTe",
        "colab_type": "code",
        "colab": {},
        "outputId": "944490a8-17f2-414a-a199-ba2d5a35d8a7"
      },
      "source": [
        "model = WellLogModel(in_dim,H,out_dim)\n",
        "to_device(model, device)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "WellLogModel(\n",
              "  (input_layer): Linear(in_features=13, out_features=18, bias=True)\n",
              "  (hidden_1): Linear(in_features=18, out_features=36, bias=True)\n",
              "  (hidden_2): Linear(in_features=36, out_features=18, bias=True)\n",
              "  (output_layer): Linear(in_features=18, out_features=1, bias=True)\n",
              ")"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 274
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "zNBiR6edRxTg",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def accuracy(outputs, labels):\n",
        "    _, preds = torch.max(outputs, dim=1)\n",
        "    return torch.tensor(torch.sum(preds == labels).item() / len(preds))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CKgqHwzORxTj",
        "colab_type": "text"
      },
      "source": [
        "Check loss for random weights"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "bllGutGrRxTj",
        "colab_type": "code",
        "colab": {},
        "outputId": "d86c905f-ff10-4467-a7eb-492480503674"
      },
      "source": [
        "history = [evaluate(model, val_loader)]\n",
        "history"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'val_loss': 47.53800582885742}]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 276
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bn9GXEnkRxTm",
        "colab_type": "text"
      },
      "source": [
        "* ## Train model on loop and epoches"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "H0i2vzdGRxTn",
        "colab_type": "code",
        "colab": {},
        "outputId": "24ebdfa7-3128-4d59-d0d1-61324b43e7e7"
      },
      "source": [
        "history += fit(300, 0.005, model, train_loader, val_loader)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Exception in thread Thread-3999:\n",
            "Traceback (most recent call last):\n",
            "  File \"/opt/conda/lib/python3.7/threading.py\", line 926, in _bootstrap_inner\n",
            "    self.run()\n",
            "  File \"/opt/conda/lib/python3.7/threading.py\", line 870, in run\n",
            "    self._target(*self._args, **self._kwargs)\n",
            "  File \"/opt/conda/lib/python3.7/site-packages/torch/utils/data/_utils/pin_memory.py\", line 25, in _pin_memory_loop\n",
            "    r = in_queue.get(timeout=MP_STATUS_CHECK_INTERVAL)\n",
            "  File \"/opt/conda/lib/python3.7/multiprocessing/queues.py\", line 113, in get\n",
            "    return _ForkingPickler.loads(res)\n",
            "  File \"/opt/conda/lib/python3.7/site-packages/torch/multiprocessing/reductions.py\", line 294, in rebuild_storage_fd\n",
            "    fd = df.detach()\n",
            "  File \"/opt/conda/lib/python3.7/multiprocessing/resource_sharer.py\", line 57, in detach\n",
            "    with _resource_sharer.get_connection(self._id) as conn:\n",
            "  File \"/opt/conda/lib/python3.7/multiprocessing/resource_sharer.py\", line 87, in get_connection\n",
            "    c = Client(address, authkey=process.current_process().authkey)\n",
            "  File \"/opt/conda/lib/python3.7/multiprocessing/connection.py\", line 498, in Client\n",
            "    answer_challenge(c, authkey)\n",
            "  File \"/opt/conda/lib/python3.7/multiprocessing/connection.py\", line 746, in answer_challenge\n",
            "    response = connection.recv_bytes(256)        # reject large message\n",
            "  File \"/opt/conda/lib/python3.7/multiprocessing/connection.py\", line 216, in recv_bytes\n",
            "    buf = self._recv_bytes(maxlength)\n",
            "  File \"/opt/conda/lib/python3.7/multiprocessing/connection.py\", line 407, in _recv_bytes\n",
            "    buf = self._recv(4)\n",
            "  File \"/opt/conda/lib/python3.7/multiprocessing/connection.py\", line 379, in _recv\n",
            "    chunk = read(handle, remaining)\n",
            "ConnectionResetError: [Errno 104] Connection reset by peer\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-277-71ede6708f03>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhistory\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m300\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.005\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrain_loader\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mval_loader\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m<ipython-input-251-c52e66813219>\u001b[0m in \u001b[0;36mfit\u001b[0;34m(epochs, lr, model, train_loader, val_loader, opt_func)\u001b[0m\n\u001b[1;32m     12\u001b[0m         \u001b[0;31m# Training Phase\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mbatch\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtrain_loader\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m             \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtraining_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m             \u001b[0mloss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m             \u001b[0moptimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-250-0560b71b2d18>\u001b[0m in \u001b[0;36mtraining_step\u001b[0;34m(self, batch)\u001b[0m\n\u001b[1;32m     19\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mtraining_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m         \u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtargets\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbatch\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 21\u001b[0;31m         \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m                  \u001b[0;31m# Generate predictions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     22\u001b[0m         \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mF\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0ml1_loss\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtargets\u001b[0m\u001b[0;34m)\u001b[0m        \u001b[0;31m# Calculate loss\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     23\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mloss\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m    548\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_slow_forward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    549\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 550\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mforward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    551\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mhook\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_forward_hooks\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    552\u001b[0m             \u001b[0mhook_result\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhook\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-250-0560b71b2d18>\u001b[0m in \u001b[0;36mforward\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m     10\u001b[0m         \u001b[0mh_relu\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minput_layer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m         \u001b[0mh_relu\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mF\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrelu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mh_relu\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# First activation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m         \u001b[0mh_relu\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhidden_1\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mh_relu\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     13\u001b[0m         \u001b[0mh_relu\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mF\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrelu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mh_relu\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Second activation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m         \u001b[0mh_relu\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhidden_2\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mh_relu\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m    548\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_slow_forward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    549\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 550\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mforward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    551\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mhook\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_forward_hooks\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    552\u001b[0m             \u001b[0mhook_result\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhook\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/torch/nn/modules/linear.py\u001b[0m in \u001b[0;36mforward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m     85\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     86\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mforward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 87\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mF\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlinear\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mweight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbias\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     88\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     89\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mextra_repr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/torch/nn/functional.py\u001b[0m in \u001b[0;36mlinear\u001b[0;34m(input, weight, bias)\u001b[0m\n\u001b[1;32m   1608\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mbias\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1609\u001b[0m         \u001b[0;31m# fused op is marginally faster\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1610\u001b[0;31m         \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maddmm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbias\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1611\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1612\u001b[0m         \u001b[0moutput\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatmul\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mweight\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e1ANVIoyRxTq",
        "colab_type": "text"
      },
      "source": [
        "## Visualize the loss."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "DNfCEeAMRxTr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "hist = []\n",
        "for i in history:\n",
        "    hist.append(i['val_loss'])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "H7ezhvs3RxTv",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "hist = np.array(hist)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "jOAxhZo6RxTx",
        "colab_type": "code",
        "colab": {},
        "outputId": "c2dc6543-8966-4d27-d1f2-c59eea66683f"
      },
      "source": [
        "plt.figure(\"Validation Loss History\")\n",
        "plt.xlabel(\"Epoches\")\n",
        "plt.ylabel(\"Cost Function or Loss\")\n",
        "plt.plot(hist)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f2d4c54d2d0>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 193
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wch6ZWSXRxTz",
        "colab_type": "text"
      },
      "source": [
        "## Visualize our predicted values and original values"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "yCl9IHsQRxTz",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "for xb,yb in val_loader:\n",
        "    X = xb\n",
        "    Y = yb\n",
        "    break"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "5vkYEN4ORxT0",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "pred_val = model(X)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "oxBezuimRxT2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "pred_val, orig_val = X_a.detach().cpu().numpy(),Y.detach().cpu().numpy()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "PGm5Z3NSRxT5",
        "colab_type": "code",
        "colab": {},
        "outputId": "c4dafb5b-e7ba-4a51-908b-ac4c75651451"
      },
      "source": [
        "plt.figure(\"Predicted Vs Original Values Plot\")\n",
        "plt.plot(pred_val[0:20], label='Predicted')\n",
        "plt.plot(orig_val[0:20], label='Original')\n",
        "plt.legend()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f2d4cab1410>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 200
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "TLG-TdKLRxT8",
        "colab_type": "code",
        "colab": {},
        "outputId": "47bf2286-0798-47d9-ed3f-39034ce1f69b"
      },
      "source": [
        "print(f'Predicted values are {pred_val[0:10]}\\n original Log Values are {orig_val[0:10]}')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Predicted values are [[ 2.65337  ]\n",
            " [30.27817  ]\n",
            " [ 2.5359268]\n",
            " [55.452778 ]\n",
            " [61.241554 ]\n",
            " [26.485723 ]\n",
            " [ 6.6008224]\n",
            " [66.39538  ]\n",
            " [31.494596 ]\n",
            " [53.68617  ]]\n",
            " original Log Values are [[ 2.8084]\n",
            " [30.4453]\n",
            " [ 4.8355]\n",
            " [60.2299]\n",
            " [63.5593]\n",
            " [26.8471]\n",
            " [11.0184]\n",
            " [64.2852]\n",
            " [38.1547]\n",
            " [51.1356]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mzkyueY4RxT-",
        "colab_type": "text"
      },
      "source": [
        "#### As we can see we have predicted the values of data as close as 2 units which is very good in terms of well log, because in well log we only want approximate values. +- of 2 unit is acceptable.\n",
        "\n",
        "#### but anybody can make it more accurate by adjusting the neural network parameters. Here the +- 2 unit of error can be due to very wide neural network. sometimes small neural network works well then more neurons.\n",
        "\n",
        "try to give the neural network to the lower in my case gives me low loss and high accuracy. You can chage the codes and try yourself."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "trusted": true,
        "id": "o3BIEHZzRxT-",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}