ischurov/pytorch-simple-function-example.ipynb

## pytorch-simple-function-example.ipynb
{
  "cells": [
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import torch\nimport torch.nn as nn\n\nn_hidden_1 = 30\nn_hidden_2 = 30\nmodel = nn.Sequential(nn.Linear(1, n_hidden_1), nn.ReLU(), \n#                      nn.Linear(n_hidden_1, n_hidden_2), nn.ReLU(), \n                      nn.Linear(n_hidden_2, 1))",
      "execution_count": 1,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import numpy as np\nimport matplotlib.pyplot as plt\n\n%matplotlib inline",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "plt.plot([1, 3, 4], [4, 3, 5])",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 3,
          "data": {
            "text/plain": "[<matplotlib.lines.Line2D at 0x12288d000>]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 432x288 with 1 Axes>",
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "x = np.linspace(-3, 3, 11)\nx",
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 20,
          "data": {
            "text/plain": "array([-3. , -2.4, -1.8, -1.2, -0.6,  0. ,  0.6,  1.2,  1.8,  2.4,  3. ])"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "np.sin(x)",
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 21,
          "data": {
            "text/plain": "array([-0.14112001, -0.67546318, -0.97384763, -0.93203909, -0.56464247,\n        0.        ,  0.56464247,  0.93203909,  0.97384763,  0.67546318,\n        0.14112001])"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "plt.plot(x, np.sin(x ** 2))",
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 22,
          "data": {
            "text/plain": "[<matplotlib.lines.Line2D at 0x122be8820>]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 432x288 with 1 Axes>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAD4CAYAAADvsV2wAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8/fFQqAAAACXBIWXMAAAsTAAALEwEAmpwYAAA3sElEQVR4nO3deXycZ3no/d812mUtY8myLY3kRfK+aElMIhdCkpKATRbbSeghbQ/0lBIozekCbRKWhpdAIUlbTj/vOVAI0FM4L4VDk3jJ4iQsWVsriRwt3h1bXqSRbMmSRpKtXXO/f8yMUGzJWmZ5nmfm+n4++qCZefw89xDp0jPXfd33JcYYlFJKxT+X1QNQSikVGxrwlVIqQWjAV0qpBKEBXymlEoQGfKWUShDJVg9gKgsWLDDLli2zehhKKeUo+/fvv2CMKZjsNdsG/GXLllFbW2v1MJRSylFE5MxUr2lKRymlEoQGfKWUShAa8JVSKkFowFdKqQQRkYAvIv8iIu0icnCK10VE/l8ROSEijSJyTSSuq5RSauYidYf/r8CWq7y+FVgZ/LoP+OcIXVcppdQMRSTgG2NeA7qucsg24CcmoAZwi0hhJK6tlFJqZmKVw/cAzRMetwSfew8RuU9EakWktqOjI0ZDU+GoPd1F3dluq4ehomxPQyvtvYNWD0OFyVaTtsaYJ4wxm4wxmwoKJl0opmzmgaca+fOf16F9FeLX0XO9/PnP6vjhG6esHooKU6wCvhcomfC4OPiccrCe/hGaOi7R3DXAO3qXH7d21bUCUN/ss3YgKmyxCvh7gE8Eq3WqgR5jTFuMrq2ipNHrG/8+FBRUfPH7DXvqA/dmB709jPn1k5yTRaos82fAPmC1iLSIyKdE5LMi8tngIc8DTcAJ4AfA5yJxXWWtxpYeAG5cVcCzja0Mj/otHpGKtLdOd9HaM8jNqwvoHx7jRPtFq4ekwhCRzdOMMfdO87oB/iwS11L2Ud/so7RgHp/YvJRP/biD1453cMu6RVYPS0XQrjovmalJfOHDq3n5WAcNzT5WL862elhqjmw1aaucwxhDfbOPymI3H1xVwPzMFHbW67RMPBkcGeO5A21sWb+YdYU55KQnU9/is3pYKgwa8NWcnOsdpKNviIoSNylJLu6oKOJXh8/TOzhi9dBUhLx8tJ2+wVG2V3lwuYSKEjcNOnHraBrw1ZyEfvErStwAbK/yMDTq54WD56wblIqonXVeCrLT+J2yfAAqit0cPdfH4MiYxSNTc6UBX81JfXMPKUnC2sJAPreqxM3S/Ex21WlaJx74+od5+Vg7d1YUkZwUCBMVJW7G/IZDrT0Wj07NlQZ8NScNzT7WFeaQlpwEgIiwvdLDvqZO2noGLB6dCtdzB9oYGTPsqPrtgviK4lwg8MdeOZMGfDVrY37DAW/PeDonZHuVB2NgT73W5DvdrjovKxZmsb4oZ/y5hTnpFOWmax7fwTTgq1lr6rjIxaFRKord73l++YJ5VJa42alpHUdr7urn7dPd7KjyICLvea2ixE2DVuo4lgZ8NWv14xO2uVe8tqPKw9FzfRxp643xqFSk7A6W195ZUXTFa+XFbs509tN9aTjWw1IRoAFfzVpDi4+stGRKF2Rd8drt5YUkuYRdWpPvSMYYdtZ5uW5ZHiV5mVe8Hvojr3f5zqQBX81aQ3MP5cW5uFxyxWv5WWncuKqA3XWt+HXfFcc56O3lZMcltlddsXs5ABs9uYgEfgaU82jAV7MyODLGkbbeKyZsJ9pe5eFc7yA1pzpjNzAVETvrvKQmubht4+T9ibLTU1hRkKV3+A6lAV/NyuG2Xkb95ooJ24luXbuIealJWpPvMKNjfvY0tHLzmgJyM1OmPC604lZ7IDiPBnw1K6GSvMqr3OFnpCaxZUMhew+c01WZDvIfJzu5cHHoPbX3k6kocdN5aZiWbl1v4TQa8NWsNLb0sCgnjcW56Vc9bkeVh76hUX59pD1GI1Ph2lXnJSc9mZtWL7zqcZXBT3eh7bGVc2jAV7PS0Oy7ajonZHNZPguz07Qm3yEuDY3ywsFz3FZeSHpK0lWPXb04m9Rkl+bxHUgDvpqxnv4Rmi5cuuqEbUiSS9hWWcQrx9q1ZtsBfnn4PAMjY2yvvHo6ByA12cX6ohxteehAGvDVjIVaGl4tfz/R9ioPo37Dcwe0m6Xd7ar34nFn8L5leTM6vqLYzYGWHkbHtMuZk0SqxeEWETkmIidE5KFJXl8iIi+LSJ2INIrIRyNxXRVboQnbjcVXrrCdzLrCHFYtytJqHZvr6Bvi9XcvsK2yaNK1FZOpLHEzMDLGiQ5teegkYQd8EUkCvgNsBdYB94rIussO+wrwC2NMFfBx4LvhXlfFXn1zD2UF88hJn7pkbyIRYXuVh9oz3Zzt7I/y6NRcPdvYypjfTFudM1EoracbqTlLJO7wrwNOGGOajDHDwM+BbZcdY4DQtnu5gG6n6DChloYzyd9PtC2YE96tWy3Y1q46L+uLcli5aOa9apflZwZaHuqKW0eJRMD3AM0THrcEn5vo/wH+UERagOeB/x6B66oYausZ5MLFoRnn70M87gyuX57HznqvLtSxoZMdF2lo6ZnV3T0EPr1py0PnidWk7b3AvxpjioGPAv9HRK64tojcJyK1IlLb0dERo6GpmRhvaTiDkszL7ajy0NRxiQNevRu0m911XlwCd0yyM+Z0KkvcHDvfx8CwLq5zikgEfC9QMuFxcfC5iT4F/ALAGLMPSAcWXH4iY8wTxphNxphNBQUFERiaipT6Fh+pSS7WFM78Y3/I1o2FpCa5tCbfZowx7Kz38jtlC1iUc/WFdJOpKNaWh04TiYD/NrBSRJaLSCqBSdk9lx1zFvgQgIisJRDw9RbeQRqafawtzB5vaTgbuRkp/O6ahTzT0KplfDbyztlumrsGptwZczrlJaGWh74IjkpFU9gB3xgzCtwPvAgcIVCNc0hEHhGRO4OHfQH4tIg0AD8D/shoQtcxxvyGAy1XtjScje1VHi5cHOaNExciNzAVlp11XtJTXHxk/aI5/fuF2cGWh7rFgmMkR+IkxpjnCUzGTnzu4QnfHwbeH4lrqdg72XGRS8Njc8rfh9y8poCc9GR21Xmn3atFRd/wqJ9nG9u4dd1ismdYZjsZnbh1Fl1pq6b125aG7jmfIy05idvKi3jx0HkuDY1GZmBqzl493oGvf4QdVbOfrJ2oosTN2a5+unT7DEfQgK+m1dDsIzstmdIF88I6z44qDwMjY7x0+FyERqbmaledl7x5qdywMrziiNCnPt1IzRk04KtpNbb0UF4yeUvD2di0dD4edwY763TdnZV6B0f45ZHz3FFeSEpSeCFgY3Gg5WGjLsByBA346qrGWxqGkb8PcbmE7VVFvPFuB+19g+EPTs3JCwfOMTzqn3N1zkRZacmsXKgtD51CA766qvGWhmHk7yfaXunBb+CZBt1B0yo767wsy8+c9arpqVQUa8tDp9CAr65qJi0NZ2Plomw2eHJ0B02LtPoGqDnVyfYqDyLhpehCtOWhc2jAV1fV0OxjcU76nFZiTmV7pYcD3h5OtPdF7JxqZvY0tGIMM2p0MlOhmwFN69ifBnx1VQ0tPVSUzGz/+5m6s6IIl8AunbyNuV11XqqWuFkWZsXVROMtD7Ue3/Y04Ksp+fqHOTXDloazsTAnnfevWMCuei9+v+Z9Y+VIWy9Hz/XNemfM6aQkudhQlEODVurYngZ8NaXG4JL5yghU6FxuR5WHlu4B9p/tjvi51eR21XlJdgm3bSyM+LkrStwc8GrLQ7vTgK+m1NDsQwQ2zLCl4Wx8ZP1iMlKSdPI2Rvx+w+76Vm5cVUB+VlrEzx9qefhuu7Y8tDMN+GpKDS0+ygqyZtzScDbmpSXz4fWLeLaxjeFRvSuMtppTnZzrHYxI7f1kxlfcah7f1jTgq0kFWhr2RGTB1VS2V3noGRjhlWPtUbuGCthV5yUrLZlb1s5tZ8zpLM3PJDcjRSt1bE4DvppUa7ClYaQrdCa6YcUC8uelskv73UbV4MgYew+cY8uGxWSkzr6fwUyICOXFudrj1uY04KtJhdPScKaSk1zcUVHEr4600zMwErXrJLpfH2mnb2g04tU5l6sscXP8fB/9w7obql1pwFeTamiee0vD2dhR5WF41M8LB3WrhWjZWedlUU4a1aX5Ub3Ob1se9kb1OmruNOCrSdU3+1hblDOnloazUV6cS+mCedrvNkq6Lg3zyrF2tlV6SApzt9PphFoe6sStfWnAV1cY8xsOenuojEI55uVEhO1VHmqauvD6dC+WSHvuQBujfhPRrRSmsjA7HY87Q1se2lhEAr6IbBGRYyJyQkQemuKY3xORwyJySET+LRLXVdEx3tIwwitsp7KtMtB1aU+9brUQabvqvKxalMXaKKfmQipKcvUO38bCDvgikgR8B9gKrAPuFZF1lx2zEvgi8H5jzHrgL8O9roqeSLQ0nI2l+fO4ZombnXUtusVuBJ3t7Gf/me6I7ow5nYpibXloZ5G4w78OOGGMaTLGDAM/B7Zddsynge8YY7oBjDFaeG1jDc0+stOTWZ4fuQ22prOjysPx8xc50qY7aEZKqNx1WwzSOSEVunOmrUUi4HuA5gmPW4LPTbQKWCUi/yEiNSKyZbITich9IlIrIrUdHR0RGJqai4YWHxXF7rBbGs7GbeVFJLtEa/IjxBjDrjov1y/Pw+POiNl1N3pycYlO3NpVrCZtk4GVwE3AvcAPRMR9+UHGmCeMMZuMMZsKCsJrrqzmZnBkjKNtfVFdcDWZvHmp3LS6gN31XsZ0B82wNbb00HThUtRr7y83Ly2ZlQuzNeDbVCQCvhcomfC4OPjcRC3AHmPMiDHmFHCcwB8AZTOHWoMtDaO44Goq26s8nO8doqapM+bXjjc767ykJrnYGoWdMadTUZJLQ0uPzsfYUCQC/tvAShFZLiKpwMeBPZcds4vA3T0isoBAiqcpAtdWERbploazccvaRWSlJWtNfphGxvw809DKh9YuJDcj8hvfTaeixE2Xtjy0pbADvjFmFLgfeBE4AvzCGHNIRB4RkTuDh70IdIrIYeBl4G+MMXobZ0MNLT4Kc9NZGMGWhjOVnpLE1g2LeeHgOQaGx2J+/XjxxokLdF4ajtrOmNMJfTqs17SO7UQkh2+Med4Ys8oYU2aM+bvgcw8bY/YEvzfGmM8bY9YZYzYaY34eieuqyGto9lmSzgnZUeXh4tAovzpy3rIxON2uOi+5GSnctNqaebDVi7NJ05aHtqQrbdU4X/8wpzv7Y1Z/P5nrS/NZnJOujVHm6OLQKC8eOsdt5YVR3xZjKilJLjZ4crU004Y04KtxoSXxsa7QmSjJJWyrLOLV4x26eGcOXjp0jsERf8yrcy5XUawtD+1IA74aF2ppuNFjXcCHQLXOqN/wXKNutTBbu+pbKZ6fwbVL5ls6joqSXAZH/Bw/ry0P7UQDvhrX0BxoaZgdhZaGs7G2MIc1i7O1WmeW2vsGeePdDrZXemK6aG4y4y0PNa1jKxrwFRBYmRlaYWsH26s8vHPWx5nOS1YPxTGeaWjDb2B7VZHVQ/lty0OduLUVDfgKCLU0HKbSwvz9RHdWFCECu+o0rTNTu+q8bPTksmJhbHbGvBoRoaLErVsl24wGfAVMaGloYYXOREXuDKqX57Or3qsrNmfgRHsfB7w9ltXeT6ayOFdbHtqMBnwFTGhpuDjH6qGM21Hl4dSFS3qXOAO76lpxCdxREfutFKZSUaItD+1GA74CAqsi1xXlkJpsnx+JLRsXk5rs0pr8afj9hl31Xj6wsoCF2bFfIT2V8tDErebxbcM+v93KMmN+wwFvjyX751xNTnoKt65dxDMNrYxoPfeU9p/tpqV7gB02mKydqCA7DY87Q7dYsBEN+IoT7RfpHx6zdMHVVLZXeei8NMwb716weii2tbPOS0ZKEh9et9jqoVyhssStpZk2ogFf/XbC1iYlmRPduKoAd2aK1uRPYWh0jOca2/jI+kXMS0u2ejhXqCjJpblrgM6LQ1YPRaEBXwH1LT5y0pNZFsOWhjOVmuzi9vJCXjp8jotDWu1xuVeOddAzMGKr6pyJQjcRjTrxbgsa8FVgh8yS2LY0nI0dVR4GR/y8ePCc1UOxnV11XhZkpfKBFQusHsqkNgRbHmoe3x404Ce4wZExjp7rs2U6J+SaJfMpycvQfreX6RkY4ddH2rm9vIjkJHv+Ks9LS2bVomzN49uEPX9KVMwcau1hzG9ss+BqMiLC9koP/3HiAud7B60ejm3sPdDG8Jj1O2NOp6LYTUOzTxfQ2YAG/ARX3xzcErnYfhU6E22r9OA38EyDbrUQsrPOS+mCeZTb/L9dRYmb7v4Rmru05aHVIhLwRWSLiBwTkRMi8tBVjrtbRIyIbIrEdVX4Gpqta2k4GysWZlFenKvVOkFe3wBvnupie5UHEXvOvYSE/iDVa1rHcmEHfBFJAr4DbAXWAfeKyLpJjssG/gJ4M9xrXk177yCf/kktr7/bEc3LxA077ZA5ne2VHg619nL8fJ/VQ7Hc7uB8xvZKe6dzQFsezta3XzrGN549HJVzR+IO/zrghDGmyRgzDPwc2DbJcV8HHgOimoTNyUjhteMdvHJMA/50ui8Nc8biloazcUdFEUkuSfitFowx7HzHy7VL57MkP9Pq4UxrvOWhBvwZ2d3Qypmu/qicOxIB3wM0T3jcEnxunIhcA5QYY56LwPWuKj0liWuWzKemqTPal3K8Rq/1LQ1noyA7jQ+sWMDu+lb8/sSdADzc1su77RdtW3s/mYpiNwdbteXhdFp9A5zp7Ke6ND8q54/6pK2IuIBvA1+YwbH3iUitiNR2dMz9Dn1zWT6H23rx9WtP1KuxS0vD2dhR5cHrG6D2TLfVQ7HM7vpWkl3C7RvtszPmdLTl4cyEblQ32zjge4GSCY+Lg8+FZAMbgFdE5DRQDeyZbOLWGPOEMWaTMWZTQUHBnAdUXZqPMfDWqa45nyMRNDT7WGGDloaz8eH1i8hMTUrYydsxv2F3vZebVi9k/rxUq4czY6GN+bQe/+pqmjpxZ6awZnF0mthEIuC/DawUkeUikgp8HNgTetEY02OMWWCMWWaMWQbUAHcaY2ojcO1JVZTkkp7iYp+mdaY03tLQIfn7kMzUZD6yfjHPNbYyNDpm9XBirqapk/O9Q7avvb/ckrxM3Jna8nA6NU1dXL88L2qr3sMO+MaYUeB+4EXgCPALY8whEXlERO4M9/xzkZacxLVL51PTpHf4U/H6BrhwcdhxAR8CO2j2Do7y8tHEm5jfWeclOy2ZD61daPVQZkVEqCh26xYLV+H1DXC2K3r5e4hQDt8Y87wxZpUxpswY83fB5x42xuyZ5Nibonl3H7K5NJ+j5zSPP5WG4IKrSoeUZE70/rJ8FmSlJVy1zsDwGC8cPMfWjYtJT0myejizVlHi1paHV1FzMpCRsH3At6NQHl/v8ifX0OIjNdnF6ijlCqMpOcnFnRVF/OZoOxcSaNvdFw61cXFo1FHVORNVluTiN3DQqy0PJ7OvqZP5mSmsXhS938m4DfjlxW4yUpK0PHMK9c0+1tuspeFs/P71SzAYHnkmOgtU7KZnYIRH9x5lzeJsrl8evTvAaNKWh1dX09TJ9cvzo7prrTN/22cgNdnFpmVajz+Z0TE/B1p6HLPCdjIrFmbxZzevYE9DK786fN7q4UTdo3uP0NE3xGN3l5Nk022sp7MgK43i+Rm6xcIkmrv6aekeYHNZdP+Yx23Ah0Ba5+i5ProuaR5/ohMdFxkYGbNdD9vZ+txNK1izOJsv7zpA7+CI1cOJmv88cYGfvdXMp28odeQk+0QVJW69w59E6MY0mvl7SICAD/Cm3uW/x3hLQ4cHj9RkF4/dXU5H3xDfev6I1cOJiv7hUR58upHlC+bxV7eusno4YassdtPSPZBQcy8zsa+pk7x5qaxalBXV68R1wC8vziUzVfP4l6tv7gm2NLT/PizTqShx8+kbSvnZW83854n4a3T+Dy8ep7lrgEfv2ujIypzLhW4yGjWtM84Yw5tNXVSX5kV959O4DvgpSS42LcvTBViXCbU0tPu2ujP1V7euYll+Jg8+3RhXJX/7z3Tzv//zFP+1einXR/mjfqxs8OQEWx5qj9uQ5q4BvL6BqG2nMFFcB3yA6tI8jp+/qB8hgwaGxzh23t4tDWcrPSWJx+4up7lrgH948bjVw4mIodExHnyqkcKcdB7Ystrq4URMZmqw5aHm8cfFKn8PCRDwN4/n8bUeH5zR0nAuri/N5w+rl/C///MU++NgY7X/+esTnGi/yDfv2uiovY5moqLYTUOLtjwM2dfUyYKsVFYsjG7+HhIg4G/w5DJP8/jjGlqc0dJwLh7csobCnHQefKrR0fvsHGrt4XuvnuSuazzctNpZWyjMREWJG5+2PAQC+fuapk6uL82PSYo17gN+SpKL9y3XPH5IQ7OPIge0NJyL7PQUvnnXRk60X+R//eaE1cOZk9ExPw8+1Yg7M5WHb7+icVxcCPVf0Hp8ONvVT1vPYEzy95AAAR8CubET7Rfp6NM8vhN3yJyNm1Yv5K5rPPzzKyc53Oq8JfxPvN7EQW8vX9+2Hnemc7Y/no1Vi7JJT9GWhwD7YrB/zkQJEfBDfz0TPa3jtJaGc/Xw7etwZ6bywFMNjuqwdLLjIv/0q3fZumExWx3U3GS2UpJcbCjSlocQiEkF2WmUFcyLyfUSIuCvL8ohKy054QN+qPlEPFXoTMadmcrXt63noLeXJ15vsno4M+L3Gx58spGMlCS+tm291cOJuoqSQMvDEQf9QY40Ywz7mjqpjlH+HhIk4CcnubhueZ4G/OaeQEvDOJywvdzWjYVsWb+Yf/rVu5zssH9bvZ/sO03tmW7+9vZ1LMyOv/mVy1WUuIMtD/usHoplTnf2c753iOrSvJhdMyECPgTq8U92XKK9d9DqoVimocXHyoVZZKUlWz2UmHhk+3oyUpJ48MlGWzc9b+7q5/EXj3HjqgLuvsaZWx/PVuX4zpmJuwArlL+P1YQtJFTAD+bxE7TPrTEmsMI2ztM5Ey3MTudvb19H7ZlufrLvtNXDmZQxhi/tPIAA37xrY9ysfp5OSV4G8xO85WFNUycLs9NYviA2+XtIoIC/viiX7LTk8b+qiaale4DOS85saRiOu6/xcOOqAh5/8RjNXf1WD+cK/76/hdffvcBDW9fgcWdYPZyYEZHAzpkJWpoZyt9vLotd/h4iFPBFZIuIHBOREyLy0CSvf15EDotIo4j8WkSWRuK6s5HkEq5bnpewO2eGfrGcviXybIlI4M4Z+NLOA7Za3dneO8g3nj3Mdcvz+IPrY/4rYbmK4kDLw0tD8bP/0Uw1XbhER99QzMoxQ8IO+CKSBHwH2AqsA+4VkctXjNQBm4wx5cCTwOPhXncuNpfl03ThEucTMI/f0Ozclobh8rgzeGjrGl5/9wL/vr/F6uEAgTu8r+w6yNCon8fuLo9qlyO7qixxB1seJl4e34r8PUTmDv864IQxpskYMwz8HNg28QBjzMvGmNDn6RqgOALXnbXqBK7Hb2juYUNRDilJCZPFe48/uH4p1y3L4xvPHrbFxP1zB9p46fB5Pn/rqpjmcO2kPFgtlohpnZqmThbnpLM0xluUR+K33wM0T3jcEnxuKp8C9k72gojcJyK1IlLb0dERgaG919rCHHLSEy+PPzrm54C3J+Hy9xO5XMKjd29kaNTPV3YdtDS1031pmK/uPsRGTy6f+sByy8ZhtfysNEryMhKuUiewf05XzPP3EONJWxH5Q2AT8PeTvW6MecIYs8kYs6mgoCDi1w/k8fMT7g7/3fb4aGkYrtKCLP7q1lW8dPg8zx1os2wcjzx7mJ6BER6/p5zkBP3EFVJR7KY+wSp1TnYEtmuPZf19SCR+2rxAyYTHxcHn3kNEbgG+DNxpjLFsU5vNZfmc7uynrSdxduoLlb6VJ1BJ5lT+5APL2ejJ5au7D1nS6/jlo+3srPPyuZtXsLYwJ+bXt5uKYjdeX2K1PNwX3Ko91hO2EJmA/zawUkSWi0gq8HFgz8QDRKQK+D6BYN8egWvOWeivaiLd5Te0xE9Lw3AlJ7l4/J5yegZGeOSZQzG9dt/gCF/aeYBVi7K4/+YVMb22XSViy8Oak50U5aazJC/2v49hB3xjzChwP/AicAT4hTHmkIg8IiJ3Bg/7eyAL+HcRqReRPVOcLurWLs4hNyMlofL48dbSMFxrC3P43M0r2FXfym+Ono/Zdb+19yjnewd5/J4KUpMTO5UTkmgtD0P738dy/5yJIrLG3hjzPPD8Zc89POH7WyJxnUhwuYTrl+dRkyAdsEItDT+3tszqodjK/Tev4IWDbXx550Fe+qu8qHeV2neyk3978yyfvmF5ws+lTJRoLQ/fbb9I56Vhqsus6VGckLcZm8vyOdvVj9cX/3n88ZaGmr9/j9RkF4/fU8H53kG+tfdoVK81MDzGQ083sjQ/k8/fGj/9aSOlsiRxWh6GUsmxrr8PSciAP16PnwBpnVAFRHlJ/O+QOVuVJW7++P3L+bc3z0Y1xfftXx7jTGc/j95VTkZqUtSu41Shlodnbbj1RaTtO9mJx51BiQX5e0jQgL96UTbzM1MSou1hQ0sPHndGQmy5Oxdf+PBqluZn8tDTjQwMR74Pbn2zjx+9cYrfv34Jmy36GG93oU+f8V6e6fcb3jzVZUl1TkhCBvxAHj8x6vEDE7Z6dz+VjNQkHr2rnDOd/fzjS8cieu6h0TEeeLKBRTnpfHHrmoieO56sWpQVbHkY3xO3x9v76Lo0bOkf/oQM+BAoz2zpHrDlDoqR0nVpmLNd/Zq/n8bmsnx+//ol/Mt/nKLubHfEzvudl09y/PxFvrljY9QnhZ0sOcnFRk9u3G+xUDPevzb2C65CEjbgby5bAMR3Pf54S0OtCpnWF7euYVFOOg882cjQaPipnSNtvXz35RPsqPJw85qFERhhfKsodnPQG98tD/c1dVKSl0HxfOvWwyRswF+5MIu8ealxXZ7Z0OzDJbDRoymd6WSnp/DNHRt5t/0i33n5ZFjnGh3z88CTjbgzU3j49ss3jlWTqShxMzTq59i5+Gx5OJ6/X27tPE7CBnyXS6guDfS5jddysIZmHysXZjMvQVoahuvmNQvZUeXhuy+f4Ehb75zP86M3TnHA28PX7tzA/HmpERxh/AqtTYjXtM7Rc334+kcsn7hP2IAPgfJMr2+Alu74q8c3xtDQ0qMTtrP0t7evIzcjhQeebGR0DumFpo6LfPuXx/nwukV8dOPiKIwwPhXPzyBvXmrcLsAKpY6vt7BCBxI84IcWP8TjNgst3QN0JWBLw3DlzUvla9vWc8Dbww/fODWrf+v3Gx566gBpyS6+sX2DbmUxCyJCRXFu3Fbq1DR1siQv0/I2lgkd8FcszGJBVmpcTtyGapq1Qmf2bttYyIfXLeJ//PI4TR0XZ/zvfvrmGd463cVXbl/Hwhxd9zBbFSVujrf3cTHOWh6G8vdWra6dKKEDvohwfWk+++Iwj9/Q7CMtQVsahktE+Mb2DaQlu3jwqUb8/ul/Nlq6+3l071FuWLmAj11rSUM3x6sodmPisOXhkXO99AyMUF1mXTlmSEIHfAjk8dt6BuNuWXdDi4/1CdzSMFwLc9L5yu3rePt0Nz9988xVjzXG8KWdBzHAN3ds1FTOHI23PIyzPP6+8fp7vcO3XDzm8UfH/Bz09mr+Pkwfu7aYG1Yu4NG9R2npnvqG4Ol3vLx2vIMHt6yxbI+UeBBqedjYEl93+DVNXSzLz6Qw19r8PWjAp6xgHgXZaXGVx9eWhpEhInxzx0YMBO7gJ0n7tfcN8sizh9m0dD7/tXpp7AcZZ+Kt5eGY3/DmqU7LyzFDEj7giwjVcZbHb9AJ24gpycvkgY+s5rXjHTz1zhWdO/nq7kMMjIzx2D3luFyayglXZUmg5WFHX3y0PDzS1kvf4Kgt0jmgAR8I7G1xvneI053xkcdvaPGRm5HCUm1pGBGf2LyMTUvn8/VnD9PeNzj+/N4Dbew9eI6/vGUlZQVZFo4wfsRby0M75e9BAz4Qf3n8+uYebWkYQS6X8Ng95QyMjPHwrkAfXF//MH+7+xAbPDncd0OpxSOMH+uLckhySdxM3NY0dVK6YB6LbFKmG5GALyJbROSYiJwQkYcmeT1NRP5v8PU3RWRZJK4bKcsXzGNhnOTx+4dHOX6+j8piXWEbSWUFWfzlLSt54dA5nj/QxiPPHsbXP8zjd1eQrJVQERNqeVgfBxO3o2N+3jrVZVk7w8mE/ZMqIknAd4CtwDrgXhG5fMeoTwHdxpgVwP8AHgv3upEUT3n8Q629gZaGOmEbcffdUMoGTw4PPNnI0+94+dObylhXlGP1sOJOZUkuDc3Ob3l4uK2XviH75O8hMnf41wEnjDFNxphh4OfAtsuO2Qb8OPj9k8CHxGb5hs1l+XT0DdF04ZLVQwlL6KNwuU7YRlxykovH765gcGSMlQuzuP93V1g9pLhUUeymZ2CEMw6fUxvP3y+3fsFVSCQCvgdonvC4JfjcpMcYY0aBHuCKP3sicp+I1IpIbUdHRwSGNnPjfW4dntapb/bhcWdQkJ1m9VDi0rqiHP7vZ6r5yaeuIy1Z+9NGQ0Wc7JxZ09RJWcE8W22zYavkozHmCWPMJmPMpoKCgphee1l+Jotz0h0/cdvQ4tP6+yi7dmmeLRbRxKuVC7PISElydD3+6Jift0932yqdA5EJ+F6gZMLj4uBzkx4jIslALmCryBrI4+dR09Tl2Nxh58UhmrsGdEtk5WjjLQ8dHPAPtvZycWjUNguuQiIR8N8GVorIchFJBT4O7LnsmD3AJ4Pf3wP8xtgwqm4uy+fCxSFOzmKHRDsJLUnXBVfK6SpKcjnY2uvYlofj+99b3OHqcmEH/GBO/n7gReAI8AtjzCEReURE7gwe9iMgX0ROAJ8HrijdtIPQx699Dm17WB9sabhBWxoqh6socTPs4JaH+052snJhlu3m0iLS+84Y8zzw/GXPPTzh+0HgY5G4VjQtycukKDedmpOdjtwXpaHFx6pF2tJQOV/oU2p9s89xNzAjY35qT3dx1zX22ybbVpO2VgvV4zuxz60xhoZm3/gWs0o5mZNbHh7w9nBpeMx2+XvQgH+F6rJ8Oi8N8267s/L4Ld0DdPeP6IIrFRdCLQ+duFXyb/P39qm/D9GAf5nNDq3H15aGKt44teXhvpOdrF6UTX6WvfL3oAH/CiXBRsNOq8fXloYq3lSUOK/lYSB/3011qf3u7kED/qSqS/N581TXjHqZ2kVDS2ByS1saqngR+rTqpDx+Y4uPgRF75u9BA/6kNpfl03VpmOPtzigJGx3zc8Dbo+kcFVfy5qWyJC/TUVss1ARLuq+zWf19iAb8SYQmW2ocktbZf6abwRG/rrBVcaeixM1bp7oYHBmzeigzsu9kJ2sWZ5M3L9XqoUxKA/4kSvIyKZ6fwT4HTNwaY3j0haMUZKfxobWLrB6OUhF173UlXLg4zI/eOGX1UKY1POqn9kyX7fbPmUgD/hQ2OySPv6ehlbqzPv7mI6vJ0gVXKs78TtkCPrxuEd95+QTtvYPT/wMLNbb4GBzxa8B3ourSfHz9Ixw7b988fv/wKI/uPcoGTw732HBVn1KR8OXb1jIy5ufxF49ZPZSr2neyExFsW6EDGvCnFGpLZufyzCdea6KtZ5CHb1+Py2WrfjJKRczS/Hn88fuX8+T+Fg7YeCFWzalO1izOwZ1pz/w9aMCfksedwZK8TNsuwGr1DfC9V09yW3kh19lwRZ9SkXT/765gQVYqX3vmkC23PRkaHaP2dPf4wk270oB/FXbO4z/+wlH8Bh7assbqoSgVddnpKXzhw6upPdPNcwfarB7OFRqaexga9ds6nQMa8K+quiyPnoERjpzrtXoo7/HO2W521bdy3w2llORlWj0cpWLi9zaVsLYwh289f9R2ZZqh/L3d9r+/nAb8qxjfH99GeXy/3/DIM4dZmJ3Gn95UZvVwlIqZJJfw8O3r8PoG+OHrTVYP5z1qmjpZV5hDbmaK1UO5Kg34V1GYm8Gy/Mzx1XN2sKehlfpmHw9sWaP73quEs7ksny3rF/PdV05y3iZlmoMjY+w/a//8PWjAn9bmsnzePNXJmA3y+KEyzI2eXO6q8lg9HKUs8cWPrmF0zPD4C/Yo06xv9jE8au/6+5CwAr6I5InIL0Xk3eD/zp/kmEoR2Scih0SkUUT+SzjXjLXq0nz6Bkc50mZ9Hv/7rzZxrneQh+9Yp2WYKmEtzZ/Hf/vAMp56p4VGG+yzs+9kJy6B9zmgWi7cO/yHgF8bY1YCv2byXrX9wCeMMeuBLcA/iYg7zOvGjF3y+K2+Ab7/2kluLy/kfcvs/4OlVDTdf3OgTPORZw5bXqZZ09TJ+qJccjPsnb+H8AP+NuDHwe9/DGy//ABjzHFjzLvB71uBdqAgzOvGzKKcdEoXzLO8Hv+xF45iDDy0VcswlcpOT+Gvg2WazzZaV6Y5ODJG3Vmf7csxQ8IN+IuMMaH/t88BV929S0SuA1KBk1O8fp+I1IpIbUdHR5hDi5zqsnzeOtXF6JjfkuvvP9PN7vpW7vtgKcXztQxTKYCPbSphXWEOj+61rkzznbPdDI/5bbv//eWmDfgi8isROTjJ17aJx5nA56opP1uJSCHwf4D/ZoyZNHIaY54wxmwyxmwqKLDPh4Dq0nz6hkY5bEEe3+83PPJsoAzzszdqGaZSIUku4eE7AmWaP3jNmjLNmqYuXAKbHJJmnbauzxhzy1Svich5ESk0xrQFA3r7FMflAM8BXzbG1Mx5tBapDk7G7DvZSXmMm4zsbvDS0OzjHz9WoWWYSl2mujSfrRsCZZq/974SFuWkx/T6NSc72ejJJSfd/vl7CD+lswf4ZPD7TwK7Lz9ARFKBncBPjDFPhnk9SyzMSaesIPZ5/P7hUR7be4zy4lx2aBmmUpP64ta1jPkNj71wNKbXHRgeo77Z54hyzJBwA/6jwK0i8i5wS/AxIrJJRH4YPOb3gA8CfyQi9cGvyjCvG3PVpfm8fbo7pnn874XKMG/XMkylprIkP5M//sBynn7HG9P+t6H8fbVD8vcQZsA3xnQaYz5kjFlpjLnFGNMVfL7WGPMnwe//P2NMijGmcsJXfQTGHlOby/K5ODTKwdbY5PG9vgG+/+pJ7qgockx+UCmr/NnNZSzISuORZ2NXplnT1EmSSxxVJq0rbWcotClSrNI6j+0NfDzVMkylppednsLffGQV+89080yMyjT3BfP3Tuo0pwF/hgqy01i5MCsmC7D2n+liT0Mrn/lgKR53RtSvp1Q8uOfaEtYX5fDo80cYGI5umWb/8CgNLc7K34MG/FmpLs2n9nQXI1HM44d2w1yUk8ZntAxTqRkL7abZ2jPID6K8m+b+M92MjBnH1N+HaMCfhc1l+VwaHuOAN3pt1nbVe2lo6eFB3Q1TqVm7vjSfj25czD+/cpJzPdHbTTOUv9+09Irtw2xNA/4sXB+sx49WHr9/eJTHXjhKRYmb7ZVahqnUXHxx61rGjOHxKJZpBtbk5DrupkwD/izkZ6WxelF21PL433vlJOd7h7QMU6kwlORl8icfWM7TdV7qo1CmeWlolMaWHkfsf385DfizVF2aR+3p7ojn8b2+Ab7/WhN3VhRxrcM+JiplN5+7eUWgTDMKTc9rz3Qz6jeOm7AFDfiztrksn4GRsYjvw/3o3qOIwINahqlU2LLSknngI6t556yPPQ2tET13TVMnyS5h0zLn3ZhpwJ+l68br8SPX9nD/mS6eaWjlvg+WaRmmUhFyz7XFgTLNvUcjWqZZ09RJRYmbzFRn5e9BA/6s5c1LZc3iyOXx/X7D1545zOKcdD57Y2lEzqmUApdL+Ood62nrGeSJCO2medHB+XvQgD8n1aX51J7pYng0/Dz+zjovjS09PLh1tSPvGJSys+uW53HbxkK+9+pJ2noGwj5f7ekuxhyavwcN+HNSXZrP4IifhjDz+JeGRnn8xUAZ5rYKLcNUKhoe2romWKYZftPzfU2dpCSJYwsrNODPQXVpHiKBvbDD8b1XA2WYX9Wm5EpFTUleJp++YTk767zUne0O61w1TV1UlrjJSE2K0OhiSwP+HLgzU1mzOId9YSzAaunu54nXmthWWcQ1S5x5t6CUU/zpTSsoyA5vN82+wREOep2bvwcN+HO2uTSf/We6GRqd2+z/eBnmFi3DVCrastKS+ZuPrKYujDLN2tPdjs7fgwb8OasuzWNo1E/9Wd+s/23t6S6ebWzjMx8so0jLMJWKiXuuKWaDJ1Cm2T88Out/v6+pk9QkF9c4NH8PGvDn7Prl+YE8/izr8SeWYX5GyzCVihmXS3j49rmXadY0dVK5xE16ijPz96ABf85yM1NYV5gz643Unq7zcsDbw0Nb12gZplIxdt3yPG4rD5RptvpmXqbZG8zfOzmdA2EGfBHJE5Ffisi7wf+d8rOOiOSISIuI/K9wrmknm0vz2X+2m8GRmeXxLw2N8vgLR6kscXNnRVGUR6eUmsxDW9bgN8xqN823T3XhNzh6whbCv8N/CPi1MWYl8Ovg46l8HXgtzOvZSnVpPsOj/hnvyPfPr5ykvW+Ih7UMUynLlORlct8Npeyqb+WdGZZp1jR1kprsomqJO7qDi7JwA/424MfB738MbJ/sIBG5FlgEvBTm9WzlfcvzcAkz2mahpbufJ15vYruWYSpluT+9qYyF2Wk88sxh/P7pyzT3NXVyjcPz9xB+wF9kjAl1DD5HIKi/h4i4gH8E/nq6k4nIfSJSKyK1HR0dYQ4t+nIzUlhflDujPP639h7FpbthKmUL89KSeWDLGuqbpy/T7BkY4VBrr+Pz9zCDgC8ivxKRg5N8bZt4nAmsZpjsT+XngOeNMS3TXcsY84QxZpMxZlNBQcGM34SVNpflU3fWd9U8/tunu3iusY3P3lhGYa6WYSplB3dVedjoyZ22TPOtU12YOMjfwwwCvjHmFmPMhkm+dgPnRaQQIPi/7ZOcYjNwv4icBv4B+ISIPBrB92Cp6tI8hsf8U+YCQ03JC3PT+cwHtSm5UnbhcgkP37GOc72DfP/Vqcs0a5o6SUt2Uenw/D2En9LZA3wy+P0ngd2XH2CM+QNjzBJjzDICaZ2fGGOuNrnrKO9bFsjjT7WvzlPvtIyXYTp1/w2l4tX7luVxe3kh339t6jLNfSc7uXbpfNKSnf/7G27AfxS4VUTeBW4JPkZENonID8MdnBNkp6ew0ZM76QKswG6Yx6haomWYStnVQ1vXYAw8NkmZpq9/mCPn4iN/D2EGfGNMpzHmQ8aYlcHUT1fw+VpjzJ9Mcvy/GmPuD+eadlRdmk9dc/cVXXW++8oJOvoCTclFtAxTKTsqnp/JfR8sZXd9K/vPvDc1+2Yof1+mAV8FVZflMzJm3pPHb+7q5wevn2JHlYcqLcNUytY+e2OwTPPZ95Zp1jR1kp7iorw418LRRY4G/Ah437I8klzynnr8R/ceJUmEB7astnBkSqmZmJeWzINb1tDQ7GN3g3f8+XjK34MG/IjISksO5vEDAf+tU108d0DLMJVykh1VHsqLc3ls7zH6h0fpvjTM0XN9cVGOGaIBP0KqS/NpaPFxcWiUR549RFFuOvd9UHfDVMopArtpBso0v/dqE2+eCtzAxcuELWjAj5jNwTz+l3ce4KC3lwe1DFMpx9m0LI87Kor4/qsnefodLxkpSZQXu60eVsRowI+QTUvnk+wSdte3co2WYSrlWA8Ftz956fB5Ni2bT2py/ITJ+HknFpuXljw+k//wHeu1DFMph/K4M/hMMB0bT+kcAO3AEUF/ccsqTl+4RGWJ2+qhKKXC8Nmbyrg0PMbd1xRbPZSIkrl2cI+2TZs2mdraWquHoZRSjiIi+40xmyZ7TVM6SimVIDTgK6VUgtCAr5RSCUIDvlJKJQgN+EoplSA04CulVILQgK+UUglCA75SSiUI2y68EpEO4EwYp1gAXIjQcKwUL+8D9L3YVby8l3h5HxDee1lqjCmY7AXbBvxwiUjtVKvNnCRe3gfoe7GreHkv8fI+IHrvRVM6SimVIDTgK6VUgojngP+E1QOIkHh5H6Dvxa7i5b3Ey/uAKL2XuM3hK6WUeq94vsNXSik1gQZ8pZRKEHEb8EXk6yLSKCL1IvKSiDi2yayI/L2IHA2+n50i4rZ6THMlIh8TkUMi4hcRx5XQicgWETkmIidE5CGrxxMOEfkXEWkXkYNWjyUcIlIiIi+LyOHgz9ZfWD2muRKRdBF5S0Qagu/laxE9f7zm8EUkxxjTG/z+z4F1xpjPWjysORGRDwO/McaMishjAMaYBy0e1pyIyFrAD3wf+GtjjGPamolIEnAcuBVoAd4G7jXGHLZ0YHMkIh8ELgI/McZssHo8cyUihUChMeYdEckG9gPbnfjfRQLNsOcZYy6KSArwBvAXxpiaSJw/bu/wQ8E+aB7g2L9sxpiXjDGjwYc1gGMbbRpjjhhjjlk9jjm6DjhhjGkyxgwDPwe2WTymOTPGvAZ0WT2OcBlj2owx7wS/7wOOAB5rRzU3JuBi8GFK8CtisStuAz6AiPydiDQDfwA8bPV4IuSPgb1WDyJBeYDmCY9bcGhgiVcisgyoAt60eChzJiJJIlIPtAO/NMZE7L04OuCLyK9E5OAkX9sAjDFfNsaUAD8F7rd2tFc33XsJHvNlYJTA+7GtmbwXpSJNRLKAp4C/vOwTvqMYY8aMMZUEPslfJyIRS7clR+pEVjDG3DLDQ38KPA98NYrDCct070VE/gi4HfiQsfnEyyz+uziNFyiZ8Lg4+JyyWDDf/RTwU2PM01aPJxKMMT4ReRnYAkRkYt3Rd/hXIyIrJzzcBhy1aizhEpEtwAPAncaYfqvHk8DeBlaKyHIRSQU+DuyxeEwJLzjR+SPgiDHm21aPJxwiUhCqwhORDAIFAhGLXfFcpfMUsJpARcgZ4LPGGEfejYnICSAN6Aw+VePgiqMdwP8ECgAfUG+M+Yilg5oFEfko8E9AEvAvxpi/s3ZEcyciPwNuIrAV73ngq8aYH1k6qDkQkQ8ArwMHCPy+A3zJGPO8daOaGxEpB35M4OfLBfzCGPNIxM4frwFfKaXUe8VtSkcppdR7acBXSqkEoQFfKaUShAZ8pZRKEBrwlVIqQWjAV0qpBKEBXymlEsT/D9X6L0MFj7v0AAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "np.array([1, 2, 3, 4, 5, 6]).reshape(-1, 1)",
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 7,
          "data": {
            "text/plain": "array([[1],\n       [2],\n       [3],\n       [4],\n       [5],\n       [6]])"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def plot_model(model, xmin=-4, xmax=4, npoints=100):\n    inputs = np.linspace(xmin, xmax, npoints).reshape(-1, 1)\n    outputs = model(torch.tensor(inputs).float()).detach().numpy()\n    plt.plot(inputs, outputs)",
      "execution_count": 8,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "for param in model.parameters():\n    print(param)",
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Parameter containing:\ntensor([[ 4.2743e-01],\n        [-5.0055e-01],\n        [ 7.5650e-01],\n        [-8.1553e-01],\n        [ 9.9174e-01],\n        [-8.3996e-01],\n        [ 1.5044e-01],\n        [ 3.0974e-01],\n        [-6.6457e-02],\n        [ 4.7461e-01],\n        [ 7.4093e-01],\n        [-3.3925e-01],\n        [ 8.3649e-01],\n        [ 3.3789e-01],\n        [-9.2626e-01],\n        [-7.7906e-01],\n        [-4.4785e-01],\n        [-8.1652e-01],\n        [ 7.4445e-01],\n        [-1.3111e-02],\n        [ 6.3134e-01],\n        [ 8.5577e-01],\n        [-4.9188e-01],\n        [-5.7354e-01],\n        [ 5.1029e-01],\n        [-5.7314e-01],\n        [ 2.7974e-01],\n        [-8.4150e-04],\n        [ 2.1194e-01],\n        [ 6.1326e-02]], requires_grad=True)\nParameter containing:\ntensor([-0.7595, -0.4352,  0.4703,  0.6161,  0.9185, -0.5220, -0.4084,  0.5563,\n         0.2487, -0.4534,  0.1685,  0.9966, -0.2362, -0.8529, -0.3274,  0.2013,\n         0.9696, -0.9952, -0.3354,  0.4088, -0.8547, -0.4180,  0.5028,  0.3702,\n         0.3630,  0.0478,  0.5392,  0.6045, -0.7784, -0.5995],\n       requires_grad=True)\nParameter containing:\ntensor([[ 0.0441,  0.1681,  0.1620,  0.1008, -0.1062, -0.0834, -0.0853, -0.1355,\n         -0.0733, -0.0559, -0.1243, -0.1357,  0.0565, -0.0875, -0.0618,  0.1050,\n          0.0592, -0.0670, -0.1322,  0.0846,  0.1301, -0.0952, -0.1370, -0.1559,\n          0.0686,  0.0567,  0.0925,  0.0344,  0.0872,  0.1421]],\n       requires_grad=True)\nParameter containing:\ntensor([0.0262], requires_grad=True)\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true,
        "scrolled": true
      },
      "cell_type": "code",
      "source": "plot_model(model, npoints=4000)",
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 432x288 with 1 Axes>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAD4CAYAAADvsV2wAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8/fFQqAAAACXBIWXMAAAsTAAALEwEAmpwYAAAnn0lEQVR4nO3deVyU5d4G8OvHvgmyoyCCghvuoqJlaZlaVlqmuaaVW3vntBzLOr1tJ8uW02Llvq/1pi2WZmblhgqKgguCG4goiGyyL/f7h1OvKYg4DPcwc30/n/nMDPM4z4XC5TPPct+ilAIREVk+G90BiIiofrDwiYisBAufiMhKsPCJiKwEC5+IyErY6Q5QHR8fHxUSEqI7BhFRgxIbG3teKeVb1WtmW/ghISGIiYnRHYOIqEERkVPVvcZdOkREVoKFT0RkJVj4RERWgoVPRGQlWPhERFaChU9EZCVY+EREVsJsz8Mnqm/nL5Zgf2oOyioUBkb4Q0R0RyKqUyx8slql5ZVYvusUYk5mIy41B2k5RX+9dk+nppj5QEc42dtqTEhUt1j4ZJXyi8swdVkstidnoZmXMzoHN8aE3iHo1KwxYk5dwMyNiUjJKsDchyLh5+6kOy5RnWDhk9U5l1eMCQv3IOlcPj4Y3gnDugX97fUeoV5o6euGf6yOw5BZ2zH3oUi0D/TQlJao7vCgLVmV5Ix83P/5DqRkFWDBhO5Xlf2fBkYE4KupvSAAhn+5ExsSztZvUCITYOGT1dhz8gKGfbETJeWVWD2lF25pVeWAgn+JaOqBdU/ehNYBjTB1WSxmbUkG54CmhsyowhcRLxHZJCJJhnvPapbbICI5IvKDMesjulEbEs5i7Lxd8HZ1wNrHe1/3Lhq/Rk5YNTkKQzo3xcyNifjnmv0oLqswOk9CWi4Wbj+B6ONZ/E+E6o2x+/CnAdislJohItMMz/9VxXIzAbgAmGLk+ohqbfGOk/if7w+ic7PGmD++O7xcHWr1553sbfHfBzsj3M8N7/98FKeyCjB7XCR8GzneUJ7o41mYsHA3issqAQATbw7F9MFteRoomZyxu3SGAFhseLwYwNCqFlJKbQaQb+S6yMoopZB1sQQHTufg96OZtd6yVkrh3Q1H8Np3B3F7G3+smBhV67L/k4jgydvC8fmYrjiUnoehs7bjcHperd8n5uQFPLJoD4I8XfDLP2/BuKjmmLftBL74/dgN5SKqDWO38P2VUumGx2cB+BvzZiIyGcBkAAgODjYyGpm78opKnMsvQVp2EdJyCg33RThtuD+TU/TXVjAA9G7pjQUTul/XufGl5ZWY9r8H8M2+NIzuGYw37o2Ana3xh6zu6tAEzTxdMHHJHgz7Ygc+HtkFd7S7vh/7fSnZmLBwDwLcnbBiYk/4uTvh9XsjkFdchvc2JMLTxQGjevDnnkxHatp/KCK/AAio4qXpABYrpRpftmy2Uqq6/fh9ATyvlLr7eoJFRkYqznhluTYdOocXv96P7MKyv33d29UBgZ7OCGzsjKaNL90HejojPacIr/9wCH1b+WL2uEg42FVf3qeyCvDKugRsTTqP5we0whP9wup8d8m5vGJMWhKD+LRcvDiwDSb1Cb3mfygJabkYNTcani4OWDOlFwI8/v/c/tLySkxaEoOtSZn4fExXDGrfpE6zknURkVilVGSVrxlzwEhEEgH0VUqli0gTAL8ppVpXs2xfsPCtXllFJWZuTMScP46jfaA7Rvdo/lfBBzZ2hrND9VvvK3al4OW18fBydUCQpzP83Z3QxMPpr/vUC0XYcPAsDqfnwc5G8M79HTA8spnJvpei0go8/9V+rI9PR2BjZzx8UwhG9giGm+PfPzgfTs/DqLnRcHWww+opUQjydLnqvQpLyzF23i4kpOVh0cPd0TvMx2S5ybKZsvBnAsi67KCtl1LqxWqW7QsWvlVLzy3Ckyv2IfZUNsZFNcf0wW1rPXTBj/Hp+D0xE2fzinE2txhn84qRW3TpU4IIENncEwMjAjCofUCVxVrXlFL45XAG5m49jt0nLqCRkx1G9wzGw71DEeDhhKRz+XhwTjQcbG2wZkovBHtXnymnsBQjZu9EWnYRVk6OQsegxibPT5bHlIXvDWANgGAApwCMUEpdEJFIAFOVUhMNy20F0AaAG4AsAI8qpTZe671Z+Jblj6OZeHZ1HErKKvDOsI64t1PTOnvvwtJynM0thruzPXzcbuzMmboQl5qDuVuP46f4dNiIYECEP3Ycy4K9oexDfVxrfI+zucUY9sUOFJVV4PunbkZgY+d6SE6WxGSFb0osfMtQUanw8S9H8emWZLTya4TPx3ZFS1833bFMKvVCIRZsP4GvYk6jbZNGeHdYR7Soxfd8PPMiBn28FcO6BuGd+zuYMClZIhY+aZGZX4JnVu3DjmNZeKBbEN4c0v6a++gtjVLqhg8Wv7ouAav2pOCPF/uhiQe38un6XavwObQCmUT08Szc9clW7E3JxnsPdMT7wztZVdkDMOrMoCm3toBSwOzfj9dhIrJ2LHyqU5WVCrO2JGP03Gg0crTDuiduwggTniljqYI8XXB/10Cs3J2CjPxi3XHIQrDwqc5kF5Ti0cV7MHNjIu7q0ATfPXUz2gS4647VYD3eNwxlFZWYv/WE7ihkIVj4VCf2pmRj8CdbsT05C28OicCno7pcdT461U6Ijyvu7dQUS6NPIbugVHccsgAsfDKKUgrzt53AiC93wsZG8PVjvTCuVwgHAqsjT/QLQ2FpBRZu51Y+GY+FTzcsr7gMjy3bizd/OIR+bfyw/qk+vFiojoX7N8Kd7QOwcMdJ5BWX1fwHiK6BhU83JCEtF/d8ug2bDp/D9LvaYs64bvBwsdcdyyI90S8M+cXl+OzXZN1RqIHjTlaqFaUUVuxOwevfH4KXiwNWT45CZIiX7lgWrX2gB0b1CMacP46jtX+jaqdlJKoJC5+uW0FJOaavjce6uDO4pZUvPhrRCd4ahzKwJm8MicCprAJM++YAAj2dEdXCW3ckaoC4S4euy9Fz+Rgyazu+238Gz93RCosmdGfZ1yN7Wxt8MaYbgr1cMGVpLI5lXtQdiRogFj7V6Nu4NAz5bDtyCkux7NGeeOr2cNjY8Cyc+ubhYo+FE3rAzkbwyKI9uMBTNamWWPh0TVuOZODZ1XHoEOiBH5/uw3HaNQv2dsGchyKRnluMKUtjUFJu/ITqZD1Y+FSt5IyLeHrlPrQNcMeiR7rDz92p5j9EJtetuSc+GN4Je05m48WvD8BcB0Ak88ODtlSl3KIyTF4SAwc7G8wdHwkXB/6omJN7OjXFqawCvP/zUYR4u+Ifd7TSHYkaAP4W01UqKhWeWrkPqdmFWD4xipNwmKkn+oXhxPlCfLw5CSE+LrivC0/XpGvjLh26yoyfDuOPo5l4Y0h79AjlOfbmSuTSvL1RLbzw4tcHEHvqgu5IZOZY+PQ3K3enYO7WE3ioV3OM6hGsOw7VwMHOBrPHRiLAwwnPrdmPolIexKXqsfDpL4t3nMRL38Tj1la+ePXudrrj0HXycLHHu8M64mRWIT765ajuOGTGWPgEAPjy92N47buDuKOdP+Y81A32tvzRaEh6t/TB6J7BmLf1OPalZOuOQ2aKv9VWTimFD39OxIyfjuCeTk3x+ZiucLSzrqkILcVLd7aBv7sT3vzhkO4oZKZY+FZMKYW31x/GJ78mY0RkEP77YGdu2TdgjZzsMeWWFtibkoPYU9zKp6vxt9tKVVYqvLIuAfO2ncCE3iGYcX9H2HK4hAZveGQzuDvZYf42Tn5OV2PhW6Hyiko8/9V+LN+Vgsf6tsRr97Tj2DgWwtXRDmOimmNDwlmkXijUHYfMDAvfypSWV+LpVfvwzb40PD+gFf41qA2nI7Qw43uFwEYE87dxWkT6Oxa+FSkuq8DUZbH4Mf4sXhncFk/eFq47EplAgIcT7u3UFGtiUpFbxGkR6f+x8K1EQUk5Hlm0B1sSM/Cf+zpgYp8WuiORCT3aJxSFpRVYuTtFdxQyIyx8K5BXXIaHFuxG9PEsfDiiE0b35BW0li6iqQd6t/TGou0nUVpeqTsOmQkWvoXLLijFmLm7cOB0DmaN7soBtqzIpD4tcDavGD/Gp+uOQmaChW/BMvKLMXJONBLP5WPOuEjc2aGJ7khUj25t5YswPzfM3XqcY+YTABa+xTqTU4QHZ0cjNbsQiyZ0R782frojUT2zsRE8enMoDp7Jw87jWbrjkBlg4VugU1kFGP7lTpzPL8HSR3twWkIrdl+XQHi7OmDeVp6iSSx8i5OckY8Rs3eisLQcKydHoVtzjmdvzZzsbTGuV3P8eiQDyRkXdcchzVj4FuTgmVw8ODsalQpYNbkX2gd66I5EZmBcVHM42NnwQixi4VuKfSnZGDUnGo52NlgzpRdaBzTSHYnMhLebI4Z1DcQ3e08j62KJ7jikEQvfAkQfz8LYebvg6eqANVN7IdTHVXckMjOP3twCJeWVWBbNC7GsmVGFLyJeIrJJRJIM955VLNNZRHaKyEEROSAiDxqzTvq7349mYsLC3WjS2BlrpvRCkKeL7khkhsL83HBbGz8sjT6J4jJOg2itjN3CnwZgs1IqHMBmw/MrFQJ4SCkVAWAQgP+KSGMj10sANh48i0mLY9DCxw2rJ0fB391JdyQyYxNvDsX5i6VYty9NdxTSxNjCHwJgseHxYgBDr1xAKXVUKZVkeHwGQAYAXyPXa/W+jUvD48v3ol1Td6ycFAVvN0fdkcjM9WrpjXZN3DFv2wlUVvJCLGtkbOH7K6X+vG77LAD/ay0sIj0AOAA4Vs3rk0UkRkRiMjMzjYxmudbsScWzq+MQ2dwTyyb2hIeLve5I1ACICCbdEorkjIv4PYm/X9aoxsIXkV9EJKGK25DLl1OXrt2udrNBRJoAWArgYaVUlaM5KaXmKKUilVKRvr78EFCVRdtP4MX/PYBbwn2x6OEecHO00x2JGpDBHZoiwN0J87ZyRixrVGNbKKX6V/eaiJwTkSZKqXRDoWdUs5w7gPUApiulom84rZX7/LdkvLchEQMj/PHJqC6cbJxqzcHOBuN7h+DdDUdw8EwuIpryWg1rYuwune8AjDc8Hg/g2ysXEBEHAGsBLFFKfW3k+qySUgof/JyI9zYkYkjnpvhsdFeWPd2w0T2C4eJgywuxrJCxhT8DwB0ikgSgv+E5RCRSROYZlhkB4BYAE0QkznDrbOR6rYZSCm+tP4xPf03GyO7N8OGIzrC35eUTdOM8XOwxIrIZvt9/BufyinXHoXpkVHMopbKUUrcrpcKVUv2VUhcMX49RSk00PF6mlLJXSnW+7BZXB9ktXmWlwstrEzB/2wk8fFMI3rm/A2w52TjVgUduCkVFpcKiHSd1R6F6xE1FM1VeUYnnvtqPlbtT8ES/lvj33e042TjVmWBvFwyMCMDy6FMoKCnXHYfqCQvfDJWWV+Kplfuwdl8aXhjYGi8MbMOypzo3sU8L5BWX4+vY07qjUD1h4ZuZ4rIKTFkag58SzuLVu9vhiX5huiORherW3BNdgxtj/rYTqOCFWFaBhW9GCkrK8fDCPfjtaCbeub8DHr05VHcksnAT+7RAyoVCrNjNQdWsAQvfTOQWleGhBbux++QFfDiiE0b1CNYdiazAoIgA3NrKF29+fwhxqTm645CJsfDNwIWCUoyZF40Dp3Mwa3QX3NclSHckshI2NoKPR3aGn7sjHlsWi/McL9+isfA1y8grxsg5O5F07iLmPBSJQe2b6I5EVqaxiwO+HNsNFwpK8dSKfSivqHLkE7IALHyN0nKKMGL2TpzOLsKih3ugX2s/3ZHISrUP9MBbQ9tj5/EszPw5UXccMhGOvKXJyfMFGDNvF/KKy7D00Z7o1vyquWOI6tXwyGaIS83B7N+Po3NQY9zZgZ82LQ238DVIOpePEbN3oqisAisnRbHsyWz8+5526NysMZ7/aj+SM/J1x6E6xsKvZwlpuXhwTjQUgNWTo9A+kKMVkvlwtLPFF2O7wsneFlOWxuIir8K1KCz8erQ3JRuj50bD2d4WX03phXD/RrojEV2liYczPh3dBSfOF+CFr/bj0lQXZAlY+PVk57EsjJu3C16uDlg9JQohPq66IxFVq3dLH0y7sw1+SjiLOX9wshRLwcKvB78lZmDCwt1o2tgZa6b0QpCni+5IRDWa1KcFBndognc3HMGO5PO641AdYOGb2IaEs5i0JAZhfm5YPaUX/NyddEciui4igncf6IgWvm54cuU+nMkp0h2JjMTCN6Fv49LwxIq96BDogRWTouDl6qA7ElGtuDna4cux3VBaXonHlu9FSXmF7khkBBa+iazanYJnV8ehR4gXlj7aEx7O9rojEd2QMD83vD+8I/an5uD17w/pjkNGYOGbwIJtJzDtm3jc2soXCx/uDldHXt9GDdug9k0w9daWWLErBWtiUnXHoRvEwq9js7Yk440fDmFQRABmj+sGJ3tONk6W4fkBrXBTmDdeWZeA+NO5uuPQDWDh1xGlFGZuPIKZGxNxX5dAfDa6CxztWPZkOexsbfDJyC7wcXXA1GWxyC4o1R2JaomFXweUUnjjh0OYteUYRvUIxgfDO8HOln+1ZHm83RzxxdhuyMwvwdOr9nGmrAaGrWSkikqFl9fGY+H2k3jkplD85772sLHh/LNkuTo1a4zXh0Rga9J5fLTpqO44VAs8mmiE8opKPP/VfqyLO4Mn+4XhuQGtONk4WYVRPYIRl5KDz7Yko2OQBwZEBOiORNeBW/g3qKS8Ak+s2It1cWfwwsDWeH5ga5Y9WZXXh0SgQ6AHnluzH8czL+qOQ9eBhX8DissqMHlJLDYePIfX7mmHJ/qF6Y5EVO+c7C+NrGlnK5iyNBY5hTyIa+5Y+LV0saQcExbuxh9JmZhxfwc8fFOo7khE2gR5umDW6K44lVWI8Qv3cDhlM8fCr4XcojKMm78Le05m478PdsbIHsG6IxFp1zvMB5+N7oKEtFxMXLwHxWUcfsFcsfCv04WCUoyeG42DaXn4fExXDOkcqDsSkdkYEBGAD4Z3wq4TF/DYsliUlnMidHPEwr8OGXnFeHD2TiRnXMTc8ZEYyDMSiK4ytEsg3h7aAVsSM/GP1XEor2DpmxuellmD09mFGDNvF87nl2DxIz0Q1cJbdyQiszW6ZzAKSsrx9o+H4exgi/eGdeR1KWaEhX8NJ88XYPTcaFwsKcfSiT3RNZiTjRPVZNItLXCxpBwfb06Cm6MdXrunHU9ZNhMs/GocPZePMfN2oaJSYeXkKEQ05WTjRNfr2f7hKCgpx7xtJ+DqaIsXBrbRHYnAwq9SQlouxs3fBXtbG6yeHMXJxolqSUQwfXBbFJSWY9aWY3B1tMPjfXm9im4s/CvEnsrGhIW74e5kjxWTeqK5NycbJ7oRIoK3hnZAYWkF3tuQCFcHO4zvHaI7llVj4V9mx7HzmLg4Bv7uTlg2sScCGzvrjkTUoNnaCN4f3gmFpRV47buDcHW0wwPdgnTHslpGnZYpIl4isklEkgz3Vx3VFJHmIrJXROJE5KCITDVmnaayJTEDDy/cgyBPZ6yeEsWyJ6oj9rY2+HRUF9wc5oMXv96PH+PTdUeyWsaehz8NwGalVDiAzYbnV0oH0Esp1RlATwDTRKSpkeutUxsS0jF5SQzC/d2wanIv+DVy0h2JyKI42dtizkPd0CXYE8+s2octRzJ0R7JKxhb+EACLDY8XAxh65QJKqVKlVInhqWMdrLNOrduXhidW7EPHoMZYMSkKXq4OuiMRWSQXBzssmNAdrfwbYeqyWOw8lqU7ktUxtnz9lVJ/fj47C8C/qoVEpJmIHACQCuBdpdQZI9dbJ1buTsE/1sShZ6gXljzSA+5O9rojEVk0D2d7LHmkB5p5uWDi4j2IS83RHcmq1Fj4IvKLiCRUcRty+XJKKQWgyvnOlFKpSqmOAMIAjBeR6v5jmCwiMSISk5mZeQPfzvWbv+0EXvomHn1b+WLBhO5wdeTxa6L64O3miOUTe8LbzRHjF+zGfpZ+vamx8JVS/ZVS7au4fQvgnIg0AQDD/TV3zBm27BMA9Knm9TlKqUilVKSvr2/tv5vr9NmvSXjzh0O4s30AZo+LhJM9Jxsnqk/+7k5YPrEn3BztMPzLnVgafQqXthnJlIzdpfMdgPGGx+MBfHvlAiISJCLOhseeAG4GkGjkem+IUgrvbTiC938+ivu7BOLTUV3gYGdWhxSIrEYzLxf88NTN6B3mjVfXJeCZVXEo4Hj6JmVs280AcIeIJAHob3gOEYkUkXmGZdoC2CUi+wH8DuB9pVS8keutNaUUXv/+ED7/7RhG9wzG+8M7wc6WZU+kk6erAxaM747nB7TCDwfOYMis7Ug6l687lsUSc/0YFRkZqWJiYurkvSoqFaavjceqPal49OZQvDK4LQdzIjIzO5LP4+lV+1BQUoF37u+AoV0458SNEJFYpVRkVa9Z/CZuWUUl/rkmDqv2pOLp28JY9kRmqneYD9Y/3QcdAj3w7Oo4vLw2nrNn1TGLLvyS8go8uWIvvo07g38NaoN/DmjNsicyY/7uTlgxqSem3toSK3al4IEvdyAlq1B3LIthsYVfVFqByUtisfHgOfzPPe3wWN+WuiMR0XWws7XBtDvbYO5DkUjJKsTgT7di06FzumNZBIss/Isl5ZiwcDf+SMrEe8M6YsJNobojEVEt3dHOH+uf7oMQb1dMWhKDd346zGkTjWRxhZ9bWIZx83ch5lQ2Ph7ZBSO6N9MdiYhuUDMvF3w1tRfGRgVj9u/HMXruLpzLK9Ydq8GyuMIvrahEUWkFvhjTFfd2Mqsx2ojoBjjZ2+KtoR3w8cjOiE/LxeBPtmJH8nndsRokizwts7yikufYE1mgpHP5eGz5Xpw8X4CFD3dHn3DTXZHfUFndaZkseyLLFO7fCN883hthfm6YujQWCWm5uiM1KGxGImpQ3J3ssejhHmjs4oAJC/cg9QJP27xeLHwianACPJyw+JHuKKuoxPgFu3GhoFR3pAaBhU9EDVKYXyPMGx+JtJwiPLp4D4pKeVVuTVj4RNRgdQ/xwscjuyAuNQdPrdzL8/RrwMInogZtUPsAvHFvBH45nIFXv03guPrXwGmeiKjBG9crBGfzijFryzEEuDvjmf7huiOZJRY+EVmE5we0xtncEnz0y1H4uztiZI9g3ZHMDgufiCyCiGDGsA7IvFiCV9YloKWfG7qHeOmOZVa4D5+ILIa9rQ0+G90Fzbxc8PjyvcjguDt/w8InIovi7mSPL8d2w8Xicjy+fC9Ky3nmzp9Y+ERkcVoHNMJ7D3REzKls/OfHw7rjmA3uwycii3RPp6aIS83B/G0n0KmZB+7rEqQ7knbcwiciizXtzjboEeqFl76Jx6EzebrjaMfCJyKLZW9rg1mju8LD2R5Tl8Uit7BMdyStWPhEZNF8Gznii7HdkJ5bhGdX70NlpfVeicvCJyKL1zXYE/++JwJbEjPx8eYk3XG0YeETkVUY2zMYw7oG4ePNSdhyJEN3HC1Y+ERkFUQEb9/XHm0CGuHltfFWOZwyC5+IrIaTvS1evzcC6bnFmL/tuO449Y6FT0RWpWcLbwyM8Mfnvx1DRr51Db3AwiciqzPtzrYoq6jER5uO6o5Sr1j4RGR1Qn1c8VCvEKzek4rD6dZzQRYLn4is0lO3haGRkz3+8+Nhq5kli4VPRFapsYsDnrk9HFuTzuO3o5m649QLFj4RWa2xUc0R6uOKt9cftooJ0Fn4RGS1HOxsMO3ONkjOuIhVe1J1xzE5Fj4RWbUB7fzRM9QLH206irxiyx5cjYVPRFZNRPDK4HbIKijF51uO6Y5jUkYVvoh4icgmEUky3HteY1l3ETktIp8Zs04iorrWIcgD93cNxILtJ5B6oVB3HJMxdgt/GoDNSqlwAJsNz6vzJoA/jFwfEZFJvDCwNWwEeG9jou4oJmNs4Q8BsNjweDGAoVUtJCLdAPgD+NnI9RERmUQTD2dM7tMC3+8/g70p2brjmISxhe+vlEo3PD6LS6X+NyJiA+ADAM/X9GYiMllEYkQkJjPTOs6LJSLzMeXWlvBt5Ii3fjhkkRdj1Vj4IvKLiCRUcRty+XLq0t9OVX9DjwP4USl1uqZ1KaXmKKUilVKRvr6+1/1NEBHVBVdHO7wwoDX2puRgfXx6zX+ggbGraQGlVP/qXhORcyLSRCmVLiJNAFQ1q0AvAH1E5HEAbgAcROSiUupa+/uJiLQY1i0IC7afwIyfjqB/W3842dvqjlRnjN2l8x2A8YbH4wF8e+UCSqkxSqlgpVQILu3WWcKyJyJzZWtz6TTN09lFWLzjpO44dcrYwp8B4A4RSQLQ3/AcIhIpIvOMDUdEpMPN4T64rY0fPvs1GVkXS3THqTNGFb5SKkspdbtSKlwp1V8pdcHw9Ril1MQqll+klHrSmHUSEdWHl+9qg8KyCoua9JxX2hIRVSHMrxHG9AzG8l0pSM7I1x2nTrDwiYiq8czt4XCxt8V/fjyiO0qdYOETEVXD280RT94Whl+PZGBb0nndcYzGwiciuobxvUPQzMsZb60/hIrKhn0xFgufiOganOxt8a9BbXDkbD6+jm3YY+az8ImIajC4QxN0DW6M938+ioKSct1xbhgLn4ioBiKCV+5uh8z8Esz+veGOmc/CJyK6Dl2DPXFPp6aYs/U40nOLdMe5ISx8IqLr9OLA1qhUwMwGOmY+C5+I6Do183LBIzeF4pu9aYg/nas7Tq2x8ImIauHxfi3h7eqAt9Y3vDHzWfhERLXg7mSPf9zRCrtOXMDPh87pjlMrLHwioloa2b0Zwv3c8M6Ph1FaXqk7znVj4RMR1ZKdrQ1eHtwWJ7MKsSz6lO44142FT0R0A/q28kWfcB98vDkJOYWluuNcFxY+EdENEBFMH9wW+cVl+GRzsu4414WFT0R0g9oEuOPB7s2wNPokTpwv0B2nRix8IiIj/OOOVnCwtcGMnw7rjlIjFj4RkRH8Gjnhsb4tsfHgOUQfz9Id55pY+ERERprYpwWaejjh7fWHUWnGY+az8ImIjORkb4sXBrVGfFou1sWl6Y5TLRY+EVEdGNIpEB2DPDBzYyKKSit0x6kSC5+IqA7Y2AheGdwO6bnFmLf1uO44VWLhExHVkR6hXhgUEYAvfj+GjLxi3XGuwsInIqpD0+5sg7KKSny46ajuKFdh4RMR1aEQH1c81CsEq2NScehMnu44f8PCJyKqY0/fFg4PZ3v858fDZjVmPgufiKiOebjY45nbw7Et+Tx+S8zUHecvLHwiIhMY07M5Qn1c8db6QyirMI8x81n4REQm4GBng5fubINjmQVYtTtFdxwALHwiIpO5o50/eoZ64aNfkpBXXKY7DgufiMhURASv3t0O2YWl+PBn/adpsvCJiEyofaAHxvQMxpKdJ5GQlqs1CwufiMjEXhjYBt5ujnh5bTwqNI6mycInIjIxD2d7vHp3Oxw4nat10nOjCl9EvERkk4gkGe49q1muQkTiDLfvjFknEVFDdE/HJugT7oOZGxNxTtM4O8Zu4U8DsFkpFQ5gs+F5VYqUUp0Nt3uNXCcRUYMjInhraHuUVlTije8PaclgbOEPAbDY8HgxgKFGvh8RkcVq7u2Kp/qFYX18OrYkZtT7+o0tfH+lVLrh8VkA/tUs5yQiMSISLSJDjVwnEVGDNfnWFmjp64p/f5tQ7xOl1Fj4IvKLiCRUcRty+XLq0ghB1R1+bq6UigQwGsB/RaRlNeuabPiPISYz03zGnyAiqiuOdrZ4+74OSL1QhE9/TarXddvVtIBSqn91r4nIORFpopRKF5EmAKr8jKKUSjPcHxeR3wB0AXCsiuXmAJgDAJGRkeYzxBwRUR2KauGNYV2DMHfrcdzfNRBhfo3qZb3G7tL5DsB4w+PxAL69cgER8RQRR8NjHwA3AdBzxIKIyEy8fFcbuDjY4ZV1CfU2hLKxhT8DwB0ikgSgv+E5RCRSROYZlmkLIEZE9gPYAmCGUoqFT0RWzdvNEf8a1AbRxy9g7b60elmnmNPg/JeLjIxUMTExumMQEZlMZaXCsC93ICWrEL8+1xceLvZGv6eIxBqOmV6FV9oSEWliY3Pp3PzswlK8t/GI6ddn8jUQEVG1Ipp6YELvUKzYnYK41ByTrouFT0Sk2T8HtIJfI0dMXxuPchPOjsXCJyLSzM3RDv++OwIHz+RhqQkHV2PhExGZgbs6BOCWVr744OejJhtcjYVPRGQGRARv3BuB0opKvPmDac5cr/FKWyIiqh8hPq54tn84iksrUFmpYGMjdfr+LHwiIjPyeN8wk703d+kQEVkJFj4RkZVg4RMRWQkWPhGRlWDhExFZCRY+EZGVYOETEVkJFj4RkZUw2wlQRCQTgDGjCPkAOF9HceoSc9UOc9UOc9WOJeZqrpTyreoFsy18Y4lITHWzvujEXLXDXLXDXLVjbbm4S4eIyEqw8ImIrIQlF/4c3QGqwVy1w1y1w1y1Y1W5LHYfPhER/Z0lb+ETEdFlWPhERFbC4gtfRJ4TESUiPrqz/ElE3hSRAyISJyI/i0hTM8g0U0SOGHKtFZHGujP9SUSGi8hBEakUEa2n0InIIBFJFJFkEZmmM8vlRGSBiGSISILuLJcTkWYiskVEDhn+DZ/RnQkARMRJRHaLyH5Drtd1Z/qTiNiKyD4R+aGu39uiC19EmgEYACBFd5YrzFRKdVRKdQbwA4B/a84DAJsAtFdKdQRwFMBLmvNcLgHA/QD+0BlCRGwBzAJwJ4B2AEaJSDudmS6zCMAg3SGqUA7gOaVUOwBRAJ4wk7+zEgC3KaU6AegMYJCIROmN9JdnABw2xRtbdOED+AjAiwDM6si0UirvsqeuMIN8SqmflVLlhqfRAIJ05rmcUuqwUipRdw4APQAkK6WOK6VKAawCMERzJgCAUuoPABd057iSUipdKbXX8Dgfl4osUG8qQF1y0fDU3nDT/nsoIkEABgOYZ4r3t9jCF5EhANKUUvt1Z6mKiLwtIqkAxsA8tvAv9wiAn3SHMEOBAFIve34aZlBeDYWIhADoAmCX5igA/tp1EgcgA8AmpZQ55PovLm2kVprizRv0JOYi8guAgCpemg7gZVzanaPFtbIppb5VSk0HMF1EXgLwJIDXdGcyLDMdlz6GLzd1ntpmo4ZLRNwA/C+AZ6/4hKuNUqoCQGfD8aq1ItJeKaXtGIiI3A0gQykVKyJ9TbGOBl34Sqn+VX1dRDoACAWwX0SAS7sn9opID6XUWZ3ZqrAcwI+oh8KvKZOITABwN4DbVT1foFGLvy+d0gA0u+x5kOFrdA0iYo9LZb9cKfWN7jxXUkrliMgWXDoGovOg900A7hWRuwA4AXAXkWVKqbF1tQKL3KWjlIpXSvkppUKUUiG49NG7a32VfU1EJPyyp0MAHNGV5U8iMgiXPkreq5Qq1J3HTO0BEC4ioSLiAGAkgO80ZzJrcmmLaz6Aw0qpD3Xn+ZOI+P55JpqIOAO4A5p/D5VSLymlggydNRLAr3VZ9oCFFn4DMENEEkTkAC7tdjKHU9U+A9AIwCbD6aJf6g70JxG5T0ROA+gFYL2IbNSRw3BQ+0kAG3Hp4OMapdRBHVmuJCIrAewE0FpETovIo7ozGdwEYByA2ww/V3GGLVjdmgDYYvgd3INL+/Dr/DRIc8OhFYiIrAS38ImIrAQLn4jISrDwiYisBAufiMhKsPCJiKwEC5+IyEqw8ImIrMT/AYK9SA7i0fG5AAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "criterion = nn.MSELoss()",
      "execution_count": 11,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "optimizer = torch.optim.SGD(model.parameters(), lr=0.001, momentum=0.9)",
      "execution_count": 12,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "n_samples = 100\nx_train = np.random.uniform(-4, 4, size=(n_samples, 1))\ny_true = np.sin(x_train)\ny_train = y_true\n\n# Мы не успели это обсудить, но интересный вопрос — что будет, если данные зашумлены\n\n# y_train = y_true + np.random.normal(scale=0.3, size=(n_samples, 1))",
      "execution_count": 13,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "plt.plot(x_train, y_train, 'o')",
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 14,
          "data": {
            "text/plain": "[<matplotlib.lines.Line2D at 0x122aa5000>]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 432x288 with 1 Axes>",
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "subsample_idxs = np.random.choice(range(x_train.shape[0]), \n                                      size=n_samples // 10, \n                                      replace=False)\nsubsample_idxs\nx_train[subsample_idxs]",
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 15,
          "data": {
            "text/plain": "array([[-0.03127898],\n       [-3.40497863],\n       [-1.72319779],\n       [-0.68769829],\n       [-2.24139767],\n       [ 1.41861052],\n       [-1.53342321],\n       [ 3.12197392],\n       [-1.56606943],\n       [-3.96000049]])"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "model",
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 16,
          "data": {
            "text/plain": "Sequential(\n  (0): Linear(in_features=1, out_features=30, bias=True)\n  (1): ReLU()\n  (2): Linear(in_features=30, out_features=1, bias=True)\n)"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "from IPython.display import clear_output, display",
      "execution_count": 17,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "n_hidden_1 = 500\nn_hidden_2 = 500\nmodel = nn.Sequential(nn.Linear(1, n_hidden_1), nn.ReLU(), \n                      nn.Linear(n_hidden_1, n_hidden_2), nn.ReLU(), \n                      nn.Linear(n_hidden_2, 1))\n\noptimizer = torch.optim.SGD(model.parameters(), lr=0.001, momentum=0.9)\n\ntraining_steps = 100\nn_samples = 100\n\nfig, ax = plt.subplots()\n# создали картинку, на которой будем рисовать\n\nfor i in range(training_steps):\n    outputs = model(torch.tensor(x_train).float())\n    loss = criterion(outputs, torch.tensor(y_train).float())\n    \n    # МАГИЯ МАГИЯ\n    optimizer.zero_grad()\n    loss.backward()\n    optimizer.step()\n    # КОНЕЦ МАГИИ\n    \n    clear_output(wait=True)\n    plt.gca().clear()\n    # Делаем анимацию\n    \n    plot_model(model, npoints=4000)\n    plt.plot(x_train, y_train, 'o')\n    plt.title(f\"loss = {loss}\")\n    display(fig)\n    \nprint(loss.item())",
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 432x288 with 1 Axes>",
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "0.021137362346053123\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 432x288 with 1 Axes>",
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "plot_model(model, npoints=4000)\nplt.plot(x_train, y_train, 'o')\n\n# можно нарисовать истинную зависимость (не зашумлённую)\n# plt.plot(x_train, y_true, 'o')",
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 19,
          "data": {
            "text/plain": "[<matplotlib.lines.Line2D at 0x122a18100>]"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 432x288 with 1 Axes>",
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "name": "py3.10",
      "display_name": "Python 3.10",
      "language": "python"
    },
    "language_info": {
      "name": "python",
      "version": "3.10.0",
      "mimetype": "text/x-python",
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "pygments_lexer": "ipython3",
      "nbconvert_exporter": "python",
      "file_extension": ".py"
    },
    "@webio": {
      "lastKernelId": null,
      "lastCommId": null
    },
    "gist": {
      "id": "bad4a836e8dd21ba9d83029e50da4e73",
      "data": {
        "description": "pytorch simple function example",
        "public": true
      }
    },
    "_draft": {
      "nbviewer_url": "https://gist.github.com/bad4a836e8dd21ba9d83029e50da4e73"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}