Lesson_6.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyPVENcKI01gny8T3OXL8Jn/",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/sanadv/MLCourse/blob/main/Lesson_6.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 544
        },
        "id": "irXukdNXA0q0",
        "outputId": "e72f9776-954e-4baf-f304-8a1df3ee1f02"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "w0 =  0.20 , w1 = -0.60 , w2 =  0.25\n",
            "w0 =  0.30 , w1 = -0.50 , w2 =  0.15\n",
            "w0 =  0.40 , w1 = -0.40 , w2 =  0.05\n",
            "w0 =  0.30 , w1 = -0.50 , w2 = -0.05\n",
            "w0 =  0.40 , w1 = -0.40 , w2 = -0.15\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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4DoBFJSXUqdrk1dAAf/6zd7sLDeAArlIX7qqmmXNDNXMu0SlpEhFJUKmpQ7iYf5BrOkhZfT2Ly/TwXsC7LlNZGWRnw9SpXTqVb2gubWiaZs4lAf2ERUQSVGrqYKw0Ms34XwB+pWqTl68B/OabwWbr0qn0+JTkoqRJRCRB2e39MZmsTObvDLClUF5fz5N790Y7rOgqKgLfDOrZs7t8Os2cSy5KmkREEpTJZMHhGIiVRuZlNwDwcEkJtclcbXr6aTAMuPBCGDKky6dT0pRclDSJiCQwh2MwAFekfc1Ah4OKhobkrTY1NMDSpd7tLjaAg3fmXO1WLTeQTJQ0iYgksNRUbzWl0bmTHxcUAN5qU00yVpteew0qKiA3Fy67rMunc+124T7qxpRiInVoaggClFinpElEJIGlpnorTXV1XzM9J4fBDgf7Ghr4U2lplCOLAl8D+C23gNXa5dP5nzl3cipmm36dJgP9lEVEEphveM7p/Bqr2eyvNj2ye3dyVZt27IC33waTKSQN4KB+pmSkpElEJIH5hufq6nYCcFNODkMcDvY3NPBEMlWbFi/2/jllCgwcGJJT6vEpyUdJk4hIAnM4BgHQ2HiIhoYjpJjN/KQpafj17t1UNzZGMboIcblg2TLvdggawH20RlPyUdIkIpLAUlJ6YLX2AbxDdADTsrM5KTWVAw0NPJEMM+lWrYIDB6BfP7j00pCc0vAY1GzV8FyyUdIkIpLgjg3ReZOmFLOZnzT1Nv26pISjiV5t8jWAz5oFKSkhOaWzxImnxoPJaiL1JM2cSxZKmkREElxgM7jPDdnZDE1N5WBjI/+TyL1N27fD+vVgNsOtt4bstP5nzg1Lw2zVr9JkoZ+0iEiCO7bswE7/eylmMw82VZse3b2bqkStNvkawC+5BPLzQ3Za9TMlJyVNIiIJzuHwDs8FVpoArs/JYVhqKocaG3k8EatNTicsX+7dDmEDOGi5gWSlpElEJMEFLnAZyGIy8WDTTLrf7N5NZaJVm159FQ4d8laYLr44pKdW0pSclDSJiCS4Yz1NxXg8Dc0+uzY7m+FpaRxubOTxPXuiEV74+BrAb70VLJaQndbwGNRu0xpNyUhJk4hIgrPb+2Iy2QE3LtfuZp9ZTCZ/b9Nv9uxJnGrT1q3wz396k6VZs0J6amexE0+tB5PNhGOII6TnltimpElEJMGZTGZSU72LXB4/RAdwTXY2p6SlcaSxkd8nSrXJ1wD+7W9712cKIX8T+LA0zCn6NZpM9NMWEUkCx5rBd57wmcVkYkFTb9Nvd+/mSEPDCfvElbo6eOYZ73aIG8BBj09JZkqaRESSQGvN4D5X9+nDiLQ0Kt1ufhfv1aaXX4YjR6CgAC66KOSn13IDyUtJk4hIEmhpgctA5oBq02N79nA4nqtNvgbw2bND2gDuo5lzyUtJk4hIEjj2KJUTh+d8rurTh9O6daMqnqtNmzfDBx94H5dyyy0hP71mziU3JU0iIkkgcFVwwzBa3MdsMrGgaSbd7+K12uSrMl1+OeTlhfz0ziInnjoPJruJ1CF65lyyUdIkIpIEHA7v7Dm3u4rGxsOt7ndlnz6MbKo2/Tbeqk01NbBihXc7DA3gENDPNDwNk8UUlmtI7FLSJCKSBCyWNGw2b+WlrSG6wN6m3+/Zw6F4qja9+CJUVcHgwXDBBWG5hPqZkpuSJhGRJNFeM7jP1KwsRnXrxlG3m9/s3t3mvjHFNzQ3Zw6Yw/PrTUlTclPSJCKSJAL7mtpiNpl4qKna9IfSUg7U14c7tK4rLISPPwarFW6+OWyX0RpNyU1Jk4hIkjg2g67tShPA5VlZjO7enep46W3yVZmuuAKys8NyCcNtUPulN2nSGk3JSUmTiEiSCHZ4DsAUUG16PNarTdXV8Nxz3u0wNYAD1H1dh8fpwewwkzpIM+eSkZImEZEkEezwnM9lvXtzRlO16dFY7m16/nk4ehSGDoXzzw/bZfwz507RzLlkpaRJJFBZGTz0kPdPkQTje/6cy7Ubj6f9ylFgtel/SkvZH6vVpsAGcFP4khn1M4mSJpFAZWWwcKGSJklINlsOZnMaYOB0Fgd1zLd79+bMHj2o8Xj4dSxWmzZt8r5sNpg5M6yX0jPnREmTiEiSMJlMHR6iC6w2PVFayr5Yqzb5qkxXXQVZWWG9lJYbkLhKmt577z2+853v0LdvX0wmE6tXr273mPXr13PGGWdgt9s56aSTWL58edjjFBGJVR1pBve5pFcvzurRg9pYqzZVVcHKld7tMDaAA3gaPdRu1/BcsourpKmmpoZRo0bxxBNPBLV/UVERl156Keeffz6FhYXcfffd3Hrrrbz55pthjlREJDYdqzQFnzQdX22qiJVq08qV3kenDB8O554b1ks5v3ZiuAzMqWYcAx1hvZbErpRoB9ARF198MRdffHHQ+z/55JMMGjSI3/zmNwCccsopvP/++zz22GNMnjw5XGGKiMQsXzO40xnc8JzPxb16Ma5HDz46epRHSkr4zUknhSO84BlGxBrA4biZc2bNnEtWcVVp6qiNGzcyadKkZu9NnjyZjRs3RikiEZHo6kylCZpXm/60dy/lLleoQ+uYTz7xrgJut8OMGWG/nPqZBOKs0tRR5eXl5OTkNHsvJyeHqqoq6urqSE09cXEyl8uFK+Afg6qqqrDHKRFWVtb67LjPPmv+Z0vy8rwvkTgU2NNkGAamDlRoJvfqxdnp6XxYVcXDu3fzWDSrTb4q0zXXQK9e/rfb+noHo7Wvt5YbEEjwpKkzFi1axMKFC6MdhoTTU095lxVoy+zZrX+2YIF3LSeROORwDARMuN3VNDTsx2YL/pEjJpOJhQMHMvnf/+bJvXu5Pz+fPLs9bLG26sgR74KWcEIDeDBf77a09vXWcgMCCZ405ebmUlFR0ey9iooK0tPTW6wyAcyfP5958+b5/15VVUV+fn5Y45QIu+02uOyylj/77DNvwvT003DGGS3voyqTxDGLxYHd3g+Xaw91dV93KGkCuLBnT8anp7OxqoqHS0r43dChYYq0Dc8+C3V1MGIETJjQ7KO2vt7BaOnrrZlz4pPQSdP48eN5/fXXm723du1axo8f3+oxdrsdezT+y0kiJ5jhtTPOaD1pEolzDsdgXK49OJ1fk5FxdoeO9VWbLvJVmwYMoG8k/80MbAC/7bYTGsDDMXpet6MOo97AnGbGUaCZc8ksrhrBq6urKSwspLCwEPAuKVBYWEhJSQngrRJNnz7dv//tt9/O119/zf3338+XX37JH//4R1566SXuueeeaIQvIhITUlO9M+iCXeDyeJN69uSc9HRchsGvmv79jZiNG2HzZkhNhZtuisgl/f1Mp3bTzLkkF1dJ06effsqYMWMYM2YMAPPmzWPMmDE8+OCDAJSVlfkTKIBBgwbx97//nbVr1zJq1Ch+85vfsGTJEi03ICJJrTMLXAYymUwsHDQIgMV791IayZl0virTtddCZmZELql+JvGJq+G5iRMnYhhGq5+3tNr3xIkT+fzzz8MYlYhIfOnoo1Ra8q3MTP5fRgb/rKxkUXEx/3PyyaEKr3WHD8NLL3m3w7wCeCAtNyA+cVVpEhGRrjs2PNe5ShMc620CeLqsjD1OZyhCa9uKFeB0wsiRMG5c+K/XREmT+ChpEhFJMr7hufr6Utzuzic7EzMzOTcjg3rDYFG4e5vaaQAPF0+Dh7r/1AFKmkRJk0hzeXnehVq0rIAkMKs1C4ulBwBOZ1GnzxNYbVpSVsbucFab3n8ftm2DtDSYNi181zlO3Vd1GA0Glu4W7AM0szrZKWkSCZSX513ZTkmTJDCTydTlZnCfiT17MjEzk3rD4JfhrDb5qkzXXw8ZGeG7znH8TeCnpnVo9XRJTEqaRESSUGefQdcSX7Xpz2VlFIej2nTwILzyinc7gg3goH4maU5Jk4hIEurqWk2Bzs3M5FuZmTQYBr8sLu7y+U7wzDPgcsGYMXDmmaE/fxv0zDkJpKRJRCQJhWp4zuehpmrT0vLy0FabDAMWL/ZuR7AB3Kdmq9ZokmOUNImIJKFQDs8B/L/MTC7IzKTRMPhFKKtNGzbA9u3QvTvccEPozhsET33AzLlTVWkSJU0iIknJ4fAOzzmdX7e5aHBH+FYJX1ZeTlFdXUjO6W8AnzYNevQIzTmDVPdVHUajgaWHBXu+Zs6JkiYRkaTkcAwAzHg8ddTXl4fknOdkZHBhz56hqzbt2wevvurdjnADOGjmnJxISZOISBIym23Y7flA6Pqa4NhMuuXl5Xzd1WrT8uXQ0ABnneVtAo8wzZyT4ylpEhFJUqGcQeczPiODyT174gZ+3pVqk8fTvAE8CpQ0yfGUNImIJKlQN4P7+GbSrSgvZ2dnq03vvAM7d0J6Olx3XeiC6wAtNyDHU9IkIpKkji07ELpKE8DZGRlM6dWra9UmXwP4jTdCt8gnLR6Xh9qvvEmTlhsQHyVNIiJJ6tjwXGgrTXCst+l/y8vZUVvbsYPLy2H1au92lIbmav9TC26wpFuw99PMOfFS0iQikqRCvcBloG+kp3NJU7XpZx2tNi1bBo2NcPbZMHJkyGMLRmA/k2bOiY+SJhGRJOWrNNXXl+N214T8/L7epmcrKvhPsNUmjweeftq7HaUqE6ifSVqmpElEJElZrT1JSckEoK6uKOTnPys9nW/37o2HDlSb1q6FoiLIyIBrrgl5TMHyr9GkfiYJoKRJRCSJhXOIDo5Vm1ZWVLA9mGqTrwF8+nRIi17CouUGpCVKmkREklg41moKNLZHD77jqzbt2tX2znv3wl//6t2O4tCc2+mmbkfTM+eUNEkAJU0iIkks3JUmOFZten7fPr6saaN3aulScLvhnHNgxIiwxdOeuu114IGUzBRsebaoxSGxR0mTiEgSC9cCl4HO6NGDy5uqTT9trbfJ7Y6JBnBo3s+kmXMSSEmTiEgSC/fwnI+v2vTCvn1sbana9OabUFICPXvCd78b1ljao34maY2SJhGRJHZseK4Iw/CE7Tqje/TgiqwsDOCnLfU2+RrAZ8yA1NSwxREMJU3SGiVNIiJJzG7Px2RKwTDqcbn2hvVaC5qqTS/t38+WwGrTnj2wZo13O8pDcwC1W7VGk7RMSZOISBIzm1Ow2wuA0D+D7nijunfnypaqTUuWeBe1PO88GD48rDG0x+10U7fTO3Mu7VSt0STNKWkSEUlykWgG9/FVm17ev5/N1dXex6UsWeL9MBaqTF/WemfO9UzBlquZc9KckiYRkSQXiWUHfEZ27853+/TBABYWF8Prr0NpKWRlwZVXhv367Ql8fIpmzsnxlDSJiCS5SM2g81lQUIAJeGX/fv79l79435w5E+z2iFy/LXp8irRFSZOISJKL5PAcwGndu3N1nz4ALBzsvTZz5kTk2u3RzDlpi5ImEZEk53B4K03hbgQP9ODAgZgMg7+cey7/d/31MHRoxK7dFiVN0hYlTSIiSS41dRAADQ0HaGysisg1R9hsXPPhhwAsnD49Itdsj7vWjfNrJ6CkSVqmpElEJMmlpGSQktIb8C5yGRFr1vDgU09h8nhY5XBQePRoZK7bhtova8GAlN4pWLOt0Q5HYpCSJhERiXgzOE89xanFxVxXXg7AQy2tEh5hgUNzmjknLVHSJCIikW0GLyqCt94C4MEzzsAMvHbwIJ9FudqkfiZpj5ImERGJ6FpNPP00GAZceCHDhw/n+uxsIPrVpsA1mkRaEndJ0xNPPMHAgQNxOByMGzeOjz/+uNV9ly9fjslkavZyOBwRjFZEJD5EbHiuoQGWLvVuN60A/pOBAzEDfzt4kE1RrDZpjSZpT1wlTS+++CLz5s1jwYIFfPbZZ4waNYrJkyezb9++Vo9JT0+nrKzM/youLo5gxCIi8SFilabXXoOKCsjNhcsuA2BYWho35OQA0as2uWvcOIs0c07aFldJ029/+1tmz57NzTffzKmnnsqTTz5JWloaS33/1dICk8lEbm6u/5XT9MUUEZFjfD1NTucuDMMdvgs99ZT3z1tuAeuxGWo/KSjADKw5eJBPqiKz7EGgmm3eKpO1jxVbHz1zTloWN0lTfX09mzZtYtKkSf73zGYzkyZNYuPGja0eV11dTUFBAfn5+Vx++eVs2bKlzeu4XC6qqqqavUREEp3d3g+TyYZhNOJ07g7PRXbsgLffBpMJZs9u9tHJaWncGMVqk/qZJBhxkzQdOHAAt9t9QqUoJyeH8qYpq8cbNmwYS5cu5bXXXuPZZ5/F4/EwYcIE9uzZ0+p1Fi1aREZGhv+Vn58f0vsQEYlFJpMFh2MgEMYhusWLvX9OmQIDB57w8U8KCrAArx86xEcR/g9W9TNJMOImaeqM8ePHM336dEaPHs15553HX/7yF/r06cNTvvJwC+bPn09lZaX/tXt3mP6LS0QkxoR12QGXC5Yt8243NYAf76S0NG7KzQVgYYSrTTVbtdyAtC9ukqasrCwsFgsVFRXN3q+oqCC36UvWHqvVypgxY9ixY0er+9jtdtLT05u9RESSQVifQbdqFRw4AP36waWXtrrbj5uqTf84dIgPKytDH0cr/MNzpyppktbFTdJks9kYO3Ys69at87/n8XhYt24d48ePD+ocbrebL774gry8vHCFKSISt8JaafJV+GfNgpSUVncbkprK9Kb/EI5Ub1NjdSPOXd6Zcxqek7bETdIEMG/ePJ5++mmeeeYZtm3bxty5c6mpqeHmm28GYPr06cyfP9+//09/+lPeeustvv76az777DNuvPFGiouLufXWW6N1CyIiMcu3VlPIe5q2b4f168FshiD+/f1xQQEpJhNvHj7MxghUm2q3eatM1mwrtizNnJPWtZ7ux6Brr72W/fv38+CDD1JeXs7o0aN54403/M3hJSUlmM3H8sDDhw8ze/ZsysvL6dmzJ2PHjuWDDz7g1FNPjdYtiIjELN9aTSFf4NLXAH7JJRDE5JrBqanMyMnhz+XlLNi1i7dGjQptPMfR41MkWCbDMIxoBxHLqqqqyMjIoLKyUv1NIpLQGhuref/9HgCcc84hrNaeXT+p0+ntYzp0CP72N/j2t4M6bFddHUM//phGw+D9MWM4JyOj67G0Yud9O9n96G763dmPoY8PDdt1JLLC8fs7robnREQkfFJSumO1eiv3IRuie/VVb8KUnw8XXxz0YQNTU7k5Qr1NWm5AgqWkSURE/ELeDO5rAL/1VrBYOnToDwcMIMVk4u3Dh3n/yJHQxNMCDc9JsJQ0iYiIX0ifQbd1K/zzn95kadasDh8+MDWVW5qqTQvCVG1qPNqIq8QFKGmS9ilpEhERP98MupA0g/sawL/9bW9fUyf8qKAAq8nEO0eO8F4Yqk21W70z52y5Nqy9rO3sLclOSZOIiPiFbHiurg6eeca73coK4MEY4HAwq2ltvXBUm9TPJB2hpElERPxCNjz38stw5AgUFMBFF3XpVD8cMACbycT6I0dYf/hw1+I6jvqZpCOUNImIiN+xBS5L8HgaOn8iXwP47NkdbgA/Xr7Dwa1N1aZQz6RT0iQdoaRJRET8bLZczGYH4MblKuncSTZvhg8+8D4u5ZZbQhLX/KZq04bKSt4NYbXJ/8w5JU0SBCVNIiLiZzKZcTgGAV3oa/JVmS6/HEL0rM/+DgezA3qbQrEuc2NlI6493plz6mmSYChpEhGRZro0g66mBlas8G53oQG8JfMLCrCbTPyzspJ3QjCTrmard2jO1teGNVMz56R9SppERKSZLjWDv/giVFXB4MFwwQUhjauf3c6cvn0BWFBU1OVqk/qZpKOUNImISDPHKk2dSJp8Q3Nz5oA59L9iHhgwAIfZzL+qqni7i71N6meSjlLSJCIizRyrNHVweK6wED7+GKxWuPnm0AcG9LXbuS1gJl1Xqk2+4Tn1M0mwlDSJiEgzgQtcdigp8VWZrrgCsrPDEJnXD5qqTR9UVbG2C9Um//Dcqao0SXCUNImISDO+2XNudxUNDQeDO6i6Gp57zrsd4gbw4+XZ7dzu623qZLWp4UgD9aX1AKSdqkqTBEdJk4iINGOxpGKzeZOSoJvBn38ejh6FoUPh/PPDGJ3XD/LzSTWb+bCqijcPHerw8f5nzvXTzDkJnpImERE5QYefQRfYAG4yhSmqY3LtduZ2odqkmXPSGUqaRETkBA6H73EqQTSDb9rkfdlsMHNmeAMLcP+AAaSazXx89Cj/6GC1SUmTdIaSJhEROUGHKk2+KtNVV0FWVhijai7HZuOOfv2Ajs+k03ID0hlKmkRE5ARBL3BZVQUrV3q3w9wA3pL78vNJM5v55OhRXu9AtclXadJyA9IRSppEROQEQT9KZeVK76NThg+Hc8+NQGTNZXei2tRwuIH6Mu/MOS03IB2hpElERE7gG55zufbg8bha3skwIt4A3pL78vPpZjbz6dGjrDnY/hIJviqTPd9OSnpKuMOTBKKkSURETmC1ZmM2dwMMnM7ilnf65BPvKuB2O8yYEcnwmuljs3FnB6pN6meSzlLSJCIiJzCZTAHN4K0M0fmqTNdcA716RSiyln0/P5/uFgufVVfz13aqTepnks5S0iQiIi1qsxn8yBHvgpYQlQbw42XZbHwvyGqTlhuQzlLSJCIiLTrWDN5C0vTss1BXByNGwIQJEY6sZfc2VZsKq6t57cCBVvdT0iSdpaRJRERa1OrwXGAD+G23Ra0B/Hi9rVb+O6Da5Gmh2tRwsIGGigZAz5yTjlPSJCIiLWp1eG7jRti8GVJT4aabohBZ6+7Nz6eHxcL/1dSwuoVqk3/mXIGdlO6aOScdo6RJRERaFDg816xHyFdluvZayMyMfGBt6GW1clf//kDL1SYNzUlXKGkSEZEWORwFgAmPp4aGhn3eNw8fhpde8m7HQAN4S+b170+6xcIXNTX8Zf/+Zp8paZKuUNIkIiItMpvt2O3eqo2/GXzFCnA6YeRIGDcuitG1rqfVyt1N1aaFxcXNqk21W7VGk3SekiYREWlVs8epxGgDeEvu7t+fDIuFzTU1vBpQbfKv0aQmcOkEJU0iItKqZs3g778P27ZBWhpMmxblyNrWrNrU1NtUf6Cehn1NM+dOUdIkHaekSUREWnVs2YGvj1WZrr8eMjKiGFVwfNWmLbW1vLx/v//xKY6BDs2ck07pUNL0f//3f/z85z/nj3/8IweOm8pZVVXFLbfcEtLgREQkuhwO7/Cc8+h2eOUV75sx2gB+vEyrlXn5+YC32lS1pRrQ41Ok84JOmt566y2+8Y1v8MILL/Dwww8zfPhw3n33Xf/ndXV1PPPMM2EJMtATTzzBwIEDcTgcjBs3jo8//rjN/V9++WWGDx+Ow+Hg9NNP5/XXXw97jCIiicJfaTqyFVwuGDMGzjwzylEF767+/clMSWFbbS2vVHn/Y19N4NJZQSdNDz30EN///vfZvHkzu3bt4v777+eyyy7jjTfeCGd8zbz44ovMmzePBQsW8NlnnzFq1CgmT57Mvn37Wtz/gw8+4Prrr2fWrFl8/vnnTJ06lalTp7J58+aIxSwiEs98PU31tircNmK+Afx4GSkp3NvU2/T4kCrcZiVN0nkmo62nGgbIyMjgs88+Y8iQIf73Vq5cyZw5c3jhhRc466yz6Nu3L263O2zBjhs3jrPOOov/+Z//AcDj8ZCfn8/3vvc9HnjggRP2v/baa6mpqWHNmjX+984++2xGjx7Nk08+GdQ1q6qqyMjIoLKykvT09NDciIhInDAMg/c39MBNDWf9VxrdPiqHHj2iHVaHVDU2MvDDDznc2MiPfg4/eHgsPcbG1z1Ix4Xj93fQlSa73c6RI0eavXfDDTewZMkSrr32WlatWhWSgFpTX1/Ppk2bmDRpkv89s9nMpEmT2LhxY4vHbNy4sdn+AJMnT251fwCXy0VVVVWzl4hIsjKZTKQesAJQd+3/i7uECSA9JYW7e/YFYMV0sA9PjXJEEq+CTppGjx7drIfJ57rrrmPJkiX893//d0gDO96BAwdwu93k5OQ0ez8nJ4fy8vIWjykvL+/Q/gCLFi0iIyPD/8pvaiIUEUlK+/bh2FYJgHPyyCgH03kz9qWTXgm7B8BLR098Jp1IMIJOmubOnUtpaWmLn11//fUsX76cc889N2SBRcv8+fOprKz0v3bv3h3tkEREomf5clJLvV0cdb1dUQ6m8yxbnFzT9PSXnxYX0+jxRDcgiUtBJ01XXHEFjz32WIvVJvAO1V133XUhC+x4WVlZWCwWKioqmr1fUVFBbm5ui8fk5uZ2aH/wDkOmp6c3e4mIJCWPBxYvxrHX+1en8+voxtMFtVtquWIV9Kw381VdHc+3MoFIpC0dXtxyypQp3HfffTQ0NPjfO3DgAN/5zndabMYOFZvNxtixY1m3bp3/PY/Hw7p16xg/fnyLx4wfP77Z/gBr165tdX8REQnwzjuwcyepR7zrGvmfPxeHarbUkFYHc+t6A6o2Sed0OGl69913WbVqFWeddRZbt27l73//O6eddhqVlZUUFhaGIcRj5s2bx9NPP80zzzzDtm3bmDt3LjU1Ndx8880ATJ8+nfnz5/v3v+uuu3jjjTf4zW9+w5dffslDDz3Ep59+yp133hnWOEVEEkLTCuCpZ18BeCtNhhF/iYZhGP5nzt2Z348sq5UddXU8p2qTdFCHk6YJEyZQWFjIaaedxhlnnMEVV1zBPffcw4YNGygoKAhHjH7XXnstjz76KA8++CCjR4+msLCQN954w9/sXVJSQllZWbNYV65cyeLFixk1ahSvvPIKq1ev5rTTTgtrnCIica+8HFavBsA+7R7AgsfjpL6+9Yk0saq+op7GQ41ghuxTenBf0wSfn+3apWqTdEinHr7zn//8h08//ZT+/fuzd+9etm/fTm1tLd26hX/BsDvvvLPVStH69etPeO/qq6/m6quvDnNUIiIJZtkyaGyEs8/GPGosjg8H4HQWUVf3NXZ732hH1yG+Z86lDk7Fkmrhjn79eHT3bnY6nfxvRQU35+VFOUKJFx2uNP3qV79i/PjxXHjhhWzevJmPP/6Yzz//nJEjR7a5/pGIiMQJjweeftq73fScOd/K4E7nzmhF1Wm+oTnfM+e6WSzc76s2FRfToGqTBKnDSdPvf/97Vq9ezeOPP47D4eC0007j448/5sorr2TixIlhCFFERCJq7VooKoKMDLjmGiDgGXRx2Axes9WbNAU+PmVuv35kW60UNVWbRILR4aTpiy++4OKLL272ntVq5de//jVvvfVWyAITEZEoaWoAZ/p0SPNWZ1JTvY/QqquLv0qTb3iu26nHkqZuFgv3DxgAwM9VbZIgdThpysrKavWz8847r0vBiIhIlO3dC3/9q3e7aWgOAofn4qvSFDhzzjc85zO3b19ymqpNz7TxpAgRnw4nTSIiksCWLgW3G845B0aM8L8dr8Nz9eX1NB72zpxLG948aUqzWPhBQLWpXtUmaYeSJhER8XK7T2gA93E4vMNzDQ0VNDZWRzqyTvNVmVKHpGJxWE74/Pa+fcm12Sh2uViuapO0Q0mTiIh4vfkmlJRAz57w3e82+8hqzSQlpScATmdRNKLrFH8/04iWl8RJtVh4oKna9AtVm6QdSppERMTL1wA+Ywakpp7wcTz2NbXWzxRoTl4eeTYbJS4Xy1RtkjYoaRIREdizB9as8W4fNzTnE48z6HxJU2uVJjix2uRStUlaoaRJRERgyRLvopbnnQfDh7e4S7w1gwfOnGsraQJvtamvzcZul4ulAY/jEgmkpElEJNk1NnqTJmi1ygTHmsHjZXiufm897ko3WCBtWOvDcwAOi4X5TdWmX5aUqNokLVLSJCKS7F5/HUpLISsLrryy1d2OVZriY3jOP3PupFTM9vZ/3d2al0c/m409LhdLVG2SFihpEhFJdr4G8JkzwW5vdbdjjeC7MAx3BALrmmCH5nwcFgs/LCgA4JfFxTjdsX+PEllKmkREkllxMfzjH97tOXPa3NXhyMdkSsEw6nG59kYguK7paNIEMCsvj/52O3vr61VtkhMoaRIRSWZLloBhwLe+BUOHtrmryWTB4RgIxMcQXXtrNLXEbjbzw6bepkUlJao2STNKmkREklVDA/z5z97tNhrAA8XLWk2GYVCztf01mlpyS14e+U3VpsWqNkkAJU0iIslqzRooK4PsbJg6NahDjq3VFNtJk2uPC3eVG1OKibSTO5Y02c1mftTU27SopIQ6VZukiZImEZFk5WsAv/lmsNmCOuRYpSm2h+f8M+eGpmK2dfxX3c25uRTY7ZTX1/PU3tjv35LIUNIkIpKMiorgrbe827NnB31YvCxw2Zl+pkC2gGrTr0pKqFW1SVDSJCKSnJ5+2tsAfuGFMGRI0IfFy6NUOtvPFGhGbi4DHQ4qGhpUbRJASZOISPJpaIClS73bQTaA+zgcgwBobDxIY2NlqCMLGf9yA6d2rtIETdWmppl0D6vaJChpEhFJPq+9BhUVkJsLl13WoUNTUtKxWrMAqKsrCkd0XWYYBrVbuzY85zMjN5dBTdWmP6nalPSUNImIJBtfA/gtt4DV2uHDjz2DLjaH6Fy7XbiPemfOpQ5N7dK5rGYzP27qbXq4pIQaVZuSmpImEZFksmMHvP02mEwdagAPFOvN4P6Zcyd3bubc8W7KyWGww8H+hgb+WFra5fNJ/FLSJCKSTBYv9v45ZQoMHNipU/iawWN1gcvOPD6lLVazmZ80VZse2b2b6sbGkJxX4o+SJhGRZOFywbJl3u0ONoAH8q3VFKsz6Lq63EBLbszJYYjDwYGGBv6o3qakpaRJRCRZrFoFBw5Av35w6aWdPk28DM91ZbmB46WYzfykqTL3a1WbkpaSJhGRZOFrAJ81C1JSOn0aXyO4y1WMxxNbyYPhOfbMuVBWmgCmZWczNDWVAw0N/I96m5KSkiYRkWSwfTusXw9mM9x6a5dOZbf3xWSyYRiNuFy7QxNfiDhLnHhqPJisJlJP6trMueOlBPQ2/Xr3bo6q2pR0lDSJiCQDXwP4JZdAfn6XTmUymf2LXMZaM7ivnyltWBpma+h/xV2fnc3JqakcamzkcVWbko6SJhGRROd0wvLl3u0uNIAHOvY4ldhKmsLRzxQoxWzmwabepkd376ZK1aakoqRJRCTRvfoqHDrkrTBdfHFITnmsGTy2ZtCFermBllyXnc2w1FQOq9qUdJQ0iYgkOl8D+K23gsUSklP6lh2IteG5SCRNFpPJX236ze7dVKralDSUNImIJLKtW+Gf//QmS7Nmhey0x4bnYqfSZHgMareFfo2mllybnc0paWkcbmzkD3v2hPVaEjuUNImIJDJfA/i3v+1dnylEYrHS5NzlxFPrwWQz4RjiCOu1LCYTDzbNpPvtnj0caWgI6/UkNsRN0nTo0CGmTZtGeno6mZmZzJo1i+rq6jaPmThxIiaTqdnr9ttvj1DEIiJRVlcHzzzj3Q5RA7hPaqp39lxj4xEaGg6H9Nyd5W8CH56GOSX8v96uzs7m1LQ0jjQ28nv1NiWFuEmapk2bxpYtW1i7di1r1qzhvffeY86cOe0eN3v2bMrKyvyvRx55JALRiojEgJdfhiNHoKAALroopKe2WLphs+UCsTNEF4l+pkAWk4kFTb1Nj+3erWpTEoiLpGnbtm288cYbLFmyhHHjxvHNb36Txx9/nBdeeIG97TwDKC0tjdzcXP8rPT09QlGLiESZrwF89uyQNYAHirUhutqtkelnCvTdPn0YkZZGpdvN79TblPDiImnauHEjmZmZnHnmmf73Jk2ahNls5qOPPmrz2Oeee46srCxOO+005s+fT21tbZv7u1wuqqqqmr1EROLO5s3wwQfex6XccktYLhFrazX5h+dODc8aTS0xB1ab9uzhsKpNCS0ukqby8nKys7ObvZeSkkKvXr0oLy9v9bgbbriBZ599lnfffZf58+fzv//7v9x4441tXmvRokVkZGT4X/ldXDlXRCQqfFWmyy+HvLywXOJYpSn6w3ORnDl3vKv69OH0bt2ocrt5TNWmhBbVpOmBBx44oVH7+NeXX37Z6fPPmTOHyZMnc/rppzNt2jRWrFjBqlWr2Lmz9S/4/Pnzqays9L92746t5yqJiLSrpgZWrPBuh7gBPNCxBS6jX2lyFjnx1Hkw2U2kDgntM+faE1ht+t2ePRxStSlhdf4x1yFw7733MnPmzDb3GTx4MLm5uezbt6/Z+42NjRw6dIjc3Nygrzdu3DgAduzYwZAhQ1rcx263Y7fbgz6niEjMefFFqKqCwYPhggvCdhnf8Fws9DQFzpwzWUwRv/4VWVmM7NaNf9fU8Nvdu/n54MERj0HCL6pJU58+fejTp0+7+40fP54jR46wadMmxo4dC8A777yDx+PxJ0LBKCwsBCAvTKVqEZGY4BuamzMHzOEbUDg2PFeCx1OP2WwL27XaE+mZc8czm0w8NHAgV27Zwh9KS7knP5/eVmtUYpHwiYueplNOOYUpU6Ywe/ZsPv74Y/71r39x5513ct1119G3b18ASktLGT58OB9//DEAO3fu5Gc/+xmbNm1i165d/PWvf2X69Omce+65jBw5Mpq3IyISPoWF8PHHYLXCzTeH9VI2Wy5mcyrgweksCeu12hPtpAng8qwsRnXrxlG3m9+qtSMhxUXSBN5ZcMOHD+eCCy7gkksu4Zvf/CaLfSvdAg0NDWzfvt0/O85ms/H2229z0UUXMXz4cO69916uuuoq/va3v0XrFkREws9XZbriCjhuAk2omUymmFl2oHZLdJrAA/mqTQB/KC3lQH191GKR8Ijq8FxH9OrVi5UrV7b6+cCBAzEMw//3/Px8NmzYEInQRERiQ3U1PPecdzuMDeCBUlMHU1u7JaoLXBpug9ovvUlT2ojILTfQksuzshjTvTufV1fzmz17WKTepoQSN5UmERFpx/PPw9GjMHQonH9+RC4ZC5Wmuq/r8Dg9mB1mUgdFdubc8UwB1abH9+xhv6pNCUVJk4hIoghsADdFZgZZLCxw6Z85d0p0Zs4d7zu9ezO2e3dqPB4eVW9TQlHSJCKSCDZt8r5sNmhnKZdQOrZWU/SG52KhnylQYLXpf0pLVW1KIEqaREQSga/KdNVVkJUVscsGDs8F9pVGkr/SFOV+pkCX9u7NmT16UOvx8GtVmxKGkiYRkXhXVQW+iTIRagD3cTgGAeB2H6Wh4UBEr+0TC8sNHC+w2vREaSn7VG1KCEqaRETi3cqV3kenDB8O554b0UtbLA5stn5AdJrBPY0e/8y5WEqaAC7p1YtvNFWbHimJ7jpWEhpKmkRE4plhRKUBPFA0m8GdO50Y9QbmNDOOgY6IX78tgdWmP+7dS7nLFd2ApMuUNImIxLNPPvGuAm63w4wZUQkhms3gzWbOmaM/c+54U3r1YlyPHtR5PDyi3qa4p6RJRCSe+apM11wDvXpFJYRortVUszX2+pkCmUwmFg7y9n39SdWmuKekSUQkXh054l3QEiLeAB4omsNz/uUGTo3NpAngop49OTs9HafHw8OqNsU1JU0iIvHq2Wehrg5GjIAJE6IWxrFKUxSH52JouYHjmUwmFjb1Nj25dy9lqjbFLSVNIiLxKLAB/LbbotIA7uPraXK5SnG7nRG7rqfRQ+322Jw5d7wLe/ZkQlO16VeaSRe3lDSJiMSjjRth82ZITYWbbopqKFZrHyyW7oCBy1UcsevW7ag7NnOuILZmzh0vsNr01N69lKraFJeUNImIxCNflenaayEzM6qhmEwm/xBdJGfQBfYzxeLMueNd0LMn38zIwGUYqjbFKSVNIiLx5vBheOkl73YUG8ADHVt2IHLN4PHQzxQosNq0WNWmuKSkSUQk3qxYAU4njBwJ48ZFOxoAHA7vDLpILjsQi49Pac/5mZn8v4wM6g2DRcWRG8qU0FDSJCIST2KoATxQNBa4jMekKbDa9HRZGbudkWucl65T0iQiEk/efx+2bYO0NJg2LdrR+EV6gUtPg4e6/9QB8ZU0AZzfsyfn+apN6m2KK0qaRETiia/KdP31kJER3VgCBC5waRhG2K9X91UdRoOBpbsF+wB72K8Xar5VwpeUlVGialPcUNIkIhIvDh6EV17xbsdIA7iPw1EAmPF4aqmvrwj79fxN4KemYYqRIcqOOC8zk/MzM2kwDH6p3qa4oaRJRCRePPMMuFwwZgyceWa0o2nGbLZht+cDkRmii8d+puM91NTbtLS8nGJVm+KCkiYRkXhgGLB4sXc7hhrAA0WyGdy/RlMcJ03nZmbyLVWb4oqSJhGReLBhA2zfDt27ww03RDuaFkWyGTze1mhqzcKAatOuurroBiPtUtIkIhIPfA3gN9wAPXpEN5ZWBDaDh5On3kPdV/E5c+5438zMZFLPnjQaBr/QTLqYp6RJRCTW7dsHr77q3b799ujG0oZIDc/V/qcWo9HAkm7B3j/+Zs4dz1dtWl5eTpGqTTFNSZOISKxbvhwaGuCss7xN4DEqUsNzzZ45F4O9XR01ISODi5qqTT9Xb1NMU9IkIhLLPJ7mDeAxzDc8V19fhttdG7br1GxNjH6mQL6ZdM+Ul/O1qk0xS0mTiEgse+cd2LkT0tPhuuuiHU2bUlJ6YrF4F9x0OovCdh3/cgOnxnc/U6DxGRlM7tkTN6jaFMOUNImIxDJfA/iNN0K32E4STCZTQF9T+IboEmG5gZb4VglfUV7OjtrwVeqk85Q0iYjEqvJyWL3aux3jQ3M+viG6cPU1eVwear/yJhSJNDwHMC49nYt79VK1KYYpaRIRiVXLlkFjI5x9NowcGe1oguJrBg/XDLra/9SCG+/MuX7xP3PueL7epv+tqOArVZtijpImkUBlZfDQQ94/RaLJ44Gnn/Zux0mVCQj78Fzg41M6PHMuDr7f30hP59JevfAAP1O1KeYoaRIJVFYGCxfG9D+qkiTWroWiIsjIgGuuiXY0QXM4wjs816V+pjj5fvuqTc9VVPAfVZtiipImEZFY5GsAnz4d0uKndyew0mQYnpCfP1Een9KWM9PT+Xbv3qo2xSAlTSIisWbvXvjrX73bcTQ0B2C3DwAsGIaL+vrQV3QCh+cSma/atLKigu2qNsWMuEmafvGLXzBhwgTS0tLIzMwM6hjDMHjwwQfJy8sjNTWVSZMm8dVXX4U3UBGRrlq6FNxuOOccGDEi2tF0iNmcgsNRAIS+GdztdFO3IzGeOdeesT16cFlTtemnu3ZFOxxpEjdJU319PVdffTVz584N+phHHnmEP/zhDzz55JN89NFHdOvWjcmTJ+N0OsMYqYhIF7jdcdkAHihczeB12+vAAymZKdjybCE9dyzyVZue37ePbTU10Q1GgDhKmhYuXMg999zD6aefHtT+hmHwu9/9jh//+MdcfvnljBw5khUrVrB3715W+9Y9ERGJNW++CSUl0LMnfPe70Y6mU8LVDB7Yz5QIz5xrz5gePZialYUB/FS9TTEhJdoBhEtRURHl5eVMmjTJ/15GRgbjxo1j48aNXNfK4whcLhcul8v/96qqqrDHKhFWVtb67JnPPmv+Z0vy8rwvkXDwNYDPmAGpqdGNpZOOVZpCOzwXVD9Tgn2/FxQUsPrAAV7ct4+fFBRwaoyvCp/oEjZpKi8vByAnJ6fZ+zk5Of7PWrJo0SIWLlwY1tgkyp56yjvtuC2zZ7f+2YIF3rVeREJtzx5Ys8a7HadDc3BsgctwVZraTJoS7Ps9ukcPrsjKYtWBA/x01y5eiLMet0QT1aTpgQce4OGHH25zn23btjF8+PAIRQTz589n3rx5/r9XVVWRn58fsetLBNx2G1x2WcufffaZ9x/Up5+GM85oeZ8Y+q9QSTBLlngXtTzvPIjgv3uh5nuUSqh7moJaoykBv98PDRzIqgMHeGn/fn5SU8MIVZuiJqpJ07333svMmTPb3Gfw4MGdOndubi4AFRUV5AV8CSoqKhg9enSrx9ntduz2xFuaXwIEU34/44zW/1EVCYfGRm/SBHFdZYJjw3MNDftobDxKSkqPLp/TXeembqd35lybazQl4Pd7ZPfuXJWVxasHDrBw1y5eUrUpaqKaNPXp04c+ffqE5dyDBg0iNzeXdevW+ZOkqqoqPvroow7NwBMRiYjXX4fSUsjKgiuvjHY0XZKSkkFKSi8aGw/hdBbRvXvXn5tX+2UtGJDSKwVbTuLPnDvegoEDefXAAV7ev58vqqs5vXv3aIeUlOJm9lxJSQmFhYWUlJTgdrspLCyksLCQ6upq/z7Dhw9n1apVAJhMJu6++25+/vOf89e//pUvvviC6dOn07dvX6ZOnRqluxARaYWvAXzmTEiAaneoh+hqtx4bmkuGmXPHO717d65uKjJoJl30xE0j+IMPPsgzzzzj//uYMWMAePfdd5k4cSIA27dvp7Ky0r/P/fffT01NDXPmzOHIkSN885vf5I033sDhcEQ0dhGRNhUXwz/+4d2eMye6sYSIwzGYo0c/wekMzQw6/3IDpybu41Pa82BBAa/s388r+/fz7+pqRqraFHFxU2lavnw5hmGc8PIlTOBdmymwR8pkMvHTn/6U8vJynE4nb7/9NieffHLkgxcRacuSJWAY8K1vwdCh0Y4mJEK9wGWyPD6lLacFVJsWapXwqIibpElEJCE1NMCf/+zdjvMG8EC+4blQLTugpMlrwcCBmIC/HDhA4dGj0Q4n6ShpEgmUl+ddpyUGpx1LglqzxrsYY3Y2JFC/pW+tplAscOmudeP82vv4qy4lTQnw/T61Wzeuzc4GYKF6myJOSZNIoLw878J2cfyPqsQZXwP4zTeDLXFmhR2rNO3CMNxdOpd/5lzvFKzZ1s6fKEG+3w8WFGACVh84wOeqNkWUkiYRkWgpKoK33vJut7VKdRyy2/thMlkxjAZcrtIunStwaC4ZZ84d75Ru3bjeV21Sb1NEKWkSEYmWp5/2NoBfeCEMGRLtaELKZLLgcAwEuj5Ep36mE/2koAAz8NrBg3ymalPEKGkSEYmGhgZYutS7nUAN4IFC1Qwe1ONTkszwgGrTQ6o2RYySJhGRaHjtNaiogNzc1p+VFudC1QzuX6OprcenJKEHBw7EDPzt4EE+raqKdjhJQUmTiEg0+BrAb7kFrF1obo5hoViryV3jxlkUgplzCejktDSm5eQAqjZFipImEZFI27ED3n4bTKaEawAP5HB0fXiuZpu3ymTtY8XWJ3FmF4bKTwoKsAB/P3SIj1VtCjslTSIikbZ4sffPKVNg4MCohhJOxypNnR+eUz9T24ampXFjU7VJM+nCT0mTiEgkuVywbJl3O0EbwH0cjkEANDYeoqHhSKfOoX6m9v24qdr0+qFDfKRqU1gpaRIRiaRVq+DAAejXDy69NNrRhFVKSg+sVu8ML6ezqFPn0HID7TspLY2bcnMB9TaFm5ImEZFI8jWAz5oFKSnRjSUCujpEp6QpOL5q0xuHDrGxsjLa4SQsJU0iIpGyfTusXw9mM9x6a7SjiQjfsgOdaQZvrG7EVewClDS1Z0hqKjNUbQo7JU0iIpHiawC/5BLIz49uLBHiW+CyM8sO1G71NoFbc6xYeyfmsgyh9OOCAlJMJt46fJgPVG0KCyVNIiKR4HTC8uXe7QRvAA90rNLU8eG5mq0amuuIQampzFS1KayUNImIRMKrr8KhQ94K08UXRzuaiOlSpcm33MCpSpqC9aMBA0gxmVh7+DD/UrUp5JQ0iYhEgq8B/NZbwWKJbiwR5GsEdzqL8XgaO3SslhvouIGpqdzcVG1aUNS5GYvSOiVNIiLhtnUr/POf3mRp1qxoRxNRNlseJpMdcONylXToWM2c65wfFRRgNZlYd+QI/zxyJNrhJBQlTSIi4eZrAP/2t73rMyURk8ncqWfQNR5txFWimXOdUeBwcIuv2qTeppBS0iQiEk51dfDMM97tJGoAD9SZZQd8M+dsuTasvTRzrqN+2FRtevfIETao2hQySppERMLp5ZfhyBEoKICLLop2NFHRmQUu1c/UNQMcDm7NywM0ky6UlDSJiISTrwF89uykagAP5JtB15FKk/qZum7+gAHYTCbWHznC+sOHox1OQlDSJCISLps3wwcfeB+Xcsst0Y4manzDc52pNClp6rz8gGrTgl27MAwjyhHFPyVNIiLh4qsyXX45NP3ySkaBw3PB/uL2r9GkpKlLfNWm9yoreVe9TV2mpElEJBxqamDFCu92kjaA+zgcgwBwu6tobGx/mKixshHXHu/MOfU0dU1/h4M5ffsCqjaFgpImEZFwePFFqKqCwYPhgguiHU1UWSxp2GzeSlswQ3S+x6fY+tqwZmrmXFfNHzAAu8nE+5WVrFNvU5coaRIRCQff0NycOWDWP7UdWXZA/Uyh1ddu57amatNDqjZ1ib7JIiKhVlgIH38MVivcfHO0o4kJHXkGnfqZQu8HAwbgMJv5V1UVb6va1GlKmkREQs1XZbriCsjOjm4sMaIjazVpjabQ62u3c5tm0nWZkiYRkVCqrobnnvNuJ3kDeCCHI/i1mjQ8Fx6+atPGqireUrWpU5Q0iYiE0vPPw9GjMHQonH9+tKOJGcE+f67hSAP1e+sB6HaqkqZQyrPbmeubSVdUpGpTJyhpEhEJpcAGcJMpurHEEF8juMu1G4+nvtX9fP1M9v52UjJSIhJbMvnBgAGkms18dPQobxw6FO1w4o6SJhGRUNm0yfuy2WDmzGhHE1NsthzM5jTAg9NZ3Op+vuUG1M8UHjk2G/+lmXSdpqRJRCRUfFWmq66CrKzoxhJjTCaTf4iurb4mfz+ThubC5r6matPHR4/yD1WbOiRukqZf/OIXTJgwgbS0NDIzM4M6ZubMmZhMpmavKVOmhDdQEUlOVVWwcqV3Ww3gLQrmGXRabiD8cmw27ujXD9BMuo6Km6Spvr6eq6++mrlz53bouClTplBWVuZ/Pf/882GKUESS2sqV3kenDB8O554b7WhiUjBrNWm5gci4Lz+fNLOZT48e5e8HD0Y7nLgRN112CxcuBGD58uUdOs5ut5ObmxuGiEREmhiGGsCDcGxV8JYrTQ2HG6gv08y5SMi22bizXz8e2b2bh3bt4tLevTHp/7ftiptKU2etX7+e7Oxshg0bxty5czmojFpEQu2TT7yrgNvtMGNGtKOJWe0tO+CrMtnz7aSkx81/08et+/Lz6WY2s6m6mr/pd2NQEjppmjJlCitWrGDdunU8/PDDbNiwgYsvvhi3293qMS6Xi6qqqmYvEZE2+apM11wDvXpFN5YY5hueczq/brGPRv1MkZVls/G9/v0BzaQLVlSTpgceeOCERu3jX19++WWnz3/ddddx2WWXcfrppzN16lTWrFnDJ598wvr161s9ZtGiRWRkZPhf+fn5nb6+iCSBI0e8C1qCGsDbYbcXACbc7moaGvaf8Ln6mSLv3v796W6x8Hl1NX9VtaldUU2a7r33XrZt29bma/DgwSG73uDBg8nKymLHjh2t7jN//nwqKyv9r927d4fs+iKSgJ59FurqYMQImDAh2tHENIvFgd3unbXV0hCdHp8SeVk2G99rmkmnalP7ojpo3KdPH/r06ROx6+3Zs4eDBw+S1/TQwpbY7XbsdnvEYhKROBbYAH7bbWoAD4LDMQSXaw9O59dkZJzd7DMlTdFxb34+/1NaSmF1NasPHOCKCP5ejjdx09NUUlJCYWEhJSUluN1uCgsLKSwspLq62r/P8OHDWbVqFQDV1dXcd999fPjhh+zatYt169Zx+eWXc9JJJzF58uRo3YaIJJKNG2HzZkhNhZtuinY0ceFYM3jzGXQNBxtoqGgAIO1UDc9FUm+rlf8OqDZ5VG1qVdwkTQ8++CBjxoxhwYIFVFdXM2bMGMaMGcOnn37q32f79u1UVlYCYLFY+Pe//81ll13GySefzKxZsxg7diz//Oc/VUkSkdDwVZmuvRaCXHQ32QU2gwfyz5wrsJPSXTPnIm1efj49LBb+XVPD6gMHoh1OzIqb/2cuX7683TWaAsdiU1NTefPNN8MclYgkrcOH4aWXvNtqAA/asVXBW06aNDQXHb2sVu7q35+fFxfz0K5dTM3Kwqzh5hPETaVJRCSmrFgBTieMHAnjxkU7mrjR2vCckqbom9e/P+kWC1/U1PCX/SfObhQlTSIiHacG8E5zOLzDc/X1pbjdTv/7WqMp+npardzdtG7TwuJi9Ta1QEmTiEhHvf8+bNsGaWkwbVq0o4krVmtvLJYeADidu/zva42m2HBP//5kWCxsrqnhFVWbTqCkSUSko3xVpuuvh4yM6MYSZ0wm0wnPoKvfX0/Dfu/MuW6nqNIUTZlWK/c0Leq8cNcu3Ko2NaOkSUSkIw4ehFde8W6rAbxTfDPofM3gtVu9Q3OOQQ4s3SxRi0u87urXj8yUFLbW1qradBwlTSIiHfHMM+BywZgxcOaZ0Y4mLvmawX3LDviH5rQ+U0zItFq5x9fbpGpTM0qaRESCZRiweLF3Ww3gnXZs2QHv8JxmzsWeu/r3JzMlhW21tby0b1+0w4kZSppERIK1YQNs3w7du8MNN0Q7mrh1/PCckqbYk5GSwr1N1aafFher2tRESZOISLB8DeA33AA9ekQ3ljh2rBH8awzD0HIDMeq/+/enV0oKX9bW8oKqTYCSJhGR4OzbB6++6t2+/fboxhLnHI4BgBmPp46avSU0HGgAE6Sdop6mWJKeksK9TTPpfrprF40eT5Qjij4lTSIiwVi+HBoa4KyzvE3g0mlms60pcYIj/9kKNM2cS9PMuVjzvX796JWSwn/q6lRtQkmTiEj7PJ7mDeDSZb4huqrS7YCG5mJVj5QUvu+rNhUXJ321SUmTiEh73nkHdu6E9HS47rpoR5MQfM3gtUe8M+iUNMWuO/v1o3dKCl/V1bEyyatNSppERNrjawC/8Ubopl/uoeCrNLkaiwA9PiWW9UhJ4b4B3uHUnyV5tUlJk4hIW8rLYfVq77aG5kLGt8Blg6MYUKUp1t3Rty9ZVis76up4tqIi2uFEjZImEZG2LFsGjY1w9tkwcmS0o0kYvuE5+uwFM6QNV6UplnVPSeH+pt6mnxUX05Ck1SYlTSIirfF44OmnvduqMoWUb3iO3odwDDdhSdXMuVj3X/360cdq5WunM2mrTUqaRERas3YtFBVBRgZcc020o0koVmtPzI0ZANjPPhjlaCQY3SyWpK82KWkSEWmNrwF8+nRI0/BRqFkqvY/psJ5+IMqRSLDm9utHttVKkdPJiiSsNilpEhFpyd698Ne/erc1NBcWxt48ACyDku+Xb7zqZrHwg6aZdD8vLqY+yapNSppERFqydCm43XDOOTBiRLSjSTiGYeD+Kse7nV0a5WikI27v25ccq5VdTifPlJdHO5yIUtIkInI8t1sN4GFWX1aP8XUuAA2pJVGORjoizWLhgSStNilpEhE53ptvQkkJ9OwJ3/1utKNJSDVba6DMOzznqi+KcjTSUbf17UuuzUaJy8XyJKo2KWkSETmerwF8xgxITY1uLAmqdkst7O0LQF1dEYaRPNWKRJAaUG36RRJVm5Q0iYgE2rMH1qzxbmtoLmxqttTAvmzwpGAYLlyuvdEOSTpoTl4eeU3VpqVlZdEOJyKUNImIBFqyxLuo5XnnwfDh0Y4mYdVsqQGPBavHu+yA07kzyhFJR6VaLMz3VZtKSnAlQbVJSZOIiE9jozdpAlWZwsgwDG/SBKQ6vI9Tqav7OpohSSfNzsujn83GHpeLPydBtUlJk4iIz+uvQ2kpZGXBlVdGO5qEVb+3HnelGyzQrfdJADidSprikcNiYX5BAQC/LC7G6XZHOaLwUtIkIuLjawCfORPs9qiGksj8VaaTUknt5qs0aXguXt3aVG0qra/nzwk+k05Jk4gIQHEx/OMf3u05c6IbS4LzJU3dRnQjNVXDc/HObjbzwySpNilpEhEBby+TYcC3vgVDh0Y7moQWmDQ5HIMBDc/Fu1l5eeTb7eytr+fpBO5tUtIkItLQAH/+s3dbDeBhV7ulFvBVmrxJU0PDfhobj0YzLOkCu9nMD5tm0i0qKaEuQatNSppERNasgbIyyM6GqVOjHU1CMwzDuxo4kDYijZSUdKzWLEDVpnh3S14eA+x2yurrWZyg1SYlTSIivgbwm28Gmy26sSQ41x4X7io3phQTaSenAfiH6NTXFN9sZjM/aupt+lWCVpuUNIlIcisqgrfe8m7Pnh3dWJKAf+bc0FTMNu+vIN8QnWbQxb+ZubkU2O2U19fz1N7EW+VdSZOIJLenn/Y2gF94IQwZEu1oEl5gP5OPo2mBSw3Pxb/jq021CVZtioukadeuXcyaNYtBgwaRmprKkCFDWLBgAfX19W0e53Q6ueOOO+jduzfdu3fnqquuoqKiIkJRi0jMa2iApUu922oAjwhfpSltRJr/vWOVJiVNiWBmbi4DHQ4qGhp4MsGqTXGRNH355Zd4PB6eeuoptmzZwmOPPcaTTz7JD3/4wzaPu+eee/jb3/7Gyy+/zIYNG9i7dy9XapVfEfF57TWoqIDcXLjssmhHkxQClxvwObbsgIbnEoHVbObHTdWmh0tKqEmgalNKtAMIxpQpU5gyZYr/74MHD2b79u386U9/4tFHH23xmMrKSv785z+zcuVKvvWtbwGwbNkyTjnlFD788EPOPvvsiMQuIjHM1wB+yy1gtUY3liRgGAa1W08cnvMtcOl07sIw3JhMlqjEJ6EzPSeHXxYX87XTyZ9KS/l+03IE8S4ukqaWVFZW0qtXr1Y/37RpEw0NDUyaNMn/3vDhwxkwYAAbN25sNWlyuVy4XK5m1wGoqqoKUeQiEhN27oS33/ZuX3cd6Dseds7dTqqqqzBZTDTkNPj/XTWM7tTWWjGMBvbt20pqakGUI5VQuLdXL+746it+9eWXTOvRg26WyCbDx/7/ZYTsnHGZNO3YsYPHH3+81SoTQHl5OTabjczMzGbv5+TkUN7Gs3EWLVrEwoULT3g/Pz+/0/GKSIwbOTLaESQXN5DV2of6WSSag0DfaF7/4EEyMjJCcq6oJk0PPPAADz/8cJv7bNu2jeHDh/v/XlpaypQpU7j66quZHYbpwfPnz2fevHn+vx85coSCggJKSkpC9j96PKiqqiI/P5/du3eTnp4e7XAiRvet+04Gum/ddzKorKxkwIABbY5KdVRUk6Z7772XmTNntrnP4MGD/dt79+7l/PPPZ8KECSxevLjN43Jzc6mvr+fIkSPNqk0VFRXk5ua2epzdbsfewtPNMzIykur/bD7p6em67ySi+04uuu/kkqz3bTaHbs5bVJOmPn360KdPn6D2LS0t5fzzz2fs2LEsW7as3f8Rxo4di9VqZd26dVx11VUAbN++nZKSEsaPH9/l2EVERCS5xMWSA6WlpUycOJEBAwbw6KOPsn//fsrLy5v1JpWWljJ8+HA+/vhjwFsZmjVrFvPmzePdd99l06ZN3HzzzYwfP14z50RERKTD4qIRfO3atezYsYMdO3bQv3//Zp/5uuIbGhrYvn07tbW1/s8ee+wxzGYzV111FS6Xi8mTJ/PHP/6xQ9e22+0sWLCgxSG7RKb71n0nA9237jsZ6L5Dd98mI5Rz8UREREQSVFwMz4mIiIhEm5ImERERkSAoaRIREREJgpImERERkSAoaTrOrl27mDVrFoMGDSI1NZUhQ4awYMEC6uvr2zzO6XRyxx130Lt3b7p3785VV11FRUVFhKIOjV/84hdMmDCBtLS0Ex4/05qZM2diMpmavQIfrhwPOnPfhmHw4IMPkpeXR2pqKpMmTeKrr74Kb6AhdujQIaZNm0Z6ejqZmZnMmjWL6urqNo+ZOHHiCT/v22+/PUIRd84TTzzBwIEDcTgcjBs3zr8sSWtefvllhg8fjsPh4PTTT+f111+PUKSh1ZH7Xr58+Qk/V4fDEcFou+69997jO9/5Dn379sVkMrF69ep2j1m/fj1nnHEGdrudk046ieXLl4c9zlDr6H2vX7/+hJ+1yWRq8/FisWjRokWcddZZ9OjRg+zsbKZOncr27dvbPa6r328lTcf58ssv8Xg8PPXUU2zZsoXHHnuMJ598kh/+8IdtHnfPPffwt7/9jZdffpkNGzawd+9errzyyghFHRr19fVcffXVzJ07t0PHTZkyhbKyMv/r+eefD1OE4dGZ+37kkUf4wx/+wJNPPslHH31Et27dmDx5Mk6nM4yRhta0adPYsmULa9euZc2aNbz33nvMmTOn3eNmz57d7Of9yCOPRCDaznnxxReZN28eCxYs4LPPPmPUqFFMnjyZffv2tbj/Bx98wPXXX8+sWbP4/PPPmTp1KlOnTmXz5s0RjrxrOnrf4F0tOvDnWlxcHMGIu66mpoZRo0bxxBNPBLV/UVERl156Keeffz6FhYXcfffd3Hrrrbz55pthjjS0OnrfPtu3b2/2887Ozg5ThOGxYcMG7rjjDj788EPWrl1LQ0MDF110ETU1Na0eE5LvtyHteuSRR4xBgwa1+vmRI0cMq9VqvPzyy/73tm3bZgDGxo0bIxFiSC1btszIyMgIat8ZM2YYl19+eVjjiZRg79vj8Ri5ubnGr3/9a/97R44cMex2u/H888+HMcLQ2bp1qwEYn3zyif+9f/zjH4bJZDJKS0tbPe68884z7rrrrghEGBrf+MY3jDvuuMP/d7fbbfTt29dYtGhRi/tfc801xqWXXtrsvXHjxhm33XZbWOMMtY7ed0e+8/EAMFatWtXmPvfff78xYsSIZu9de+21xuTJk8MYWXgFc9/vvvuuARiHDx+OSEyRsm/fPgMwNmzY0Oo+ofh+q9IUhMrKyjYf+Ldp0yYaGhqYNGmS/73hw4czYMAANm7cGIkQo2r9+vVkZ2czbNgw5s6dy8GDB6MdUlgVFRVRXl7e7OedkZHBuHHj4ubnvXHjRjIzMznzzDP9702aNAmz2cxHH33U5rHPPfccWVlZnHbaacyfP7/ZgrKxpL6+nk2bNjX7OZnNZiZNmtTqz2njxo3N9geYPHly3PxcoXP3DVBdXU1BQQH5+flcfvnlbNmyJRLhRk0i/Ky7YvTo0eTl5XHhhRfyr3/9K9rhdFllZSVAm7+rQ/Ezj4sVwaNpx44dPP744zz66KOt7lNeXo7NZjuhHyYnJyfuxok7asqUKVx55ZUMGjSInTt38sMf/pCLL76YjRs3YrFYoh1eWPh+pjk5Oc3ej6efd3l5+Qnl+JSUFHr16tXmPdxwww0UFBTQt29f/v3vf/ODH/yA7du385e//CXcIXfYgQMHcLvdLf6cvvzyyxaPKS8vj+ufK3TuvocNG8bSpUsZOXIklZWVPProo0yYMIEtW7ac8BSGRNHaz7qqqoq6ujpSU1OjFFl45eXl8eSTT3LmmWficrlYsmQJEydO5KOPPuKMM86Idnid4vF4uPvuuznnnHM47bTTWt0vFN/vpKk0PfDAAy02vwW+jv8HpbS0lClTpnD11Vcze/bsKEXeNZ2574647rrruOyyyzj99NOZOnUqa9as4ZNPPmH9+vWhu4lOCPd9x6pw3/ecOXOYPHkyp59+OtOmTWPFihWsWrWKnTt3hvAuJNLGjx/P9OnTGT16NOeddx5/+ctf6NOnD0899VS0Q5MQGzZsGLfddhtjx45lwoQJLF26lAkTJvDYY49FO7ROu+OOO9i8eTMvvPBC2K+VNJWme++9l5kzZ7a5z+DBg/3be/fu5fzzz2fChAksXry4zeNyc3Opr6/nyJEjzapNFRUV5ObmdiXsLuvofXfV4MGDycrKYseOHVxwwQUhO29HhfO+fT/TiooK8vLy/O9XVFQwevToTp0zVIK979zc3BOaghsbGzl06FCH/j87btw4wFuRHTJkSIfjDaesrCwsFssJs1jb+l7m5uZ2aP9Y1Jn7Pp7VamXMmDHs2LEjHCHGhNZ+1unp6QlbZWrNN77xDd5///1oh9Epd955p38iS3tV0VB8v5MmaerTpw99+vQJat/S0lLOP/98xo4dy7JlyzCb2y7IjR07FqvVyrp167jqqqsA78yEkpISxo8f3+XYu6Ij9x0Ke/bs4eDBg82SiWgI530PGjSI3Nxc1q1b50+Sqqqq+Oijjzo88zDUgr3v8ePHc+TIETZt2sTYsWMBeOedd/B4PP5EKBiFhYUAUf95t8RmszF27FjWrVvH1KlTAW8Zf926ddx5550tHjN+/HjWrVvH3Xff7X9v7dq1Uf8ed0Rn7vt4brebL774gksuuSSMkUbX+PHjT5huHm8/61ApLCyMye9wWwzD4Hvf+x6rVq1i/fr1DBo0qN1jQvL97myneqLas2ePcdJJJxkXXHCBsWfPHqOsrMz/Ctxn2LBhxkcffeR/7/bbbzcGDBhgvPPOO8ann35qjB8/3hg/fnw0bqHTiouLjc8//9xYuHCh0b17d+Pzzz83Pv/8c+Po0aP+fYYNG2b85S9/MQzDMI4ePWp8//vfNzZu3GgUFRUZb7/9tnHGGWcYQ4cONZxOZ7Ruo8M6et+GYRi/+tWvjMzMTOO1114z/v3vfxuXX365MWjQIKOuri4at9ApU6ZMMcaMGWN89NFHxvvvv28MHTrUuP766/2fH///8x07dhg//elPjU8//dQoKioyXnvtNWPw4MHGueeeG61baNcLL7xg2O12Y/ny5cbWrVuNOXPmGJmZmUZ5eblhGIZx0003GQ888IB//3/9619GSkqK8eijjxrbtm0zFixYYFitVuOLL76I1i10Skfve+HChcabb75p7Ny509i0aZNx3XXXGQ6Hw9iyZUu0bqHDjh496v/uAsZvf/tb4/PPPzeKi4sNwzCMBx54wLjpppv8+3/99ddGWlqacd999xnbtm0znnjiCcNisRhvvPFGtG6hUzp634899pixevVq46uvvjK++OIL46677jLMZrPx9ttvR+sWOmXu3LlGRkaGsX79+ma/p2tra/37hOP7raTpOMuWLTOAFl8+RUVFBmC8++67/vfq6uqM//qv/zJ69uxppKWlGVdccUWzRCsezJgxo8X7DrxPwFi2bJlhGIZRW1trXHTRRUafPn0Mq9VqFBQUGLNnz/b/wxwvOnrfhuFdduAnP/mJkZOTY9jtduOCCy4wtm/fHvngu+DgwYPG9ddfb3Tv3t1IT083br755maJ4vH/Py8pKTHOPfdco1evXobdbjdOOukk47777jMqKyujdAfBefzxx40BAwYYNpvN+MY3vmF8+OGH/s/OO+88Y8aMGc32f+mll4yTTz7ZsNlsxogRI4y///3vEY44NDpy33fffbd/35ycHOOSSy4xPvvssyhE3Xm+qfTHv3z3OWPGDOO888474ZjRo0cbNpvNGDx4cLPveLzo6H0//PDDxpAhQwyHw2H06tXLmDhxovHOO+9EJ/guaO33dODPMBzfb1PTxUVERESkDUkze05ERESkK5Q0iYiIiARBSZOIiIhIEJQ0iYiIiARBSZOIiIhIEJQ0iYiIiARBSZOIiIhIEJQ0iYiIiARBSZOIJLWysjJuuOEGTj75ZMxmc7PnUomIBFLSJCJJzeVy0adPH3784x8zatSoaIcjIjFMSZOIJLT9+/eTm5vLL3/5S/97H3zwATabjXXr1jFw4EB+//vfM336dDIyMqIYqYjEupRoByAiEk59+vRh6dKlTJ06lYsuuohhw4Zx0003ceedd3LBBRdEOzwRiSNKmkQk4V1yySXMnj2badOmceaZZ9KtWzcWLVoU7bBEJM5oeE5EksKjjz5KY2MjL7/8Ms899xx2uz3aIYlInFHSJCJJYefOnezduxePx8OuXbuiHY6IxCENz4lIwquvr+fGG2/k2muvZdiwYdx666188cUXZGdnRzs0EYkjSppEJOH96Ec/orKykj/84Q90796d119/nVtuuYU1a9YAUFhYCEB1dTX79++nsLAQm83GqaeeGsWoRSTWmAzDMKIdhIhIuKxfv54LL7yQd999l29+85sA7Nq1i1GjRvGrX/2KuXPnYjKZTjiuoKBAw3gi0oySJhEREZEgqBFcREREJAhKmkRERESCoKRJREREJAhKmkRERESCoKRJREREJAhKmkRERESCoKRJREREJAhKmkRERESCoKRJREREJAhKmkRERESCoKRJREREJAhKmkRERESC8P8BNBNquWLD+DAAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# 6.1 Perceptron\n",
        "\n",
        "import random\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.pyplot as plt2\n",
        "\n",
        "import numpy as np\n",
        "def compute_output(w, x):\n",
        "    z = 0.0\n",
        "    for i in range(len(w)):\n",
        "        z += x[i] * w[i]  # Compute sum of weighted inputs\n",
        "    if z < 0:  # Apply sign function\n",
        "        return -1\n",
        "    else:\n",
        "        return 1\n",
        "\n",
        "random.seed(7)  # To make repeatable\n",
        "LEARNING_RATE = 0.1\n",
        "index_list = [0, 1, 2, 3]  # Used to randomize order\n",
        "def show_learning(w):\n",
        "    print('w0 =', '%5.2f' % w[0], ', w1 =', '%5.2f' % w[1],\n",
        "    ', w2 =', '%5.2f' % w[2])\n",
        "\n",
        "# Define variables needed for plotting.\n",
        "color_list = ['r-', 'm-', 'y-', 'c-', 'b-', 'g-']\n",
        "color_index = 0\n",
        "def show_learningplot(w):\n",
        "    global color_index\n",
        "    print('w0 =', '%5.2f' % w[0], ', w1 =', '%5.2f' % w[1],\n",
        "    ', w2 =', '%5.2f' % w[2])\n",
        "    if color_index == 0:\n",
        "        plt.plot([1.0], [1.0], 'b_', markersize=12)\n",
        "        plt.plot([-1.0, 1.0, -1.0], [1.0, -1.0, -1.0],\n",
        "        'r+', markersize=12)\n",
        "        plt.axis([-2, 2, -2, 2])\n",
        "        plt.xlabel('x1')\n",
        "        plt.ylabel('x2')\n",
        "    x = [-2.0, 2.0]\n",
        "    if abs(w[2]) < 1e-5:\n",
        "        y = [-w[1]/(1e-5)*(-2.0)+(-w[0]/(1e-5)),\n",
        "        -w[1]/(1e-5)*(2.0)+(-w[0]/(1e-5))]\n",
        "    else:\n",
        "        y = [-w[1]/w[2]*(-2.0)+(-w[0]/w[2]),\n",
        "        -w[1]/w[2]*(2.0)+(-w[0]/w[2])]\n",
        "    plt.plot(x, y, color_list[color_index])\n",
        "    if color_index < (len(color_list) - 1):\n",
        "       color_index += 1\n",
        "\n",
        "x_train = [(1.0, -1.0, -1.0), (1.0, -1.0, 1.0),\n",
        "           (1.0, 1.0, -1.0), (1.0, 1.0, 1.0)]\n",
        "y_train = [1.0, 1.0, 1.0, -1.0]\n",
        "\n",
        "w = [0.2, -0.6, 0.25]  # Initialize to some \"random\" numbers\n",
        "show_learning(w)\n",
        "# Running the training loop again to adjust the weights\n",
        "all_correct = False\n",
        "while not all_correct:\n",
        "    all_correct = True\n",
        "    random.shuffle(index_list)  # Randomize order\n",
        "    for i in index_list:\n",
        "        x = x_train[i]\n",
        "        y = y_train[i]\n",
        "        p_out = compute_output(w, x)  # Perceptron function\n",
        "        if y != p_out:  # Update weights when wrong\n",
        "            for j in range(len(w)):\n",
        "                w[j] += (y * LEARNING_RATE * x[j])\n",
        "            all_correct = False\n",
        "            show_learningplot(w)\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# After Training\n",
        "# Plotting the decision boundary after training\n",
        "x1 = np.linspace(-2, 2, 100)\n",
        "x2 = -(w[1]/w[2])*x1 - (w[0]/w[2])\n",
        "\n",
        "plt.scatter([x[1] for x in x_train], [x[2] for x in x_train], c=y_train, cmap='bwr')\n",
        "\n",
        "plt.plot(x1, x2, label='Decision Boundary')\n",
        "\n",
        "plt.xlabel('x1')\n",
        "plt.ylabel('x2')\n",
        "plt.title('Perceptron Decision Boundary After Training')\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.xlim([-2, 2])\n",
        "plt.ylim([-2, 2])\n",
        "plt.show(), w\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "gj31WUL1G9Ll",
        "outputId": "142ee6b2-f31e-4fee-d1ad-7ea83517f0ab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(None, [0.4, -0.4, -0.15000000000000002])"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "Function: compute_output(w, x)\n",
        "- Purpose: Computes the output of the Perceptron given a set of weights and inputs.\n",
        "- Parameters:\n",
        "  - `w`: A list of weights where `w[i]` corresponds to the weight for the `i`th input.\n",
        "  - `x`: A list of inputs where `x[i]` is the `i`th input value.\n",
        "- Process: It calculates the dot product of the weights and inputs and applies a sign function to determine the output. If the dot product is negative, it returns `-1`, otherwise, it returns `1`.\n",
        "- Returns: The binary classification result (`-1` or `1`) based on the sign of the weighted sum.\n",
        "\n",
        "Global Setup\n",
        "- `random.seed(7)`: Ensures repeatability of the script by initializing the random number generator with a fixed seed.\n",
        "- `LEARNING_RATE = 0.1`: Sets the learning rate, which controls how much the weights are adjusted during each iteration.\n",
        "- `index_list = [0, 1, 2, 3]`: A list used to randomize the order in which training examples are presented to the model.\n",
        "\n",
        "Function: show_learning(w)\n",
        "- Purpose: Prints the current weights of the Perceptron model.\n",
        "- Parameters:\n",
        "  - `w`: The current set of weights.\n",
        "- Process: Formats and prints the weights to the console, providing insight into how the model is learning.\n",
        "\n",
        "Training Data\n",
        "- `x_train`: A list of tuples representing the input vectors. The first element of each tuple is always `1.0` to account for the bias term in linear models.\n",
        "- `y_train`: A list of expected output values (`1.0` or `-1.0`) corresponding to each input vector in `x_train`.\n",
        "\n",
        "Training Loop\n",
        "- Initializes the weights `w` to some random values.\n",
        "- Enters a loop that continues until the model correctly classifies all training examples.\n",
        "- Randomly shuffles the order of training examples to introduce variability in the training process.\n",
        "- For each training example, it computes the output and compares it to the expected output. If they don't match, it adjusts the weights according to the Perceptron learning rule.\n",
        "\n",
        "Weight Adjustment\n",
        "- Rule: `w[j] += (y * LEARNING_RATE * x[j])`\n",
        "- Explanation: For each weight, it is adjusted by adding the product of the learning rate, the error (`y - output`), and the corresponding input value. This rule gradually nudges the weights in the direction that reduces the classification error.\n",
        "\n",
        "Plotting the Decision Boundary\n",
        "- After training, calculates a line that represents the decision boundary of the model.\n",
        "- The decision boundary is determined by the equation `w[0] + w[1]*x1 + w[2]*x2 = 0`.\n",
        "- Visualizes the training data and the decision boundary on a scatter plot, showing how well the model has learned to separate the two classes.\n",
        "\n",
        "Key Concepts Illustrated\n",
        "- Perceptron Model: Demonstrates the basic principles of neural networks, including weight adjustment based on learning from errors.\n",
        "- Linear Separability: The model's ability to classify examples is based on the premise that the data is linearly separable.\n",
        "- Learning Process: Through iterative adjustments, the model learns a decision boundary that best separates the two classes.\n",
        "\n",
        "This script effectively demonstrates the fundamental mechanism behind the training of neural networks, particularly in the context of binary classification with linear models."
      ],
      "metadata": {
        "id": "bblpOmNpFMVa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 6.2 Gradient Descent\n",
        "import random\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "def compute_output(w, x):\n",
        "    # x is expected to be a 2D array where each row is an input vector\n",
        "    z = np.dot(x, w)  # Use x as is, without transposing\n",
        "    return z\n",
        "\n",
        "def compute_gradient(w, x, y):\n",
        "    # Correct gradient calculation for batch processing\n",
        "    y_pred = compute_output(w, x)\n",
        "    errors = y - y_pred\n",
        "    # Compute gradient as the average of the individual gradients\n",
        "    gradient = -2 * np.dot(x.T, errors) / len(x)  # Adjusted to correct gradient formula\n",
        "    return gradient\n",
        "\n",
        "def compute_loss(y_true, y_pred):\n",
        "    # Mean Squared Error loss\n",
        "    return np.mean((y_true - y_pred) ** 2)\n",
        "\n",
        "# Seed for reproducibility\n",
        "random.seed(7)\n",
        "\n",
        "# Hyperparameters\n",
        "LEARNING_RATE = 0.01\n",
        "EPOCHS = 1000\n",
        "\n",
        "# Training data\n",
        "x_train = np.array([\n",
        "    (1.0, -1.0, -1.0),\n",
        "    (1.0, -1.0, 1.0),\n",
        "    (1.0, 1.0, -1.0),\n",
        "    (1.0, 1.0, 1.0)\n",
        "])\n",
        "y_train = np.array([1.0, 1.0, 1.0, -1.0])\n",
        "\n",
        "# Initialize weights\n",
        "w = np.array([0.2, -0.6, 0.25])\n",
        "\n",
        "losses = []  # To track the loss at each epoch\n",
        "\n",
        "for epoch in range(EPOCHS):\n",
        "    # Compute the model's output\n",
        "    y_pred = compute_output(w, x_train)  # Corrected\n",
        "\n",
        "    # Compute the loss\n",
        "    loss = compute_loss(y_train, y_pred)\n",
        "    losses.append(loss)\n",
        "\n",
        "    # Compute gradients\n",
        "    gradient = compute_gradient(w, x_train, y_train)\n",
        "\n",
        "    # Update weights\n",
        "    w -= LEARNING_RATE * gradient\n",
        "\n",
        "    # Optional: Print loss every 100 epochs\n",
        "    if epoch % 100 == 0:\n",
        "        print(f\"Epoch {epoch}, Loss: {loss}\")\n",
        "\n",
        "# Plotting decision boundary after training\n",
        "plt.figure(figsize=(10, 6))\n",
        "plt.scatter(x_train[:,1], x_train[:,2], c=y_train, cmap='bwr')\n",
        "x_values = np.array(plt.gca().get_xlim())\n",
        "y_values = -(w[0] + w[1]*x_values)/w[2]\n",
        "plt.plot(x_values, y_values, label='Decision Boundary')\n",
        "plt.xlabel('x1')\n",
        "plt.ylabel('x2')\n",
        "plt.title('Perceptron Decision Boundary After Training with Gradient Descent')\n",
        "plt.legend()\n",
        "plt.show()\n",
        "\n",
        "# Return the final weights and last loss for reference\n",
        "w, losses[-1]\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        },
        "id": "YJYi95zjFL7H",
        "outputId": "073626b5-db06-4aa1-861d-f0bc115ce31c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 0, Loss: 0.9125\n",
            "Epoch 100, Loss: 0.2616520146262905\n",
            "Epoch 200, Loss: 0.2502049350110963\n",
            "Epoch 300, Loss: 0.25000360438603286\n",
            "Epoch 400, Loss: 0.2500000633937491\n",
            "Epoch 500, Loss: 0.2500000011149659\n",
            "Epoch 600, Loss: 0.25000000001961\n",
            "Epoch 700, Loss: 0.2500000000003449\n",
            "Epoch 800, Loss: 0.250000000000006\n",
            "Epoch 900, Loss: 0.2500000000000001\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([ 0.5, -0.5, -0.5]), 0.25)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 6.3 ANN Library\n",
        "import tensorflow as tf\n",
        "from tensorflow.keras.datasets import mnist\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import Dense, Flatten\n",
        "from tensorflow.keras.utils import to_categorical\n",
        "\n",
        "# Load the dataset\n",
        "(train_images, train_labels), (test_images, test_labels) = mnist.load_data()\n",
        "\n",
        "# Normalize the images to have pixel values between 0 and 1\n",
        "train_images = train_images / 255.0\n",
        "test_images = test_images / 255.0\n",
        "\n",
        "# Convert labels to one-hot encoded vectors\n",
        "train_labels = to_categorical(train_labels)\n",
        "test_labels = to_categorical(test_labels)\n",
        "\n",
        "# Define the model architecture\n",
        "model = Sequential([\n",
        "    Flatten(input_shape=(28, 28)),  # Flattens the input\n",
        "    Dense(10, activation='Softmax')  # A softmax layer with 10 output units for each digit\n",
        "])\n",
        "\n",
        "# Compile the model\n",
        "model.compile(optimizer='adam',\n",
        "              loss='categorical_crossentropy',\n",
        "              metrics=['accuracy'])\n",
        "\n",
        "# Train the model\n",
        "model.fit(train_images, train_labels, epochs=5, batch_size=32)\n",
        "\n",
        "# Evaluate the model\n",
        "test_loss, test_acc = model.evaluate(test_images, test_labels)\n",
        "print(f'Test accuracy: {test_acc}')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "weA6mi1Xvjr4",
        "outputId": "71d26a0d-1f2f-4246-aa64-3e2a4cdacb7c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/5\n",
            "1875/1875 [==============================] - 3s 2ms/step - loss: 0.4645 - accuracy: 0.8794\n",
            "Epoch 2/5\n",
            "1875/1875 [==============================] - 3s 2ms/step - loss: 0.3036 - accuracy: 0.9159\n",
            "Epoch 3/5\n",
            "1875/1875 [==============================] - 3s 2ms/step - loss: 0.2833 - accuracy: 0.9207\n",
            "Epoch 4/5\n",
            "1875/1875 [==============================] - 4s 2ms/step - loss: 0.2731 - accuracy: 0.9231\n",
            "Epoch 5/5\n",
            "1875/1875 [==============================] - 3s 2ms/step - loss: 0.2667 - accuracy: 0.9260\n",
            "313/313 [==============================] - 1s 1ms/step - loss: 0.2634 - accuracy: 0.9281\n",
            "Test accuracy: 0.9280999898910522\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 6.4 Backpropagation\n",
        "import numpy as np\n",
        "np.random.seed(3) # To make repeatable\n",
        "LEARNING_RATE = 0.1\n",
        "index_list = [0, 1, 2, 3] # Used to randomize order\n",
        "# Define training examples.\n",
        "x_train = [np.array([1.0, -1.0, -1.0]),\n",
        "           np.array([1.0, -1.0, 1.0]),\n",
        "np.array([1.0, 1.0, -1.0]),\n",
        "np.array([1.0, 1.0, 1.0])]\n",
        "y_train = [0.0, 1.0, 1.0, 0.0] # Output (ground truth)\n",
        "def neuron_w(input_count):\n",
        "    weights = np.zeros(input_count+1)\n",
        "    for i in range(1, (input_count+1)):\n",
        "        weights[i] = np.random.uniform(-1.0, 1.0)\n",
        "    return weights\n",
        "n_w = [neuron_w(2), neuron_w(2), neuron_w(2)]\n",
        "n_y = [0, 0, 0]\n",
        "n_error = [0, 0, 0]\n",
        "\n",
        "def show_learning():\n",
        "    print('Current weights:')\n",
        "    for i, w in enumerate(n_w):\n",
        "        print('neuron ', i, ': w0 =', '%5.2f' % w[0],\n",
        "        ', w1 =', '%5.2f' % w[1], ', w2 =',\n",
        "        '%5.2f' % w[2])\n",
        "    print('----------------')\n",
        "\n",
        "def forward_pass(x):\n",
        "    global n_y\n",
        "    n_y[0] = np.tanh(np.dot(n_w[0], x)) # Neuron 0\n",
        "    n_y[1] = np.tanh(np.dot(n_w[1], x)) # Neuron 1\n",
        "    n2_inputs = np.array([1.0, n_y[0], n_y[1]]) # 1.0 is bias\n",
        "    z2 = np.dot(n_w[2], n2_inputs)\n",
        "    n_y[2] = 1.0 / (1.0 + np.exp(-z2))\n",
        "\n",
        "def backward_pass(y_truth):\n",
        "    global n_error\n",
        "    error_prime = -(y_truth - n_y[2]) # Derivative of loss-func\n",
        "    derivative = n_y[2] * (1.0 - n_y[2]) # Logistic derivative\n",
        "    n_error[2] = error_prime * derivative\n",
        "    derivative = 1.0 - n_y[0]**2 # tanh derivative\n",
        "    n_error[0] = n_w[2][1] * n_error[2] * derivative\n",
        "    derivative = 1.0 - n_y[1]**2 # tanh derivative\n",
        "    n_error[1] = n_w[2][2] * n_error[2] * derivative\n",
        "def adjust_weights(x):\n",
        "    global n_w\n",
        "    n_w[0] -= (x * LEARNING_RATE * n_error[0])\n",
        "    n_w[1] -= (x * LEARNING_RATE * n_error[1])\n",
        "    n2_inputs = np.array([1.0, n_y[0], n_y[1]]) # 1.0 is bias\n",
        "    n_w[2] -= (n2_inputs * LEARNING_RATE * n_error[2])\n",
        "\n",
        "# Network training loop.\n",
        "all_correct = False\n",
        "while not all_correct: # Train until converged\n",
        "    all_correct = True\n",
        "    np.random.shuffle(index_list) # Randomize order\n",
        "    for i in index_list: # Train on all examples\n",
        "      forward_pass(x_train[i])\n",
        "      backward_pass(y_train[i])\n",
        "      adjust_weights(x_train[i])\n",
        "      show_learning() # Show updated weights\n",
        "    for i in range(len(x_train)): # Check if converged\n",
        "        forward_pass(x_train[i])\n",
        "        print('x1 =', '%4.1f' % x_train[i][1], ', x2 =',\n",
        "        '%4.1f' % x_train[i][2], ', y =',\n",
        "        '%.4f' % n_y[2])\n",
        "        if(((y_train[i] < 0.5) and (n_y[2] >= 0.5))\n",
        "        or ((y_train[i] >= 0.5) and (n_y[2] < 0.5))):\n",
        "           all_correct = False"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QEWnN5an_rL-",
        "outputId": "43672761-c5a5-4228-cf2a-37402def770b"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.11 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.41 , w2 =  0.01\n",
            "neuron  2 : w0 =  0.01 , w1 =  0.78 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.00 , w1 =  0.12 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.40 , w2 =  0.02\n",
            "neuron  2 : w0 =  0.00 , w1 =  0.79 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 = -0.00 , w1 =  0.11 , w2 =  0.41\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.41 , w2 =  0.01\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.78 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.00 , w1 =  0.11 , w2 =  0.41\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.42 , w2 =  0.02\n",
            "neuron  2 : w0 = -0.00 , w1 =  0.78 , w2 =  0.79\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4811\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6347\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3645\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5179\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.10 , w2 =  0.42\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.42 , w2 =  0.02\n",
            "neuron  2 : w0 =  0.01 , w1 =  0.79 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.11 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.41 , w2 =  0.01\n",
            "neuron  2 : w0 =  0.02 , w1 =  0.78 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.10 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.42 , w2 =  0.00\n",
            "neuron  2 : w0 =  0.01 , w1 =  0.77 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.00 , w1 =  0.11 , w2 =  0.41\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.41 , w2 =  0.01\n",
            "neuron  2 : w0 = -0.00 , w1 =  0.78 , w2 =  0.79\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4808\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6309\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3670\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5167\n",
            "Current weights:\n",
            "neuron  0 : w0 = -0.01 , w1 =  0.10 , w2 =  0.40\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.42 , w2 =  0.00\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.77 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.11 , w2 =  0.39\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.41 , w2 = -0.01\n",
            "neuron  2 : w0 = -0.00 , w1 =  0.77 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 = -0.00 , w1 =  0.12 , w2 =  0.40\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.40 , w2 =  0.00\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.78 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.00 , w1 =  0.11 , w2 =  0.40\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.41 , w2 =  0.01\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.78 , w2 =  0.78\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4809\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6278\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3697\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5161\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.12 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.40 , w2 = -0.00\n",
            "neuron  2 : w0 =  0.01 , w1 =  0.77 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.12 , w2 =  0.38\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.41 , w2 = -0.01\n",
            "neuron  2 : w0 = -0.00 , w1 =  0.77 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 = -0.00 , w1 =  0.12 , w2 =  0.39\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.40 , w2 = -0.00\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.77 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.12 , w2 =  0.40\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.41 , w2 =  0.00\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.78 , w2 =  0.78\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4810\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6248\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3723\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5155\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.11 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.41 , w2 =  0.01\n",
            "neuron  2 : w0 =  0.00 , w1 =  0.78 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.12 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.40 , w2 = -0.00\n",
            "neuron  2 : w0 =  0.02 , w1 =  0.77 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.11 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.41 , w2 = -0.01\n",
            "neuron  2 : w0 =  0.00 , w1 =  0.77 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.12 , w2 =  0.39\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.40 , w2 = -0.00\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.77 , w2 =  0.78\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4809\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6214\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3749\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5147\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.13 , w2 =  0.38\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.39 , w2 = -0.01\n",
            "neuron  2 : w0 =  0.01 , w1 =  0.77 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.13 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.40 , w2 = -0.00\n",
            "neuron  2 : w0 =  0.01 , w1 =  0.77 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.13 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.39 , w2 =  0.00\n",
            "neuron  2 : w0 =  0.00 , w1 =  0.78 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.13 , w2 =  0.39\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.40 , w2 = -0.01\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.77 , w2 =  0.78\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4808\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6181\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3775\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5140\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.00 , w1 =  0.13 , w2 =  0.40\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.39 , w2 =  0.00\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.78 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.13 , w2 =  0.40\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.40 , w2 =  0.01\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.78 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.14 , w2 =  0.39\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.39 , w2 = -0.00\n",
            "neuron  2 : w0 =  0.00 , w1 =  0.77 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.13 , w2 =  0.39\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.40 , w2 = -0.01\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.77 , w2 =  0.78\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4811\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6153\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3803\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5135\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.00 , w1 =  0.14 , w2 =  0.39\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.39 , w2 = -0.00\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.77 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.13 , w2 =  0.40\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.39 , w2 =  0.00\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.78 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.14 , w2 =  0.39\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.39 , w2 = -0.00\n",
            "neuron  2 : w0 = -0.00 , w1 =  0.77 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.13 , w2 =  0.38\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.39 , w2 = -0.01\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.77 , w2 =  0.77\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4815\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6126\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3830\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5130\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.12 , w2 =  0.37\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.40 , w2 = -0.02\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.76 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.12 , w2 =  0.38\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.41 , w2 = -0.02\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.76 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.13 , w2 =  0.37\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.40 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.00 , w1 =  0.76 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.14 , w2 =  0.38\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.39 , w2 = -0.02\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.76 , w2 =  0.77\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4816\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6100\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3858\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5129\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.14 , w2 =  0.38\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.38 , w2 = -0.01\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.77 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.00 , w1 =  0.14 , w2 =  0.38\n",
            "neuron  1 : w0 = -0.03 , w1 = -0.39 , w2 = -0.02\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.76 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.15 , w2 =  0.37\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.38 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.76 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.14 , w2 =  0.37\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.39 , w2 = -0.02\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.76 , w2 =  0.77\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4821\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6078\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3886\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5129\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.01 , w1 =  0.15 , w2 =  0.38\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.38 , w2 = -0.01\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.77 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.00 , w1 =  0.14 , w2 =  0.37\n",
            "neuron  1 : w0 = -0.03 , w1 = -0.39 , w2 = -0.02\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.76 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.15 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.38 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.76 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.14 , w2 =  0.37\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.39 , w2 = -0.02\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.76 , w2 =  0.77\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4827\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6057\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3914\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5130\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.03 , w1 =  0.14 , w2 =  0.38\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.39 , w2 = -0.02\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.76 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.15 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.38 , w2 = -0.03\n",
            "neuron  2 : w0 =  0.01 , w1 =  0.76 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.03 , w1 =  0.14 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.39 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.00 , w1 =  0.75 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.15 , w2 =  0.37\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.38 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.76 , w2 =  0.77\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4828\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6030\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3941\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5127\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.14 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.39 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.75 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.03 , w1 =  0.15 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.38 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.75 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.03 , w1 =  0.14 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.39 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.75 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.03 , w1 =  0.15 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.38 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.76 , w2 =  0.76\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4830\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6008\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3968\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5128\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.16 , w2 =  0.37\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.37 , w2 = -0.02\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.76 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.03 , w1 =  0.17 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.36 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.76 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.16 , w2 =  0.37\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.37 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.76 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.03 , w1 =  0.15 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.38 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.75 , w2 =  0.76\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4835\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5986\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.3996\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5127\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.15 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.39 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.75 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.15 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.03 , w1 = -0.38 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.75 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.02 , w1 =  0.15 , w2 =  0.37\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.39 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.76 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.03 , w1 =  0.16 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.38 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.75 , w2 =  0.76\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4841\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5969\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4024\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5130\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.03 , w1 =  0.16 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.37 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.76 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.18 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.36 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.76 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.17 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.36 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.76 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.16 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.37 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.75 , w2 =  0.76\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4846\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5949\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4052\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5130\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.15 , w2 =  0.36\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.38 , w2 = -0.03\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.75 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.15 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.39 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.75 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.16 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.38 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.74 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.16 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.37 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.75 , w2 =  0.76\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4848\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5927\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4078\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5131\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.18 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.36 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.75 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.18 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.35 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.75 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.18 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.36 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.75 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.17 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.37 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.75 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4852\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5910\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4105\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5134\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.16 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.38 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.75 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.15 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.38 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.74 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.03 , w1 =  0.16 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.38 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.75 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.17 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.37 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.75 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4856\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5890\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4132\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5136\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.16 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.37 , w2 = -0.04\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.75 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.06 , w1 =  0.18 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.36 , w2 = -0.05\n",
            "neuron  2 : w0 =  0.00 , w1 =  0.75 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.06 , w1 =  0.17 , w2 =  0.33\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.37 , w2 = -0.06\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.74 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.18 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.36 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.75 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4857\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5869\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4157\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5136\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.06 , w1 =  0.17 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.37 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.75 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.16 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.38 , w2 = -0.06\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.17 , w2 =  0.35\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.37 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.75 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.18 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.36 , w2 = -0.06\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.74 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4861\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5851\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4184\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5139\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.06 , w1 =  0.17 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.37 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.75 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.17 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.38 , w2 = -0.06\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.17 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.37 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.18 , w2 =  0.33\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.36 , w2 = -0.06\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4865\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5833\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4211\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5142\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.19 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.35 , w2 = -0.05\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.75 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.04 , w1 =  0.18 , w2 =  0.33\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.36 , w2 = -0.06\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.74 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.19 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.35 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.06 , w1 =  0.19 , w2 =  0.33\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.36 , w2 = -0.06\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4871\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5821\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4239\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5147\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.07 , w1 =  0.20 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.35 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.06 , w1 =  0.19 , w2 =  0.31\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.36 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.73 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.20 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.35 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.06 , w1 =  0.19 , w2 =  0.33\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.35 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4876\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5808\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4264\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5152\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.18 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.36 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.19 , w2 =  0.33\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.36 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.74 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.18 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.36 , w2 = -0.06\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.07 , w1 =  0.19 , w2 =  0.33\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.35 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4882\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5796\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4291\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5158\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.06 , w1 =  0.19 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.36 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.05 , w1 =  0.19 , w2 =  0.33\n",
            "neuron  1 : w0 = -0.02 , w1 = -0.35 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.06 , w1 =  0.20 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.34 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.07 , w1 =  0.20 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.35 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4889\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5785\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4318\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5164\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.21 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.07 , w1 =  0.21 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.33 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.06 , w1 =  0.21 , w2 =  0.31\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.34 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.07 , w1 =  0.20 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.35 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4893\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5774\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4342\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5168\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.07 , w1 =  0.19 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.36 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.20 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.35 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.20 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.36 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.73 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.20 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.35 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4895\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5760\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4367\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5174\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.07 , w1 =  0.21 , w2 =  0.33\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.34 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.20 , w2 =  0.34\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.35 , w2 = -0.06\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.21 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.21 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.35 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4900\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5747\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4391\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5177\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.22 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.21 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.34 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.20 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.35 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.21 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.34 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4902\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5734\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4414\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5181\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.20 , w2 =  0.31\n",
            "neuron  1 : w0 = -0.01 , w1 = -0.35 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.21 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.34 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.22 , w2 =  0.31\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.33 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.21 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.34 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4906\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5724\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4438\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5187\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.22 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.33 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.22 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.34 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.01 , w1 =  0.74 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.22 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.33 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.22 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.34 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4907\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5710\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4459\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5189\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.23 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.33 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.22 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.34 , w2 = -0.07\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.08 , w1 =  0.21 , w2 =  0.32\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.35 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.22 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4912\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5699\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4483\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5194\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.21 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.35 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.22 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.23 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.33 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.22 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4914\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5686\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4506\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5197\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.22 , w2 =  0.30\n",
            "neuron  1 : w0 = -0.00 , w1 = -0.35 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.72 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.23 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.72 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.24 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.33 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.23 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4918\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5678\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4528\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5203\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.11 , w1 =  0.22 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.34 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.23 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.08\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.09 , w1 =  0.22 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.34 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.23 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.33 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4920\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5666\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4551\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5208\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.23 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.34 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.72 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.22 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.35 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.23 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.34 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.11 , w1 =  0.24 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.33 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4923\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5657\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4574\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5214\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.24 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.11 , w1 =  0.25 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.32 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.24 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.11 , w1 =  0.24 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.33 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4925\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5647\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4593\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5217\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.10 , w1 =  0.25 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.32 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.11 , w1 =  0.24 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.33 , w2 = -0.09\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.25 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.11 , w1 =  0.24 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.33 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4929\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5638\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4614\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5221\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.23 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.34 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.13 , w1 =  0.24 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.33 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.02 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.25 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.25 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.33 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4928\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5627\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4633\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5223\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.13 , w1 =  0.26 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.26 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.31 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.11 , w1 =  0.26 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.32 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.25 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.33 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4931\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5621\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4652\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5228\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.11 , w1 =  0.26 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.32 , w2 = -0.10\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.11 , w1 =  0.25 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.00 , w1 = -0.33 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.24 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.13 , w1 =  0.25 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.33 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4936\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5616\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4674\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5235\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.25 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.72 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.13 , w1 =  0.24 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.34 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.72 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.25 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.34 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.13 , w1 =  0.26 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.33 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4938\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5609\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4694\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5241\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.12 , w1 =  0.25 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.33 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.72 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.13 , w1 =  0.24 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.34 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.72 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.25 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.33 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.72 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.13 , w1 =  0.26 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.33 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4938\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5601\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4713\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5247\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.27 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.32 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.26 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.72 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.25 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.33 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.72 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.26 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4938\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5593\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4730\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5251\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.25 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.33 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.26 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.33 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.13 , w1 =  0.26 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.33 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.27 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4939\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5585\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4749\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5255\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.15 , w1 =  0.26 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.33 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.27 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.11\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.13 , w1 =  0.26 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.33 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.27 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.32 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4940\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5577\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4768\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5259\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.28 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.13 , w1 =  0.27 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.01 , w1 = -0.32 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.14 , w1 =  0.26 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.33 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.15 , w1 =  0.27 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.32 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4944\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5574\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4788\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5266\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.28 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.31 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.15 , w1 =  0.29 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.31 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.28 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.31 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.15 , w1 =  0.28 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.32 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4944\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5568\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4803\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5269\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.29 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.31 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.17 , w1 =  0.28 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.32 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.03 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.29 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.31 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.15 , w1 =  0.28 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.32 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4943\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5559\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4817\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5271\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.27 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.33 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.15 , w1 =  0.28 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.32 , w2 = -0.12\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.29 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.31 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.04 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.28 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.32 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4942\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5552\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4834\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5274\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.15 , w1 =  0.29 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.31 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.30 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.30 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.15 , w1 =  0.29 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.31 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.29 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.32 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4945\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5550\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4850\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5279\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.15 , w1 =  0.29 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.31 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.15 , w1 =  0.29 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.02 , w1 = -0.32 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.30 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.31 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.17 , w1 =  0.29 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4948\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5548\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4868\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5285\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.16 , w1 =  0.28 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.33 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.72 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.17 , w1 =  0.29 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.28 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.33 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.72 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.17 , w1 =  0.29 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4947\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5544\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4883\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5290\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.30 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.31 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.17 , w1 =  0.31 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.30 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.30 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.31 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.17 , w1 =  0.30 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4947\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5540\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4896\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5293\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.29 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.33 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.17 , w1 =  0.30 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.31 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.31 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.30 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4946\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5533\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4911\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5295\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.17 , w1 =  0.31 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.31 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.30 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.13\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.17 , w1 =  0.29 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.33 , w2 = -0.14\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.30 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4948\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5531\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4928\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5300\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.30 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.33 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.31 , w2 =  0.29\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.31 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.31 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.19 , w1 =  0.31 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4948\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5530\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4942\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5305\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.31 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.31 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.17 , w1 =  0.31 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.03 , w1 = -0.32 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.18 , w1 =  0.32 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.31 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.19 , w1 =  0.31 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.32 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4950\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5530\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4959\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5311\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.32 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.31 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.19 , w1 =  0.33 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.30 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.32 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.31 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.19 , w1 =  0.31 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.32 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4949\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5526\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4970\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5313\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.19 , w1 =  0.31 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.33 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.32 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.32 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.31 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.32 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.32 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.32 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4947\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5524\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4984\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5318\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.21 , w1 =  0.32 , w2 =  0.30\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.31 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.21 , w1 =  0.32 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.05 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.21 , w1 =  0.31 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.32 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.32 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.32 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4944\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5519\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.4994\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5318\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.19 , w1 =  0.33 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.31 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.34 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.30 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.33 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.31 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.32 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.32 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4945\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5519\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5008\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5323\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.21 , w1 =  0.33 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.31 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.32 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.32 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.33 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.21 , w1 =  0.33 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.32 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4942\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5515\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5018\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5323\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.32 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.33 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.21 , w1 =  0.33 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.32 , w2 = -0.15\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.32 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.33 , w2 = -0.16\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.21 , w1 =  0.33 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.32 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4941\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5511\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5032\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5327\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.34 , w2 =  0.31\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.31 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.23 , w1 =  0.33 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.06 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.34 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.31 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.33 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.32 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4937\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5507\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5042\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5328\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.21 , w1 =  0.34 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.31 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.20 , w1 =  0.34 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.04 , w1 = -0.32 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.21 , w1 =  0.33 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.33 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.34 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.32 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4938\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5509\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5058\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5334\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.23 , w1 =  0.33 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.33 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.32 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.33 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.33 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.33 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.34 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.32 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4937\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5506\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5071\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5336\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.35 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.31 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.21 , w1 =  0.34 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.32 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.22 , w1 =  0.35 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.31 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.23 , w1 =  0.34 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4937\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5509\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5086\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5342\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.24 , w1 =  0.34 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.33 , w2 = -0.17\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.34 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.32 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.07 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.24 , w1 =  0.34 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.33 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.23 , w1 =  0.35 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4933\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5505\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5095\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5342\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.23 , w1 =  0.35 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.31 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.73 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.23 , w1 =  0.36 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.30 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.24 , w1 =  0.36 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.31 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.08 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.24 , w1 =  0.35 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4933\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5506\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5107\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5344\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.23 , w1 =  0.35 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.33 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.23 , w1 =  0.35 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.05 , w1 = -0.32 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.23 , w1 =  0.36 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.31 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.24 , w1 =  0.35 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4934\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5509\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5120\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5349\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.24 , w1 =  0.35 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.06 , w1 = -0.33 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.36 , w2 =  0.32\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.72 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.35 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.33 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.36 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4930\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5509\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5132\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5353\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.24 , w1 =  0.37 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.37 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.31 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.37 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.31 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.36 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.32 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4929\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5510\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5142\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5354\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.24 , w1 =  0.37 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.32 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.36 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.32 , w2 = -0.18\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.36 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.33 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.36 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.32 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4929\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5511\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5156\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5357\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.26 , w1 =  0.36 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.33 , w2 = -0.19\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.26 , w1 =  0.35 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.34 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.27 , w1 =  0.36 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.33 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.26 , w1 =  0.37 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.32 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4924\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5509\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5166\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5359\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.27 , w1 =  0.38 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.31 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.26 , w1 =  0.37 , w2 =  0.33\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.32 , w2 = -0.22\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.27 , w1 =  0.36 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.33 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.26 , w1 =  0.37 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.32 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4920\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5510\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5175\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5360\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.26 , w1 =  0.38 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.32 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.25 , w1 =  0.38 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.07 , w1 = -0.33 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.26 , w1 =  0.38 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.32 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.27 , w1 =  0.38 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.32 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4920\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5515\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5188\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5365\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.26 , w1 =  0.37 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.33 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.27 , w1 =  0.36 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.34 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.26 , w1 =  0.37 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.33 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.27 , w1 =  0.38 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.33 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4918\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5516\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5201\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5368\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.28 , w1 =  0.37 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.33 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.29 , w1 =  0.38 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.32 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.09 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.28 , w1 =  0.39 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.32 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.75 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.28 , w1 =  0.38 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.33 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4912\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5515\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5209\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5368\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.27 , w1 =  0.39 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.32 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.74 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.28 , w1 =  0.38 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.33 , w2 = -0.20\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.75 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.28 , w1 =  0.39 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.32 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.75 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.28 , w1 =  0.39 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.33 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4910\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5517\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5220\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5368\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.29 , w1 =  0.40 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.32 , w2 = -0.22\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.28 , w1 =  0.39 , w2 =  0.34\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.33 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.28 , w1 =  0.40 , w2 =  0.35\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.32 , w2 = -0.22\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.29 , w1 =  0.39 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.33 , w2 = -0.22\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4907\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5521\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5229\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5370\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.29 , w1 =  0.38 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.34 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.30 , w1 =  0.39 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.33 , w2 = -0.22\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.30 , w1 =  0.39 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.34 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.29 , w1 =  0.40 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.33 , w2 = -0.22\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4902\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5520\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5237\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5369\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.29 , w1 =  0.39 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.34 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.28 , w1 =  0.40 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.08 , w1 = -0.33 , w2 = -0.22\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.73 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.29 , w1 =  0.39 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.09 , w1 = -0.34 , w2 = -0.21\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.29 , w1 =  0.40 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.33 , w2 = -0.22\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4901\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5525\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5250\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5373\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.30 , w1 =  0.41 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.32 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.11 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.40 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.33 , w2 = -0.22\n",
            "neuron  2 : w0 = -0.10 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.40 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.34 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.30 , w1 =  0.40 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.33 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4896\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5526\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5258\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5372\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.41 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.32 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.30 , w1 =  0.42 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.32 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.75 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.41 , w2 =  0.38\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.33 , w2 = -0.22\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.75 , w2 =  0.71\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.30 , w1 =  0.41 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.33 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4891\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5528\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5266\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5371\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.41 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.33 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.41 , w2 =  0.36\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.33 , w2 = -0.25\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.32 , w1 =  0.40 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.34 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.41 , w2 =  0.38\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.34 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4886\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5531\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5275\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5372\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.30 , w1 =  0.41 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.34 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.73 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.41 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.33 , w2 = -0.25\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.30 , w1 =  0.42 , w2 =  0.37\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.33 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.41 , w2 =  0.38\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.34 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4884\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5537\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5286\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5375\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.41 , w2 =  0.38\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.34 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.32 , w1 =  0.40 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.35 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.31 , w1 =  0.41 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.10 , w1 = -0.35 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.74 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.32 , w1 =  0.42 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.34 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4880\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5541\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5299\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5377\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.33 , w1 =  0.41 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.35 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.32 , w1 =  0.41 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.35 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.33 , w1 =  0.42 , w2 =  0.38\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.34 , w2 = -0.25\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.32 , w1 =  0.42 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.34 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4875\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5543\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5309\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5378\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.33 , w1 =  0.42 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.35 , w2 = -0.23\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.33 , w1 =  0.41 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.11 , w1 = -0.35 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.33 , w1 =  0.42 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.35 , w2 = -0.25\n",
            "neuron  2 : w0 = -0.13 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.33 , w1 =  0.43 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.34 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4869\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5544\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5319\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5378\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.33 , w1 =  0.42 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.35 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.34 , w1 =  0.43 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.34 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.12 , w1 =  0.76 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.33 , w1 =  0.43 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.33 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.76 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.33 , w1 =  0.43 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.34 , w2 = -0.25\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4863\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5546\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5328\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5376\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.34 , w1 =  0.44 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.33 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.76 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.33 , w1 =  0.45 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.33 , w2 = -0.25\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.76 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.34 , w1 =  0.44 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.34 , w2 = -0.24\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.76 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.34 , w1 =  0.44 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.34 , w2 = -0.25\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4858\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5550\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5336\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5375\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.34 , w1 =  0.44 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.34 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.76 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.34 , w1 =  0.44 , w2 =  0.39\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.34 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.75 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.35 , w1 =  0.43 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.35 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.75 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.34 , w1 =  0.44 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.35 , w2 = -0.25\n",
            "neuron  2 : w0 = -0.16 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4852\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5555\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5345\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5375\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.34 , w1 =  0.44 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.35 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.74 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.35 , w1 =  0.43 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.36 , w2 = -0.25\n",
            "neuron  2 : w0 = -0.16 , w1 =  0.75 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.35 , w1 =  0.44 , w2 =  0.40\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.35 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.75 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.35 , w1 =  0.44 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.35 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.16 , w1 =  0.76 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4847\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5560\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5356\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5376\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.34 , w1 =  0.44 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.36 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.75 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.35 , w1 =  0.43 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.36 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.16 , w1 =  0.75 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.36 , w1 =  0.44 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.14 , w1 = -0.35 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.75 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.35 , w1 =  0.45 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.35 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.16 , w1 =  0.76 , w2 =  0.72\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4842\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5565\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5368\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5378\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.36 , w1 =  0.44 , w2 =  0.42\n",
            "neuron  1 : w0 =  0.14 , w1 = -0.36 , w2 = -0.25\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.76 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.37 , w1 =  0.45 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.35 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.14 , w1 =  0.77 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.36 , w1 =  0.46 , w2 =  0.42\n",
            "neuron  1 : w0 =  0.14 , w1 = -0.34 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.77 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.35 , w1 =  0.45 , w2 =  0.42\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.35 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.76 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4835\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5567\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5376\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5376\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.35 , w1 =  0.45 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.36 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.75 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.34 , w1 =  0.46 , w2 =  0.42\n",
            "neuron  1 : w0 =  0.12 , w1 = -0.35 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.75 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.35 , w1 =  0.46 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.34 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.76 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.36 , w1 =  0.46 , w2 =  0.42\n",
            "neuron  1 : w0 =  0.14 , w1 = -0.35 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.76 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4833\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5577\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5390\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5378\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.37 , w1 =  0.46 , w2 =  0.41\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.34 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.16 , w1 =  0.77 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.38 , w1 =  0.46 , w2 =  0.42\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.35 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.15 , w1 =  0.77 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.37 , w1 =  0.46 , w2 =  0.43\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.35 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.16 , w1 =  0.78 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.37 , w1 =  0.46 , w2 =  0.43\n",
            "neuron  1 : w0 =  0.14 , w1 = -0.35 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.76 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4826\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5580\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5398\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5376\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.36 , w1 =  0.46 , w2 =  0.42\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.36 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.75 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.37 , w1 =  0.45 , w2 =  0.43\n",
            "neuron  1 : w0 =  0.14 , w1 = -0.37 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.76 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.36 , w1 =  0.46 , w2 =  0.44\n",
            "neuron  1 : w0 =  0.13 , w1 = -0.37 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.76 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.37 , w1 =  0.47 , w2 =  0.43\n",
            "neuron  1 : w0 =  0.14 , w1 = -0.36 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.77 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4822\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5587\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5411\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5377\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.38 , w1 =  0.46 , w2 =  0.44\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.36 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.16 , w1 =  0.77 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.37 , w1 =  0.47 , w2 =  0.45\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.36 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.78 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.38 , w1 =  0.47 , w2 =  0.44\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.35 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.16 , w1 =  0.78 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.38 , w1 =  0.47 , w2 =  0.43\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.36 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.77 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4816\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5590\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5422\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5375\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.37 , w1 =  0.48 , w2 =  0.44\n",
            "neuron  1 : w0 =  0.14 , w1 = -0.35 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.77 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.38 , w1 =  0.47 , w2 =  0.45\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.36 , w2 = -0.26\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.78 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.38 , w1 =  0.48 , w2 =  0.44\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.35 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.78 , w2 =  0.72\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.38 , w1 =  0.47 , w2 =  0.44\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.36 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.77 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4812\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5597\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5433\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5373\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.38 , w1 =  0.47 , w2 =  0.44\n",
            "neuron  1 : w0 =  0.14 , w1 = -0.37 , w2 = -0.29\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.76 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.39 , w1 =  0.46 , w2 =  0.44\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.38 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.76 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.39 , w1 =  0.47 , w2 =  0.44\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.29\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.77 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.39 , w1 =  0.48 , w2 =  0.44\n",
            "neuron  1 : w0 =  0.15 , w1 = -0.36 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.77 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4806\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5604\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5445\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5373\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.39 , w1 =  0.47 , w2 =  0.45\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.78 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.39 , w1 =  0.48 , w2 =  0.46\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.27\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.78 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.39 , w1 =  0.49 , w2 =  0.45\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.36 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.79 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.39 , w1 =  0.48 , w2 =  0.45\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.29\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.77 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4799\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5608\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5455\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5371\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.40 , w1 =  0.48 , w2 =  0.46\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.78 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.39 , w1 =  0.48 , w2 =  0.46\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.78 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.40 , w1 =  0.49 , w2 =  0.46\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.36 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.79 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.40 , w1 =  0.49 , w2 =  0.45\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.29\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.78 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4793\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5613\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5466\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5368\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.40 , w1 =  0.50 , w2 =  0.45\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.36 , w2 = -0.30\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.78 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.41 , w1 =  0.49 , w2 =  0.45\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.37 , w2 = -0.29\n",
            "neuron  2 : w0 = -0.17 , w1 =  0.79 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.41 , w1 =  0.49 , w2 =  0.45\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.37 , w2 = -0.30\n",
            "neuron  2 : w0 = -0.18 , w1 =  0.77 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.40 , w1 =  0.49 , w2 =  0.46\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.30\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.78 , w2 =  0.73\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4786\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5618\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5475\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5364\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.39 , w1 =  0.50 , w2 =  0.46\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.29\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.79 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.40 , w1 =  0.49 , w2 =  0.47\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.28\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.79 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.40 , w1 =  0.49 , w2 =  0.47\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.38 , w2 = -0.29\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.78 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.41 , w1 =  0.50 , w2 =  0.46\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.30\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.78 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4782\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5627\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5489\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5364\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.41 , w1 =  0.51 , w2 =  0.46\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.36 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.79 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.41 , w1 =  0.50 , w2 =  0.45\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.37 , w2 = -0.32\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.77 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.40 , w1 =  0.51 , w2 =  0.46\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.37 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.78 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.41 , w1 =  0.50 , w2 =  0.47\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.37 , w2 = -0.30\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.78 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4776\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5636\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5499\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5362\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.41 , w1 =  0.50 , w2 =  0.46\n",
            "neuron  1 : w0 =  0.16 , w1 = -0.38 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.77 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.42 , w1 =  0.49 , w2 =  0.47\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.39 , w2 = -0.30\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.78 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.42 , w1 =  0.50 , w2 =  0.47\n",
            "neuron  1 : w0 =  0.18 , w1 = -0.38 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.78 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.42 , w1 =  0.51 , w2 =  0.47\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.38 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.79 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4769\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5644\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5511\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5362\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.41 , w1 =  0.51 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.37 , w2 = -0.30\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.79 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.42 , w1 =  0.51 , w2 =  0.49\n",
            "neuron  1 : w0 =  0.18 , w1 = -0.38 , w2 = -0.29\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.80 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.42 , w1 =  0.50 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.39 , w2 = -0.30\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.79 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.42 , w1 =  0.51 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.18 , w1 = -0.38 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.79 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4765\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5653\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5525\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5361\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.42 , w1 =  0.52 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.38 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.80 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.42 , w1 =  0.53 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.18 , w1 = -0.37 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.80 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.43 , w1 =  0.52 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.37 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.80 , w2 =  0.73\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.43 , w1 =  0.52 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.18 , w1 = -0.38 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.79 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4759\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5662\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5536\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5358\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.44 , w1 =  0.52 , w2 =  0.47\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.37 , w2 = -0.32\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.80 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.44 , w1 =  0.52 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.38 , w2 = -0.32\n",
            "neuron  2 : w0 = -0.19 , w1 =  0.80 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.44 , w1 =  0.51 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.39 , w2 = -0.32\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.79 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.43 , w1 =  0.52 , w2 =  0.49\n",
            "neuron  1 : w0 =  0.18 , w1 = -0.39 , w2 = -0.32\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.80 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4751\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5668\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5545\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5353\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.43 , w1 =  0.52 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.39 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.23 , w1 =  0.78 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.43 , w1 =  0.53 , w2 =  0.49\n",
            "neuron  1 : w0 =  0.17 , w1 = -0.39 , w2 = -0.32\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.79 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.43 , w1 =  0.52 , w2 =  0.50\n",
            "neuron  1 : w0 =  0.18 , w1 = -0.40 , w2 = -0.31\n",
            "neuron  2 : w0 = -0.23 , w1 =  0.79 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.44 , w1 =  0.53 , w2 =  0.49\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.39 , w2 = -0.32\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.80 , w2 =  0.74\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4747\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5679\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5560\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5353\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.45 , w1 =  0.53 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.38 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.80 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.45 , w1 =  0.53 , w2 =  0.48\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.39 , w2 = -0.34\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.79 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.44 , w1 =  0.54 , w2 =  0.49\n",
            "neuron  1 : w0 =  0.18 , w1 = -0.38 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.23 , w1 =  0.80 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.45 , w1 =  0.53 , w2 =  0.50\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.39 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.80 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4740\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5690\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5571\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5351\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.45 , w1 =  0.52 , w2 =  0.50\n",
            "neuron  1 : w0 =  0.20 , w1 = -0.40 , w2 = -0.32\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.81 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.46 , w1 =  0.53 , w2 =  0.50\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.39 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.20 , w1 =  0.81 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.45 , w1 =  0.54 , w2 =  0.50\n",
            "neuron  1 : w0 =  0.20 , w1 = -0.39 , w2 = -0.32\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.82 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.45 , w1 =  0.54 , w2 =  0.50\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.39 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.80 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4730\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5696\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5580\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5346\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.45 , w1 =  0.53 , w2 =  0.50\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.40 , w2 = -0.34\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.79 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.44 , w1 =  0.54 , w2 =  0.51\n",
            "neuron  1 : w0 =  0.18 , w1 = -0.40 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.25 , w1 =  0.80 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.45 , w1 =  0.53 , w2 =  0.51\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.40 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.80 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.46 , w1 =  0.54 , w2 =  0.51\n",
            "neuron  1 : w0 =  0.20 , w1 = -0.40 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.23 , w1 =  0.81 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4726\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5708\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5596\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5345\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.45 , w1 =  0.54 , w2 =  0.51\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.40 , w2 = -0.34\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.80 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.46 , w1 =  0.53 , w2 =  0.51\n",
            "neuron  1 : w0 =  0.20 , w1 = -0.41 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.23 , w1 =  0.80 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.45 , w1 =  0.54 , w2 =  0.52\n",
            "neuron  1 : w0 =  0.19 , w1 = -0.41 , w2 = -0.33\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.81 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.46 , w1 =  0.54 , w2 =  0.51\n",
            "neuron  1 : w0 =  0.20 , w1 = -0.40 , w2 = -0.34\n",
            "neuron  2 : w0 = -0.23 , w1 =  0.81 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4719\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5718\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5611\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5344\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.55 , w2 =  0.51\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.39 , w2 = -0.35\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.82 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.48 , w1 =  0.54 , w2 =  0.51\n",
            "neuron  1 : w0 =  0.22 , w1 = -0.40 , w2 = -0.34\n",
            "neuron  2 : w0 = -0.21 , w1 =  0.82 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.55 , w2 =  0.52\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.39 , w2 = -0.34\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.83 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.55 , w2 =  0.52\n",
            "neuron  1 : w0 =  0.20 , w1 = -0.40 , w2 = -0.34\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.81 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4709\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5725\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5620\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5338\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.56 , w2 =  0.51\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.39 , w2 = -0.35\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.82 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.56 , w2 =  0.52\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.39 , w2 = -0.35\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.83 , w2 =  0.74\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.56 , w2 =  0.52\n",
            "neuron  1 : w0 =  0.20 , w1 = -0.40 , w2 = -0.35\n",
            "neuron  2 : w0 = -0.25 , w1 =  0.81 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.55 , w2 =  0.52\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.41 , w2 = -0.35\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.82 , w2 =  0.75\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4701\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5737\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5631\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5335\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.55 , w2 =  0.52\n",
            "neuron  1 : w0 =  0.20 , w1 = -0.41 , w2 = -0.35\n",
            "neuron  2 : w0 = -0.25 , w1 =  0.81 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.48 , w1 =  0.56 , w2 =  0.51\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.41 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.81 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.57 , w2 =  0.52\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.40 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.25 , w1 =  0.82 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.48 , w1 =  0.56 , w2 =  0.53\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.41 , w2 = -0.35\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.82 , w2 =  0.76\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4694\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5749\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5644\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5333\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.57 , w2 =  0.54\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.41 , w2 = -0.35\n",
            "neuron  2 : w0 = -0.25 , w1 =  0.83 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.47 , w1 =  0.56 , w2 =  0.53\n",
            "neuron  1 : w0 =  0.20 , w1 = -0.41 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.82 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.48 , w1 =  0.57 , w2 =  0.53\n",
            "neuron  1 : w0 =  0.21 , w1 = -0.40 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.26 , w1 =  0.82 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.48 , w1 =  0.56 , w2 =  0.53\n",
            "neuron  1 : w0 =  0.22 , w1 = -0.41 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.25 , w1 =  0.82 , w2 =  0.76\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4689\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5762\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5660\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5332\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.49 , w1 =  0.57 , w2 =  0.53\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.40 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.83 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.50 , w1 =  0.56 , w2 =  0.53\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.41 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.22 , w1 =  0.83 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.49 , w1 =  0.57 , w2 =  0.54\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.41 , w2 = -0.35\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.84 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.49 , w1 =  0.57 , w2 =  0.54\n",
            "neuron  1 : w0 =  0.22 , w1 = -0.42 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.25 , w1 =  0.83 , w2 =  0.76\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4678\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5770\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5669\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5325\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.50 , w1 =  0.58 , w2 =  0.53\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.41 , w2 = -0.37\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.83 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.49 , w1 =  0.58 , w2 =  0.54\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.40 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.25 , w1 =  0.84 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.50 , w1 =  0.58 , w2 =  0.55\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.41 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.84 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.49 , w1 =  0.57 , w2 =  0.55\n",
            "neuron  1 : w0 =  0.22 , w1 = -0.42 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.25 , w1 =  0.83 , w2 =  0.76\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4669\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5780\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5680\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5319\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.49 , w1 =  0.58 , w2 =  0.55\n",
            "neuron  1 : w0 =  0.22 , w1 = -0.42 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.84 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.50 , w1 =  0.59 , w2 =  0.55\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.41 , w2 = -0.37\n",
            "neuron  2 : w0 = -0.26 , w1 =  0.84 , w2 =  0.75\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.50 , w1 =  0.58 , w2 =  0.55\n",
            "neuron  1 : w0 =  0.24 , w1 = -0.41 , w2 = -0.36\n",
            "neuron  2 : w0 = -0.24 , w1 =  0.85 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.50 , w1 =  0.58 , w2 =  0.55\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.42 , w2 = -0.37\n",
            "neuron  2 : w0 = -0.26 , w1 =  0.83 , w2 =  0.76\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4662\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5790\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5693\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5313\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.50 , w1 =  0.58 , w2 =  0.55\n",
            "neuron  1 : w0 =  0.22 , w1 = -0.43 , w2 = -0.38\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.82 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.49 , w1 =  0.58 , w2 =  0.56\n",
            "neuron  1 : w0 =  0.22 , w1 = -0.43 , w2 = -0.37\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.83 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.50 , w1 =  0.58 , w2 =  0.56\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.43 , w2 = -0.37\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.83 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.51 , w1 =  0.58 , w2 =  0.56\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.43 , w2 = -0.37\n",
            "neuron  2 : w0 = -0.26 , w1 =  0.84 , w2 =  0.77\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4655\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5804\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5709\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5311\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.51 , w1 =  0.58 , w2 =  0.55\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.43 , w2 = -0.38\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.83 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.50 , w1 =  0.59 , w2 =  0.56\n",
            "neuron  1 : w0 =  0.22 , w1 = -0.43 , w2 = -0.38\n",
            "neuron  2 : w0 = -0.29 , w1 =  0.83 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.51 , w1 =  0.58 , w2 =  0.57\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.44 , w2 = -0.37\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.84 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.51 , w1 =  0.59 , w2 =  0.56\n",
            "neuron  1 : w0 =  0.24 , w1 = -0.43 , w2 = -0.38\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.84 , w2 =  0.77\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4649\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5817\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5726\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5308\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.51 , w1 =  0.59 , w2 =  0.56\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.44 , w2 = -0.39\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.83 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.52 , w1 =  0.58 , w2 =  0.57\n",
            "neuron  1 : w0 =  0.24 , w1 = -0.44 , w2 = -0.38\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.84 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.51 , w1 =  0.59 , w2 =  0.57\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.44 , w2 = -0.37\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.84 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.52 , w1 =  0.59 , w2 =  0.57\n",
            "neuron  1 : w0 =  0.24 , w1 = -0.43 , w2 = -0.38\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.85 , w2 =  0.77\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4641\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5828\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5742\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5305\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.52 , w1 =  0.59 , w2 =  0.56\n",
            "neuron  1 : w0 =  0.23 , w1 = -0.44 , w2 = -0.39\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.83 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.52 , w1 =  0.59 , w2 =  0.57\n",
            "neuron  1 : w0 =  0.24 , w1 = -0.45 , w2 = -0.38\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.84 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.53 , w1 =  0.59 , w2 =  0.56\n",
            "neuron  1 : w0 =  0.25 , w1 = -0.44 , w2 = -0.39\n",
            "neuron  2 : w0 = -0.26 , w1 =  0.84 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.52 , w1 =  0.60 , w2 =  0.57\n",
            "neuron  1 : w0 =  0.25 , w1 = -0.44 , w2 = -0.39\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.85 , w2 =  0.77\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4630\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5839\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5756\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5301\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.52 , w1 =  0.61 , w2 =  0.58\n",
            "neuron  1 : w0 =  0.24 , w1 = -0.43 , w2 = -0.38\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.86 , w2 =  0.76\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.52 , w1 =  0.60 , w2 =  0.59\n",
            "neuron  1 : w0 =  0.25 , w1 = -0.44 , w2 = -0.38\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.86 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.53 , w1 =  0.61 , w2 =  0.58\n",
            "neuron  1 : w0 =  0.26 , w1 = -0.43 , w2 = -0.38\n",
            "neuron  2 : w0 = -0.26 , w1 =  0.87 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.53 , w1 =  0.60 , w2 =  0.58\n",
            "neuron  1 : w0 =  0.25 , w1 = -0.44 , w2 = -0.39\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.85 , w2 =  0.77\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4622\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5849\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5769\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5294\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.52 , w1 =  0.61 , w2 =  0.58\n",
            "neuron  1 : w0 =  0.25 , w1 = -0.44 , w2 = -0.39\n",
            "neuron  2 : w0 = -0.29 , w1 =  0.86 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.52 , w1 =  0.61 , w2 =  0.58\n",
            "neuron  1 : w0 =  0.24 , w1 = -0.44 , w2 = -0.40\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.85 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.53 , w1 =  0.62 , w2 =  0.58\n",
            "neuron  1 : w0 =  0.25 , w1 = -0.44 , w2 = -0.40\n",
            "neuron  2 : w0 = -0.29 , w1 =  0.85 , w2 =  0.77\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.54 , w1 =  0.61 , w2 =  0.58\n",
            "neuron  1 : w0 =  0.26 , w1 = -0.44 , w2 = -0.40\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.86 , w2 =  0.78\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4614\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5864\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5785\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5290\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.53 , w1 =  0.61 , w2 =  0.58\n",
            "neuron  1 : w0 =  0.25 , w1 = -0.45 , w2 = -0.40\n",
            "neuron  2 : w0 = -0.29 , w1 =  0.85 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.54 , w1 =  0.61 , w2 =  0.57\n",
            "neuron  1 : w0 =  0.26 , w1 = -0.44 , w2 = -0.41\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.85 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.53 , w1 =  0.62 , w2 =  0.58\n",
            "neuron  1 : w0 =  0.25 , w1 = -0.44 , w2 = -0.41\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.86 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.54 , w1 =  0.61 , w2 =  0.59\n",
            "neuron  1 : w0 =  0.26 , w1 = -0.45 , w2 = -0.40\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.86 , w2 =  0.78\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4605\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5878\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5800\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5286\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.55 , w1 =  0.61 , w2 =  0.59\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.45 , w2 = -0.39\n",
            "neuron  2 : w0 = -0.27 , w1 =  0.87 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.55 , w1 =  0.61 , w2 =  0.59\n",
            "neuron  1 : w0 =  0.26 , w1 = -0.46 , w2 = -0.40\n",
            "neuron  2 : w0 = -0.29 , w1 =  0.86 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.55 , w1 =  0.61 , w2 =  0.59\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.45 , w2 = -0.41\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.86 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.55 , w1 =  0.62 , w2 =  0.59\n",
            "neuron  1 : w0 =  0.26 , w1 = -0.45 , w2 = -0.41\n",
            "neuron  2 : w0 = -0.29 , w1 =  0.87 , w2 =  0.78\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4593\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5887\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5814\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5279\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.55 , w1 =  0.61 , w2 =  0.60\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.46 , w2 = -0.40\n",
            "neuron  2 : w0 = -0.28 , w1 =  0.87 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.55 , w1 =  0.61 , w2 =  0.60\n",
            "neuron  1 : w0 =  0.26 , w1 = -0.47 , w2 = -0.41\n",
            "neuron  2 : w0 = -0.29 , w1 =  0.86 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.54 , w1 =  0.62 , w2 =  0.61\n",
            "neuron  1 : w0 =  0.26 , w1 = -0.46 , w2 = -0.40\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.87 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.55 , w1 =  0.63 , w2 =  0.60\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.45 , w2 = -0.41\n",
            "neuron  2 : w0 = -0.29 , w1 =  0.87 , w2 =  0.79\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4583\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5897\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5829\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5272\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.54 , w1 =  0.63 , w2 =  0.61\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.45 , w2 = -0.41\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.88 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.55 , w1 =  0.62 , w2 =  0.61\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.46 , w2 = -0.40\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.88 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.55 , w1 =  0.62 , w2 =  0.61\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.47 , w2 = -0.41\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.87 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.56 , w1 =  0.63 , w2 =  0.60\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.46 , w2 = -0.42\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.88 , w2 =  0.79\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4575\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5909\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5846\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5265\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.56 , w1 =  0.63 , w2 =  0.60\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.47 , w2 = -0.42\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.86 , w2 =  0.80\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.56 , w1 =  0.64 , w2 =  0.60\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.46 , w2 = -0.43\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.87 , w2 =  0.80\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.57 , w1 =  0.63 , w2 =  0.60\n",
            "neuron  1 : w0 =  0.28 , w1 = -0.46 , w2 = -0.42\n",
            "neuron  2 : w0 = -0.29 , w1 =  0.87 , w2 =  0.80\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.56 , w1 =  0.64 , w2 =  0.61\n",
            "neuron  1 : w0 =  0.28 , w1 = -0.46 , w2 = -0.42\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.88 , w2 =  0.79\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4563\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5921\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5860\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5259\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.56 , w1 =  0.64 , w2 =  0.62\n",
            "neuron  1 : w0 =  0.27 , w1 = -0.46 , w2 = -0.42\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.89 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.56 , w1 =  0.65 , w2 =  0.61\n",
            "neuron  1 : w0 =  0.28 , w1 = -0.45 , w2 = -0.43\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.89 , w2 =  0.78\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.57 , w1 =  0.64 , w2 =  0.62\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.46 , w2 = -0.42\n",
            "neuron  2 : w0 = -0.29 , w1 =  0.90 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.57 , w1 =  0.64 , w2 =  0.62\n",
            "neuron  1 : w0 =  0.28 , w1 = -0.47 , w2 = -0.43\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.88 , w2 =  0.79\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4554\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5934\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5873\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5250\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.57 , w1 =  0.63 , w2 =  0.62\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.47 , w2 = -0.42\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.89 , w2 =  0.80\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.57 , w1 =  0.64 , w2 =  0.63\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.47 , w2 = -0.42\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.90 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.57 , w1 =  0.65 , w2 =  0.62\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.46 , w2 = -0.42\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.90 , w2 =  0.79\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.57 , w1 =  0.65 , w2 =  0.62\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.47 , w2 = -0.43\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.89 , w2 =  0.80\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4542\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5944\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5886\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5241\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.58 , w1 =  0.64 , w2 =  0.63\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.48 , w2 = -0.43\n",
            "neuron  2 : w0 = -0.30 , w1 =  0.89 , w2 =  0.80\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.58 , w1 =  0.64 , w2 =  0.63\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.48 , w2 = -0.43\n",
            "neuron  2 : w0 = -0.32 , w1 =  0.88 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.57 , w1 =  0.64 , w2 =  0.63\n",
            "neuron  1 : w0 =  0.28 , w1 = -0.48 , w2 = -0.43\n",
            "neuron  2 : w0 = -0.33 , w1 =  0.89 , w2 =  0.80\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.58 , w1 =  0.65 , w2 =  0.63\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.47 , w2 = -0.44\n",
            "neuron  2 : w0 = -0.32 , w1 =  0.89 , w2 =  0.80\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4532\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5955\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5903\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5233\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.59 , w1 =  0.66 , w2 =  0.62\n",
            "neuron  1 : w0 =  0.30 , w1 = -0.47 , w2 = -0.44\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.90 , w2 =  0.80\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.58 , w1 =  0.66 , w2 =  0.62\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.47 , w2 = -0.45\n",
            "neuron  2 : w0 = -0.32 , w1 =  0.89 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.58 , w1 =  0.66 , w2 =  0.63\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.47 , w2 = -0.45\n",
            "neuron  2 : w0 = -0.33 , w1 =  0.89 , w2 =  0.80\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.58 , w1 =  0.66 , w2 =  0.63\n",
            "neuron  1 : w0 =  0.30 , w1 = -0.48 , w2 = -0.44\n",
            "neuron  2 : w0 = -0.32 , w1 =  0.90 , w2 =  0.80\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4521\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5969\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5915\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5225\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.58 , w1 =  0.66 , w2 =  0.63\n",
            "neuron  1 : w0 =  0.29 , w1 = -0.49 , w2 = -0.45\n",
            "neuron  2 : w0 = -0.33 , w1 =  0.89 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.59 , w1 =  0.66 , w2 =  0.62\n",
            "neuron  1 : w0 =  0.30 , w1 = -0.48 , w2 = -0.46\n",
            "neuron  2 : w0 = -0.32 , w1 =  0.89 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.60 , w1 =  0.65 , w2 =  0.63\n",
            "neuron  1 : w0 =  0.30 , w1 = -0.49 , w2 = -0.45\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.90 , w2 =  0.82\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.59 , w1 =  0.66 , w2 =  0.64\n",
            "neuron  1 : w0 =  0.30 , w1 = -0.48 , w2 = -0.45\n",
            "neuron  2 : w0 = -0.33 , w1 =  0.90 , w2 =  0.81\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4509\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5983\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5930\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5218\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.60 , w1 =  0.65 , w2 =  0.64\n",
            "neuron  1 : w0 =  0.31 , w1 = -0.49 , w2 = -0.44\n",
            "neuron  2 : w0 = -0.32 , w1 =  0.91 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.60 , w1 =  0.66 , w2 =  0.64\n",
            "neuron  1 : w0 =  0.31 , w1 = -0.48 , w2 = -0.45\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.91 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.60 , w1 =  0.67 , w2 =  0.64\n",
            "neuron  1 : w0 =  0.31 , w1 = -0.48 , w2 = -0.45\n",
            "neuron  2 : w0 = -0.32 , w1 =  0.92 , w2 =  0.80\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.59 , w1 =  0.67 , w2 =  0.64\n",
            "neuron  1 : w0 =  0.30 , w1 = -0.49 , w2 = -0.45\n",
            "neuron  2 : w0 = -0.33 , w1 =  0.91 , w2 =  0.81\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4496\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.5993\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5942\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5207\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.60 , w1 =  0.67 , w2 =  0.64\n",
            "neuron  1 : w0 =  0.31 , w1 = -0.48 , w2 = -0.46\n",
            "neuron  2 : w0 = -0.32 , w1 =  0.91 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.61 , w1 =  0.67 , w2 =  0.64\n",
            "neuron  1 : w0 =  0.32 , w1 = -0.49 , w2 = -0.45\n",
            "neuron  2 : w0 = -0.31 , w1 =  0.92 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.60 , w1 =  0.67 , w2 =  0.65\n",
            "neuron  1 : w0 =  0.32 , w1 = -0.48 , w2 = -0.45\n",
            "neuron  2 : w0 = -0.32 , w1 =  0.92 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.60 , w1 =  0.67 , w2 =  0.65\n",
            "neuron  1 : w0 =  0.31 , w1 = -0.49 , w2 = -0.46\n",
            "neuron  2 : w0 = -0.34 , w1 =  0.91 , w2 =  0.81\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4482\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6004\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5954\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5196\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.59 , w1 =  0.68 , w2 =  0.66\n",
            "neuron  1 : w0 =  0.31 , w1 = -0.49 , w2 = -0.46\n",
            "neuron  2 : w0 = -0.35 , w1 =  0.92 , w2 =  0.80\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.59 , w1 =  0.68 , w2 =  0.65\n",
            "neuron  1 : w0 =  0.30 , w1 = -0.50 , w2 = -0.46\n",
            "neuron  2 : w0 = -0.36 , w1 =  0.91 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.60 , w1 =  0.67 , w2 =  0.66\n",
            "neuron  1 : w0 =  0.31 , w1 = -0.50 , w2 = -0.46\n",
            "neuron  2 : w0 = -0.35 , w1 =  0.91 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.61 , w1 =  0.68 , w2 =  0.66\n",
            "neuron  1 : w0 =  0.31 , w1 = -0.50 , w2 = -0.46\n",
            "neuron  2 : w0 = -0.34 , w1 =  0.92 , w2 =  0.82\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4474\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6021\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5973\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5190\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.61 , w1 =  0.67 , w2 =  0.66\n",
            "neuron  1 : w0 =  0.32 , w1 = -0.50 , w2 = -0.46\n",
            "neuron  2 : w0 = -0.33 , w1 =  0.92 , w2 =  0.82\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.61 , w1 =  0.67 , w2 =  0.66\n",
            "neuron  1 : w0 =  0.31 , w1 = -0.51 , w2 = -0.46\n",
            "neuron  2 : w0 = -0.34 , w1 =  0.91 , w2 =  0.83\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.62 , w1 =  0.68 , w2 =  0.65\n",
            "neuron  1 : w0 =  0.32 , w1 = -0.50 , w2 = -0.47\n",
            "neuron  2 : w0 = -0.33 , w1 =  0.91 , w2 =  0.83\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.61 , w1 =  0.68 , w2 =  0.66\n",
            "neuron  1 : w0 =  0.32 , w1 = -0.50 , w2 = -0.47\n",
            "neuron  2 : w0 = -0.34 , w1 =  0.92 , w2 =  0.82\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4461\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6032\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.5988\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5180\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.62 , w1 =  0.69 , w2 =  0.65\n",
            "neuron  1 : w0 =  0.33 , w1 = -0.49 , w2 = -0.48\n",
            "neuron  2 : w0 = -0.34 , w1 =  0.93 , w2 =  0.82\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.61 , w1 =  0.70 , w2 =  0.66\n",
            "neuron  1 : w0 =  0.32 , w1 = -0.49 , w2 = -0.47\n",
            "neuron  2 : w0 = -0.35 , w1 =  0.93 , w2 =  0.81\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.61 , w1 =  0.69 , w2 =  0.66\n",
            "neuron  1 : w0 =  0.32 , w1 = -0.50 , w2 = -0.48\n",
            "neuron  2 : w0 = -0.36 , w1 =  0.92 , w2 =  0.82\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.62 , w1 =  0.69 , w2 =  0.67\n",
            "neuron  1 : w0 =  0.32 , w1 = -0.50 , w2 = -0.47\n",
            "neuron  2 : w0 = -0.35 , w1 =  0.93 , w2 =  0.82\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4449\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6048\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6002\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5171\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.62 , w1 =  0.69 , w2 =  0.66\n",
            "neuron  1 : w0 =  0.33 , w1 = -0.50 , w2 = -0.48\n",
            "neuron  2 : w0 = -0.34 , w1 =  0.93 , w2 =  0.83\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.63 , w1 =  0.69 , w2 =  0.67\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.50 , w2 = -0.47\n",
            "neuron  2 : w0 = -0.33 , w1 =  0.94 , w2 =  0.83\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.62 , w1 =  0.69 , w2 =  0.67\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.50 , w2 = -0.47\n",
            "neuron  2 : w0 = -0.34 , w1 =  0.94 , w2 =  0.82\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.62 , w1 =  0.69 , w2 =  0.67\n",
            "neuron  1 : w0 =  0.33 , w1 = -0.51 , w2 = -0.48\n",
            "neuron  2 : w0 = -0.35 , w1 =  0.93 , w2 =  0.83\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4436\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6060\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6014\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5159\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.63 , w1 =  0.70 , w2 =  0.67\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.50 , w2 = -0.49\n",
            "neuron  2 : w0 = -0.35 , w1 =  0.94 , w2 =  0.83\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.63 , w1 =  0.70 , w2 =  0.67\n",
            "neuron  1 : w0 =  0.33 , w1 = -0.51 , w2 = -0.49\n",
            "neuron  2 : w0 = -0.36 , w1 =  0.92 , w2 =  0.84\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.62 , w1 =  0.70 , w2 =  0.67\n",
            "neuron  1 : w0 =  0.33 , w1 = -0.51 , w2 = -0.49\n",
            "neuron  2 : w0 = -0.37 , w1 =  0.93 , w2 =  0.83\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.63 , w1 =  0.70 , w2 =  0.68\n",
            "neuron  1 : w0 =  0.33 , w1 = -0.51 , w2 = -0.48\n",
            "neuron  2 : w0 = -0.36 , w1 =  0.94 , w2 =  0.83\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4425\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6076\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6028\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5149\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.62 , w1 =  0.70 , w2 =  0.68\n",
            "neuron  1 : w0 =  0.33 , w1 = -0.51 , w2 = -0.48\n",
            "neuron  2 : w0 = -0.37 , w1 =  0.94 , w2 =  0.82\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.63 , w1 =  0.71 , w2 =  0.68\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.50 , w2 = -0.49\n",
            "neuron  2 : w0 = -0.36 , w1 =  0.95 , w2 =  0.82\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.63 , w1 =  0.71 , w2 =  0.68\n",
            "neuron  1 : w0 =  0.33 , w1 = -0.51 , w2 = -0.50\n",
            "neuron  2 : w0 = -0.37 , w1 =  0.94 , w2 =  0.83\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.63 , w1 =  0.70 , w2 =  0.68\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.52 , w2 = -0.49\n",
            "neuron  2 : w0 = -0.36 , w1 =  0.94 , w2 =  0.83\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4415\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6093\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6044\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5139\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.64 , w1 =  0.71 , w2 =  0.68\n",
            "neuron  1 : w0 =  0.35 , w1 = -0.51 , w2 = -0.50\n",
            "neuron  2 : w0 = -0.35 , w1 =  0.95 , w2 =  0.84\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.63 , w1 =  0.71 , w2 =  0.68\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.51 , w2 = -0.49\n",
            "neuron  2 : w0 = -0.37 , w1 =  0.95 , w2 =  0.83\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.63 , w1 =  0.71 , w2 =  0.68\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.52 , w2 = -0.50\n",
            "neuron  2 : w0 = -0.38 , w1 =  0.94 , w2 =  0.84\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.64 , w1 =  0.71 , w2 =  0.69\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.52 , w2 = -0.49\n",
            "neuron  2 : w0 = -0.37 , w1 =  0.95 , w2 =  0.84\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4403\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6109\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6058\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5129\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.63 , w1 =  0.71 , w2 =  0.70\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.52 , w2 = -0.49\n",
            "neuron  2 : w0 = -0.38 , w1 =  0.95 , w2 =  0.83\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.64 , w1 =  0.72 , w2 =  0.69\n",
            "neuron  1 : w0 =  0.35 , w1 = -0.51 , w2 = -0.50\n",
            "neuron  2 : w0 = -0.37 , w1 =  0.96 , w2 =  0.83\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.64 , w1 =  0.71 , w2 =  0.70\n",
            "neuron  1 : w0 =  0.36 , w1 = -0.52 , w2 = -0.49\n",
            "neuron  2 : w0 = -0.36 , w1 =  0.96 , w2 =  0.84\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.64 , w1 =  0.71 , w2 =  0.69\n",
            "neuron  1 : w0 =  0.35 , w1 = -0.53 , w2 = -0.50\n",
            "neuron  2 : w0 = -0.37 , w1 =  0.95 , w2 =  0.84\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4392\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6123\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6073\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5117\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.64 , w1 =  0.71 , w2 =  0.69\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.54 , w2 = -0.51\n",
            "neuron  2 : w0 = -0.39 , w1 =  0.94 , w2 =  0.85\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.65 , w1 =  0.72 , w2 =  0.69\n",
            "neuron  1 : w0 =  0.35 , w1 = -0.53 , w2 = -0.51\n",
            "neuron  2 : w0 = -0.38 , w1 =  0.94 , w2 =  0.85\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.64 , w1 =  0.72 , w2 =  0.69\n",
            "neuron  1 : w0 =  0.35 , w1 = -0.53 , w2 = -0.51\n",
            "neuron  2 : w0 = -0.39 , w1 =  0.95 , w2 =  0.84\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.65 , w1 =  0.72 , w2 =  0.70\n",
            "neuron  1 : w0 =  0.35 , w1 = -0.53 , w2 = -0.50\n",
            "neuron  2 : w0 = -0.38 , w1 =  0.96 , w2 =  0.85\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4381\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6140\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6090\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5108\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.64 , w1 =  0.72 , w2 =  0.71\n",
            "neuron  1 : w0 =  0.35 , w1 = -0.53 , w2 = -0.50\n",
            "neuron  2 : w0 = -0.39 , w1 =  0.96 , w2 =  0.84\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.64 , w1 =  0.72 , w2 =  0.71\n",
            "neuron  1 : w0 =  0.34 , w1 = -0.54 , w2 = -0.51\n",
            "neuron  2 : w0 = -0.40 , w1 =  0.95 , w2 =  0.84\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.65 , w1 =  0.73 , w2 =  0.70\n",
            "neuron  1 : w0 =  0.35 , w1 = -0.53 , w2 = -0.52\n",
            "neuron  2 : w0 = -0.39 , w1 =  0.96 , w2 =  0.85\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.65 , w1 =  0.72 , w2 =  0.71\n",
            "neuron  1 : w0 =  0.36 , w1 = -0.54 , w2 = -0.51\n",
            "neuron  2 : w0 = -0.38 , w1 =  0.96 , w2 =  0.85\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4371\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6157\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6109\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5100\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.65 , w1 =  0.72 , w2 =  0.71\n",
            "neuron  1 : w0 =  0.35 , w1 = -0.54 , w2 = -0.52\n",
            "neuron  2 : w0 = -0.40 , w1 =  0.95 , w2 =  0.86\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.66 , w1 =  0.72 , w2 =  0.71\n",
            "neuron  1 : w0 =  0.36 , w1 = -0.55 , w2 = -0.51\n",
            "neuron  2 : w0 = -0.39 , w1 =  0.95 , w2 =  0.86\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.67 , w1 =  0.72 , w2 =  0.71\n",
            "neuron  1 : w0 =  0.37 , w1 = -0.54 , w2 = -0.52\n",
            "neuron  2 : w0 = -0.38 , w1 =  0.96 , w2 =  0.86\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.66 , w1 =  0.73 , w2 =  0.71\n",
            "neuron  1 : w0 =  0.36 , w1 = -0.54 , w2 = -0.52\n",
            "neuron  2 : w0 = -0.39 , w1 =  0.97 , w2 =  0.86\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4357\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6172\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6126\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5090\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.65 , w1 =  0.73 , w2 =  0.72\n",
            "neuron  1 : w0 =  0.36 , w1 = -0.54 , w2 = -0.51\n",
            "neuron  2 : w0 = -0.40 , w1 =  0.97 , w2 =  0.85\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.65 , w1 =  0.73 , w2 =  0.72\n",
            "neuron  1 : w0 =  0.36 , w1 = -0.55 , w2 = -0.52\n",
            "neuron  2 : w0 = -0.41 , w1 =  0.96 , w2 =  0.85\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.66 , w1 =  0.74 , w2 =  0.71\n",
            "neuron  1 : w0 =  0.36 , w1 = -0.54 , w2 = -0.53\n",
            "neuron  2 : w0 = -0.40 , w1 =  0.97 , w2 =  0.86\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.66 , w1 =  0.73 , w2 =  0.72\n",
            "neuron  1 : w0 =  0.37 , w1 = -0.55 , w2 = -0.52\n",
            "neuron  2 : w0 = -0.39 , w1 =  0.97 , w2 =  0.86\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4347\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6190\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6145\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5080\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.67 , w1 =  0.73 , w2 =  0.72\n",
            "neuron  1 : w0 =  0.38 , w1 = -0.55 , w2 = -0.51\n",
            "neuron  2 : w0 = -0.38 , w1 =  0.98 , w2 =  0.86\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.68 , w1 =  0.73 , w2 =  0.72\n",
            "neuron  1 : w0 =  0.38 , w1 = -0.55 , w2 = -0.52\n",
            "neuron  2 : w0 = -0.38 , w1 =  0.98 , w2 =  0.87\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.68 , w1 =  0.73 , w2 =  0.72\n",
            "neuron  1 : w0 =  0.38 , w1 = -0.55 , w2 = -0.53\n",
            "neuron  2 : w0 = -0.39 , w1 =  0.97 , w2 =  0.87\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.67 , w1 =  0.74 , w2 =  0.72\n",
            "neuron  1 : w0 =  0.37 , w1 = -0.55 , w2 = -0.53\n",
            "neuron  2 : w0 = -0.40 , w1 =  0.98 , w2 =  0.86\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4332\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6201\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6159\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5066\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.66 , w1 =  0.74 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.37 , w1 = -0.55 , w2 = -0.52\n",
            "neuron  2 : w0 = -0.41 , w1 =  0.98 , w2 =  0.85\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.66 , w1 =  0.74 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.37 , w1 = -0.56 , w2 = -0.53\n",
            "neuron  2 : w0 = -0.42 , w1 =  0.97 , w2 =  0.86\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.67 , w1 =  0.74 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.37 , w1 = -0.56 , w2 = -0.52\n",
            "neuron  2 : w0 = -0.41 , w1 =  0.98 , w2 =  0.87\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.68 , w1 =  0.74 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.38 , w1 = -0.56 , w2 = -0.53\n",
            "neuron  2 : w0 = -0.40 , w1 =  0.98 , w2 =  0.87\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4322\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6218\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6178\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5056\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.67 , w1 =  0.74 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.37 , w1 = -0.56 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.42 , w1 =  0.97 , w2 =  0.88\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.67 , w1 =  0.75 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.37 , w1 = -0.56 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.43 , w1 =  0.98 , w2 =  0.87\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.67 , w1 =  0.75 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.38 , w1 = -0.55 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.42 , w1 =  0.98 , w2 =  0.87\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.68 , w1 =  0.75 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.38 , w1 = -0.56 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.41 , w1 =  0.99 , w2 =  0.87\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4311\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6236\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6197\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5046\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.69 , w1 =  0.75 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.39 , w1 = -0.55 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.40 , w1 =  0.99 , w2 =  0.88\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.69 , w1 =  0.75 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.40 , w1 = -0.56 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.39 , w1 =  1.00 , w2 =  0.88\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.69 , w1 =  0.75 , w2 =  0.73\n",
            "neuron  1 : w0 =  0.39 , w1 = -0.57 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.40 , w1 =  0.99 , w2 =  0.89\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.69 , w1 =  0.75 , w2 =  0.74\n",
            "neuron  1 : w0 =  0.39 , w1 = -0.57 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.41 , w1 =  0.99 , w2 =  0.88\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4296\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6248\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6210\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5030\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.69 , w1 =  0.75 , w2 =  0.74\n",
            "neuron  1 : w0 =  0.40 , w1 = -0.57 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.41 , w1 =  1.00 , w2 =  0.88\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.69 , w1 =  0.75 , w2 =  0.74\n",
            "neuron  1 : w0 =  0.39 , w1 = -0.58 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.42 , w1 =  0.99 , w2 =  0.89\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.70 , w1 =  0.75 , w2 =  0.74\n",
            "neuron  1 : w0 =  0.40 , w1 = -0.57 , w2 = -0.55\n",
            "neuron  2 : w0 = -0.41 , w1 =  0.99 , w2 =  0.89\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.69 , w1 =  0.76 , w2 =  0.74\n",
            "neuron  1 : w0 =  0.39 , w1 = -0.57 , w2 = -0.55\n",
            "neuron  2 : w0 = -0.42 , w1 =  1.00 , w2 =  0.88\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4282\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6261\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6227\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5017\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.70 , w1 =  0.75 , w2 =  0.75\n",
            "neuron  1 : w0 =  0.40 , w1 = -0.58 , w2 = -0.54\n",
            "neuron  2 : w0 = -0.41 , w1 =  1.00 , w2 =  0.89\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.70 , w1 =  0.75 , w2 =  0.75\n",
            "neuron  1 : w0 =  0.39 , w1 = -0.58 , w2 = -0.55\n",
            "neuron  2 : w0 = -0.42 , w1 =  0.99 , w2 =  0.89\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.70 , w1 =  0.76 , w2 =  0.74\n",
            "neuron  1 : w0 =  0.40 , w1 = -0.58 , w2 = -0.56\n",
            "neuron  2 : w0 = -0.41 , w1 =  1.00 , w2 =  0.90\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.70 , w1 =  0.76 , w2 =  0.75\n",
            "neuron  1 : w0 =  0.40 , w1 = -0.58 , w2 = -0.55\n",
            "neuron  2 : w0 = -0.43 , w1 =  1.00 , w2 =  0.89\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4268\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6274\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6243\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.5003\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.70 , w1 =  0.77 , w2 =  0.74\n",
            "neuron  1 : w0 =  0.41 , w1 = -0.57 , w2 = -0.56\n",
            "neuron  2 : w0 = -0.42 , w1 =  1.01 , w2 =  0.89\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.69 , w1 =  0.78 , w2 =  0.75\n",
            "neuron  1 : w0 =  0.40 , w1 = -0.57 , w2 = -0.56\n",
            "neuron  2 : w0 = -0.43 , w1 =  1.02 , w2 =  0.88\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.69 , w1 =  0.78 , w2 =  0.75\n",
            "neuron  1 : w0 =  0.40 , w1 = -0.57 , w2 = -0.57\n",
            "neuron  2 : w0 = -0.44 , w1 =  1.00 , w2 =  0.89\n",
            "----------------\n",
            "Current weights:\n",
            "neuron  0 : w0 =  0.70 , w1 =  0.77 , w2 =  0.76\n",
            "neuron  1 : w0 =  0.40 , w1 = -0.58 , w2 = -0.56\n",
            "neuron  2 : w0 = -0.43 , w1 =  1.01 , w2 =  0.89\n",
            "----------------\n",
            "x1 = -1.0 , x2 = -1.0 , y = 0.4255\n",
            "x1 = -1.0 , x2 =  1.0 , y = 0.6291\n",
            "x1 =  1.0 , x2 = -1.0 , y = 0.6258\n",
            "x1 =  1.0 , x2 =  1.0 , y = 0.4990\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "Overview\n",
        "The code models a basic neural network with a specific architecture designed to learn from a set of training examples. It employs backpropagation to adjust the network's weights based on the error between the predicted outputs and the actual outputs (ground truths).\n",
        "\n",
        "Initialization\n",
        "\n",
        "- `np.random.seed(3)`: Ensures reproducibility of results by setting the seed for random number generation.\n",
        "- `LEARNING_RATE`: Controls the size of the weight adjustments during the training process. A smaller learning rate might make the training more stable, but slower.\n",
        "- `index_list`: A list of indices representing the training data. Used to shuffle the order of training examples for each epoch to prevent the model from memorizing the sequence of inputs.\n",
        "- `x_train` and `y_train`: Arrays holding the training inputs (`x_train`) and their corresponding target outputs (`y_train`).\n",
        "\n",
        "Neuron Initialization: `neuron_w(input_count)`\n",
        "- Initializes weights for each neuron. The function creates an array of weights, with the first weight being set to 0 (representing the bias term) and the rest randomly initialized between -1 and 1.\n",
        "\n",
        "Forward Pass: `forward_pass(x)`\n",
        "- Computes the output of the network for a given input `x`.\n",
        "- The tanh activation function is used for the first two neurons, and a sigmoid function is applied for the output neuron.\n",
        "- This step calculates the network's prediction based on current weights.\n",
        "\n",
        "Backward Pass: `backward_pass(y_truth)`\n",
        "- Calculates the error gradients for each neuron starting from the output layer and moving backward through the network.\n",
        "- It uses the derivative of the loss function (assumed here to be the difference between the predicted and actual outputs) and the derivatives of the activation functions (tanh and sigmoid) to compute the gradients.\n",
        "- These gradients indicate how much and in what direction the weights should be adjusted to reduce the error.\n",
        "\n",
        "Adjust Weights: `adjust_weights(x)`\n",
        "- Updates the weights of the neurons based on the errors calculated during the backward pass.\n",
        "- The adjustments are made in the direction that is expected to reduce the error, scaled by the learning rate.\n",
        "\n",
        "Training Loop\n",
        "- Continues to perform forward passes, backward passes, and weight adjustments for each training example until the predictions correctly classify all training examples.\n",
        "- Shuffles the order of training examples in each epoch to improve generalization.\n",
        "- Uses a simple convergence criterion that checks whether all predictions match their corresponding targets.\n",
        "\n",
        "Auxiliary Functions\n",
        "- `show_learning()`: Prints the current weights of the neurons, providing insight into how the weights evolve over time.\n",
        "\n",
        "- Backpropagation is illustrated through the computation of gradients in `backward_pass` and their use in adjusting weights in `adjust_weights`.\n",
        "- The learning rate plays a crucial role in how significantly the weights are adjusted during training.\n",
        "- Activation functions (tanh and sigmoid) and their derivatives are crucial for calculating the gradients during the backward pass.\n",
        "- The training process involves iteratively updating the model's weights based on the errors computed until the model predictions sufficiently match the target outputs.\n",
        "\n"
      ],
      "metadata": {
        "id": "jb9Ht57-CBNk"
      }
    }
  ]
}