{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "! pip install conx -U"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from conx import Network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "net = Network(2, 2, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "inputs = [[0, 0],\n",
    "          [0, 1],\n",
    "          [1, 0],\n",
    "          [1, 1]]\n",
    "\n",
    "def xor(inputs):\n",
    "    a = inputs[0]\n",
    "    b = inputs[1]\n",
    "    return [int((a or b) and not(a and b))]\n",
    "\n",
    "net.set_inputs(inputs)\n",
    "net.set_target_function(xor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------\n",
      "Test:\n",
      "Input: [0, 0]\n",
      "Output: [ 0.74875197]\n",
      "\n",
      "Input: [0, 1]\n",
      "Output: [ 0.74896436]\n",
      "\n",
      "Input: [1, 0]\n",
      "Output: [ 0.74200833]\n",
      "\n",
      "Input: [1, 1]\n",
      "Output: [ 0.74127745]\n",
      "\n",
      "--------------------------------------------------\n",
      "Epoch: 0 TSS error: 1.23970035705 %correct: 0.0\n"
     ]
    }
   ],
   "source": [
    "net.test()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------\n",
      "Training for max trails: 5000 ...\n",
      "Epoch: 0 TSS error: 1.23970035705 %correct: 0.0\n",
      "Epoch: 500 TSS error: 0.990417151637 %correct: 0.0\n",
      "Epoch: 1000 TSS error: 0.92610197098 %correct: 0.0\n",
      "Epoch: 1500 TSS error: 0.72078861406 %correct: 0.0\n",
      "Epoch: 2000 TSS error: 0.19019734546 %correct: 0.0\n",
      "Epoch: 2500 TSS error: 0.05709380045 %correct: 0.0\n",
      "--------------------------------------------------\n",
      "Epoch: 2844 TSS error: 0.036218270215 %correct: 1.0\n",
      "CPU times: user 2.19 s, sys: 28 ms, total: 2.21 s\n",
      "Wall time: 2.18 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "net.train()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------\n",
      "Test:\n",
      "Input: [1, 0]\n",
      "Output: [ 0.90276211]\n",
      "\n",
      "Input: [0, 0]\n",
      "Output: [ 0.09716267]\n",
      "\n",
      "Input: [1, 1]\n",
      "Output: [ 0.08541021]\n",
      "\n",
      "Input: [0, 1]\n",
      "Output: [ 0.90000903]\n",
      "\n",
      "--------------------------------------------------\n",
      "Epoch: 2844 TSS error: 0.0361888890534 %correct: 1.0\n"
     ]
    }
   ],
   "source": [
    "net.test()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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