ML_Lab04_02_DataFromFiles.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading Data from Files with TF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(25, 3) \n",
      " [[ 73.  80.  75.]\n",
      " [ 93.  88.  93.]\n",
      " [ 89.  91.  90.]\n",
      " [ 96.  98. 100.]\n",
      " [ 73.  66.  70.]\n",
      " [ 53.  46.  55.]\n",
      " [ 69.  74.  77.]\n",
      " [ 47.  56.  60.]\n",
      " [ 87.  79.  90.]\n",
      " [ 79.  70.  88.]\n",
      " [ 69.  70.  73.]\n",
      " [ 70.  65.  74.]\n",
      " [ 93.  95.  91.]\n",
      " [ 79.  80.  73.]\n",
      " [ 70.  73.  78.]\n",
      " [ 93.  89.  96.]\n",
      " [ 78.  75.  68.]\n",
      " [ 81.  90.  93.]\n",
      " [ 88.  92.  86.]\n",
      " [ 78.  83.  77.]\n",
      " [ 82.  86.  90.]\n",
      " [ 86.  82.  89.]\n",
      " [ 78.  83.  85.]\n",
      " [ 76.  83.  71.]\n",
      " [ 96.  93.  95.]] \n",
      "Length:  25\n",
      "(25, 1) \n",
      " [[152.]\n",
      " [185.]\n",
      " [180.]\n",
      " [196.]\n",
      " [142.]\n",
      " [101.]\n",
      " [149.]\n",
      " [115.]\n",
      " [175.]\n",
      " [164.]\n",
      " [141.]\n",
      " [141.]\n",
      " [184.]\n",
      " [152.]\n",
      " [148.]\n",
      " [192.]\n",
      " [147.]\n",
      " [183.]\n",
      " [177.]\n",
      " [159.]\n",
      " [177.]\n",
      " [175.]\n",
      " [175.]\n",
      " [149.]\n",
      " [192.]]\n",
      "WARNING:tensorflow:From C:\\Users\\iknee\\Anaconda3\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n",
      "0 Cost:  21027.0 \n",
      "Prediction:\n",
      " [[22.048063 ]\n",
      " [21.619772 ]\n",
      " [24.096693 ]\n",
      " [22.29302  ]\n",
      " [18.633902 ]\n",
      " [ 7.2669735]\n",
      " [12.33103  ]\n",
      " [ 3.150511 ]\n",
      " [14.347944 ]\n",
      " [ 4.2534237]\n",
      " [14.485708 ]\n",
      " [10.678068 ]\n",
      " [28.80464  ]\n",
      " [29.298803 ]\n",
      " [11.237837 ]\n",
      " [18.646544 ]\n",
      " [31.189451 ]\n",
      " [13.344656 ]\n",
      " [28.841742 ]\n",
      " [25.66281  ]\n",
      " [15.084753 ]\n",
      " [16.798368 ]\n",
      " [15.924551 ]\n",
      " [31.36112  ]\n",
      " [24.986364 ]]\n",
      "100 Cost:  88.71045 \n",
      "Prediction:\n",
      " [[157.79552 ]\n",
      " [185.16716 ]\n",
      " [185.02408 ]\n",
      " [197.75952 ]\n",
      " [143.2941  ]\n",
      " [ 99.535034]\n",
      " [143.86804 ]\n",
      " [100.923935]\n",
      " [167.5352  ]\n",
      " [146.62894 ]\n",
      " [141.12161 ]\n",
      " [135.79485 ]\n",
      " [194.86229 ]\n",
      " [167.07516 ]\n",
      " [143.46056 ]\n",
      " [184.76736 ]\n",
      " [162.27657 ]\n",
      " [171.24031 ]\n",
      " [187.06117 ]\n",
      " [167.22626 ]\n",
      " [169.31621 ]\n",
      " [170.4023  ]\n",
      " [162.88062 ]\n",
      " [167.75441 ]\n",
      " [194.32646 ]]\n",
      "200 Cost:  82.28211 \n",
      "Prediction:\n",
      " [[157.52545]\n",
      " [185.21312]\n",
      " [184.86227]\n",
      " [197.7795 ]\n",
      " [143.25938]\n",
      " [ 99.85554]\n",
      " [144.07088]\n",
      " [101.32598]\n",
      " [167.90384]\n",
      " [147.43724]\n",
      " [141.22595]\n",
      " [136.13652]\n",
      " [194.50058]\n",
      " [166.51862]\n",
      " [143.7414 ]\n",
      " [184.96681]\n",
      " [161.62318]\n",
      " [171.5218 ]\n",
      " [186.62805]\n",
      " [166.83426]\n",
      " [169.5374 ]\n",
      " [170.6133 ]\n",
      " [163.00415]\n",
      " [167.0283 ]\n",
      " [194.22336]]\n",
      "300 Cost:  76.37185 \n",
      "Prediction:\n",
      " [[157.2686 ]\n",
      " [185.25523]\n",
      " [184.70755]\n",
      " [197.79916]\n",
      " [143.22343]\n",
      " [100.16049]\n",
      " [144.26712]\n",
      " [101.71486]\n",
      " [168.25456]\n",
      " [148.20953]\n",
      " [141.32632]\n",
      " [136.46245]\n",
      " [194.15399]\n",
      " [165.98476]\n",
      " [144.01178]\n",
      " [185.15657]\n",
      " [160.99501]\n",
      " [171.7949 ]\n",
      " [186.21368]\n",
      " [166.45972]\n",
      " [169.7509 ]\n",
      " [170.81416]\n",
      " [163.12428]\n",
      " [166.33385]\n",
      " [194.12317]]\n",
      "400 Cost:  70.93686 \n",
      "Prediction:\n",
      " [[157.02443]\n",
      " [185.29378]\n",
      " [184.55959]\n",
      " [197.81857]\n",
      " [143.1864 ]\n",
      " [100.45062]\n",
      " [144.45705]\n",
      " [102.09103]\n",
      " [168.58824]\n",
      " [148.94743]\n",
      " [141.42284]\n",
      " [136.77339]\n",
      " [193.82191]\n",
      " [165.47263]\n",
      " [144.27216]\n",
      " [185.33714]\n",
      " [160.39104]\n",
      " [172.05995]\n",
      " [185.81723]\n",
      " [166.10187]\n",
      " [169.957  ]\n",
      " [171.00542]\n",
      " [163.24117]\n",
      " [165.66971]\n",
      " [194.0258 ]]\n",
      "500 Cost:  65.93819 \n",
      "Prediction:\n",
      " [[156.79225]\n",
      " [185.3289 ]\n",
      " [184.41808]\n",
      " [197.83768]\n",
      " [143.14839]\n",
      " [100.72662]\n",
      " [144.64084]\n",
      " [102.45494]\n",
      " [168.90562]\n",
      " [149.65242]\n",
      " [141.51566]\n",
      " [137.06999]\n",
      " [193.50374]\n",
      " [164.98135]\n",
      " [144.5229 ]\n",
      " [185.50893]\n",
      " [159.81024]\n",
      " [172.31715]\n",
      " [185.43794]\n",
      " [165.75995]\n",
      " [170.15596]\n",
      " [171.18742]\n",
      " [163.35483]\n",
      " [165.03453]\n",
      " [193.93121]]\n",
      "600 Cost:  61.339928 \n",
      "Prediction:\n",
      " [[156.5716 ]\n",
      " [185.36086]\n",
      " [184.28278]\n",
      " [197.85648]\n",
      " [143.10953]\n",
      " [100.98915]\n",
      " [144.81873]\n",
      " [102.80703]\n",
      " [169.20749]\n",
      " [150.32596]\n",
      " [141.60495]\n",
      " [137.3529 ]\n",
      " [193.19884]\n",
      " [164.51004]\n",
      " [144.76439]\n",
      " [185.67233]\n",
      " [159.25174]\n",
      " [172.56676]\n",
      " [185.07509]\n",
      " [165.43329]\n",
      " [170.34808]\n",
      " [171.36067]\n",
      " [163.4654 ]\n",
      " [164.42706]\n",
      " [193.83926]]\n",
      "700 Cost:  57.1092 \n",
      "Prediction:\n",
      " [[156.3619  ]\n",
      " [185.3898  ]\n",
      " [184.1534  ]\n",
      " [197.87503 ]\n",
      " [143.06987 ]\n",
      " [101.238815]\n",
      " [144.99092 ]\n",
      " [103.14772 ]\n",
      " [169.49452 ]\n",
      " [150.96945 ]\n",
      " [141.69086 ]\n",
      " [137.62274 ]\n",
      " [192.90668 ]\n",
      " [164.05786 ]\n",
      " [144.99701 ]\n",
      " [185.82774 ]\n",
      " [158.71461 ]\n",
      " [172.80905 ]\n",
      " [184.72792 ]\n",
      " [165.12123 ]\n",
      " [170.53358 ]\n",
      " [171.52556 ]\n",
      " [163.57298 ]\n",
      " [163.84612 ]\n",
      " [193.74994 ]]\n",
      "800 Cost:  53.21599 \n",
      "Prediction:\n",
      " [[156.16264]\n",
      " [185.41588]\n",
      " [184.0297 ]\n",
      " [197.89325]\n",
      " [143.02956]\n",
      " [101.47621]\n",
      " [145.15764]\n",
      " [103.47739]\n",
      " [169.76746]\n",
      " [151.58418]\n",
      " [141.7735 ]\n",
      " [137.8801 ]\n",
      " [192.62671]\n",
      " [163.62404]\n",
      " [145.22107]\n",
      " [185.97554]\n",
      " [158.19803]\n",
      " [173.0442 ]\n",
      " [184.39578]\n",
      " [164.8231 ]\n",
      " [170.71274]\n",
      " [171.68243]\n",
      " [163.67764]\n",
      " [163.29051]\n",
      " [193.66309]]\n",
      "900 Cost:  49.632496 \n",
      "Prediction:\n",
      " [[155.9733 ]\n",
      " [185.43927]\n",
      " [183.91136]\n",
      " [197.9112 ]\n",
      " [142.98865]\n",
      " [101.70193]\n",
      " [145.319  ]\n",
      " [103.79644]\n",
      " [170.02692]\n",
      " [152.17148]\n",
      " [141.85301]\n",
      " [138.12552]\n",
      " [192.35841]\n",
      " [163.20776]\n",
      " [145.43692]\n",
      " [186.11606]\n",
      " [157.70113]\n",
      " [173.27248]\n",
      " [184.078  ]\n",
      " [164.53827]\n",
      " [170.88576]\n",
      " [171.8317 ]\n",
      " [163.77945]\n",
      " [162.75914]\n",
      " [193.57867]]\n",
      "1000 Cost:  46.333565 \n",
      "Prediction:\n",
      " [[155.79349]\n",
      " [185.46011]\n",
      " [183.79823]\n",
      " [197.92883]\n",
      " [142.94722]\n",
      " [101.91647]\n",
      " [145.47525]\n",
      " [104.10523]\n",
      " [170.27351]\n",
      " [152.7325 ]\n",
      " [141.92949]\n",
      " [138.35954]\n",
      " [192.10132]\n",
      " [162.8083 ]\n",
      " [145.64488]\n",
      " [186.24965]\n",
      " [157.22313]\n",
      " [173.49408]\n",
      " [183.77399]\n",
      " [164.26619]\n",
      " [171.05286]\n",
      " [171.97368]\n",
      " [163.87852]\n",
      " [162.25096]\n",
      " [193.49664]]\n",
      "1100 Cost:  43.295918 \n",
      "Prediction:\n",
      " [[155.62274 ]\n",
      " [185.4786  ]\n",
      " [183.69008 ]\n",
      " [197.9462  ]\n",
      " [142.90541 ]\n",
      " [102.12039 ]\n",
      " [145.62657 ]\n",
      " [104.404144]\n",
      " [170.50789 ]\n",
      " [153.26843 ]\n",
      " [142.00313 ]\n",
      " [138.5827  ]\n",
      " [191.85492 ]\n",
      " [162.42502 ]\n",
      " [145.84529 ]\n",
      " [186.37662 ]\n",
      " [156.76332 ]\n",
      " [173.70926 ]\n",
      " [183.48312 ]\n",
      " [164.00629 ]\n",
      " [171.21431 ]\n",
      " [172.10875 ]\n",
      " [163.97493 ]\n",
      " [161.76497 ]\n",
      " [193.4169  ]]\n",
      "1200 Cost:  40.49828 \n",
      "Prediction:\n",
      " [[155.46057]\n",
      " [185.49483]\n",
      " [183.5866 ]\n",
      " [197.96324]\n",
      " [142.86319]\n",
      " [102.31417]\n",
      " [145.77309]\n",
      " [104.69349]\n",
      " [170.73055]\n",
      " [153.78036]\n",
      " [142.07396]\n",
      " [138.79547]\n",
      " [191.61873]\n",
      " [162.05719]\n",
      " [146.03838]\n",
      " [186.49728]\n",
      " [156.3209 ]\n",
      " [173.91815]\n",
      " [183.2048 ]\n",
      " [163.75798]\n",
      " [171.37022]\n",
      " [172.23715]\n",
      " [164.0687 ]\n",
      " [161.30019]\n",
      " [193.33936]]\n",
      "1300 Cost:  37.921116 \n",
      "Prediction:\n",
      " [[155.30664]\n",
      " [185.50896]\n",
      " [183.48769]\n",
      " [197.98003]\n",
      " [142.82072]\n",
      " [102.49828]\n",
      " [145.915  ]\n",
      " [104.97362]\n",
      " [170.9421 ]\n",
      " [154.26936]\n",
      " [142.14214]\n",
      " [138.99832]\n",
      " [191.39238]\n",
      " [161.70415]\n",
      " [146.22444]\n",
      " [186.61194]\n",
      " [155.89523]\n",
      " [174.12097]\n",
      " [182.93854]\n",
      " [163.5208 ]\n",
      " [171.5209 ]\n",
      " [172.35927]\n",
      " [164.15994]\n",
      " [160.85568]\n",
      " [193.26398]]\n",
      "1400 Cost:  35.546516 \n",
      "Prediction:\n",
      " [[155.16054]\n",
      " [185.5211 ]\n",
      " [183.3931 ]\n",
      " [197.99655]\n",
      " [142.77803]\n",
      " [102.67319]\n",
      " [146.05244]\n",
      " [105.24484]\n",
      " [171.14305]\n",
      " [154.7365 ]\n",
      " [142.20778]\n",
      " [139.19173]\n",
      " [191.17546]\n",
      " [161.36537]\n",
      " [146.4038 ]\n",
      " [186.7209 ]\n",
      " [155.48564]\n",
      " [174.31795]\n",
      " [182.6838 ]\n",
      " [163.29427]\n",
      " [171.66649]\n",
      " [172.4754 ]\n",
      " [164.24875]\n",
      " [160.43057]\n",
      " [193.1907 ]]\n",
      "1500 Cost:  33.35809 \n",
      "Prediction:\n",
      " [[155.02193 ]\n",
      " [185.53139 ]\n",
      " [183.30264 ]\n",
      " [198.01274 ]\n",
      " [142.7352  ]\n",
      " [102.839294]\n",
      " [146.18555 ]\n",
      " [105.50746 ]\n",
      " [171.33385 ]\n",
      " [155.18266 ]\n",
      " [142.27092 ]\n",
      " [139.37605 ]\n",
      " [190.9675  ]\n",
      " [161.04016 ]\n",
      " [146.57666 ]\n",
      " [186.82434 ]\n",
      " [155.09146 ]\n",
      " [174.5092  ]\n",
      " [182.44006 ]\n",
      " [163.07785 ]\n",
      " [171.80717 ]\n",
      " [172.58574 ]\n",
      " [164.33514 ]\n",
      " [160.02402 ]\n",
      " [193.11945 ]]\n",
      "1600 Cost:  31.340765 \n",
      "Prediction:\n",
      " [[154.8904 ]\n",
      " [185.5399 ]\n",
      " [183.21616]\n",
      " [198.02866]\n",
      " [142.69223]\n",
      " [102.99703]\n",
      " [146.31453]\n",
      " [105.76177]\n",
      " [171.51505]\n",
      " [155.60881]\n",
      " [142.33174]\n",
      " [139.55176]\n",
      " [190.76819]\n",
      " [160.72803]\n",
      " [146.74329]\n",
      " [186.92262]\n",
      " [154.7121 ]\n",
      " [174.69495]\n",
      " [182.20686]\n",
      " [162.87117]\n",
      " [171.94312]\n",
      " [172.69066]\n",
      " [164.41925]\n",
      " [159.63524]\n",
      " [193.05019]]\n",
      "1700 Cost:  29.480663 \n",
      "Prediction:\n",
      " [[154.76564 ]\n",
      " [185.54677 ]\n",
      " [183.13345 ]\n",
      " [198.0443  ]\n",
      " [142.64923 ]\n",
      " [103.14677 ]\n",
      " [146.43945 ]\n",
      " [106.008064]\n",
      " [171.68703 ]\n",
      " [156.01582 ]\n",
      " [142.39027 ]\n",
      " [139.71922 ]\n",
      " [190.5771  ]\n",
      " [160.42839 ]\n",
      " [146.90393 ]\n",
      " [187.01591 ]\n",
      " [154.34697 ]\n",
      " [174.87537 ]\n",
      " [181.98373 ]\n",
      " [162.67377 ]\n",
      " [172.07454 ]\n",
      " [172.79033 ]\n",
      " [164.5011  ]\n",
      " [159.26341 ]\n",
      " [192.98282 ]]\n",
      "1800 Cost:  27.765226 \n",
      "Prediction:\n",
      " [[154.64735 ]\n",
      " [185.55212 ]\n",
      " [183.05437 ]\n",
      " [198.05966 ]\n",
      " [142.60625 ]\n",
      " [103.288925]\n",
      " [146.56053 ]\n",
      " [106.24663 ]\n",
      " [171.85027 ]\n",
      " [156.40456 ]\n",
      " [142.44666 ]\n",
      " [139.87881 ]\n",
      " [190.39398 ]\n",
      " [160.14076 ]\n",
      " [147.05882 ]\n",
      " [187.10449 ]\n",
      " [153.99553 ]\n",
      " [175.0506  ]\n",
      " [181.77028 ]\n",
      " [162.48523 ]\n",
      " [172.20155 ]\n",
      " [172.88503 ]\n",
      " [164.58075 ]\n",
      " [158.90784 ]\n",
      " [192.9173  ]]\n",
      "1900 Cost:  26.182701 \n",
      "Prediction:\n",
      " [[154.53522]\n",
      " [185.55606]\n",
      " [182.97878]\n",
      " [198.07474]\n",
      " [142.5633 ]\n",
      " [103.42381]\n",
      " [146.67784]\n",
      " [106.4777 ]\n",
      " [172.00516]\n",
      " [156.77583]\n",
      " [142.50093]\n",
      " [140.03091]\n",
      " [190.2184 ]\n",
      " [159.86464]\n",
      " [147.20818]\n",
      " [187.18857]\n",
      " [153.65724]\n",
      " [175.22084]\n",
      " [181.56604]\n",
      " [162.30518]\n",
      " [172.32436]\n",
      " [172.97499]\n",
      " [164.65828]\n",
      " [158.56778]\n",
      " [192.8536 ]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2000 Cost:  24.722485 \n",
      "Prediction:\n",
      " [[154.42894 ]\n",
      " [185.5586  ]\n",
      " [182.90646 ]\n",
      " [198.08955 ]\n",
      " [142.52043 ]\n",
      " [103.551796]\n",
      " [146.79152 ]\n",
      " [106.70152 ]\n",
      " [172.15207 ]\n",
      " [157.13037 ]\n",
      " [142.5532  ]\n",
      " [140.17581 ]\n",
      " [190.05006 ]\n",
      " [159.59953 ]\n",
      " [147.35217 ]\n",
      " [187.26833 ]\n",
      " [153.3315  ]\n",
      " [175.3862  ]\n",
      " [181.3706  ]\n",
      " [162.1332  ]\n",
      " [172.44307 ]\n",
      " [173.06042 ]\n",
      " [164.7337  ]\n",
      " [158.24257 ]\n",
      " [192.79166 ]]\n",
      "Your score will be  [[181.73279]]\n",
      "Other scores will be  [[145.86269]\n",
      " [187.2313 ]]\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "tf.set_random_seed(777)  # for reproducibility\n",
    "\n",
    "xy = np.loadtxt('data-01-test-score.csv', delimiter=',', dtype=np.float32)\n",
    "x_data = xy[:, 0:-1]\n",
    "y_data = xy[:, [-1]]\n",
    "\n",
    "# Make sure the shape and data are OK\n",
    "print(x_data.shape, \"\\n\", x_data, \"\\nLength: \", len(x_data))\n",
    "print(y_data.shape, \"\\n\", y_data)\n",
    "\n",
    "# placeholders for a tensor that will be always fed.\n",
    "X = tf.placeholder(tf.float32, shape=[None, 3])\n",
    "Y = tf.placeholder(tf.float32, shape=[None, 1])\n",
    "\n",
    "W = tf.Variable(tf.random_normal([3, 1]), name='weight')\n",
    "b = tf.Variable(tf.random_normal([1]), name='bias')\n",
    "\n",
    "# Hypothesis\n",
    "hypothesis = tf.matmul(X, W) + b\n",
    "\n",
    "# Simplified cost/loss function\n",
    "cost = tf.reduce_mean(tf.square(hypothesis - Y))\n",
    "\n",
    "# Minimize\n",
    "optimizer = tf.train.GradientDescentOptimizer(learning_rate=1e-5)\n",
    "train = optimizer.minimize(cost)\n",
    "\n",
    "# Launch the graph in a session\n",
    "sess = tf.Session()\n",
    "# Initialize global variables in the graph\n",
    "sess.run(tf.global_variables_initializer())\n",
    "# Set up feed_dict variables inside the loop\n",
    "for step in range(2001):\n",
    "    cost_val, hy_val, _ = sess.run(\n",
    "        [cost, hypothesis, train], feed_dict={X: x_data, Y: y_data})\n",
    "    if step % 100 == 0:\n",
    "        print(step, \"Cost: \", cost_val,\n",
    "             \"\\nPrediction:\\n\", hy_val)\n",
    "        \n",
    "# Ask my score\n",
    "print(\"Your score will be \", sess.run(hypothesis, \n",
    "                                      feed_dict={X: [[100, 70, 101]]}))\n",
    "print(\"Other scores will be \", sess.run(hypothesis, \n",
    "                                       feed_dict={X: [[60, 70, 110], [90, 100, 80]]}))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Queue Runners"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "한번에 메모리에 올리기엔 너무 클 때가 있다. 그때 사용.  \n",
    "  \n",
    "1) Filenames  \n",
    "2) Filename Queue  \n",
    "3) Example Queue  "
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "#1st step:  \n",
    "  filename_queue = tf.train.string_input_producer(  \n",
    "    ['data-01-test-score.csv', 'data-02-test-score.csv', ...],   \n",
    "    shuffle=False, name='filename_queue')\n",
    "\n",
    "#2nd step:  \n",
    "  reader = tf.TextLineReader()  \n",
    "  key, value = reader.read(filename_queue)  \n",
    "    \n",
    "#3rd step:  \n",
    "  record_defaults = [[0.], [0.], [0.],[0.]]  \n",
    "  xy = tf.decode_csv(value, record_defaults=record_defaults)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## tf.train.batch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "#collect batches of csv in\n",
    "train_x_batch, train_y_batch = \\\n",
    "    tf.train.batch([xy[0:-1], xy[-1:]], batch_size=10)\n",
    "\n",
    "sess = tf.Sesstion()\n",
    "...\n",
    "\n",
    "#Start populating the fileneame queue\n",
    "coord = tf.train.Coordinator()\n",
    "threads = tf.train.start_queue_runners(sess=sess, coord=coord)\n",
    "\n",
    "for step in range(2001):\n",
    "    x_batch, y_batch = sess.run([train_x_batch, train_y_batch])\n",
    "    ...\n",
    "    \n",
    "coord.request_stop()\n",
    "coord.join(threads)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-5-711f7f46421b>:15: batch (from tensorflow.python.training.input) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Queue-based input pipelines have been replaced by `tf.data`. Use `tf.data.Dataset.batch(batch_size)` (or `padded_batch(...)` if `dynamic_pad=True`).\n",
      "WARNING:tensorflow:From <ipython-input-5-711f7f46421b>:41: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "To construct input pipelines, use the `tf.data` module.\n",
      "0 Cost:  63.133812 \n",
      "Prediction:\n",
      " [[143.5054 ]\n",
      " [187.99063]\n",
      " [176.89337]\n",
      " [196.49518]\n",
      " [144.11916]\n",
      " [114.12243]\n",
      " [148.54465]\n",
      " [111.67695]\n",
      " [184.05104]\n",
      " [180.44626]]\n",
      "100 Cost:  73.35393 \n",
      "Prediction:\n",
      " [[145.91956]\n",
      " [190.30627]\n",
      " [179.48752]\n",
      " [199.1922 ]\n",
      " [145.84529]\n",
      " [115.12868]\n",
      " [150.53722]\n",
      " [113.13476]\n",
      " [185.92258]\n",
      " [181.84398]]\n",
      "200 Cost:  67.941444 \n",
      "Prediction:\n",
      " [[146.22487]\n",
      " [190.11105]\n",
      " [179.59492]\n",
      " [199.18695]\n",
      " [145.65746]\n",
      " [114.73584]\n",
      " [150.50922]\n",
      " [113.09701]\n",
      " [185.46034]\n",
      " [181.09534]]\n",
      "300 Cost:  62.968456 \n",
      "Prediction:\n",
      " [[146.51732]\n",
      " [189.92352]\n",
      " [179.69751]\n",
      " [199.1822 ]\n",
      " [145.47652]\n",
      " [114.35965]\n",
      " [150.48366]\n",
      " [113.06328]\n",
      " [185.01772]\n",
      " [180.37964]]\n",
      "400 Cost:  58.398537 \n",
      "Prediction:\n",
      " [[146.79749]\n",
      " [189.74338]\n",
      " [179.7955 ]\n",
      " [199.17795]\n",
      " [145.30217]\n",
      " [113.9994 ]\n",
      " [150.46043]\n",
      " [113.03334]\n",
      " [184.59383]\n",
      " [179.69547]]\n",
      "500 Cost:  54.19825 \n",
      "Prediction:\n",
      " [[147.06587]\n",
      " [189.57031]\n",
      " [179.88908]\n",
      " [199.17413]\n",
      " [145.13417]\n",
      " [113.6544 ]\n",
      " [150.43939]\n",
      " [113.00699]\n",
      " [184.18788]\n",
      " [179.0414 ]]\n",
      "600 Cost:  50.336956 \n",
      "Prediction:\n",
      " [[147.32298 ]\n",
      " [189.40402 ]\n",
      " [179.97847 ]\n",
      " [199.17075 ]\n",
      " [144.97224 ]\n",
      " [113.324005]\n",
      " [150.42041 ]\n",
      " [112.983986]\n",
      " [183.7991  ]\n",
      " [178.4161  ]]\n",
      "700 Cost:  46.786564 \n",
      "Prediction:\n",
      " [[147.56932]\n",
      " [189.24422]\n",
      " [180.06383]\n",
      " [199.16777]\n",
      " [144.81621]\n",
      " [113.00755]\n",
      " [150.40335]\n",
      " [112.96414]\n",
      " [183.42676]\n",
      " [177.81831]]\n",
      "800 Cost:  43.52141 \n",
      "Prediction:\n",
      " [[147.80534]\n",
      " [189.09067]\n",
      " [180.14537]\n",
      " [199.16519]\n",
      " [144.66579]\n",
      " [112.70446]\n",
      " [150.38814]\n",
      " [112.94725]\n",
      " [183.07011]\n",
      " [177.2468 ]]\n",
      "900 Cost:  40.517914 \n",
      "Prediction:\n",
      " [[148.03151 ]\n",
      " [188.9431  ]\n",
      " [180.22325 ]\n",
      " [199.16295 ]\n",
      " [144.52077 ]\n",
      " [112.41414 ]\n",
      " [150.37463 ]\n",
      " [112.933136]\n",
      " [182.7285  ]\n",
      " [176.7004  ]]\n",
      "1000 Cost:  37.754547 \n",
      "Prediction:\n",
      " [[148.24821 ]\n",
      " [188.80124 ]\n",
      " [180.29764 ]\n",
      " [199.16103 ]\n",
      " [144.38095 ]\n",
      " [112.13603 ]\n",
      " [150.36276 ]\n",
      " [112.921616]\n",
      " [182.40126 ]\n",
      " [176.17801 ]]\n",
      "1100 Cost:  35.211586 \n",
      "Prediction:\n",
      " [[148.45586]\n",
      " [188.66489]\n",
      " [180.36867]\n",
      " [199.15942]\n",
      " [144.24614]\n",
      " [111.86964]\n",
      " [150.35237]\n",
      " [112.91253]\n",
      " [182.08778]\n",
      " [175.67854]]\n",
      "1200 Cost:  32.870964 \n",
      "Prediction:\n",
      " [[148.65486]\n",
      " [188.5338 ]\n",
      " [180.43651]\n",
      " [199.15813]\n",
      " [144.11613]\n",
      " [111.61442]\n",
      " [150.34343]\n",
      " [112.90573]\n",
      " [181.78748]\n",
      " [175.20103]]\n",
      "1300 Cost:  30.716156 \n",
      "Prediction:\n",
      " [[148.84561]\n",
      " [188.4078 ]\n",
      " [180.50131]\n",
      " [199.1571 ]\n",
      " [143.99078]\n",
      " [111.36991]\n",
      " [150.33585]\n",
      " [112.90106]\n",
      " [181.49979]\n",
      " [174.74449]]\n",
      "1400 Cost:  28.731747 \n",
      "Prediction:\n",
      " [[149.02841]\n",
      " [188.28662]\n",
      " [180.56322]\n",
      " [199.15633]\n",
      " [143.86983]\n",
      " [111.13566]\n",
      " [150.32948]\n",
      " [112.89837]\n",
      " [181.22414]\n",
      " [174.30794]]\n",
      "1500 Cost:  26.904072 \n",
      "Prediction:\n",
      " [[149.20361]\n",
      " [188.1701 ]\n",
      " [180.62231]\n",
      " [199.15579]\n",
      " [143.75317]\n",
      " [110.91121]\n",
      " [150.32431]\n",
      " [112.89755]\n",
      " [180.96004]\n",
      " [173.89056]]\n",
      "1600 Cost:  25.22024 \n",
      "Prediction:\n",
      " [[149.37157 ]\n",
      " [188.05806 ]\n",
      " [180.67877 ]\n",
      " [199.15549 ]\n",
      " [143.64062 ]\n",
      " [110.696144]\n",
      " [150.32024 ]\n",
      " [112.89846 ]\n",
      " [180.70697 ]\n",
      " [173.49149 ]]\n",
      "1700 Cost:  23.66853 \n",
      "Prediction:\n",
      " [[149.53256 ]\n",
      " [187.95029 ]\n",
      " [180.73268 ]\n",
      " [199.15538 ]\n",
      " [143.53204 ]\n",
      " [110.49006 ]\n",
      " [150.31718 ]\n",
      " [112.900986]\n",
      " [180.46448 ]\n",
      " [173.10988 ]]\n",
      "1800 Cost:  22.238277 \n",
      "Prediction:\n",
      " [[149.6869  ]\n",
      " [187.84663 ]\n",
      " [180.78416 ]\n",
      " [199.15547 ]\n",
      " [143.42726 ]\n",
      " [110.29257 ]\n",
      " [150.31511 ]\n",
      " [112.905014]\n",
      " [180.23209 ]\n",
      " [172.745   ]]\n",
      "1900 Cost:  20.919607 \n",
      "Prediction:\n",
      " [[149.83487]\n",
      " [187.7469 ]\n",
      " [180.83334]\n",
      " [199.15575]\n",
      " [143.32613]\n",
      " [110.1033 ]\n",
      " [150.31392]\n",
      " [112.91043]\n",
      " [180.00938]\n",
      " [172.39609]]\n",
      "2000 Cost:  19.703526 \n",
      "Prediction:\n",
      " [[149.97675]\n",
      " [187.65097]\n",
      " [180.8803 ]\n",
      " [199.1562 ]\n",
      " [143.22852]\n",
      " [109.92191]\n",
      " [150.3136 ]\n",
      " [112.91714]\n",
      " [179.79593]\n",
      " [172.06244]]\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "filename_queue = tf.train.string_input_producer(\n",
    "    ['data-01-test-score.csv'], shuffle=False, name='filename_queue')\n",
    "\n",
    "reader = tf.TextLineReader()\n",
    "key, value = reader.read(filename_queue)\n",
    "\n",
    "# Default values, in case of empty columns. Also speifies the type of the\n",
    "# decoded result.\n",
    "record_defaults = [[0.], [0.], [0.], [0.]]\n",
    "xy = tf.decode_csv(value, record_defaults=record_defaults)\n",
    "\n",
    "# Collect batches of csv in\n",
    "train_x_batch, train_y_batch = \\\n",
    "    tf.train.batch([xy[0:-1], xy[-1:]], batch_size=10)\n",
    "\n",
    "# placeholders for a tensor that will be always fed.\n",
    "X = tf.placeholder(tf.float32, shape=[None, 3])\n",
    "Y = tf.placeholder(tf.float32, shape=[None, 1])\n",
    "\n",
    "W = tf.Variable(tf.random_normal([3, 1]), name='weight')\n",
    "b = tf.Variable(tf.random_normal([1]), name='bias')\n",
    "\n",
    "# Hypothesis\n",
    "hypothesis = tf.matmul(X, W) + b\n",
    "\n",
    "# Simplified cost/loss function\n",
    "cost = tf.reduce_mean(tf.square(hypothesis - Y))\n",
    "\n",
    "# Minimize\n",
    "optimizer = tf.train.GradientDescentOptimizer(learning_rate=1e-5)\n",
    "train = optimizer.minimize(cost)\n",
    "\n",
    "# Launch the graph in a session\n",
    "sess = tf.Session()\n",
    "# Initialize global variables in the graph\n",
    "sess.run(tf.global_variables_initializer())\n",
    "\n",
    "#Start populating the fileneame queue\n",
    "coord = tf.train.Coordinator()\n",
    "threads = tf.train.start_queue_runners(sess=sess, coord=coord)\n",
    "\n",
    "for step in range(2001):\n",
    "    x_batch, y_batch = sess.run([train_x_batch, train_y_batch])\n",
    "    cost_val, hy_val, _ = sess.run(\n",
    "        [cost, hypothesis, train], \n",
    "        feed_dict={X: x_batch, Y: y_batch})\n",
    "    if step % 100 == 0:\n",
    "        print(step, \"Cost: \", cost_val,\n",
    "             \"\\nPrediction:\\n\", hy_val)\n",
    "        \n",
    "coord.request_stop()\n",
    "coord.join(threads)"
   ]
  }
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