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October 24, 2016 17:13
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Playing with TensorFlow" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 174, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [], | |
"source": [ | |
"%matplotlib inline\n", | |
"import tensorflow as tf\n", | |
"import numpy as np\n", | |
"from matplotlib import pylab as plt\n", | |
"from sklearn.datasets import load_iris" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Simple calculations" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 70, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"4 * 5 = 20\n", | |
"4 * [1 2] = [4 8]\n", | |
"5.0 * [ 1. 1. 1.] = [ 5. 5. 5.]\n", | |
"[[ 1. 1.]\n", | |
" [ 1. 1.]] .*\n", | |
"[[ 0.11538697 -0.33664498]\n", | |
" [ 0.72886461 -1.6635133 ]] =\n", | |
"[[ 0.11538697 -0.33664498]\n", | |
" [ 0.72886461 -1.6635133 ]] , * =\n", | |
"[[ 0.84425157 -2.00015831]\n", | |
" [ 0.84425157 -2.00015831]]\n" | |
] | |
} | |
], | |
"source": [ | |
"# Multiply two constant scalars\n", | |
"with tf.Session():\n", | |
" x = tf.constant(4, name='x')\n", | |
" y = tf.constant(5, name='y')\n", | |
" z = x * y\n", | |
" print(x.eval(), '*', y.eval(), '=', z.eval())\n", | |
"# Multiply a const scalar and a const vector\n", | |
"with tf.Session():\n", | |
" x = tf.constant(4, name='x')\n", | |
" y = tf.constant([1, 2], name='y')\n", | |
" z = x * y\n", | |
" print(x.eval(), '*', y.eval(), '=', z.eval())\n", | |
"# Multiply a const scalar and a vector variable\n", | |
"with tf.Session():\n", | |
" x = tf.constant(5, dtype=tf.float32)\n", | |
" y = tf.Variable(tf.ones((3,)))\n", | |
" z = x*y\n", | |
" tf.initialize_all_variables().run()\n", | |
" print(x.eval(), '*', y.eval(), '=', z.eval())\n", | |
"# Multiply two vector variables\n", | |
"with tf.Session():\n", | |
" x = tf.Variable(tf.ones(shape=(2, 2)))\n", | |
" y = tf.Variable(tf.random_normal(shape=(2, 2)))\n", | |
" z = x * y\n", | |
" z2 = tf.matmul(x, y)\n", | |
" tf.initialize_all_variables().run()\n", | |
" print(x.eval(), '.*')\n", | |
" print(y.eval(), '=')\n", | |
" print(z.eval(), ', * =')\n", | |
" print(z2.eval())" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Linear regression\n", | |
"Given some data points, we want to minimize the distance between a certain line $y=Wx+b$ and each data point.\n", | |
"\n", | |
"We start by generating some data, by uniform sampling [35, 350), and generating Y values using the linear law plus a gaussian noise, with standard deviation of 45. We will use `X` and `Y` as true values, and we try to learn the underlying variables `m` and `q` from those.\n", | |
"\n", | |
"Given the data, `X` and `Y`, we setup a model to learn from them. We want to learn `W` and `b` such that `y' = W*X+b` is as close as possible to `Y`.\n", | |
"\n", | |
"We define \"as close as possible\" as a distance $$D(x, y) = \\frac{1}{N}\\sum_i^N (x_i - y_i)^2$$.\n", | |
"\n", | |
"Therefore, we want to minimize $D(WX+b, Y)$, called the **cost** function." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 173, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"[<matplotlib.lines.Line2D at 0x7f13734c3198>]" | |
] | |
}, | |
"execution_count": 173, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
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WbpFa0tXVFf//S7Pz8bs/0J4LMxsGTAR+mRDMOKATmJLhtCmx/Yk6shwvMiQF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\n64qIDFUKLqTs8q1B4WchLBi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QZM/Fg8BRwCnAacBU4O4c5ywBGoG/AI4G/gt4yMw+E2A7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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x7f13734c3358>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"# Define the real parameters of our line\n", | |
"m, q = 0.5, 0\n", | |
"# Define some data\n", | |
"N = 100 # Number of datapoints\n", | |
"train_X = np.random.uniform(-1, 1, size=N)\n", | |
"train_Y = np.random.normal(m * train_X + q, 0.1)\n", | |
"# Plot the data, just out of curiosity\n", | |
"plt.scatter(train_X, train_Y)\n", | |
"x_ = np.linspace(-1, 1, 10)\n", | |
"plt.plot(x_, x_ * m + q)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 176, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"<a list of 12 text.Text objects>" | |
] | |
}, | |
"execution_count": 176, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": 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PMEO6ReoMM2RajGIW64tibGLBYrhHioBVhAjRTDOVVFBBBTvYztu8hYZGLrkU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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x7f13735d3da0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"cw = np.linspace(-0.5, 1.5, 100)\n", | |
"cb = np.linspace(-1, 1, 100)\n", | |
"CW, CB = np.meshgrid(cw, cb)\n", | |
"def fun(w, b):\n", | |
" return np.average((train_X * w + b - train_Y)**2)\n", | |
"vfun = np.vectorize(fun)\n", | |
"cs = plt.contour(CW, CB, vfun(CW, CB))#, levels=np.linspace(0.01, 1, 7))\n", | |
"plt.clabel(cs, inline=1, fontsize=8, inline_spacing=2)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 182, | |
"metadata": { | |
"collapsed": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"<matplotlib.collections.PathCollection at 0x7f1372db6198>" | |
] | |
}, | |
"execution_count": 182, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": 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8Eq9ZCjOrAT4KDJvp9CV4FEif4nwmw+TnLGQTKPb/X+Wu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\nmQAAAABJRU5ErkJggg==\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x7f13723ad2b0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": 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H8elQ4YcyP+zzwz4flPuhPGD0frm/0t/xYJNsDCqhNtoeGXiS92uJJpndukz9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\nEBMMhmEYhmEMyP8HcmDKJ/1ZpdcAAAAASUVORK5CYII=\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x7f13723af7f0>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"with tf.Session() as sess:\n", | |
" x = tf.placeholder('float', shape=(N,), name='x')\n", | |
" y = tf.placeholder('float', shape=(N,), name='y')\n", | |
" \n", | |
" feed = {x: train_X, y: train_Y}\n", | |
" W = tf.Variable(tf.random_uniform([1], -0.5, 1.5), name='W')\n", | |
" b = tf.Variable(tf.random_uniform([1], -1, 1), name='b')\n", | |
" cost = tf.reduce_mean(tf.square(x * W + b - x))\n", | |
" \n", | |
" opt = tf.train.GradientDescentOptimizer(0.1).minimize(cost)\n", | |
" \n", | |
" tf.initialize_all_variables().run()\n", | |
" \n", | |
" w_points = [W.eval()]\n", | |
" b_points = [b.eval()]\n", | |
" p_size = [10]\n", | |
"\n", | |
" for i in range(1000):\n", | |
" if i % 10 == 0:\n", | |
" w_points.append(W.eval())\n", | |
" b_points.append(b.eval())\n", | |
" p_size.append(max(p_size[-1] * 0.9, 5))\n", | |
"\n", | |
" sess.run(opt, feed_dict=feed)\n", | |
" \n", | |
" plt.figure()\n", | |
" plt.scatter(train_X, train_Y)\n", | |
" plt.plot(train_X, m * train_X + q)\n", | |
" plt.plot(train_X, W.eval() * train_X + b.eval())\n", | |
"\n", | |
"plt.figure()\n", | |
"cs = plt.contour(CW, CB, vfun(CW, CB))\n", | |
"plt.scatter([m], [q], c='red')\n", | |
"plt.clabel(cs, inline=1, fontsize=8, inline_spacing=2)\n", | |
"plt.scatter(w_points, b_points, s=p_size)" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.4.3" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 0 | |
} |
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