Skip to content

Instantly share code, notes, and snippets.

@sebboie
Created June 16, 2017 18:20
Show Gist options
  • Save sebboie/2d7485d33a7c1cdb817adfbb2501302d to your computer and use it in GitHub Desktop.
Save sebboie/2d7485d33a7c1cdb817adfbb2501302d to your computer and use it in GitHub Desktop.
Display the source blob
Display the rendered blob
Raw
{
"cells": [
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "import numpy as np\nimport matplotlib.pyplot as plt\nimport tensorflow as tf\n\n%matplotlib inline",
"execution_count": 1,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Generate some uniformly distributed random data on [-2, 2]"
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "x = 4*np.random.rand(2000)-2",
"execution_count": 2,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "plt.plot(x, '.')",
"execution_count": 3,
"outputs": [
{
"output_type": "execute_result",
"metadata": {},
"data": {
"text/plain": "[<matplotlib.lines.Line2D at 0x11d9c0e80>]"
},
"execution_count": 3
},
{
"output_type": "display_data",
"metadata": {},
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAD7CAYAAABpJS8eAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n",
"text/plain": "<matplotlib.figure.Figure at 0x105e2a470>"
}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Generate $$ y = \\sin(2\\pi x)\\sin(3\\pi x),$$ with some additive noise:"
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "def generate_fn(data, noise_amp = 0.1):\n noise = np.random.randn(len(data))*noise_amp\n y = np.sin(2*np.pi*data)*np.sin(3*np.pi*data)+noise\n return y",
"execution_count": 4,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "plt.plot(x, generate_fn(x), '.')",
"execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
"metadata": {},
"data": {
"text/plain": "[<matplotlib.lines.Line2D at 0x11dae53c8>]"
},
"execution_count": 5
},
{
"output_type": "display_data",
"metadata": {},
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAD7CAYAAABpJS8eAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nCSZ8IqKSYMInIioJJnwiopL4H09wdNRt7u+uAAAAAElFTkSuQmCC\n",
"text/plain": "<matplotlib.figure.Figure at 0x11da26160>"
}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "# Start tensorflow\ntf.reset_default_graph()\nsess = tf.Session()",
"execution_count": 6,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "# generate some training data\nx_train = 4*np.random.rand(5000)-2\ny_train = generate_fn(x_train)\n\n\n# Adds a singleton dimension to tensors: shape = 5000 -> shape = (5000, 1)\nx_train = x_train[:, None]\ny_train = y_train[:, None]",
"execution_count": 7,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "# Start a tensorflow session\ntf.reset_default_graph()\nsess = tf.Session()",
"execution_count": 8,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "# Create placeholder where training data will be fed in; \n# shape = (None, 1) means that an arbitrary number of points can be fed but each of size 1\nx_placeholder = tf.placeholder(shape=[None, 1], dtype=tf.float32, name='x_input')\ny_placeholder = tf.placeholder(shape=[None, 1], dtype=tf.float32, name='y_input')",
"execution_count": 9,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "# Function to create a fully connected layer\ndef layer(input, size_out, name = \"layer\", activation = None):\n # just for naming\n with tf.name_scope(name):\n size_in = int(input.shape[1])\n # initialize some weights and bias\n W = tf.Variable(tf.truncated_normal([size_in, size_out], stddev=0.1), name = \"Weights\")\n b = tf.Variable(tf.constant(0.1, shape=[size_out]), name = \"Bias\")\n \n y_interm = tf.matmul(input, W) + b\n \n # If activation function is used\n if activation: \n return activation(y_interm)\n \n return y_interm",
"execution_count": 10,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "# Assemble a model with input, 3 hidden and output layer for first exercise\nwith tf.name_scope('model'):\n fc1 = layer(x_placeholder, 100, \"input_layer\")\n fc2 = layer(fc1, 100, \"hidden_layer_1\", activation=tf.nn.relu)\n fc3 = layer(fc2, 100, \"hidden_layer_2\", activation=tf.nn.relu)\n fc4 = layer(fc3, 100, \"hidden_layer_3\", activation=tf.nn.relu)\n y = layer(fc4, 1, \"output\")\n",
"execution_count": 11,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "LEARNING_RATE = 0.01\n\n# Scopes are like namespaces in the graph\nwith tf.name_scope('training'):\n with tf.name_scope('loss'):\n # cost function mean squared error\n loss = tf.reduce_mean(tf.square(y - y_placeholder))\n with tf.name_scope('optimizer'):\n # optimizer Adam\n optimizer = tf.train.AdamOptimizer(learning_rate = LEARNING_RATE)\n train = optimizer.minimize(loss)",
"execution_count": 12,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "# Write out some summary statistics to the folder ./graph. \n# The folder graph should be deleted before every run otherwise it clutters up.\nwriter = tf.summary.FileWriter(\"graph\")\nwriter.add_graph(sess.graph)\ntf.summary.scalar('loss', loss)\n\nsummary = tf.summary.merge_all()",
"execution_count": 13,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "# Variables need to be initialized before they can be used\nsess.run(tf.global_variables_initializer())",
"execution_count": 14,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "# Training\nfor step in range(1000):\n train_loss, summary_writer, _ = sess.run([loss, summary, train], feed_dict={x_placeholder: x_train, \n y_placeholder: y_train})\n # Add training summary to writer\n writer.add_summary(summary_writer, step)\n \n # Print out mean squared error every 10th step\n if step % 10 == 0:\n print(\"mean squared error: {}\".format(sess.run(tf.reduce_sum(train_loss))))\n\nwriter.close()",
"execution_count": 15,
"outputs": [
{
"output_type": "stream",
"text": "mean squared error: 0.28983789682388306\nmean squared error: 0.2685641944408417\nmean squared error: 0.257078617811203\nmean squared error: 0.239362895488739\nmean squared error: 0.19349870085716248\nmean squared error: 0.15152688324451447\nmean squared error: 0.13814948499202728\nmean squared error: 0.12921442091464996\nmean squared error: 0.12658251821994781\nmean squared error: 0.1244097650051117\nmean squared error: 0.12320592254400253\nmean squared error: 0.12223837524652481\nmean squared error: 0.12239504605531693\nmean squared error: 0.12114761024713516\nmean squared error: 0.11984818428754807\nmean squared error: 0.12053051590919495\nmean squared error: 0.11940212547779083\nmean squared error: 0.11831662803888321\nmean squared error: 0.11917936056852341\nmean squared error: 0.11708090454339981\nmean squared error: 0.1157243400812149\nmean squared error: 0.11621814221143723\nmean squared error: 0.11687997728586197\nmean squared error: 0.11521252244710922\nmean squared error: 0.11196347326040268\nmean squared error: 0.12078991532325745\nmean squared error: 0.10850199311971664\nmean squared error: 0.10585888475179672\nmean squared error: 0.11839843541383743\nmean squared error: 0.10892488062381744\nmean squared error: 0.10689517855644226\nmean squared error: 0.09667868912220001\nmean squared error: 0.0899939090013504\nmean squared error: 0.10019136965274811\nmean squared error: 0.08771096169948578\nmean squared error: 0.10536975413560867\nmean squared error: 0.10746689140796661\nmean squared error: 0.08443383872509003\nmean squared error: 0.07067348808050156\nmean squared error: 0.06895943731069565\nmean squared error: 0.056711699813604355\nmean squared error: 0.05405762791633606\nmean squared error: 0.08382802456617355\nmean squared error: 0.06273435056209564\nmean squared error: 0.05874090641736984\nmean squared error: 0.04463105648756027\nmean squared error: 0.041728898882865906\nmean squared error: 0.03564863279461861\nmean squared error: 0.07425559312105179\nmean squared error: 0.0393388532102108\nmean squared error: 0.03306806460022926\nmean squared error: 0.029107162728905678\nmean squared error: 0.025961261242628098\nmean squared error: 0.025568947196006775\nmean squared error: 0.05209239572286606\nmean squared error: 0.03648722916841507\nmean squared error: 0.02543230541050434\nmean squared error: 0.02508619613945484\nmean squared error: 0.02052420936524868\nmean squared error: 0.02217281423509121\nmean squared error: 0.018928971141576767\nmean squared error: 0.018525054678320885\nmean squared error: 0.017618369311094284\nmean squared error: 0.020526491105556488\nmean squared error: 0.03254661336541176\nmean squared error: 0.01513152476400137\nmean squared error: 0.01670798286795616\nmean squared error: 0.014762680046260357\nmean squared error: 0.045568931847810745\nmean squared error: 0.020232653245329857\nmean squared error: 0.0146106518805027\nmean squared error: 0.014251145534217358\nmean squared error: 0.013954754918813705\nmean squared error: 0.012023735791444778\nmean squared error: 0.015367808751761913\nmean squared error: 0.013060333207249641\nmean squared error: 0.04029102623462677\nmean squared error: 0.019396407529711723\nmean squared error: 0.012755182571709156\nmean squared error: 0.012617522850632668\nmean squared error: 0.012655720114707947\nmean squared error: 0.013563497923314571\nmean squared error: 0.011866377666592598\nmean squared error: 0.012433607131242752\nmean squared error: 0.012617852538824081\nmean squared error: 0.01193941943347454\nmean squared error: 0.011581807397305965\nmean squared error: 0.01072072982788086\nmean squared error: 0.015952548012137413\nmean squared error: 0.014146286062896252\nmean squared error: 0.015038315206766129\nmean squared error: 0.011773322708904743\nmean squared error: 0.011248794384300709\nmean squared error: 0.01388420257717371\nmean squared error: 0.02883416973054409\nmean squared error: 0.012556776404380798\nmean squared error: 0.011865305714309216\nmean squared error: 0.011159620247781277\nmean squared error: 0.016062341630458832\nmean squared error: 0.01185465045273304\n",
"name": "stdout"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Plot learned function in orange and data in blue"
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "fig = plt.figure()\nax = fig.add_subplot(111)\nax.plot(x_train, y_train, '.', label = \"input data\")\nax.plot(x_train, sess.run(y, feed_dict={x_placeholder : x_train}), '.', color = 'orange', markersize = 7, label = \"TF fit\")\nax.legend(loc = 'lower left')",
"execution_count": 16,
"outputs": [
{
"output_type": "execute_result",
"metadata": {},
"data": {
"text/plain": "<matplotlib.legend.Legend at 0x107e22518>"
},
"execution_count": 16
},
{
"output_type": "display_data",
"metadata": {},
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAD7CAYAAABpJS8eAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n+BwOhzNL4Aafw+FwZgnc4HM4HM4s4f8DEyu6PMXS0b8AAAAASUVORK5CYII=\n",
"text/plain": "<matplotlib.figure.Figure at 0x11d973860>"
}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "check out the computational graph and training history by\n- running tensorboard --logdir=./graph\n- in your browser go to localhost:6006\n - tab \"scalars\" shows loss history\n - tab \"graphs\" shows the computational graph"
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
}
],
"metadata": {
"kernelspec": {
"name": "python3",
"display_name": "Python 3",
"language": "python"
},
"language_info": {
"version": "3.5.1",
"pygments_lexer": "ipython3",
"nbconvert_exporter": "python",
"name": "python",
"codemirror_mode": {
"version": 3,
"name": "ipython"
},
"mimetype": "text/x-python",
"file_extension": ".py"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment