{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# A Network Tour of Data Science\n", "###       Xavier Bresson, Winter 2016/17\n", "## Assignment 2 : Convolutional Neural Networks" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Import libraries\n", "import numpy as np\n", "import tensorflow as tf\n", "import time\n", "import collections\n", "import os\n", "\n", "import matplotlib.pyplot as plt\n", "# This is a bit of magic to make matplotlib figures appear inline in the notebook\n", "# rather than in a new window.\n", "%matplotlib inline\n", "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n", "plt.rcParams['image.interpolation'] = 'nearest'\n", "plt.rcParams['image.cmap'] = 'gray'" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training data shape: (2500, 32, 32, 3)\n", "Training label shape: (2500,)\n", "Test data shape: (100, 32, 32, 3)\n", "Test label shape: (100,)\n" ] } ], "source": [ "# Load small part of CIFAR dataset\n", "[X_train, y_train, X_test, y_test] = np.load(os.path.join('datasets', 'cifar.npy'))\n", "\n", "# Convert to float\n", "train_data_orig = X_train.astype('float32')\n", "y_train = y_train.astype('float32')\n", "test_data_orig = X_test.astype('float32')\n", "y_test = y_test.astype('float32')\n", "\n", "# See shapes of matrices\n", "print('Training data shape: ', train_data_orig.shape)\n", "print('Training label shape: ', y_train.shape)\n", "print('Test data shape: ', test_data_orig.shape)\n", "print('Test label shape: ', y_test.shape)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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LJF4UnudVjDG/DEpBP2CM+WsA60Cnz0kAn27Y/FdBO31EdtgNOosOAUhc1YZfYSzVri6B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hJpXleTLHCkz2cfApt8tl0ztE4fEqOYEGMTjuxOgnzPQaYlWF5lH/WNiN1VH756lrGq6bQvLZ8X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\nHTIA4wdQY5Oid0iD+9LNSxdEROTqletu21Xm4+9sq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c8vgqXPsxB9kuamOCm8F+C11Wu+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IOGl6Flif3Ec8DdbOYq0eDcnctxET8OJLWH80OanG4IiI5MnIM9RERm3czzyflZ6LuRFaLX6O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Ol0cUAyMDOzfh/1X33njpmZPf7EM/fUdn/6jZ+kZmZzHdS9WUddWk20U7ON4tpzzewcjYkk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ojvPDbC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\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qHl70rbYQMGtCgXM7wnXl9Czm8PsrKziAdZlIY85XBgByZnK436VpgCnxMF/2Jia8snu7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\nqCIDESTa3CRC3CXyVtgDQp5LAw1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MbZBOFf3Z45q0Hb2d4rNV5tunQujXPCurVyq41qvL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\n8yMdwzEU7c1SlBtQxobj1KG4WsQwTm0iriF+ll4GrrBerWf7znDCbhGRN96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E\nEEIsBNrcCCGEEEIIIRYCbW6EEEIIIYQQC4E2N0IIIYQQQoiFQJsbIYQQQgghxEKgzY0QQgghhBBi\nIdDmRgghhBBCCLEQaHMjhBBCCCGEWAj+HwnJV+xWmw9xAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Visualize a few examples of training images from each class\n", "classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n", "num_classes = len(classes)\n", "samples_per_class = 7\n", "for y, cls in enumerate(classes):\n", " idxs = np.flatnonzero(y_train == y)\n", " idxs = np.random.choice(idxs, samples_per_class, replace=False)\n", " for i, idx in enumerate(idxs):\n", " plt_idx = i * num_classes + y + 1\n", " plt.subplot(samples_per_class, num_classes, plt_idx)\n", " xx = train_data_orig[idx,:,:,:]\n", " xx -= np.min(xx)\n", " xx /= np.max(xx)\n", " plt.imshow(xx)\n", " plt.axis('off')\n", " if i == 0:\n", " plt.title(cls)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(2500, 1024)\n", "(100, 1024)\n" ] } ], "source": [ "# Data pre-processing\n", "n = train_data_orig.shape[0]\n", "train_data = np.zeros([n,32**2])\n", "for i in range(n):\n", " xx = train_data_orig[i,:,:,:]\n", " xx = np.linalg.norm(xx,axis=2)\n", " xx -= np.mean(xx)\n", " xx /= np.linalg.norm(xx)\n", " train_data[i] = np.reshape(xx,[-1])\n", "\n", "n = test_data_orig.shape[0]\n", "test_data = np.zeros([n,32**2])\n", "for i in range(n):\n", " xx = test_data_orig[i,:,:,:]\n", " xx = np.linalg.norm(xx,axis=2)\n", " xx -= np.mean(xx)\n", " xx /= np.linalg.norm(xx)\n", " test_data[i] = np.reshape(xx,[-1])\n", "\n", "print(train_data.shape)\n", "print(test_data.shape)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(2500, 10)\n", "(100, 10)\n" ] } ], "source": [ "# Convert label values to one_hot vector\n", "from scipy.sparse import coo_matrix\n", "def convert_to_one_hot(a,max_val=None):\n", " N = a.size\n", " data = np.ones(N,dtype=int)\n", " sparse_out = coo_matrix((data,(np.arange(N),a.ravel())), shape=(N,max_val))\n", " return np.array(sparse_out.todense())\n", "\n", "train_labels = convert_to_one_hot(y_train,10)\n", "test_labels = convert_to_one_hot(y_test,10)\n", "\n", "print(train_labels.shape)\n", "print(test_labels.shape)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "# Model 1\n", "**Question 1** Define with TensorFlow a linear classifier model:\n", "\n", "$$\n", "y=\\textrm{softmax}(xW+b)\n", "$$\n", "\n", "Compute the train accuracy and the test accuracy (you should get a test accuracy around 25% at iteration 10,000)

\n", "Hints:
\n", "(1) You may use functions *tf.matmul(), tf.nn.softmax()*
\n", "(2) You may use Xavier's initialization discussed during lectures for W, and b=0
\n", "(3) You may use optimization schemes *tf.train.GradientDescentOptimizer(), tf.train.AdamOptimizer()*
" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Define computational graph (CG)\n", "batch_size = 100 # batch size\n", "d = train_data.shape[1] # data dimensionality\n", "nc = 10 # number of classes\n", "\n", "# CG inputs\n", "xin = tf.placeholder(tf.float32,[batch_size,d]); #print('xin=',xin,xin.get_shape())\n", "y_label = tf.placeholder(tf.float32,[batch_size,nc]); #print('y_label=',y_label,y_label.get_shape())\n", "\n", "# Fully Connected layer\n", "W = tf.Variable(tf.truncated_normal([d,nc], stddev=tf.sqrt(6./tf.to_float(d+nc)) )); #print('W=',W.get_shape())\n", "b = tf.Variable(tf.zeros([nc])); #print('b=',b.get_shape())\n", "y = tf.matmul(xin, W); #print('y1=',y,y.get_shape())\n", "y += b; #print('y2=',y,y.get_shape())\n", "\n", "# Softmax\n", "y = tf.nn.softmax(y); #print('y3=',y,y.get_shape())\n", "\n", "# Loss\n", "cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_label * tf.log(y), 1))\n", "total_loss = cross_entropy\n", "\n", "# Optimization scheme\n", "#train_step = tf.train.GradientDescentOptimizer(0.025).minimize(total_loss)\n", "train_step = tf.train.AdamOptimizer(0.001).minimize(total_loss)\n", "\n", "# Accuracy\n", "correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_label,1))\n", "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Iteration i= 0 , train accuracy= 0.09 , loss= 2.30283\n", "test accuracy= 0.09\n", "\n", "Iteration i= 1000 , train accuracy= 0.36 , loss= 1.87004\n", "test accuracy= 0.35\n", "\n", "Iteration i= 2000 , train accuracy= 0.45 , loss= 1.77595\n", "test accuracy= 0.34\n", "\n", "Iteration i= 3000 , train accuracy= 0.43 , loss= 1.7689\n", "test accuracy= 0.33\n", "\n", "Iteration i= 4000 , train accuracy= 0.31 , loss= 1.83218\n", "test accuracy= 0.29\n", "\n", "Iteration i= 5000 , train accuracy= 0.47 , loss= 1.71852\n", "test accuracy= 0.27\n", "\n", "Iteration i= 6000 , train accuracy= 0.51 , loss= 1.67397\n", "test accuracy= 0.25\n", "\n", "Iteration i= 7000 , train accuracy= 0.47 , loss= 1.64769\n", "test accuracy= 0.24\n", "\n", "Iteration i= 8000 , train accuracy= 0.54 , loss= 1.60107\n", "test accuracy= 0.25\n", "\n", "Iteration i= 9000 , train accuracy= 0.5 , loss= 1.5663\n", "test accuracy= 0.23\n", "\n", "Iteration i= 10000 , train accuracy= 0.55 , loss= 1.46647\n", "test accuracy= 0.23\n" ] } ], "source": [ "# Run Computational Graph\n", "n = train_data.shape[0]\n", "indices = collections.deque()\n", "init = tf.initialize_all_variables()\n", "sess = tf.Session()\n", "sess.run(init)\n", "for i in range(10001):\n", " \n", " # Batch extraction\n", " if len(indices) < batch_size:\n", " indices.extend(np.random.permutation(n)) \n", " idx = [indices.popleft() for i in range(batch_size)]\n", " batch_x, batch_y = train_data[idx,:], train_labels[idx]\n", " #print(batch_x.shape,batch_y.shape)\n", " \n", " # Run CG for variable training\n", " _,acc_train,total_loss_o = sess.run([train_step,accuracy,total_loss], feed_dict={xin: batch_x, y_label: batch_y})\n", " \n", " # Run CG for test set\n", " if not i%1000:\n", " print('\\nIteration i=',i,', train accuracy=',acc_train,', loss=',total_loss_o)\n", " acc_test = sess.run(accuracy, feed_dict={xin: test_data, y_label: test_labels})\n", " print('test accuracy=',acc_test)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "# Model 2\n", "**Question 2a.** Define with TensorFlow a 2-layer neural network classifier:\n", "\n", "$$\n", "y=\\textrm{softmax}(ReLU(xW_1+b_1)W_2+b_2)\n", "$$\n", "\n", "Compute the train accuracy and the test accuracy (you should be able to overfit the train set)
\n", "Hint: You may use functions *tf.nn.relu()*

\n", "\n", "**Question 2b.** Add a L2 regularization term to prevent overfitting. Compute the train accuracy and the test accuracy (you should get a test accuracy around 35%)
\n", "Hints:
\n", "(1) You may use functions *tf.nn.l2_loss()*
\n", "(2) Do not forget the constant parameter *reg_par*: total_loss = cross_entropy + reg_par* reg_loss
" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Define computational graph (CG)\n", "batch_size = 100 # batch size\n", "d = train_data.shape[1] # data dimensionality\n", "nc = 10 # number of classes\n", "\n", "# CG inputs\n", "xin = tf.placeholder(tf.float32,[batch_size,d]); #print('xin=',xin,xin.get_shape())\n", "y_label = tf.placeholder(tf.float32,[batch_size,nc]); #print('y_label=',y_label,y_label.get_shape())\n", "\n", "# 1st Fully Connected layer\n", "nfc1 = 100\n", "Wfc1 = tf.Variable(tf.truncated_normal([d,nfc1], stddev=tf.sqrt(6./tf.to_float(d+nfc1)) )); #print('Wfc1=',Wfc1.get_shape())\n", "bfc1 = tf.Variable(tf.zeros([nfc1])); #print('bfc1=',bfc1.get_shape())\n", "y = tf.matmul(xin, Wfc1); #print('y1=',y,y.get_shape())\n", "y += bfc1; #print('y2=',y,y.get_shape())\n", "\n", "# ReLU activation\n", "y = tf.nn.relu(y)\n", "\n", "# 2nd Fully Connected layer\n", "Wfc2 = tf.Variable(tf.truncated_normal([nfc1,nc], stddev=tf.sqrt(6./tf.to_float(nfc1+nc)) )); #print('Wfc2=',Wfc2.get_shape())\n", "bfc2 = tf.Variable(tf.zeros([nc])); #print('bfc2=',bfc2.get_shape())\n", "y = tf.matmul(y, Wfc2); #print('y1b=',y,y.get_shape())\n", "y += bfc2; #print('y2b=',y,y.get_shape())\n", "\n", "# Softmax\n", "y = tf.nn.softmax(y); #print('y3=',y,y.get_shape())\n", "\n", "# Loss\n", "cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_label * tf.log(y), 1))\n", "\n", "# L2 Regularization\n", "reg_loss = 0.0\n", "reg_loss += tf.nn.l2_loss(Wfc1)\n", "reg_loss += tf.nn.l2_loss(bfc1)\n", "reg_loss += tf.nn.l2_loss(Wfc2)\n", "reg_loss += tf.nn.l2_loss(bfc2)\n", "reg_par = 1*1e-3\n", "total_loss = cross_entropy + reg_par* reg_loss\n", "\n", "# Optimization scheme\n", "#train_step = tf.train.GradientDescentOptimizer(0.025).minimize(total_loss)\n", "train_step = tf.train.AdamOptimizer(0.001).minimize(total_loss)\n", "\n", "# Accuracy\n", "correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_label,1))\n", "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Iteration i= 0 , train accuracy= 0.13 , loss= 2.55773\n", "test accuracy= 0.21\n", "\n", "Iteration i= 1000 , train accuracy= 0.57 , loss= 1.69043\n", "test accuracy= 0.43\n", "\n", "Iteration i= 2000 , train accuracy= 0.79 , loss= 1.4181\n", "test accuracy= 0.38\n", "\n", "Iteration i= 3000 , train accuracy= 0.77 , loss= 1.48924\n", "test accuracy= 0.37\n", "\n", "Iteration i= 4000 , train accuracy= 0.87 , loss= 1.40621\n", "test accuracy= 0.37\n", "\n", "Iteration i= 5000 , train accuracy= 0.89 , loss= 1.34421\n", "test accuracy= 0.34\n", "\n", "Iteration i= 6000 , train accuracy= 0.91 , loss= 1.31852\n", "test accuracy= 0.38\n", "\n", "Iteration i= 7000 , train accuracy= 0.96 , loss= 1.27738\n", "test accuracy= 0.39\n", "\n", "Iteration i= 8000 , train accuracy= 0.92 , loss= 1.3528\n", "test accuracy= 0.35\n", "\n", "Iteration i= 9000 , train accuracy= 0.91 , loss= 1.28683\n", "test accuracy= 0.4\n", "\n", "Iteration i= 10000 , train accuracy= 0.95 , loss= 1.29855\n", "test accuracy= 0.38\n" ] } ], "source": [ "# Run Computational Graph\n", "n = train_data.shape[0]\n", "indices = collections.deque()\n", "init = tf.initialize_all_variables()\n", "sess = tf.Session()\n", "sess.run(init)\n", "for i in range(10001):\n", " \n", " # Batch extraction\n", " if len(indices) < batch_size:\n", " indices.extend(np.random.permutation(n)) \n", " idx = [indices.popleft() for i in range(batch_size)]\n", " batch_x, batch_y = train_data[idx,:], train_labels[idx]\n", " #print(batch_x.shape,batch_y.shape)\n", " \n", " # Run CG for variable training\n", " _,acc_train,total_loss_o = sess.run([train_step,accuracy,total_loss], feed_dict={xin: batch_x, y_label: batch_y})\n", " \n", " # Run CG for test set\n", " if not i%1000:\n", " print('\\nIteration i=',i,', train accuracy=',acc_train,', loss=',total_loss_o)\n", " acc_test = sess.run(accuracy, feed_dict={xin: test_data, y_label: test_labels})\n", " print('test accuracy=',acc_test)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "# Model 3\n", "**Question 3.** Define a convolutional neural network classifier:\n", "\n", "$$\n", "y=\\textrm{softmax}(ReLU(x\\ast W_1+b_1)W_2+b_2)\n", "$$\n", "\n", "Hint: You may use function *tf.nn.conv2d(x_2d, Wcl, strides=[1, 1, 1, 1], padding='SAME')*
\n", "with *Wcl = tf.Variable(tf.truncated_normal([K,K,1,F], stddev=YOUR CODE HERE ))*\n", "for the convolution operator $\\ast$
\n", "and *x_2d = tf.reshape(xin, [-1,32,32,1])*
\n", "\n", "Compute the train accuracy and the test accuracy (you should be able to overfit the train set)

" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Define computational graph (CG)\n", "batch_size = 100 # batch size\n", "d = train_data.shape[1] # data dimensionality\n", "nc = 10 # number of classes\n", "\n", "# CG inputs\n", "xin = tf.placeholder(tf.float32,[batch_size,d]); #print('xin=',xin,xin.get_shape())\n", "y_label = tf.placeholder(tf.float32,[batch_size,nc]); #print('y_label=',y_label,y_label.get_shape())\n", "\n", "\n", "# Convolutional layer\n", "K = 5 # size of the patch\n", "F = 10 # number of filters\n", "ncl = K*K*F\n", "Wcl = tf.Variable(tf.truncated_normal([K,K,1,F], stddev=tf.sqrt(2./tf.to_float(ncl)) )); #print('Wcl=',Wcl.get_shape())\n", "bcl = tf.Variable(tf.zeros([F])); #print('bcl=',bcl.get_shape())\n", "x_2d = tf.reshape(xin, [-1,32,32,1]); #print('x_2d=',x_2d.get_shape())\n", "x = tf.nn.conv2d(x_2d, Wcl, strides=[1, 1, 1, 1], padding='SAME')\n", "x += bcl; #print('x2=',x.get_shape())\n", "\n", "# ReLU activation\n", "x = tf.nn.relu(x)\n", "\n", "# Fully Connected layer\n", "nfc = 32*32*F\n", "x = tf.reshape(x, [batch_size,-1]); #print('x3=',x.get_shape())\n", "Wfc = tf.Variable(tf.truncated_normal([nfc,nc], stddev=tf.sqrt(6./tf.to_float(nfc+nc)) )); #print('Wfc=',Wfc.get_shape())\n", "bfc = tf.Variable(tf.zeros([nc])); #print('bfc=',bfc.get_shape())\n", "y = tf.matmul(x, Wfc); #print('y1=',y,y.get_shape())\n", "y += bfc; #print('y2=',y,y.get_shape())\n", "\n", "# Softmax\n", "y = tf.nn.softmax(y); #print('y3=',y,y.get_shape())\n", "\n", "# Loss\n", "cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_label * tf.log(y), 1))\n", "total_loss = cross_entropy\n", "\n", "# Optimization scheme\n", "#train_step = tf.train.GradientDescentOptimizer(0.025).minimize(total_loss)\n", "train_step = tf.train.AdamOptimizer(0.001).minimize(total_loss)\n", "\n", "# Accuracy\n", "correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_label,1))\n", "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Iteration i= 0 , train accuracy= 0.09 , loss= 2.30147\n", "test accuracy= 0.27\n", "\n", "Iteration i= 1000 , train accuracy= 0.78 , loss= 0.83385\n", "test accuracy= 0.47\n", "\n", "Iteration i= 2000 , train accuracy= 0.96 , loss= 0.365053\n", "test accuracy= 0.43\n", "\n", "Iteration i= 3000 , train accuracy= 1.0 , loss= 0.11215\n", "test accuracy= 0.43\n", "\n", "Iteration i= 4000 , train accuracy= 1.0 , loss= 0.0405993\n", "test accuracy= 0.41\n", "\n", "Iteration i= 5000 , train accuracy= 1.0 , loss= 0.0227767\n", "test accuracy= 0.38\n", "\n", "Iteration i= 6000 , train accuracy= 1.0 , loss= 0.00813836\n", "test accuracy= 0.4\n", "\n", "Iteration i= 7000 , train accuracy= 1.0 , loss= 0.00548526\n", "test accuracy= 0.36\n", "\n", "Iteration i= 8000 , train accuracy= 1.0 , loss= 0.00261935\n", "test accuracy= 0.35\n", "\n", "Iteration i= 9000 , train accuracy= 1.0 , loss= 0.00158593\n", "test accuracy= 0.35\n", "\n", "Iteration i= 10000 , train accuracy= 1.0 , loss= 0.000753821\n", "test accuracy= 0.35\n" ] } ], "source": [ "# Run Computational Graph\n", "n = train_data.shape[0]\n", "indices = collections.deque()\n", "init = tf.initialize_all_variables()\n", "sess = tf.Session()\n", "sess.run(init)\n", "for i in range(10001):\n", " \n", " # Batch extraction\n", " if len(indices) < batch_size:\n", " indices.extend(np.random.permutation(n)) \n", " idx = [indices.popleft() for i in range(batch_size)]\n", " batch_x, batch_y = train_data[idx,:], train_labels[idx]\n", " #print(batch_x.shape,batch_y.shape)\n", " \n", " # Run CG for variable training\n", " _,acc_train,total_loss_o = sess.run([train_step,accuracy,total_loss], feed_dict={xin: batch_x, y_label: batch_y})\n", " \n", " # Run CG for test set\n", " if not i%1000:\n", " print('\\nIteration i=',i,', train accuracy=',acc_train,', loss=',total_loss_o)\n", " acc_test = sess.run(accuracy, feed_dict={xin: test_data, y_label: test_labels})\n", " print('test accuracy=',acc_test)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "# Model 4\n", "**Question 4.** Regularize the previous convolutional neural network classifier:\n", "\n", "$$\n", "y=\\textrm{softmax}(ReLU(x\\ast W_1+b_1)W_2+b_2)\n", "$$\n", "\n", "with the dropout technique discussed during lectures.\n", "\n", "Hint: You may use function *tf.nn.dropout()* with probability around 0.25.
\n", "\n", "Compute the train accuracy and the test accuracy (you should get a test accuracy of 45%)
\n", "Note: It is not mandatory to achieve 40% (as quality may change depending on initialization), but it is essential to implement correctly the classifier.

" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Define computational graph (CG)\n", "batch_size = 100 # batch size\n", "d = train_data.shape[1] # data dimensionality\n", "nc = 10 # number of classes\n", "\n", "# CG inputs\n", "xin = tf.placeholder(tf.float32,[batch_size,d]); #print('xin=',xin,xin.get_shape())\n", "y_label = tf.placeholder(tf.float32,[batch_size,nc]); #print('y_label=',y_label,y_label.get_shape())\n", "d = tf.placeholder(tf.float32);\n", "\n", "# Convolutional layer\n", "K = 5 # size of the patch\n", "F = 10 # number of filters\n", "ncl = K*K*F\n", "Wcl = tf.Variable(tf.truncated_normal([K,K,1,F], stddev=tf.sqrt(2./tf.to_float(ncl)) )); #print('Wcl=',Wcl.get_shape())\n", "bcl = tf.Variable(tf.zeros([F])); #print('bcl=',bcl.get_shape())\n", "x_2d = tf.reshape(xin, [-1,32,32,1]); #print('x_2d=',x_2d.get_shape())\n", "x = tf.nn.conv2d(x_2d, Wcl, strides=[1, 1, 1, 1], padding='SAME')\n", "x += bcl; #print('x2=',x.get_shape())\n", "\n", "# ReLU activation\n", "x = tf.nn.relu(x)\n", "\n", "# Dropout\n", "x = tf.nn.dropout(x, d)\n", "\n", "# Fully Connected layer\n", "nfc = 32*32*F\n", "x = tf.reshape(x, [batch_size,-1]); #print('x3=',x.get_shape())\n", "Wfc = tf.Variable(tf.truncated_normal([nfc,nc], stddev=tf.sqrt(6./tf.to_float(nfc+nc)) )); #print('Wfc=',Wfc.get_shape())\n", "bfc = tf.Variable(tf.zeros([nc])); #print('bfc=',bfc.get_shape())\n", "y = tf.matmul(x, Wfc); #print('y1=',y,y.get_shape())\n", "y += bfc; #print('y2=',y,y.get_shape())\n", "\n", "# Softmax\n", "y = tf.nn.softmax(y); #print('y3=',y,y.get_shape())\n", "\n", "# Loss\n", "cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_label * tf.log(y), 1))\n", "total_loss = cross_entropy\n", "\n", "# Optimization scheme\n", "#train_step = tf.train.GradientDescentOptimizer(0.025).minimize(total_loss)\n", "train_step = tf.train.AdamOptimizer(0.001).minimize(total_loss)\n", "\n", "# Accuracy\n", "correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_label,1))\n", "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Iteration i= 0 , train accuracy= 0.09 , loss= 2.30708\n", "test accuracy= 0.11\n", "\n", "Iteration i= 1000 , train accuracy= 0.49 , loss= 1.46592\n", "test accuracy= 0.45\n", "\n", "Iteration i= 2000 , train accuracy= 0.66 , loss= 0.944804\n", "test accuracy= 0.5\n", "\n", "Iteration i= 3000 , train accuracy= 0.67 , loss= 0.939819\n", "test accuracy= 0.49\n", "\n", "Iteration i= 4000 , train accuracy= 0.77 , loss= 0.723346\n", "test accuracy= 0.49\n", "\n", "Iteration i= 5000 , train accuracy= 0.8 , loss= 0.715067\n", "test accuracy= 0.47\n", "\n", "Iteration i= 6000 , train accuracy= 0.77 , loss= 0.644074\n", "test accuracy= 0.48\n", "\n", "Iteration i= 7000 , train accuracy= 0.81 , loss= 0.530919\n", "test accuracy= 0.48\n", "\n", "Iteration i= 8000 , train accuracy= 0.86 , loss= 0.506795\n", "test accuracy= 0.48\n", "\n", "Iteration i= 9000 , train accuracy= 0.89 , loss= 0.344195\n", "test accuracy= 0.46\n", "\n", "Iteration i= 10000 , train accuracy= 0.85 , loss= 0.509171\n", "test accuracy= 0.47\n" ] } ], "source": [ "# Run Computational Graph\n", "n = train_data.shape[0]\n", "indices = collections.deque()\n", "init = tf.initialize_all_variables()\n", "sess = tf.Session()\n", "sess.run(init)\n", "for i in range(10001):\n", " \n", " # Batch extraction\n", " if len(indices) < batch_size:\n", " indices.extend(np.random.permutation(n)) \n", " idx = [indices.popleft() for i in range(batch_size)]\n", " batch_x, batch_y = train_data[idx,:], train_labels[idx]\n", " #print(batch_x.shape,batch_y.shape)\n", " \n", " # Run CG for variable training\n", " _,acc_train,total_loss_o = sess.run([train_step,accuracy,total_loss], feed_dict={xin: batch_x, y_label: batch_y, d: 0.25})\n", " \n", " # Run CG for test set\n", " if not i%1000:\n", " print('\\nIteration i=',i,', train accuracy=',acc_train,', loss=',total_loss_o)\n", " acc_test = sess.run(accuracy, feed_dict={xin: test_data, y_label: test_labels, d: 1.0})\n", " print('test accuracy=',acc_test)" ] } ], "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": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 0 }