{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# E19 - Neural Networks Implementation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It's time to build your first neural network, which will have a hidden layer. \n", "\n", "**You will learn how to:**\n", "- Implement a 2-class classification neural network with a single hidden layer\n", "- Use units with a non-linear activation function, such as tanh \n", "- Compute the cross entropy loss \n", "- Implement forward and backward propagation\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 19.1 Planar data classification" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Package imports\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import sklearn\n", "import sklearn.datasets\n", "import sklearn.linear_model\n", "\n", "%matplotlib inline\n", "\n", "np.random.seed(1) # set a seed so that the results are consistent" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Function toolbox" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# Useful function to deploy your neural network.\n", "def plot_decision_boundary(model, X, y):\n", " plt.figure(figsize=(15,10))\n", " # Set min and max values and give it some padding\n", " x_min, x_max = X[0, :].min() - 1, X[0, :].max() + 1\n", " y_min, y_max = X[1, :].min() - 1, X[1, :].max() + 1\n", " h = 0.01\n", " # Generate a grid of points with distance h between them\n", " xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))\n", " # Predict the function value for the whole grid\n", " Z = model(np.c_[xx.ravel(), yy.ravel()])\n", " Z = Z.reshape(xx.shape)\n", " # Plot the contour and training examples\n", " plt.contourf(xx, yy, Z, cmap=plt.cm.Spectral)\n", " plt.ylabel('x2')\n", " plt.xlabel('x1')\n", " plt.scatter(X[0, :], X[1, :], c=y.ravel(), s=80, cmap=plt.cm.Spectral)\n", " \n", "\n", "def sigmoid(x):\n", " \"\"\"\n", " Compute the sigmoid of x\n", " Arguments:\n", " x -- A scalar or numpy array of any size.\n", " Return:\n", " s -- sigmoid(x)\n", " \"\"\"\n", " s = 1/(1+np.exp(-x))\n", " return s\n", "\n", "def load_planar_dataset():\n", " np.random.seed(1)\n", " m = 400 # number of examples\n", " N = int(m/2) # number of points per class\n", " D = 2 # dimensionality\n", " X = np.zeros((m,D)) # data matrix where each row is a single example\n", " Y = np.zeros((m,1), dtype='uint8') # labels vector (0 for red, 1 for blue)\n", " a = 4 # maximum ray of the flower\n", "\n", " for j in range(2):\n", " ix = range(N*j,N*(j+1))\n", " t = np.linspace(j*3.12,(j+1)*3.12,N) + np.random.randn(N)*0.2 # theta\n", " r = a*np.sin(4*t) + np.random.randn(N)*0.2 # radius\n", " X[ix] = np.c_[r*np.sin(t), r*np.cos(t)]\n", " Y[ix] = j\n", " \n", " X = X.T\n", " Y = Y.T\n", "\n", " return X, Y" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# These functions will be used to test in a simple way the correctness of the procedure. \n", "\n", "def layer_sizes_test_case():\n", " np.random.seed(1)\n", " X_assess = np.random.randn(5, 3)\n", " Y_assess = np.random.randn(2, 3)\n", " return X_assess, Y_assess\n", "\n", "def initialize_parameters_test_case():\n", " n_x, n_h, n_y = 2, 4, 1\n", " return n_x, n_h, n_y\n", "\n", "\n", "def forward_propagation_test_case():\n", " np.random.seed(1)\n", " X_assess = np.random.randn(2, 3)\n", " b1 = np.random.randn(4,1)\n", " b2 = np.array([[ -1.3]])\n", "\n", " parameters = {'W1': np.array([[-0.00416758, -0.00056267],\n", " [-0.02136196, 0.01640271],\n", " [-0.01793436, -0.00841747],\n", " [ 0.00502881, -0.01245288]]),\n", " 'W2': np.array([[-0.01057952, -0.00909008, 0.00551454, 0.02292208]]),\n", " 'b1': b1,\n", " 'b2': b2}\n", "\n", " return X_assess, parameters\n", "\n", "def compute_cost_test_case():\n", " np.random.seed(1)\n", " Y_assess = (np.random.randn(1, 3) > 0)\n", " parameters = {'W1': np.array([[-0.00416758, -0.00056267],\n", " [-0.02136196, 0.01640271],\n", " [-0.01793436, -0.00841747],\n", " [ 0.00502881, -0.01245288]]),\n", " 'W2': np.array([[-0.01057952, -0.00909008, 0.00551454, 0.02292208]]),\n", " 'b1': np.array([[ 0.],\n", " [ 0.],\n", " [ 0.],\n", " [ 0.]]),\n", " 'b2': np.array([[ 0.]])}\n", "\n", " a2 = (np.array([[ 0.5002307 , 0.49985831, 0.50023963]]))\n", " \n", " return a2, Y_assess, parameters\n", "\n", "def backward_propagation_test_case():\n", " np.random.seed(1)\n", " X_assess = np.random.randn(2, 3)\n", " Y_assess = (np.random.randn(1, 3) > 0)\n", " parameters = {'W1': np.array([[-0.00416758, -0.00056267],\n", " [-0.02136196, 0.01640271],\n", " [-0.01793436, -0.00841747],\n", " [ 0.00502881, -0.01245288]]),\n", " 'W2': np.array([[-0.01057952, -0.00909008, 0.00551454, 0.02292208]]),\n", " 'b1': np.array([[ 0.],\n", " [ 0.],\n", " [ 0.],\n", " [ 0.]]),\n", " 'b2': np.array([[ 0.]])}\n", "\n", " cache = {'A1': np.array([[-0.00616578, 0.0020626 , 0.00349619],\n", " [-0.05225116, 0.02725659, -0.02646251],\n", " [-0.02009721, 0.0036869 , 0.02883756],\n", " [ 0.02152675, -0.01385234, 0.02599885]]),\n", " 'A2': np.array([[ 0.5002307 , 0.49985831, 0.50023963]]),\n", " 'Z1': np.array([[-0.00616586, 0.0020626 , 0.0034962 ],\n", " [-0.05229879, 0.02726335, -0.02646869],\n", " [-0.02009991, 0.00368692, 0.02884556],\n", " [ 0.02153007, -0.01385322, 0.02600471]]),\n", " 'Z2': np.array([[ 0.00092281, -0.00056678, 0.00095853]])}\n", " return parameters, cache, X_assess, Y_assess\n", "\n", "def update_parameters_test_case():\n", " parameters = {'W1': np.array([[-0.00615039, 0.0169021 ],\n", " [-0.02311792, 0.03137121],\n", " [-0.0169217 , -0.01752545],\n", " [ 0.00935436, -0.05018221]]),\n", " 'W2': np.array([[-0.0104319 , -0.04019007, 0.01607211, 0.04440255]]),\n", " 'b1': np.array([[ -8.97523455e-07],\n", " [ 8.15562092e-06],\n", " [ 6.04810633e-07],\n", " [ -2.54560700e-06]]),\n", " 'b2': np.array([[ 9.14954378e-05]])}\n", "\n", " grads = {'dW1': np.array([[ 0.00023322, -0.00205423],\n", " [ 0.00082222, -0.00700776],\n", " [-0.00031831, 0.0028636 ],\n", " [-0.00092857, 0.00809933]]),\n", " 'dW2': np.array([[ -1.75740039e-05, 3.70231337e-03, -1.25683095e-03,\n", " -2.55715317e-03]]),\n", " 'db1': np.array([[ 1.05570087e-07],\n", " [ -3.81814487e-06],\n", " [ -1.90155145e-07],\n", " [ 5.46467802e-07]]),\n", " 'db2': np.array([[ -1.08923140e-05]])}\n", " return parameters, grads\n", "\n", "def nn_model_test_case():\n", " np.random.seed(1)\n", " X_assess = np.random.randn(2, 3)\n", " Y_assess = (np.random.randn(1, 3) > 0)\n", " return X_assess, Y_assess\n", "\n", "def predict_test_case():\n", " np.random.seed(1)\n", " X_assess = np.random.randn(2, 3)\n", " parameters = {'W1': np.array([[-0.00615039, 0.0169021 ],\n", " [-0.02311792, 0.03137121],\n", " [-0.0169217 , -0.01752545],\n", " [ 0.00935436, -0.05018221]]),\n", " 'W2': np.array([[-0.0104319 , -0.04019007, 0.01607211, 0.04440255]]),\n", " 'b1': np.array([[ -8.97523455e-07],\n", " [ 8.15562092e-06],\n", " [ 6.04810633e-07],\n", " [ -2.54560700e-06]]),\n", " 'b2': np.array([[ 9.14954378e-05]])}\n", " return parameters, X_assess" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Create Dataset\n", "\n", "First, let's get the dataset you will work on. The following code will load a \"flower\" 2-class dataset into variables `X` and `Y`." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "X, Y = load_planar_dataset()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visualize the dataset using matplotlib. The data looks like a \"flower\" with some red (label y=0) and some blue (y=1) points. Your goal is to build a model to fit this data. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Visualize the data:\n", "plt.figure(figsize=(15,10))\n", "plt.scatter(X[0, :], X[1, :], c=Y.ravel(), s=40, cmap=plt.cm.Spectral);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You have:\n", " - a numpy-array (matrix) X that contains your features (x1, x2)\n", " - a numpy-array (vector) Y that contains your labels (red:0, blue:1).\n", "\n", "Lets first get a better sense of what our data is like. \n", "\n", "**Exercise**: How many training examples do you have? In addition, what is the `shape` of the variables `X` and `Y`? " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Simple Logistic Regression Baseline\n", "\n", "Before building a full neural network, lets first see how logistic regression performs on this problem. You can use sklearn's built-in functions to do that. Run the code below to train a logistic regression classifier on the dataset." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# Train the logistic regression classifier\n", "clf = sklearn.linear_model.LogisticRegressionCV(cv=10);\n", "clf.fit(X.T, Y.ravel().T);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can now plot the decision boundary of these models. Run the code below." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Accuracy of logistic regression: 46 % (percentage of correctly labelled datapoints)\n" ] } ], "source": [ "# Plot the decision boundary for logistic regression\n", "plot_decision_boundary(lambda x: clf.predict(x), X, Y)\n", "plt.title(\"Logistic Regression\")\n", "plt.show()\n", "# Print accuracy\n", "LR_predictions = clf.predict(X.T)\n", "print ('Accuracy of logistic regression: %d ' % float((np.dot(Y,LR_predictions) + np.dot(1-Y,1-LR_predictions))/float(Y.size)*100) +\n", " '% ' + \"(percentage of correctly labelled datapoints)\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Exercise**: Why is the model performance too low? Explain it with the knowledge you learnt in class." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Neural Network model - MLP\n", "\n", "Logistic regression did not work well on the \"flower dataset\". You are going to train a Neural Network with a single hidden layer.\n", "\n", "**Here is our model**:\n", "\n", "\n", "**Mathematically**:\n", "\n", "For one example $x^{(i)}$:\n", "$$z^{[1] (i)} = W^{[1]} x^{(i)} + b^{[1]}\\tag{1}$$ \n", "$$a^{[1] (i)} = \\tanh(z^{[1] (i)})\\tag{2}$$\n", "$$z^{[2] (i)} = W^{[2]} a^{[1] (i)} + b^{[2]}\\tag{3}$$\n", "$$\\hat{y}^{(i)} = a^{[2] (i)} = \\sigma(z^{ [2] (i)})\\tag{4}$$\n", "$$y^{(i)}_{prediction} = \\begin{cases} 1 & \\mbox{if } a^{[2](i)} > 0.5 \\\\ 0 & \\mbox{otherwise } \\end{cases}\\tag{5}$$\n", "\n", "Given the predictions on all the examples, you can also compute the cost $J$ as follows: \n", "$$J = - \\frac{1}{m} \\sum\\limits_{i = 0}^{m} \\large\\left(\\small y^{(i)}\\log\\left(a^{[2] (i)}\\right) + (1-y^{(i)})\\log\\left(1- a^{[2] (i)}\\right) \\large \\right) \\small \\tag{6}$$\n", "\n", "**Reminder**: The general methodology to build a Neural Network is to:\n", " 1. Define the neural network structure ( # of input units, # of hidden units, etc). \n", " 2. Initialize the model's parameters\n", " 3. Loop:\n", " - Implement forward propagation\n", " - Compute loss\n", " - Implement backward propagation to get the gradients\n", " - Update parameters (gradient descent)\n", "\n", "You often build helper functions to compute steps 1-3 and then merge them into one function we call `nn_model()`. Once you've built `nn_model()` and learnt the right parameters, you can make predictions on new data." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Defining the neural network structure ####\n", "\n", "**Exercise**: Define three variables:\n", " - n_x: the size of the input layer\n", " - n_h: the size of the hidden layer (set this to 4) \n", " - n_y: the size of the output layer\n", "\n", "**Hint**: Use shapes of X and Y to find n_x and n_y. Also, hard code the hidden layer size to be 4." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# Solved Exercise\n", "\n", "def layer_sizes(X, Y):\n", " \"\"\"\n", " Arguments:\n", " X -- input dataset of shape (input size, number of examples)\n", " Y -- labels of shape (output size, number of examples)\n", " \n", " Returns:\n", " n_x -- the size of the input layer\n", " n_h -- the size of the hidden layer\n", " n_y -- the size of the output layer\n", " \"\"\"\n", " ### START CODE HERE ### (≈ 3 lines of code)\n", " n_x = X.shape[0] # size of input layer\n", " n_h = 4\n", " n_y = Y.shape[0] # size of output layer\n", " ### END CODE HERE ###\n", " return (n_x, n_h, n_y)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The size of the input layer is: n_x = 5\n", "The size of the hidden layer is: n_h = 4\n", "The size of the output layer is: n_y = 2\n" ] } ], "source": [ "X_assess, Y_assess = layer_sizes_test_case()\n", "(n_x, n_h, n_y) = layer_sizes(X_assess, Y_assess)\n", "print(\"The size of the input layer is: n_x = \" + str(n_x))\n", "print(\"The size of the hidden layer is: n_h = \" + str(n_h))\n", "print(\"The size of the output layer is: n_y = \" + str(n_y))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output** (these are not the sizes you will use for your network, they are just used to assess the function you've just coded).\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
**n_x** 5
**n_h** 4
**n_y** 2
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Initialize the model's parameters ####\n", "\n", "**Exercise**: Implement the function `initialize_parameters()`.\n", "\n", "**Instructions**:\n", "- Make sure your parameters' sizes are right. Refer to the neural network figure above if needed.\n", "- You will initialize the weights matrices with random values. \n", " - Use: `np.random.randn(a,b) * 0.01` to randomly initialize a matrix of shape (a,b).\n", "- You will initialize the bias vectors as zeros. \n", " - Use: `np.zeros((a,b))` to initialize a matrix of shape (a,b) with zeros." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# Solved Exercise: initialize_parameters\n", "\n", "def initialize_parameters(n_x, n_h, n_y):\n", " \"\"\"\n", " Argument:\n", " n_x -- size of the input layer\n", " n_h -- size of the hidden layer\n", " n_y -- size of the output layer\n", " \n", " Returns:\n", " params -- python dictionary containing your parameters:\n", " W1 -- weight matrix of shape (n_h, n_x)\n", " b1 -- bias vector of shape (n_h, 1)\n", " W2 -- weight matrix of shape (n_y, n_h)\n", " b2 -- bias vector of shape (n_y, 1)\n", " \"\"\"\n", " \n", " np.random.seed(2) # we set up a seed so that your output matches ours although the initialization is random.\n", " \n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " W1 = np.random.randn(n_h,n_x) * 0.01\n", " b1 = np.zeros(shape=(n_h,1))\n", " W2 = np.random.randn(n_y,n_h) * 0.01\n", " b2 = np.zeros(shape=(n_y,1))\n", " ### END CODE HERE ###\n", " \n", " assert (W1.shape == (n_h, n_x))\n", " assert (b1.shape == (n_h, 1))\n", " assert (W2.shape == (n_y, n_h))\n", " assert (b2.shape == (n_y, 1))\n", " \n", " parameters = {\"W1\": W1,\n", " \"b1\": b1,\n", " \"W2\": W2,\n", " \"b2\": b2}\n", " \n", " return parameters" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "W1 = [[-0.00416758 -0.00056267]\n", " [-0.02136196 0.01640271]\n", " [-0.01793436 -0.00841747]\n", " [ 0.00502881 -0.01245288]]\n", "b1 = [[0.]\n", " [0.]\n", " [0.]\n", " [0.]]\n", "W2 = [[-0.01057952 -0.00909008 0.00551454 0.02292208]]\n", "b2 = [[0.]]\n" ] } ], "source": [ "n_x, n_h, n_y = initialize_parameters_test_case()\n", "\n", "parameters = initialize_parameters(n_x, n_h, n_y)\n", "print(\"W1 = \" + str(parameters[\"W1\"]))\n", "print(\"b1 = \" + str(parameters[\"b1\"]))\n", "print(\"W2 = \" + str(parameters[\"W2\"]))\n", "print(\"b2 = \" + str(parameters[\"b2\"]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "
**W1** [[-0.00416758 -0.00056267]\n", " [-0.02136196 0.01640271]\n", " [-0.01793436 -0.00841747]\n", " [ 0.00502881 -0.01245288]]
**b1** [[ 0.]\n", " [ 0.]\n", " [ 0.]\n", " [ 0.]]
**W2** [[-0.01057952 -0.00909008 0.00551454 0.02292208]]
**b2** [[ 0.]]
\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The Loop ####\n", "\n", "**Question**: Implement `forward_propagation()`.\n", "\n", "**Instructions**:\n", "- Look above at the mathematical representation of your classifier.\n", "- You can use the function `sigmoid()`. It is built-in (imported) in the notebook.\n", "- You can use the function `np.tanh()`. It is part of the numpy library.\n", "- The steps you have to implement are:\n", " 1. Retrieve each parameter from the dictionary \"parameters\" (which is the output of `initialize_parameters()`) by using `parameters[\"..\"]`.\n", " 2. Implement Forward Propagation. Compute $Z^{[1]}, A^{[1]}, Z^{[2]}$ and $A^{[2]}$ (the vector of all your predictions on all the examples in the training set).\n", "- Values needed in the backpropagation are stored in \"`cache`\". The `cache` will be given as an input to the backpropagation function." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "# Solved Exercise: forward_propagation\n", "\n", "def forward_propagation(X, parameters):\n", " \"\"\"\n", " Argument:\n", " X -- input data of size (n_x, m)\n", " parameters -- python dictionary containing your parameters (output of initialization function)\n", " \n", " Returns:\n", " A2 -- The sigmoid output of the second activation\n", " cache -- a dictionary containing \"Z1\", \"A1\", \"Z2\" and \"A2\"\n", " \"\"\"\n", " # Retrieve each parameter from the dictionary \"parameters\"\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " W1 = parameters[\"W1\"]\n", " b1 = parameters[\"b1\"]\n", " W2 = parameters[\"W2\"]\n", " b2 = parameters[\"b2\"]\n", " ### END CODE HERE ###\n", " \n", " # Implement Forward Propagation to calculate A2 (probabilities)\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " Z1 = np.dot(W1,X)+b1\n", " A1 = np.tanh(Z1)\n", " Z2 = np.dot(W2,A1)+b2\n", " A2 = sigmoid(Z2)\n", " ### END CODE HERE ###\n", " \n", " assert(A2.shape == (1, X.shape[1]))\n", " \n", " cache = {\"Z1\": Z1,\n", " \"A1\": A1,\n", " \"Z2\": Z2,\n", " \"A2\": A2}\n", " \n", " return A2, cache" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.26281864019752443 0.09199904522700113 -1.3076660128732143 0.21287768171914198\n" ] } ], "source": [ "X_assess, parameters = forward_propagation_test_case()\n", "A2, cache = forward_propagation(X_assess, parameters)\n", "\n", "# Note: we use the mean here just to make sure that your output matches ours. \n", "print(np.mean(cache['Z1']) ,np.mean(cache['A1']),np.mean(cache['Z2']),np.mean(cache['A2']))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", " \n", " \n", " \n", "
0.262818640198 0.091999045227 -1.30766601287 0.212877681719
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that you have computed $A^{[2]}$ (in the Python variable \"`A2`\"), which contains $a^{[2](i)}$ for every example, you can compute the cost function as follows:\n", "\n", "$$J = - \\frac{1}{m} \\sum\\limits_{i = 0}^{m} \\large{(} \\small y^{(i)}\\log\\left(a^{[2] (i)}\\right) + (1-y^{(i)})\\log\\left(1- a^{[2] (i)}\\right) \\large{)} \\small\\tag{13}$$\n", "\n", "**Exercise**: Implement `compute_cost()` to compute the value of the cost $J$.\n", "\n", "**Instructions**:\n", "- There are many ways to implement the cross-entropy loss. To help you, we give you how we would have implemented\n", "$- \\sum\\limits_{i=0}^{m} y^{(i)}\\log(a^{[2](i)})$:\n", "```python\n", "logprobs = np.multiply(np.log(A2),Y)\n", "cost = - np.sum(logprobs) # no need to use a for loop!\n", "```\n", "\n", "(you can use either `np.multiply()` and then `np.sum()` or directly `np.dot()`).\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# Solved function: compute_cost\n", "\n", "def compute_cost(A2, Y, parameters):\n", " \"\"\"\n", " Computes the cross-entropy cost given in equation (13)\n", " \n", " Arguments:\n", " A2 -- The sigmoid output of the second activation, of shape (1, number of examples)\n", " Y -- \"true\" labels vector of shape (1, number of examples)\n", " parameters -- python dictionary containing your parameters W1, b1, W2 and b2\n", " \n", " Returns:\n", " cost -- cross-entropy cost given equation (13)\n", " \"\"\"\n", " \n", " m = Y.shape[1] # number of example\n", "\n", " # Compute the cross-entropy cost\n", " ### START CODE HERE ### (≈ 2 lines of code)\n", " logprobs = np.multiply(Y,np.log(A2)) + np.multiply(1-Y,np.log(1-A2))\n", " cost = -1/m * np.sum(logprobs)\n", " ### END CODE HERE ###\n", " \n", " cost = np.squeeze(cost) # makes sure cost is the dimension we expect. \n", " # E.g., turns [[17]] into 17 \n", " assert(isinstance(cost, float))\n", " \n", " return cost" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "cost = 0.6930587610394646\n" ] } ], "source": [ "A2, Y_assess, parameters = compute_cost_test_case()\n", "\n", "print(\"cost = \" + str(compute_cost(A2, Y_assess, parameters)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", " \n", " \n", " \n", " \n", " \n", "
**cost** 0.693058761...
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using the cache computed during forward propagation, you can now implement backward propagation.\n", "\n", "**Question**: Implement the function `backward_propagation()`.\n", "\n", "**Instructions**:\n", "Backpropagation is usually the hardest (most mathematical) part in deep learning. To help you, here again is the slide from the lecture on backpropagation. You'll want to use the six equations on the right of this slide, since you are building a vectorized implementation. \n", "\n", "\n", "\n", "\n", "\n", "- Tips:\n", " - To compute dZ1 you'll need to compute $g^{[1]'}(Z^{[1]})$. Since $g^{[1]}(.)$ is the tanh activation function, if $a = g^{[1]}(z)$ then $g^{[1]'}(z) = 1-a^2$. So you can compute \n", " $g^{[1]'}(Z^{[1]})$ using `(1 - np.power(A1, 2))`." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "# Solved Function: backward_propagation\n", "\n", "def backward_propagation(parameters, cache, X, Y):\n", " \"\"\"\n", " Implement the backward propagation using the instructions above.\n", " \n", " Arguments:\n", " parameters -- python dictionary containing our parameters \n", " cache -- a dictionary containing \"Z1\", \"A1\", \"Z2\" and \"A2\".\n", " X -- input data of shape (2, number of examples)\n", " Y -- \"true\" labels vector of shape (1, number of examples)\n", " \n", " Returns:\n", " grads -- python dictionary containing your gradients with respect to different parameters\n", " \"\"\"\n", " m = X.shape[1]\n", " \n", " # First, retrieve W1 and W2 from the dictionary \"parameters\".\n", " ### START CODE HERE ### (≈ 2 lines of code)\n", " W1 = parameters[\"W1\"]\n", " W2 = parameters[\"W2\"]\n", " ### END CODE HERE ###\n", " \n", " # Retrieve also A1 and A2 from dictionary \"cache\".\n", " ### START CODE HERE ### (≈ 2 lines of code)\n", " A1 = cache[\"A1\"]\n", " A2 = cache[\"A2\"]\n", " ### END CODE HERE ###\n", " \n", " # Backward propagation: calculate dW1, db1, dW2, db2. \n", " ### START CODE HERE ### (≈ 6 lines of code, corresponding to 6 equations on slide above)\n", " dZ2 = A2 - Y\n", " dW2 = 1/m * np.dot(dZ2,A1.T)\n", " db2 = 1/m*np.sum(dZ2,axis=1,keepdims=True)\n", " dZ1 = np.dot(W2.T,dZ2) * (1 - np.power(A1,2))\n", " dW1 = 1/m* np.dot(dZ1,X.T)\n", " db1 = 1/m*np.sum(dZ1,axis=1,keepdims=True)\n", " ### END CODE HERE ###\n", " \n", " grads = {\"dW1\": dW1,\n", " \"db1\": db1,\n", " \"dW2\": dW2,\n", " \"db2\": db2}\n", " \n", " return grads" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dW1 = [[ 0.00301023 -0.00747267]\n", " [ 0.00257968 -0.00641288]\n", " [-0.00156892 0.003893 ]\n", " [-0.00652037 0.01618243]]\n", "db1 = [[ 0.00176201]\n", " [ 0.00150995]\n", " [-0.00091736]\n", " [-0.00381422]]\n", "dW2 = [[ 0.00078841 0.01765429 -0.00084166 -0.01022527]]\n", "db2 = [[-0.16655712]]\n" ] } ], "source": [ "parameters, cache, X_assess, Y_assess = backward_propagation_test_case()\n", "\n", "grads = backward_propagation(parameters, cache, X_assess, Y_assess)\n", "print (\"dW1 = \"+ str(grads[\"dW1\"]))\n", "print (\"db1 = \"+ str(grads[\"db1\"]))\n", "print (\"dW2 = \"+ str(grads[\"dW2\"]))\n", "print (\"db2 = \"+ str(grads[\"db2\"]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected output**:\n", "\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "
**dW1** [[ 0.00301023 -0.00747267]\n", " [ 0.00257968 -0.00641288]\n", " [-0.00156892 0.003893 ]\n", " [-0.00652037 0.01618243]]
**db1** [[ 0.00176201]\n", " [ 0.00150995]\n", " [-0.00091736]\n", " [-0.00381422]]
**dW2** [[ 0.00078841 0.01765429 -0.00084166 -0.01022527]]
**db2** [[-0.16655712]]
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Question**: Implement the update rule. Use gradient descent. You have to use (dW1, db1, dW2, db2) in order to update (W1, b1, W2, b2).\n", "\n", "**General gradient descent rule**: $ \\theta = \\theta - \\alpha \\frac{\\partial J }{ \\partial \\theta }$ where $\\alpha$ is the learning rate and $\\theta$ represents a parameter.\n", "\n", "**Illustration**: The gradient descent algorithm with a good learning rate (converging) and a bad learning rate (diverging). Images courtesy of Adam Harley.\n", "\n", " \n", "\n" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "# Solved Function : update_parameters\n", "\n", "def update_parameters(parameters, grads, learning_rate = 1.2):\n", " \"\"\"\n", " Updates parameters using the gradient descent update rule given above\n", " \n", " Arguments:\n", " parameters -- python dictionary containing your parameters \n", " grads -- python dictionary containing your gradients \n", " \n", " Returns:\n", " parameters -- python dictionary containing your updated parameters \n", " \"\"\"\n", " # Retrieve each parameter from the dictionary \"parameters\"\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " W1 = parameters[\"W1\"]\n", " b1 = parameters[\"b1\"]\n", " W2 = parameters[\"W2\"]\n", " b2 = parameters[\"b2\"]\n", " ### END CODE HERE ###\n", " \n", " # Retrieve each gradient from the dictionary \"grads\"\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " dW1 = grads[\"dW1\"]\n", " db1 = grads[\"db1\"]\n", " dW2 = grads[\"dW2\"]\n", " db2 = grads[\"db2\"]\n", " ## END CODE HERE ###\n", " \n", " # Update rule for each parameter\n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " W1 = W1 - learning_rate * dW1\n", " b1 = b1 - learning_rate * db1\n", " W2 = W2 - learning_rate * dW2\n", " b2 = b2 - learning_rate * db2\n", " ### END CODE HERE ###\n", " \n", " parameters = {\"W1\": W1,\n", " \"b1\": b1,\n", " \"W2\": W2,\n", " \"b2\": b2}\n", " \n", " return parameters" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "W1 = [[-0.00643025 0.01936718]\n", " [-0.02410458 0.03978052]\n", " [-0.01653973 -0.02096177]\n", " [ 0.01046864 -0.05990141]]\n", "b1 = [[-1.02420756e-06]\n", " [ 1.27373948e-05]\n", " [ 8.32996807e-07]\n", " [-3.20136836e-06]]\n", "W2 = [[-0.01041081 -0.04463285 0.01758031 0.04747113]]\n", "b2 = [[0.00010457]]\n" ] } ], "source": [ "parameters, grads = update_parameters_test_case()\n", "parameters = update_parameters(parameters, grads)\n", "\n", "print(\"W1 = \" + str(parameters[\"W1\"]))\n", "print(\"b1 = \" + str(parameters[\"b1\"]))\n", "print(\"W2 = \" + str(parameters[\"W2\"]))\n", "print(\"b2 = \" + str(parameters[\"b2\"]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "
**W1** [[-0.00643025 0.01936718]\n", " [-0.02410458 0.03978052]\n", " [-0.01653973 -0.02096177]\n", " [ 0.01046864 -0.05990141]]
**b1** [[ -1.02420756e-06]\n", " [ 1.27373948e-05]\n", " [ 8.32996807e-07]\n", " [ -3.20136836e-06]]
**W2** [[-0.01041081 -0.04463285 0.01758031 0.04747113]]
**b2** [[ 0.00010457]]
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Integrate parts [Network structure ,Model Parameters, the loop] in nn_model() ####\n", "\n", "**Question**: Build your neural network model in `nn_model()`.\n", "\n", "**Instructions**: The neural network model has to use the previous functions in the right order." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "# Solved Function: nn_model\n", "\n", "def nn_model(X, Y, n_h, num_iterations = 10000, print_cost=False):\n", " \"\"\"\n", " Arguments:\n", " X -- dataset of shape (2, number of examples)\n", " Y -- labels of shape (1, number of examples)\n", " n_h -- size of the hidden layer\n", " num_iterations -- Number of iterations in gradient descent loop\n", " print_cost -- if True, print the cost every 1000 iterations\n", " \n", " Returns:\n", " parameters -- parameters learnt by the model. They can then be used to predict.\n", " \"\"\"\n", " \n", " np.random.seed(3)\n", " n_x = layer_sizes(X, Y)[0]\n", " n_y = layer_sizes(X, Y)[2]\n", " \n", " # Initialize parameters, then retrieve W1, b1, W2, b2. Inputs: \"n_x, n_h, n_y\". Outputs = \"W1, b1, W2, b2, parameters\".\n", " ### START CODE HERE ### (≈ 5 lines of code)\n", " parameters = initialize_parameters(n_x,n_h,n_y)\n", " W1 = parameters[\"W1\"]\n", " b1 = parameters[\"b1\"]\n", " W2 = parameters[\"W2\"]\n", " b2 = parameters[\"b2\"]\n", " ### END CODE HERE ###\n", " \n", " # Loop (gradient descent)\n", "\n", " for i in range(0, num_iterations):\n", " \n", " ### START CODE HERE ### (≈ 4 lines of code)\n", " # Forward propagation. Inputs: \"X, parameters\". Outputs: \"A2, cache\".\n", " A2, cache = forward_propagation(X, parameters)\n", " \n", " # Cost function. Inputs: \"A2, Y, parameters\". Outputs: \"cost\".\n", " cost = compute_cost(A2,Y,parameters)\n", " \n", " # Backpropagation. Inputs: \"parameters, cache, X, Y\". Outputs: \"grads\".\n", " grads = backward_propagation(parameters,cache,X,Y)\n", " \n", " # Gradient descent parameter update. Inputs: \"parameters, grads\". Outputs: \"parameters\".\n", " parameters = update_parameters(parameters,grads)\n", " \n", " ### END CODE HERE ###\n", " \n", " # Print the cost every 1000 iterations\n", " if print_cost and i % 1000 == 0:\n", " print (\"Cost after iteration %i: %f\" %(i, cost))\n", "\n", " return parameters" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Cost after iteration 0: 0.692739\n", "Cost after iteration 1000: 0.000218\n", "Cost after iteration 2000: 0.000107\n", "Cost after iteration 3000: 0.000071\n", "Cost after iteration 4000: 0.000053\n", "Cost after iteration 5000: 0.000042\n", "Cost after iteration 6000: 0.000035\n", "Cost after iteration 7000: 0.000030\n", "Cost after iteration 8000: 0.000026\n", "Cost after iteration 9000: 0.000023\n", "W1 = [[-0.65848169 1.21866811]\n", " [-0.76204273 1.39377573]\n", " [ 0.5792005 -1.10397703]\n", " [ 0.76773391 -1.41477129]]\n", "b1 = [[ 0.287592 ]\n", " [ 0.3511264 ]\n", " [-0.2431246 ]\n", " [-0.35772805]]\n", "W2 = [[-2.45566237 -3.27042274 2.00784958 3.36773273]]\n", "b2 = [[0.20459656]]\n" ] } ], "source": [ "X_assess, Y_assess = nn_model_test_case()\n", "parameters = nn_model(X_assess, Y_assess, 4, num_iterations=10000, print_cost=True)\n", "print(\"W1 = \" + str(parameters[\"W1\"]))\n", "print(\"b1 = \" + str(parameters[\"b1\"]))\n", "print(\"W2 = \" + str(parameters[\"W2\"]))\n", "print(\"b2 = \" + str(parameters[\"b2\"]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "
\n", " **cost after iteration 0**\n", " \n", " 0.692739\n", "
\n", "
$\\vdots$
\n", "
\n", "
$\\vdots$
\n", "
**W1** [[-0.65848169 1.21866811]\n", " [-0.76204273 1.39377573]\n", " [ 0.5792005 -1.10397703]\n", " [ 0.76773391 -1.41477129]]
**b1** [[ 0.287592 ]\n", " [ 0.3511264 ]\n", " [-0.2431246 ]\n", " [-0.35772805]]
**W2** [[-2.45566237 -3.27042274 2.00784958 3.36773273]]
**b2** [[ 0.20459656]]
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Predictions\n", "\n", "**Question**: Use your model to predict by building predict().\n", "Use forward propagation to predict results.\n", "\n", "**Reminder**: predictions = $y_{prediction} = \\mathbb 1 \\text{{activation > 0.5}} = \\begin{cases}\n", " 1 & \\text{if}\\ activation > 0.5 \\\\\n", " 0 & \\text{otherwise}\n", " \\end{cases}$ \n", " \n", "As an example, if you would like to set the entries of a matrix X to 0 and 1 based on a threshold you would do: ```X_new = (X > threshold)```" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "# Solved Function: predict\n", "\n", "def predict(parameters, X):\n", " \"\"\"\n", " Using the learned parameters, predicts a class for each example in X\n", " \n", " Arguments:\n", " parameters -- python dictionary containing your parameters \n", " X -- input data of size (n_x, m)\n", " \n", " Returns\n", " predictions -- vector of predictions of our model (red: 0 / blue: 1)\n", " \"\"\"\n", " \n", " # Computes probabilities using forward propagation, and classifies to 0/1 using 0.5 as the threshold.\n", " ### START CODE HERE ### (≈ 2 lines of code)\n", " A2, cache = forward_propagation(X,parameters)\n", " predictions = A2 > 0.5\n", " ### END CODE HERE ###\n", " \n", " return predictions" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "predictions mean = 0.6666666666666666\n" ] } ], "source": [ "parameters, X_assess = predict_test_case()\n", "\n", "predictions = predict(parameters, X_assess)\n", "print(\"predictions mean = \" + str(np.mean(predictions)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**: \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", "
**predictions mean** 0.666666666667
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is time to run the model and see how it performs on a planar dataset. Run the following code to test your model with a single hidden layer of $n_h$ hidden units." ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Cost after iteration 0: 0.693048\n", "Cost after iteration 1000: 0.288083\n", "Cost after iteration 2000: 0.254385\n", "Cost after iteration 3000: 0.233864\n", "Cost after iteration 4000: 0.226792\n", "Cost after iteration 5000: 0.222644\n", "Cost after iteration 6000: 0.219731\n", "Cost after iteration 7000: 0.217504\n", "Cost after iteration 8000: 0.219467\n", "Cost after iteration 9000: 0.218561\n" ] }, { "data": { "text/plain": [ "Text(0.5, 1.0, 'Decision Boundary for hidden layer size 4')" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Build a model with a n_h-dimensional hidden layer\n", "parameters = nn_model(X, Y, n_h = 4, num_iterations = 10000, print_cost=True)\n", "\n", "# Plot the decision boundary\n", "plot_decision_boundary(lambda x: predict(parameters, x.T), X, Y)\n", "plt.title(\"Decision Boundary for hidden layer size \" + str(4))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**:\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", "
**Cost after iteration 9000** 0.218607
\n" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 90%\n" ] } ], "source": [ "# Print accuracy\n", "predictions = predict(parameters, X)\n", "print ('Accuracy: %d' % float((np.dot(Y,predictions.T) + np.dot(1-Y,1-predictions.T))/float(Y.size)*100) + '%')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Expected Output**: \n", "\n", "\n", " \n", " \n", " \n", " \n", "
**Accuracy** 90%
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Accuracy is really high compared to Logistic Regression. The model has learnt the leaf patterns of the flower! Neural networks are able to learn even highly non-linear decision boundaries, unlike logistic regression. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 19.2 Tunning hidden layer size " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Exercise:** \n", "Iterate over the number of hidden neurons and report the accuracy and boundary decision plot. Expected results are as follows(Include plots and accuracy).\n", "\n", "" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 19.2 Moons Dataset \n", "\n", "Replicate the planar points model and report your best accuracy and decision boundary" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from sklearn.datasets.samples_generator import make_moons\n", "\n", "x_train, y_train = make_moons(n_samples=1000, noise= 0.2, random_state=3)\n", "plt.figure(figsize=(15, 10))\n", "plt.scatter(x_train[:, 0], x_train[:,1], c=y_train, s=40, cmap=plt.cm.Spectral);" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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": "3.6.7" } }, "nbformat": 4, "nbformat_minor": 2 }