diff --git a/2-cnn-and-adversarials/1 Intro CNN.ipynb b/2-cnn-and-adversarials/1 Intro CNN.ipynb new file mode 100644 index 0000000..0adafd8 --- /dev/null +++ b/2-cnn-and-adversarials/1 Intro CNN.ipynb @@ -0,0 +1,4424 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "
\n", + " The notebook is using\n", + " \n", + " no$\\TeX$book Jupyter Theme (release 2.0.1).\n", + "\n", + "
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%load_ext notexbook\n", + "\n", + "%texify -fs 18" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Deep Networks in a Nutshell" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\"learning\n", + "\n", + "**Source**: Antiga, L et al. _Deep Learning with PyTorch_ [link](https://www.manning.com/books/deep-learning-with-pytorch)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Setup the learning process\n", + "\n", + "**Main Components of the learning process of a `NN`**:\n", + "\n", + "\"Main\n", + "\n", + "**Source**: Antiga, L et al. _Deep Learning with PyTorch_ [link](https://www.manning.com/books/deep-learning-with-pytorch)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "# Convolutional Neural Network" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "A convolutional neural network (CNN, or ConvNet) is a type of **feed-forward** artificial neural network in which the connectivity pattern between its neurons is inspired by the organization of the animal visual cortex." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "The networks consist of multiple layers of small neuron collections which process portions of the input image, called **receptive fields**. \n", + "\n", + "The outputs of these collections are then tiled so that their input regions overlap, to obtain a _better representation_ of the original image; this is repeated for every such layer." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "## How does it look like?" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "-" + } + }, + "source": [ + "\n", + "\n", + "> source: https://flickrcode.files.wordpress.com/2014/10/conv-net2.png" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "## The Problem Space \n", + "\n", + "### Image Classification" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Image classification is the task of taking an input image and outputting a class (a cat, dog, etc) or a probability of classes that best describes the image. \n", + "\n", + "For humans, this task of recognition is one of the first skills we learn from the moment we are born and is one that comes naturally and effortlessly as adults." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "These skills of being able to quickly recognize patterns, *generalize* from prior knowledge, and adapt to different image environments are ones that we do not share with machines." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "#### Inputs and Outputs" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "source: [http://www.pawbuzz.com/wp-content/uploads/sites/551/2014/11/corgi-puppies-21.jpg]()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "When a computer sees an image (takes an image as input), it will see an array of pixel values. \n", + "\n", + "Depending on the resolution and size of the image, it will see a 32 x 32 x 3 array of numbers (The 3 refers to RGB values).\n", + "\n", + "let's say we have a color image in JPG form and its size is 480 x 480. The representative array will be 480 x 480 x 3. Each of these numbers is given a value from 0 to 255 which describes the pixel intensity at that point." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "#### Goal" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "What we want the computer to do is to be able to differentiate between all the images it’s given and figure out the unique features that make a dog a dog or that make a cat a cat. " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "When we look at a picture of a dog, we can classify it as such if the picture has identifiable features such as paws or 4 legs. \n", + "\n", + "In a similar way, the computer should be able to perform image classification by looking for *low level* features such as edges and curves, and then building up to more abstract concepts through a series of **convolutional layers**." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Structure of a CNN" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> A more detailed overview of what CNNs do would be that you take the image, pass it through a series of convolutional, nonlinear, pooling (downsampling), and fully connected layers, and get an output. As we said earlier, the output can be a single class or a probability of classes that best describes the image. \n", + "\n", + "source: [1]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "#### Convolutional Layer" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "The first layer in a CNN is always a **Convolutional Layer**." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### tldr;" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "**Reference**: [conv_arithmetic](https://github.com/vdumoulin/conv_arithmetic)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "#### Convolutional filters\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A Convolutional filter much like a **kernel** in image recognition is a small matrix useful for blurring, sharpening, embossing, edge detection, and more. \n", + "\n", + "This is accomplished by means of convolution between a kernel and an image.\n", + "\n", + "The main goal of CNN is to **learn** the convolutional filters to be applied on images." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "As the filter is sliding, or **convolving**, around the input image, it is multiplying the values in the filter with the original pixel values of the image
\n", + "(a.k.a. computing **element wise multiplications**)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Now, we repeat this process for every location on the input volume. (Next step would be moving the filter to the right by 1 unit, then right again by 1, and so on)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "After sliding the filter over all the locations, we are left with an array of numbers usually called an **activation map** or **feature map**." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "### Convolution in a Nutshell\n", + "\n", + "Let’s talk about briefly what this convolution is actually doing from a high level. " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Each of these filters can be thought of as **feature identifiers** (e.g. *straight edges, simple colors, curves*)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "#### Visualisation of the Receptive Field" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "The value is much lower! This is because there wasn’t anything in the image section that responded to the curve detector filter. Remember, the output of this conv layer is an activation map. \n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "### Convolution $\\mapsto$ Convolutional Neural Networks" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Now in a traditional **convolutional neural network** architecture, there are other layers that are interspersed between these conv layers.\n", + "\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "##### ReLU (Rectified Linear Units) Layer" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + " After each conv layer, it is convention to apply a *nonlinear layer* (or **activation layer**) immediately afterward.\n", + "\n", + "\n", + "The purpose of this layer is to introduce nonlinearity to a system that basically has just been computing linear operations during the conv layers (just element wise multiplications and summations)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "In the past, nonlinear functions like tanh and sigmoid were used, but researchers found out that **ReLU layers** work far better because the network is able to train a lot faster (because of the computational efficiency) without making a significant difference to the accuracy." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "It also helps to alleviate the **vanishing gradient problem**, which is the issue where the lower layers of the network train very slowly because the gradient decreases exponentially through the layers" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "(**very briefly**)\n", + "\n", + "Vanishing gradient problem depends on the choice of the activation function. \n", + "\n", + "Many common activation functions (e.g `sigmoid` or `tanh`) *squash* their input into a very small output range in a very non-linear fashion. \n", + "\n", + "For example, sigmoid maps the real number line onto a \"small\" range of [0, 1]." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "As a result, there are large regions of the input space which are mapped to an extremely small range. \n", + "\n", + "In these regions of the input space, even a large change in the input will produce a small change in the output - hence the **gradient is small**." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "###### ReLu\n", + "\n", + "The **ReLu** function is defined as $f(x) = \\max(0, x),$ [2]\n", + "\n", + "A smooth approximation to the rectifier is the *analytic function*: $f(x) = \\ln(1 + e^x)$\n", + "\n", + "which is called the **softplus** function.\n", + "\n", + "The derivative of softplus is $f'(x) = e^x / (e^x + 1) = 1 / (1 + e^{-x})$, i.e. the **logistic function**.\n", + "\n", + "\n", + "[2] \n", + " [http://www.cs.toronto.edu/~fritz/absps/reluICML.pdf]() by G. E. Hinton" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "#### Pooling Layers" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + " After some ReLU layers, it is customary to apply a **pooling layer** (aka *downsampling layer*)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "In this category, there are also several layer options, with **maxpooling** being the most popular. " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Example of a MaxPooling filter" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "Other options for pooling layers are average pooling and L2-norm pooling. " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "The intuition behind this Pooling layer is that once we know that a specific feature is in the original input volume (there will be a high activation value), its exact location is not as important as its relative location to the other features. \n", + "\n", + "Therefore this layer drastically reduces the spatial dimension (the length and the width but not the depth) of the input volume.\n", + "\n", + "This serves two main purposes: reduce the amount of parameters; controlling overfitting. " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "An intuitive explanation for the usefulness of pooling could be explained by an example: \n", + "\n", + "Lets assume that we have a filter that is used for detecting faces. The exact pixel location of the face is less relevant then the fact that there is a face \"somewhere at the top\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "#### Fully Connected Layer" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, + "source": [ + "The last layer, however, is an important one, namely the **Fully Connected Layer**." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "Basically, a FC layer looks at what high level features most strongly correlate to a particular class and has particular weights so that when you compute the products between the weights and the previous layer, you get the correct probabilities for the different classes." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\"Resnet\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "## Hands-on on `Fashion-MNIST`\n", + "\n", + "**Deep Learning Training in `10` steps**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### 1. Import Required Packages" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "import torch\n", + "import torchvision\n", + "import torchvision.transforms as transforms\n", + "\n", + "import torch.nn as nn\n", + "import torch.nn.functional as F\n", + "import torch.optim as optim" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### 2. Get Dataset and Setup Data Pipeline" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Transformers\n", + "\n", + "# transforms\n", + "transform = transforms.Compose(\n", + " [transforms.ToTensor(),\n", + " transforms.Normalize((0.5,), (0.5,))])" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# datasets\n", + "trainset = torchvision.datasets.FashionMNIST('./data',\n", + " download=True,\n", + " train=True,\n", + " transform=transform)\n", + "testset = torchvision.datasets.FashionMNIST('./data',\n", + " download=True,\n", + " train=False,\n", + " transform=transform)\n", + "\n", + "# dataloaders\n", + "trainloader = torch.utils.data.DataLoader(trainset, batch_size=4,\n", + " shuffle=True, num_workers=2)\n", + "\n", + "\n", + "testloader = torch.utils.data.DataLoader(testset, batch_size=4,\n", + " shuffle=False, num_workers=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# constant for classes\n", + "classes = ('T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat',\n", + " 'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle Boot')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# helper function to show an image\n", + "# (used in the `plot_classes_preds` function below)\n", + "def matplotlib_imshow(img, one_channel=False):\n", + " if one_channel:\n", + " img = img.mean(dim=0)\n", + " img = img / 2 + 0.5 # unnormalize\n", + " npimg = img.numpy()\n", + " if one_channel:\n", + " plt.imshow(npimg, cmap=\"Greys\")\n", + " else:\n", + " plt.imshow(np.transpose(npimg, (1, 2, 0)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### 3. Define Model and Loss" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We’ll define a similar model architecture from that tutorial, making only minor modifications to account for the fact that the images are now one channel instead of three and 28x28 instead of 32x32:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "class Net(nn.Module):\n", + " def __init__(self):\n", + " super(Net, self).__init__()\n", + " self.conv1 = nn.Conv2d(1, 6, 5)\n", + " self.pool = nn.MaxPool2d(2, 2)\n", + " self.conv2 = nn.Conv2d(6, 16, 5)\n", + " self.fc1 = nn.Linear(16 * 4 * 4, 120)\n", + " self.fc2 = nn.Linear(120, 84)\n", + " self.fc3 = nn.Linear(84, 10)\n", + "\n", + " def forward(self, x):\n", + " x = self.pool(F.relu(self.conv1(x)))\n", + " x = self.pool(F.relu(self.conv2(x)))\n", + " x = x.view(-1, 16 * 4 * 4)\n", + " x = F.relu(self.fc1(x))\n", + " x = F.relu(self.fc2(x))\n", + " x = self.fc3(x)\n", + " return x\n", + "\n", + "\n", + "net = Net()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We’ll define the same `optimizer` and `criterion` from before:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "criterion = nn.CrossEntropyLoss()\n", + "optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.9)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we’ll set up TensorBoard, importing `tensorboard` from `torch.utils` and defining a `SummaryWriter`, our key object for writing information to TensorBoard." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "from torch.utils.tensorboard import SummaryWriter\n", + "\n", + "# default `log_dir` is \"runs\" - we'll be more specific here\n", + "writer = SummaryWriter('runs/fashion_mnist_experiment_1')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that this line alone creates a `runs/fashion_mnist_experiment_1` folder." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### 4. Writing in TensorBoard" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# get some random training images\n", + "dataiter = iter(trainloader)\n", + "images, labels = dataiter.next()\n", + "\n", + "# create grid of images\n", + "img_grid = torchvision.utils.make_grid(images)\n", + "\n", + "# show images\n", + "matplotlib_imshow(img_grid, one_channel=True)\n", + "\n", + "# write to tensorboard\n", + "writer.add_image('four_fashion_mnist_images', img_grid)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 5. Running `Tensorboard` Server\n", + "\n", + "🛑 **STOP** HERE ✋\n", + "\n", + "Please Run the following command in your terminal:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```bash \n", + "cd cnn-and-adversarial\n", + "tensorboard --logdir=runs\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now you know how to use TensorBoard! \n", + "\n", + "$\\rightarrow$ [http://localhost:6006](http://localhost:6006)\n", + "\n", + "This example, however, could be done in a Jupyter Notebook - where TensorBoard really excels is in creating interactive visualizations. We’ll cover one of those next, and several more by the end of the tutorial.\n", + "\n", + "**NOTE** ⚠️: If possible, use **Google Chrome** for better performance, see [here](https://github.com/pytorch/pytorch/issues/30525)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### 6. Inspect the model using TensorBoard" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "One of TensorBoard’s strengths is its ability to visualize complex model structures. \n", + "\n", + "Let’s visualize the model we built." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "writer.add_graph(net, images)\n", + "writer.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "🛑 **STOP** HERE ✋\n", + "\n", + "Now upon refreshing TensorBoard you should see a **Graphs** tab." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Go ahead and double click on “Net” to see it expand, seeing a detailed view of the individual operations that make up the model.\n", + "\n", + "TensorBoard has a very handy feature for visualizing high dimensional data such as image data in a lower dimensional space; we’ll cover this next." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### 7. Adding a “Projector” to TensorBoard\n", + "\n", + "We can visualize the lower dimensional representation of higher dimensional data via the add_embedding method" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "# helper function\n", + "def select_n_random(data, labels, n=100):\n", + " '''\n", + " Selects n random datapoints and their corresponding labels from a dataset\n", + " '''\n", + " assert len(data) == len(labels)\n", + "\n", + " perm = torch.randperm(len(data))\n", + " return data[perm][:n], labels[perm][:n]\n", + "\n", + "# select random images and their target indices\n", + "images, labels = select_n_random(trainset.data, trainset.targets)\n", + "\n", + "# get the class labels for each image\n", + "class_labels = [classes[lab] for lab in labels]\n", + "\n", + "# log embeddings\n", + "features = images.view(-1, 28 * 28)\n", + "writer.add_embedding(features,\n", + " metadata=class_labels,\n", + " label_img=images.unsqueeze(1))\n", + "writer.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "🛑 **STOP** HERE ✋\n", + "\n", + "Now in the “Projector” tab of TensorBoard, you can see these `100` images - each of which is `784` dimensional - projected down into three dimensional space. \n", + "\n", + "⚠️: If possible, use **Google Chrome** for better performance, see [here](https://github.com/pytorch/pytorch/issues/30525)\n", + "\n", + "Furthermore, this is interactive: you can click and drag to rotate the three dimensional projection. \n", + "\n", + "🧙 \n", + "Finally, a couple of tips to make the visualization easier to see: select `color: label` on the top left, as well as enabling `night mode`, which will make the images easier to see since their background is white." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### 8. Tracking model training with TensorBoard\n", + "\n", + "In the previous example, we simply printed the model’s running loss every `2000` iterations. \n", + "\n", + "Now, we’ll instead log the running loss to TensorBoard, along with a view into the predictions the model is making via the `plot_classes_preds` function." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "# helper functions\n", + "\n", + "def images_to_probs(net, images):\n", + " '''\n", + " Generates predictions and corresponding probabilities from a trained\n", + " network and a list of images\n", + " '''\n", + " output = net(images)\n", + " # convert output probabilities to predicted class\n", + " _, preds_tensor = torch.max(output, 1)\n", + " preds = np.squeeze(preds_tensor.numpy())\n", + " return preds, [F.softmax(el, dim=0)[i].item() for i, el in zip(preds, output)]" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_classes_preds(net, images, labels):\n", + " '''\n", + " Generates matplotlib Figure using a trained network, along with images\n", + " and labels from a batch, that shows the network's top prediction along\n", + " with its probability, alongside the actual label, coloring this\n", + " information based on whether the prediction was correct or not.\n", + " Uses the \"images_to_probs\" function.\n", + " '''\n", + " preds, probs = images_to_probs(net, images)\n", + " # plot the images in the batch, along with predicted and true labels\n", + " fig = plt.figure(figsize=(12, 48))\n", + " for idx in np.arange(4):\n", + " ax = fig.add_subplot(1, 4, idx+1, xticks=[], yticks=[])\n", + " matplotlib_imshow(images[idx], one_channel=True)\n", + " ax.set_title(\"{0}, {1:.1f}%\\n(label: {2})\".format(\n", + " classes[preds[idx]],\n", + " probs[idx] * 100.0,\n", + " classes[labels[idx]]),\n", + " color=(\"green\" if preds[idx]==labels[idx].item() else \"red\"))\n", + " return fig" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, let’s train the model using the same model training code from the prior tutorial, but writing results to TensorBoard every `1000` batches instead of printing to console; this is done using the `add_scalar` function.\n", + "\n", + "In addition, as we train, we’ll generate an image showing the model’s predictions vs. the actual results on the four images included in that batch." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### 9. Model Training (loop)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Finished Training\n" + ] + } + ], + "source": [ + "running_loss = 0.0\n", + "for epoch in range(1): # loop over the dataset multiple times\n", + "\n", + " for i, data in enumerate(trainloader, 0):\n", + "\n", + " # get the inputs; data is a list of [inputs, labels]\n", + " inputs, labels = data\n", + "\n", + " # zero the parameter gradients\n", + " optimizer.zero_grad()\n", + "\n", + " # forward + backward + optimize\n", + " outputs = net(inputs)\n", + " loss = criterion(outputs, labels)\n", + " loss.backward()\n", + " optimizer.step()\n", + "\n", + " running_loss += loss.item()\n", + " if i % 1000 == 999: # every 1000 mini-batches...\n", + "\n", + " # ...log the running loss\n", + " writer.add_scalar('training loss',\n", + " running_loss / 1000,\n", + " epoch * len(trainloader) + i)\n", + "\n", + " # ...log a Matplotlib Figure showing the model's predictions on a\n", + " # random mini-batch\n", + " writer.add_figure('predictions vs. actuals',\n", + " plot_classes_preds(net, inputs, labels),\n", + " global_step=epoch * len(trainloader) + i)\n", + " running_loss = 0.0\n", + "print('Finished Training')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "###### 9.1 Training on a GPU" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "Just like how you transfer a Tensor onto the GPU, you transfer the neural\n", + "net onto the GPU.\n", + "\n", + "Let's first define our device as the first visible cuda device if we have\n", + "CUDA available:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "jupyter": { + "outputs_hidden": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cpu\n" + ] + } + ], + "source": [ + "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n", + "\n", + "# Assuming that we are on a CUDA machine, this should print a CUDA device:\n", + "\n", + "print(device)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The rest of this section assumes that ``device`` is a CUDA device.\n", + "\n", + "Then these methods will recursively go over all modules and convert their\n", + "parameters and buffers to CUDA tensors:\n", + "\n", + "```python\n", + " net.to(device)\n", + "```\n", + "\n", + "Remember that you will have to send the inputs and targets at every step\n", + "to the GPU too:\n", + "\n", + "```python\n", + " inputs, labels = data[0].to(device), data[1].to(device)\n", + "```\n", + "\n", + "Why don't I notice MASSIVE speedup compared to CPU? \n", + "\n", + "Because your network is really small." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "🛑 **STOP** HERE ✋\n", + "\n", + "You can now look at the scalars tab to see the running loss plotted over the `15,000` iterations of training" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### 10. Model Assessment and Precision/Recall Curve" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "# 1. gets the probability predictions in a test_size x num_classes Tensor\n", + "# 2. gets the preds in a test_size Tensor\n", + "# takes ~10 seconds to run\n", + "class_probs = []\n", + "class_preds = []\n", + "with torch.no_grad():\n", + " for data in testloader:\n", + " images, labels = data\n", + " output = net(images)\n", + " class_probs_batch = [F.softmax(el, dim=0) for el in output]\n", + " _, class_preds_batch = torch.max(output, 1)\n", + "\n", + " class_probs.append(class_probs_batch)\n", + " class_preds.append(class_preds_batch)\n", + "\n", + "test_probs = torch.cat([torch.stack(batch) for batch in class_probs])\n", + "test_preds = torch.cat(class_preds)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "# helper function\n", + "def add_pr_curve_tensorboard(class_index, test_probs, test_preds, global_step=0):\n", + " '''\n", + " Takes in a \"class_index\" from 0 to 9 and plots the corresponding\n", + " precision-recall curve\n", + " '''\n", + " tensorboard_preds = test_preds == class_index\n", + " tensorboard_probs = test_probs[:, class_index]\n", + "\n", + " writer.add_pr_curve(classes[class_index],\n", + " tensorboard_preds,\n", + " tensorboard_probs,\n", + " global_step=global_step)\n", + " writer.close()\n", + "\n", + "# plot all the pr curves\n", + "for i in range(len(classes)):\n", + " add_pr_curve_tensorboard(i, test_probs, test_preds)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You will now see a “PR Curves” tab that contains the precision-recall curves for each class.\n", + "\n", + "Go ahead and poke around; you’ll see that on some classes the model has nearly 100% “area under the curve”, whereas on others this area is lower" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.8.11" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/2-cnn-and-adversarials/2 Adversarial Attacks.ipynb b/2-cnn-and-adversarials/2 Adversarial Attacks.ipynb new file mode 100644 index 0000000..32e8020 --- /dev/null +++ b/2-cnn-and-adversarials/2 Adversarial Attacks.ipynb @@ -0,0 +1,21772 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "
\n", + " The notebook is using\n", + " \n", + " no$\\TeX$book Jupyter Theme (release 2.0.1).\n", + "\n", + "
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%load_ext notexbook \n", + "%texify" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "73COBSgLtrGF" + }, + "source": [ + "# Adversarial attacks\n", + "\n", + "**Original Version**: [Tutorial 10-UvA DL Notebooks](https://uvadlc-notebooks.readthedocs.io/en/latest/tutorial_notebooks/tutorial10/Adversarial_Attacks.html)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1-o99kX-trGG" + }, + "source": [ + "[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/WebValley2021ReImagined/privacy-preserving-data-science/blob/main/cnn-and-adversarials/2%20Adversarial%20Attacks.ipynb)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "EtL4bl-LHNFS", + "tags": [] + }, + "source": [ + "Threat Model\n", + "------------\n", + "\n", + "For context, there are many categories of adversarial attacks, each with\n", + "a different goal and assumption of the attacker’s knowledge. \n", + "\n", + "However, in\n", + "general the overarching goal is to add the least amount of perturbation\n", + "to the input data to cause the desired misclassification. \n", + "\n", + "There are several kinds of assumptions of the attacker’s knowledge, two of which\n", + "are: **white-box** and **black-box**. \n", + "\n", + "* A *white-box* attack assumes the\n", + "attacker has full knowledge and access to the model, including\n", + "architecture, inputs, outputs, and weights. \n", + "\n", + "* A *black-box* attack assumes\n", + "the attacker only has access to the inputs and outputs of the model, and\n", + "knows nothing about the underlying architecture or weights. \n", + "\n", + "There are\n", + "also several types of goals, including **misclassification** and\n", + "**source/target misclassification**. \n", + "\n", + "1. A goal of *misclassification* means\n", + "the adversary only wants the output classification to be wrong but does\n", + "not care what the new classification is. \n", + "\n", + "2. A *source/target\n", + "misclassification* means the adversary wants to alter an image that is\n", + "originally of a specific source class so that it is classified as a\n", + "specific target class.\n", + "\n", + "In this case, the **FAST GRADIENT SIGN ATTACK** (`FGSM`) attack is a *white-box* attack with the goal of\n", + "*misclassification*. With this background information, we can now\n", + "discuss the attack in detail.\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XzyhqzBgtrGH" + }, + "source": [ + "**Example**\n", + "\n", + "For instance, take a look at the example below (figure credit - [Goodfellow et al.](https://arxiv.org/pdf/1412.6572.pdf)):\n", + "\n", + "
\n", + "\n", + "The image on the left is the original image from ImageNet, and a deep CNN classifies the image correctly as \"panda\" with a class likelihood of 57%. \n", + "\n", + "Nevertheless, if we add a little noise to every pixel of the image, the prediction of the model changes completely. Instead of a panda, our CNN tells us that the image contains a \"gibbon\" with the confidence of over 99%. \n", + "\n", + "For a human, however, these two images look exactly alike, and you cannot distinguish which one has noise added and which doesn't.\n", + "\n", + "While this first seems like a fun game to fool trained networks, it can have a serious impact on the usage of neural networks. More and more deep learning models are used in applications, such as for example autonomous driving. \n", + "\n", + "Some attack types don't even require to add noise, but minor changes on a stop sign can be already sufficient for the network to recognize it as a \"50km/h\" speed sign ([paper](https://arxiv.org/pdf/1707.08945.pdf), [paper](https://arxiv.org/pdf/1802.06430.pdf)). The consequences of such attacks can be devastating. Hence, every deep learning engineer who designs models for an application should be aware of the possibility of adversarial attacks." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "_Hf12FVZ1Mup" + }, + "outputs": [], + "source": [ + "## Standard libraries\n", + "import os\n", + "import json\n", + "import math\n", + "import time\n", + "import numpy as np \n", + "import scipy.linalg" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "GLvH-UyU1Muq" + }, + "outputs": [], + "source": [ + "## Imports for plotting\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline \n", + "from matplotlib_inline.backend_inline import set_matplotlib_formats\n", + "set_matplotlib_formats('svg', 'pdf') # For export\n", + "from matplotlib.colors import to_rgb\n", + "import matplotlib\n", + "matplotlib.rcParams['lines.linewidth'] = 2.0\n", + "import seaborn as sns\n", + "sns.set()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "id": "TujCwxVO1Muq" + }, + "outputs": [], + "source": [ + "## Progress bar\n", + "from tqdm.notebook import tqdm" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "id": "u2MjW9VP1Mur" + }, + "outputs": [], + "source": [ + "## PyTorch\n", + "import torch\n", + "import torch.nn as nn\n", + "import torch.nn.functional as F\n", + "import torch.utils.data as data\n", + "import torch.optim as optim\n", + "# Torchvision\n", + "import torchvision\n", + "from torchvision.datasets import CIFAR10\n", + "from torchvision import transforms" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "eiMxm5nQtrGH", + "outputId": "5e4a708c-edfc-4f71-aec0-5472d4b2d958" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Global seed set to 42\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using device cuda:0\n" + ] + } + ], + "source": [ + "# PyTorch Lightning\n", + "try:\n", + " import pytorch_lightning as pl\n", + "except ModuleNotFoundError: # Google Colab does not have PyTorch Lightning installed by default. Hence, we do it here if necessary\n", + " !pip install pytorch-lightning==1.3.4\n", + " import pytorch_lightning as pl\n", + "from pytorch_lightning.callbacks import LearningRateMonitor, ModelCheckpoint\n", + "\n", + "# Path to the folder where the datasets are/should be downloaded (e.g. MNIST)\n", + "DATASET_PATH = \"./data\"\n", + "# Path to the folder where the pretrained models are saved\n", + "CHECKPOINT_PATH = \"./checkpoints\"\n", + "\n", + "# Setting the seed\n", + "pl.seed_everything(42)\n", + "\n", + "# Ensure that all operations are deterministic on GPU (if used) for reproducibility\n", + "torch.backends.cudnn.determinstic = True\n", + "torch.backends.cudnn.benchmark = False\n", + "\n", + "# Fetching the device that will be used throughout this notebook\n", + "device = torch.device(\"cpu\") if not torch.cuda.is_available() else torch.device(\"cuda:0\")\n", + "print(\"Using device\", device)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vFgbK_JVtrGI" + }, + "source": [ + "We have again a few download statements. This includes both a dataset, and a few pretrained patches we will use later." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "UBF9Yts1trGJ", + "outputId": "f2bea346-20a4-4b28-d9a3-8835bc90fc08" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading https://raw.githubusercontent.com/phlippe/saved_models/main/tutorial10/TinyImageNet.zip...\n", + "Unzipping file...\n", + "Downloading https://raw.githubusercontent.com/phlippe/saved_models/main/tutorial10/patches.zip...\n", + "Unzipping file...\n" + ] + } + ], + "source": [ + "import urllib.request\n", + "from urllib.error import HTTPError\n", + "import zipfile\n", + "\n", + "# Github URL where the dataset is stored for this tutorial\n", + "base_url = \"https://raw.githubusercontent.com/phlippe/saved_models/main/tutorial10/\"\n", + "\n", + "# Files to download\n", + "pretrained_files = [(DATASET_PATH, \"TinyImageNet.zip\"), (CHECKPOINT_PATH, \"patches.zip\")]\n", + "\n", + "# Create checkpoint path if it doesn't exist yet\n", + "os.makedirs(DATASET_PATH, exist_ok=True)\n", + "os.makedirs(CHECKPOINT_PATH, exist_ok=True)\n", + "\n", + "# For each file, check whether it already exists. If not, try downloading it.\n", + "for dir_name, file_name in pretrained_files:\n", + " file_path = os.path.join(dir_name, file_name)\n", + " if not os.path.isfile(file_path):\n", + " file_url = base_url + file_name\n", + " print(\"Downloading %s...\" % file_url)\n", + " try:\n", + " urllib.request.urlretrieve(file_url, file_path)\n", + " except HTTPError as e:\n", + " print(\"Something went wrong. Please try to download the file from the GDrive folder, or contact the author with the full output including the following error:\\n\", e)\n", + " \n", + " if file_name.endswith(\".zip\"):\n", + " print(\"Unzipping file...\")\n", + " with zipfile.ZipFile(file_path, 'r') as zip_ref:\n", + " zip_ref.extractall(file_path.rsplit(\"/\",1)[0])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "C6ooTINytrGJ" + }, + "source": [ + "## Deep CNNs on ImageNet\n", + "\n", + "For our experiments in this notebook, we will use common CNN architectures trained on the ImageNet dataset, in particular we will be using the `ResNet34` model, (luckily) provided by the `torchvision` package, already **pre-trained** and ready for use. " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 66, + "referenced_widgets": [ + "d76957fdf7cf43a5b8b7f2cfc2b5a8e5", + "8064a2498e214a2185ba203a0b3bd653", + "1aa20359cc6e43169d7aa57c3796d983", + "505f74c946324d6e89d5a471c6350791", + "9f364948303f40288a1c17be5302bff6", + "b29d0b3ab3a2422185f396854412fc03", + "29046cf541ed48d1b18d833e96d17a47", + "bb8a434458f0498ba066506d892a8182", + "a72fda9fe7f54401a2d557bdaa4eefae", + "83d376256e744b14b99cd03ca60c1f4f", + "e2fa97666400468499b2a57d8712f625" + ] + }, + "id": "b6mYhhGRtrGJ", + "outputId": "197171ae-b0cf-4494-a27a-226b77ab6937" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading: \"https://download.pytorch.org/models/resnet34-b627a593.pth\" to ./checkpoints/hub/checkpoints/resnet34-b627a593.pth\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d76957fdf7cf43a5b8b7f2cfc2b5a8e5", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0.00/83.3M [00:00 1e-4:\n", + " pred = torch.softmax(pred, dim=-1)\n", + " topk_vals, topk_idx = pred.topk(K, dim=-1)\n", + " topk_vals, topk_idx = topk_vals.cpu().numpy(), topk_idx.cpu().numpy()\n", + " \n", + " ax[-1].barh(np.arange(K), topk_vals*100.0, align='center', color=[\"C0\" if topk_idx[i]!=label else \"C2\" for i in range(K)])\n", + " ax[-1].set_yticks(np.arange(K))\n", + " ax[-1].set_yticklabels([label_names[c] for c in topk_idx])\n", + " \n", + " ax[-1].invert_yaxis()\n", + " ax[-1].set_xlabel('Confidence')\n", + " ax[-1].set_title('Predictions')\n", + " \n", + " plt.show()\n", + " plt.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ilxJaoMOtrGM" + }, + "source": [ + "Let's visualize a few images below:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 961 + }, + "id": "WjAYifs4trGM", + "outputId": "b51a9163-d362-4983-9106-2e492aafd0ea" + }, + "outputs": [ + { + "data": { + "application/pdf": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "exmp_batch, label_batch = next(iter(data_loader))\n", + "with torch.no_grad():\n", + " preds = pretrained_model(exmp_batch.to(device))\n", + "for i in range(1,17,5):\n", + " show_prediction(exmp_batch[i], label_batch[i], preds[i])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "fx1eYZPetrGN" + }, + "source": [ + "The bar plot on the right shows the top-5 predictions of the model with their class probabilities. \n", + "\n", + "We denote the class probabilities with **confidence** as it somewhat resembles how confident the network is that the image is of one specific class. \n", + "\n", + "Some of the images have a highly peaked probability distribution, and we would expect the model to be rather robust against noise for those. However, we will see below that this is not always the case. " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "qVcl6B3QtrGN" + }, + "source": [ + "### Fast Gradient Sign Method (FGSM)\n", + "\n", + "One of the first attack strategies proposed is Fast Gradient Sign Method (FGSM), developed by [Ian Goodfellow et al.](https://arxiv.org/pdf/1412.6572.pdf) in 2014.\n", + "\n", + "**The idea is simple**:\n", + "\n", + ">rather than working to minimize the loss by adjusting the weights based on the\n", + "backpropagated gradients, the attack **adjusts the input data to maximize\n", + "the loss** based on the same backpropagated gradients. \n", + "\n", + "Given an image, we create an adversarial example by the following expression:\n", + "\n", + "$$\\tilde{x} = x + \\epsilon \\cdot \\text{sign}(\\nabla_x J(\\theta,x,y))$$\n", + "\n", + "- The term $J(\\theta,x,y)$ represents the loss of the network for classifying input image $x$ as label $y$; \n", + "- $\\epsilon$ is the intensity of the noise; \n", + "- $\\tilde{x}$ the final adversarial example. \n", + "\n", + "The equation resembles `SGD` and is actually nothing else than that. \n", + "\n", + "We change the input image $x$ in the direction of *maximizing* the loss $J(\\theta,x,y)$. \n", + "\n", + "This is exactly the **other way round** as during training, where we try to minimize the loss. \n", + "\n", + "The sign function and $\\epsilon$ can be seen as gradient clipping and learning rate specifically. \n", + "\n", + "We only allow our attack to change each pixel value by $\\epsilon$. You can also see that the attack can be performed very fast, as it only requires a single forward and backward pass. \n", + "\n", + "Let's implement it below:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "id": "K1Pq16vdtrGN" + }, + "outputs": [], + "source": [ + "def fast_gradient_sign_method(model, imgs, labels, epsilon=0.02):\n", + " \"\"\"Fasdt Gradient Sign Attack\"\"\"\n", + " \n", + " # Determine prediction of the model\n", + " inp_imgs = imgs.clone().requires_grad_()\n", + " preds = model(inp_imgs.to(device))\n", + " preds = F.log_softmax(preds, dim=-1)\n", + " # Calculate loss by NLL\n", + " loss = -torch.gather(preds, 1, labels.to(device).unsqueeze(dim=-1))\n", + " loss.sum().backward()\n", + " # Update image to adversarial example as written above\n", + " noise_grad = torch.sign(inp_imgs.grad.to(imgs.device))\n", + " fake_imgs = imgs + epsilon * noise_grad\n", + " fake_imgs.detach_()\n", + " return fake_imgs, noise_grad" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pLsaCGgdtrGO" + }, + "source": [ + "The default value of $\\epsilon=0.02$ corresponds to changing a pixel value by about `1` in the range of `0` to `255`, e.g. changing `127` to `128`. \n", + "\n", + "This difference is marginal and can often not be recognized by humans. Let's try it below on our example images:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 961 + }, + "id": "lyUzO6ZvtrGO", + "outputId": "9c9f3e37-76b2-4479-e63a-08ede1ffe7fe" + }, + "outputs": [ + { + "data": { + "application/pdf": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "adv_imgs, noise_grad = fast_gradient_sign_method(pretrained_model, exmp_batch, label_batch, epsilon=0.02)\n", + "with torch.no_grad():\n", + " adv_preds = pretrained_model(adv_imgs.to(device))\n", + " \n", + "for i in range(1,17,5):\n", + " show_prediction(exmp_batch[i], label_batch[i], adv_preds[i], adv_img=adv_imgs[i], noise=noise_grad[i])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "VR2lAceatrGO" + }, + "source": [ + "Despite the minor amount of noise, we are able to fool the network on all of our examples. \n", + "\n", + "**NOTE:** None of the labels have made it into the `top-5` for the four images, showing that we indeed fooled the model. \n", + "\n", + "We can also check the accuracy of the model on the adversarial images:" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 83, + 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def show_patches():\n", + " fig, ax = plt.subplots(len(patch_sizes), len(class_names), figsize=(len(class_names)*2.2, len(patch_sizes)*2.2))\n", + " for c_idx, cname in enumerate(class_names):\n", + " for p_idx, psize in enumerate(patch_sizes):\n", + " patch = patch_dict[cname][psize][\"patch\"]\n", + " patch = (torch.tanh(patch) + 1) / 2 # Parameter to pixel values\n", + " patch = patch.cpu().permute(1, 2, 0).numpy()\n", + " patch = np.clip(patch, a_min=0.0, a_max=1.0)\n", + " ax[p_idx][c_idx].imshow(patch)\n", + " ax[p_idx][c_idx].set_title(\"%s, size %i\" % (cname, psize))\n", + " ax[p_idx][c_idx].axis('off')\n", + " fig.subplots_adjust(hspace=0.3, wspace=0.3)\n", + " plt.show()\n", + "show_patches()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ncHFva-etrGT" + }, + "source": [ + "We can see a clear difference between patches of different classes and sizes. \n", + "\n", + "In the smallest size, $32\\times 32$ pixels, some of the patches clearly resemble their class. \n", + "\n", + "For instance, the goldfish patch clearly shows a goldfish. The eye and the color are very characteristic of the class. Overall, the patches with $32$ pixels have very strong colors that are typical for their class (`yellow school bus`, `pink lipstick`, `greenish pineapple`).\n", + "\n", + "Let's now look at the quantitative results." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "id": "zTOoR0qWtrGU" + }, + "outputs": [], + "source": [ + "import tabulate\n", + "from IPython.display import display, HTML\n", + "\n", + "def show_table(top_1=True):\n", + " i = 0 if top_1 else 1\n", + " table = [[name] + [\"%4.2f%%\" % (100.0 * patch_dict[name][psize][\"results\"][i]) for psize in patch_sizes]\n", + " for name in class_names]\n", + " display(HTML(tabulate.tabulate(table, tablefmt='html', headers=[\"Class name\"] + [\"Patch size %ix%i\" % (psize, psize) for psize in patch_sizes])))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3UQVovAQtrGU" + }, + "source": [ + "First, we will create a table of top-1 accuracy, meaning that how many images have been classified with the target class as highest prediction?" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 145 + }, + "id": "Df8bwCKPtrGU", + "outputId": "e8ca8282-4136-4a76-adad-73e0834676bc" + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
Class name Patch size 32x32 Patch size 48x48 Patch size 64x64
toaster 48.89% 90.48% 98.58%
goldfish 69.53% 93.53% 98.34%
school bus 78.79% 93.95% 98.22%
lipstick 43.36% 86.05% 96.41%
pineapple 79.74% 94.48% 98.72%
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "show_table(top_1=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kA0KHzEwtrGV" + }, + "source": [ + "The clear trend, that we would also have expected, is that **the larger the patch, the easier it is to fool the model.** \n", + "\n", + "For the largest patch size of $64\\times 64$, we are able to fool the model on almost all images, despite the patch covering only `8%` of the image. \n", + "\n", + "The smallest patch actually covers `2%` of the image, which is almost neglectable. Still, the fooling accuracy is quite remarkable. \n", + "\n", + "Let's also take a look at the top-5 accuracy:" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 145 + }, + "id": "Q33pdIaStrGV", + "outputId": "5866a208-5b21-40a4-8b27-71eed211eda8" + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
Class name Patch size 32x32 Patch size 48x48 Patch size 64x64
toaster 72.02% 98.12% 99.93%
goldfish 86.31% 99.07% 99.95%
school bus 91.64% 99.15% 99.89%
lipstick 70.10% 96.86% 99.73%
pineapple 92.23% 99.26% 99.96%
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "show_table(top_1=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Fzz2Jhv0trGV" + }, + "source": [ + "We see a very similar pattern across classes and patch sizes. \n", + "\n", + "The patch size $64$ obtains >99.7% top-5 accuracy for any class, showing that we can almost fool the network on any image. \n", + "\n", + "A top-5 accuracy of >70% for the hard classes and small patches is still impressive and shows how vulnerable deep CNNs are to such attacks.\n", + "\n", + "Finally, let's create some example visualizations of the **patch attack** in action." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "⚠️ Highly recommended to run on **GPU**" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "id": "Q6P0QrP4trGV" + }, + "outputs": [], + "source": [ + "def perform_patch_attack(patch):\n", + " patch_batch = exmp_batch.clone()\n", + " patch_batch = place_patch(patch_batch, patch)\n", + " with torch.no_grad():\n", + " patch_preds = pretrained_model(patch_batch.to(device))\n", + " for i in range(1,17,5):\n", + " show_prediction(patch_batch[i], label_batch[i], patch_preds[i])" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 961 + }, + "id": "fTGLPePItrGW", + "outputId": "2669c6b5-65a4-43b1-9d10-056550178431" + }, + "outputs": [ + { + "data": { + "application/pdf": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "perform_patch_attack(patch_dict['goldfish'][32]['patch'])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SfKDxbGktrGW" + }, + "source": [ + "The tiny goldfish patch can change all of the predictions to \"goldfish\" as top class. Note that the patch attacks work especially well if the input image is semantically similar to the target class (e.g. a fish and the target class \"goldfish\" works better than an airplane image with that patch). Nevertheless, we can also let the network predict semantically dis-similar classes by using a larger patch:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "⚠️ Highly recommended to run on **GPU**" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 961 + }, + "id": "ng5RAZOutrGW", + "outputId": "893db26b-e320-4f6e-f7c0-6077bdefb22e" + }, + "outputs": [ + { + "data": { + "application/pdf": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "perform_patch_attack(patch_dict['school bus'][64]['patch'])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "NGYWtIYXtrGX" + }, + "source": [ + "## Protecting against adversarial attacks\n", + "\n", + "There are many more attack strategies than just **FGSM** and **adversarial patches** that we haven't discussed and implemented ourselves here. \n", + "\n", + "However, what about the other perspective? What can we do to *protect* a network against adversarial attacks? The sad truth to this is: _not much_.\n", + "\n", + "White-box attacks require access to the model and its gradient calculation. The easiest way of preventing this is by ensuring safe, private storage of the model and its weights. \n", + "\n", + "However, **black-box attacks**, also work without access to the model's parameters, or white-box attacks can also generalize. \n", + "\n", + "**So, how could we eventually protect a model?** \n", + "\n", + "An intuitive approach would to _train/finetune_ a model on such adversarial images, leading to an adversarial training similar to a GAN. \n", + "During training, we would pretend to be the attacker, and use for example FGSM as an augmentation strategy. \n", + "\n", + "However, this usually just ends up in an oscillation of the defending network between weak spots. Another common trick to increase robustness against adversarial attacks is **defensive distillation** ([Papernot et al.](https://arxiv.org/pdf/1511.04508.pdf)). \n", + "\n", + "Instead of training the model on the dataset labels, we train a secondary model on the `softmax predictions` of the first one. \n", + "This way, the loss surface is \"smoothed\" in the directions an attacker might try to exploit, and it becomes more difficult for the attacker to find adversarial examples. \n", + "Nevertheless, there hasn't been found the one, true strategy that works against all possible adversarial attacks.\n", + "\n", + "**Why CNN?**\n", + "\n", + "Why are CNNs, or neural networks in general, so vulnerable to adversarial attacks? While there are many possible explanations, the most intuitive is that neural networks don't know what they don't know. \n", + "\n", + "Another possible explanation lies in the activation function. As we know, most CNNs use ReLU-based activation functions: while those have enabled great success in training deep neural networks due to their stable gradient for positive values, they also constitute a possible flaw. \n", + "\n", + "The output range of a `ReLU` neuron can be arbitrarily high. Thus, if we design a patch or the noise in the image to cause a very high value for a single neuron, it can overpower many other features in the network. Thus, although `ReLU` stabilizes training, it also offers a potential point of attack for adversaries." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SkVXr8YwtrGY" + }, + "source": [ + "## References\n", + "\n", + "[1] Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy. \"Explaining and harnessing adversarial examples.\" ICLR 2015.\n", + "\n", + "[2] Hendrik Metzen, Jan, et al. \"Universal adversarial perturbations against semantic image segmentation.\" Proceedings of the IEEE International Conference on Computer Vision. 2017.\n", + "\n", + "[3] Anant Jain. \"Breaking neural networks with adversarial attacks.\" [Blog post](https://towardsdatascience.com/breaking-neural-networks-with-adversarial-attacks-f4290a9a45aa) 2019." + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "collapsed_sections": [], + "name": "Copy of Adversarial_Attacks.ipynb", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": 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