{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| include: false\n",
"! [ -e /content ] && pip install -Uqq fastbook\n",
"import fastbook\n",
"fastbook.setup_book()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"hide_input": false
},
"outputs": [],
"source": [
"#| include: false\n",
"from fastbook import *"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# CNN Interpretation with CAM {#sec-cam}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we know how to build up pretty much anything from scratch, let's use that knowledge to create entirely new (and very useful!) functionality: the *class activation map*. It gives us some insight into why a CNN made the predictions it did.\n",
"\n",
"In the process, we'll learn about one handy feature of PyTorch we haven't seen before, the *hook*, and we'll apply many of the concepts introduced in the rest of the book. If you want to really test out your understanding of the material in this book, after you've finished this chapter, try putting it aside and recreating the ideas here yourself from scratch (no peeking!)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## CAM and Hooks"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The class activation map (CAM) was introduced by Bolei Zhou et al. in [\"Learning Deep Features for Discriminative Localization\"](https://arxiv.org/abs/1512.04150). It uses the output of the last convolutional layer (just before the average pooling layer) together with the predictions to give us a heatmap visualization of why the model made its decision. This is a useful tool for interpretation.\n",
"\n",
"More precisely, at each position of our final convolutional layer, we have as many filters as in the last linear layer. We can therefore compute the dot product of those activations with the final weights to get, for each location on our feature map, the score of the feature that was used to make a decision.\n",
"\n",
"We're going to need a way to get access to the activations inside the model while it's training. In PyTorch this can be done with a *hook*. Hooks are PyTorch's equivalent of fastai's callbacks. However, rather than allowing you to inject code into the training loop like a fastai `Learner` callback, hooks allow you to inject code into the forward and backward calculations themselves. We can attach a hook to any layer of the model, and it will be executed when we compute the outputs (forward hook) or during backpropagation (backward hook). A forward hook is a function that takes three things—a module, its input, and its output—and it can perform any behavior you want. (fastai also provides a handy `HookCallback` that we won't cover here, but take a look at the fastai docs; it makes working with hooks a little easier.)\n",
"\n",
"To illustrate, we'll use the same cats and dogs model we trained in @sec-intro:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"path = untar_data(URLs.PETS)/'images'\n",
"def is_cat(x): return x[0].isupper()\n",
"dls = ImageDataLoaders.from_name_func(\n",
" path, get_image_files(path), valid_pct=0.2, seed=21,\n",
" label_func=is_cat, item_tfms=Resize(224))\n",
"learn = vision_learner(dls, resnet34, metrics=error_rate)\n",
"learn.fine_tune(1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To start, we'll grab a cat picture and a batch of data:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"img = PILImage.create(image_cat())\n",
"x, = first(dls.test_dl([img]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For CAM we want to store the activations of the last convolutional layer. We put our hook function in a class so it has a state that we can access later, and just store a copy of the output:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"class Hook():\n",
" def hook_func(self, m, i, o): self.stored = o.detach().clone()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can then instantiate a `Hook` and attach it to the layer we want, which is the last layer of the CNN body:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"hook_output = Hook()\n",
"hook = learn.model[0].register_forward_hook(hook_output.hook_func)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we can grab a batch and feed it through our model:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"with torch.no_grad(): output = learn.model.eval()(x)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And we can access our stored activations:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"act = hook_output.stored[0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's also double-check our predictions:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tensor([[0.0010, 0.9990]], device='cuda:0')"
]
},
"execution_count": null,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"F.softmax(output, dim=-1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We know `0` (for `False`) is \"dog,\" because the classes are automatically sorted in fastai, bu we can still double-check by looking at `dls.vocab`: "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(#2) [False,True]"
]
},
"execution_count": null,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dls.vocab"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So, our model is very confident this was a picture of a cat."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To do the dot product of our weight matrix (2 by number of activations) with the activations (batch size by activations by rows by cols), we use a custom `einsum`:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([1, 3, 224, 224])"
]
},
"execution_count": null,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([2, 7, 7])"
]
},
"execution_count": null,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cam_map = torch.einsum('ck,kij->cij', learn.model[1][-1].weight, act)\n",
"cam_map.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For each image in our batch, and for each class, we get a 7×7 feature map that tells us where the activations were higher and where they were lower. This will let us see which areas of the pictures influenced the model's decision.\n",
"\n",
"For instance, we can find out which areas made the model decide this animal was a cat (note that we need to `decode` the input `x` since it's been normalized by the `DataLoader`, and we need to cast to `TensorImage` since at the time this book is written PyTorch does not maintain types when indexing—this may be fixed by the time you are reading this):"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
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\n",
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