\n",
+ " Extra info on nn.Linear:
\n",
+ " nn.Linear(33232, 512):
\n",
+ "Input Features (33232) - This is the number of input features to the first layer of the neural network. The CIFAR-10 images are colored (RGB) and each image is 32x32 pixels. Therefore, each image consists of 3 color channels × 32 pixels (height) × 32 pixels (width) = 3,072 features. When you input an image to the network, it is typically flattened from a 3D tensor of shape (3, 32, 32) to a 1D tensor of shape (33232), which is a common practice for fully connected layers.
\n",
+ "Output Features (512) - This number defines how many neurons there are in the first hidden layer of the network. The choice of 512 neurons is somewhat arbitrary but is influenced by factors like the complexity of the task and the amount of available data. More neurons can potentially capture more complex patterns but also increase computational load and the risk of overfitting, especially with smaller datasets. The number 512 is a power of 2, which is often chosen due to how memory is allocated in many computing systems, potentially improving performance.
\n",
+ "nn.Linear(512, 256):
\n",
+ "Input Features (512) - This layer takes the output from the previous layer (512 features) as its input.
\n",
+ "Output Features (256) - This continues the pattern of creating a \"funnel\" where each subsequent layer has fewer neurons than the previous one. This design can help to condense the information from the high-dimensional input into increasingly abstract and useful representations. Halving the number of neurons in each layer (a common heuristic) helps in gradually reducing the dimensionality of the problem, which can aid in learning more generalized features.
\n",
+ "nn.Linear(256, 128):
\n",
+ "Input Features (256) - Inputs from the second layer are fed into the third.
\n",
+ "Output Features (128) - Further reduces the complexity and continues the pattern of halving. This reduction helps in focusing the network on the most important features to make decisions.
\n",
+ "nn.Linear(128, 10):
\n",
+ "Input Features (128) - Takes outputs from the previous layer.
\n",
+ "Output Features (10) - This is determined by the number of classes in the CIFAR-10 dataset. Each of the 10 output units corresponds to one of the classes (like cats, dogs, birds, etc.), which the network will learn to predict.
\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "- The ```forward()``` function is an important part of defining neural networks in PyTorch. It specifies how the input data is transformed as it passes through the network, essentially defining the computation that occurs within the network. This is where you apply layers, activation functions, and other computational steps to the input tensors.\n",
+ "\n",
+ "- ```F.relu()``` is the Rectified Linear Activation Function [(ReLU)](https://www.geeksforgeeks.org/activation-functions-in-pytorch/) applied element-wise. It introduces non-linearity into the model, allowing it to learn more complex patterns. ReLU is defined as ```f(x) = max(0, x)``` , which sets all negative values in the input tensor to zero.\n",
+ "\n",
+ "- ```F.log_softmax()``` is applied to the output of the final layer. This function computes the logarithm of the softmax of the input tensor. Softmax converts the logits (raw predictions) into probabilities by taking the exponentials of each output and then normalizing these values by dividing by the sum of all exponentials; this ensures that the output values are between 0 and 1 and sum to 1.\n",
+ "\n",
+ "The ```forward()``` function is automatically invoked when you call the model on an input batch of data, e.g., ```output = model(data)```. The backward pass, used to compute gradients during training, is automatically defined by PyTorch using autograd based on the operations specified in the forward() function. This makes implementing complex neural networks more straightforward, as the user only needs to define the forward computation."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Data Loading and Preprocessing:\n",
+ "\n",
+ "One of the main tasks when building your machine learning model is preparing your training and testing data.\n",
+ "\n",
+ "In this example we are using the [CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html) dataset. This dataset contains images of animals but it also contains images of vehicles like cars/trains/planes/etc. We need to filter this dataset so that it only contains the classes we want, like birds, cats, dogs, and other animals."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 66,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Custom dataset to filter only animal classes\n",
+ "class AnimalCIFAR10(Dataset):\n",
+ " def __init__(self, root, train=True, transform=None, download=False):\n",
+ " self.cifar10 = datasets.CIFAR10(root=root, train=train, transform=transform, download=download)\n",
+ " self.animal_classes = [2, 3, 4, 5, 6, 7] # Indices of animal classes in CIFAR-10\n",
+ " self.animal_class_map = {2: 0, 3: 1, 4: 2, 5: 3, 6: 4, 7: 5} # Map original class to new class index\n",
+ " self.data = []\n",
+ " self.targets = []\n",
+ "\n",
+ " for i in range(len(self.cifar10)):\n",
+ " if self.cifar10.targets[i] in self.animal_classes:\n",
+ " self.data.append(self.cifar10.data[i])\n",
+ " self.targets.append(self.animal_class_map[self.cifar10.targets[i]])\n",
+ "\n",
+ " def __len__(self):\n",
+ " return len(self.data)\n",
+ "\n",
+ " def __getitem__(self, idx):\n",
+ " img, target = self.data[idx], self.targets[idx]\n",
+ " if self.cifar10.transform is not None:\n",
+ " img = self.cifar10.transform(img)\n",
+ " return img, target"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Files already downloaded and verified\n",
+ "Files already downloaded and verified\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Data loading ino tensors and transformation\n",
+ "transform = transforms.Compose([\n",
+ " transforms.ToTensor(),\n",
+ " transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)) # Normalize the RGB channels\n",
+ "])\n",
+ "\n",
+ "# Load in our training data from CIFAR10\n",
+ "train_dataset = AnimalCIFAR10(root='./data', train=True, download=True, transform=transform)\n",
+ "train_loader = DataLoader(train_dataset, batch_size=6, shuffle=True)\n",
+ "\n",
+ "# Load in our testing data from CIFAR10\n",
+ "test_dataset = AnimalCIFAR10(root='./data', train=False, download=True, transform=transform)\n",
+ "test_loader = DataLoader(test_dataset, batch_size=6, shuffle=False)\n",
+ "\n",
+ "animal_classes = ['bird', 'cat', 'deer', 'dog', 'frog', 'horse']"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Lets show what some of the images look like:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 69,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
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