{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "![](../docs/banner.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Chapter 4: Training Neural Networks\n", "\n", "**By [Tomas Beuzen](https://www.tomasbeuzen.com/) 🚀**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![](img/robot.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Chapter Outline\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Chapter Learning Objectives\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- Explain how backpropagation works at a high level.\n", "- Describe the difference between training loss and validation loss when creating a neural network.\n", "- Identify and describe common techniques to avoid overfitting/apply regularization to neural networks, e.g., early stopping, drop out, L2 regularization.\n", "- Use `PyTorch` to develop a fully-connected neural network and training pipeline." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Imports\n", "
" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import torch\n", "from torch import nn\n", "from torchvision import transforms, datasets, utils\n", "from torch.utils.data import DataLoader, TensorDataset\n", "from utils.plotting import *" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. Differentiation, Backpropagation, Autograd\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In previous chapters we've discussed optimization algorithms like gradient descent, stochastic gradient descent, ADAM, etc. These algorithms need the gradient of the loss function w.r.t the model parameters to optimize the parameters:\n", "\n", "$$\\nabla \\mathscr{L}(\\mathbf{w}) = \\begin{bmatrix} \\frac{\\partial \\mathscr{L}}{\\partial w_1} \\\\ \\frac{\\partial \\mathscr{L}}{\\partial w_2} \\\\ \\vdots \\\\ \\frac{\\partial \\mathscr{L}}{\\partial w_d} \\end{bmatrix}$$ \n", "\n", "We've been able to calculate the gradient by hand for things like linear regression and logistic regression. But how would you work out the gradient for this *very* simple network for regression:\n", "\n", "![](img/backprop-1.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The equation for calculating the output of that network is below, it's the linear layers and activation functions (Sigmoid in this case) recursively stuck together:\n", "\n", "$$S(x)=\\frac{1}{1+e^{-x}}$$\n", "\n", "$$\\hat{y}=w_3S(w_1x+b_1) + w_4S(w_2x+b_2) + b_3$$\n", "\n", "So how would we calculate the gradient of say the MSE loss w.r.t to all our parameters?\n", "\n", "$$\\mathscr{L}(\\mathbf{w}) = \\frac{1}{n}\\sum^{n}_{i=1}(y_i-\\hat{y_i})^2$$ \n", "\n", "$$\\nabla \\mathscr{L}(\\mathbf{w}) = \\begin{bmatrix} \\frac{\\partial \\mathscr{L}}{\\partial w_1} \\\\ \\frac{\\partial \\mathscr{L}}{\\partial w_2} \\\\ \\vdots \\\\ \\frac{\\partial \\mathscr{L}}{\\partial w_d} \\end{bmatrix}$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We have 3 options:\n", "1. **Symbolic differentiation**: i.e., \"do it by hand\" like we learned in calculus.\n", "2. **Numerical differentiation**: for example, approximating the derivative using finite differences $\\frac{df(x)}{dx} \\approx \\frac{f(x+h)-f(x)}{h}$.\n", "3. **Automatic differentiation**: the \"best of both worlds\". \n", "\n", "We'll be looking at option 3 Automatic Differentiation (AD) here, as we use a particular flavour of AD called \"backpropagation\" to train neural networks. But if you're interested in learning more about the other methods, see [Appendix C: Computing Derivatives](appendixC_computing-derivatives.ipynb)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.1. Backpropagation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Backpropagation is the algorithm we use to compute the gradients needed to train the parameters of a neural network. In backpropagation, the main idea is to decompose our network into smaller operations with simple, codeable derivatives. We then combine all these smaller operations together with the chain rule. The term \"backpropagation\" stems from the fact that we start at the end of our network and then propagate backwards. I'm going to go through a short example based on this network:\n", "\n", "![](img/backprop-2.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's decompose that into smaller operations. I've introduced some new variables to hold intermediate states $z_i$ (node output before activation) and $a_i$ (node output after activation). I'll also feed in one sample data point `(x, y)` = `(1, 3)` and am showing intermediate outputs in green and the final loss in red. This is called the \"forward pass\" step - where I feed in data and calculate outputs from left to right:\n", "\n", "![](img/backprop-3.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's zoom in to the outpout node and calculate the gradients for just the parameters connected to that node. It looks complicated but the derivatives are very simple - take some time to examine this figure and you'll see!\n", "\n", "![](img/backprop-4.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "That all boils down to this:\n", "\n", "![](img/backprop-5.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, the beauty of backpropagation is that we can use these results to easily calculate derivatives earlier in the network using the *chain rule*. I'll do that for $b_1$ and $b_2$ below. Once again, it looks complicated, but we're simply combining a bunch of small, simple derivatives with the chain rule:\n", "\n", "![](img/backprop-6.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "I've left calculating the gradients of $w_1$ and $w_2$ up to you. All the gradients for the network boil down to this:\n", "\n", "![](img/backprop-7.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So summarising the process:\n", "1. We \"forward pass\" some data through our network\n", "2. We \"backpropagate\" the error through the network to calculate gradients\n", "\n", "Luckily, you'll never do this by hand again, because `torch.autograd` does all this for us!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.2. Autograd" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`torch.autograd` is PyTorch's automatic differentiation engine which helps us implement backpropagation. In plain English: `torch.autograd` automatically calculates and stores derivatives for your network. Consider our simple network above:\n", "\n", "![](img/backprop-2.png)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "class network(torch.nn.Module):\n", " def __init__(self, input_size, hidden_size, output_size):\n", " super().__init__()\n", " self.hidden = torch.nn.Linear(input_size, hidden_size)\n", " self.output = torch.nn.Linear(hidden_size, output_size)\n", "\n", " def forward(self, x):\n", " x = self.hidden(x)\n", " x = torch.sigmoid(x)\n", " x = self.output(x)\n", " return x" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "model = network(1, 2, 1) # make an instance of our network\n", "model.state_dict()['hidden.weight'][:] = torch.tensor([[1], [-1]]) # fix the weights manually based on the earlier figure\n", "model.state_dict()['hidden.bias'][:] = torch.tensor([1, 2])\n", "model.state_dict()['output.weight'][:] = torch.tensor([[1, 2]])\n", "model.state_dict()['output.bias'][:] = torch.tensor([-1])\n", "x, y = torch.tensor([1.0]), torch.tensor([3.0]) # our x, y data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's check the gradient of the bias of the output node:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "None\n" ] } ], "source": [ "print(model.output.bias.grad)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It's currently `None`!\n", "\n", "PyTorch is tracking the operations in our network and how to calculate the gradient (more on that a bit later), but it hasn't calculated anything yet because we don't have a loss function and we haven't done a forward pass to calculate the loss so there's nothing to backpropagate yet!\n", "\n", "Let's define a loss now:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "criterion = torch.nn.MSELoss()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can force Pytorch to \"backpropagate\" the errors, like we just did by hand earlier by:\n", "1. Doing a \"forward pass\" of our `(x, y)` data and calculating the `loss`;\n", "2. \"Backpropagating\" the loss by calling `loss.backward()`" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "loss = criterion(model(x), y)\n", "loss.backward() # backpropagates the error to calculate gradients!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's check the gradient of the bias of the output node ($\\frac{\\partial \\mathscr{L}}{\\partial b_3}$):" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "tensor([-3.3142])\n" ] } ], "source": [ "print(model.output.bias.grad)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It matches what we calculated earlier!\n", "\n", "![](img/backprop-8.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "That is just so fantastic! In fact, we can make sure that all our gradients match what we calculated by hand:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Hidden Layer Gradients\n", "Bias: tensor([-0.3480, -1.3032])\n", "Weights: tensor([-0.3480, -1.3032])\n", "\n", "Output Layer Gradients\n", "Bias: tensor([-3.3142])\n", "Weights: tensor([-2.9191, -2.4229])\n" ] } ], "source": [ "print(\"Hidden Layer Gradients\")\n", "print(\"Bias:\", model.hidden.bias.grad)\n", "print(\"Weights:\", model.hidden.weight.grad.squeeze())\n", "print()\n", "print(\"Output Layer Gradients\")\n", "print(\"Bias:\", model.output.bias.grad)\n", "print(\"Weights:\", model.output.weight.grad.squeeze())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have the gradients, what's the next step? We use our optimization algorithm to update our weights! These are our current weights:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "OrderedDict([('hidden.weight',\n", " tensor([[ 1.],\n", " [-1.]])),\n", " ('hidden.bias', tensor([1., 2.])),\n", " ('output.weight', tensor([[1., 2.]])),\n", " ('output.bias', tensor([-1.]))])" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model.state_dict()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To optimize them, we:\n", "1. Define an `optimizer`;\n", "2. Ask it to update our weights based on our gradients using `optimizer.step()`." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "optimizer = torch.optim.SGD(model.parameters(), lr=0.1)\n", "optimizer.step()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Our weights should now be different:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "OrderedDict([('hidden.weight',\n", " tensor([[ 1.0348],\n", " [-0.8697]])),\n", " ('hidden.bias', tensor([1.0348, 2.1303])),\n", " ('output.weight', tensor([[1.2919, 2.2423]])),\n", " ('output.bias', tensor([-0.6686]))])" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model.state_dict()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Amazing!\n", "\n", "One last thing for you to know: **Pytorch does not automatically clear the gradients** after using them. So if I call `loss.backward()` again, my gradients accumulate:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "b3 gradient after call 1 of loss.backward(): tensor([-0.1991, -0.5976])\n", "b3 gradient after call 2 of loss.backward(): tensor([-0.3983, -1.1953])\n", "b3 gradient after call 3 of loss.backward(): tensor([-0.5974, -1.7929])\n", "b3 gradient after call 4 of loss.backward(): tensor([-0.7966, -2.3906])\n", "b3 gradient after call 5 of loss.backward(): tensor([-0.9957, -2.9882])\n" ] } ], "source": [ "optimizer.zero_grad() # <- I'll explain this in the next cell\n", "for _ in range(1, 6):\n", " loss = criterion(model(x), y)\n", " loss.backward()\n", " print(f\"b3 gradient after call {_} of loss.backward():\", model.hidden.bias.grad)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Our gradients are accumulating each time we call `loss.backward()`! So we need to tell Pytorch to \"zero the gradients\" each iteration using `optimizer.zero_grad()`:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "b3 gradient after call 1 of loss.backward(): tensor([-0.1991, -0.5976])\n", "b3 gradient after call 2 of loss.backward(): tensor([-0.1991, -0.5976])\n", "b3 gradient after call 3 of loss.backward(): tensor([-0.1991, -0.5976])\n", "b3 gradient after call 4 of loss.backward(): tensor([-0.1991, -0.5976])\n", "b3 gradient after call 5 of loss.backward(): tensor([-0.1991, -0.5976])\n" ] } ], "source": [ "for _ in range(1, 6):\n", " optimizer.zero_grad() # <- don't forget this!!!\n", " loss = criterion(model(x), y)\n", " loss.backward()\n", " print(f\"b3 gradient after call {_} of loss.backward():\", model.hidden.bias.grad)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> Note: you might wonder why PyTorch behaves like this. Well, there are some cases we might want to accumulate the gradient. For example, if we want to calculate the gradients over several batches before updating our weights. But don't worry about that for now - most of the time, you'll want to be \"zeroing out\" the gradients each iteration." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.3. Computational Graph (Optional)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "PyTorch's `autograd` basically keeps a record of our data and network operations in a computational graph. That's beyond the scope of this chapter, but if you're interested in learning more, I recommend [this excellent video](https://www.youtube.com/watch?v=MswxJw-8PvE). Also, `torchviz` is a useful package to look at the \"computational graph\" PyTorch is building for us under the hood:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "4984431632\n", "\n", "AddmmBackward\n", "\n", "\n", "\n", "4984262736\n", "\n", " (1)\n", "\n", "\n", "\n", "4984262736->4984431632\n", "\n", "\n", "\n", "\n", "\n", "4982166608\n", "\n", "SigmoidBackward\n", "\n", "\n", "\n", "4982166608->4984431632\n", "\n", "\n", "\n", "\n", "\n", "4984459728\n", "\n", "AddmmBackward\n", "\n", "\n", "\n", "4984459728->4982166608\n", "\n", "\n", "\n", "\n", "\n", "4984470096\n", "\n", " (2)\n", "\n", "\n", "\n", "4984470096->4984459728\n", "\n", "\n", "\n", "\n", "\n", "4984469904\n", "\n", "TBackward\n", "\n", "\n", "\n", "4984469904->4984459728\n", "\n", "\n", "\n", "\n", "\n", "4984470416\n", "\n", " (2, 1)\n", "\n", "\n", "\n", "4984470416->4984469904\n", "\n", "\n", "\n", "\n", "\n", "4984459536\n", "\n", "TBackward\n", "\n", "\n", "\n", "4984459536->4984431632\n", "\n", "\n", "\n", "\n", "\n", "4984470224\n", "\n", " (1, 2)\n", "\n", "\n", "\n", "4984470224->4984459536\n", "\n", "\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from torchviz import make_dot\n", "make_dot(model(torch.rand(1, 1)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2. Training Neural Networks\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The big takeaway from the last section is that PyTorch's `autograd` takes care of the gradients for us. We just need to put all the pieces together properly. Remember the below `trainer()` function I used last chapter to train my network. Now we know what all this means!" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "def trainer(model, criterion, optimizer, dataloader, epochs=5):\n", " \"\"\"Simple training wrapper for PyTorch network.\"\"\"\n", " \n", " train_loss = []\n", " for epoch in range(epochs): # for each epoch\n", " losses = 0\n", " for X, y in dataloader: # for each batch\n", " optimizer.zero_grad() # Zero all the gradients w.r.t. parameters\n", " y_hat = model(X).flatten() # Forward pass to get output\n", " loss = criterion(y_hat, y) # Calculate loss based on output\n", " loss.backward() # Calculate gradients w.r.t. parameters\n", " optimizer.step() # Update parameters\n", " losses += loss.item() # Add loss for this batch to running total\n", " train_loss.append(losses / len(dataloader)) # loss = total loss in epoch / number of batches = loss per batch\n", " return train_loss" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notice how I calculate the loss for each epoch by summing up the loss for each batch in that epoch? I then divide the loss per epoch by total number of batches to get the average loss per batch in an epoch (I store that loss in `running_losses`).\n", "\n", ">Dividing by the number of batches \"decouples\" our loss from the batch size. So if I run another experiment with a different batch size, I'll still be able to compare losses for that experiment with this one. We'll explore this concept more later.\n", "\n", "If our model is being trained correctly, our loss should go down over time. Let's try it out with some sample data:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "marker": { "size": 10 }, "mode": "markers", "name": "data", "type": "scatter", "x": [ -3, -2.8499999046325684, -2.700000047683716, -2.549999952316284, -2.4000000953674316, -2.25, -2.0999999046325684, -1.9500000476837158, -1.7999999523162842, -1.649999976158142, -1.5, -1.3499999046325684, -1.1999999284744263, -1.0499999523162842, -0.8999999761581421, -0.7499999403953552, -0.6000000238418579, -0.45000001788139343, -0.30000001192092896, -0.15000002086162567, -2.3841858265427618e-08, 0.1499999761581421, 0.29999998211860657, 0.44999998807907104, 0.6000000238418579, 0.75, 0.9000000357627869, 1.0500000715255737, 1.2000000476837158, 1.350000023841858, 1.5, 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", 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", "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model = network(1, 3, 1)\n", "criterion = torch.nn.MSELoss()\n", "optimizer = torch.optim.Adam(model.parameters(), 0.1)\n", "train_loss = trainer(model, criterion, optimizer, dataloader, epochs=101)\n", "plot_regression(X, y, model(X[:, None]).detach(), y_range=[-1, 10], dy=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The model looks like a good fit, so presumably the loss went down as epochs progressed, let's take a look:" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "line": { "width": 2 }, "mode": "lines", "name": "Training loss", "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_loss(train_loss)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.1. Validation Loss" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We've been focussing on training loss so far, but as we know, we need to validate our model on new \"unseen\" data! For this, we'll need some validation data, I'm going to split our dataset in half to create a `trainloader` and a `validloader`:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "# Create dataset\n", "torch.manual_seed(0)\n", "X_valid = torch.arange(-3.0, 3.0)\n", "y_valid = X_valid ** 2\n", "trainloader = DataLoader(TensorDataset(X, y), batch_size=1, shuffle=True)\n", "validloader = DataLoader(TensorDataset(X_valid, y_valid), batch_size=1, shuffle=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now the wonderful thing about PyTorch is that you are in full control - you can do whatever you want! So here, after each epoch, I'm going to record the validation loss by looping over my validation batches, it's just a little extra module I add to my training function:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "def trainer(model, criterion, optimizer, trainloader, validloader, epochs=5):\n", " \"\"\"Simple training wrapper for PyTorch network.\"\"\"\n", " \n", " train_loss = []\n", " valid_loss = []\n", " for epoch in range(epochs): # for each epoch\n", " train_batch_loss = 0\n", " valid_batch_loss = 0\n", " \n", " # Training\n", " model.train() # This puts the model in \"training mode\", this is the default mode.\n", " # We'll use a different mode, \"evaluation mode\", for validation.\n", " for X, y in trainloader:\n", " optimizer.zero_grad() # Zero all the gradients w.r.t. parameters\n", " y_hat = model(X).flatten() # Forward pass to get output\n", " loss = criterion(y_hat, y) # Calculate loss based on output\n", " loss.backward() # Calculate gradients w.r.t. parameters\n", " optimizer.step() # Update parameters\n", " train_batch_loss += loss.item() # Add loss for this batch to running total\n", " train_loss.append(train_batch_loss / len(trainloader)) # loss = total loss in epoch / number of batches = loss per batch\n", " \n", " # Validation\n", " model.train() # This puts the model in \"evaluation mode\". It's important to do this when our model\n", " # includes some randomness like dropout layers which we'll see later. It turns off \n", " # this randomness for validation purposes.\n", " with torch.no_grad(): # this stops pytorch doing computational graph stuff under-the-hood and saves memory and time\n", " for X_valid, y_valid in validloader:\n", " y_hat = model(X_valid).flatten() # Forward pass to get output\n", " loss = criterion(y_hat, y_valid) # Calculate loss based on output\n", " valid_batch_loss += loss.item() # Add loss for this batch to running total\n", " \n", " \n", " valid_loss.append(valid_batch_loss / len(validloader))\n", " return train_loss, valid_loss" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "line": { "width": 2 }, "mode": "lines", "name": "Training loss", "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model = network(1, 6, 1)\n", "criterion = torch.nn.MSELoss()\n", "optimizer = torch.optim.Adam(model.parameters(), lr=0.05)\n", "train_loss, valid_loss = trainer(model, criterion, optimizer, trainloader, validloader, epochs=201)\n", "plot_loss(train_loss, valid_loss)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What do we see above? Well, we're obviously overfitting (fitting to closely to the training data such that we do poorly on the validation data). We are optimizing too well! One way we could avoid overfitting is by terminating the training if our validation loss starts going up, this is called \"early stopping\"." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.2. Early stopping" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Early stopping is a way of avoiding overfitting. As training progresses, if we notice the validation loss increasing (while the training loss decreases), that's usually an indication of overfitting. The validation loss may go up and down from epoch to epoch, so usually we define a \"patience\" which is a number of consecutive epochs we're willing to allow the validation loss to increase before we stop. Once again, the beauty of PyTorch is how easy it is to customize your network in this way:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "def trainer(model, criterion, optimizer, trainloader, validloader, epochs=5, patience=5):\n", " \"\"\"Simple training wrapper for PyTorch network.\"\"\"\n", " \n", " train_loss = []\n", " valid_loss = []\n", " for epoch in range(epochs): # for each epoch\n", " train_batch_loss = 0\n", " valid_batch_loss = 0\n", " \n", " # Training\n", " for X, y in trainloader:\n", " optimizer.zero_grad() # Zero all the gradients w.r.t. parameters\n", " y_hat = model(X).flatten() # Forward pass to get output\n", " loss = criterion(y_hat, y) # Calculate loss based on output\n", " loss.backward() # Calculate gradients w.r.t. parameters\n", " optimizer.step() # Update parameters\n", " train_batch_loss += loss.item() # Add loss for this batch to running total\n", " train_loss.append(train_batch_loss / len(trainloader)) # loss = total loss in epoch / number of batches = loss per batch\n", " \n", " # Validation\n", " with torch.no_grad(): # this stops pytorch doing computational graph stuff under-the-hood and saves memory and time\n", " for X_valid, y_valid in validloader:\n", " y_hat = model(X_valid).flatten() # Forward pass to get output\n", " loss = criterion(y_hat, y_valid) # Calculate loss based on output\n", " valid_batch_loss += loss.item() # Add loss for this batch to running total\n", " \n", " valid_loss.append(valid_batch_loss / len(validloader))\n", " \n", " # Early stopping\n", " if epoch > 0 and valid_loss[-1] > valid_loss[-2]:\n", " consec_increases += 1\n", " else:\n", " consec_increases = 0\n", " if consec_increases == patience:\n", " print(f\"Stopped early at epoch {epoch + 1} - val loss increased for {consec_increases} consecutive epochs!\")\n", " break\n", " \n", " return train_loss, valid_loss" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Stopped early at epoch 58 - val loss increased for 3 consecutive epochs!\n" ] }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "line": { "width": 2 }, "mode": "lines", "name": "Training loss", "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57 ], "y": [ 13.192530316510238, 11.91498707337305, 11.562104489557168, 10.829653614247217, 10.511115354881621, 10.121629650145769, 9.66899603274651, 9.226016867905855, 9.076635855948552, 8.355432985376684, 7.729225528240204, 7.279382384355268, 6.683980354594678, 6.037736817263067, 5.785133236711954, 4.978836443368346, 4.678916783930617, 4.4872714368651945, 5.161363640398486, 3.925811215734575, 3.829822329045237, 4.152977855864447, 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", "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model = network(1, 6, 1)\n", "criterion = torch.nn.MSELoss()\n", "optimizer = torch.optim.Adam(model.parameters(), lr=0.05)\n", "train_loss, valid_loss = trainer(model, criterion, optimizer, trainloader, validloader, epochs=201, patience=3)\n", "plot_loss(train_loss, valid_loss)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are more advanced implementations of early stopping out there, but you get the idea!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3. Regularization\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Recall that regularization is a technique to help avoid overfitting. There are many regularization techniques available in neural networks. I'll discuss the two main ones here:\n", "1. Drop out\n", "2. L2 regularization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3.1. Drop Out" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Drop out is a common regularization technique and is very simple. Basically, each iteration, we randomly chose some nodes in a layer and don't update their weights (to do this we set the output of the nodes to 0). A simple example:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "tensor([[ 0.8693, -2.1287, 0.6825],\n", " [-0.8968, -0.4331, -0.4829],\n", " [-1.8682, -1.0257, 0.5033],\n", " [ 1.5761, 1.8840, -1.2248],\n", " [-1.4531, 0.3420, -1.1799]])" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dropout_layer = torch.nn.Dropout(p=0.5) # 50% probability that a node will be set to 0 (\"dropped out\")\n", "inputs = torch.randn(5, 3)\n", "inputs" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "tensor([[ 1.7386, -0.0000, 1.3651],\n", " [-1.7936, -0.0000, -0.0000],\n", " [-0.0000, -0.0000, 0.0000],\n", " [ 0.0000, 0.0000, -2.4496],\n", " [-2.9063, 0.6840, -2.3598]])" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dropout_layer(inputs)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the above, note how about 50% of nodes have been given a value of 0!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3.2. L2 Regularization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Recall that in L2 we had this penalty to the loss: $\\frac{\\lambda}{2}||w||^2$. $\\lambda$ is the regularization parameter. L2 regularization is called \"weight-decay\" in PyTorch (because we are coercing the weights to be smaller I suppose). It's an argument in most optimizers which you can specify:" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Adam (\n", "Parameter Group 0\n", " amsgrad: False\n", " betas: (0.9, 0.999)\n", " eps: 1e-08\n", " lr: 0.1\n", " weight_decay: 0.5\n", ")" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "torch.optim.Adam(model.parameters(), lr=0.1, weight_decay=0.5) # here weight_decay is λ in the above equation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4. Putting it all Together with Bitmojis\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here I thought we'd put everything we learned in this chapter together to predict some bitmojis. I have a folder of images with the following structure:\n", "\n", "```\n", "data\n", "└── bitmoji_bw\n", " ├── train\n", " │ ├── not_tom\n", " │ └── tom\n", " └── valid\n", " ├── not_tom\n", " └── tom\n", "```" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [], "source": [ "TRAIN_DIR = \"data/bitmoji_bw/train/\"\n", "VALID_DIR = \"data/bitmoji_bw/valid/\"\n", "IMAGE_SIZE = 50\n", "BATCH_SIZE = 32\n", "\n", "data_transforms = transforms.Compose([\n", " transforms.Resize(IMAGE_SIZE),\n", " transforms.Grayscale(num_output_channels=1),\n", " transforms.ToTensor()\n", "])\n", "# Training data\n", "train_dataset = datasets.ImageFolder(root=TRAIN_DIR, transform=data_transforms)\n", "train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=BATCH_SIZE, shuffle=True)\n", "# Validation data\n", "valid_dataset = datasets.ImageFolder(root=VALID_DIR, transform=data_transforms)\n", "valid_loader = torch.utils.data.DataLoader(valid_dataset, batch_size=BATCH_SIZE, shuffle=True)" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sample_batch = next(iter(train_loader))\n", "plot_bitmojis(sample_batch)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now to the network. I'm going to make a function `linear_block()` to help create my network and keep things DRY:" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "def linear_block(input_size, output_size):\n", " return nn.Sequential(\n", " nn.Linear(input_size, output_size),\n", " nn.LeakyReLU(),\n", " nn.Dropout(0.1)\n", " )\n", "\n", "class BitmojiClassifier(nn.Module):\n", " def __init__(self, input_size):\n", " super().__init__()\n", " self.main = nn.Sequential(\n", " linear_block(input_size, 256),\n", " linear_block(256, 128),\n", " linear_block(128, 64),\n", " linear_block(64, 16),\n", " nn.Linear(16, 1)\n", " )\n", " \n", " def forward(self, x):\n", " out = self.main(x)\n", " return out" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now the training function. This is getting long but it's just all the bits we've seen before!" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [], "source": [ "def trainer(model, criterion, optimizer, trainloader, validloader, epochs=5, patience=5, verbose=True):\n", " \"\"\"Simple training wrapper for PyTorch network.\"\"\"\n", " \n", " train_loss = []\n", " valid_loss = []\n", " train_accuracy = []\n", " valid_accuracy = []\n", " for epoch in range(epochs): # for each epoch\n", " train_batch_loss = 0\n", " train_batch_acc = 0\n", " valid_batch_loss = 0\n", " valid_batch_acc = 0\n", " \n", " # Training\n", " for X, y in trainloader:\n", " optimizer.zero_grad() # Zero all the gradients w.r.t. parameters\n", " y_hat = model(X.view(X.shape[0], -1)).flatten() # Forward pass to get output\n", " y_hat_labels = torch.sigmoid(y_hat) > 0.5 # convert probabilities to False (0) and True (1)\n", " loss = criterion(y_hat, y.type(torch.float32)) # Calculate loss based on output\n", " loss.backward() # Calculate gradients w.r.t. parameters\n", " optimizer.step() # Update parameters\n", " train_batch_loss += loss.item() # Add loss for this batch to running total\n", " train_batch_acc += (y_hat_labels == y).type(torch.float32).mean().item() # Average accuracy for this batch\n", " train_loss.append(train_batch_loss / len(trainloader)) # loss = total loss in epoch / number of batches = loss per batch\n", " train_accuracy.append(train_batch_acc / len(trainloader)) # accuracy\n", " \n", " # Validation\n", " model.eval() # this turns off those random dropout layers, we don't want them for validation!\n", " with torch.no_grad(): # this stops pytorch doing computational graph stuff under-the-hood and saves memory and time\n", " for X, y in validloader:\n", " y_hat = model(X.view(X.shape[0], -1)).flatten() # Forward pass to get output\n", " y_hat_labels = torch.sigmoid(y_hat) > 0.5 # convert probabilities to False (0) and True (1)\n", " loss = criterion(y_hat, y.type(torch.float32)) # Calculate loss based on output\n", " valid_batch_loss += loss.item() # Add loss for this batch to running total\n", " valid_batch_acc += (y_hat_labels == y).type(torch.float32).mean().item() # Average accuracy for this batch \n", " valid_loss.append(valid_batch_loss / len(validloader))\n", " valid_accuracy.append(valid_batch_acc / len(validloader)) # accuracy\n", " model.train() # turn back on the dropout layers for the next training loop\n", " \n", " # Print progress\n", " if verbose:\n", " print(f\"Epoch {epoch + 1}:\",\n", " f\"Train Loss: {train_loss[-1]:.3f}.\",\n", " f\"Valid Loss: {valid_loss[-1]:.3f}.\",\n", " f\"Train Accuracy: {train_accuracy[-1]:.2f}.\",\n", " f\"Valid Accuracy: {valid_accuracy[-1]:.2f}.\")\n", " \n", " # Early stopping\n", " if epoch > 0 and valid_loss[-1] > valid_loss[-2]:\n", " consec_increases += 1\n", " else:\n", " consec_increases = 0\n", " if consec_increases == patience:\n", " print(f\"Stopped early at epoch {epoch + 1} - val loss increased for {consec_increases} consecutive epochs!\")\n", " break\n", " \n", " results = {\"train_loss\": train_loss,\n", " \"valid_loss\": valid_loss,\n", " \"train_accuracy\": train_accuracy,\n", " \"valid_accuracy\": valid_accuracy}\n", " return results" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's do it!" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1: Train Loss: 0.697. Valid Loss: 0.693. Train Accuracy: 0.48. Valid Accuracy: 0.49.\n", "Epoch 2: Train Loss: 0.694. Valid Loss: 0.694. Train Accuracy: 0.50. Valid Accuracy: 0.50.\n", "Epoch 3: Train Loss: 0.693. Valid Loss: 0.693. Train Accuracy: 0.50. Valid Accuracy: 0.48.\n", "Epoch 4: Train Loss: 0.692. Valid Loss: 0.693. Train Accuracy: 0.52. Valid Accuracy: 0.50.\n", "Epoch 5: Train Loss: 0.693. Valid Loss: 0.693. Train Accuracy: 0.51. Valid Accuracy: 0.51.\n", "Epoch 6: Train Loss: 0.692. Valid Loss: 0.691. Train Accuracy: 0.52. Valid Accuracy: 0.52.\n", "Epoch 7: Train Loss: 0.694. Valid Loss: 0.693. Train Accuracy: 0.50. Valid Accuracy: 0.50.\n", "Epoch 8: Train Loss: 0.692. Valid Loss: 0.689. Train Accuracy: 0.54. Valid Accuracy: 0.56.\n", "Epoch 9: Train Loss: 0.691. Valid Loss: 0.690. Train Accuracy: 0.52. Valid Accuracy: 0.57.\n", "Epoch 10: Train Loss: 0.683. Valid Loss: 0.682. Train Accuracy: 0.57. Valid Accuracy: 0.56.\n", "Epoch 11: Train Loss: 0.693. Valid Loss: 0.693. Train Accuracy: 0.53. Valid Accuracy: 0.52.\n", "Epoch 12: Train Loss: 0.685. Valid Loss: 0.683. Train Accuracy: 0.56. Valid Accuracy: 0.54.\n", "Epoch 13: Train Loss: 0.677. Valid Loss: 0.678. Train Accuracy: 0.59. Valid Accuracy: 0.58.\n", "Epoch 14: Train Loss: 0.668. Valid Loss: 0.665. Train Accuracy: 0.61. Valid Accuracy: 0.61.\n", "Epoch 15: Train Loss: 0.664. Valid Loss: 0.654. Train Accuracy: 0.61. Valid Accuracy: 0.62.\n", "Epoch 16: Train Loss: 0.668. Valid Loss: 0.682. Train Accuracy: 0.60. Valid Accuracy: 0.56.\n", "Epoch 17: Train Loss: 0.681. Valid Loss: 0.685. Train Accuracy: 0.56. Valid Accuracy: 0.55.\n", "Epoch 18: Train Loss: 0.677. Valid Loss: 0.654. Train Accuracy: 0.58. Valid Accuracy: 0.63.\n", "Epoch 19: Train Loss: 0.665. Valid Loss: 0.667. Train Accuracy: 0.61. Valid Accuracy: 0.60.\n", "Epoch 20: Train Loss: 0.654. Valid Loss: 0.651. Train Accuracy: 0.62. Valid Accuracy: 0.65.\n", "Epoch 21: Train Loss: 0.664. Valid Loss: 0.655. Train Accuracy: 0.61. Valid Accuracy: 0.62.\n", "Epoch 22: Train Loss: 0.658. Valid Loss: 0.652. Train Accuracy: 0.61. Valid Accuracy: 0.63.\n", "Epoch 23: Train Loss: 0.652. Valid Loss: 0.643. Train Accuracy: 0.62. Valid Accuracy: 0.65.\n", "Epoch 24: Train Loss: 0.653. Valid Loss: 0.621. Train Accuracy: 0.61. Valid Accuracy: 0.66.\n", "Epoch 25: Train Loss: 0.653. Valid Loss: 0.641. Train Accuracy: 0.63. Valid Accuracy: 0.66.\n", "Epoch 26: Train Loss: 0.647. Valid Loss: 0.635. Train Accuracy: 0.61. Valid Accuracy: 0.65.\n", "Epoch 27: Train Loss: 0.644. Valid Loss: 0.680. Train Accuracy: 0.62. Valid Accuracy: 0.54.\n", "Epoch 28: Train Loss: 0.642. Valid Loss: 0.625. Train Accuracy: 0.63. Valid Accuracy: 0.65.\n", "Epoch 29: Train Loss: 0.627. Valid Loss: 0.648. Train Accuracy: 0.66. Valid Accuracy: 0.65.\n", "Epoch 30: Train Loss: 0.650. Valid Loss: 0.660. Train Accuracy: 0.63. Valid Accuracy: 0.58.\n" ] } ], "source": [ "model = BitmojiClassifier(IMAGE_SIZE * IMAGE_SIZE)\n", "criterion = nn.BCEWithLogitsLoss()\n", "optimizer = torch.optim.Adam(model.parameters())\n", "results = trainer(model, criterion, optimizer, train_loader, valid_loader, epochs=20, patience=3)" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "line": { "width": 2 }, "mode": "lines", "name": "Training loss", "type": "scatter", "x": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 ], "y": [ 0.6971313390466902, 0.6935842865043216, 0.6931286123063829, 0.6922572486930423, 0.6933103446607236, 0.6923315469865445, 0.6936712419545209, 0.6916223742343761, 0.6914468860184705, 0.6827302840020921, 0.6930794947677188, 0.6846947824513471, 0.6769615146848891, 0.6681079069773356, 0.6640994526721813, 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_loss(results[\"train_loss\"], results[\"valid_loss\"], results[\"train_accuracy\"], results[\"valid_accuracy\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "I couldn't get very good accuracy with this model and there's a reason for that - we're not considering the structure in our image. We're flattening our images down into independent pixels, but the relationship between pixels is probably important! We'll exploit that next chapter when we get to CNNs. For now, let's try a random image for fun:" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "image = torch.from_numpy(plt.imread(\"img/tom.png\"))\n", "image = transforms.Resize(IMAGE_SIZE)(image[None, None, :, :])\n", "prediction = model(image.view(1, -1)) # Flatten image to shape (1, 784) and predict it\n", "prediction = torch.sigmoid(prediction) # Coerce predictions to probabilities\n", "label = int(prediction > 0.5) # Get class label - 1 if propbability > 0.5, else 0\n", "plot_bitmoji(image, label)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Well, at least we got that one!" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [conda env:mds572]", "language": "python", "name": "conda-env-mds572-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": false, "sideBar": true, "skip_h1_title": true, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": true, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 4 }