{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", " \"cognitiveclass.ai\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "

Linear Regression 1D: Training One Parameter

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Objective

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Table of Contents

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In this lab, you will train a model with PyTorch by using data that you created. The model only has one parameter: the slope.

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Estimated Time Needed: 20 min

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Preparation

\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The following are the libraries we are going to use for this lab.\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# These are the libraries will be used for this lab.\n", "\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The class plot_diagram helps us to visualize the data space and the parameter space during training and has nothing to do with PyTorch.\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# The class for plotting\n", "\n", "class plot_diagram():\n", " \n", " # Constructor\n", " def __init__(self, X, Y, w, stop, go = False):\n", " start = w.data\n", " self.error = []\n", " self.parameter = []\n", " self.X = X.numpy()\n", " self.Y = Y.numpy()\n", " self.parameter_values = torch.arange(start, stop)\n", " self.Loss_function = [criterion(forward(X), Y) for w.data in self.parameter_values] \n", " w.data = start\n", " \n", " # Executor\n", " def __call__(self, Yhat, w, error, n):\n", " self.error.append(error)\n", " self.parameter.append(w.data)\n", " plt.subplot(212)\n", " plt.plot(self.X, Yhat.detach().numpy())\n", " plt.plot(self.X, self.Y,'ro')\n", " plt.xlabel(\"A\")\n", " plt.ylim(-20, 20)\n", " plt.subplot(211)\n", " plt.title(\"Data Space (top) Estimated Line (bottom) Iteration \" + str(n))\n", " plt.plot(self.parameter_values.numpy(), self.Loss_function) \n", " plt.plot(self.parameter, self.error, 'ro')\n", " plt.xlabel(\"B\")\n", " plt.figure()\n", " \n", " # Destructor\n", " def __del__(self):\n", " plt.close('all')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "

Make Some Data

\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import PyTorch library:\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# Import the library PyTorch\n", "\n", "import torch" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Generate values from -3 to 3 that create a line with a slope of -3. This is the line you will estimate.\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# Create the f(X) with a slope of -3\n", "\n", "X = torch.arange(-3, 3, 0.1).view(-1, 1)\n", "f = -3 * X" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let us plot the line.\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Plot the line with blue\n", "\n", "plt.plot(X.numpy(), f.numpy(), label = 'f')\n", "plt.xlabel('x')\n", "plt.ylabel('y')\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let us add some noise to the data in order to simulate the real data. Use torch.randn(X.size()) to generate Gaussian noise that is the same size as X and has a standard deviation opf 0.1.\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# Add some noise to f(X) and save it in Y\n", "\n", "Y = f + 0.1 * torch.randn(X.size())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the Y: \n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Plot the data points\n", "\n", "plt.plot(X.numpy(), Y.numpy(), 'rx', label = 'Y')\n", "\n", "plt.plot(X.numpy(), f.numpy(), label = 'f')\n", "plt.xlabel('x')\n", "plt.ylabel('y')\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "

Create the Model and Cost Function (Total Loss)

\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this section, let us create the model and the cost function (total loss) we are going to use to train the model and evaluate the result.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, define the forward function $y=w*x$. (We will add the bias in the next lab.)\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# Create forward function for prediction\n", "\n", "def forward(x):\n", " return w * x" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Define the cost or criterion function using MSE (Mean Square Error): \n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# Create the MSE function for evaluate the result.\n", "\n", "def criterion(yhat, y):\n", " return torch.mean((yhat - y) ** 2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Define the learning rate lr and an empty list LOSS to record the loss for each iteration: \n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# Create Learning Rate and an empty list to record the loss for each iteration\n", "\n", "lr = 0.1\n", "LOSS = []" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, we create a model parameter by setting the argument requires_grad to True because the system must learn it.\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "w = torch.tensor(-10.0, requires_grad = True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create a plot_diagram object to visualize the data space and the parameter space for each iteration during training:\n" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "gradient_plot = plot_diagram(X, Y, w, stop = 5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "

Train the Model

\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let us define a function for training the model. The steps will be described in the comments.\n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "# Define a function for train the model\n", "\n", "def train_model(iter):\n", " for epoch in range (iter):\n", " \n", " # make the prediction as we learned in the last lab\n", " Yhat = forward(X)\n", " \n", " # calculate the iteration\n", " loss = criterion(Yhat,Y)\n", " \n", " # plot the diagram for us to have a better idea\n", " gradient_plot(Yhat, w, loss.item(), epoch)\n", " \n", " # store the loss into list\n", " LOSS.append(loss.item())\n", " \n", " # backward pass: compute gradient of the loss with respect to all the learnable parameters\n", " loss.backward()\n", " \n", " # updata parameters\n", " w.data = w.data - lr * w.grad.data\n", " \n", " # zero the gradients before running the backward pass\n", " w.grad.data.zero_()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let us try to run 4 iterations of gradient descent: \n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Give 4 iterations for training the model here.\n", "\n", "train_model(4)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the cost for each iteration: \n" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(23.875, 0.5, 'Cost')" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Plot the loss for each iteration\n", "\n", "plt.plot(LOSS)\n", "plt.tight_layout()\n", "plt.xlabel(\"Epoch/Iterations\")\n", "plt.ylabel(\"Cost\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "

Practice

\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create a new learnable parameter w with an initial value of -15.0.\n" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "# Practice: Create w with the inital value of -15.0\n", "\n", "w = torch.tensor(-15.0, requires_grad=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Double-click here for the solution.\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create an empty list LOSS2:\n" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# Practice: Create LOSS2 list\n", "\n", "LOSS2 = []" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Double-click here for the solution.\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Write your own my_train_model function with loss list LOSS2. And run it with 4 iterations.\n" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Practice: Create your own my_train_model\n", "\n", "gradient_plot1 = plot_diagram(X, Y, w, stop = 15)\n", "\n", "def my_train_model(iter):\n", " for epoch in range (iter):\n", " Yhat = forward(X)\n", " loss = criterion(Yhat,Y)\n", " gradient_plot1(Yhat, w, loss.item(), epoch)\n", " LOSS2.append(loss)\n", " loss.backward()\n", " w.data = w.data - lr * w.grad.data\n", " w.grad.data.zero_()\n", "my_train_model(4)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Double-click here for the solution.\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot an overlay of the list LOSS2 and LOSS. \n" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Practice: Plot the list LOSS2 and LOSS\n", "\n", "plt.plot(LOSS, label = \"LOSS\")\n", "plt.plot(LOSS2, label = \"LOSS2\")\n", "plt.tight_layout()\n", "plt.xlabel(\"Epoch/Iterations\")\n", "plt.ylabel(\"Cost\")\n", "plt.legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Double-click here for the solution.\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What does this tell you about the parameter value? \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Double-click here for the solution.\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "

About the Authors:

\n", "\n", "Joseph Santarcangelo has a PhD in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Other contributors: Michelle Carey, Mavis Zhou \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Change Log\n", "\n", "| Date (YYYY-MM-DD) | Version | Changed By | Change Description |\n", "| ----------------- | ------- | ---------- | ----------------------------------------------------------- |\n", "| 2020-09-21 | 2.0 | Shubham | Migrated Lab to Markdown and added to course repo in GitLab |\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##

© IBM Corporation 2020. All rights reserved.

\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 2 }