updates for lecture 2025

.github/workflows/formatting.yaml

@@ -9,15 +9,4 @@ jobs:
         uses: lgeiger/black-action@master
         with:
           args: "--line-length 120 . --check"
-          name: black-action
-
-  auto-formatting:
-    name: runner / black
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v2
-      - name: Check files using the black formatter
-        uses: rickstaa/action-black@v1
-        id: action_black
-        with:
-          black_args: "--line-length 120 ."
+          name: black-action

.gitignore

@@ -0,0 +1,2 @@
+scripts/wandb/*
+scripts/images/*

scripts/03_wandb.ipynb

@@ -0,0 +1,165 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Install and Import Required Libraries\n",
+    "Install wandb using pip and import the necessary libraries."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Import the necessary ibraries\n",
+    "import wandb\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from PIL import Image\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Initialize wandb Project\n",
+    "Initialize a new wandb project and configure the settings."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Initialize wandb Project\n",
+    "wandb.init(project=\"plr-exercise\", config={\n",
+    "    \"learning_rate\": 0.001,\n",
+    "    \"epochs\": 10,\n",
+    "    \"batch_size\": 32\n",
+    "})\n",
+    "\n",
+    "# Access the configuration\n",
+    "config = wandb.config\n",
+    "\n",
+    "# Log the configuration\n",
+    "wandb.config.update({\n",
+    "    \"optimizer\": \"adam\",\n",
+    "    \"loss_function\": \"categorical_crossentropy\"\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Log Random Curves\n",
+    "Generate random curves and log them to wandb."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate random curves and log them to wandb\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y1 = np.sin(x) + np.random.normal(0, 0.1, 100)\n",
+    "y2 = np.cos(x) + np.random.normal(0, 0.1, 100)\n",
+    "\n",
+    "plt.figure()\n",
+    "plt.plot(x, y1, label='Random Sine Curve')\n",
+    "plt.plot(x, y2, label='Random Cosine Curve')\n",
+    "\n",
+    "plt.legend()\n",
+    "plt.title('Random Curves')\n",
+    "plt.xlabel('X-axis')\n",
+    "plt.ylabel('Y-axis')\n",
+    "\n",
+    "# Save the plot as an image file\n",
+    "plt.savefig('random_curves.png')\n",
+    "\n",
+    "# Log the plot image to wandb\n",
+    "wandb.log({\"random_curves\": wandb.Image('random_curves.png')})\n",
+    "\n",
+    "# Optionally, log the data points as well\n",
+    "wandb.log({\"x\": x, \"y1\": y1, \"y2\": y2})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Upload Images of Dogs and Cats\n",
+    "Upload images of dogs and cats to wandb."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Upload Images of Dogs and Cats\n",
+    "\n",
+    "# Create a directory to store images\n",
+    "os.makedirs('images', exist_ok=True)\n",
+    "\n",
+    "# Download sample images of dogs and cats\n",
+    "!wget -O images/dog.jpg https://images.unsplash.com/photo-1560807707-8cc77767d783\n",
+    "!wget -O images/cat.jpg https://images.unsplash.com/photo-1518791841217-8f162f1e1131\n",
+    "\n",
+    "# Load the images using PIL\n",
+    "dog_image = Image.open('images/dog.jpg')\n",
+    "cat_image = Image.open('images/cat.jpg')\n",
+    "\n",
+    "# Log the images to wandb\n",
+    "wandb.log({\"dog_image\": wandb.Image(dog_image, caption=\"Dog\")})\n",
+    "wandb.log({\"cat_image\": wandb.Image(cat_image, caption=\"Cat\")})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a new artifact\n",
+    "artifact = wandb.Artifact('source_code', type='code')\n",
+    "\n",
+    "# Add files to the artifact\n",
+    "artifact.add_file('./03_wandb.ipynb')\n",
+    "\n",
+    "# Log the artifact\n",
+    "wandb.log_artifact(artifact)\n",
+    "wandb.finish()\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": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}