mirror of
https://github.com/MLSysBook/TinyTorch.git
synced 2026-05-01 16:57:21 -05:00
82defeafd3
- Restored tools/py_to_notebook.py as a focused, standalone tool - Updated tito notebooks command to use subprocess to call the separate tool - Maintains clean separation of concerns: tito.py for CLI orchestration, py_to_notebook.py for conversion logic - Updated documentation to use 'tito notebooks' command instead of direct tool calls - Benefits: easier debugging, better maintainability, focused single-responsibility modules
684 lines
26 KiB
Plaintext
684 lines
26 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"---\n",
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"jupyter:\n",
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" jupytext:\n",
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" text_representation:\n",
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" extension: .py\n",
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" format_name: percent\n",
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" format_version: '1.3'\n",
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" jupytext_version: 1.17.1\n",
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"---\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"\"\"\"\n",
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"# Module 0: Setup - Tiny\ud83d\udd25Torch Development Workflow\n",
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"\n",
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"Welcome to TinyTorch! This module teaches you the development workflow you'll use throughout the course.\n",
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"\n",
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"## Learning Goals\n",
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"- Understand the nbdev notebook-to-Python workflow\n",
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"- Write your first TinyTorch code\n",
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"- Run tests and use the CLI tools\n",
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"- Get comfortable with the development rhythm\n",
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"\n",
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"## The TinyTorch Development Cycle\n",
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"\n",
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"1. **Write code** in this notebook using `#| export` \n",
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"2. **Export code** with `python bin/tito.py sync --module setup`\n",
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"3. **Run tests** with `python bin/tito.py test --module setup`\n",
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"4. **Check progress** with `python bin/tito.py info`\n",
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"\n",
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"Let's get started!\n",
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"\"\"\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#| default_exp core.utils\n",
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"\n",
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"# Setup imports and environment\n",
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"import sys\n",
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"import platform\n",
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"from datetime import datetime\n",
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"import os\n",
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"from pathlib import Path\n",
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"\n",
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"print(\"\ud83d\udd25 TinyTorch Development Environment\")\n",
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"print(f\"Python {sys.version}\")\n",
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"print(f\"Platform: {platform.system()} {platform.release()}\")\n",
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"print(f\"Started: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"\"\"\"\n",
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"## Step 1: Understanding the Module \u2192 Package Structure\n",
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"\n",
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"**\ud83c\udf93 Teaching vs. \ud83d\udd27 Building**: This course has two sides:\n",
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"- **Teaching side**: You work in `modules/setup/setup_dev.ipynb` (learning-focused)\n",
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"- **Building side**: Your code exports to `tinytorch/core/utils.py` (production package)\n",
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"\n",
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"**Key Concept**: The `#| default_exp core.utils` directive at the top tells nbdev to export all `#| export` cells to `tinytorch/core/utils.py`.\n",
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"\n",
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"This separation allows us to:\n",
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"- Organize learning by **concepts** (modules) \n",
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"- Organize code by **function** (package structure)\n",
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"- Build a real ML framework while learning systematically\n",
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"\n",
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"Let's write a simple \"Hello World\" function with the `#| export` directive:\n",
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"\"\"\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#| export\n",
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"def hello_tinytorch():\n",
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" \"\"\"\n",
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" A simple hello world function for TinyTorch.\n",
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" \n",
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" TODO: Implement this function to display TinyTorch ASCII art and welcome message.\n",
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" Load the flame art from tinytorch_flame.txt file with graceful fallback.\n",
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" \"\"\"\n",
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" raise NotImplementedError(\"Student implementation required\")\n",
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"\n",
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"def add_numbers(a, b):\n",
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" \"\"\"\n",
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" Add two numbers together.\n",
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" \n",
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" TODO: Implement addition of two numbers.\n",
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" This is the foundation of all mathematical operations in ML.\n",
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" \"\"\"\n",
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" raise NotImplementedError(\"Student implementation required\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#| hide\n",
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"#| export\n",
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"def hello_tinytorch():\n",
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" \"\"\"Display the TinyTorch ASCII art and welcome message.\"\"\"\n",
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" try:\n",
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" # Get the directory containing this file\n",
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" current_dir = Path(__file__).parent\n",
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" art_file = current_dir / \"tinytorch_flame.txt\"\n",
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" \n",
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" if art_file.exists():\n",
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" with open(art_file, 'r') as f:\n",
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" ascii_art = f.read()\n",
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" print(ascii_art)\n",
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" print(\"Tiny\ud83d\udd25Torch\")\n",
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" print(\"Build ML Systems from Scratch!\")\n",
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" else:\n",
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" print(\"\ud83d\udd25 TinyTorch \ud83d\udd25\")\n",
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" print(\"Build ML Systems from Scratch!\")\n",
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" except NameError:\n",
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" # Handle case when running in notebook where __file__ is not defined\n",
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" try:\n",
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" art_file = Path(os.getcwd()) / \"tinytorch_flame.txt\"\n",
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" if art_file.exists():\n",
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" with open(art_file, 'r') as f:\n",
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" ascii_art = f.read()\n",
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" print(ascii_art)\n",
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" print(\"Tiny\ud83d\udd25Torch\")\n",
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" print(\"Build ML Systems from Scratch!\")\n",
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" else:\n",
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" print(\"\ud83d\udd25 TinyTorch \ud83d\udd25\")\n",
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" print(\"Build ML Systems from Scratch!\")\n",
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" except:\n",
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" print(\"\ud83d\udd25 TinyTorch \ud83d\udd25\")\n",
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" print(\"Build ML Systems from Scratch!\")\n",
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"\n",
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"def add_numbers(a, b):\n",
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" \"\"\"Add two numbers together.\"\"\"\n",
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" return a + b"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"\"\"\"\n",
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"### \ud83e\uddea Test Your Implementation\n",
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"\n",
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"Once you implement the functions above, run this cell to test them:\n",
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"\"\"\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Test the functions in the notebook (will fail until implemented)\n",
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"try:\n",
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" print(\"Testing hello_tinytorch():\")\n",
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" hello_tinytorch()\n",
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" print()\n",
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" print(\"Testing add_numbers():\")\n",
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" print(f\"2 + 3 = {add_numbers(2, 3)}\")\n",
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"except NotImplementedError as e:\n",
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" print(f\"\u26a0\ufe0f {e}\")\n",
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" print(\"Implement the functions above first!\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"\"\"\"\n",
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"## Step 2: A Simple Class\n",
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"\n",
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"Let's create a simple class that will help us understand system information. This is still basic, but shows how to structure classes in TinyTorch.\n",
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"\"\"\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#| export\n",
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"class SystemInfo:\n",
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" \"\"\"\n",
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" Simple system information class.\n",
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" \n",
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" TODO: Implement this class to collect and display system information.\n",
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" \"\"\"\n",
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" \n",
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" def __init__(self):\n",
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" \"\"\"\n",
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" Initialize system information collection.\n",
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" \n",
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" TODO: Collect Python version, platform, and machine information.\n",
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" \"\"\"\n",
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" raise NotImplementedError(\"Student implementation required\")\n",
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" \n",
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" def __str__(self):\n",
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" \"\"\"\n",
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" Return human-readable system information.\n",
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" \n",
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" TODO: Format system info as a readable string.\n",
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" \"\"\"\n",
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" raise NotImplementedError(\"Student implementation required\")\n",
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" \n",
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" def is_compatible(self):\n",
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" \"\"\"\n",
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" Check if system meets minimum requirements.\n",
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" \n",
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" TODO: Check if Python version is >= 3.8\n",
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" \"\"\"\n",
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" raise NotImplementedError(\"Student implementation required\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#| hide\n",
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"#| export\n",
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"class SystemInfo:\n",
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" \"\"\"Simple system information class.\"\"\"\n",
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" \n",
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" def __init__(self):\n",
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" self.python_version = sys.version_info\n",
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" self.platform = platform.system()\n",
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" self.machine = platform.machine()\n",
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" \n",
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" def __str__(self):\n",
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" return f\"Python {self.python_version.major}.{self.python_version.minor} on {self.platform} ({self.machine})\"\n",
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" \n",
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" def is_compatible(self):\n",
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" \"\"\"Check if system meets minimum requirements.\"\"\"\n",
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" return self.python_version >= (3, 8)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"\"\"\"\n",
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"### \ud83e\uddea Test Your SystemInfo Class\n",
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"\n",
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"Once you implement the SystemInfo class above, run this cell to test it:\n",
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"\"\"\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Test the SystemInfo class (will fail until implemented)\n",
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"try:\n",
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" print(\"Testing SystemInfo class:\")\n",
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" info = SystemInfo()\n",
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" print(f\"System: {info}\")\n",
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" print(f\"Compatible: {info.is_compatible()}\")\n",
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"except NotImplementedError as e:\n",
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" print(f\"\u26a0\ufe0f {e}\")\n",
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" print(\"Implement the SystemInfo class above first!\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"\"\"\"\n",
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"## Step 3: Developer Personalization\n",
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"\n",
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"Let's make TinyTorch yours! Create a developer profile that will identify you throughout your ML systems journey.\n",
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"\"\"\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#| export\n",
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"class DeveloperProfile:\n",
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" \"\"\"\n",
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" Developer profile for personalizing TinyTorch experience.\n",
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" \n",
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" TODO: Implement this class to store and display developer information.\n",
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" Default to course instructor but allow students to personalize.\n",
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" \"\"\"\n",
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" \n",
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" @staticmethod\n",
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" def _load_default_flame():\n",
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" \"\"\"\n",
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" Load the default TinyTorch flame ASCII art from file.\n",
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" \n",
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" TODO: Implement file loading for tinytorch_flame.txt with fallback.\n",
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" \"\"\"\n",
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" raise NotImplementedError(\"Student implementation required\")\n",
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" \n",
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" def __init__(self, name=\"Vijay Janapa Reddi\", affiliation=\"Harvard University\", \n",
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" email=\"vj@eecs.harvard.edu\", github_username=\"profvjreddi\", ascii_art=None):\n",
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" \"\"\"\n",
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" Initialize developer profile.\n",
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" \n",
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" TODO: Store developer information with sensible defaults.\n",
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" Students should be able to customize this with their own info and ASCII art.\n",
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" \"\"\"\n",
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" raise NotImplementedError(\"Student implementation required\")\n",
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" \n",
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" def __str__(self):\n",
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" \"\"\"\n",
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" Return formatted developer information.\n",
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" \n",
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" TODO: Format developer info as a professional signature with optional ASCII art.\n",
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" \"\"\"\n",
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" raise NotImplementedError(\"Student implementation required\")\n",
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" \n",
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" def get_signature(self):\n",
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" \"\"\"\n",
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" Get a short signature for code headers.\n",
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" \n",
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" TODO: Return a concise signature like \"Built by Name (@github)\"\n",
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" \"\"\"\n",
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" raise NotImplementedError(\"Student implementation required\")\n",
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" \n",
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" def get_ascii_art(self):\n",
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" \"\"\"\n",
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" Get ASCII art for the profile.\n",
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" \n",
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" TODO: Return custom ASCII art or default flame loaded from file.\n",
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" \"\"\"\n",
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" raise NotImplementedError(\"Student implementation required\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#| hide\n",
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"#| export\n",
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"class DeveloperProfile:\n",
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" \"\"\"Developer profile for personalizing TinyTorch experience.\"\"\"\n",
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" \n",
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" @staticmethod\n",
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" def _load_default_flame():\n",
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" \"\"\"Load the default TinyTorch flame ASCII art from file.\"\"\"\n",
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" try:\n",
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" # Try to load from the same directory as this module\n",
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" try:\n",
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" # Try to get the directory of the current file\n",
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" current_dir = os.path.dirname(__file__)\n",
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" except NameError:\n",
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" # If __file__ is not defined (e.g., in notebook), use current directory\n",
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" current_dir = os.getcwd()\n",
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" \n",
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" flame_path = os.path.join(current_dir, 'tinytorch_flame.txt')\n",
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" \n",
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" with open(flame_path, 'r', encoding='utf-8') as f:\n",
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" flame_art = f.read()\n",
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" \n",
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" # Add the Tiny\ud83d\udd25Torch text below the flame\n",
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" return f\"\"\"{flame_art}\n",
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" \n",
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" Tiny\ud83d\udd25Torch\n",
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" Build ML Systems from Scratch!\n",
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" \"\"\"\n",
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" except (FileNotFoundError, IOError):\n",
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" # Fallback to simple flame if file not found\n",
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" return \"\"\"\n",
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" \ud83d\udd25 TinyTorch Developer \ud83d\udd25\n",
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" . . . . . .\n",
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" . . . . . .\n",
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" . . . . . . .\n",
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" . . . . . . . .\n",
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" . . . . . . . . .\n",
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" . . . . . . . . . .\n",
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" . . . . . . . . . . .\n",
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" . . . . . . . . . . . .\n",
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" . . . . . . . . . . . . .\n",
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". . . . . . . . . . . . . .\n",
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" \\\\ \\\\ \\\\ \\\\ \\\\ \\\\ \\\\ \\\\ \\\\ / / / / / /\n",
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" \\\\ \\\\ \\\\ \\\\ \\\\ \\\\ \\\\ \\\\ / / / / / /\n",
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" \\\\ \\\\ \\\\ \\\\ \\\\ \\\\ \\\\ / / / / / /\n",
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" \\\\ \\\\ \\\\ \\\\ \\\\ \\\\ / / / / / /\n",
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" \\\\ \\\\ \\\\ \\\\ \\\\ / / / / / /\n",
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" \\\\ \\\\ \\\\ \\\\ / / / / / /\n",
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" \\\\ \\\\ \\\\ / / / / / /\n",
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" \\\\ \\\\ / / / / / /\n",
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" \\\\ / / / / / /\n",
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" \\\\/ / / / / /\n",
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" \\\\/ / / / /\n",
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" \\\\/ / / /\n",
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" \\\\/ / /\n",
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" \\\\/ /\n",
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" \\\\/\n",
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" \n",
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" Tiny\ud83d\udd25Torch\n",
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" Build ML Systems from Scratch!\n",
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" \"\"\"\n",
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" \n",
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" def __init__(self, name=\"Vijay Janapa Reddi\", affiliation=\"Harvard University\", \n",
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" email=\"vj@eecs.harvard.edu\", github_username=\"profvjreddi\", ascii_art=None):\n",
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" self.name = name\n",
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" self.affiliation = affiliation\n",
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" self.email = email\n",
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" self.github_username = github_username\n",
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" self.ascii_art = ascii_art or self._load_default_flame()\n",
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" \n",
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" def __str__(self):\n",
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" return f\"\ud83d\udc68\u200d\ud83d\udcbb {self.name} | {self.affiliation} | @{self.github_username}\"\n",
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" \n",
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" def get_signature(self):\n",
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" \"\"\"Get a short signature for code headers.\"\"\"\n",
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" return f\"Built by {self.name} (@{self.github_username})\"\n",
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" \n",
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" def get_ascii_art(self):\n",
|
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" \"\"\"Get ASCII art for the profile.\"\"\"\n",
|
|
" return self.ascii_art\n",
|
|
" \n",
|
|
" def get_full_profile(self):\n",
|
|
" \"\"\"Get complete profile with ASCII art.\"\"\"\n",
|
|
" return f\"\"\"{self.ascii_art}\n",
|
|
" \n",
|
|
"\ud83d\udc68\u200d\ud83d\udcbb Developer: {self.name}\n",
|
|
"\ud83c\udfdb\ufe0f Affiliation: {self.affiliation}\n",
|
|
"\ud83d\udce7 Email: {self.email}\n",
|
|
"\ud83d\udc19 GitHub: @{self.github_username}\n",
|
|
"\ud83d\udd25 Ready to build ML systems from scratch!\n",
|
|
"\"\"\""
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"\"\"\"\n",
|
|
"### \ud83e\uddea Test Your Developer Profile\n",
|
|
"\n",
|
|
"Customize your developer profile! Replace the default information with your own:\n",
|
|
"\"\"\""
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Test the DeveloperProfile class\n",
|
|
"try:\n",
|
|
" print(\"Testing DeveloperProfile (with defaults):\")\n",
|
|
" # Default profile (instructor)\n",
|
|
" default_profile = DeveloperProfile()\n",
|
|
" print(f\"Profile: {default_profile}\")\n",
|
|
" print(f\"Signature: {default_profile.get_signature()}\")\n",
|
|
" print()\n",
|
|
" \n",
|
|
" print(\"\ud83c\udfa8 ASCII Art Preview:\")\n",
|
|
" print(default_profile.get_ascii_art())\n",
|
|
" print()\n",
|
|
" \n",
|
|
" print(\"\ud83d\udd25 Full Profile Display:\")\n",
|
|
" print(default_profile.get_full_profile())\n",
|
|
" print()\n",
|
|
" \n",
|
|
" # TODO: Students should customize this with their own information!\n",
|
|
" print(\"\ud83c\udfaf YOUR TURN: Create your own profile!\")\n",
|
|
" print(\"Uncomment and modify the lines below:\")\n",
|
|
" print(\"# my_profile = DeveloperProfile(\")\n",
|
|
" print(\"# name='Your Name',\")\n",
|
|
" print(\"# affiliation='Your University/Company',\")\n",
|
|
" print(\"# email='your.email@example.com',\")\n",
|
|
" print(\"# github_username='yourgithub',\")\n",
|
|
" print(\"# ascii_art='''\")\n",
|
|
" print(\"# Your Custom ASCII Art Here!\")\n",
|
|
" print(\"# Maybe your initials, a logo, or something fun!\")\n",
|
|
" print(\"# '''\")\n",
|
|
" print(\"# )\")\n",
|
|
" print(\"# print(f'My Profile: {my_profile}')\")\n",
|
|
" print(\"# print(f'My Signature: {my_profile.get_signature()}')\")\n",
|
|
" print(\"# print(my_profile.get_full_profile())\")\n",
|
|
" \n",
|
|
"except NotImplementedError as e:\n",
|
|
" print(f\"\u26a0\ufe0f {e}\")\n",
|
|
" print(\"Implement the DeveloperProfile class above first!\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"\"\"\"\n",
|
|
"### \ud83c\udfa8 Personalization Challenge\n",
|
|
"\n",
|
|
"**For Students**: Make TinyTorch truly yours by:\n",
|
|
"\n",
|
|
"1. **Update your profile** in the cell above with your real information\n",
|
|
"2. **Create custom ASCII art** - your initials, a simple logo, or something that represents you\n",
|
|
"3. **Customize the flame file** - edit `tinytorch_flame.txt` to create your own default art\n",
|
|
"4. **Add your signature** to code you write throughout the course\n",
|
|
"5. **Show off your full profile** with the `get_full_profile()` method\n",
|
|
"\n",
|
|
"This isn't just about customization - it's about taking ownership of your learning journey in ML systems!\n",
|
|
"\n",
|
|
"**ASCII Art Customization Options:**\n",
|
|
"\n",
|
|
"**Option 1: Custom ASCII Art Parameter**\n",
|
|
"```python\n",
|
|
"my_profile = DeveloperProfile(\n",
|
|
" name=\"Your Name\",\n",
|
|
" ascii_art='''\n",
|
|
" Your Custom ASCII Art Here!\n",
|
|
" Maybe your initials, a logo, or something fun!\n",
|
|
" '''\n",
|
|
")\n",
|
|
"```\n",
|
|
"\n",
|
|
"**Option 2: Edit the Default Flame File**\n",
|
|
"- Edit `tinytorch_flame.txt` in this directory\n",
|
|
"- Replace with your own ASCII art design\n",
|
|
"- All students using defaults will see your custom art!\n",
|
|
"\n",
|
|
"**ASCII Art Ideas:**\n",
|
|
"- Your initials in block letters\n",
|
|
"- A simple logo or symbol that represents you\n",
|
|
"- Your university mascot in ASCII\n",
|
|
"- A coding-themed design\n",
|
|
"- Something that motivates you!\n",
|
|
"\n",
|
|
"**Pro Tip**: The `tinytorch_flame.txt` file contains the beautiful default flame art. You can:\n",
|
|
"- Edit it directly for a personalized default\n",
|
|
"- Create your own `.txt` file and modify the code to load it\n",
|
|
"- Use online ASCII art generators for inspiration\n",
|
|
"\"\"\""
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"\"\"\"\n",
|
|
"## Step 4: Try the Export Process\n",
|
|
"\n",
|
|
"Now let's export our code! In your terminal, run:\n",
|
|
"\n",
|
|
"```bash\n",
|
|
"python bin/tito.py sync --module setup\n",
|
|
"```\n",
|
|
"\n",
|
|
"This will export the code marked with `#| export` to `tinytorch/core/utils.py`.\n",
|
|
"\n",
|
|
"**What happens during export:**\n",
|
|
"1. nbdev scans this notebook for `#| export` cells\n",
|
|
"2. Extracts the Python code \n",
|
|
"3. Writes it to `tinytorch/core/utils.py` (because of `#| default_exp core.utils`)\n",
|
|
"4. Handles imports and dependencies automatically\n",
|
|
"\n",
|
|
"**\ud83d\udd0d Verification**: After export, check `tinytorch/core/utils.py` - you'll see your functions there with auto-generated headers pointing back to this notebook!\n",
|
|
"\n",
|
|
"**Note**: The export process will use the instructor solutions (from `#|hide` cells) so the package will have working implementations even if you haven't completed the exercises yet.\n",
|
|
"\"\"\""
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"\"\"\"\n",
|
|
"## Step 5: Run Tests\n",
|
|
"\n",
|
|
"After exporting, run the tests:\n",
|
|
"\n",
|
|
"```bash\n",
|
|
"python bin/tito.py test --module setup\n",
|
|
"```\n",
|
|
"\n",
|
|
"This will run all tests for the setup module and verify your implementation works correctly.\n",
|
|
"\n",
|
|
"## Step 6: Check Your Progress\n",
|
|
"\n",
|
|
"See your overall progress:\n",
|
|
"\n",
|
|
"```bash\n",
|
|
"python bin/tito.py info\n",
|
|
"```\n",
|
|
"\n",
|
|
"This shows which modules are complete and which are pending.\n",
|
|
"\"\"\""
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"\"\"\"\n",
|
|
"## \ud83c\udf89 Congratulations!\n",
|
|
"\n",
|
|
"You've learned the TinyTorch development workflow:\n",
|
|
"\n",
|
|
"1. \u2705 Write code in notebooks with `#| export`\n",
|
|
"2. \u2705 Export with `tito sync --module setup` \n",
|
|
"3. \u2705 Test with `tito test --module setup`\n",
|
|
"4. \u2705 Check progress with `tito info`\n",
|
|
"\n",
|
|
"**This is the rhythm you'll use for every module in TinyTorch.**\n",
|
|
"\n",
|
|
"### Next Steps\n",
|
|
"\n",
|
|
"Ready for the real work? Head to **Module 1: Tensor** where you'll build the core data structures that power everything else in TinyTorch.\n",
|
|
"\n",
|
|
"**Development Tips:**\n",
|
|
"- Always test your code in the notebook first\n",
|
|
"- Export frequently to catch issues early \n",
|
|
"- Read error messages carefully - they're designed to help\n",
|
|
"- When stuck, check if your code exports cleanly first\n",
|
|
"\n",
|
|
"Happy building! \ud83d\udd25\n",
|
|
"\"\"\""
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"name": "python",
|
|
"version": "3.8.0"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
} |