TinyTorch/modules/setup

🔥 Module 01: Setup & Environment

Welcome to your first TinyTorch module! This setup project gets your development environment ready and introduces you to the workflow you'll use throughout the course.

🎯 Learning Objectives

By the end of this module, you will:

• ✅ Have a fully working development environment
• ✅ Understand the tito CLI workflow
• ✅ Know how to check system status and run tests
• ✅ Have implemented your first TinyTorch component
• ✅ Be ready to build the entire ML system

📋 Module Structure

modules/setup/
├── README.md                    # 📖 This file - Module overview
├── notebook/                    # 📓 Interactive development
│   └── setup_dev.ipynb         # Main development notebook
├── tutorials/                   # 🎓 Step-by-step learning guides
│   └── 01_setup_basics.ipynb   # Setup fundamentals tutorial
├── test_setup.py               # 🧪 Automated tests
├── check_setup.py              # ✅ Manual verification
├── create_env.py               # 🔧 Environment creation
├── QUICKSTART.md               # ⚡ Quick start guide
└── solutions/                  # 🔑 Reference solutions (instructors)
    └── solution_setup.py

🚀 Getting Started

Step 1: Environment Setup

# The only command you need!
source bin/activate-tinytorch.sh

This smart script handles everything:

• 🆕 First time: Creates environment, installs dependencies, activates it
• 💤 Already exists: Just activates the existing environment
• ✅ Already active: Already good to go!

Important: Use source (not ./) to activate in your current shell!

Step 2: System Verification

# Check that everything is working
tito --version
tito info
tito info --show-architecture

Step 3: Read the Tutorial (Recommended)

# Start Jupyter
tito jupyter --lab

# Then open this tutorial:
# tutorials/01_setup_basics.ipynb - Learn the workflow

Step 4: Implement Your First Function

# Open the main development notebook
# Navigate to: notebook/setup_dev.ipynb

# Work through the implementation step by step:
# 1. Environment check
# 2. Import verification
# 3. Function implementation
# 4. Testing and validation

Step 5: Test Your Implementation

# Run automated tests
tito test --module setup

# Run manual verification
python check_setup.py

# Test integration
python -c "from tinytorch.core.utils import hello_tinytorch; print(hello_tinytorch())"

Step 6: Submit Your Work

# Submit when ready
tito submit --module setup

# Move to next module
cd ../tensor/
cat README.md

📚 What You'll Implement

Hello World Function

Your task is to implement a hello_tinytorch() function in tinytorch/core/utils.py:

def hello_tinytorch() -> str:
    """
    Return a greeting message for new TinyTorch users.
    
    Returns:
        A welcoming message string
    """
    return "🔥 Welcome to TinyTorch! Ready to build ML systems from scratch! 🔥"

Requirements

1. Function signature: Must be named hello_tinytorch() with return type -> str
2. Return value: Must return a non-empty string
3. Content: Must contain welcoming content (welcome, hello, tinytorch, ready)
4. Branding: Must include the 🔥 emoji (TinyTorch branding)
5. Documentation: Must have proper docstring explaining the function

🧪 Testing Your Implementation

Automated Tests

tito test --module setup

This runs comprehensive tests for:

• ✅ Function exists and can be imported
• ✅ Returns correct type (string)
• ✅ Returns non-empty content
• ✅ Contains welcoming content
• ✅ Contains 🔥 emoji
• ✅ Has proper documentation

Manual Verification

python check_setup.py

This provides human-readable feedback on:

• 📊 Environment status
• 🔍 Function implementation
• 💡 Specific error messages
• 📋 Next steps guidance

Direct Testing

from tinytorch.core.utils import hello_tinytorch
result = hello_tinytorch()
print(result)

🎯 Success Criteria

Your implementation is complete when:

1. All automated tests pass: tito test --module setup shows ✅
2. Manual verification passes: python check_setup.py shows all tests passed
3. Function works correctly: Returns proper greeting with 🔥 emoji
4. Environment is ready: All CLI commands work properly

📖 Learning Resources

Tutorial Notebooks

• 01_setup_basics.ipynb: Introduction to TinyTorch workflow and development process

Key Concepts to Understand

• Project structure: How modules are organized
• Development workflow: Using notebooks, tests, and CLI
• Testing process: Automated vs manual verification
• Environment management: Virtual environments and dependencies

🔧 Implementation Tips

Start Simple

1. Read the tutorial: Understand the workflow first
2. Check the environment: Make sure everything is working
3. Implement the function: Add it to the correct file
4. Test frequently: Run tests after each change

Common Patterns

• File location: Always add functions to the correct module file
• Import testing: Test imports before implementing
• Error messages: Read error messages carefully for guidance
• Documentation: Always add proper docstrings

Common Pitfalls

• Wrong file: Make sure you're editing tinytorch/core/utils.py
• Syntax errors: Check your Python syntax carefully
• Missing requirements: Ensure your function meets all requirements
• Import issues: Make sure your function can be imported

🚀 Next Steps

Once you complete this module:

1. Move to Tensor module: cd ../tensor/
2. Build core tensors: Implement the fundamental data structure
3. Learn operations: Add arithmetic and utility methods
4. Test thoroughly: Use the comprehensive testing framework

💡 Need Help?

Common Issues

• Environment not working: Run bin/activate-tinytorch.sh
• Import errors: Check file paths and syntax
• Test failures: Read error messages for specific guidance
• CLI not working: Make sure environment is activated

Getting Support

• Check tutorials: The tutorial notebook has detailed explanations
• Run verification: python check_setup.py provides specific feedback
• Review tests: The test files show exactly what's expected

🎉 You're Starting Something Amazing!

This setup module introduces you to the TinyTorch development workflow:

• Environment management: Virtual environments and dependencies
• Testing framework: Automated and manual verification
• CLI workflow: Using tito commands for development
• Project structure: Understanding how modules are organized

This foundation will support everything you build in the coming modules!

Good luck, and happy coding! 🔥