TinyTorch/modules/setup/setup_dev.ipynb

Module 0: Setup - Tiny🔥Torch Development Workflow

Welcome to TinyTorch! This module teaches you the development workflow you'll use throughout the course.

Learning Goals

• Understand the nbdev notebook-to-Python workflow
• Write your first TinyTorch code
• Run tests and use the CLI tools
• Get comfortable with the development rhythm

The TinyTorch Development Cycle

1. Write code in this notebook using #| export
2. Export code with python bin/tito.py sync --module setup
3. Run tests with python bin/tito.py test --module setup
4. Check progress with python bin/tito.py info

Let's get started!

In [1]:

#| default_exp core.utils

# Setup imports and environment
import sys
import platform
from datetime import datetime
import os
from pathlib import Path

print("🔥 TinyTorch Development Environment")
print(f"Python {sys.version}")
print(f"Platform: {platform.system()} {platform.release()}")
print(f"Started: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")

🔥 TinyTorch Development Environment
Python 3.13.3 (v3.13.3:6280bb54784, Apr  8 2025, 10:47:54) [Clang 15.0.0 (clang-1500.3.9.4)]
Platform: Darwin 24.5.0
Started: 2025-07-10 19:28:59

Step 1: Understanding the Module → Package Structure

🎓 Teaching vs. 🔧 Building: This course has two sides:

• Teaching side: You work in modules/setup/setup_dev.ipynb (learning-focused)
• Building side: Your code exports to tinytorch/core/utils.py (production package)

Key Concept: The #| default_exp core.utils directive at the top tells nbdev to export all #| export cells to tinytorch/core/utils.py.

This separation allows us to:

• Organize learning by concepts (modules)
• Organize code by function (package structure)
• Build a real ML framework while learning systematically

Let's write a simple "Hello World" function with the #| export directive:

In [2]:

#| export
def hello_tinytorch():
    """
    A simple hello world function for TinyTorch.
    
    TODO: Implement this function to display TinyTorch ASCII art and welcome message.
    Load the flame art from tinytorch_flame.txt file with graceful fallback.
    """
    raise NotImplementedError("Student implementation required")

def add_numbers(a, b):
    """
    Add two numbers together.
    
    TODO: Implement addition of two numbers.
    This is the foundation of all mathematical operations in ML.
    """
    raise NotImplementedError("Student implementation required")

In [3]:

#| hide
#| export
def hello_tinytorch():
    """Display the TinyTorch ASCII art and welcome message."""
    try:
        # Get the directory containing this file
        current_dir = Path(__file__).parent
        art_file = current_dir / "tinytorch_flame.txt"
        
        if art_file.exists():
            with open(art_file, 'r') as f:
                ascii_art = f.read()
            print(ascii_art)
            print("Tiny🔥Torch")
            print("Build ML Systems from Scratch!")
        else:
            print("🔥 TinyTorch 🔥")
            print("Build ML Systems from Scratch!")
    except NameError:
        # Handle case when running in notebook where __file__ is not defined
        try:
            art_file = Path(os.getcwd()) / "tinytorch_flame.txt"
            if art_file.exists():
                with open(art_file, 'r') as f:
                    ascii_art = f.read()
                print(ascii_art)
                print("Tiny🔥Torch")
                print("Build ML Systems from Scratch!")
            else:
                print("🔥 TinyTorch 🔥")
                print("Build ML Systems from Scratch!")
        except:
            print("🔥 TinyTorch 🔥")
            print("Build ML Systems from Scratch!")

def add_numbers(a, b):
    """Add two numbers together."""
    return a + b

🧪 Test Your Implementation

Once you implement the functions above, run this cell to test them:

In [4]:

# Test the functions in the notebook (will fail until implemented)
try:
    print("Testing hello_tinytorch():")
    hello_tinytorch()
    print()
    print("Testing add_numbers():")
    print(f"2 + 3 = {add_numbers(2, 3)}")
except NotImplementedError as e:
    print(f"⚠️  {e}")
    print("Implement the functions above first!")

Testing hello_tinytorch():
. .    ... .......  ....    ...      .   .   ..  ....   .        ..   .   .     .   . . ....        
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...+++++===========++++++=.   .  .  . .#%%...  -%%+.....=%%+..#%*..+%%-. .*%%-.....#%*..%%+.. ..%%%.
. ..-+++===========+++++..   . ..    ..#%%.    .:%%%###%%%=...#%*...+%%=...+%%####%%#...%%+.. ..%%%.
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 .... . ......:.....  ... . ..    .   ... . .  ... .  . .     ... .  .  . ...      ..   .....   . . 

Tiny🔥Torch
Build ML Systems from Scratch!

Testing add_numbers():
2 + 3 = 5

Step 2: A Simple Class

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.

In [5]:

#| export
class SystemInfo:
    """
    Simple system information class.
    
    TODO: Implement this class to collect and display system information.
    """
    
    def __init__(self):
        """
        Initialize system information collection.
        
        TODO: Collect Python version, platform, and machine information.
        """
        raise NotImplementedError("Student implementation required")
    
    def __str__(self):
        """
        Return human-readable system information.
        
        TODO: Format system info as a readable string.
        """
        raise NotImplementedError("Student implementation required")
    
    def is_compatible(self):
        """
        Check if system meets minimum requirements.
        
        TODO: Check if Python version is >= 3.8
        """
        raise NotImplementedError("Student implementation required")

In [6]:

#| hide
#| export
class SystemInfo:
    """Simple system information class."""
    
    def __init__(self):
        self.python_version = sys.version_info
        self.platform = platform.system()
        self.machine = platform.machine()
    
    def __str__(self):
        return f"Python {self.python_version.major}.{self.python_version.minor} on {self.platform} ({self.machine})"
    
    def is_compatible(self):
        """Check if system meets minimum requirements."""
        return self.python_version >= (3, 8)

🧪 Test Your SystemInfo Class

Once you implement the SystemInfo class above, run this cell to test it:

In [7]:

# Test the SystemInfo class (will fail until implemented)
try:
    print("Testing SystemInfo class:")
    info = SystemInfo()
    print(f"System: {info}")
    print(f"Compatible: {info.is_compatible()}")
except NotImplementedError as e:
    print(f"⚠️  {e}")
    print("Implement the SystemInfo class above first!")

Testing SystemInfo class:
System: Python 3.13 on Darwin (arm64)
Compatible: True

Step 3: Developer Personalization

Let's make TinyTorch yours! Create a developer profile that will identify you throughout your ML systems journey.

In [8]:

#| export
class DeveloperProfile:
    """
    Developer profile for personalizing TinyTorch experience.
    
    TODO: Implement this class to store and display developer information.
    Default to course instructor but allow students to personalize.
    """
    
    @staticmethod
    def _load_default_flame():
        """
        Load the default TinyTorch flame ASCII art from file.
        
        TODO: Implement file loading for tinytorch_flame.txt with fallback.
        """
        raise NotImplementedError("Student implementation required")
    
    def __init__(self, name="Vijay Janapa Reddi", affiliation="Harvard University", 
                 email="vj@eecs.harvard.edu", github_username="profvjreddi", ascii_art=None):
        """
        Initialize developer profile.
        
        TODO: Store developer information with sensible defaults.
        Students should be able to customize this with their own info and ASCII art.
        """
        raise NotImplementedError("Student implementation required")
    
    def __str__(self):
        """
        Return formatted developer information.
        
        TODO: Format developer info as a professional signature with optional ASCII art.
        """
        raise NotImplementedError("Student implementation required")
    
    def get_signature(self):
        """
        Get a short signature for code headers.
        
        TODO: Return a concise signature like "Built by Name (@github)"
        """
        raise NotImplementedError("Student implementation required")
    
    def get_ascii_art(self):
        """
        Get ASCII art for the profile.
        
        TODO: Return custom ASCII art or default flame loaded from file.
        """
        raise NotImplementedError("Student implementation required")

In [9]:

#| hide
#| export
class DeveloperProfile:
    """Developer profile for personalizing TinyTorch experience."""
    
    @staticmethod
    def _load_default_flame():
        """Load the default TinyTorch flame ASCII art from file."""
        try:
            # Try to load from the same directory as this module
            try:
                # Try to get the directory of the current file
                current_dir = os.path.dirname(__file__)
            except NameError:
                # If __file__ is not defined (e.g., in notebook), use current directory
                current_dir = os.getcwd()
            
            flame_path = os.path.join(current_dir, 'tinytorch_flame.txt')
            
            with open(flame_path, 'r', encoding='utf-8') as f:
                flame_art = f.read()
            
            # Add the Tiny🔥Torch text below the flame
            return f"""{flame_art}
                    
                    Tiny🔥Torch
            Build ML Systems from Scratch!
            """
        except (FileNotFoundError, IOError):
            # Fallback to simple flame if file not found
            return """
    🔥 TinyTorch Developer 🔥
         .  .  .  .  .  .
        .    .  .  .  .   .
       .  .    .  .  .  .  .
      .  .  .    .  .  .  .  .
     .  .  .  .    .  .  .  .  .
    .  .  .  .  .    .  .  .  .  .
   .  .  .  .  .  .    .  .  .  .  .
  .  .  .  .  .  .  .    .  .  .  .  .
 .  .  .  .  .  .  .  .    .  .  .  .  .
.  .  .  .  .  .  .  .  .    .  .  .  .  .
 \\  \\  \\  \\  \\  \\  \\  \\  \\  /  /  /  /  /  /
  \\  \\  \\  \\  \\  \\  \\  \\  /  /  /  /  /  /
   \\  \\  \\  \\  \\  \\  \\  /  /  /  /  /  /
    \\  \\  \\  \\  \\  \\  /  /  /  /  /  /
     \\  \\  \\  \\  \\  /  /  /  /  /  /
      \\  \\  \\  \\  /  /  /  /  /  /
       \\  \\  \\  /  /  /  /  /  /
        \\  \\  /  /  /  /  /  /
         \\  /  /  /  /  /  /
          \\/  /  /  /  /  /
           \\/  /  /  /  /
            \\/  /  /  /
             \\/  /  /
              \\/  /
               \\/
                    
                    Tiny🔥Torch
            Build ML Systems from Scratch!
            """
    
    def __init__(self, name="Vijay Janapa Reddi", affiliation="Harvard University", 
                 email="vj@eecs.harvard.edu", github_username="profvjreddi", ascii_art=None):
        self.name = name
        self.affiliation = affiliation
        self.email = email
        self.github_username = github_username
        self.ascii_art = ascii_art or self._load_default_flame()
    
    def __str__(self):
        return f"👨‍💻 {self.name} | {self.affiliation} | @{self.github_username}"
    
    def get_signature(self):
        """Get a short signature for code headers."""
        return f"Built by {self.name} (@{self.github_username})"
    
    def get_ascii_art(self):
        """Get ASCII art for the profile."""
        return self.ascii_art
    
    def get_full_profile(self):
        """Get complete profile with ASCII art."""
        return f"""{self.ascii_art}
        
👨‍💻 Developer: {self.name}
🏛️  Affiliation: {self.affiliation}
📧 Email: {self.email}
🐙 GitHub: @{self.github_username}
🔥 Ready to build ML systems from scratch!
"""

🧪 Test Your Developer Profile

Customize your developer profile! Replace the default information with your own:

In [10]:

# Test the DeveloperProfile class
try:
    print("Testing DeveloperProfile (with defaults):")
    # Default profile (instructor)
    default_profile = DeveloperProfile()
    print(f"Profile: {default_profile}")
    print(f"Signature: {default_profile.get_signature()}")
    print()
    
    print("🎨 ASCII Art Preview:")
    print(default_profile.get_ascii_art())
    print()
    
    print("🔥 Full Profile Display:")
    print(default_profile.get_full_profile())
    print()
    
    # TODO: Students should customize this with their own information!
    print("🎯 YOUR TURN: Create your own profile!")
    print("Uncomment and modify the lines below:")
    print("# my_profile = DeveloperProfile(")
    print("#     name='Your Name',")
    print("#     affiliation='Your University/Company',")
    print("#     email='your.email@example.com',")
    print("#     github_username='yourgithub',")
    print("#     ascii_art='''")
    print("#     Your Custom ASCII Art Here!")
    print("#     Maybe your initials, a logo, or something fun!")
    print("#     '''")
    print("# )")
    print("# print(f'My Profile: {my_profile}')")
    print("# print(f'My Signature: {my_profile.get_signature()}')")
    print("# print(my_profile.get_full_profile())")
    
except NotImplementedError as e:
    print(f"⚠️  {e}")
    print("Implement the DeveloperProfile class above first!")

Testing DeveloperProfile (with defaults):
Profile: 👨‍💻 Vijay Janapa Reddi | Harvard University | @profvjreddi
Signature: Built by Vijay Janapa Reddi (@profvjreddi)

🎨 ASCII Art Preview:
. .    ... .......  ....    ...      .   .   ..  ....   .        ..   .   .     .   . . ....        
.   . ..     .++.     ..           .     . . ..  ...            .     .         .   ..  ...    ..   
 .    .    . .=++=..   .     .   .             ..         . .   ..  .         ...       ..  .   .   
.    ..  ... .++++=.  .      .             .  .             ..                .      ..            .
. . .  . ....-+++++.... ... ..   .        ....  .. . .  . .  .    . .  .       .       .  .      .  
  .   .. ...-++++++-...... ..  .    ..... ..-:..  ..  .      .... ..      . .     ..   . ..   . . . 
 ..  ..  ..++++++++-..       .   . ..##... -%#.          .  .                 .           .      .  
.   ..  .:+++++++++.... ... .    ...:%%:............:-:. ..... ......    . .   .......    ..    . . 
      ..+++++++++++. ...     . .. .=#%%##+.-##..#%####%%=.=%%.  .*%+..   .      .  .          ...   
  . ..++++++++++++...-++.....   .   .%%... -##..##=...=%#..*%*..=%#.. . ..   ... . . .  . ..  .  ...
  ..-+++++++++++++..=++++...    .....%#..  -##..#%-.. -##. .%%=.%%.. .             .  .  .  .  ... .
. .=++++++++++++++-+++++++.... .  ...%%:...-##..#%-. .-%#. ..#%#%=..     .  ..   ...       . .   . .
..=+++++++++++++++++++++++-.  .    ..=%%%+.-%#..##-. .-%#....-%%*..   .         ..  .     .. ..  .. 
.:+++++++++++=+++++++++++++. .      ................  .......-%%...     .          ..   .  .  .. .  
.++++++++++===+++++++++++++: .   .................... . ...%%%#:........ .  .. .....  ......... ....
:+++++++++====+++++++++++++=..  ...-----------.....-+#*=:.....-------:.......:=*#+-.. ..--:.....--=.
:++++++++======++++++++++++=..  ...#%%%%%%%%%#..-#%%###%%#=...#%####%%%=...+%%%###%%#...#%+.. ..#%%.
.+++++++========+++++++++++-       .. .#%%.. ..-%%+.. ..-%%+..#%*.. .*%%..*%%:.  ..#%*..#%+... .#%%.
.=++++++==========+++++++++:  .       .#%%.....#%#....  .*%#..#%*...-%%*..#%+.  ... . ..##%#####%%%.
..++++++===========+++++++-.    .   ...#%%. . .#%#.   . .*%#..#%%%%%%#-. .#%+.  .   ....#%*-----#%%.
...+++++===========++++++=.   .  .  . .#%%...  -%%+.....=%%+..#%*..+%%-. .*%%-.....#%*..%%+.. ..%%%.
. ..-+++===========+++++..   . ..    ..#%%.    .:%%%###%%%=...#%*...+%%=...+%%####%%#...%%+.. ..%%%.
 . ...-++==========+++:....  ...  .   .===.  ... ..-+++=..  ..-=-....-==:  ..:=+++-.. ..==-... .===.
     ....-+=======+-...... .. .  .   ... .  . ..  ...  . . ....   .   . .  . .....   .  ... .....  .
 .... . ......:.....  ... . ..    .   ... . .  ... .  . .     ... .  .  . ...      ..   .....   . . 


                    Tiny🔥Torch
            Build ML Systems from Scratch!
            

🔥 Full Profile Display:
. .    ... .......  ....    ...      .   .   ..  ....   .        ..   .   .     .   . . ....        
.   . ..     .++.     ..           .     . . ..  ...            .     .         .   ..  ...    ..   
 .    .    . .=++=..   .     .   .             ..         . .   ..  .         ...       ..  .   .   
.    ..  ... .++++=.  .      .             .  .             ..                .      ..            .
. . .  . ....-+++++.... ... ..   .        ....  .. . .  . .  .    . .  .       .       .  .      .  
  .   .. ...-++++++-...... ..  .    ..... ..-:..  ..  .      .... ..      . .     ..   . ..   . . . 
 ..  ..  ..++++++++-..       .   . ..##... -%#.          .  .                 .           .      .  
.   ..  .:+++++++++.... ... .    ...:%%:............:-:. ..... ......    . .   .......    ..    . . 
      ..+++++++++++. ...     . .. .=#%%##+.-##..#%####%%=.=%%.  .*%+..   .      .  .          ...   
  . ..++++++++++++...-++.....   .   .%%... -##..##=...=%#..*%*..=%#.. . ..   ... . . .  . ..  .  ...
  ..-+++++++++++++..=++++...    .....%#..  -##..#%-.. -##. .%%=.%%.. .             .  .  .  .  ... .
. .=++++++++++++++-+++++++.... .  ...%%:...-##..#%-. .-%#. ..#%#%=..     .  ..   ...       . .   . .
..=+++++++++++++++++++++++-.  .    ..=%%%+.-%#..##-. .-%#....-%%*..   .         ..  .     .. ..  .. 
.:+++++++++++=+++++++++++++. .      ................  .......-%%...     .          ..   .  .  .. .  
.++++++++++===+++++++++++++: .   .................... . ...%%%#:........ .  .. .....  ......... ....
:+++++++++====+++++++++++++=..  ...-----------.....-+#*=:.....-------:.......:=*#+-.. ..--:.....--=.
:++++++++======++++++++++++=..  ...#%%%%%%%%%#..-#%%###%%#=...#%####%%%=...+%%%###%%#...#%+.. ..#%%.
.+++++++========+++++++++++-       .. .#%%.. ..-%%+.. ..-%%+..#%*.. .*%%..*%%:.  ..#%*..#%+... .#%%.
.=++++++==========+++++++++:  .       .#%%.....#%#....  .*%#..#%*...-%%*..#%+.  ... . ..##%#####%%%.
..++++++===========+++++++-.    .   ...#%%. . .#%#.   . .*%#..#%%%%%%#-. .#%+.  .   ....#%*-----#%%.
...+++++===========++++++=.   .  .  . .#%%...  -%%+.....=%%+..#%*..+%%-. .*%%-.....#%*..%%+.. ..%%%.
. ..-+++===========+++++..   . ..    ..#%%.    .:%%%###%%%=...#%*...+%%=...+%%####%%#...%%+.. ..%%%.
 . ...-++==========+++:....  ...  .   .===.  ... ..-+++=..  ..-=-....-==:  ..:=+++-.. ..==-... .===.
     ....-+=======+-...... .. .  .   ... .  . ..  ...  . . ....   .   . .  . .....   .  ... .....  .
 .... . ......:.....  ... . ..    .   ... . .  ... .  . .     ... .  .  . ...      ..   .....   . . 


                    Tiny🔥Torch
            Build ML Systems from Scratch!
            

👨‍💻 Developer: Vijay Janapa Reddi
🏛️  Affiliation: Harvard University
📧 Email: vj@eecs.harvard.edu
🐙 GitHub: @profvjreddi
🔥 Ready to build ML systems from scratch!


🎯 YOUR TURN: Create your own profile!
Uncomment and modify the lines below:
# my_profile = DeveloperProfile(
#     name='Your Name',
#     affiliation='Your University/Company',
#     email='your.email@example.com',
#     github_username='yourgithub',
#     ascii_art='''
#     Your Custom ASCII Art Here!
#     Maybe your initials, a logo, or something fun!
#     '''
# )
# print(f'My Profile: {my_profile}')
# print(f'My Signature: {my_profile.get_signature()}')
# print(my_profile.get_full_profile())

🎨 Personalization Challenge

For Students: Make TinyTorch truly yours by:

1. Update your profile in the cell above with your real information
2. Create custom ASCII art - your initials, a simple logo, or something that represents you
3. Customize the flame file - edit tinytorch_flame.txt to create your own default art
4. Add your signature to code you write throughout the course
5. Show off your full profile with the get_full_profile() method

This isn't just about customization - it's about taking ownership of your learning journey in ML systems!

ASCII Art Customization Options:

Option 1: Custom ASCII Art Parameter

my_profile = DeveloperProfile(
    name="Your Name",
    ascii_art='''
    Your Custom ASCII Art Here!
    Maybe your initials, a logo, or something fun!
    '''
)

Option 2: Edit the Default Flame File

• Edit tinytorch_flame.txt in this directory
• Replace with your own ASCII art design
• All students using defaults will see your custom art!

ASCII Art Ideas:

• Your initials in block letters
• A simple logo or symbol that represents you
• Your university mascot in ASCII
• A coding-themed design
• Something that motivates you!

Pro Tip: The tinytorch_flame.txt file contains the beautiful default flame art. You can:

• Edit it directly for a personalized default
• Create your own .txt file and modify the code to load it
• Use online ASCII art generators for inspiration

Step 4: Try the Export Process

Now let's export our code! In your terminal, run:

python bin/tito.py sync --module setup

This will export the code marked with #| export to tinytorch/core/utils.py.

What happens during export:

1. nbdev scans this notebook for #| export cells
2. Extracts the Python code
3. Writes it to tinytorch/core/utils.py (because of #| default_exp core.utils)
4. Handles imports and dependencies automatically

🔍 Verification: After export, check tinytorch/core/utils.py - you'll see your functions there with auto-generated headers pointing back to this notebook!

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.

Step 5: Run Tests

After exporting, run the tests:

python bin/tito.py test --module setup

This will run all tests for the setup module and verify your implementation works correctly.

Step 6: Check Your Progress

See your overall progress:

python bin/tito.py info

This shows which modules are complete and which are pending.

🎉 Congratulations!

You've learned the TinyTorch development workflow:

1. ✅ Write code in notebooks with #| export
2. ✅ Export with tito sync --module setup
3. ✅ Test with tito test --module setup
4. ✅ Check progress with tito info

This is the rhythm you'll use for every module in TinyTorch.

Next Steps

Ready for the real work? Head to Module 1: Tensor where you'll build the core data structures that power everything else in TinyTorch.

Development Tips:

• Always test your code in the notebook first
• Export frequently to catch issues early
• Read error messages carefully - they're designed to help
• When stuck, check if your code exports cleanly first

Happy building! 🔥