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Major changes: - Moved TinyGPT from Module 16 to examples/tinygpt (capstone demo) - Fixed Module 10 (optimizers) and Module 11 (training) bugs - All 16 modules now passing tests (100% health) - Added comprehensive testing with 'tito test --comprehensive' - Renamed example files for clarity (train_xor_network.py, etc.) - Created working TinyGPT example structure - Updated documentation to reflect 15 core modules + examples - Added KISS principle and testing framework documentation
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TinyTorch: Build Your Own ML Framework from First Principles
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<i class="fa-solid fa-magnifying-glass fa-lg"></i>
|
||
</button>
|
||
`);
|
||
</script>
|
||
<button class="sidebar-toggle secondary-toggle btn btn-sm" title="Toggle secondary sidebar" data-bs-placement="bottom" data-bs-toggle="tooltip">
|
||
<span class="fa-solid fa-list"></span>
|
||
</button>
|
||
</div></div>
|
||
|
||
</div>
|
||
|
||
</div>
|
||
</div>
|
||
|
||
|
||
|
||
<div id="jb-print-docs-body" class="onlyprint">
|
||
<h1>Serious Development Path</h1>
|
||
<!-- Table of contents -->
|
||
<div id="print-main-content">
|
||
<div id="jb-print-toc">
|
||
|
||
<div>
|
||
<h2> Contents </h2>
|
||
</div>
|
||
<nav aria-label="Page">
|
||
<ul class="visible nav section-nav flex-column">
|
||
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#what-youll-build">What You’ll Build</a></li>
|
||
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#quick-start-5-minutes">Quick Start (5 minutes)</a><ul class="nav section-nav flex-column">
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#step-1-get-the-code">Step 1: Get the Code</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#step-2-setup-environment">Step 2: Setup Environment</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#step-3-start-building">Step 3: Start Building</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#step-4-build-test-export-use">Step 4: Build → Test → Export → Use</a></li>
|
||
</ul>
|
||
</li>
|
||
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#learning-path-progressive-complexity">Learning Path (Progressive Complexity)</a><ul class="nav section-nav flex-column">
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#foundation-weeks-1-2">Foundation (Weeks 1-2)</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#building-blocks-weeks-3-4">🧱 Building Blocks (Weeks 3-4)</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#training-systems-weeks-5-6">Training Systems (Weeks 5-6)</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#production-performance-weeks-7-8">Production & Performance (Weeks 7-8)</a></li>
|
||
</ul>
|
||
</li>
|
||
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#development-workflow">Development Workflow</a><ul class="nav section-nav flex-column">
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-tito-cli-system">The <code class="docutils literal notranslate"><span class="pre">tito</span></code> CLI System</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#quality-assurance">Quality Assurance</a></li>
|
||
</ul>
|
||
</li>
|
||
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#proven-student-outcomes">Proven Student Outcomes</a></li>
|
||
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#why-this-approach-works">Why This Approach Works</a><ul class="nav section-nav flex-column">
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#build-use-understand">Build → Use → Understand</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#real-data-real-systems">Real Data, Real Systems</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#immediate-feedback">Immediate Feedback</a></li>
|
||
</ul>
|
||
</li>
|
||
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#ready-to-start">Ready to Start?</a><ul class="nav section-nav flex-column">
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#choose-your-module">Choose Your Module</a></li>
|
||
<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#get-help">Get Help</a></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</nav>
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
|
||
|
||
<div id="searchbox"></div>
|
||
<article class="bd-article">
|
||
|
||
<section id="serious-development-path">
|
||
<h1>Serious Development Path<a class="headerlink" href="#serious-development-path" title="Link to this heading">#</a></h1>
|
||
<p><strong>Perfect for:</strong> “I want to build this myself” • “This is my class assignment” • “I want to understand ML frameworks deeply”</p>
|
||
<hr class="docutils" />
|
||
<section id="what-youll-build">
|
||
<h2>What You’ll Build<a class="headerlink" href="#what-youll-build" title="Link to this heading">#</a></h2>
|
||
<p>A complete ML framework from scratch, including:</p>
|
||
<ul class="simple">
|
||
<li><p><strong>Your own tensor library</strong> with operations and autograd</p></li>
|
||
<li><p><strong>Neural network components</strong> (layers, activations, optimizers)</p></li>
|
||
<li><p><strong>Training systems</strong> that work on real datasets (CIFAR-10)</p></li>
|
||
<li><p><strong>Production features</strong> (compression, monitoring, benchmarking)</p></li>
|
||
<li><p><strong>Language models</strong> that extend your vision framework to TinyGPT</p></li>
|
||
</ul>
|
||
<p><strong>End result:</strong> A working ML framework that powers both computer vision AND language models.</p>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="quick-start-5-minutes">
|
||
<h2>Quick Start (5 minutes)<a class="headerlink" href="#quick-start-5-minutes" title="Link to this heading">#</a></h2>
|
||
<section id="step-1-get-the-code">
|
||
<h3>Step 1: Get the Code<a class="headerlink" href="#step-1-get-the-code" title="Link to this heading">#</a></h3>
|
||
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>clone<span class="w"> </span>https://github.com/your-org/tinytorch.git
|
||
<span class="nb">cd</span><span class="w"> </span>TinyTorch
|
||
</pre></div>
|
||
</div>
|
||
</section>
|
||
<section id="step-2-setup-environment">
|
||
<h3>Step 2: Setup Environment<a class="headerlink" href="#step-2-setup-environment" title="Link to this heading">#</a></h3>
|
||
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1"># Activate virtual environment </span>
|
||
<span class="nb">source</span><span class="w"> </span>bin/activate-tinytorch.sh
|
||
|
||
<span class="c1"># Install dependencies</span>
|
||
make<span class="w"> </span>install
|
||
|
||
<span class="c1"># Verify everything works</span>
|
||
tito<span class="w"> </span>system<span class="w"> </span>doctor
|
||
</pre></div>
|
||
</div>
|
||
</section>
|
||
<section id="step-3-start-building">
|
||
<h3>Step 3: Start Building<a class="headerlink" href="#step-3-start-building" title="Link to this heading">#</a></h3>
|
||
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1"># Open first assignment</span>
|
||
<span class="nb">cd</span><span class="w"> </span>modules/source/01_setup
|
||
jupyter<span class="w"> </span>lab<span class="w"> </span>setup_dev.py
|
||
</pre></div>
|
||
</div>
|
||
</section>
|
||
<section id="step-4-build-test-export-use">
|
||
<h3>Step 4: Build → Test → Export → Use<a class="headerlink" href="#step-4-build-test-export-use" title="Link to this heading">#</a></h3>
|
||
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1"># After implementing code in the notebook:</span>
|
||
tito<span class="w"> </span><span class="nb">export</span><span class="w"> </span><span class="c1"># Export your code to tinytorch package</span>
|
||
tito<span class="w"> </span><span class="nb">test</span><span class="w"> </span>setup<span class="w"> </span><span class="c1"># Test your implementation</span>
|
||
|
||
<span class="c1"># Now use YOUR own code:</span>
|
||
python<span class="w"> </span>-c<span class="w"> </span><span class="s2">"from tinytorch.core.setup import hello_tinytorch; hello_tinytorch()"</span>
|
||
<span class="c1"># 🔥 TinyTorch! Built by: [Your Name]</span>
|
||
</pre></div>
|
||
</div>
|
||
</section>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="learning-path-progressive-complexity">
|
||
<h2>Learning Path (Progressive Complexity)<a class="headerlink" href="#learning-path-progressive-complexity" title="Link to this heading">#</a></h2>
|
||
<section id="foundation-weeks-1-2">
|
||
<h3>Foundation (Weeks 1-2)<a class="headerlink" href="#foundation-weeks-1-2" title="Link to this heading">#</a></h3>
|
||
<p>Build the core infrastructure:</p>
|
||
<p><strong>Module 01: Setup & CLI</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Professional development workflow with <code class="docutils literal notranslate"><span class="pre">tito</span></code> CLI</p></li>
|
||
<li><p>Understanding package architecture and exports</p></li>
|
||
<li><p>Quality assurance with automated testing</p></li>
|
||
</ul>
|
||
<p><strong>Module 01: Tensors</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Multi-dimensional arrays and operations</p></li>
|
||
<li><p>Memory management and data types</p></li>
|
||
<li><p>Foundation for all ML operations</p></li>
|
||
</ul>
|
||
<p><strong>Module 02: Activations</strong></p>
|
||
<ul class="simple">
|
||
<li><p>ReLU, Sigmoid, Tanh, Softmax functions</p></li>
|
||
<li><p>Understanding nonlinearity in neural networks</p></li>
|
||
<li><p>Mathematical foundations of deep learning</p></li>
|
||
</ul>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="building-blocks-weeks-3-4">
|
||
<h3>🧱 Building Blocks (Weeks 3-4)<a class="headerlink" href="#building-blocks-weeks-3-4" title="Link to this heading">#</a></h3>
|
||
<p>Create neural network components:</p>
|
||
<p><strong>Module 03: Layers</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Dense (linear) layers with matrix multiplication</p></li>
|
||
<li><p>Weight initialization strategies</p></li>
|
||
<li><p>Building blocks that stack together</p></li>
|
||
</ul>
|
||
<p><strong>Module 04: Networks</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Sequential model architecture</p></li>
|
||
<li><p>Composition patterns and forward propagation</p></li>
|
||
<li><p>Creating complete neural networks</p></li>
|
||
</ul>
|
||
<p><strong>Module 05: CNNs</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Convolutional operations for computer vision</p></li>
|
||
<li><p>Understanding spatial processing</p></li>
|
||
<li><p>Building blocks for image classification</p></li>
|
||
</ul>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="training-systems-weeks-5-6">
|
||
<h3>Training Systems (Weeks 5-6)<a class="headerlink" href="#training-systems-weeks-5-6" title="Link to this heading">#</a></h3>
|
||
<p>Complete training infrastructure:</p>
|
||
<p><strong>Module 06: DataLoader</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Efficient data loading and preprocessing</p></li>
|
||
<li><p>Real dataset handling (CIFAR-10)</p></li>
|
||
<li><p>Batching, shuffling, and memory management</p></li>
|
||
</ul>
|
||
<p><strong>Module 07: Autograd</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Automatic differentiation engine</p></li>
|
||
<li><p>Computational graphs and backpropagation</p></li>
|
||
<li><p>The magic that makes training possible</p></li>
|
||
</ul>
|
||
<p><strong>Module 08: Optimizers</strong></p>
|
||
<ul class="simple">
|
||
<li><p>SGD, Adam, and learning rate scheduling</p></li>
|
||
<li><p>Understanding gradient descent variants</p></li>
|
||
<li><p>Convergence and training dynamics</p></li>
|
||
</ul>
|
||
<p><strong>Module 09: Training</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Complete training loops and loss functions</p></li>
|
||
<li><p>Model evaluation and metrics</p></li>
|
||
<li><p>Checkpointing and persistence</p></li>
|
||
</ul>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="production-performance-weeks-7-8">
|
||
<h3>Production & Performance (Weeks 7-8)<a class="headerlink" href="#production-performance-weeks-7-8" title="Link to this heading">#</a></h3>
|
||
<p>Real-world deployment:</p>
|
||
<p><strong>Module 10: Compression</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Model pruning and quantization</p></li>
|
||
<li><p>Reducing model size by 75%+</p></li>
|
||
<li><p>Deployment optimization</p></li>
|
||
</ul>
|
||
<p><strong>Module 11: Kernels</strong></p>
|
||
<ul class="simple">
|
||
<li><p>High-performance custom operations</p></li>
|
||
<li><p>Hardware-aware optimization</p></li>
|
||
<li><p>Understanding framework internals</p></li>
|
||
</ul>
|
||
<p><strong>Module 12: Benchmarking</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Systematic performance measurement</p></li>
|
||
<li><p>Statistical validation and reporting</p></li>
|
||
<li><p>MLPerf-style evaluation</p></li>
|
||
</ul>
|
||
<p><strong>Module 13: MLOps</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Production deployment and monitoring</p></li>
|
||
<li><p>Continuous learning and model updates</p></li>
|
||
<li><p>Complete production pipeline</p></li>
|
||
</ul>
|
||
<p><strong>Module 16: TinyGPT 🔥</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Extend vision framework to language models</p></li>
|
||
<li><p>GPT-style transformers with 95% component reuse</p></li>
|
||
<li><p>Autoregressive text generation</p></li>
|
||
<li><p>Framework generalization mastery</p></li>
|
||
</ul>
|
||
</section>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="development-workflow">
|
||
<h2>Development Workflow<a class="headerlink" href="#development-workflow" title="Link to this heading">#</a></h2>
|
||
<section id="the-tito-cli-system">
|
||
<h3>The <code class="docutils literal notranslate"><span class="pre">tito</span></code> CLI System<a class="headerlink" href="#the-tito-cli-system" title="Link to this heading">#</a></h3>
|
||
<p>TinyTorch includes a complete CLI for professional development:</p>
|
||
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1"># System management</span>
|
||
tito<span class="w"> </span>system<span class="w"> </span>doctor<span class="w"> </span><span class="c1"># Check environment health</span>
|
||
tito<span class="w"> </span>system<span class="w"> </span>info<span class="w"> </span><span class="c1"># Show module status</span>
|
||
|
||
<span class="c1"># Module development </span>
|
||
tito<span class="w"> </span><span class="nb">export</span><span class="w"> </span><span class="c1"># Export dev code to package</span>
|
||
tito<span class="w"> </span><span class="nb">test</span><span class="w"> </span>setup<span class="w"> </span><span class="c1"># Test specific module</span>
|
||
tito<span class="w"> </span><span class="nb">test</span><span class="w"> </span>--all<span class="w"> </span><span class="c1"># Test everything</span>
|
||
|
||
<span class="c1"># NBGrader integration</span>
|
||
tito<span class="w"> </span>nbgrader<span class="w"> </span>generate<span class="w"> </span>setup<span class="w"> </span><span class="c1"># Create assignments</span>
|
||
tito<span class="w"> </span>nbgrader<span class="w"> </span>release<span class="w"> </span>setup<span class="w"> </span><span class="c1"># Release to students</span>
|
||
tito<span class="w"> </span>nbgrader<span class="w"> </span>autograde<span class="w"> </span>setup<span class="w"> </span><span class="c1"># Auto-grade submissions</span>
|
||
</pre></div>
|
||
</div>
|
||
</section>
|
||
<section id="quality-assurance">
|
||
<h3>Quality Assurance<a class="headerlink" href="#quality-assurance" title="Link to this heading">#</a></h3>
|
||
<p>Every module includes comprehensive testing:</p>
|
||
<ul class="simple">
|
||
<li><p><strong>100+ automated tests</strong> ensure correctness</p></li>
|
||
<li><p><strong>Inline tests</strong> provide immediate feedback</p></li>
|
||
<li><p><strong>Integration tests</strong> verify cross-module functionality</p></li>
|
||
<li><p><strong>Performance benchmarks</strong> track optimization</p></li>
|
||
</ul>
|
||
</section>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="proven-student-outcomes">
|
||
<h2>Proven Student Outcomes<a class="headerlink" href="#proven-student-outcomes" title="Link to this heading">#</a></h2>
|
||
<div class="success admonition">
|
||
<p class="admonition-title">Real Results</p>
|
||
<p><strong>After 6-8 weeks, students consistently:</strong></p>
|
||
<p>✅ Build multi-layer perceptrons that classify CIFAR-10 images<br />
|
||
✅ Implement automatic differentiation from scratch<br />
|
||
✅ Create custom optimizers (SGD, Adam) that converge reliably<br />
|
||
✅ Optimize models with pruning and quantization<br />
|
||
✅ Deploy production ML systems with monitoring<br />
|
||
✅ Understand framework internals better than most ML engineers<br />
|
||
🔥 <strong>Extend their vision framework to language models with 95% reuse</strong></p>
|
||
<p><strong>Test Coverage:</strong> 200+ tests across all modules ensure student implementations work</p>
|
||
</div>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="why-this-approach-works">
|
||
<h2>Why This Approach Works<a class="headerlink" href="#why-this-approach-works" title="Link to this heading">#</a></h2>
|
||
<section id="build-use-understand">
|
||
<h3>Build → Use → Understand<a class="headerlink" href="#build-use-understand" title="Link to this heading">#</a></h3>
|
||
<p>Every component follows this pattern:</p>
|
||
<ol class="arabic simple">
|
||
<li><p><strong>🔧 Build</strong>: Implement <code class="docutils literal notranslate"><span class="pre">ReLU()</span></code> from scratch</p></li>
|
||
<li><p><strong>🚀 Use</strong>: <code class="docutils literal notranslate"><span class="pre">from</span> <span class="pre">tinytorch.core.activations</span> <span class="pre">import</span> <span class="pre">ReLU</span></code> - your code!</p></li>
|
||
<li><p><strong>💡 Understand</strong>: See how it enables complex pattern learning</p></li>
|
||
</ol>
|
||
</section>
|
||
<section id="real-data-real-systems">
|
||
<h3>Real Data, Real Systems<a class="headerlink" href="#real-data-real-systems" title="Link to this heading">#</a></h3>
|
||
<ul class="simple">
|
||
<li><p>Work with CIFAR-10 (not toy datasets)</p></li>
|
||
<li><p>Production-style code organization</p></li>
|
||
<li><p>Performance and engineering considerations</p></li>
|
||
<li><p>Professional development practices</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="immediate-feedback">
|
||
<h3>Immediate Feedback<a class="headerlink" href="#immediate-feedback" title="Link to this heading">#</a></h3>
|
||
<ul class="simple">
|
||
<li><p>Code works immediately after implementation</p></li>
|
||
<li><p>Visual progress indicators and success messages</p></li>
|
||
<li><p>Comprehensive error handling and guidance</p></li>
|
||
<li><p>Professional-quality development experience</p></li>
|
||
</ul>
|
||
</section>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="ready-to-start">
|
||
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|
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|
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|
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<p><em>🎉 Ready to build your own ML framework? Your unified vision+language framework is 8 weeks away!</em></p>
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