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04cbc65724
Major fixes for complete training pipeline functionality: Core Components Fixed: - Parameter class: Now wraps Variables with requires_grad=True for proper gradient tracking - Variable.sum(): Essential for scalar loss computation from multi-element tensors - Gradient handling: Fixed memoryview issues in autograd and activations - Tensor indexing: Added __getitem__ support for weight inspection Training Results: - XOR learning: 100% accuracy (4/4) - network successfully learns XOR function - Linear regression: Weight=1.991 (target=2.0), Bias=0.980 (target=1.0) - Integration tests: 21/22 passing (95.5% success rate) - Module tests: All individual modules passing - General functionality: 4/5 tests passing with core training working Technical Details: - Fixed gradient data access patterns throughout activations.py - Added safe memoryview handling in Variable.backward() - Implemented proper Parameter-Variable delegation - Added Tensor subscripting for debugging access 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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<h1>🏆 TinyTorch Competitions</h1>
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<ul class="visible nav section-nav flex-column">
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#educational-challenges-not-just-leaderboards">Educational Challenges, Not Just Leaderboards</a><ul class="nav section-nav flex-column">
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#the-educational-vision">The Educational Vision</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#planned-competition-categories">Planned Competition Categories</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#how-competitions-will-work">How Competitions Will Work</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#competition-timeline">Competition Timeline</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#educational-focus-areas">Educational Focus Areas</a></li>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#what-you-can-do-now">What You Can Do Now</a></li>
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<div id="searchbox"></div>
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<article class="bd-article">
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<section id="tinytorch-competitions">
|
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<h1>🏆 TinyTorch Competitions<a class="headerlink" href="#tinytorch-competitions" title="Link to this heading">#</a></h1>
|
||
<section id="educational-challenges-not-just-leaderboards">
|
||
<h2>Educational Challenges, Not Just Leaderboards<a class="headerlink" href="#educational-challenges-not-just-leaderboards" title="Link to this heading">#</a></h2>
|
||
<p>TinyTorch competitions are <strong>planned educational challenges</strong> designed to deepen your understanding of ML systems through hands-on problem solving. These aren’t just about who gets the highest scores—they’re about learning systems engineering principles while building real ML systems.</p>
|
||
<section id="the-educational-vision">
|
||
<h3>The Educational Vision<a class="headerlink" href="#the-educational-vision" title="Link to this heading">#</a></h3>
|
||
<p>We’re designing competitions that teach you to think like an ML systems engineer:</p>
|
||
<ul class="simple">
|
||
<li><p><strong>Efficiency Mastery</strong>: Achieve accuracy targets within strict memory/compute constraints</p></li>
|
||
<li><p><strong>Systems Understanding</strong>: Debug and optimize real bottlenecks in your implementations</p></li>
|
||
<li><p><strong>Innovation Challenges</strong>: Solve problems using creative system design approaches</p></li>
|
||
<li><p><strong>Collaborative Learning</strong>: Learn from others’ approaches while building your own solutions</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="planned-competition-categories">
|
||
<h3>Planned Competition Categories<a class="headerlink" href="#planned-competition-categories" title="Link to this heading">#</a></h3>
|
||
<p><strong>🎯 Accuracy Challenges</strong></p>
|
||
<ul class="simple">
|
||
<li><p><strong>CIFAR-10 Sprint</strong>: First to achieve 75% accuracy using only your TinyTorch implementations</p></li>
|
||
<li><p><strong>Efficient Training</strong>: Highest accuracy achieved within memory limits (256MB, 512MB, 1GB tiers)</p></li>
|
||
<li><p><strong>Small Model Olympics</strong>: Best performance with parameter count restrictions</p></li>
|
||
</ul>
|
||
<p><strong>⚡ Performance Challenges</strong></p>
|
||
<ul class="simple">
|
||
<li><p><strong>Speed Runs</strong>: Fastest training time to reach accuracy milestones</p></li>
|
||
<li><p><strong>Memory Optimization</strong>: Lowest memory usage while maintaining target accuracy</p></li>
|
||
<li><p><strong>Inference Efficiency</strong>: Fastest model inference on standard hardware</p></li>
|
||
</ul>
|
||
<p><strong>🛠️ Systems Mastery Challenges</strong></p>
|
||
<ul class="simple">
|
||
<li><p><strong>Debugging Olympics</strong>: Identify and fix intentionally buggy implementations</p></li>
|
||
<li><p><strong>Scaling Challenges</strong>: Optimize code for larger datasets and models</p></li>
|
||
<li><p><strong>Hardware Awareness</strong>: Best use of CPU vectorization and cache efficiency</p></li>
|
||
</ul>
|
||
<p><strong>💡 Innovation Competitions</strong></p>
|
||
<ul class="simple">
|
||
<li><p><strong>Creative Implementations</strong>: Most elegant solution to standard ML problems</p></li>
|
||
<li><p><strong>Novel Optimizations</strong>: Discover new ways to improve training efficiency</p></li>
|
||
<li><p><strong>Educational Tools</strong>: Build the best learning aids for future TinyTorch students</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="how-competitions-will-work">
|
||
<h3>How Competitions Will Work<a class="headerlink" href="#how-competitions-will-work" title="Link to this heading">#</a></h3>
|
||
<p><strong>Learning-First Design:</strong></p>
|
||
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1"># Future CLI commands (in development)</span>
|
||
tito<span class="w"> </span>compete<span class="w"> </span>list<span class="w"> </span><span class="c1"># See available challenges</span>
|
||
tito<span class="w"> </span>compete<span class="w"> </span>join<span class="w"> </span>accuracy-sprint<span class="w"> </span><span class="c1"># Register for a challenge</span>
|
||
tito<span class="w"> </span>compete<span class="w"> </span>submit<span class="w"> </span>--challenge<span class="o">=</span>cifar10<span class="w"> </span><span class="c1"># Submit your solution</span>
|
||
tito<span class="w"> </span>compete<span class="w"> </span>results<span class="w"> </span>--detailed<span class="w"> </span><span class="c1"># See results with learning insights</span>
|
||
</pre></div>
|
||
</div>
|
||
<p><strong>What Makes These Different:</strong></p>
|
||
<ul class="simple">
|
||
<li><p><strong>Detailed Analysis</strong>: Every submission gets performance profiling and optimization suggestions</p></li>
|
||
<li><p><strong>Learning Resources</strong>: Access to hints, debugging guides, and optimization tutorials</p></li>
|
||
<li><p><strong>Peer Review</strong>: Option to share your approach and learn from others’ solutions</p></li>
|
||
<li><p><strong>Multiple Tiers</strong>: Challenges for beginners (20% accuracy) through experts (90%+)</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="competition-timeline">
|
||
<h3>Competition Timeline<a class="headerlink" href="#competition-timeline" title="Link to this heading">#</a></h3>
|
||
<p><strong>Phase 1: Foundation Building</strong> (Next 2-3 months)</p>
|
||
<ul class="simple">
|
||
<li><p>Community feedback and competition design</p></li>
|
||
<li><p>Initial infrastructure development</p></li>
|
||
<li><p>Beta testing with volunteer participants</p></li>
|
||
</ul>
|
||
<p><strong>Phase 2: Soft Launch</strong> (3-4 months)</p>
|
||
<ul class="simple">
|
||
<li><p>First “CIFAR-10 Efficiency Challenge”</p></li>
|
||
<li><p>Small group of participants (~20-50)</p></li>
|
||
<li><p>Rapid iteration based on feedback</p></li>
|
||
</ul>
|
||
<p><strong>Phase 3: Full Launch</strong> (4-6 months)</p>
|
||
<ul class="simple">
|
||
<li><p>Multiple simultaneous competitions</p></li>
|
||
<li><p>Automated submission and scoring</p></li>
|
||
<li><p>Rich community features and collaboration tools</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="educational-focus-areas">
|
||
<h3>Educational Focus Areas<a class="headerlink" href="#educational-focus-areas" title="Link to this heading">#</a></h3>
|
||
<p><strong>Systems Engineering Skills:</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Memory profiling and optimization techniques</p></li>
|
||
<li><p>Performance bottleneck identification</p></li>
|
||
<li><p>Scaling behavior analysis</p></li>
|
||
<li><p>Cache-efficient algorithm design</p></li>
|
||
</ul>
|
||
<p><strong>Real-World ML Engineering:</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Production-ready code practices</p></li>
|
||
<li><p>Debugging distributed training issues</p></li>
|
||
<li><p>Resource constraint optimization</p></li>
|
||
<li><p>Hardware-aware implementations</p></li>
|
||
</ul>
|
||
<p><strong>Collaborative Problem Solving:</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Code review and peer learning</p></li>
|
||
<li><p>Mentoring between experience levels</p></li>
|
||
<li><p>Team-based challenges for larger projects</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="join-the-design-process">
|
||
<h3>Join the Design Process<a class="headerlink" href="#join-the-design-process" title="Link to this heading">#</a></h3>
|
||
<p><strong>Help Us Build Better Competitions:</strong></p>
|
||
<p>We want your input on what would make these competitions most valuable for learning:</p>
|
||
<ul class="simple">
|
||
<li><p>What systems engineering skills do you want to develop?</p></li>
|
||
<li><p>What types of challenges would motivate you to participate?</p></li>
|
||
<li><p>How can we make competitions inclusive for all skill levels?</p></li>
|
||
<li><p>What would help you learn most from other participants’ approaches?</p></li>
|
||
</ul>
|
||
<p><strong>Current Discussion Topics:</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Competition format and scoring criteria</p></li>
|
||
<li><p>Mentorship and collaboration features</p></li>
|
||
<li><p>Fair resource usage policies</p></li>
|
||
<li><p>Educational content integration</p></li>
|
||
</ul>
|
||
<p><strong>Share Your Ideas:</strong> <a class="reference external" href="https://github.com/harvard-edge/TinyTorch/discussions">GitHub Discussions - Competitions</a></p>
|
||
</section>
|
||
</section>
|
||
<hr class="docutils" />
|
||
<section id="what-you-can-do-now">
|
||
<h2>What You Can Do Now<a class="headerlink" href="#what-you-can-do-now" title="Link to this heading">#</a></h2>
|
||
<p>🚧 <strong>While We Build This Feature</strong></p>
|
||
<p><strong>1. Practice Competition Skills:</strong></p>
|
||
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1"># Use existing tools to prepare</span>
|
||
tito<span class="w"> </span>checkpoint<span class="w"> </span><span class="nb">test</span><span class="w"> </span><span class="m">14</span><span class="w"> </span><span class="c1"># Practice benchmarking skills</span>
|
||
tito<span class="w"> </span>checkpoint<span class="w"> </span><span class="nb">test</span><span class="w"> </span><span class="m">13</span><span class="w"> </span><span class="c1"># Test your kernel optimization knowledge</span>
|
||
tito<span class="w"> </span>module<span class="w"> </span><span class="nb">complete</span><span class="w"> </span>11_training<span class="w"> </span><span class="c1"># Master the training pipeline</span>
|
||
</pre></div>
|
||
</div>
|
||
<p><strong>2. Connect with Future Competitors:</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Find training partners in GitHub Discussions</p></li>
|
||
<li><p>Share your current accuracy achievements</p></li>
|
||
<li><p>Ask for optimization tips and debugging help</p></li>
|
||
<li><p>Form study groups for collaborative learning</p></li>
|
||
</ul>
|
||
<p><strong>3. Build Your Competition Portfolio:</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Track your CIFAR-10 accuracy improvements over time</p></li>
|
||
<li><p>Document your optimization techniques and learnings</p></li>
|
||
<li><p>Practice explaining your system design decisions</p></li>
|
||
<li><p>Build profiling and debugging skills</p></li>
|
||
</ul>
|
||
<p><strong>4. Share Your Training Journey:</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Post milestone achievements (50%, 60%, 70%+ accuracy)</p></li>
|
||
<li><p>Share interesting bugs you’ve debugged</p></li>
|
||
<li><p>Explain optimization techniques you’ve discovered</p></li>
|
||
<li><p>Help others troubleshoot their implementations</p></li>
|
||
</ul>
|
||
<hr class="docutils" />
|
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<div style="background: #e8f4fd; border: 2px solid #1976d2; padding: 2rem; border-radius: 0.5rem; margin: 2rem 0; text-align: center;">
|
||
<h3 style="margin: 0 0 1rem 0; color: #1976d2;">🚀 Early Access Program</h3>
|
||
<p style="margin: 0 0 1rem 0; color: #424242;">Want to be among the first to try TinyTorch competitions?</p>
|
||
<p style="margin: 0 0 1rem 0; color: #424242;"><strong>Join our beta testing group:</strong> We'll notify you when the first challenges are ready for testing</p>
|
||
<a href="https://github.com/harvard-edge/TinyTorch/discussions/new?category=competitions" style="display: inline-block; background: #1976d2; color: white; padding: 0.5rem 1rem; border-radius: 0.25rem; text-decoration: none;">Join Beta Program →</a>
|
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</div>
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</section>
|
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<hr class="docutils" />
|
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<section id="the-bigger-picture">
|
||
<h2>The Bigger Picture<a class="headerlink" href="#the-bigger-picture" title="Link to this heading">#</a></h2>
|
||
<p><strong>Why We’re Building This:</strong></p>
|
||
<p>TinyTorch competitions aren’t about proving who’s the smartest—they’re about creating a community where everyone can push their understanding of ML systems engineering further. Whether you’re aiming for your first 30% accuracy or optimizing for 95%+, these challenges will help you think like a systems engineer.</p>
|
||
<p><strong>Our Promise:</strong></p>
|
||
<ul class="simple">
|
||
<li><p>Educational value always comes first</p></li>
|
||
<li><p>Inclusive design for all skill levels</p></li>
|
||
<li><p>Honest timelines and realistic expectations</p></li>
|
||
<li><p>Community collaboration over individual competition</p></li>
|
||
<li><p>Real learning outcomes, not just leaderboard positions</p></li>
|
||
</ul>
|
||
<p><strong>The ultimate goal:</strong> Help you become the kind of ML engineer who can debug any training issue, optimize any bottleneck, and build systems that scale—skills you’ll use throughout your career.</p>
|
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</section>
|
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</section>
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<div class="footer-item">
|
||
|
||
</div>
|
||
|
||
</div>
|
||
</footer>
|
||
|
||
|
||
</main>
|
||
</div>
|
||
</div>
|
||
|
||
<!-- Scripts loaded after <body> so the DOM is not blocked -->
|
||
<script src="_static/scripts/bootstrap.js?digest=dfe6caa3a7d634c4db9b"></script>
|
||
<script src="_static/scripts/pydata-sphinx-theme.js?digest=dfe6caa3a7d634c4db9b"></script>
|
||
|
||
<footer class="bd-footer">
|
||
</footer>
|
||
</body>
|
||
</html> |