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[WIP] The 'Leaf: Machine Learning for hackers' book This PR is a work in progress. So far I added the 1. Leaf and 2. Layers chapters. Feedback for the overall structure of the book as well as the general ideas and style of the first two chapters are highly welcome. There are probably a lot of typos and grammar mistakes in there. You don't have to bother yet pointing them out, the text might change quickly. REFERENCE: #91
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<!DOCTYPE HTML> | ||
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<ul class="chapter"><li><a href="./leaf.html"><strong>1.</strong> Leaf</a></li><li><a href="./layers.html"><strong>2.</strong> Layers</a></li><li><ul class="section"><li><a href="./layer-lifecycle.html"><strong>2.1.</strong> Layer Lifecycle</a></li><li><a href="./building-networks.html"><strong>2.2.</strong> Create a Network</a></li><li><a href="./create-new-layer.html"><strong>2.3.</strong> Create a new Layer</a></li></ul></li><li><a href="./solvers.html"><strong>3.</strong> Solvers</a></li><li><ul class="section"><li><a href="./optimize-layers.html"><strong>3.1.</strong> Optimize Layers</a></li><li><a href="./multi-device-optimization.html"><strong>3.2.</strong> Multi-Device Optimization</a></li><li><a href="./distributed-optimization.html"><strong>3.3.</strong> Distributed Optimization</a></li></ul></li><li><a href="./backend.html" class="active"><strong>4.</strong> Backend</a></li><li><a href="./deep-learning-glossary.html"><strong>5.</strong> Glossary</a></li><li class="spacer"></li><li><a href="http://autumnai.github.io/leaf/leaf/index.html"><strong>6.</strong> Rust API Documentation</a></li></ul> | ||
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<h1>Backend</h1> | ||
<p>Via the concept of a backend we can abstract over the platform we will execute | ||
or optimize a network on. The construction of a backend is trivial. The backend | ||
is passed to the <code>Solver</code>, (one backend for <code>network</code> and one for the | ||
<code>objectve</code>). The Solver than executes all operations on the provided backend.</p> | ||
<pre><code class="language-rust">let backend = ::std::rc::Rc::new(Backend::<Cuda>::default().unwrap()); | ||
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// set up solver | ||
let mut solver_cfg = SolverConfig { minibatch_size: batch_size, base_lr: learning_rate, momentum: momentum, .. SolverConfig::default() }; | ||
solver_cfg.network = LayerConfig::new("network", net_cfg); | ||
solver_cfg.objective = LayerConfig::new("classifier", classifier_cfg); | ||
let mut solver = Solver::from_config(backend.clone(), backend.clone(), &solver_cfg); | ||
</code></pre> | ||
<p>The backend is a concept of | ||
<a href="https://github.com/autumnai/collenchyma">Collenchyma</a>, to which you can refer | ||
for now, until this chapter becomes more fleshed out.</p> | ||
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