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| |
| <h1 id="mxnet-clojure-api">MXNet - Clojure API</h1> |
| |
| <p>MXNet supports the Clojure programming language. The MXNet Clojure package brings flexible and efficient GPU |
| computing and state-of-art deep learning to Clojure. It enables you to write seamless tensor/matrix computation with multiple GPUs in Clojure. It also lets you construct and customize the state-of-art deep learning models in Clojure, and apply them to tasks, such as image classification and data science challenges.</p> |
| |
| <h2 id="tensor-and-matrix-computations">Tensor and Matrix Computations</h2> |
| |
| <p>You can perform tensor or matrix computation in pure Clojure:</p> |
| <div class="highlight"><pre><code class="language-clojure" data-lang="clojure"><span class="p">(</span><span class="k">def</span><span class="w"> </span><span class="n">arr</span><span class="w"> </span><span class="p">(</span><span class="nf">ndarray/ones</span><span class="w"> </span><span class="p">[</span><span class="mi">2</span><span class="w"> </span><span class="mi">3</span><span class="p">]))</span><span class="w"> |
| |
| </span><span class="n">arr</span><span class="w"> </span><span class="c1">;=> #object[org.apache.mxnet.NDArray 0x597d72e "org.apache.mxnet.NDArray@e35c3ba9"]</span><span class="w"> |
| |
| </span><span class="p">(</span><span class="nf">ndarray/shape-vec</span><span class="w"> </span><span class="n">arr</span><span class="p">)</span><span class="w"> </span><span class="c1">;=> [2 3]</span><span class="w"> |
| |
| </span><span class="p">(</span><span class="nb">-></span><span class="w"> </span><span class="p">(</span><span class="nf">ndarray/*</span><span class="w"> </span><span class="n">arr</span><span class="w"> </span><span class="mi">2</span><span class="p">)</span><span class="w"> |
| </span><span class="p">(</span><span class="nf">ndarray/->vec</span><span class="p">))</span><span class="w"> </span><span class="c1">;=> [2.0 2.0 2.0 2.0 2.0 2.0]</span><span class="w"> |
| |
| </span><span class="p">(</span><span class="nf">ndarray/shape-vec</span><span class="w"> </span><span class="p">(</span><span class="nf">ndarray/*</span><span class="w"> </span><span class="n">arr</span><span class="w"> </span><span class="mi">2</span><span class="p">))</span><span class="w"> </span><span class="c1">;=> [2 3]</span><span class="w"> |
| |
| </span></code></pre></div> |
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