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 <!--- under the License. --><div class="section" id="mxnet-scala-api">
 <span id="mxnet-scala-api"></span><h1>MXNet - Scala API<a class="headerlink" href="#mxnet-scala-api" title="Permalink to this headline">¶</a></h1>
 <p>MXNet supports the Scala programming language. The MXNet Scala package brings flexible and efficient GPU
 computing and state-of-art deep learning to Scala. It enables you to write seamless tensor/matrix computation with multiple GPUs in Scala. It also lets you construct and customize the state-of-art deep learning models in Scala, and apply them to tasks, such as image classification and data science challenges.</p>
 <p>See the <a class="reference external" href="/versions/1.5.0/api/scala/docs/index.html#org.apache.mxnet.package">MXNet Scala API Documentation</a> for detailed API information.</p>
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 <li class="toctree-l1"><a class="reference internal" href="infer.html">Infer API</a></li>
 <li class="toctree-l1"><a class="reference internal" href="io.html">MXNet Scala Data Loading API</a></li>
 <li class="toctree-l1"><a class="reference internal" href="kvstore.html">KVStore API</a></li>
 <li class="toctree-l1"><a class="reference internal" href="model.html">MXNet Scala Model API</a></li>
 <li class="toctree-l1"><a class="reference internal" href="module.html">Module API</a></li>
 <li class="toctree-l1"><a class="reference internal" href="ndarray.html">NDArray API</a></li>
 <li class="toctree-l1"><a class="reference internal" href="symbol_in_pictures.html">Symbolic Configuration and Execution in Pictures</a></li>
 <li class="toctree-l1"><a class="reference internal" href="symbol.html">MXNet Scala Symbolic API</a></li>
 </ul>
 </div>
 <div class="section" id="image-classification-with-the-scala-infer-api">
 <span id="image-classification-with-the-scala-infer-api"></span><h2>Image Classification with the Scala Infer API<a class="headerlink" href="#image-classification-with-the-scala-infer-api" title="Permalink to this headline">¶</a></h2>
 <p>The Infer API can be used for single and batch image classification. More information can be found at the following locations:</p>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference external" href="/versions/1.5.0/api/scala/infer.html">Infer API Overview</a></li>
 <li class="toctree-l1"><a class="reference external" href="/versions/1.5.0/api/scala/docs/index.html#org.apache.mxnet.infer.package">Infer API Scaladocs</a></li>
 <li class="toctree-l1"><a class="reference external" href="https://github.com/apache/incubator-mxnet/tree/1.5.0/scala-package/examples/src/main/scala/org/apache/mxnetexamples/infer/objectdetector">Single Shot Detector Inference Example</a></li>
 <li class="toctree-l1"><a class="reference external" href="https://github.com/apache/incubator-mxnet/tree/1.5.0/scala-package/examples/src/main/scala/org/apache/mxnetexamples/infer/imageclassifier">Image Classification Example</a></li>
 </ul>
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 <div class="section" id="tensor-and-matrix-computations">
 <span id="tensor-and-matrix-computations"></span><h2>Tensor and Matrix Computations<a class="headerlink" href="#tensor-and-matrix-computations" title="Permalink to this headline">¶</a></h2>
 <p>You can perform tensor or matrix computation in pure Scala:</p>
 <div class="highlight-scala"><div class="highlight"><pre><span></span>   <span class="k">import</span> <span class="nn">org.apache.mxnet._</span>

    <span class="k">val</span> <span class="n">arr</span> <span class="k">=</span> <span class="nc">NDArray</span><span class="o">.</span><span class="n">ones</span><span class="o">(</span><span class="mi">2</span><span class="o">,</span> <span class="mi">3</span><span class="o">)</span>
    <span class="c1">// arr: org.apache.mxnet.NDArray = org.apache.mxnet.NDArray@f5e74790</span>

    <span class="n">arr</span><span class="o">.</span><span class="n">shape</span>
    <span class="c1">// org.apache.mxnet.Shape = (2,3)</span>

    <span class="o">(</span><span class="n">arr</span> <span class="o">*</span> <span class="mi">2</span><span class="o">).</span><span class="n">toArray</span>
    <span class="c1">// Array[Float] = Array(2.0, 2.0, 2.0, 2.0, 2.0, 2.0)</span>

    <span class="o">(</span><span class="n">arr</span> <span class="o">*</span> <span class="mi">2</span><span class="o">).</span><span class="n">shape</span>
    <span class="c1">// org.apache.mxnet.Shape = (2,3)</span>
 </pre></div>
 </div>
 </div>
 <div class="section" id="scala-api-tutorials">
 <span id="scala-api-tutorials"></span><h2>Scala API Tutorials<a class="headerlink" href="#scala-api-tutorials" title="Permalink to this headline">¶</a></h2>
 <ul class="simple">
 <li><a class="reference external" href="/versions/1.5.0/api/scala/module.html">Module API is a flexible high-level interface for training neural networks.</a></li>
 <li><a class="reference external" href="/versions/1.5.0/api/scala/symbol.html">Symbolic API performs operations on NDArrays to assemble neural networks from layers.</a></li>
 <li><a class="reference external" href="/versions/1.5.0/api/scala/io.html">IO Data Loading API performs parsing and data loading.</a></li>
 <li><a class="reference external" href="/versions/1.5.0/api/scala/ndarray.html">NDArray API performs vector/matrix/tensor operations.</a></li>
 <li><a class="reference external" href="/versions/1.5.0/api/scala/kvstore.html">KVStore API performs multi-GPU and multi-host distributed training.</a></li>
 <li><a class="reference external" href="/versions/1.5.0/api/scala/model.html">Model API is an alternate simple high-level interface for training neural networks.</a> <strong>DEPRECATED</strong></li>
 </ul>
 </div>
 <div class="section" id="related-resources">
 <span id="related-resources"></span><h2>Related Resources<a class="headerlink" href="#related-resources" title="Permalink to this headline">¶</a></h2>
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 <li><a class="reference internal" href="#image-classification-with-the-scala-infer-api">Image Classification with the Scala Infer API</a></li>
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