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| <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>See the <a class="reference external" href="https://mxnet.incubator.apache.org/api/scala/docs/index.html">MXNet Scala API Documentation</a>.</p> |
| <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>You can perform tensor or matrix computation in pure Scala:</p> |
| <div class="highlight-scala"><div class="highlight"><pre><span></span> <span class="n">scala</span><span class="o">></span> <span class="k">import</span> <span class="nn">ml.dmlc.mxnet._</span> |
| <span class="k">import</span> <span class="nn">ml.dmlc.mxnet._</span> |
| |
| <span class="n">scala</span><span class="o">></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="n">arr</span><span class="k">:</span> <span class="kt">ml.dmlc.mxnet.NDArray</span> <span class="o">=</span> <span class="n">ml</span><span class="o">.</span><span class="n">dmlc</span><span class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span class="nc">NDArray</span><span class="nd">@f5e74790</span> |
| |
| <span class="n">scala</span><span class="o">></span> <span class="n">arr</span><span class="o">.</span><span class="n">shape</span> |
| <span class="n">res0</span><span class="k">:</span> <span class="kt">ml.dmlc.mxnet.Shape</span> <span class="o">=</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="n">scala</span><span class="o">></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="n">res2</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Float</span><span class="o">]</span> <span class="k">=</span> <span class="nc">Array</span><span class="o">(</span><span class="mf">2.0</span><span class="o">,</span> <span class="mf">2.0</span><span class="o">,</span> <span class="mf">2.0</span><span class="o">,</span> <span class="mf">2.0</span><span class="o">,</span> <span class="mf">2.0</span><span class="o">,</span> <span class="mf">2.0</span><span class="o">)</span> |
| |
| <span class="n">scala</span><span class="o">></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="n">res3</span><span class="k">:</span> <span class="kt">ml.dmlc.mxnet.Shape</span> <span class="o">=</span> <span class="o">(</span><span class="mi">2</span><span class="o">,</span><span class="mi">3</span><span class="o">)</span> |
| </pre></div> |
| </div> |
| <div class="section" id="scala-api-reference"> |
| <span id="scala-api-reference"></span><h2>Scala API Reference<a class="headerlink" href="#scala-api-reference" title="Permalink to this headline">¶</a></h2> |
| <div class="toctree-wrapper compound"> |
| <ul> |
| <li class="toctree-l1"><a class="reference internal" href="module.html">Module API is a flexible high-level interface for training neural networks.</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="model.html">Model API is an alternate simple high-level interface for training neural networks.</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="symbol.html">Symbolic API performs operations on NDArrays to assemble neural networks from layers.</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="io.html">IO Data Loading API performs parsing and data loading.</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="ndarray.html">NDArray API performs vector/matrix/tensor operations.</a></li> |
| <li class="toctree-l1"><a class="reference internal" href="kvstore.html">KVStore API performs multi-GPU and multi-host distributed training.</a></li> |
| </ul> |
| </div> |
| </div> |
| <div class="section" id="resources"> |
| <span id="resources"></span><h2>Resources<a class="headerlink" href="#resources" title="Permalink to this headline">¶</a></h2> |
| <div class="toctree-wrapper compound"> |
| <ul> |
| <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/api/scala/docs/index.html">MXNet Scala API Documentation</a></li> |
| <li class="toctree-l1"><a class="reference external" href="https://mxnet.incubator.apache.org/tutorials/scala/mnist.html">Handwritten Digit Classification in Scala</a></li> |
| <li class="toctree-l1"><a class="reference external" href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala">Neural Style in Scala on MXNet</a></li> |
| <li class="toctree-l1"><a class="reference external" href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples">More Scala Examples</a></li> |
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| <li><a class="reference internal" href="#">MXNet - Scala API</a><ul> |
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| <p> |
| Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), <strong>sponsored by the <i>Apache Incubator</i></strong>. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF. |
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