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 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/1-ndarray.html">Step 1: Manipulate data with NP on MXNet</a></li>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/2-nn.html">Step 2: Create a neural network</a></li>
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 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/index.html">NDArray</a><ul>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/01-ndarray-intro.html">An Intro: Manipulate Data the MXNet Way with NDArray</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/02-ndarray-operations.html">NDArray Operations</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/03-ndarray-contexts.html">NDArray Contexts</a></li>
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 <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/sparse/csr.html">CSRNDArray - NDArray in Compressed Sparse Row Storage Format</a></li>
 <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/sparse/row_sparse.html">RowSparseNDArray - NDArray for Sparse Gradient Updates</a></li>
 <li class="toctree-l6"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/sparse/train_gluon.html">Sparse NDArrays with Gluon</a></li>
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 <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/np/index.html">What is NP on MXNet</a><ul>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/np/cheat-sheet.html">The NP on MXNet cheat sheet</a></li>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/np/np-vs-numpy.html">Differences between NP on MXNet and NumPy</a></li>
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 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/onnx/inference_on_onnx_model.html">Running inference on MXNet/Gluon from an ONNX model</a></li>
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 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/index.html">Python Tutorials</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/getting-started/index.html">Getting Started</a><ul>
 <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/index.html">Getting started with NP on MXNet</a><ul>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/1-ndarray.html">Step 1: Manipulate data with NP on MXNet</a></li>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/2-nn.html">Step 2: Create a neural network</a></li>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/3-autograd.html">Step 3: Automatic differentiation with autograd</a></li>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/4-train.html">Step 4: Train the neural network</a></li>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/5-predict.html">Step 5: Predict with a pretrained model</a></li>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/6-use_gpus.html">Step 6: Use GPUs to increase efficiency</a></li>
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 <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/to-mxnet/index.html">Moving to MXNet from Other Frameworks</a><ul>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/to-mxnet/pytorch.html">PyTorch vs Apache MXNet</a></li>
 </ul>
 </li>
 <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/gluon_from_experiment_to_deployment.html">Gluon: from experiment to deployment</a></li>
 <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/logistic_regression_explained.html">Logistic regression explained</a></li>
 <li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/image/mnist.html">MNIST</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="../../../tutorials/packages/index.html">Packages</a><ul>
 <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/autograd/index.html">Automatic Differentiation</a></li>
 <li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/gluon/index.html">Gluon</a><ul>
 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/index.html">Blocks</a><ul>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/custom-layer.html">Custom Layers</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/custom_layer_beginners.html">Customer Layers (Beginners)</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/hybridize.html">Hybridize</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/init.html">Initialization</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/naming.html">Parameter and Block Naming</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/nn.html">Layers and Blocks</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/parameters.html">Parameter Management</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/save_load_params.html">Saving and Loading Gluon Models</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/activations/activations.html">Activation Blocks</a></li>
 </ul>
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 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/data/index.html">Data Tutorials</a><ul>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/data_augmentation.html">Image Augmentation</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/data_augmentation.html#Spatial-Augmentation">Spatial Augmentation</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/data_augmentation.html#Color-Augmentation">Color Augmentation</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/data_augmentation.html#Composed-Augmentations">Composed Augmentations</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html">Gluon <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s and <code class="docutils literal notranslate"><span class="pre">DataLoader</span></code></a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html#Using-own-data-with-included-Datasets">Using own data with included <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html#Using-own-data-with-custom-Datasets">Using own data with custom <code class="docutils literal notranslate"><span class="pre">Dataset</span></code>s</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/data/datasets.html#Appendix:-Upgrading-from-Module-DataIter-to-Gluon-DataLoader">Appendix: Upgrading from Module <code class="docutils literal notranslate"><span class="pre">DataIter</span></code> to Gluon <code class="docutils literal notranslate"><span class="pre">DataLoader</span></code></a></li>
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 <li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/image/index.html">Image Tutorials</a><ul>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/image/info_gan.html">Image similarity search with InfoGAN</a></li>
 <li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/image/mnist.html">Handwritten Digit Recognition</a></li>
 </ul>
 </li>
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   <div class="section" id="mxnet-np-ndarray">
 <h1>mxnet.np.ndarray<a class="headerlink" href="#mxnet-np-ndarray" title="Permalink to this headline">¶</a></h1>
 <dl class="class">
 <dt id="mxnet.np.ndarray">
 <em class="property">class </em><code class="sig-prename descclassname">mxnet.np.</code><code class="sig-name descname">ndarray</code><a class="headerlink" href="#mxnet.np.ndarray" title="Permalink to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">mxnet.ndarray.ndarray.NDArray</span></code></p>
 <p>ndarray(handle, writable=True):</p>
 <p>An array object represents a multidimensional, homogeneous array of fixed-size items.
 An associated data-type object describes the format of each element in the array
 (its byte-order, how many bytes it occupies in memory, whether it is an integer, a
 floating point number, or something else, etc.). Arrays should be constructed using
 <cite>array</cite>, <cite>zeros</cite> or <cite>empty</cite>. Currently, only c-contiguous arrays are supported.</p>
 <p>Arrays should be constructed using <cite>array</cite>, <cite>zeros</cite> or <cite>empty</cite> (refer
 to the See Also section below).  The parameters given here refer to
 a low-level method (<cite>ndarray(…)</cite>) for instantiating an array.</p>
 <p>For more information, refer to the <cite>mxnet.numpy</cite> module and examine the
 methods and attributes of an array.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>handle</strong> (<em>int</em>) – The ndarray handle in backend (C++).</p></li>
 <li><p><strong>writable</strong> (<em>bool</em>) – Indicates whether inplace-assignment is allowed for the array.</p></li>
 </ul>
 </dd>
 </dl>
 <dl class="attribute">
 <dt id="mxnet.np.ndarray.T">
 <code class="sig-name descname">T</code><a class="headerlink" href="#mxnet.np.ndarray.T" title="Permalink to this definition">¶</a></dt>
 <dd><p>Transpose of the array.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type</dt>
 <dd class="field-odd"><p><a class="reference internal" href="#mxnet.np.ndarray" title="mxnet.np.ndarray">ndarray</a></p>
 </dd>
 </dl>
 </dd></dl>

 <dl class="attribute">
 <dt id="mxnet.np.ndarray.dtype">
 <code class="sig-name descname">dtype</code><a class="headerlink" href="#mxnet.np.ndarray.dtype" title="Permalink to this definition">¶</a></dt>
 <dd><p>Describes the format of the elements in the array.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type</dt>
 <dd class="field-odd"><p>dtype object</p>
 </dd>
 </dl>
 </dd></dl>

 <dl class="attribute">
 <dt id="mxnet.np.ndarray.size">
 <code class="sig-name descname">size</code><a class="headerlink" href="#mxnet.np.ndarray.size" title="Permalink to this definition">¶</a></dt>
 <dd><p>Number of elements in the array.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type</dt>
 <dd class="field-odd"><p>int</p>
 </dd>
 </dl>
 </dd></dl>

 <dl class="attribute">
 <dt id="mxnet.np.ndarray.ndim">
 <code class="sig-name descname">ndim</code><a class="headerlink" href="#mxnet.np.ndarray.ndim" title="Permalink to this definition">¶</a></dt>
 <dd><p>The array’s number of dimensions.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type</dt>
 <dd class="field-odd"><p>int</p>
 </dd>
 </dl>
 </dd></dl>

 <dl class="attribute">
 <dt id="mxnet.np.ndarray.shape">
 <code class="sig-name descname">shape</code><a class="headerlink" href="#mxnet.np.ndarray.shape" title="Permalink to this definition">¶</a></dt>
 <dd><p>Shape of the array.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Type</dt>
 <dd class="field-odd"><p>tuple of ints</p>
 </dd>
 </dl>
 </dd></dl>

 <div class="admonition seealso">
 <p class="admonition-title">See also</p>
 <dl class="simple">
 <dt><a class="reference internal" href="mxnet.np.array.html#mxnet.np.array" title="mxnet.np.array"><code class="xref py py-class docutils literal notranslate"><span class="pre">array</span></code></a></dt><dd><p>Construct an array.</p>
 </dd>
 <dt><a class="reference internal" href="mxnet.np.zeros.html#mxnet.np.zeros" title="mxnet.np.zeros"><code class="xref py py-class docutils literal notranslate"><span class="pre">zeros</span></code></a></dt><dd><p>Create an array, each element of which is zero.</p>
 </dd>
 <dt><a class="reference internal" href="mxnet.np.empty.html#mxnet.np.empty" title="mxnet.np.empty"><code class="xref py py-class docutils literal notranslate"><span class="pre">empty</span></code></a></dt><dd><p>Create an array, but leave its allocated memory unchanged (i.e., it contains “garbage”).</p>
 </dd>
 </dl>
 </div>
 <dl class="method">
 <dt id="mxnet.np.ndarray.__init__">
 <code class="sig-name descname">__init__</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.__init__" title="Permalink to this definition">¶</a></dt>
 <dd><p>Initialize self.  See help(type(self)) for accurate signature.</p>
 </dd></dl>

 <p class="rubric">Methods</p>
 <table class="longtable docutils align-default">
 <colgroup>
 <col style="width: 10%" />
 <col style="width: 90%" />
 </colgroup>
 <tbody>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.__init__" title="mxnet.np.ndarray.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a></p></td>
 <td><p>Initialize self.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.abs" title="mxnet.np.ndarray.abs"><code class="xref py py-obj docutils literal notranslate"><span class="pre">abs</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.abs" title="mxnet.np.ndarray.abs"><code class="xref py py-func docutils literal notranslate"><span class="pre">abs()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="mxnet.np.ndarray.all.html#mxnet.np.ndarray.all" title="mxnet.np.ndarray.all"><code class="xref py py-obj docutils literal notranslate"><span class="pre">all</span></code></a>([axis, out, keepdims])</p></td>
 <td><p></p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="mxnet.np.ndarray.any.html#mxnet.np.ndarray.any" title="mxnet.np.ndarray.any"><code class="xref py py-obj docutils literal notranslate"><span class="pre">any</span></code></a>([axis, out, keepdims])</p></td>
 <td><p></p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.arccos" title="mxnet.np.ndarray.arccos"><code class="xref py py-obj docutils literal notranslate"><span class="pre">arccos</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arccos.html#mxnet.np.arccos" title="mxnet.np.arccos"><code class="xref py py-func docutils literal notranslate"><span class="pre">arccos()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.arccosh" title="mxnet.np.ndarray.arccosh"><code class="xref py py-obj docutils literal notranslate"><span class="pre">arccosh</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arccosh.html#mxnet.np.arccosh" title="mxnet.np.arccosh"><code class="xref py py-func docutils literal notranslate"><span class="pre">arccosh()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.arcsin" title="mxnet.np.ndarray.arcsin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">arcsin</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arcsin.html#mxnet.np.arcsin" title="mxnet.np.arcsin"><code class="xref py py-func docutils literal notranslate"><span class="pre">arcsin()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.arcsinh" title="mxnet.np.ndarray.arcsinh"><code class="xref py py-obj docutils literal notranslate"><span class="pre">arcsinh</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arcsinh.html#mxnet.np.arcsinh" title="mxnet.np.arcsinh"><code class="xref py py-func docutils literal notranslate"><span class="pre">arcsinh()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.arctan" title="mxnet.np.ndarray.arctan"><code class="xref py py-obj docutils literal notranslate"><span class="pre">arctan</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arctan.html#mxnet.np.arctan" title="mxnet.np.arctan"><code class="xref py py-func docutils literal notranslate"><span class="pre">arctan()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.arctanh" title="mxnet.np.ndarray.arctanh"><code class="xref py py-obj docutils literal notranslate"><span class="pre">arctanh</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arctanh.html#mxnet.np.arctanh" title="mxnet.np.arctanh"><code class="xref py py-func docutils literal notranslate"><span class="pre">arctanh()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.argmax" title="mxnet.np.ndarray.argmax"><code class="xref py py-obj docutils literal notranslate"><span class="pre">argmax</span></code></a>([axis, out])</p></td>
 <td><p>Return indices of the maximum values along the given axis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.argmax_channel" title="mxnet.np.ndarray.argmax_channel"><code class="xref py py-obj docutils literal notranslate"><span class="pre">argmax_channel</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.argmax_channel" title="mxnet.np.ndarray.argmax_channel"><code class="xref py py-func docutils literal notranslate"><span class="pre">argmax_channel()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.argmin" title="mxnet.np.ndarray.argmin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">argmin</span></code></a>([axis, out])</p></td>
 <td><p>Return indices of the minium values along the given axis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.argsort" title="mxnet.np.ndarray.argsort"><code class="xref py py-obj docutils literal notranslate"><span class="pre">argsort</span></code></a>([axis, kind, order])</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.argsort.html#mxnet.np.argsort" title="mxnet.np.argsort"><code class="xref py py-func docutils literal notranslate"><span class="pre">argsort()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.as_in_context" title="mxnet.np.ndarray.as_in_context"><code class="xref py py-obj docutils literal notranslate"><span class="pre">as_in_context</span></code></a>(context)</p></td>
 <td><p>This function has been deprecated.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.as_in_ctx" title="mxnet.np.ndarray.as_in_ctx"><code class="xref py py-obj docutils literal notranslate"><span class="pre">as_in_ctx</span></code></a>(ctx)</p></td>
 <td><p>Returns an array on the target device with the same value as this array.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.as_nd_ndarray" title="mxnet.np.ndarray.as_nd_ndarray"><code class="xref py py-obj docutils literal notranslate"><span class="pre">as_nd_ndarray</span></code></a>()</p></td>
 <td><p>Convert mxnet.numpy.ndarray to mxnet.ndarray.NDArray to use its fluent methods.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.as_np_ndarray" title="mxnet.np.ndarray.as_np_ndarray"><code class="xref py py-obj docutils literal notranslate"><span class="pre">as_np_ndarray</span></code></a>()</p></td>
 <td><p>A convenience function for creating a numpy ndarray from the current ndarray with zero copy.</p></td>
 </tr>
 <tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">asnumpy</span></code>()</p></td>
 <td><p>Returns a <code class="docutils literal notranslate"><span class="pre">numpy.ndarray</span></code> object with value copied from this array.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.asscalar" title="mxnet.np.ndarray.asscalar"><code class="xref py py-obj docutils literal notranslate"><span class="pre">asscalar</span></code></a>()</p></td>
 <td><p>Returns a scalar whose value is copied from this array.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.astype" title="mxnet.np.ndarray.astype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">astype</span></code></a>(dtype[, order, casting, subok, copy])</p></td>
 <td><p>Copy of the array, cast to a specified type.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.attach_grad" title="mxnet.np.ndarray.attach_grad"><code class="xref py py-obj docutils literal notranslate"><span class="pre">attach_grad</span></code></a>([grad_req])</p></td>
 <td><p>Attach a gradient buffer to this ndarray, so that <cite>backward</cite> can compute gradient with respect to it.</p></td>
 </tr>
 <tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">backward</span></code>([out_grad, retain_graph, train_mode])</p></td>
 <td><p>Compute the gradients of this NDArray w.r.t variables.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.broadcast_axes" title="mxnet.np.ndarray.broadcast_axes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">broadcast_axes</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.broadcast_axes" title="mxnet.np.ndarray.broadcast_axes"><code class="xref py py-func docutils literal notranslate"><span class="pre">broadcast_axes()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.broadcast_like" title="mxnet.np.ndarray.broadcast_like"><code class="xref py py-obj docutils literal notranslate"><span class="pre">broadcast_like</span></code></a>(other)</p></td>
 <td><p>Broadcasts the input array to the shape of other.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.broadcast_to" title="mxnet.np.ndarray.broadcast_to"><code class="xref py py-obj docutils literal notranslate"><span class="pre">broadcast_to</span></code></a>(shape)</p></td>
 <td><p>Broadcasts the input array to a new shape.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.cbrt" title="mxnet.np.ndarray.cbrt"><code class="xref py py-obj docutils literal notranslate"><span class="pre">cbrt</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.cbrt.html#mxnet.np.cbrt" title="mxnet.np.cbrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">cbrt()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.ceil" title="mxnet.np.ndarray.ceil"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ceil</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.ceil.html#mxnet.np.ceil" title="mxnet.np.ceil"><code class="xref py py-func docutils literal notranslate"><span class="pre">ceil()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.clip" title="mxnet.np.ndarray.clip"><code class="xref py py-obj docutils literal notranslate"><span class="pre">clip</span></code></a>([min, max, out])</p></td>
 <td><p>Return an array whose values are limited to [min, max].</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.copy" title="mxnet.np.ndarray.copy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">copy</span></code></a>([order])</p></td>
 <td><p>Return a coyp of the array, keeping the same context.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.copyto" title="mxnet.np.ndarray.copyto"><code class="xref py py-obj docutils literal notranslate"><span class="pre">copyto</span></code></a>(other)</p></td>
 <td><p>Copies the value of this array to another array.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.cos" title="mxnet.np.ndarray.cos"><code class="xref py py-obj docutils literal notranslate"><span class="pre">cos</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.cos.html#mxnet.np.cos" title="mxnet.np.cos"><code class="xref py py-func docutils literal notranslate"><span class="pre">cos()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.cosh" title="mxnet.np.ndarray.cosh"><code class="xref py py-obj docutils literal notranslate"><span class="pre">cosh</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.cosh.html#mxnet.np.cosh" title="mxnet.np.cosh"><code class="xref py py-func docutils literal notranslate"><span class="pre">cosh()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.cumsum" title="mxnet.np.ndarray.cumsum"><code class="xref py py-obj docutils literal notranslate"><span class="pre">cumsum</span></code></a>([axis, dtype, out])</p></td>
 <td><p>Return the cumulative sum of the elements along the given axis.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.degrees" title="mxnet.np.ndarray.degrees"><code class="xref py py-obj docutils literal notranslate"><span class="pre">degrees</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.degrees.html#mxnet.np.degrees" title="mxnet.np.degrees"><code class="xref py py-func docutils literal notranslate"><span class="pre">degrees()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.depth_to_space" title="mxnet.np.ndarray.depth_to_space"><code class="xref py py-obj docutils literal notranslate"><span class="pre">depth_to_space</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.depth_to_space" title="mxnet.np.ndarray.depth_to_space"><code class="xref py py-func docutils literal notranslate"><span class="pre">depth_to_space()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.detach" title="mxnet.np.ndarray.detach"><code class="xref py py-obj docutils literal notranslate"><span class="pre">detach</span></code></a>()</p></td>
 <td><p>Returns a new ndarray, detached from the current graph.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.diag" title="mxnet.np.ndarray.diag"><code class="xref py py-obj docutils literal notranslate"><span class="pre">diag</span></code></a>([k])</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.diag" title="mxnet.np.ndarray.diag"><code class="xref py py-func docutils literal notranslate"><span class="pre">diag()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.dot" title="mxnet.np.ndarray.dot"><code class="xref py py-obj docutils literal notranslate"><span class="pre">dot</span></code></a>(b[, out])</p></td>
 <td><p>Dot product of two arrays.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.exp" title="mxnet.np.ndarray.exp"><code class="xref py py-obj docutils literal notranslate"><span class="pre">exp</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.exp.html#mxnet.np.exp" title="mxnet.np.exp"><code class="xref py py-func docutils literal notranslate"><span class="pre">exp()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.expand_dims" title="mxnet.np.ndarray.expand_dims"><code class="xref py py-obj docutils literal notranslate"><span class="pre">expand_dims</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.expand_dims.html#mxnet.np.expand_dims" title="mxnet.np.expand_dims"><code class="xref py py-func docutils literal notranslate"><span class="pre">expand_dims()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.expm1" title="mxnet.np.ndarray.expm1"><code class="xref py py-obj docutils literal notranslate"><span class="pre">expm1</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.expm1.html#mxnet.np.expm1" title="mxnet.np.expm1"><code class="xref py py-func docutils literal notranslate"><span class="pre">expm1()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.fix" title="mxnet.np.ndarray.fix"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fix</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.fix.html#mxnet.np.fix" title="mxnet.np.fix"><code class="xref py py-func docutils literal notranslate"><span class="pre">fix()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.flatten" title="mxnet.np.ndarray.flatten"><code class="xref py py-obj docutils literal notranslate"><span class="pre">flatten</span></code></a>([order])</p></td>
 <td><p>Return a copy of the array collapsed into one dimension.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.flip" title="mxnet.np.ndarray.flip"><code class="xref py py-obj docutils literal notranslate"><span class="pre">flip</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.flip.html#mxnet.np.flip" title="mxnet.np.flip"><code class="xref py py-func docutils literal notranslate"><span class="pre">flip()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.floor" title="mxnet.np.ndarray.floor"><code class="xref py py-obj docutils literal notranslate"><span class="pre">floor</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.floor.html#mxnet.np.floor" title="mxnet.np.floor"><code class="xref py py-func docutils literal notranslate"><span class="pre">floor()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.item" title="mxnet.np.ndarray.item"><code class="xref py py-obj docutils literal notranslate"><span class="pre">item</span></code></a>(*args)</p></td>
 <td><p>Copy an element of an array to a standard Python scalar and return it.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.log" title="mxnet.np.ndarray.log"><code class="xref py py-obj docutils literal notranslate"><span class="pre">log</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.log.html#mxnet.np.log" title="mxnet.np.log"><code class="xref py py-func docutils literal notranslate"><span class="pre">log()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.log10" title="mxnet.np.ndarray.log10"><code class="xref py py-obj docutils literal notranslate"><span class="pre">log10</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.log10.html#mxnet.np.log10" title="mxnet.np.log10"><code class="xref py py-func docutils literal notranslate"><span class="pre">log10()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.log1p" title="mxnet.np.ndarray.log1p"><code class="xref py py-obj docutils literal notranslate"><span class="pre">log1p</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.log1p.html#mxnet.np.log1p" title="mxnet.np.log1p"><code class="xref py py-func docutils literal notranslate"><span class="pre">log1p()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.log2" title="mxnet.np.ndarray.log2"><code class="xref py py-obj docutils literal notranslate"><span class="pre">log2</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.log2.html#mxnet.np.log2" title="mxnet.np.log2"><code class="xref py py-func docutils literal notranslate"><span class="pre">log2()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.log_softmax" title="mxnet.np.ndarray.log_softmax"><code class="xref py py-obj docutils literal notranslate"><span class="pre">log_softmax</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.log_softmax" title="mxnet.np.ndarray.log_softmax"><code class="xref py py-func docutils literal notranslate"><span class="pre">log_softmax()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.max" title="mxnet.np.ndarray.max"><code class="xref py py-obj docutils literal notranslate"><span class="pre">max</span></code></a>([axis, out, keepdims])</p></td>
 <td><p>Return the maximum along a given axis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.mean" title="mxnet.np.ndarray.mean"><code class="xref py py-obj docutils literal notranslate"><span class="pre">mean</span></code></a>([axis, dtype, out, keepdims])</p></td>
 <td><p>Returns the average of the array elements along given axis.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.min" title="mxnet.np.ndarray.min"><code class="xref py py-obj docutils literal notranslate"><span class="pre">min</span></code></a>([axis, out, keepdims])</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.min.html#mxnet.np.min" title="mxnet.np.min"><code class="xref py py-func docutils literal notranslate"><span class="pre">min()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.nanprod" title="mxnet.np.ndarray.nanprod"><code class="xref py py-obj docutils literal notranslate"><span class="pre">nanprod</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.nanprod.html#mxnet.np.nanprod" title="mxnet.np.nanprod"><code class="xref py py-func docutils literal notranslate"><span class="pre">nanprod()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.nansum" title="mxnet.np.ndarray.nansum"><code class="xref py py-obj docutils literal notranslate"><span class="pre">nansum</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.nansum" title="mxnet.np.ndarray.nansum"><code class="xref py py-func docutils literal notranslate"><span class="pre">nansum()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.nonzero" title="mxnet.np.ndarray.nonzero"><code class="xref py py-obj docutils literal notranslate"><span class="pre">nonzero</span></code></a>()</p></td>
 <td><p>Return the indices of the elements that are non-zero.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.norm" title="mxnet.np.ndarray.norm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">norm</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.norm" title="mxnet.np.ndarray.norm"><code class="xref py py-func docutils literal notranslate"><span class="pre">norm()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.one_hot" title="mxnet.np.ndarray.one_hot"><code class="xref py py-obj docutils literal notranslate"><span class="pre">one_hot</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.one_hot" title="mxnet.np.ndarray.one_hot"><code class="xref py py-func docutils literal notranslate"><span class="pre">one_hot()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.ones_like" title="mxnet.np.ndarray.ones_like"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ones_like</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.ones_like.html#mxnet.np.ones_like" title="mxnet.np.ones_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">ones_like()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.pad" title="mxnet.np.ndarray.pad"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pad</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.pad" title="mxnet.np.ndarray.pad"><code class="xref py py-func docutils literal notranslate"><span class="pre">pad()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.pick" title="mxnet.np.ndarray.pick"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pick</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.pick" title="mxnet.np.ndarray.pick"><code class="xref py py-func docutils literal notranslate"><span class="pre">pick()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.prod" title="mxnet.np.ndarray.prod"><code class="xref py py-obj docutils literal notranslate"><span class="pre">prod</span></code></a>([axis, dtype, out, keepdims])</p></td>
 <td><p>Return the product of the array elements over the given axis.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.radians" title="mxnet.np.ndarray.radians"><code class="xref py py-obj docutils literal notranslate"><span class="pre">radians</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.radians.html#mxnet.np.radians" title="mxnet.np.radians"><code class="xref py py-func docutils literal notranslate"><span class="pre">radians()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.rcbrt" title="mxnet.np.ndarray.rcbrt"><code class="xref py py-obj docutils literal notranslate"><span class="pre">rcbrt</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.rcbrt" title="mxnet.np.ndarray.rcbrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">rcbrt()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.reciprocal" title="mxnet.np.ndarray.reciprocal"><code class="xref py py-obj docutils literal notranslate"><span class="pre">reciprocal</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.reciprocal.html#mxnet.np.reciprocal" title="mxnet.np.reciprocal"><code class="xref py py-func docutils literal notranslate"><span class="pre">reciprocal()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.relu" title="mxnet.np.ndarray.relu"><code class="xref py py-obj docutils literal notranslate"><span class="pre">relu</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.relu" title="mxnet.np.ndarray.relu"><code class="xref py py-func docutils literal notranslate"><span class="pre">relu()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.repeat" title="mxnet.np.ndarray.repeat"><code class="xref py py-obj docutils literal notranslate"><span class="pre">repeat</span></code></a>(repeats[, axis])</p></td>
 <td><p>Repeat elements of an array.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.reshape" title="mxnet.np.ndarray.reshape"><code class="xref py py-obj docutils literal notranslate"><span class="pre">reshape</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Returns a copy of the array with a new shape.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.reshape_like" title="mxnet.np.ndarray.reshape_like"><code class="xref py py-obj docutils literal notranslate"><span class="pre">reshape_like</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.reshape_like" title="mxnet.np.ndarray.reshape_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">reshape_like()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.reshape_view" title="mxnet.np.ndarray.reshape_view"><code class="xref py py-obj docutils literal notranslate"><span class="pre">reshape_view</span></code></a>(*shape, **kwargs)</p></td>
 <td><p>Returns a <strong>view</strong> of this array with a new shape without altering any data.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.rint" title="mxnet.np.ndarray.rint"><code class="xref py py-obj docutils literal notranslate"><span class="pre">rint</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.rint.html#mxnet.np.rint" title="mxnet.np.rint"><code class="xref py py-func docutils literal notranslate"><span class="pre">rint()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.round" title="mxnet.np.ndarray.round"><code class="xref py py-obj docutils literal notranslate"><span class="pre">round</span></code></a>([decimals, out])</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.round" title="mxnet.np.ndarray.round"><code class="xref py py-func docutils literal notranslate"><span class="pre">round()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.rsqrt" title="mxnet.np.ndarray.rsqrt"><code class="xref py py-obj docutils literal notranslate"><span class="pre">rsqrt</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.rsqrt" title="mxnet.np.ndarray.rsqrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">rsqrt()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.shape_array" title="mxnet.np.ndarray.shape_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">shape_array</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.shape_array" title="mxnet.np.ndarray.shape_array"><code class="xref py py-func docutils literal notranslate"><span class="pre">shape_array()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.sigmoid" title="mxnet.np.ndarray.sigmoid"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sigmoid</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.sigmoid" title="mxnet.np.ndarray.sigmoid"><code class="xref py py-func docutils literal notranslate"><span class="pre">sigmoid()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.sign" title="mxnet.np.ndarray.sign"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sign</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.sign.html#mxnet.np.sign" title="mxnet.np.sign"><code class="xref py py-func docutils literal notranslate"><span class="pre">sign()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.sin" title="mxnet.np.ndarray.sin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sin</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.sin.html#mxnet.np.sin" title="mxnet.np.sin"><code class="xref py py-func docutils literal notranslate"><span class="pre">sin()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.sinh" title="mxnet.np.ndarray.sinh"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sinh</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.sinh.html#mxnet.np.sinh" title="mxnet.np.sinh"><code class="xref py py-func docutils literal notranslate"><span class="pre">sinh()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.size_array" title="mxnet.np.ndarray.size_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">size_array</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.size_array" title="mxnet.np.ndarray.size_array"><code class="xref py py-func docutils literal notranslate"><span class="pre">size_array()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.slice" title="mxnet.np.ndarray.slice"><code class="xref py py-obj docutils literal notranslate"><span class="pre">slice</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.slice" title="mxnet.np.ndarray.slice"><code class="xref py py-func docutils literal notranslate"><span class="pre">slice()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.slice_assign" title="mxnet.np.ndarray.slice_assign"><code class="xref py py-obj docutils literal notranslate"><span class="pre">slice_assign</span></code></a>(rhs, begin, end, step)</p></td>
 <td><p>Assign the rhs to a cropped subset of this ndarray in place.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.slice_assign_scalar" title="mxnet.np.ndarray.slice_assign_scalar"><code class="xref py py-obj docutils literal notranslate"><span class="pre">slice_assign_scalar</span></code></a>(value, begin, end, step)</p></td>
 <td><p>Assign the scalar to a cropped subset of this ndarray.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.slice_axis" title="mxnet.np.ndarray.slice_axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">slice_axis</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.slice_axis" title="mxnet.np.ndarray.slice_axis"><code class="xref py py-func docutils literal notranslate"><span class="pre">slice_axis()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.slice_like" title="mxnet.np.ndarray.slice_like"><code class="xref py py-obj docutils literal notranslate"><span class="pre">slice_like</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.slice_like" title="mxnet.np.ndarray.slice_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">slice_like()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.softmax" title="mxnet.np.ndarray.softmax"><code class="xref py py-obj docutils literal notranslate"><span class="pre">softmax</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.softmax" title="mxnet.np.ndarray.softmax"><code class="xref py py-func docutils literal notranslate"><span class="pre">softmax()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.softmin" title="mxnet.np.ndarray.softmin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">softmin</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.softmin" title="mxnet.np.ndarray.softmin"><code class="xref py py-func docutils literal notranslate"><span class="pre">softmin()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.sort" title="mxnet.np.ndarray.sort"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sort</span></code></a>([axis, kind, order])</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.sort.html#mxnet.np.sort" title="mxnet.np.sort"><code class="xref py py-func docutils literal notranslate"><span class="pre">sort()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.space_to_depth" title="mxnet.np.ndarray.space_to_depth"><code class="xref py py-obj docutils literal notranslate"><span class="pre">space_to_depth</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.space_to_depth" title="mxnet.np.ndarray.space_to_depth"><code class="xref py py-func docutils literal notranslate"><span class="pre">space_to_depth()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.split" title="mxnet.np.ndarray.split"><code class="xref py py-obj docutils literal notranslate"><span class="pre">split</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.split.html#mxnet.np.split" title="mxnet.np.split"><code class="xref py py-func docutils literal notranslate"><span class="pre">split()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.split_v2" title="mxnet.np.ndarray.split_v2"><code class="xref py py-obj docutils literal notranslate"><span class="pre">split_v2</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.split_v2" title="mxnet.np.ndarray.split_v2"><code class="xref py py-func docutils literal notranslate"><span class="pre">split_v2()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.sqrt" title="mxnet.np.ndarray.sqrt"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sqrt</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.sqrt.html#mxnet.np.sqrt" title="mxnet.np.sqrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">sqrt()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.square" title="mxnet.np.ndarray.square"><code class="xref py py-obj docutils literal notranslate"><span class="pre">square</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.square.html#mxnet.np.square" title="mxnet.np.square"><code class="xref py py-func docutils literal notranslate"><span class="pre">square()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.squeeze" title="mxnet.np.ndarray.squeeze"><code class="xref py py-obj docutils literal notranslate"><span class="pre">squeeze</span></code></a>([axis])</p></td>
 <td><p>Remove single-dimensional entries from the shape of a.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.std" title="mxnet.np.ndarray.std"><code class="xref py py-obj docutils literal notranslate"><span class="pre">std</span></code></a>([axis, dtype, out, ddof, keepdims])</p></td>
 <td><p>Returns the standard deviation of the array elements along given axis.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.sum" title="mxnet.np.ndarray.sum"><code class="xref py py-obj docutils literal notranslate"><span class="pre">sum</span></code></a>([axis, dtype, out, keepdims])</p></td>
 <td><p>Return the sum of the array elements over the given axis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.swapaxes" title="mxnet.np.ndarray.swapaxes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">swapaxes</span></code></a>(axis1, axis2)</p></td>
 <td><p>Return a copy of the array with axis1 and axis2 interchanged.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.take" title="mxnet.np.ndarray.take"><code class="xref py py-obj docutils literal notranslate"><span class="pre">take</span></code></a>(indices[, axis, mode])</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.take" title="mxnet.np.ndarray.take"><code class="xref py py-func docutils literal notranslate"><span class="pre">take()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.tan" title="mxnet.np.ndarray.tan"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tan</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.tan.html#mxnet.np.tan" title="mxnet.np.tan"><code class="xref py py-func docutils literal notranslate"><span class="pre">tan()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.tanh" title="mxnet.np.ndarray.tanh"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tanh</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.tanh.html#mxnet.np.tanh" title="mxnet.np.tanh"><code class="xref py py-func docutils literal notranslate"><span class="pre">tanh()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.tile" title="mxnet.np.ndarray.tile"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tile</span></code></a>(reps)</p></td>
 <td><p>Construct an array by repeating A the number of times given by reps.</p></td>
 </tr>
 <tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_dlpack_for_read</span></code>()</p></td>
 <td><p>Returns a reference view of NDArray that represents as DLManagedTensor until all previous write operations on the current array are finished.</p></td>
 </tr>
 <tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_dlpack_for_write</span></code>()</p></td>
 <td><p>Returns a reference view of NDArray that represents as DLManagedTensor until all previous read/write operations on the current array are finished.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="mxnet.np.ndarray.tolist.html#mxnet.np.ndarray.tolist" title="mxnet.np.ndarray.tolist"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tolist</span></code></a>()</p></td>
 <td><p></p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.topk" title="mxnet.np.ndarray.topk"><code class="xref py py-obj docutils literal notranslate"><span class="pre">topk</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.topk" title="mxnet.np.ndarray.topk"><code class="xref py py-func docutils literal notranslate"><span class="pre">topk()</span></code></a>.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.tostype" title="mxnet.np.ndarray.tostype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">tostype</span></code></a>(stype)</p></td>
 <td><p>Return a copy of the array with chosen storage type.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.transpose" title="mxnet.np.ndarray.transpose"><code class="xref py py-obj docutils literal notranslate"><span class="pre">transpose</span></code></a>(*axes)</p></td>
 <td><p>Permute the dimensions of an array.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.trunc" title="mxnet.np.ndarray.trunc"><code class="xref py py-obj docutils literal notranslate"><span class="pre">trunc</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.trunc.html#mxnet.np.trunc" title="mxnet.np.trunc"><code class="xref py py-func docutils literal notranslate"><span class="pre">trunc()</span></code></a>.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.var" title="mxnet.np.ndarray.var"><code class="xref py py-obj docutils literal notranslate"><span class="pre">var</span></code></a>([axis, dtype, out, ddof, keepdims])</p></td>
 <td><p>Returns the variance of the array elements, along given axis.</p></td>
 </tr>
 <tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">wait_to_read</span></code>()</p></td>
 <td><p>Waits until all previous write operations on the current array are finished.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.zeros_like" title="mxnet.np.ndarray.zeros_like"><code class="xref py py-obj docutils literal notranslate"><span class="pre">zeros_like</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.zeros_like.html#mxnet.np.zeros_like" title="mxnet.np.zeros_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">zeros_like()</span></code></a>.</p></td>
 </tr>
 </tbody>
 </table>
 <p class="rubric">Attributes</p>
 <table class="longtable docutils align-default">
 <colgroup>
 <col style="width: 10%" />
 <col style="width: 90%" />
 </colgroup>
 <tbody>
 <tr class="row-odd"><td><p><a class="reference internal" href="mxnet.np.ndarray.T.html#mxnet.np.ndarray.T" title="mxnet.np.ndarray.T"><code class="xref py py-obj docutils literal notranslate"><span class="pre">T</span></code></a></p></td>
 <td><p>Same as self.transpose().</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.context" title="mxnet.np.ndarray.context"><code class="xref py py-obj docutils literal notranslate"><span class="pre">context</span></code></a></p></td>
 <td><p>This function has been deprecated.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.ctx" title="mxnet.np.ndarray.ctx"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ctx</span></code></a></p></td>
 <td><p>Device context of the array.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.dtype" title="mxnet.np.ndarray.dtype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">dtype</span></code></a></p></td>
 <td><p>Data-type of the array’s elements.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.grad" title="mxnet.np.ndarray.grad"><code class="xref py py-obj docutils literal notranslate"><span class="pre">grad</span></code></a></p></td>
 <td><p>Returns gradient buffer attached to this ndarray.</p></td>
 </tr>
 <tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">handle</span></code></p></td>
 <td><p></p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.ndim" title="mxnet.np.ndarray.ndim"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ndim</span></code></a></p></td>
 <td><p>Number of array dimensions.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="#mxnet.np.ndarray.shape" title="mxnet.np.ndarray.shape"><code class="xref py py-obj docutils literal notranslate"><span class="pre">shape</span></code></a></p></td>
 <td><p>Tuple of array dimensions.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="#mxnet.np.ndarray.size" title="mxnet.np.ndarray.size"><code class="xref py py-obj docutils literal notranslate"><span class="pre">size</span></code></a></p></td>
 <td><p>Number of elements in the array.</p></td>
 </tr>
 <tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">stype</span></code></p></td>
 <td><p>Storage-type of the array.</p></td>
 </tr>
 <tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">writable</span></code></p></td>
 <td><p></p></td>
 </tr>
 </tbody>
 </table>
 <dl class="method">
 <dt>
 <em class="property">property </em><code class="sig-name descname">T</code></dt>
 <dd><p>Same as self.transpose(). This always returns a copy of self.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.abs">
 <code class="sig-name descname">abs</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.abs" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.abs" title="mxnet.np.ndarray.abs"><code class="xref py py-func docutils literal notranslate"><span class="pre">abs()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.abs" title="mxnet.np.ndarray.abs"><code class="xref py py-func docutils literal notranslate"><span class="pre">abs()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.arccos">
 <code class="sig-name descname">arccos</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.arccos" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arccos.html#mxnet.np.arccos" title="mxnet.np.arccos"><code class="xref py py-func docutils literal notranslate"><span class="pre">arccos()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.arccos.html#mxnet.np.arccos" title="mxnet.np.arccos"><code class="xref py py-func docutils literal notranslate"><span class="pre">arccos()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.arccosh">
 <code class="sig-name descname">arccosh</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.arccosh" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arccosh.html#mxnet.np.arccosh" title="mxnet.np.arccosh"><code class="xref py py-func docutils literal notranslate"><span class="pre">arccosh()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.arccosh.html#mxnet.np.arccosh" title="mxnet.np.arccosh"><code class="xref py py-func docutils literal notranslate"><span class="pre">arccosh()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.arcsin">
 <code class="sig-name descname">arcsin</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.arcsin" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arcsin.html#mxnet.np.arcsin" title="mxnet.np.arcsin"><code class="xref py py-func docutils literal notranslate"><span class="pre">arcsin()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.arcsin.html#mxnet.np.arcsin" title="mxnet.np.arcsin"><code class="xref py py-func docutils literal notranslate"><span class="pre">arcsin()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.arcsinh">
 <code class="sig-name descname">arcsinh</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.arcsinh" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arcsinh.html#mxnet.np.arcsinh" title="mxnet.np.arcsinh"><code class="xref py py-func docutils literal notranslate"><span class="pre">arcsinh()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.arcsinh.html#mxnet.np.arcsinh" title="mxnet.np.arcsinh"><code class="xref py py-func docutils literal notranslate"><span class="pre">arcsinh()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.arctan">
 <code class="sig-name descname">arctan</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.arctan" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arctan.html#mxnet.np.arctan" title="mxnet.np.arctan"><code class="xref py py-func docutils literal notranslate"><span class="pre">arctan()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.arctan.html#mxnet.np.arctan" title="mxnet.np.arctan"><code class="xref py py-func docutils literal notranslate"><span class="pre">arctan()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.arctanh">
 <code class="sig-name descname">arctanh</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.arctanh" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.arctanh.html#mxnet.np.arctanh" title="mxnet.np.arctanh"><code class="xref py py-func docutils literal notranslate"><span class="pre">arctanh()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.arctanh.html#mxnet.np.arctanh" title="mxnet.np.arctanh"><code class="xref py py-func docutils literal notranslate"><span class="pre">arctanh()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.argmax">
 <code class="sig-name descname">argmax</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em>, <em class="sig-param">out=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.argmax" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return indices of the maximum values along the given axis.
 Refer to <cite>mxnet.numpy.argmax</cite> for full documentation.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.argmax_channel">
 <code class="sig-name descname">argmax_channel</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.argmax_channel" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.argmax_channel" title="mxnet.np.ndarray.argmax_channel"><code class="xref py py-func docutils literal notranslate"><span class="pre">argmax_channel()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.argmax_channel" title="mxnet.np.ndarray.argmax_channel"><code class="xref py py-func docutils literal notranslate"><span class="pre">argmax_channel()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.argmin">
 <code class="sig-name descname">argmin</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em>, <em class="sig-param">out=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.argmin" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return indices of the minium values along the given axis.
 Refer to <cite>mxnet.numpy.argmin</cite> for full documentation.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.argsort">
 <code class="sig-name descname">argsort</code><span class="sig-paren">(</span><em class="sig-param">axis=-1</em>, <em class="sig-param">kind=None</em>, <em class="sig-param">order=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.argsort" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.argsort.html#mxnet.np.argsort" title="mxnet.np.argsort"><code class="xref py py-func docutils literal notranslate"><span class="pre">argsort()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.argsort.html#mxnet.np.argsort" title="mxnet.np.argsort"><code class="xref py py-func docutils literal notranslate"><span class="pre">argsort()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.as_in_context">
 <code class="sig-name descname">as_in_context</code><span class="sig-paren">(</span><em class="sig-param">context</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.as_in_context" title="Permalink to this definition">¶</a></dt>
 <dd><p>This function has been deprecated. Please refer to <code class="docutils literal notranslate"><span class="pre">ndarray.as_in_ctx</span></code>.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.as_in_ctx">
 <code class="sig-name descname">as_in_ctx</code><span class="sig-paren">(</span><em class="sig-param">ctx</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.as_in_ctx" title="Permalink to this definition">¶</a></dt>
 <dd><p>Returns an array on the target device with the same value as this array.</p>
 <p>If the target context is the same as <code class="docutils literal notranslate"><span class="pre">self.context</span></code>, then <code class="docutils literal notranslate"><span class="pre">self</span></code> is
 returned.  Otherwise, a copy is made.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><p><strong>context</strong> (<a class="reference internal" href="../../context/index.html#mxnet.context.Context" title="mxnet.context.Context"><em>Context</em></a>) – The target context.</p>
 </dd>
 <dt class="field-even">Returns</dt>
 <dd class="field-even"><p>The target array.</p>
 </dd>
 <dt class="field-odd">Return type</dt>
 <dd class="field-odd"><p><a class="reference internal" href="#mxnet.np.ndarray" title="mxnet.np.ndarray">ndarray</a></p>
 </dd>
 </dl>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.as_nd_ndarray">
 <code class="sig-name descname">as_nd_ndarray</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.as_nd_ndarray" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convert mxnet.numpy.ndarray to mxnet.ndarray.NDArray to use its fluent methods.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.as_np_ndarray">
 <code class="sig-name descname">as_np_ndarray</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.as_np_ndarray" title="Permalink to this definition">¶</a></dt>
 <dd><p>A convenience function for creating a numpy ndarray from the current ndarray
 with zero copy. For this class, it just returns itself since it’s already a
 numpy ndarray.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.asscalar">
 <code class="sig-name descname">asscalar</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.asscalar" title="Permalink to this definition">¶</a></dt>
 <dd><p>Returns a scalar whose value is copied from this array.</p>
 <p>This function is equivalent to <code class="docutils literal notranslate"><span class="pre">self.asnumpy()[0]</span></code>. This NDArray must have shape (1,).</p>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">1</span><span class="p">,),</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">&#39;int32&#39;</span><span class="p">)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">asscalar</span><span class="p">()</span>
 <span class="go">1</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="nb">type</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">asscalar</span><span class="p">())</span>
 <span class="go">&lt;type &#39;numpy.int32&#39;&gt;</span>
 </pre></div>
 </div>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.astype">
 <code class="sig-name descname">astype</code><span class="sig-paren">(</span><em class="sig-param">dtype</em>, <em class="sig-param">order='K'</em>, <em class="sig-param">casting='unsafe'</em>, <em class="sig-param">subok=True</em>, <em class="sig-param">copy=True</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.astype" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of the array, cast to a specified type.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>dtype</strong> (<em>str</em><em> or </em><em>dtype</em>) – Typecode or data-type to which the array is cast.</p></li>
 <li><p><strong>order</strong> (<em>{'C'</em><em>, </em><em>'F'</em><em>, </em><em>'A'</em><em>, </em><em>'K'}</em><em>, </em><em>optional</em>) – Controls the memory layout order of the result.
 ‘C’ means C order, ‘F’ means Fortran order, ‘A’
 means ‘F’ order if all the arrays are Fortran contiguous,
 ‘C’ order otherwise, and ‘K’ means as close to the
 order the array elements appear in memory as possible.
 Default is ‘K’.</p></li>
 <li><p><strong>casting</strong> (<em>{'no'</em><em>, </em><em>'equiv'</em><em>, </em><em>'safe'</em><em>, </em><em>'same_kind'</em><em>, </em><em>'unsafe'}</em><em>, </em><em>optional</em>) – <p>Controls what kind of data casting may occur. Defaults to ‘unsafe’
 for backwards compatibility.</p>
 <blockquote>
 <div><ul>
 <li><p>’no’ means the data types should not be cast at all.</p></li>
 <li><p>’equiv’ means only byte-order changes are allowed.</p></li>
 <li><p>’safe’ means only casts which can preserve values are allowed.</p></li>
 <li><p>’same_kind’ means only safe casts or casts within a kind,
 like float64 to float32, are allowed.</p></li>
 <li><p>’unsafe’ means any data conversions may be done.</p></li>
 </ul>
 </div></blockquote>
 </p></li>
 <li><p><strong>subok</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, then sub-classes will be passed-through (default), otherwise
 the returned array will be forced to be a base-class array.</p></li>
 <li><p><strong>copy</strong> (<em>bool</em><em>, </em><em>optional</em>) – Default <cite>True</cite>. By default, astype always returns a newly
 allocated ndarray on the same context. If this is set to
 <cite>False</cite>, and the dtype requested is the same as the ndarray’s
 dtype, the ndarray is returned instead of a copy.</p></li>
 </ul>
 </dd>
 <dt class="field-even">Returns</dt>
 <dd class="field-even"><p><strong>arr_t</strong> – Unless <cite>copy</cite> is False and the other conditions for returning the input
 array are satisfied (see description for <cite>copy</cite> input parameter), <cite>arr_t</cite>
 is a new array of the same shape as the input array with <cite>dtype</cite>.</p>
 </dd>
 <dt class="field-odd">Return type</dt>
 <dd class="field-odd"><p><a class="reference internal" href="#mxnet.np.ndarray" title="mxnet.np.ndarray">ndarray</a></p>
 </dd>
 </dl>
 <p class="rubric">Notes</p>
 <p>This function differs from the official <cite>ndarray</cite>’s <code class="docutils literal notranslate"><span class="pre">astype</span></code> function in the following
 aspects:</p>
 <blockquote>
 <div><ul class="simple">
 <li><p><cite>order</cite> only supports ‘C’ and ‘K’.</p></li>
 <li><p><cite>casting</cite> only supports ‘unsafe’.</p></li>
 <li><p><cite>subok</cite> only supports <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p></li>
 </ul>
 </div></blockquote>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.attach_grad">
 <code class="sig-name descname">attach_grad</code><span class="sig-paren">(</span><em class="sig-param">grad_req='write'</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.attach_grad" title="Permalink to this definition">¶</a></dt>
 <dd><p>Attach a gradient buffer to this ndarray, so that <cite>backward</cite>
 can compute gradient with respect to it.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><p><strong>grad_req</strong> (<em>{'write'</em><em>, </em><em>'add'</em><em>, </em><em>'null'}</em>) – How gradient will be accumulated.
 - ‘write’: gradient will be overwritten on every backward.
 - ‘add’: gradient will be added to existing value on every backward.
 - ‘null’: do not compute gradient for this NDArray.</p>
 </dd>
 </dl>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.broadcast_axes">
 <code class="sig-name descname">broadcast_axes</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.broadcast_axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.broadcast_axes" title="mxnet.np.ndarray.broadcast_axes"><code class="xref py py-func docutils literal notranslate"><span class="pre">broadcast_axes()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.broadcast_axes" title="mxnet.np.ndarray.broadcast_axes"><code class="xref py py-func docutils literal notranslate"><span class="pre">broadcast_axes()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.broadcast_like">
 <code class="sig-name descname">broadcast_like</code><span class="sig-paren">(</span><em class="sig-param">other</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.broadcast_like" title="Permalink to this definition">¶</a></dt>
 <dd><p>Broadcasts the input array to the shape of other.</p>
 <p>Broadcasting is only allowed on axes with size 1. The new shape cannot change
 the number of dimensions.
 For example, you could broadcast from shape (2, 1) to (2, 3), but not from
 shape (2, 3) to (2, 3, 3).</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><p><strong>other</strong> (<a class="reference internal" href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" title="mxnet.ndarray.NDArray"><em>NDArray</em></a>) – Array with shape of the desired array.</p>
 </dd>
 <dt class="field-even">Returns</dt>
 <dd class="field-even"><p>A NDArray with the desired shape that is not sharing data with this
 array, even if the new shape is the same as <code class="docutils literal notranslate"><span class="pre">self.shape</span></code>.</p>
 </dd>
 <dt class="field-odd">Return type</dt>
 <dd class="field-odd"><p><a class="reference internal" href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" title="mxnet.ndarray.NDArray">NDArray</a></p>
 </dd>
 </dl>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">3</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">1</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span>
 <span class="go">array([[[ 0.],</span>
 <span class="go">        [ 1.],</span>
 <span class="go">        [ 2.]]], dtype=float32)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">broadcast_like</span><span class="p">(</span><span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">)))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span>
 <span class="go">array([[[ 0.,  0.,  0.],</span>
 <span class="go">        [ 1.,  1.,  1.],</span>
 <span class="go">        [ 2.,  2.,  2.]],</span>

 <span class="go">       [[ 0.,  0.,  0.],</span>
 <span class="go">        [ 1.,  1.,  1.],</span>
 <span class="go">        [ 2.,  2.,  2.]]], dtype=float32)</span>
 </pre></div>
 </div>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.broadcast_to">
 <code class="sig-name descname">broadcast_to</code><span class="sig-paren">(</span><em class="sig-param">shape</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.broadcast_to" title="Permalink to this definition">¶</a></dt>
 <dd><p>Broadcasts the input array to a new shape.</p>
 <p>Broadcasting is only allowed on axes with size 1. The new shape cannot change
 the number of dimensions.
 For example, you could broadcast from shape (2, 1) to (2, 3), but not from
 shape (2, 3) to (2, 3, 3).</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><p><strong>shape</strong> (<em>tuple of int</em>) – The shape of the desired array.</p>
 </dd>
 <dt class="field-even">Returns</dt>
 <dd class="field-even"><p>A NDArray with the desired shape that is not sharing data with this
 array, even if the new shape is the same as <code class="docutils literal notranslate"><span class="pre">self.shape</span></code>.</p>
 </dd>
 <dt class="field-odd">Return type</dt>
 <dd class="field-odd"><p><a class="reference internal" href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" title="mxnet.ndarray.NDArray">NDArray</a></p>
 </dd>
 </dl>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">3</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">1</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span>
 <span class="go">array([[[ 0.],</span>
 <span class="go">        [ 1.],</span>
 <span class="go">        [ 2.]]], dtype=float32)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">broadcast_to</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">3</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span>
 <span class="go">array([[[ 0.,  0.,  0.],</span>
 <span class="go">        [ 1.,  1.,  1.],</span>
 <span class="go">        [ 2.,  2.,  2.]],</span>

 <span class="go">       [[ 0.,  0.,  0.],</span>
 <span class="go">        [ 1.,  1.,  1.],</span>
 <span class="go">        [ 2.,  2.,  2.]]], dtype=float32)</span>
 </pre></div>
 </div>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.cbrt">
 <code class="sig-name descname">cbrt</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.cbrt" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.cbrt.html#mxnet.np.cbrt" title="mxnet.np.cbrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">cbrt()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.cbrt.html#mxnet.np.cbrt" title="mxnet.np.cbrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">cbrt()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.ceil">
 <code class="sig-name descname">ceil</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.ceil" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.ceil.html#mxnet.np.ceil" title="mxnet.np.ceil"><code class="xref py py-func docutils literal notranslate"><span class="pre">ceil()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.ceil.html#mxnet.np.ceil" title="mxnet.np.ceil"><code class="xref py py-func docutils literal notranslate"><span class="pre">ceil()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.clip">
 <code class="sig-name descname">clip</code><span class="sig-paren">(</span><em class="sig-param">min=None</em>, <em class="sig-param">max=None</em>, <em class="sig-param">out=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.clip" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return an array whose values are limited to [min, max].
 One of max or min must be given.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.context">
 <em class="property">property </em><code class="sig-name descname">context</code><a class="headerlink" href="#mxnet.np.ndarray.context" title="Permalink to this definition">¶</a></dt>
 <dd><p>This function has been deprecated. Please refer to <code class="docutils literal notranslate"><span class="pre">ndarray.ctx</span></code>.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.copy">
 <code class="sig-name descname">copy</code><span class="sig-paren">(</span><em class="sig-param">order='C'</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.copy" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return a coyp of the array, keeping the same context.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><p><strong>order</strong> (<em>str</em>) – The memory layout of the copy. Currently, only c-contiguous memory
 layout is supported.</p>
 </dd>
 </dl>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span>
 <span class="go">array([[ 1.,  1.,  1.],</span>
 <span class="go">       [ 1.,  1.,  1.]])</span>
 </pre></div>
 </div>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.copyto">
 <code class="sig-name descname">copyto</code><span class="sig-paren">(</span><em class="sig-param">other</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.copyto" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copies the value of this array to another array.</p>
 <p>If <code class="docutils literal notranslate"><span class="pre">other</span></code> is a <code class="docutils literal notranslate"><span class="pre">ndarray</span></code> object, then <code class="docutils literal notranslate"><span class="pre">other.shape</span></code> and
 <code class="docutils literal notranslate"><span class="pre">self.shape</span></code> should be the same. This function copies the value from
 <code class="docutils literal notranslate"><span class="pre">self</span></code> to <code class="docutils literal notranslate"><span class="pre">other</span></code>.</p>
 <p>If <code class="docutils literal notranslate"><span class="pre">other</span></code> is a context, a new <code class="docutils literal notranslate"><span class="pre">np.ndarray</span></code> will be first created on
 the target context, and the value of <code class="docutils literal notranslate"><span class="pre">self</span></code> is copied.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><p><strong>other</strong> (<a class="reference internal" href="#mxnet.np.ndarray" title="mxnet.np.ndarray"><em>ndarray</em></a><em> or </em><a class="reference internal" href="../../context/index.html#mxnet.context.Context" title="mxnet.context.Context"><em>Context</em></a>) – The destination array or context.</p>
 </dd>
 <dt class="field-even">Returns</dt>
 <dd class="field-even"><p><strong>out</strong> – The copied array. If <code class="docutils literal notranslate"><span class="pre">other</span></code> is an <code class="docutils literal notranslate"><span class="pre">ndarray</span></code>, then the return value
 and <code class="docutils literal notranslate"><span class="pre">other</span></code> will point to the same <code class="docutils literal notranslate"><span class="pre">ndarray</span></code>.</p>
 </dd>
 <dt class="field-odd">Return type</dt>
 <dd class="field-odd"><p><a class="reference internal" href="#mxnet.np.ndarray" title="mxnet.np.ndarray">ndarray</a></p>
 </dd>
 </dl>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">),</span> <span class="n">ctx</span><span class="o">=</span><span class="n">npx</span><span class="o">.</span><span class="n">gpu</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">z</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">copyto</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">z</span> <span class="ow">is</span> <span class="n">y</span>
 <span class="go">True</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span>
 <span class="go">array([[ 1.,  1.,  1.],</span>
 <span class="go">       [ 1.,  1.,  1.]])</span>
 </pre></div>
 </div>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.cos">
 <code class="sig-name descname">cos</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.cos" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.cos.html#mxnet.np.cos" title="mxnet.np.cos"><code class="xref py py-func docutils literal notranslate"><span class="pre">cos()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.cos.html#mxnet.np.cos" title="mxnet.np.cos"><code class="xref py py-func docutils literal notranslate"><span class="pre">cos()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.cosh">
 <code class="sig-name descname">cosh</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.cosh" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.cosh.html#mxnet.np.cosh" title="mxnet.np.cosh"><code class="xref py py-func docutils literal notranslate"><span class="pre">cosh()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.cosh.html#mxnet.np.cosh" title="mxnet.np.cosh"><code class="xref py py-func docutils literal notranslate"><span class="pre">cosh()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.ctx">
 <em class="property">property </em><code class="sig-name descname">ctx</code><a class="headerlink" href="#mxnet.np.ndarray.ctx" title="Permalink to this definition">¶</a></dt>
 <dd><p>Device context of the array.</p>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">])</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">ctx</span>
 <span class="go">cpu(0)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="nb">type</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">ctx</span><span class="p">)</span>
 <span class="go">&lt;class &#39;mxnet.context.Context&#39;&gt;</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">),</span> <span class="n">npx</span><span class="o">.</span><span class="n">gpu</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span><span class="o">.</span><span class="n">ctx</span>
 <span class="go">gpu(0)</span>
 </pre></div>
 </div>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.cumsum">
 <code class="sig-name descname">cumsum</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em>, <em class="sig-param">dtype=None</em>, <em class="sig-param">out=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.cumsum" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return the cumulative sum of the elements along the given axis.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.degrees">
 <code class="sig-name descname">degrees</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.degrees" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.degrees.html#mxnet.np.degrees" title="mxnet.np.degrees"><code class="xref py py-func docutils literal notranslate"><span class="pre">degrees()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.degrees.html#mxnet.np.degrees" title="mxnet.np.degrees"><code class="xref py py-func docutils literal notranslate"><span class="pre">degrees()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.depth_to_space">
 <code class="sig-name descname">depth_to_space</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.depth_to_space" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.depth_to_space" title="mxnet.np.ndarray.depth_to_space"><code class="xref py py-func docutils literal notranslate"><span class="pre">depth_to_space()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.depth_to_space" title="mxnet.np.ndarray.depth_to_space"><code class="xref py py-func docutils literal notranslate"><span class="pre">depth_to_space()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.detach">
 <code class="sig-name descname">detach</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.detach" title="Permalink to this definition">¶</a></dt>
 <dd><p>Returns a new ndarray, detached from the current graph.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.diag">
 <code class="sig-name descname">diag</code><span class="sig-paren">(</span><em class="sig-param">k=0</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.diag" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.diag" title="mxnet.np.ndarray.diag"><code class="xref py py-func docutils literal notranslate"><span class="pre">diag()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.diag" title="mxnet.np.ndarray.diag"><code class="xref py py-func docutils literal notranslate"><span class="pre">diag()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.dot">
 <code class="sig-name descname">dot</code><span class="sig-paren">(</span><em class="sig-param">b</em>, <em class="sig-param">out=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.dot" title="Permalink to this definition">¶</a></dt>
 <dd><p>Dot product of two arrays.
 Refer to <code class="docutils literal notranslate"><span class="pre">numpy.dot</span></code> for full documentation.</p>
 </dd></dl>

 <dl class="method">
 <dt>
 <em class="property">property </em><code class="sig-name descname">dtype</code></dt>
 <dd><p>Data-type of the array’s elements.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Returns</dt>
 <dd class="field-odd"><p>This NDArray’s data type.</p>
 </dd>
 <dt class="field-even">Return type</dt>
 <dd class="field-even"><p>numpy.dtype</p>
 </dd>
 </dl>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">dtype</span>
 <span class="go">dtype(&#39;float32&#39;)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">&#39;int32&#39;</span><span class="p">)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span><span class="o">.</span><span class="n">dtype</span>
 <span class="go">dtype(&#39;int32&#39;)</span>
 </pre></div>
 </div>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.exp">
 <code class="sig-name descname">exp</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.exp" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.exp.html#mxnet.np.exp" title="mxnet.np.exp"><code class="xref py py-func docutils literal notranslate"><span class="pre">exp()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.exp.html#mxnet.np.exp" title="mxnet.np.exp"><code class="xref py py-func docutils literal notranslate"><span class="pre">exp()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.expand_dims">
 <code class="sig-name descname">expand_dims</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.expand_dims" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.expand_dims.html#mxnet.np.expand_dims" title="mxnet.np.expand_dims"><code class="xref py py-func docutils literal notranslate"><span class="pre">expand_dims()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.expand_dims.html#mxnet.np.expand_dims" title="mxnet.np.expand_dims"><code class="xref py py-func docutils literal notranslate"><span class="pre">expand_dims()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.expm1">
 <code class="sig-name descname">expm1</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.expm1" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.expm1.html#mxnet.np.expm1" title="mxnet.np.expm1"><code class="xref py py-func docutils literal notranslate"><span class="pre">expm1()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.expm1.html#mxnet.np.expm1" title="mxnet.np.expm1"><code class="xref py py-func docutils literal notranslate"><span class="pre">expm1()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.fix">
 <code class="sig-name descname">fix</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.fix" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.fix.html#mxnet.np.fix" title="mxnet.np.fix"><code class="xref py py-func docutils literal notranslate"><span class="pre">fix()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.fix.html#mxnet.np.fix" title="mxnet.np.fix"><code class="xref py py-func docutils literal notranslate"><span class="pre">fix()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.flatten">
 <code class="sig-name descname">flatten</code><span class="sig-paren">(</span><em class="sig-param">order='C'</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.flatten" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return a copy of the array collapsed into one dimension.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.flip">
 <code class="sig-name descname">flip</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.flip" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.flip.html#mxnet.np.flip" title="mxnet.np.flip"><code class="xref py py-func docutils literal notranslate"><span class="pre">flip()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.flip.html#mxnet.np.flip" title="mxnet.np.flip"><code class="xref py py-func docutils literal notranslate"><span class="pre">flip()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.floor">
 <code class="sig-name descname">floor</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.floor" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.floor.html#mxnet.np.floor" title="mxnet.np.floor"><code class="xref py py-func docutils literal notranslate"><span class="pre">floor()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.floor.html#mxnet.np.floor" title="mxnet.np.floor"><code class="xref py py-func docutils literal notranslate"><span class="pre">floor()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.grad">
 <em class="property">property </em><code class="sig-name descname">grad</code><a class="headerlink" href="#mxnet.np.ndarray.grad" title="Permalink to this definition">¶</a></dt>
 <dd><p>Returns gradient buffer attached to this ndarray.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.item">
 <code class="sig-name descname">item</code><span class="sig-paren">(</span><em class="sig-param">*args</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.item" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy an element of an array to a standard Python scalar and return it.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><p><strong>*args</strong> (<em>Arguments</em><em> (</em><em>variable number and type</em><em>)</em>) – <p>none: in this case, the method only works for arrays with one element (a.size == 1),
 which element is copied into a standard Python scalar object and returned.</p>
 <p>int_type: this argument is interpreted as a flat index into the array, specifying which
 element to copy and return.</p>
 <p>tuple of int_types: functions as does a single int_type argument, except that the
 argument is interpreted as an nd-index into the array.</p>
 </p>
 </dd>
 <dt class="field-even">Returns</dt>
 <dd class="field-even"><p><strong>z</strong> – A copy of the specified element of the array as a suitable Python scalar.</p>
 </dd>
 <dt class="field-odd">Return type</dt>
 <dd class="field-odd"><p>Standard Python scalar object</p>
 </dd>
 </dl>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.log">
 <code class="sig-name descname">log</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.log" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.log.html#mxnet.np.log" title="mxnet.np.log"><code class="xref py py-func docutils literal notranslate"><span class="pre">log()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.log.html#mxnet.np.log" title="mxnet.np.log"><code class="xref py py-func docutils literal notranslate"><span class="pre">log()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.log10">
 <code class="sig-name descname">log10</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.log10" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.log10.html#mxnet.np.log10" title="mxnet.np.log10"><code class="xref py py-func docutils literal notranslate"><span class="pre">log10()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.log10.html#mxnet.np.log10" title="mxnet.np.log10"><code class="xref py py-func docutils literal notranslate"><span class="pre">log10()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.log1p">
 <code class="sig-name descname">log1p</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.log1p" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.log1p.html#mxnet.np.log1p" title="mxnet.np.log1p"><code class="xref py py-func docutils literal notranslate"><span class="pre">log1p()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.log1p.html#mxnet.np.log1p" title="mxnet.np.log1p"><code class="xref py py-func docutils literal notranslate"><span class="pre">log1p()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.log2">
 <code class="sig-name descname">log2</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.log2" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.log2.html#mxnet.np.log2" title="mxnet.np.log2"><code class="xref py py-func docutils literal notranslate"><span class="pre">log2()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.log2.html#mxnet.np.log2" title="mxnet.np.log2"><code class="xref py py-func docutils literal notranslate"><span class="pre">log2()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.log_softmax">
 <code class="sig-name descname">log_softmax</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.log_softmax" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.log_softmax" title="mxnet.np.ndarray.log_softmax"><code class="xref py py-func docutils literal notranslate"><span class="pre">log_softmax()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.log_softmax" title="mxnet.np.ndarray.log_softmax"><code class="xref py py-func docutils literal notranslate"><span class="pre">log_softmax()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.max">
 <code class="sig-name descname">max</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em>, <em class="sig-param">out=None</em>, <em class="sig-param">keepdims=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.max" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return the maximum along a given axis.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.mean">
 <code class="sig-name descname">mean</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em>, <em class="sig-param">dtype=None</em>, <em class="sig-param">out=None</em>, <em class="sig-param">keepdims=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.mean" title="Permalink to this definition">¶</a></dt>
 <dd><p>Returns the average of the array elements along given axis.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.min">
 <code class="sig-name descname">min</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em>, <em class="sig-param">out=None</em>, <em class="sig-param">keepdims=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.min" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.min.html#mxnet.np.min" title="mxnet.np.min"><code class="xref py py-func docutils literal notranslate"><span class="pre">min()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.min.html#mxnet.np.min" title="mxnet.np.min"><code class="xref py py-func docutils literal notranslate"><span class="pre">min()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.nanprod">
 <code class="sig-name descname">nanprod</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.nanprod" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.nanprod.html#mxnet.np.nanprod" title="mxnet.np.nanprod"><code class="xref py py-func docutils literal notranslate"><span class="pre">nanprod()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.nanprod.html#mxnet.np.nanprod" title="mxnet.np.nanprod"><code class="xref py py-func docutils literal notranslate"><span class="pre">nanprod()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.nansum">
 <code class="sig-name descname">nansum</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.nansum" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.nansum" title="mxnet.np.ndarray.nansum"><code class="xref py py-func docutils literal notranslate"><span class="pre">nansum()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.nansum" title="mxnet.np.ndarray.nansum"><code class="xref py py-func docutils literal notranslate"><span class="pre">nansum()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt>
 <em class="property">property </em><code class="sig-name descname">ndim</code></dt>
 <dd><p>Number of array dimensions.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.nonzero">
 <code class="sig-name descname">nonzero</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.nonzero" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return the indices of the elements that are non-zero.</p>
 <p>Refer to <cite>numpy.nonzero</cite> for full documentation.</p>
 <div class="admonition seealso">
 <p class="admonition-title">See also</p>
 <dl class="simple">
 <dt><code class="xref py py-meth docutils literal notranslate"><span class="pre">numpy.nonzero()</span></code></dt><dd><p>equivalent function</p>
 </dd>
 </dl>
 </div>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.norm">
 <code class="sig-name descname">norm</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.norm" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.norm" title="mxnet.np.ndarray.norm"><code class="xref py py-func docutils literal notranslate"><span class="pre">norm()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.norm" title="mxnet.np.ndarray.norm"><code class="xref py py-func docutils literal notranslate"><span class="pre">norm()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.one_hot">
 <code class="sig-name descname">one_hot</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.one_hot" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.one_hot" title="mxnet.np.ndarray.one_hot"><code class="xref py py-func docutils literal notranslate"><span class="pre">one_hot()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.one_hot" title="mxnet.np.ndarray.one_hot"><code class="xref py py-func docutils literal notranslate"><span class="pre">one_hot()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.ones_like">
 <code class="sig-name descname">ones_like</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.ones_like" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.ones_like.html#mxnet.np.ones_like" title="mxnet.np.ones_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">ones_like()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.ones_like.html#mxnet.np.ones_like" title="mxnet.np.ones_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">ones_like()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.pad">
 <code class="sig-name descname">pad</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.pad" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.pad" title="mxnet.np.ndarray.pad"><code class="xref py py-func docutils literal notranslate"><span class="pre">pad()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.pad" title="mxnet.np.ndarray.pad"><code class="xref py py-func docutils literal notranslate"><span class="pre">pad()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.pick">
 <code class="sig-name descname">pick</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.pick" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.pick" title="mxnet.np.ndarray.pick"><code class="xref py py-func docutils literal notranslate"><span class="pre">pick()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.pick" title="mxnet.np.ndarray.pick"><code class="xref py py-func docutils literal notranslate"><span class="pre">pick()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.prod">
 <code class="sig-name descname">prod</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em>, <em class="sig-param">dtype=None</em>, <em class="sig-param">out=None</em>, <em class="sig-param">keepdims=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.prod" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return the product of the array elements over the given axis.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.radians">
 <code class="sig-name descname">radians</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.radians" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.radians.html#mxnet.np.radians" title="mxnet.np.radians"><code class="xref py py-func docutils literal notranslate"><span class="pre">radians()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.radians.html#mxnet.np.radians" title="mxnet.np.radians"><code class="xref py py-func docutils literal notranslate"><span class="pre">radians()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.rcbrt">
 <code class="sig-name descname">rcbrt</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.rcbrt" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.rcbrt" title="mxnet.np.ndarray.rcbrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">rcbrt()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.rcbrt" title="mxnet.np.ndarray.rcbrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">rcbrt()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.reciprocal">
 <code class="sig-name descname">reciprocal</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.reciprocal" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.reciprocal.html#mxnet.np.reciprocal" title="mxnet.np.reciprocal"><code class="xref py py-func docutils literal notranslate"><span class="pre">reciprocal()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.reciprocal.html#mxnet.np.reciprocal" title="mxnet.np.reciprocal"><code class="xref py py-func docutils literal notranslate"><span class="pre">reciprocal()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.relu">
 <code class="sig-name descname">relu</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.relu" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.relu" title="mxnet.np.ndarray.relu"><code class="xref py py-func docutils literal notranslate"><span class="pre">relu()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.relu" title="mxnet.np.ndarray.relu"><code class="xref py py-func docutils literal notranslate"><span class="pre">relu()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.repeat">
 <code class="sig-name descname">repeat</code><span class="sig-paren">(</span><em class="sig-param">repeats</em>, <em class="sig-param">axis=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.repeat" title="Permalink to this definition">¶</a></dt>
 <dd><p>Repeat elements of an array.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.reshape">
 <code class="sig-name descname">reshape</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.reshape" title="Permalink to this definition">¶</a></dt>
 <dd><p>Returns a copy of the array with a new shape.</p>
 <p class="rubric">Notes</p>
 <p>Unlike the free function <cite>numpy.reshape</cite>, this method on <cite>ndarray</cite> allows
 the elements of the shape parameter to be passed in as separate arguments.
 For example, <code class="docutils literal notranslate"><span class="pre">a.reshape(10,</span> <span class="pre">11)</span></code> is equivalent to
 <code class="docutils literal notranslate"><span class="pre">a.reshape((10,</span> <span class="pre">11))</span></code>.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.reshape_like">
 <code class="sig-name descname">reshape_like</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.reshape_like" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.reshape_like" title="mxnet.np.ndarray.reshape_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">reshape_like()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.reshape_like" title="mxnet.np.ndarray.reshape_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">reshape_like()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.reshape_view">
 <code class="sig-name descname">reshape_view</code><span class="sig-paren">(</span><em class="sig-param">*shape</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.reshape_view" title="Permalink to this definition">¶</a></dt>
 <dd><p>Returns a <strong>view</strong> of this array with a new shape without altering any data.
 Inheritated from NDArray.reshape.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.rint">
 <code class="sig-name descname">rint</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.rint" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.rint.html#mxnet.np.rint" title="mxnet.np.rint"><code class="xref py py-func docutils literal notranslate"><span class="pre">rint()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.rint.html#mxnet.np.rint" title="mxnet.np.rint"><code class="xref py py-func docutils literal notranslate"><span class="pre">rint()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.round">
 <code class="sig-name descname">round</code><span class="sig-paren">(</span><em class="sig-param">decimals=0</em>, <em class="sig-param">out=None</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.round" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.round" title="mxnet.np.ndarray.round"><code class="xref py py-func docutils literal notranslate"><span class="pre">round()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.round" title="mxnet.np.ndarray.round"><code class="xref py py-func docutils literal notranslate"><span class="pre">round()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.rsqrt">
 <code class="sig-name descname">rsqrt</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.rsqrt" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.rsqrt" title="mxnet.np.ndarray.rsqrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">rsqrt()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.rsqrt" title="mxnet.np.ndarray.rsqrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">rsqrt()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt>
 <em class="property">property </em><code class="sig-name descname">shape</code></dt>
 <dd><p>Tuple of array dimensions.</p>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">])</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">shape</span>
 <span class="go">(4L,)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span><span class="o">.</span><span class="n">shape</span>
 <span class="go">(2L, 3L, 4L)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">z</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">z</span><span class="o">.</span><span class="n">shape</span>
 <span class="go">()</span>
 </pre></div>
 </div>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.shape_array">
 <code class="sig-name descname">shape_array</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.shape_array" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.shape_array" title="mxnet.np.ndarray.shape_array"><code class="xref py py-func docutils literal notranslate"><span class="pre">shape_array()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.shape_array" title="mxnet.np.ndarray.shape_array"><code class="xref py py-func docutils literal notranslate"><span class="pre">shape_array()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.sigmoid">
 <code class="sig-name descname">sigmoid</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.sigmoid" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.sigmoid" title="mxnet.np.ndarray.sigmoid"><code class="xref py py-func docutils literal notranslate"><span class="pre">sigmoid()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.sigmoid" title="mxnet.np.ndarray.sigmoid"><code class="xref py py-func docutils literal notranslate"><span class="pre">sigmoid()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.sign">
 <code class="sig-name descname">sign</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.sign" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.sign.html#mxnet.np.sign" title="mxnet.np.sign"><code class="xref py py-func docutils literal notranslate"><span class="pre">sign()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.sign.html#mxnet.np.sign" title="mxnet.np.sign"><code class="xref py py-func docutils literal notranslate"><span class="pre">sign()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.sin">
 <code class="sig-name descname">sin</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.sin" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.sin.html#mxnet.np.sin" title="mxnet.np.sin"><code class="xref py py-func docutils literal notranslate"><span class="pre">sin()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.sin.html#mxnet.np.sin" title="mxnet.np.sin"><code class="xref py py-func docutils literal notranslate"><span class="pre">sin()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.sinh">
 <code class="sig-name descname">sinh</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.sinh" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.sinh.html#mxnet.np.sinh" title="mxnet.np.sinh"><code class="xref py py-func docutils literal notranslate"><span class="pre">sinh()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.sinh.html#mxnet.np.sinh" title="mxnet.np.sinh"><code class="xref py py-func docutils literal notranslate"><span class="pre">sinh()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt>
 <em class="property">property </em><code class="sig-name descname">size</code></dt>
 <dd><p>Number of elements in the array.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.size_array">
 <code class="sig-name descname">size_array</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.size_array" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.size_array" title="mxnet.np.ndarray.size_array"><code class="xref py py-func docutils literal notranslate"><span class="pre">size_array()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.size_array" title="mxnet.np.ndarray.size_array"><code class="xref py py-func docutils literal notranslate"><span class="pre">size_array()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.slice">
 <code class="sig-name descname">slice</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.slice" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.slice" title="mxnet.np.ndarray.slice"><code class="xref py py-func docutils literal notranslate"><span class="pre">slice()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.slice" title="mxnet.np.ndarray.slice"><code class="xref py py-func docutils literal notranslate"><span class="pre">slice()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.slice_assign">
 <code class="sig-name descname">slice_assign</code><span class="sig-paren">(</span><em class="sig-param">rhs</em>, <em class="sig-param">begin</em>, <em class="sig-param">end</em>, <em class="sig-param">step</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.slice_assign" title="Permalink to this definition">¶</a></dt>
 <dd><p>Assign the rhs to a cropped subset of this ndarray in place.
 Returns the view of this ndarray.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>rhs</strong> (<em>ndarray.</em>) – rhs and this NDArray should be of the same data type, and on the same device.
 The shape of rhs should be the same as the cropped shape of this ndarray.</p></li>
 <li><p><strong>begin</strong> (<em>tuple of begin indices</em>) – </p></li>
 <li><p><strong>end</strong> (<em>tuple of end indices</em>) – </p></li>
 <li><p><strong>step</strong> (<em>tuple of step lenghths</em>) – </p></li>
 </ul>
 </dd>
 <dt class="field-even">Returns</dt>
 <dd class="field-even"><p><strong>out</strong> – This ndarray.</p>
 </dd>
 <dt class="field-odd">Return type</dt>
 <dd class="field-odd"><p><a class="reference internal" href="#mxnet.np.ndarray" title="mxnet.np.ndarray">ndarray</a></p>
 </dd>
 </dl>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">assigned</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">slice_assign</span><span class="p">(</span><span class="n">assigned</span><span class="p">,</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="kc">None</span><span class="p">),</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">None</span><span class="p">),</span> <span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span>
 <span class="go">array([[[0., 0.],</span>
 <span class="go">        [1., 1.]],</span>
 </pre></div>
 </div>
 <blockquote>
 <div><dl class="simple">
 <dt>[[1., 1.],</dt><dd><p>[1., 1.]]])</p>
 </dd>
 </dl>
 </div></blockquote>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span>
 <span class="go">array([[[0., 0.],</span>
 <span class="go">        [1., 1.]],</span>
 </pre></div>
 </div>
 <blockquote>
 <div><dl class="simple">
 <dt>[[1., 1.],</dt><dd><p>[1., 1.]]])</p>
 </dd>
 </dl>
 </div></blockquote>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.slice_assign_scalar">
 <code class="sig-name descname">slice_assign_scalar</code><span class="sig-paren">(</span><em class="sig-param">value</em>, <em class="sig-param">begin</em>, <em class="sig-param">end</em>, <em class="sig-param">step</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.slice_assign_scalar" title="Permalink to this definition">¶</a></dt>
 <dd><p>Assign the scalar to a cropped subset of this ndarray. Value will broadcast to the shape of the cropped shape
 and will be cast to the same dtype of the ndarray.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>value</strong> (<em>numeric value</em>) – Value and this ndarray should be of the same data type.
 The shape of rhs should be the same as the cropped shape of this ndarray.</p></li>
 <li><p><strong>begin</strong> (<em>tuple of begin indices</em>) – </p></li>
 <li><p><strong>end</strong> (<em>tuple of end indices</em>) – </p></li>
 <li><p><strong>step</strong> (<em>tuple of step lenghths</em>) – </p></li>
 </ul>
 </dd>
 <dt class="field-even">Returns</dt>
 <dd class="field-even"><p></p>
 </dd>
 <dt class="field-odd">Return type</dt>
 <dd class="field-odd"><p>This ndarray.</p>
 </dd>
 </dl>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">slice_assign_scalar</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="kc">None</span><span class="p">),</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">None</span><span class="p">),</span> <span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">))</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">y</span>
 <span class="go">array([[[0., 0.],</span>
 <span class="go">        [1., 1.]],</span>
 </pre></div>
 </div>
 <blockquote>
 <div><dl class="simple">
 <dt>[[1., 1.],</dt><dd><p>[1., 1.]]])</p>
 </dd>
 </dl>
 </div></blockquote>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span>
 <span class="go">array([[[0., 0.],</span>
 <span class="go">        [1., 1.]],</span>
 </pre></div>
 </div>
 <blockquote>
 <div><dl class="simple">
 <dt>[[1., 1.],</dt><dd><p>[1., 1.]]])</p>
 </dd>
 </dl>
 </div></blockquote>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.slice_axis">
 <code class="sig-name descname">slice_axis</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.slice_axis" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.slice_axis" title="mxnet.np.ndarray.slice_axis"><code class="xref py py-func docutils literal notranslate"><span class="pre">slice_axis()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.slice_axis" title="mxnet.np.ndarray.slice_axis"><code class="xref py py-func docutils literal notranslate"><span class="pre">slice_axis()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.slice_like">
 <code class="sig-name descname">slice_like</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.slice_like" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.slice_like" title="mxnet.np.ndarray.slice_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">slice_like()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.slice_like" title="mxnet.np.ndarray.slice_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">slice_like()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.softmax">
 <code class="sig-name descname">softmax</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.softmax" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.softmax" title="mxnet.np.ndarray.softmax"><code class="xref py py-func docutils literal notranslate"><span class="pre">softmax()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.softmax" title="mxnet.np.ndarray.softmax"><code class="xref py py-func docutils literal notranslate"><span class="pre">softmax()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.softmin">
 <code class="sig-name descname">softmin</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.softmin" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.softmin" title="mxnet.np.ndarray.softmin"><code class="xref py py-func docutils literal notranslate"><span class="pre">softmin()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.softmin" title="mxnet.np.ndarray.softmin"><code class="xref py py-func docutils literal notranslate"><span class="pre">softmin()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.sort">
 <code class="sig-name descname">sort</code><span class="sig-paren">(</span><em class="sig-param">axis=-1</em>, <em class="sig-param">kind=None</em>, <em class="sig-param">order=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.sort" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.sort.html#mxnet.np.sort" title="mxnet.np.sort"><code class="xref py py-func docutils literal notranslate"><span class="pre">sort()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.sort.html#mxnet.np.sort" title="mxnet.np.sort"><code class="xref py py-func docutils literal notranslate"><span class="pre">sort()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.space_to_depth">
 <code class="sig-name descname">space_to_depth</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.space_to_depth" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.space_to_depth" title="mxnet.np.ndarray.space_to_depth"><code class="xref py py-func docutils literal notranslate"><span class="pre">space_to_depth()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.space_to_depth" title="mxnet.np.ndarray.space_to_depth"><code class="xref py py-func docutils literal notranslate"><span class="pre">space_to_depth()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.split">
 <code class="sig-name descname">split</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.split" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.split.html#mxnet.np.split" title="mxnet.np.split"><code class="xref py py-func docutils literal notranslate"><span class="pre">split()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.split.html#mxnet.np.split" title="mxnet.np.split"><code class="xref py py-func docutils literal notranslate"><span class="pre">split()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.split_v2">
 <code class="sig-name descname">split_v2</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.split_v2" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.split_v2" title="mxnet.np.ndarray.split_v2"><code class="xref py py-func docutils literal notranslate"><span class="pre">split_v2()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.split_v2" title="mxnet.np.ndarray.split_v2"><code class="xref py py-func docutils literal notranslate"><span class="pre">split_v2()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.sqrt">
 <code class="sig-name descname">sqrt</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.sqrt" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.sqrt.html#mxnet.np.sqrt" title="mxnet.np.sqrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">sqrt()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.sqrt.html#mxnet.np.sqrt" title="mxnet.np.sqrt"><code class="xref py py-func docutils literal notranslate"><span class="pre">sqrt()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.square">
 <code class="sig-name descname">square</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.square" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.square.html#mxnet.np.square" title="mxnet.np.square"><code class="xref py py-func docutils literal notranslate"><span class="pre">square()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.square.html#mxnet.np.square" title="mxnet.np.square"><code class="xref py py-func docutils literal notranslate"><span class="pre">square()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.squeeze">
 <code class="sig-name descname">squeeze</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.squeeze" title="Permalink to this definition">¶</a></dt>
 <dd><p>Remove single-dimensional entries from the shape of a.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.std">
 <code class="sig-name descname">std</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em>, <em class="sig-param">dtype=None</em>, <em class="sig-param">out=None</em>, <em class="sig-param">ddof=0</em>, <em class="sig-param">keepdims=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.std" title="Permalink to this definition">¶</a></dt>
 <dd><p>Returns the standard deviation of the array elements along given axis.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.sum">
 <code class="sig-name descname">sum</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em>, <em class="sig-param">dtype=None</em>, <em class="sig-param">out=None</em>, <em class="sig-param">keepdims=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.sum" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return the sum of the array elements over the given axis.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.swapaxes">
 <code class="sig-name descname">swapaxes</code><span class="sig-paren">(</span><em class="sig-param">axis1</em>, <em class="sig-param">axis2</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.swapaxes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return a copy of the array with axis1 and axis2 interchanged.
 Refer to <cite>mxnet.numpy.swapaxes</cite> for full documentation.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.take">
 <code class="sig-name descname">take</code><span class="sig-paren">(</span><em class="sig-param">indices</em>, <em class="sig-param">axis=None</em>, <em class="sig-param">mode='raise'</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.take" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.take" title="mxnet.np.ndarray.take"><code class="xref py py-func docutils literal notranslate"><span class="pre">take()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.take" title="mxnet.np.ndarray.take"><code class="xref py py-func docutils literal notranslate"><span class="pre">take()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.tan">
 <code class="sig-name descname">tan</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.tan" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.tan.html#mxnet.np.tan" title="mxnet.np.tan"><code class="xref py py-func docutils literal notranslate"><span class="pre">tan()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.tan.html#mxnet.np.tan" title="mxnet.np.tan"><code class="xref py py-func docutils literal notranslate"><span class="pre">tan()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.tanh">
 <code class="sig-name descname">tanh</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.tanh" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.tanh.html#mxnet.np.tanh" title="mxnet.np.tanh"><code class="xref py py-func docutils literal notranslate"><span class="pre">tanh()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.tanh.html#mxnet.np.tanh" title="mxnet.np.tanh"><code class="xref py py-func docutils literal notranslate"><span class="pre">tanh()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.tile">
 <code class="sig-name descname">tile</code><span class="sig-paren">(</span><em class="sig-param">reps</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.tile" title="Permalink to this definition">¶</a></dt>
 <dd><p>Construct an array by repeating A the number of times given by reps.
 Refer to <cite>mxnet.numpy.tile</cite> for full documentation.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.topk">
 <code class="sig-name descname">topk</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.topk" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="#mxnet.np.ndarray.topk" title="mxnet.np.ndarray.topk"><code class="xref py py-func docutils literal notranslate"><span class="pre">topk()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="#mxnet.np.ndarray.topk" title="mxnet.np.ndarray.topk"><code class="xref py py-func docutils literal notranslate"><span class="pre">topk()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.tostype">
 <code class="sig-name descname">tostype</code><span class="sig-paren">(</span><em class="sig-param">stype</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.tostype" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return a copy of the array with chosen storage type.</p>
 <div class="admonition seealso">
 <p class="admonition-title">See also</p>
 <p><a class="reference internal" href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.cast_storage" title="mxnet.ndarray.cast_storage"><code class="xref py py-meth docutils literal notranslate"><span class="pre">mxnet.ndarray.cast_storage()</span></code></a></p>
 </div>
 <dl class="field-list simple">
 <dt class="field-odd">Returns</dt>
 <dd class="field-odd"><p>A copy of the array with the chosen storage stype</p>
 </dd>
 <dt class="field-even">Return type</dt>
 <dd class="field-even"><p><a class="reference internal" href="../../legacy/ndarray/ndarray.html#mxnet.ndarray.NDArray" title="mxnet.ndarray.NDArray">NDArray</a>, <a class="reference internal" href="../../legacy/ndarray/sparse/index.html#mxnet.ndarray.sparse.CSRNDArray" title="mxnet.ndarray.sparse.CSRNDArray">CSRNDArray</a> or <a class="reference internal" href="../../legacy/ndarray/sparse/index.html#mxnet.ndarray.sparse.RowSparseNDArray" title="mxnet.ndarray.sparse.RowSparseNDArray">RowSparseNDArray</a></p>
 </dd>
 </dl>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.transpose">
 <code class="sig-name descname">transpose</code><span class="sig-paren">(</span><em class="sig-param">*axes</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.transpose" title="Permalink to this definition">¶</a></dt>
 <dd><p>Permute the dimensions of an array.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.trunc">
 <code class="sig-name descname">trunc</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.trunc" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.trunc.html#mxnet.np.trunc" title="mxnet.np.trunc"><code class="xref py py-func docutils literal notranslate"><span class="pre">trunc()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.trunc.html#mxnet.np.trunc" title="mxnet.np.trunc"><code class="xref py py-func docutils literal notranslate"><span class="pre">trunc()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.var">
 <code class="sig-name descname">var</code><span class="sig-paren">(</span><em class="sig-param">axis=None</em>, <em class="sig-param">dtype=None</em>, <em class="sig-param">out=None</em>, <em class="sig-param">ddof=0</em>, <em class="sig-param">keepdims=False</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.var" title="Permalink to this definition">¶</a></dt>
 <dd><p>Returns the variance of the array elements, along given axis.</p>
 </dd></dl>

 <dl class="method">
 <dt id="mxnet.np.ndarray.zeros_like">
 <code class="sig-name descname">zeros_like</code><span class="sig-paren">(</span><em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.np.ndarray.zeros_like" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convenience fluent method for <a class="reference internal" href="mxnet.np.zeros_like.html#mxnet.np.zeros_like" title="mxnet.np.zeros_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">zeros_like()</span></code></a>.</p>
 <p>The arguments are the same as for <a class="reference internal" href="mxnet.np.zeros_like.html#mxnet.np.zeros_like" title="mxnet.np.zeros_like"><code class="xref py py-func docutils literal notranslate"><span class="pre">zeros_like()</span></code></a>, with
 this array as data.</p>
 </dd></dl>

 </dd></dl>

 </div>


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