Google Git
Sign in
apache / mxnet-site / 7c979c3950c5081994a0e7d0c43c288c6fefb049 / . / versions / 1.0.0 / _modules / mxnet / module / python_module.html
blob: b28a19d1c857efdbf3b294cfd558813c66137ba7 [file] [log] [blame]
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8"/>
<meta content="IE=edge" http-equiv="X-UA-Compatible"/>
<meta content="width=device-width, initial-scale=1" name="viewport"/>
<title>mxnet.module.python_module — mxnet documentation</title>
<link crossorigin="anonymous" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/css/bootstrap.min.css" integrity="sha384-1q8mTJOASx8j1Au+a5WDVnPi2lkFfwwEAa8hDDdjZlpLegxhjVME1fgjWPGmkzs7" rel="stylesheet"/>
<link href="https://maxcdn.bootstrapcdn.com/font-awesome/4.5.0/css/font-awesome.min.css" rel="stylesheet"/>
<link href="../../../_static/basic.css" rel="stylesheet" type="text/css"/>
<link href="../../../_static/pygments.css" rel="stylesheet" type="text/css"/>
<link href="../../../_static/mxnet.css" rel="stylesheet" type="text/css">
<script type="text/javascript">
var DOCUMENTATION_OPTIONS = {
URL_ROOT: '../../../',
VERSION: '',
COLLAPSE_INDEX: false,
FILE_SUFFIX: '.html',
HAS_SOURCE: true,
SOURCELINK_SUFFIX: ''
};
</script>
<script src="https://code.jquery.com/jquery-1.11.1.min.js" type="text/javascript"></script>
<script src="../../../_static/underscore.js" type="text/javascript"></script>
<script src="../../../_static/searchtools_custom.js" type="text/javascript"></script>
<script src="../../../_static/doctools.js" type="text/javascript"></script>
<script src="../../../_static/selectlang.js" type="text/javascript"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML" type="text/javascript"></script>
<script type="text/javascript"> jQuery(function() { Search.loadIndex("/searchindex.js"); Search.init();}); </script>
<script>
(function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new
Date();a=s.createElement(o),
m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
})(window,document,'script','https://www.google-analytics.com/analytics.js','ga');
ga('create', 'UA-96378503-1', 'auto');
ga('send', 'pageview');
</script>
<!-- -->
<!-- <script type="text/javascript" src="../../../_static/jquery.js"></script> -->
<!-- -->
<!-- <script type="text/javascript" src="../../../_static/underscore.js"></script> -->
<!-- -->
<!-- <script type="text/javascript" src="../../../_static/doctools.js"></script> -->
<!-- -->
<!-- <script type="text/javascript" src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script> -->
<!-- -->
<link href="../../index.html" rel="up" title="Module code"/>
<link href="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-icon.png" rel="icon" type="image/png">
</link></link></head>
<body background="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-background-compressed.jpeg" role="document">
<div class="content-block"><div class="navbar navbar-fixed-top">
<div class="container" id="navContainer">
<div class="innder" id="header-inner">
<h1 id="logo-wrap">
<a href="../../../" id="logo"><img src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet_logo.png"/></a>
</h1>
<nav class="nav-bar" id="main-nav">
<a class="main-nav-link" href="../../../install/index.html">Install</a>
<a class="main-nav-link" href="../../../tutorials/index.html">Tutorials</a>
<span id="dropdown-menu-position-anchor">
<a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">Gluon <span class="caret"></span></a>
<ul class="dropdown-menu navbar-menu" id="package-dropdown-menu">
<li><a class="main-nav-link" href="../../../gluon/index.html">About</a></li>
<li><a class="main-nav-link" href="http://gluon.mxnet.io">Tutorials</a></li>
</ul>
</span>
<span id="dropdown-menu-position-anchor">
<a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">API <span class="caret"></span></a>
<ul class="dropdown-menu navbar-menu" id="package-dropdown-menu">
<li><a class="main-nav-link" href="../../../api/python/index.html">Python</a></li>
<li><a class="main-nav-link" href="../../../api/scala/index.html">Scala</a></li>
<li><a class="main-nav-link" href="../../../api/r/index.html">R</a></li>
<li><a class="main-nav-link" href="../../../api/julia/index.html">Julia</a></li>
<li><a class="main-nav-link" href="../../../api/c++/index.html">C++</a></li>
<li><a class="main-nav-link" href="../../../api/perl/index.html">Perl</a></li>
</ul>
</span>
<span id="dropdown-menu-position-anchor-docs">
<a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">Docs <span class="caret"></span></a>
<ul class="dropdown-menu navbar-menu" id="package-dropdown-menu-docs">
<li><a class="main-nav-link" href="../../../faq/index.html">FAQ</a></li>
<li><a class="main-nav-link" href="../../../architecture/index.html">Architecture</a></li>
<li><a class="main-nav-link" href="https://github.com/apache/incubator-mxnet/tree/1.0.0/example">Examples</a></li>
<li><a class="main-nav-link" href="../../../model_zoo/index.html">Model Zoo</a></li>
</ul>
</span>
<a class="main-nav-link" href="https://github.com/dmlc/mxnet">Github</a>
<span id="dropdown-menu-position-anchor-community">
<a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">Community <span class="caret"></span></a>
<ul class="dropdown-menu navbar-menu" id="package-dropdown-menu-community">
<li><a class="main-nav-link" href="../../../community/index.html">Community</a></li>
<li><a class="main-nav-link" href="../../../community/contribute.html">Contribute</a></li>
<li><a class="main-nav-link" href="../../../community/powered_by.html">Powered By</a></li>
</ul>
</span>
<a class="main-nav-link" href="http://discuss.mxnet.io">Discuss</a>
<span id="dropdown-menu-position-anchor-version" style="position: relative"><a href="#" class="main-nav-link dropdown-toggle" data-toggle="dropdown" role="button" aria-haspopup="true" aria-expanded="true">Versions(1.0.0)<span class="caret"></span></a><ul id="package-dropdown-menu" class="dropdown-menu"><li><a class="main-nav-link" href=https://mxnet.incubator.apache.org/>1.1.0</a></li><li><a class="main-nav-link" href=https://mxnet.incubator.apache.org/versions/1.0.0/index.html>1.0.0</a></li><li><a class="main-nav-link" href=https://mxnet.incubator.apache.org/versions/0.12.1/index.html>0.12.1</a></li><li><a class="main-nav-link" href=https://mxnet.incubator.apache.org/versions/0.12.0/index.html>0.12.0</a></li><li><a class="main-nav-link" href=https://mxnet.incubator.apache.org/versions/0.11.0/index.html>0.11.0</a></li><li><a class="main-nav-link" href=https://mxnet.incubator.apache.org/versions/master/index.html>master</a></li></ul></span></nav>
<script> function getRootPath(){ return "../../../" } </script>
<div class="burgerIcon dropdown">
<a class="dropdown-toggle" data-toggle="dropdown" href="#" role="button">☰</a>
<ul class="dropdown-menu" id="burgerMenu">
<li><a href="../../../install/index.html">Install</a></li>
<li><a class="main-nav-link" href="../../../tutorials/index.html">Tutorials</a></li>
<li class="dropdown-submenu">
<a href="#" tabindex="-1">Community</a>
<ul class="dropdown-menu">
<li><a href="../../../community/index.html" tabindex="-1">Community</a></li>
<li><a href="../../../community/contribute.html" tabindex="-1">Contribute</a></li>
<li><a href="../../../community/powered_by.html" tabindex="-1">Powered By</a></li>
</ul>
</li>
<li class="dropdown-submenu">
<a href="#" tabindex="-1">API</a>
<ul class="dropdown-menu">
<li><a href="../../../api/python/index.html" tabindex="-1">Python</a>
</li>
<li><a href="../../../api/scala/index.html" tabindex="-1">Scala</a>
</li>
<li><a href="../../../api/r/index.html" tabindex="-1">R</a>
</li>
<li><a href="../../../api/julia/index.html" tabindex="-1">Julia</a>
</li>
<li><a href="../../../api/c++/index.html" tabindex="-1">C++</a>
</li>
<li><a href="../../../api/perl/index.html" tabindex="-1">Perl</a>
</li>
</ul>
</li>
<li class="dropdown-submenu">
<a href="#" tabindex="-1">Docs</a>
<ul class="dropdown-menu">
<li><a href="../../../tutorials/index.html" tabindex="-1">Tutorials</a></li>
<li><a href="../../../faq/index.html" tabindex="-1">FAQ</a></li>
<li><a href="../../../architecture/index.html" tabindex="-1">Architecture</a></li>
<li><a href="https://github.com/apache/incubator-mxnet/tree/1.0.0/example" tabindex="-1">Examples</a></li>
<li><a href="../../../model_zoo/index.html" tabindex="-1">Model Zoo</a></li>
</ul>
</li>
<li><a href="../../../architecture/index.html">Architecture</a></li>
<li><a class="main-nav-link" href="https://github.com/dmlc/mxnet">Github</a></li>
<li id="dropdown-menu-position-anchor-version-mobile" class="dropdown-submenu" style="position: relative"><a href="#" tabindex="-1">Versions(1.0.0)</a><ul class="dropdown-menu"><li><a tabindex="-1" href=https://mxnet.incubator.apache.org/>1.1.0</a></li><li><a tabindex="-1" href=https://mxnet.incubator.apache.org/versions/1.0.0/index.html>1.0.0</a></li><li><a tabindex="-1" href=https://mxnet.incubator.apache.org/versions/0.12.1/index.html>0.12.1</a></li><li><a tabindex="-1" href=https://mxnet.incubator.apache.org/versions/0.12.0/index.html>0.12.0</a></li><li><a tabindex="-1" href=https://mxnet.incubator.apache.org/versions/0.11.0/index.html>0.11.0</a></li><li><a tabindex="-1" href=https://mxnet.incubator.apache.org/versions/master/index.html>master</a></li></ul></li></ul>
</div>
<div class="plusIcon dropdown">
<a class="dropdown-toggle" data-toggle="dropdown" href="#" role="button"><span aria-hidden="true" class="glyphicon glyphicon-plus"></span></a>
<ul class="dropdown-menu dropdown-menu-right" id="plusMenu"></ul>
</div>
<div id="search-input-wrap">
<form action="../../../search.html" autocomplete="off" class="" method="get" role="search">
<div class="form-group inner-addon left-addon">
<i class="glyphicon glyphicon-search"></i>
<input class="form-control" name="q" placeholder="Search" type="text"/>
</div>
<input name="check_keywords" type="hidden" value="yes"/>
<input name="area" type="hidden" value="default">
</input></form>
<div id="search-preview"></div>
</div>
<div id="searchIcon">
<span aria-hidden="true" class="glyphicon glyphicon-search"></span>
</div>
<!-- <div id="lang-select-wrap"> -->
<!-- <label id="lang-select-label"> -->
<!-- <\!-- <i class="fa fa-globe"></i> -\-> -->
<!-- <span></span> -->
<!-- </label> -->
<!-- <select id="lang-select"> -->
<!-- <option value="en">Eng</option> -->
<!-- <option value="zh">中文</option> -->
<!-- </select> -->
<!-- </div> -->
<!-- <a id="mobile-nav-toggle">
<span class="mobile-nav-toggle-bar"></span>
<span class="mobile-nav-toggle-bar"></span>
<span class="mobile-nav-toggle-bar"></span>
</a> -->
</div>
</div>
</div>
<script type="text/javascript">
$('body').css('background', 'white');
</script>
<div class="container">
<div class="row">
<div aria-label="main navigation" class="sphinxsidebar leftsidebar" role="navigation">
<div class="sphinxsidebarwrapper">
<ul>
<li class="toctree-l1"><a class="reference internal" href="../../../api/python/index.html">Python Documents</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../api/r/index.html">R Documents</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../api/julia/index.html">Julia Documents</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../api/c++/index.html">C++ Documents</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../api/scala/index.html">Scala Documents</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../api/perl/index.html">Perl Documents</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../faq/index.html">HowTo Documents</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../architecture/index.html">System Documents</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/index.html">Tutorials</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../community/index.html">Community</a></li>
</ul>
</div>
</div>
<div class="content">
<div class="page-tracker"></div>
<h1>Source code for mxnet.module.python_module</h1><div class="highlight"><pre>
<span></span><span class="c1"># Licensed to the Apache Software Foundation (ASF) under one</span>
<span class="c1"># or more contributor license agreements. See the NOTICE file</span>
<span class="c1"># distributed with this work for additional information</span>
<span class="c1"># regarding copyright ownership. The ASF licenses this file</span>
<span class="c1"># to you under the Apache License, Version 2.0 (the</span>
<span class="c1"># "License"); you may not use this file except in compliance</span>
<span class="c1"># with the License. You may obtain a copy of the License at</span>
<span class="c1">#</span>
<span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c1">#</span>
<span class="c1"># Unless required by applicable law or agreed to in writing,</span>
<span class="c1"># software distributed under the License is distributed on an</span>
<span class="c1"># "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span>
<span class="c1"># KIND, either express or implied. See the License for the</span>
<span class="c1"># specific language governing permissions and limitations</span>
<span class="c1"># under the License.</span>
<span class="c1"># pylint: disable=too-many-instance-attributes, too-many-arguments</span>
<span class="sd">"""Provide some handy classes for user to implement a simple computation module</span>
<span class="sd">in Python easily.</span>
<span class="sd">"""</span>
<span class="kn">import</span> <span class="nn">logging</span>
<span class="kn">from</span> <span class="nn">.base_module</span> <span class="kn">import</span> <span class="n">BaseModule</span>
<span class="kn">from</span> <span class="nn">..initializer</span> <span class="kn">import</span> <span class="n">Uniform</span>
<span class="kn">from</span> <span class="nn">..</span> <span class="kn">import</span> <span class="n">ndarray</span> <span class="k">as</span> <span class="n">nd</span>
<div class="viewcode-block" id="PythonModule"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonModule">[docs]</a><span class="k">class</span> <span class="nc">PythonModule</span><span class="p">(</span><span class="n">BaseModule</span><span class="p">):</span>
<span class="sd">"""A convenient module class that implements many of the module APIs as</span>
<span class="sd"> empty functions.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> data_names : list of str</span>
<span class="sd"> Names of the data expected by the module.</span>
<span class="sd"> label_names : list of str</span>
<span class="sd"> Names of the labels expected by the module. Could be ``None`` if the</span>
<span class="sd"> module does not need labels.</span>
<span class="sd"> output_names : list of str</span>
<span class="sd"> Names of the outputs.</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data_names</span><span class="p">,</span> <span class="n">label_names</span><span class="p">,</span> <span class="n">output_names</span><span class="p">,</span> <span class="n">logger</span><span class="o">=</span><span class="n">logging</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">PythonModule</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">logger</span><span class="o">=</span><span class="n">logger</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data_names</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
<span class="n">data_names</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">data_names</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">label_names</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
<span class="n">label_names</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">label_names</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_data_names</span> <span class="o">=</span> <span class="n">data_names</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_label_names</span> <span class="o">=</span> <span class="n">label_names</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_output_names</span> <span class="o">=</span> <span class="n">output_names</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_data_shapes</span> <span class="o">=</span> <span class="bp">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_label_shapes</span> <span class="o">=</span> <span class="bp">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_output_shapes</span> <span class="o">=</span> <span class="bp">None</span>
<span class="c1">################################################################################</span>
<span class="c1"># Symbol information</span>
<span class="c1">################################################################################</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">data_names</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""A list of names for data required by this module."""</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_data_names</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">output_names</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""A list of names for the outputs of this module."""</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_output_names</span>
<span class="c1">################################################################################</span>
<span class="c1"># Input/Output information</span>
<span class="c1">################################################################################</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">data_shapes</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""A list of (name, shape) pairs specifying the data inputs to this module."""</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_data_shapes</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">label_shapes</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""A list of (name, shape) pairs specifying the label inputs to this module.</span>
<span class="sd"> If this module does not accept labels -- either it is a module without loss</span>
<span class="sd"> function, or it is not bound for training, then this should return an empty</span>
<span class="sd"> list ``[]```.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_label_shapes</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">output_shapes</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""A list of (name, shape) pairs specifying the outputs of this module."""</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_output_shapes</span>
<span class="c1">################################################################################</span>
<span class="c1"># Parameters of a module</span>
<span class="c1">################################################################################</span>
<div class="viewcode-block" id="PythonModule.get_params"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonModule.get_params">[docs]</a> <span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""Gets parameters, those are potentially copies of the the actual parameters used</span>
<span class="sd"> to do computation on the device. Subclass should override this method if contains</span>
<span class="sd"> parameters.</span>
<span class="sd"> Returns</span>
<span class="sd"> -------</span>
<span class="sd"> ``({}, {})``, a pair of empty dict.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="p">(</span><span class="nb">dict</span><span class="p">(),</span> <span class="nb">dict</span><span class="p">())</span></div>
<div class="viewcode-block" id="PythonModule.init_params"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonModule.init_params">[docs]</a> <span class="k">def</span> <span class="nf">init_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">initializer</span><span class="o">=</span><span class="n">Uniform</span><span class="p">(</span><span class="mf">0.01</span><span class="p">),</span> <span class="n">arg_params</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span> <span class="n">aux_params</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">allow_missing</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span> <span class="n">force_init</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span> <span class="n">allow_extra</span><span class="o">=</span><span class="bp">False</span><span class="p">):</span>
<span class="sd">"""Initializes the parameters and auxiliary states. By default this function</span>
<span class="sd"> does nothing. Subclass should override this method if contains parameters.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> initializer : Initializer</span>
<span class="sd"> Called to initialize parameters if needed.</span>
<span class="sd"> arg_params : dict</span>
<span class="sd"> If not ``None``, should be a dictionary of existing `arg_params`. Initialization</span>
<span class="sd"> will be copied from that.</span>
<span class="sd"> aux_params : dict</span>
<span class="sd"> If not ``None``, should be a dictionary of existing `aux_params`. Initialization</span>
<span class="sd"> will be copied from that.</span>
<span class="sd"> allow_missing : bool</span>
<span class="sd"> If ``True``, params could contain missing values, and the initializer will be</span>
<span class="sd"> called to fill those missing params.</span>
<span class="sd"> force_init : bool</span>
<span class="sd"> If ``True``, will force re-initialize even if already initialized.</span>
<span class="sd"> allow_extra : boolean, optional</span>
<span class="sd"> Whether allow extra parameters that are not needed by symbol.</span>
<span class="sd"> If this is True, no error will be thrown when arg_params or aux_params</span>
<span class="sd"> contain extra parameters that is not needed by the executor.</span>
<span class="sd"> """</span>
<span class="k">pass</span></div>
<div class="viewcode-block" id="PythonModule.update"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonModule.update">[docs]</a> <span class="k">def</span> <span class="nf">update</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""Updates parameters according to the installed optimizer and the gradients computed</span>
<span class="sd"> in the previous forward-backward batch. Currently we do nothing here. Subclass should</span>
<span class="sd"> override this method if contains parameters.</span>
<span class="sd"> """</span>
<span class="k">pass</span></div>
<div class="viewcode-block" id="PythonModule.update_metric"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonModule.update_metric">[docs]</a> <span class="k">def</span> <span class="nf">update_metric</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">eval_metric</span><span class="p">,</span> <span class="n">labels</span><span class="p">):</span>
<span class="sd">"""Evaluates and accumulates evaluation metric on outputs of the last forward computation.</span>
<span class="sd"> Subclass should override this method if needed.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> eval_metric : EvalMetric</span>
<span class="sd"> labels : list of NDArray</span>
<span class="sd"> Typically ``data_batch.label``.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_label_shapes</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="c1"># since we do not need labels, we are probably not a module with a loss</span>
<span class="c1"># function or predictions, so just ignore this call</span>
<span class="k">return</span>
<span class="c1"># by default we expect our outputs are some scores that could be evaluated</span>
<span class="n">eval_metric</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_outputs</span><span class="p">())</span></div>
<span class="c1">################################################################################</span>
<span class="c1"># module setup</span>
<span class="c1">################################################################################</span>
<div class="viewcode-block" id="PythonModule.bind"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonModule.bind">[docs]</a> <span class="k">def</span> <span class="nf">bind</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data_shapes</span><span class="p">,</span> <span class="n">label_shapes</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span> <span class="n">for_training</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span>
<span class="n">inputs_need_grad</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span> <span class="n">force_rebind</span><span class="o">=</span><span class="bp">False</span><span class="p">,</span> <span class="n">shared_module</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
<span class="n">grad_req</span><span class="o">=</span><span class="s1">'write'</span><span class="p">):</span>
<span class="sd">"""Binds the symbols to construct executors. This is necessary before one</span>
<span class="sd"> can perform computation with the module.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> data_shapes : list of (str, tuple)</span>
<span class="sd"> Typically is ``data_iter.provide_data``.</span>
<span class="sd"> label_shapes : list of (str, tuple)</span>
<span class="sd"> Typically is ``data_iter.provide_label``.</span>
<span class="sd"> for_training : bool</span>
<span class="sd"> Default is ``True``. Whether the executors should be bind for training.</span>
<span class="sd"> inputs_need_grad : bool</span>
<span class="sd"> Default is ``False``. Whether the gradients to the input data need to be computed.</span>
<span class="sd"> Typically this is not needed. But this might be needed when implementing composition</span>
<span class="sd"> of modules.</span>
<span class="sd"> force_rebind : bool</span>
<span class="sd"> Default is ``False``. This function does nothing if the executors are already</span>
<span class="sd"> bound. But with this ``True``, the executors will be forced to rebind.</span>
<span class="sd"> shared_module : Module</span>
<span class="sd"> Default is ``None``. This is used in bucketing. When not ``None``, the shared module</span>
<span class="sd"> essentially corresponds to a different bucket -- a module with different symbol</span>
<span class="sd"> but with the same sets of parameters (e.g. unrolled RNNs with different lengths).</span>
<span class="sd"> grad_req : str, list of str, dict of str to str</span>
<span class="sd"> Requirement for gradient accumulation. Can be 'write', 'add', or 'null'</span>
<span class="sd"> (default to 'write').</span>
<span class="sd"> Can be specified globally (str) or for each argument (list, dict).</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">binded</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">force_rebind</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="s1">'Already bound, ignoring bind()'</span><span class="p">)</span>
<span class="k">return</span>
<span class="k">assert</span> <span class="n">grad_req</span> <span class="o">==</span> <span class="s1">'write'</span><span class="p">,</span> <span class="s2">"Python module only support write gradient"</span>
<span class="bp">self</span><span class="o">.</span><span class="n">for_training</span> <span class="o">=</span> <span class="n">for_training</span>
<span class="bp">self</span><span class="o">.</span><span class="n">inputs_need_grad</span> <span class="o">=</span> <span class="n">inputs_need_grad</span>
<span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">data_shapes</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_data_names</span><span class="p">)</span>
<span class="k">assert</span> <span class="p">[</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">data_shapes</span><span class="p">]</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">_data_names</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_data_shapes</span> <span class="o">=</span> <span class="n">data_shapes</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_label_shapes</span> <span class="o">=</span> <span class="n">label_shapes</span>
<span class="k">if</span> <span class="n">label_shapes</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">_label_names</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span>
<span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_label_names</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">label_shapes</span><span class="p">)</span>
<span class="k">assert</span> <span class="p">[</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">label_shapes</span><span class="p">]</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">_label_names</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_output_shapes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_compute_output_shapes</span><span class="p">()</span></div>
<span class="k">def</span> <span class="nf">_compute_output_shapes</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""The subclass should implement this method to compute the shape of</span>
<span class="sd"> outputs. This method can assume that the ``data_shapes`` and ``label_shapes``</span>
<span class="sd"> are already initialized.</span>
<span class="sd"> """</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span>
<div class="viewcode-block" id="PythonModule.init_optimizer"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonModule.init_optimizer">[docs]</a> <span class="k">def</span> <span class="nf">init_optimizer</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kvstore</span><span class="o">=</span><span class="s1">'local'</span><span class="p">,</span> <span class="n">optimizer</span><span class="o">=</span><span class="s1">'sgd'</span><span class="p">,</span>
<span class="n">optimizer_params</span><span class="o">=</span><span class="p">((</span><span class="s1">'learning_rate'</span><span class="p">,</span> <span class="mf">0.01</span><span class="p">),),</span> <span class="n">force_init</span><span class="o">=</span><span class="bp">False</span><span class="p">):</span>
<span class="sd">"""Installs and initializes optimizers. By default we do nothing. Subclass should</span>
<span class="sd"> override this method if needed.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> kvstore : str or KVStore</span>
<span class="sd"> Default `'local'`.</span>
<span class="sd"> optimizer : str or Optimizer</span>
<span class="sd"> Default `'sgd'`</span>
<span class="sd"> optimizer_params : dict</span>
<span class="sd"> Default `(('learning_rate', 0.01),)`. The default value is not a dictionary,</span>
<span class="sd"> just to avoid pylint warning of dangerous default values.</span>
<span class="sd"> force_init : bool</span>
<span class="sd"> Default `False`, indicating whether we should force re-initializing the</span>
<span class="sd"> optimizer in the case an optimizer is already installed.</span>
<span class="sd"> """</span>
<span class="k">pass</span></div></div>
<div class="viewcode-block" id="PythonLossModule"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonLossModule">[docs]</a><span class="k">class</span> <span class="nc">PythonLossModule</span><span class="p">(</span><span class="n">PythonModule</span><span class="p">):</span>
<span class="sd">"""A convenient module class that implements many of the module APIs as</span>
<span class="sd"> empty functions.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> name : str</span>
<span class="sd"> Names of the module. The outputs will be named `[name + '_output']`.</span>
<span class="sd"> data_names : list of str</span>
<span class="sd"> Defaults to ``['data']``. Names of the data expected by this module.</span>
<span class="sd"> Should be a list of only one name.</span>
<span class="sd"> label_names : list of str</span>
<span class="sd"> Default ``['softmax_label']``. Names of the labels expected by the module.</span>
<span class="sd"> Should be a list of only one name.</span>
<span class="sd"> grad_func : function</span>
<span class="sd"> Optional. If not ``None``, should be a function that takes `scores`</span>
<span class="sd"> and `labels`, both of type `NDArray`, and return the gradients with</span>
<span class="sd"> respect to the scores according to this loss function. The return</span>
<span class="sd"> value could be a numpy array or an `NDArray`.</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">'pyloss'</span><span class="p">,</span> <span class="n">data_names</span><span class="o">=</span><span class="p">(</span><span class="s1">'data'</span><span class="p">,),</span> <span class="n">label_names</span><span class="o">=</span><span class="p">(</span><span class="s1">'softmax_label'</span><span class="p">,),</span>
<span class="n">logger</span><span class="o">=</span><span class="n">logging</span><span class="p">,</span> <span class="n">grad_func</span><span class="o">=</span><span class="bp">None</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">PythonLossModule</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">data_names</span><span class="p">,</span> <span class="n">label_names</span><span class="p">,</span>
<span class="p">[</span><span class="n">name</span> <span class="o">+</span> <span class="s1">'_output'</span><span class="p">],</span> <span class="n">logger</span><span class="o">=</span><span class="n">logger</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_name</span> <span class="o">=</span> <span class="n">name</span>
<span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">data_names</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span>
<span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">label_names</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_scores</span> <span class="o">=</span> <span class="bp">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_labels</span> <span class="o">=</span> <span class="bp">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_scores_grad</span> <span class="o">=</span> <span class="bp">None</span>
<span class="k">if</span> <span class="n">grad_func</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
<span class="k">assert</span> <span class="nb">callable</span><span class="p">(</span><span class="n">grad_func</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_grad_func</span> <span class="o">=</span> <span class="n">grad_func</span>
<span class="k">def</span> <span class="nf">_compute_output_shapes</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""Computes the shapes of outputs. As a loss module with outputs, we simply</span>
<span class="sd"> output whatever we receive as inputs (i.e. the scores).</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="p">[(</span><span class="bp">self</span><span class="o">.</span><span class="n">_name</span> <span class="o">+</span> <span class="s1">'_output'</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_data_shapes</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">])]</span>
<div class="viewcode-block" id="PythonLossModule.forward"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonLossModule.forward">[docs]</a> <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data_batch</span><span class="p">,</span> <span class="n">is_train</span><span class="o">=</span><span class="bp">None</span><span class="p">):</span>
<span class="sd">"""Forward computation. Here we do nothing but to keep a reference to</span>
<span class="sd"> the scores and the labels so that we can do backward computation.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> data_batch : DataBatch</span>
<span class="sd"> Could be anything with similar API implemented.</span>
<span class="sd"> is_train : bool</span>
<span class="sd"> Default is ``None``, which means `is_train` takes the value of ``self.for_training``.</span>
<span class="sd"> """</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_scores</span> <span class="o">=</span> <span class="n">data_batch</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">if</span> <span class="n">is_train</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">is_train</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">for_training</span>
<span class="k">if</span> <span class="n">is_train</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_labels</span> <span class="o">=</span> <span class="n">data_batch</span><span class="o">.</span><span class="n">label</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span></div>
<div class="viewcode-block" id="PythonLossModule.get_outputs"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonLossModule.get_outputs">[docs]</a> <span class="k">def</span> <span class="nf">get_outputs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">merge_multi_context</span><span class="o">=</span><span class="bp">True</span><span class="p">):</span>
<span class="sd">"""Gets outputs of the previous forward computation. As a output loss module,</span>
<span class="sd"> we treat the inputs to this module as scores, and simply return them.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> merge_multi_context : bool</span>
<span class="sd"> Should always be ``True``, because we do not use multiple contexts for computing.</span>
<span class="sd"> """</span>
<span class="k">assert</span> <span class="n">merge_multi_context</span> <span class="ow">is</span> <span class="bp">True</span>
<span class="k">return</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_scores</span><span class="p">]</span></div>
<div class="viewcode-block" id="PythonLossModule.backward"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonLossModule.backward">[docs]</a> <span class="k">def</span> <span class="nf">backward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">out_grads</span><span class="o">=</span><span class="bp">None</span><span class="p">):</span>
<span class="sd">"""Backward computation.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> out_grads : NDArray or list of NDArray, optional</span>
<span class="sd"> Gradient on the outputs to be propagated back.</span>
<span class="sd"> This parameter is only needed when bind is called</span>
<span class="sd"> on outputs that are not a loss function.</span>
<span class="sd"> """</span>
<span class="k">assert</span> <span class="n">out_grads</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">,</span> <span class="s1">'For a loss module, out_grads should be None'</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">for_training</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_backward_impl</span><span class="p">()</span></div>
<span class="k">def</span> <span class="nf">_backward_impl</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""Actual implementation of the backward computation. The computation</span>
<span class="sd"> should take ``self._scores`` and ``self._labels`` and then compute the</span>
<span class="sd"> gradients with respect to the scores, store it as an `NDArray` in</span>
<span class="sd"> ``self._scores_grad``.</span>
<span class="sd"> Instead of defining a subclass and overriding this function,</span>
<span class="sd"> a more convenient way is to pass in a `grad_func` when constructing</span>
<span class="sd"> the module object. Then it will be called to compute the gradients.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_grad_func</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">grad</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_grad_func</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_scores</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_labels</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">grad</span><span class="p">,</span> <span class="n">nd</span><span class="o">.</span><span class="n">NDArray</span><span class="p">):</span>
<span class="n">grad</span> <span class="o">=</span> <span class="n">nd</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">grad</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_scores_grad</span> <span class="o">=</span> <span class="n">grad</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span>
<div class="viewcode-block" id="PythonLossModule.get_input_grads"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonLossModule.get_input_grads">[docs]</a> <span class="k">def</span> <span class="nf">get_input_grads</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">merge_multi_context</span><span class="o">=</span><span class="bp">True</span><span class="p">):</span>
<span class="sd">"""Gets the gradients to the inputs, computed in the previous backward computation.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> merge_multi_context : bool</span>
<span class="sd"> Should always be ``True`` because we do not use multiple context for computation.</span>
<span class="sd"> """</span>
<span class="k">assert</span> <span class="n">merge_multi_context</span> <span class="ow">is</span> <span class="bp">True</span>
<span class="k">return</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_scores_grad</span><span class="p">]</span></div>
<div class="viewcode-block" id="PythonLossModule.install_monitor"><a class="viewcode-back" href="../../../api/python/module/module.html#mxnet.module.PythonLossModule.install_monitor">[docs]</a> <span class="k">def</span> <span class="nf">install_monitor</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">mon</span><span class="p">):</span>
<span class="sd">"""Installs monitor on all executors."""</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span></div></div>
</pre></div>
</div>
</div>
<div aria-label="main navigation" class="sphinxsidebar rightsidebar" role="navigation">
<div class="sphinxsidebarwrapper">
</div>
</div>
</div><div class="footer">
<div class="section-disclaimer">
<div class="container">
<div>
<img height="60" src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/apache_incubator_logo.png"/>
<p>
Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), <strong>sponsored by the <i>Apache Incubator</i></strong>. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
</p>
<p>
"Copyright © 2017, The Apache Software Foundation
Apache MXNet, MXNet, Apache, the Apache feather, and the Apache MXNet project logo are either registered trademarks or trademarks of the Apache Software Foundation."
</p>
</div>
</div>
</div>
</div> <!-- pagename != index -->
</div>
<script crossorigin="anonymous" integrity="sha384-0mSbJDEHialfmuBBQP6A4Qrprq5OVfW37PRR3j5ELqxss1yVqOtnepnHVP9aJ7xS" src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/js/bootstrap.min.js"></script>
<script src="../../../_static/js/sidebar.js" type="text/javascript"></script>
<script src="../../../_static/js/search.js" type="text/javascript"></script>
<script src="../../../_static/js/navbar.js" type="text/javascript"></script>
<script src="../../../_static/js/clipboard.min.js" type="text/javascript"></script>
<script src="../../../_static/js/copycode.js" type="text/javascript"></script>
<script src="../../../_static/js/page.js" type="text/javascript"></script>
<script type="text/javascript">
$('body').ready(function () {
$('body').css('visibility', 'visible');
});
</script>
</body>
</html>