Deci-AI
/
super-gradients
connected to https://github.com/Deci-AI/super-gradients.git


  
1

	
2

	
3

	
4

	
5

	
6

	
7

	
8

	
9

	
10

	
11

	
12

	
13

	
14

	
15

	
16

	
17

	
18

	
19

	
20

	
21

	
22

	
23

	
24

	
25

	
26

	
27

	
28

	
29

	
30

	
31

	
32

	
33

	
34

	
35

	
36

	
37

	
38

	
39

	
40

	
41

	
42

	
43

	
44

	
45

	
46

	
47

	
48

	
49

	
50

	
51

	
52

	
53

	
54

	
55

	
56

	
57

	
58

	
59

	
60

	
61

	
62

	
63

	
64

	
65

	
66

	
67

	
68

	
69

	
70

	
71

	
72

	
73

	
74

	
75

	
76

	
77

	
78

	
79

	
80

	
81

	
82

	
83

	
84

	
85

	
86

	
87

	
88

	
89

	
90

	
91

	
92

	
93

	
94

	
95

	
96

	
97

	
98

	
99

	
100

	
101

	
102

	
103

	
104

	
105

	
106

	
107

	
108

	
109

	
110

	
111

	
112

	
113

	
114

	
115

	
116

	
117

	
118

	
119

	
120

	
121

	
122

	
123

	
124

	
125

	
126

	
127

	
128

	
129

	
130

	
131

	
132

	
133

	
134

	
135

	
136

	
137

	
138

	
139

	
140

	
141

	
142

	
143

	
144

	
145

	
146

	
147

	
148

	
149

	
150

	
151

	
152

	
153

	
154

	
155

	
156

	
157

	
158

	
159

	
160

	
161

	
162

	
163

	
164

	
165

	
166

	
167

	
168

	
169

	
170

	
171

	
172

	
173

	
174

	
175

	
176

	
177

	
178

	
179

	
180

	
181

	
182

	
183

	
            <!DOCTYPE html>
<html class="writer-html5" lang="en" >
<head>
  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />

  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
  <title>super_gradients.training.utils.optimizers package &mdash; SuperGradients 1.0 documentation</title>
      <link rel="stylesheet" href="_static/pygments.css" type="text/css" />
      <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
  <!--[if lt IE 9]>
    <script src="_static/js/html5shiv.min.js"></script>
  <![endif]-->
  
        <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
        <script src="_static/jquery.js"></script>
        <script src="_static/underscore.js"></script>
        <script src="_static/doctools.js"></script>
    <script src="_static/js/theme.js"></script>
    <link rel="index" title="Index" href="genindex.html" />
    <link rel="search" title="Search" href="search.html" />
    <link rel="prev" title="super_gradients.training.utils package" href="super_gradients.training.utils.html" /> 
</head>

<body class="wy-body-for-nav"> 
  <div class="wy-grid-for-nav">
    <nav data-toggle="wy-nav-shift" class="wy-nav-side">
      <div class="wy-side-scroll">
        <div class="wy-side-nav-search" >
            <a href="index.html" class="icon icon-home"> SuperGradients
          </a>
<div role="search">
  <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
    <input type="text" name="q" placeholder="Search docs" />
    <input type="hidden" name="check_keywords" value="yes" />
    <input type="hidden" name="area" value="default" />
  </form>
</div>
        </div><div class="wy-menu wy-menu-vertical" data-spy="affix" role="navigation" aria-label="Navigation menu">
              <p class="caption"><span class="caption-text">Contents:</span></p>
<ul class="current">
<li class="toctree-l1"><a class="reference internal" href="intro.html">Introduction</a></li>
<li class="toctree-l1"><a class="reference internal" href="intro.html#installation">Installation</a></li>
<li class="toctree-l1 current"><a class="reference internal" href="super_gradients.training.html">super_gradients.training package</a><ul class="current">
<li class="toctree-l2 current"><a class="reference internal" href="super_gradients.training.html#subpackages">Subpackages</a><ul class="current">
<li class="toctree-l3"><a class="reference internal" href="super_gradients.training.datasets.html">super_gradients.training.datasets package</a></li>
<li class="toctree-l3"><a class="reference internal" href="super_gradients.training.exceptions.html">super_gradients.training.exceptions package</a></li>
<li class="toctree-l3"><a class="reference internal" href="super_gradients.training.legacy.html">super_gradients.training.legacy package</a></li>
<li class="toctree-l3"><a class="reference internal" href="super_gradients.training.losses.html">super_gradients.training.losses package</a></li>
<li class="toctree-l3"><a class="reference internal" href="super_gradients.training.metrics.html">super_gradients.training.metrics package</a></li>
<li class="toctree-l3"><a class="reference internal" href="super_gradients.training.models.html">super_gradients.training.models package</a></li>
<li class="toctree-l3"><a class="reference internal" href="super_gradients.training.sg_model.html">super_gradients.training.sg_model package</a></li>
<li class="toctree-l3 current"><a class="reference internal" href="super_gradients.training.utils.html">super_gradients.training.utils package</a><ul class="current">
<li class="toctree-l4 current"><a class="reference internal" href="super_gradients.training.utils.html#subpackages">Subpackages</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#submodules">Submodules</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.callbacks">super_gradients.training.utils.callbacks module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.checkpoint_utils">super_gradients.training.utils.checkpoint_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.detection_utils">super_gradients.training.utils.detection_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.distributed_training_utils">super_gradients.training.utils.distributed_training_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.early_stopping">super_gradients.training.utils.early_stopping module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.ema">super_gradients.training.utils.ema module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.export_utils">super_gradients.training.utils.export_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#super-gradients-training-utils-get-model-stats-module">super_gradients.training.utils.get_model_stats module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.module_utils">super_gradients.training.utils.module_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.optimizer_utils">super_gradients.training.utils.optimizer_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.regularization_utils">super_gradients.training.utils.regularization_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.segmentation_utils">super_gradients.training.utils.segmentation_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.sg_model_utils">super_gradients.training.utils.sg_model_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.ssd_utils">super_gradients.training.utils.ssd_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.utils">super_gradients.training.utils.utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils.weight_averaging_utils">super_gradients.training.utils.weight_averaging_utils module</a></li>
<li class="toctree-l4"><a class="reference internal" href="super_gradients.training.utils.html#module-super_gradients.training.utils">Module contents</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="super_gradients.training.html#submodules">Submodules</a></li>
<li class="toctree-l2"><a class="reference internal" href="super_gradients.training.html#module-super_gradients.training.params">super_gradients.training.params module</a></li>
<li class="toctree-l2"><a class="reference internal" href="super_gradients.training.html#module-super_gradients.training.pretrained_models">super_gradients.training.pretrained_models module</a></li>
<li class="toctree-l2"><a class="reference internal" href="super_gradients.training.html#module-super_gradients.training">Module contents</a></li>
</ul>
</li>
</ul>

        </div>
      </div>
    </nav>

    <section data-toggle="wy-nav-shift" class="wy-nav-content-wrap"><nav class="wy-nav-top" aria-label="Mobile navigation menu" >
          <i data-toggle="wy-nav-top" class="fa fa-bars"></i>
          <a href="index.html">SuperGradients</a>
      </nav>

      <div class="wy-nav-content">
        <div class="rst-content">
          <div role="navigation" aria-label="Page navigation">
  <ul class="wy-breadcrumbs">
      <li><a href="index.html" class="icon icon-home"></a> &raquo;</li>
          <li><a href="super_gradients.training.html">super_gradients.training package</a> &raquo;</li>
          <li><a href="super_gradients.training.utils.html">super_gradients.training.utils package</a> &raquo;</li>
      <li>super_gradients.training.utils.optimizers package</li>
      <li class="wy-breadcrumbs-aside">
            <a href="_sources/super_gradients.training.utils.optimizers.rst.txt" rel="nofollow"> View page source</a>
      </li>
  </ul>
  <hr/>
</div>
          <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
           <div itemprop="articleBody">
             
  <section id="super-gradients-training-utils-optimizers-package">
<h1>super_gradients.training.utils.optimizers package<a class="headerlink" href="#super-gradients-training-utils-optimizers-package" title="Permalink to this headline"></a></h1>
<section id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
</section>
<section id="module-super_gradients.training.utils.optimizers.rmsprop_tf">
<span id="super-gradients-training-utils-optimizers-rmsprop-tf-module"></span><h2>super_gradients.training.utils.optimizers.rmsprop_tf module<a class="headerlink" href="#module-super_gradients.training.utils.optimizers.rmsprop_tf" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="super_gradients.training.utils.optimizers.rmsprop_tf.RMSpropTF">
<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">super_gradients.training.utils.optimizers.rmsprop_tf.</span></span><span class="sig-name descname"><span class="pre">RMSpropTF</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lr</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.01</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.9</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1e-10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weight_decay</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">momentum</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">centered</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">decoupled_decay</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lr_in_momentum</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/utils/optimizers/rmsprop_tf.html#RMSpropTF"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.utils.optimizers.rmsprop_tf.RMSpropTF" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">torch.optim.optimizer.Optimizer</span></code></p>
<p>Implements RMSprop algorithm (TensorFlow style epsilon)
NOTE: This is a direct cut-and-paste of PyTorch RMSprop with eps applied before sqrt
and a few other modifications to closer match Tensorflow for matching hyper-params.
Noteworthy changes include:
1. Epsilon applied inside square-root
2. square_avg initialized to ones
3. LR scaling of update accumulated in momentum buffer
Proposed by G. Hinton in his
<a class="reference external" href="http://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf">course</a>.
The centered version first appears in <a class="reference external" href="https://arxiv.org/pdf/1308.0850v5.pdf">Generating Sequences
With Recurrent Neural Networks</a>.</p>
<dl class="py method">
<dt class="sig sig-object py" id="super_gradients.training.utils.optimizers.rmsprop_tf.RMSpropTF.step">
<span class="sig-name descname"><span class="pre">step</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">closure</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/super_gradients/training/utils/optimizers/rmsprop_tf.html#RMSpropTF.step"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#super_gradients.training.utils.optimizers.rmsprop_tf.RMSpropTF.step" title="Permalink to this definition"></a></dt>
<dd><p>Performs a single optimization step.
Arguments:</p>
<blockquote>
<div><dl class="simple">
<dt>closure (callable, optional): A closure that reevaluates the model</dt><dd><p>and returns the loss.</p>
</dd>
</dl>
</div></blockquote>
</dd></dl>

</dd></dl>

</section>
<section id="module-super_gradients.training.utils.optimizers">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-super_gradients.training.utils.optimizers" title="Permalink to this headline"></a></h2>
</section>
</section>


           </div>
          </div>
          <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
        <a href="super_gradients.training.utils.html" class="btn btn-neutral float-left" title="super_gradients.training.utils package" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
    </div>

  <hr/>

  <div role="contentinfo">
    <p>&#169; Copyright 2021, SuperGradients team.</p>
  </div>

  Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a
    <a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
    provided by <a href="https://readthedocs.org">Read the Docs</a>.
   

</footer>
        </div>
      </div>
    </section>
  </div>
  <script>
      jQuery(function () {
          SphinxRtdTheme.Navigation.enable(true);
      });
  </script> 

</body>
</html>