Log In Sign Up
Models:
Amanda Davis
Amanda-D/
DeepPurpose
0
Downloads: 1
[0a9449]: / docs / build / html / notes / cnn.html

Download this file

155 lines (118 with data), 6.8 kB 

  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
<!DOCTYPE html>



<html xmlns="http://www.w3.org/1999/xhtml">

  <head>

    <meta charset="utf-8" />

    <title>CNN &#8212; DeepPurpose 0.0.1 documentation</title>

    <link rel="stylesheet" href="../_static/alabaster.css" type="text/css" />

    <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />

    <script id="documentation_options" data-url_root="../" 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/language_data.js"></script>

    <link rel="index" title="Index" href="../genindex.html" />

    <link rel="search" title="Search" href="../search.html" />

    <link rel="next" title="MLP" href="mlp.html" />

    <link rel="prev" title="CNN+RNN" href="cnnrnn.html" />

   

  <link rel="stylesheet" href="../_static/custom.css" type="text/css" />

  

  

  <meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />



  </head><body>

  



    <div class="document">

      <div class="documentwrapper">

        <div class="bodywrapper">

          



          <div class="body" role="main">

            

  <div class="section" id="cnn">

<h1>CNN<a class="headerlink" href="#cnn" title="Permalink to this headline"></a></h1>

<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">DeepPurpose</span><span class="o">.</span><span class="n">models</span><span class="o">.</span><span class="n">CNN</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">)</span>

</pre></div>

</div>

<p><a class="reference external" href="https://en.wikipedia.org/wiki/Convolutional_neural_network">CNN (Convolutional Neural Network)</a> can be used to encode both drug and protein on <a class="reference external" href="https://en.wikipedia.org/wiki/Simplified_molecular-input_line-entry_system">SMILES</a>.</p>

<p><strong>constructor</strong> create CNN.</p>

<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">encoding</span><span class="p">,</span> <span class="o">**</span><span class="n">config</span><span class="p">)</span>

</pre></div>

</div>

<ul class="simple">

<li><p><strong>encoding</strong> (string, “drug” or “protein”) - specify input type of model, “drug” or “protein”.</p></li>

<li><dl class="simple">

<dt><strong>config</strong> (kwargs, keyword arguments) - specify the parameter of CNN. The keys include</dt><dd><ul>

<li><p>cnn_drug_filters (list, each element is int) - specify the size of filter when encoding drug, e.g., cnn_drug_filters = [32,64,96].</p></li>

<li><p>cnn_drug_kernels (list, each element is int) - specify the size of kernel when encoding drug, e.g., cnn_drug_kernels = [4,6,8].</p></li>

<li><p>hidden_dim_drug (int) - specify the hidden dimension when encoding drug, e.g., hidden_dim_drug = 256.</p></li>

<li><p>cnn_target_filters (list, each element is int) - specify the size of filter when encoding protein, e.g, cnn_target_filters = [32,64,96].</p></li>

<li><p>cnn_target_kernels (list, each element is int) - specify the size of kernel when encoding protein, e.g, cnn_target_kernels = [4,8,12].</p></li>

<li><p>hidden_dim_protein (int) - specify the hidden dimension when encoding protein, e.g., hidden_dim_protein = 256.</p></li>

</ul>

</dd>

</dl>

</li>

</ul>

<p><strong>Calling functions</strong> implement the feedforward procedure of CNN.</p>

<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">v</span><span class="p">)</span>

</pre></div>

</div>

<ul class="simple">

<li><p><strong>v</strong> (torch.Tensor) - input feature of CNN.</p></li>

</ul>

</div>





          </div>

          

        </div>

      </div>

      <div class="sphinxsidebar" role="navigation" aria-label="main navigation">

        <div class="sphinxsidebarwrapper">

<h1 class="logo"><a href="../index.html">DeepPurpose</a></h1>

















<h3>Navigation</h3>

<p class="caption"><span class="caption-text">Background</span></p>

<ul>

<li class="toctree-l1"><a class="reference internal" href="introduction.html">Feature of DeepPurpose</a></li>

<li class="toctree-l1"><a class="reference internal" href="DTI.html">What is Drug Target Interaction?</a></li>

</ul>

<p class="caption"><span class="caption-text">How to run</span></p>

<ul>

<li class="toctree-l1"><a class="reference internal" href="download.html">Download</a></li>

<li class="toctree-l1"><a class="reference internal" href="installation.html">Installation</a></li>

<li class="toctree-l1"><a class="reference internal" href="casestudy.html">Case Study</a></li>

</ul>

<p class="caption"><span class="caption-text">Package Reference</span></p>

<ul class="current">

<li class="toctree-l1"><a class="reference internal" href="model.html">Model</a></li>

<li class="toctree-l1 current"><a class="reference internal" href="encoder.html">Drug/Target Encoder</a></li>

<li class="toctree-l1"><a class="reference internal" href="process_data.html">Processing Data</a></li>

<li class="toctree-l1"><a class="reference internal" href="configuration.html">Configuration</a></li>

<li class="toctree-l1"><a class="reference internal" href="utility_function.html">Utility Function</a></li>

</ul>



<div class="relations">

<h3>Related Topics</h3>

<ul>

  <li><a href="../index.html">Documentation overview</a><ul>

  <li><a href="encoder.html">Drug/Target Encoder</a><ul>

      <li>Previous: <a href="cnnrnn.html" title="previous chapter">CNN+RNN</a></li>

      <li>Next: <a href="mlp.html" title="next chapter">MLP</a></li>

  </ul></li>

  </ul></li>

</ul>

</div>

<div id="searchbox" style="display: none" role="search">

  <h3 id="searchlabel">Quick search</h3>

    <div class="searchformwrapper">

    <form class="search" action="../search.html" method="get">

      <input type="text" name="q" aria-labelledby="searchlabel" />

      <input type="submit" value="Go" />

    </form>

    </div>

</div>

<script>$('#searchbox').show(0);</script>

















        </div>

      </div>

      <div class="clearer"></div>

    </div>

    <div class="footer">

      &copy;2020, Kexin Huang, Tianfan Fu.

      

      |

      Powered by <a href="http://sphinx-doc.org/">Sphinx 3.0.0</a>

      &amp; <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.12</a>

      

      |

      <a href="../_sources/notes/cnn.rst.txt"

          rel="nofollow">Page source</a>

    </div>



    



    

  </body>

</html>