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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><pre class="fragment">Wrapper for a Data Augmentation module and a model.
Attributes:
_mods (nn.ModuleDict): A dictionary containing the modules.
_data_augmentation (bool): Wether data augmentation should be used.
</pre> </div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="a057f438ee15dcd93cb6040b7389e3785"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a057f438ee15dcd93cb6040b7389e3785">&#9670;&nbsp;</a></span>__init__()</h2>
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<td class="memname">def dataug.Augmented_model.__init__ </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>data_augmenter</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>model</em>&#160;</td>
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<td></td>
<td>)</td>
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<pre class="fragment">Init Augmented Model.
By default, data augmentation will be performed.
Args:
data_augmenter (nn.Module): Data augmentation module.
model (nn.Module): Network.
</pre>
</div>
</div>
<h2 class="groupheader">Member Function Documentation</h2>
<a id="ad4adbd067e1370602884983ed2f751fa"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad4adbd067e1370602884983ed2f751fa">&#9670;&nbsp;</a></span>__getitem__()</h2>
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<td class="memname">def dataug.Augmented_model.__getitem__ </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>key</em>&#160;</td>
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<td></td>
<td>)</td>
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</tr>
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<pre class="fragment">Access to the modules.
Args:
key (string): Name of the module to access.
Returns:
nn.Module.
</pre>
</div>
</div>
<a id="a875e90c6e69ec6bf1233a80ba97b1791"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a875e90c6e69ec6bf1233a80ba97b1791">&#9670;&nbsp;</a></span>__str__()</h2>
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<td class="memname">def dataug.Augmented_model.__str__ </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em></td><td>)</td>
<td></td>
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<pre class="fragment">Name of the module
Returns:
String containing the name of the module as well as the higher levels parameters.
</pre>
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<a id="af5fae5304c9d75f50ffc4ee1ac7db9ac"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af5fae5304c9d75f50ffc4ee1ac7db9ac">&#9670;&nbsp;</a></span>augment()</h2>
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<td class="memname">def dataug.Augmented_model.augment </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>mode</em> = <code>True</code>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
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</div><div class="memdoc">
<pre class="fragment">Set the augmentation mode.
Args:
mode (bool): Wether to perform data augmentation on the forward pass. (default: True)
</pre>
</div>
</div>
<a id="aff7c48066b6c81cccfdab4bc68b696eb"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aff7c48066b6c81cccfdab4bc68b696eb">&#9670;&nbsp;</a></span>eval()</h2>
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<td class="memname">def dataug.Augmented_model.eval </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em></td><td>)</td>
<td></td>
</tr>
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</div><div class="memdoc">
<pre class="fragment">Set the module to evaluation mode.
</pre>
</div>
</div>
<a id="ad49e8b4696636766d9f7a31aeb497182"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad49e8b4696636766d9f7a31aeb497182">&#9670;&nbsp;</a></span>forward()</h2>
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<td class="memname">def dataug.Augmented_model.forward </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>x</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
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<pre class="fragment">Main method of the Augmented model.
Perform the forward pass of both modules.
Args:
x (Tensor): Batch of data.
Returns:
Tensor : Output of the networks. Should be logits.
</pre>
</div>
</div>
<a id="a0452448f74cc24e6a9c3564a6d8bf5c7"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a0452448f74cc24e6a9c3564a6d8bf5c7">&#9670;&nbsp;</a></span>is_augmenting()</h2>
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<td class="memname">def dataug.Augmented_model.is_augmenting </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em></td><td>)</td>
<td></td>
</tr>
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</div><div class="memdoc">
<pre class="fragment">Return wether data augmentation is applied.
Returns:
bool : True if data augmentation is applied.
</pre>
</div>
</div>
<a id="a8604cb4a03363f3631b3321d531484e3"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a8604cb4a03363f3631b3321d531484e3">&#9670;&nbsp;</a></span>items()</h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
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<td class="memname">def dataug.Augmented_model.items </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em></td><td>)</td>
<td></td>
</tr>
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</div><div class="memdoc">
<pre class="fragment">Return an iterable of the ModuleDict key/value pairs.
</pre>
</div>
</div>
<a id="a1b9db2dc8c0f15bcb8185d23bb126d5f"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a1b9db2dc8c0f15bcb8185d23bb126d5f">&#9670;&nbsp;</a></span>TF_names()</h2>
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<td class="memname">def dataug.Augmented_model.TF_names </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em></td><td>)</td>
<td></td>
</tr>
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</div><div class="memdoc">
<pre class="fragment">Get the transformations names used by the data augmentation module.
Returns:
list : names of the transformations of the data augmentation module.
</pre>
</div>
</div>
<a id="afec6a703c32dc59eb23e9ae23358be07"></a>
<h2 class="memtitle"><span class="permalink"><a href="#afec6a703c32dc59eb23e9ae23358be07">&#9670;&nbsp;</a></span>train()</h2>
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<td class="memname">def dataug.Augmented_model.train </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>mode</em> = <code>True</code>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
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<pre class="fragment">Set the module training mode.
Args:
mode (bool): Wether to learn the parameter of the module. (default: None)
</pre>
</div>
</div>
<a id="a399dd88785d6f9f8f01a4d562ae1f015"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a399dd88785d6f9f8f01a4d562ae1f015">&#9670;&nbsp;</a></span>update()</h2>
<div class="memitem">
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<td class="memname">def dataug.Augmented_model.update </td>
<td>(</td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>self</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">&#160;</td>
<td class="paramname"><em>modules</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
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</div><div class="memdoc">
<pre class="fragment">Update the module dictionnary.
The new dictionnary should keep the same structure.
</pre>
</div>
</div>
<hr/>The documentation for this class was generated from the following file:<ul>
<li>/home/antoineh/github/smart_augmentation/higher/smart_aug/dataug.py</li>
</ul>
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