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authorAli Labbene <ali.labbene@st.com>2019-12-11 08:59:21 +0100
committerAli Labbene <ali.labbene@st.com>2019-12-16 16:35:24 +0100
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Official ARM version: v5.4.0
Add CMSIS V5.4.0, please refer to index.html available under \docs folder. Note: content of \CMSIS\Core\Include has been copied under \Include to keep the same structure used in existing projects, and thus avoid projects mass update Note: the following components have been removed from ARM original delivery (as not used in ST packages) - CMSIS_EW2018.pdf - .gitattributes - .gitignore - \Device - \CMSIS - \CoreValidation - \DAP - \Documentation - \DoxyGen - \Driver - \Pack - \RTOS\CMSIS_RTOS_Tutorial.pdf - \RTOS\RTX - \RTOS\Template - \RTOS2\RTX - \Utilities - All ARM/GCC projects files are deleted from \DSP, \RTOS and \RTOS2 Change-Id: Ia026c3f0f0d016627a4fb5a9032852c33d24b4d3
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+<title>Convolutional Neural Network Example</title>
+<title>CMSIS-NN: Convolutional Neural Network Example</title>
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+ <div id="projectname">CMSIS-NN
+ &#160;<span id="projectnumber">Version 1.1.0</span>
+ </div>
+ <div id="projectbrief">CMSIS NN Software Library</div>
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+<div class="title">Convolutional Neural Network Example</div> </div>
+</div><!--header-->
+<div class="contents">
+<dl class="section user"><dt>Description:</dt><dd></dd></dl>
+<dl class="section user"><dt></dt><dd>Demonstrates a convolutional neural network (CNN) example with the use of convolution, ReLU activation, pooling and fully-connected functions.</dd></dl>
+<dl class="section user"><dt>Model definition:</dt><dd></dd></dl>
+<dl class="section user"><dt></dt><dd>The CNN used in this example is based on CIFAR-10 example from Caffe [1]. The neural network consists of 3 convolution layers interspersed by ReLU activation and max pooling layers, followed by a fully-connected layer at the end. The input to the network is a 32x32 pixel color image, which will be classified into one of the 10 output classes. This example model implementation needs 32.3 KB to store weights, 40 KB for activations and 3.1 KB for storing the <code>im2col</code> data.</dd></dl>
+<div class="image">
+<img src="CIFAR10_CNN.gif" alt="CIFAR10_CNN.gif"/>
+<div class="caption">
+Neural Network model definition</div></div>
+ <dl class="section user"><dt>Variables Description:</dt><dd></dd></dl>
+<dl class="section user"><dt></dt><dd><ul>
+<li><code>conv1_wt</code>, <code>conv2_wt</code>, <code>conv3_wt</code> are convolution layer weight matrices </li>
+<li><code>conv1_bias</code>, <code>conv2_bias</code>, <code>conv3_bias</code> are convolution layer bias arrays </li>
+<li><code>ip1_wt</code>, ip1_bias point to fully-connected layer weights and biases </li>
+<li><code>input_data</code> points to the input image data </li>
+<li><code>output_data</code> points to the classification output </li>
+<li><code>col_buffer</code> is a buffer to store the <code>im2col</code> output </li>
+<li><code>scratch_buffer</code> is used to store the activation data (intermediate layer outputs)</li>
+</ul>
+</dd></dl>
+<dl class="section user"><dt>CMSIS DSP Software Library Functions Used:</dt><dd></dd></dl>
+<dl class="section user"><dt></dt><dd><ul>
+<li><a class="el" href="group__NNConv.html#ga98f2ead67d7cbdf558b0cd8a3b8fc148" title="Q7 version of convolution for RGB image. ">arm_convolve_HWC_q7_RGB()</a></li>
+<li><a class="el" href="group__NNConv.html#gae00d3c1285907d59657369fc98bcc83f" title="Fast Q7 convolution function. ">arm_convolve_HWC_q7_fast()</a></li>
+<li><a class="el" href="group__Acti.html#ga638e803b4fe00426f401783a6255ca30" title="Q7 RELU function. ">arm_relu_q7()</a></li>
+<li><a class="el" href="group__Pooling.html#ga99afcdcc61eaf429ab3ee823702e44ce" title="Q7 max pooling function. ">arm_maxpool_q7_HWC()</a></li>
+<li><a class="el" href="group__Pooling.html#gae4a7b07f97ec4313524c9fb9fbcb1f6a" title="Q7 average pooling function. ">arm_avepool_q7_HWC()</a></li>
+<li><a class="el" href="group__FC.html#gaf82b71ef472a38f8fc9ac414d9d07e67" title="Q7 opt fully-connected layer function. ">arm_fully_connected_q7_opt()</a></li>
+<li><a class="el" href="group__FC.html#ga8b7e0c2e989e8c75f0dc789f3115323d" title="Q7 basic fully-connected layer function. ">arm_fully_connected_q7()</a></li>
+</ul>
+</dd></dl>
+<p><b> Refer </b> <a class="el" href="arm__nnexamples__cifar10_8cpp.html">arm_nnexamples_cifar10.cpp</a></p>
+<dl class="section user"><dt>[1] https://github.com/BVLC/caffe</dt><dd></dd></dl>
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