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| <a href="_deserializer_support_8md.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> # The layers that ArmNN SDK Deserializer currently supports.</div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> </div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> This reference guide provides a list of layers which can be deserialized currently by the Arm NN SDK.</div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> </div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> ## Fully supported</div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> The Arm NN SDK Deserialize parser currently supports the following layers:</div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> * Abs</div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> * Activation</div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> * Addition</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> * ArgMinMax</div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> * BatchToSpaceNd</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> * BatchNormalization</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> * Concat</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> * Comparison</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> * Constant</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> * Convolution2d</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> * DepthToSpace</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> * DepthwiseConvolution2d</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> * Dequantize</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> * DetectionPostProcess</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> * Division</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> * ElementwiseUnary</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> * Floor</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> * FullyConnected</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> * Gather</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> * Input</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> * InstanceNormalization</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> * L2Normalization</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> * LogSoftmax</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> * Lstm</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> * Maximum</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> * Mean</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> * Merge</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> * Minimum</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> * Multiplication</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> * Normalization</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> * Output</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> * Pad</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> * Permute</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> * Pooling2d</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> * Prelu</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> * Quantize</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> * QuantizedLstm</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> * Reshape</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> * Resize</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> * ResizeBilinear</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> * Rsqrt</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> * Slice</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> * Softmax</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> * SpaceToBatchNd</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> * SpaceToDepth</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> * Splitter</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> * Stack</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> * StandIn</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> * StridedSlice</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> * Subtraction</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> * Switch</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> * TransposeConvolution2d</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> * Resize</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> More machine learning layers will be supported in future releases.</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> ## Deprecated layers</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> Some layers have been deprecated and replaced by others layers. In order to maintain backward compatibility, serializations of these deprecated layers will deserialize to the layers that have replaced them, as follows:</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> </div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> * Equal will deserialize as Comparison</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> * Merger will deserialize as Concat</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> * Greater will deserialize as Comparison</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> * ResizeBilinear will deserialize as Resize</div></div><!-- fragment --></div><!-- contents --> |
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