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<a href="_f_a_q_8md.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> Frequently asked questions</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> </div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> Problems seen when trying to build armnn and ComputeLibrary obtained from GitHub</div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> -----------------------------------------------------------------------------</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> Some users have encountered difficulties when attempting to build armnn and ComputeLibrary obtained from GitHub. The build generally fails reporting missing dependencies or fields in aclCommon, backendsCommon, cl or neon. These errors can look like this:</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> error: ‘HARD_SWISH’ is not a member of ‘AclActivationFunction {aka arm_compute::ActivationLayerInfo::ActivationFunction}’</div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> The most common reason for these errors are a mismatch between armnn and clframework revisions. For any version of Arm NN the coresponding version of ComputeLibrary is detailed in scripts/get_compute_library.sh as DEFAULT_CLFRAMEWORKREVISION</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> On *nix like systems running this script will checkout ComputeLibrary, with the current default SHA, into ../../clframework/ relative to the location of the script.</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> Segmentation fault following a failed call to armnn::Optimize using CpuRef backend.</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> ---------------------------------------------------------</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> In some error scenarios of calls to armnn::Optimize a null pointer may be returned. This contravenes the function documentation however, it can happen. Users are advised to check the value returned from the function as a precaution.</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> If you encounter this problem and are able to isolate it consider contributing a solution.</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> </div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> Adding or removing -Dxxx options when building Arm NN does not always work.</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> ---------------------------------------------------------</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> Arm NN uses CMake for build configuration. CMake uses a cumulative cache of user options. That is, setting a value once on a cmake command line will be persisted until either you explicitly change the value or delete the cache. To delete the cache in Arm NN you must delete the build directory.</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> Many DynamicBackendTests fail with "Base path for shared objects does not exist".</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> ---------------------------------------------------------</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> This problem most commonly occurs when the compile and runtime environments for the unit tests differ. These dynamic backend tests rely on a set of test files and directories at runtime. These files are created by default during the cmake build. At runtime the tests will look for these files in src/backends/backendsCommon/test/ relative to where the Unittests executable was built. The usual solution to to copy these files and directories into the new unit test execution environment. You can also specify a new root path for these files by adding a command line parameter to the Unittests executable: Unittests -- --dynamic-backend-build-dir "new path"</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> Tensorflow Lite benchmarking tool fails with segmentation fault when using the Arm NN delegate.</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> ---------------------------------------------------------</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> There are occaisional problems using native build versions of the Tensorflow Lite benchmarking tool. It can be sensitive to errors in command line parameter usage. A simple misspelling of a delegate name will result in a bus error. Here is a sample command line usage that is known to work for the Arm NN delegate.</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> This example is for:</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> </div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> * Execution on Android using a native binary downloaded from [Tensorflow Lite performance measurment](https://www.tensorflow.org/lite/performance/measurement#native_benchmark_binary).</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> * Uses a TF Lite model that has been downloaded from the ML-zoo. In this case [MobileNet v2 1.0 224 UINT8](https://github.com/ARM-software/ML-zoo/tree/master/models/image_classification/mobilenet_v2_1.0_224/tflite_uint8).</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> * Arm NN and its dependent libraries are in the current directory, /data/local/tmp.</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> </div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> ~~~</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> LD_LIBRARY_PATH=/vendor/lib64/egl:/vendor/lib/egl/:. ./android_aarch64_benchmark_model --num_threads=4 --graph=/data/local/tmp/mobilenet_v2_1.0_224_quantized_1_default_1.tflite --external_delegate_path="libarmnnDelegate.so" --external_delegate_options="backends:GpuAcc"</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> ~~~</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> Arm NN fails to build intermittently on 18.04 Ubuntu</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> ---------------------------------------------------------</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> Building Arm NN fails intermittently with error:</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> c++: internal compiler error: Killed (program cc1plus)</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> This errors appears to be related to the number of cmake jobs used to build Arm NN.Try limiting the jobs to 2 by modifying the make to:</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> make -j2</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> Arm NN UnitTests fails intermittently with segmentation fault on aarch64.</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> ----------------------------------------------------------</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> The DefaultAsyncExeuteWithThreads test seems to be throwing intermittent segmentation fault while running Arm NN Unittest in aarch64 architecture. 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