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| author | Nikhil Raj <nikhil.raj@arm.com> | 2022-11-23 11:05:29 +0000 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-11-23 11:09:30 +0000 |
| commit | cb0630959aeae05bc2ae9f6d80cf5f5983a8fb77 (patch) | |
| tree | 0dbcf7ed5eb76622aba7bb742f39621aa476e3e8 /22.11/_build_guide_native_8md_source.xhtml | |
| parent | 7bfd38a721360183f3392f9ab35db18a0dd7fef8 (diff) | |
| download | armnn-cb0630959aeae05bc2ae9f6d80cf5f5983a8fb77.tar.gz | |
IVGCVSW-7075 Update Doxygen for 22.11 Release
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: Ib5669e8fd3739d1b10f5dd694d020d51799896dc
Diffstat (limited to '22.11/_build_guide_native_8md_source.xhtml')
| -rw-r--r-- | 22.11/_build_guide_native_8md_source.xhtml | 113 |
1 files changed, 113 insertions, 0 deletions
diff --git a/22.11/_build_guide_native_8md_source.xhtml b/22.11/_build_guide_native_8md_source.xhtml new file mode 100644 index 0000000000..d457f74fae --- /dev/null +++ b/22.11/_build_guide_native_8md_source.xhtml @@ -0,0 +1,113 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: delegate/BuildGuideNative.md Source File</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! 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[Doctest](https://github.com/onqtam/doctest) was used to create those tests. Using test filters you can</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> filter out tests that your build is not configured for. In this case, we run all test suites that have `CpuAcc` in their name.</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> ```bash</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> cd <PATH_TO_ARMNN_BUILD_DIRECTORY>/delegate/build</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> ./DelegateUnitTests --test-suite=*CpuAcc*</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> ```</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> If you have built for Gpu acceleration as well you might want to change your test-suite filter:</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> ```bash</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> ./DelegateUnitTests --test-suite=*CpuAcc*,*GpuAcc*</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> </div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> ## Run the TFLite Model Benchmark Tool</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> The [TFLite Model Benchmark](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/tools/benchmark) Tool has a useful command line interface to test the TF Lite Delegate.</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> We can use this to demonstrate the use of the Arm NN TF Lite Delegate and its options.</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> Some examples of this can be viewed in this [YouTube demonstration](https://www.youtube.com/watch?v=NResQ1kbm-M&t=920s).</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> ### Download the TFLite Model Benchmark Tool</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> </div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> Binary builds of the benchmarking tool for various platforms are available [here](https://www.tensorflow.org/lite/performance/measurement#native_benchmark_binary). In this example I will target an aarch64 Linux environment. I will also download a sample uint8 tflite model from the [Arm ML Model Zoo](https://github.com/ARM-software/ML-zoo).</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> ```bash</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> mkdir $BASEDIR/benchmarking</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> cd $BASEDIR/benchmarking</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> # Get the benchmarking binary.</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> wget https://storage.googleapis.com/tensorflow-nightly-public/prod/tensorflow/release/lite/tools/nightly/latest/linux_aarch64_benchmark_model -O benchmark_model</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> # Make it executable.</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> chmod +x benchmark_model</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> # and a sample model from model zoo.</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> wget https://github.com/ARM-software/ML-zoo/blob/master/models/image_classification/mobilenet_v2_1.0_224/tflite_uint8/mobilenet_v2_1.0_224_quantized_1_default_1.tflite?raw=true -O mobilenet_v2_1.0_224_quantized_1_default_1.tflite</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> ```</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> ### Execute the benchmarking tool with the Arm NN TF Lite Delegate</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> You are already at $BASEDIR/benchmarking from the previous stage.</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> ```bash</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> LD_LIBRARY_PATH=<PATH_TO_ARMNN_BUILD_DIRECTORY> ./benchmark_model --graph=mobilenet_v2_1.0_224_quantized_1_default_1.tflite --external_delegate_path="<PATH_TO_ARMNN_BUILD_DIRECTORY>/delegate/libarmnnDelegate.so" --external_delegate_options="backends:CpuAcc;logging-severity:info"</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> ```</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> The "external_delegate_options" here are specific to the Arm NN delegate. They are used to specify a target Arm NN backend or to enable/disable various options in Arm NN. A full description can be found in the parameters of function tflite_plugin_create_delegate.</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> ## Integrate the Arm NN TfLite Delegate into your project</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> The delegate can be integrated into your c++ project by creating a TfLite Interpreter and</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> instructing it to use the Arm NN delegate for the graph execution. This should look similar</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> to the following code snippet.</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> ```objectivec</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> // Create TfLite Interpreter</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> std::unique_ptr<Interpreter> armnnDelegateInterpreter;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  (&armnnDelegateInterpreter)</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> // Create the Arm NN Delegate</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> armnnDelegate::DelegateOptions delegateOptions(backends);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  armnnDelegate::TfLiteArmnnDelegateDelete);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> // Instruct the Interpreter to use the armnnDelegate</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get());</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> ```</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> For further information on using TfLite Delegates please visit the [TensorFlow website](https://www.tensorflow.org/lite/guide).</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> For more details of the kind of options you can pass to the Arm NN delegate please check the parameters of function tflite_plugin_create_delegate.</div></div><!-- fragment --></div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="_build_guide_native_8md.xhtml">BuildGuideNative.md</a></li> + <li class="footer">Generated on Wed Nov 23 2022 10:57:36 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + </ul> +</div> +</body> +</html> |