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+<div class="title">DeserializePad.cpp</div> </div>
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+<a href="_deserialize_pad_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></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> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_parser_flatbuffers_serialize_fixture_8hpp.html">ParserFlatbuffersSerializeFixture.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "../Deserializer.hpp"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <a class="code" href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(Deserializer)</div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="keyword">struct </span>PadFixture : <span class="keyword">public</span> <a class="code" href="struct_parser_flatbuffers_serialize_fixture.html">ParserFlatbuffersSerializeFixture</a></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> {</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>  <span class="keyword">explicit</span> PadFixture(<span class="keyword">const</span> std::string &inputShape,</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <span class="keyword">const</span> std::string &padList,</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="keyword">const</span> std::string &outputShape,</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="keyword">const</span> std::string &dataType)</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  {</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="struct_parser_flatbuffers_fixture.html#a803c86dca3acef653c1cc481a27be7a9">m_JsonString</a> = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="stringliteral"> inputIds: [0],</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="stringliteral"> outputIds: [2],</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="stringliteral"> layers: [</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="stringliteral"> layer_type: "InputLayer",</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="stringliteral"> layer: {</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="stringliteral"> base: {</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="stringliteral"> layerBindingId: 0,</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="stringliteral"> base: {</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="stringliteral"> index: 0,</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="stringliteral"> layerName: "InputLayer",</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="stringliteral"> layerType: "Input",</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="stringliteral"> inputSlots: [{</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="stringliteral"> index: 0,</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="stringliteral"> connection: {sourceLayerIndex:0, outputSlotIndex:0 },</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="stringliteral"> }],</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="stringliteral"> outputSlots: [{</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="stringliteral"> index: 0,</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="stringliteral"> tensorInfo: {</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="stringliteral"> dimensions: )" + inputShape + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="stringliteral"> dataType: )" + dataType + R</span><span class="stringliteral">"(</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="stringliteral"> }]</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="stringliteral"> layer_type: "PadLayer",</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="stringliteral"> layer: {</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="stringliteral"> base: {</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="stringliteral"> index: 1,</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="stringliteral"> layerName: "PadLayer",</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="stringliteral"> layerType: "Pad",</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="stringliteral"> inputSlots: [{</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="stringliteral"> index: 0,</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="stringliteral"> connection: {sourceLayerIndex:0, outputSlotIndex:0 },</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="stringliteral"> }],</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="stringliteral"> outputSlots: [{</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="stringliteral"> index: 0,</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="stringliteral"> tensorInfo: {</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="stringliteral"> dimensions: )" + outputShape + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="stringliteral"> dataType: )" + dataType + R</span><span class="stringliteral">"(</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="stringliteral"> }]</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="stringliteral"> descriptor: {</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="stringliteral"> padList: )" + padList + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="stringliteral"> layer_type: "OutputLayer",</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="stringliteral"> layer: {</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="stringliteral"> base:{</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="stringliteral"> layerBindingId: 2,</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="stringliteral"> base: {</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="stringliteral"> index: 2,</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="stringliteral"> layerName: "OutputLayer",</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="stringliteral"> layerType: "Output",</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="stringliteral"> inputSlots: [{</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="stringliteral"> index: 0,</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="stringliteral"> connection: {sourceLayerIndex:1, outputSlotIndex:0 },</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="stringliteral"> }],</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="stringliteral"> outputSlots: [{</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="stringliteral"> index: 0,</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="stringliteral"> tensorInfo: {</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="stringliteral"> dimensions: )" + outputShape + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="stringliteral"> dataType: )" + dataType + R</span><span class="stringliteral">"(</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="stringliteral"> }],</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="stringliteral"> ]</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="stringliteral"> )";</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="stringliteral"> <a class="code" href="struct_parser_flatbuffers_serialize_fixture.html#a2bb4ea256fbbf6d53068ca93bb4bc95c">SetupSingleInputSingleOutput</a>(</span><span class="stringliteral">"InputLayer"</span>, <span class="stringliteral">"OutputLayer"</span>);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  }</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> };</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="keyword">struct </span>SimplePadFixture : PadFixture</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> {</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  SimplePadFixture() : PadFixture(<span class="stringliteral">"[ 2, 2, 2 ]"</span>,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="stringliteral">"[ 0, 1, 2, 1, 2, 2 ]"</span>,</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="stringliteral">"[ 3, 5, 6 ]"</span>,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="stringliteral">"QuantisedAsymm8"</span>) {}</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> };</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"><a class="line" href="_deserialize_pad_8cpp.html#a0a0993fe79bb41264ab2082e09bbc4f7"> 113</a></span> <a class="code" href="_deserialize_pad_8cpp.html#a0a0993fe79bb41264ab2082e09bbc4f7">BOOST_FIXTURE_TEST_CASE</a>(SimplePadQuantisedAsymm8, SimplePadFixture)</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> {</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  RunTest<3, armnn::DataType::QAsymmU8>(0,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  0, 4, 2, 5, 6, 1, 5, 2</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  },</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  {</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  4, 0, 0, 0, 0, 2, 5, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  1, 0, 0, 0, 0, 5, 2, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  });</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> }</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <a class="code" href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="ttc" id="struct_parser_flatbuffers_fixture_html_a803c86dca3acef653c1cc481a27be7a9"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.html#a803c86dca3acef653c1cc481a27be7a9">ParserFlatbuffersFixture::m_JsonString</a></div><div class="ttdeci">std::string m_JsonString</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.html#l00051">ParserFlatbuffersFixture.hpp:51</a></div></div>
+<div class="ttc" id="struct_parser_flatbuffers_serialize_fixture_html"><div class="ttname"><a href="struct_parser_flatbuffers_serialize_fixture.html">ParserFlatbuffersSerializeFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_serialize_fixture_8hpp_source.html#l00028">ParserFlatbuffersSerializeFixture.hpp:28</a></div></div>
+<div class="ttc" id="struct_parser_flatbuffers_serialize_fixture_html_a2bb4ea256fbbf6d53068ca93bb4bc95c"><div class="ttname"><a href="struct_parser_flatbuffers_serialize_fixture.html#a2bb4ea256fbbf6d53068ca93bb4bc95c">ParserFlatbuffersSerializeFixture::SetupSingleInputSingleOutput</a></div><div class="ttdeci">void SetupSingleInputSingleOutput(const std::string &inputName, const std::string &outputName)</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_serialize_fixture_8hpp_source.html#l00084">ParserFlatbuffersSerializeFixture.hpp:84</a></div></div>
+<div class="ttc" id="_parser_flatbuffers_serialize_fixture_8hpp_html"><div class="ttname"><a href="_parser_flatbuffers_serialize_fixture_8hpp.html">ParserFlatbuffersSerializeFixture.hpp</a></div></div>
+<div class="ttc" id="_profiler_tests_8cpp_html_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div>
+<div class="ttc" id="_output_shape_of_squeeze_8cpp_html_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div>
+<div class="ttc" id="_deserialize_pad_8cpp_html_a0a0993fe79bb41264ab2082e09bbc4f7"><div class="ttname"><a href="_deserialize_pad_8cpp.html#a0a0993fe79bb41264ab2082e09bbc4f7">BOOST_FIXTURE_TEST_CASE</a></div><div class="ttdeci">BOOST_FIXTURE_TEST_CASE(SimplePadQuantisedAsymm8, SimplePadFixture)</div><div class="ttdef"><b>Definition:</b> <a href="_deserialize_pad_8cpp_source.html#l00113">DeserializePad.cpp:113</a></div></div>
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