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<div class="title">Decoders.hpp</div> </div>
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<a href="_decoders_8hpp.xhtml">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">#pragma once</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_base_iterator_8hpp.xhtml">BaseIterator.hpp</a>"</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 <<a class="code" href="_floating_point_converter_8hpp.xhtml">armnnUtils/FloatingPointConverter.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_tensor_utils_8hpp.xhtml">armnnUtils/TensorUtils.hpp</a>></span></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> <span class="preprocessor">#include <<a class="code" href="_assert_8hpp.xhtml">armnn/utility/Assert.hpp</a>></span></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> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></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> <span class="keyword">namespace</span></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> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="keyword">inline</span> std::unique_ptr<Decoder<float>> MakeSigned32PerAxisDecoder(<span class="keyword">const</span> TensorInfo& info, <span class="keyword">const</span> <span class="keywordtype">void</span>* data)</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>  <span class="keyword">auto</span> params = <a class="code" href="namespacearmnn_utils.xhtml#a1826e433f7e6817976a8175b4ef8296c">armnnUtils::GetPerAxisParams</a>(info);</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keywordflow">return</span> std::make_unique<ScaledInt32PerAxisDecoder>(</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keyword">static_cast<</span><span class="keyword">const </span>int32_t*<span class="keyword">></span>(data),</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  params.second,</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  params.first);</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> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword">inline</span> std::unique_ptr<Decoder<float>> MakeSigned32Decoder(<span class="keyword">const</span> TensorInfo& info, <span class="keyword">const</span> <span class="keywordtype">void</span>* data)</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>  <span class="keywordflow">if</span>(info.HasMultipleQuantizationScales())</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>  <span class="comment">// NOTE: If we have multiple quantization scales, we create a ScaledInt32PerAxisDecoder.</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="comment">// This will be used to decode per-axis quantized convolution biases.</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keywordflow">return</span> MakeSigned32PerAxisDecoder(info, data);</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>  <span class="keywordflow">else</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  {</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordflow">if</span> (info.GetQuantizationDim().has_value())</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>  <span class="comment">// NOTE: Even though we only have a single quantization scale, if the quantization</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="comment">// dimension is set, the tensor has per-axis quantization and we need to create a</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="comment">// ScaledInt32PerAxisDecoder</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">return</span> MakeSigned32PerAxisDecoder(info, data);</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  }</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>  <span class="keyword">const</span> <span class="keywordtype">float</span> scale = info.GetQuantizationScale();</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keywordflow">if</span> (scale == 0.f)</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="comment">// NOTE:: If no quantization scale is set, we create an Int32Decoder, which simply</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="comment">// casts the int value to float. This will be used for any INT32 data other than</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="comment">// convolution biases.</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">return</span> std::make_unique<Int32Decoder>(<span class="keyword">static_cast<</span><span class="keyword">const </span>int32_t*<span class="keyword">></span>(data));</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> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// NOTE: If we only have a single (non-zero) quantization scale and no quantization</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="comment">// dimension is specified, we need to create a ScaledInt32Decoder. This will be used</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="comment">// to decode per-tensor quantized convolution biases.</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordflow">return</span> std::make_unique<ScaledInt32Decoder>(<span class="keyword">static_cast<</span><span class="keyword">const </span>int32_t*<span class="keyword">></span>(data), scale);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  }</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> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> } <span class="comment">// anonymous namespace</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="keyword">template</span><<span class="keyword">typename</span> T></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="keyword">inline</span> std::unique_ptr<Decoder<T>> <a class="code" href="namespacearmnn.xhtml#a1545cb162c5a64d75d9c0c05e8ea387c">MakeDecoder</a>(<span class="keyword">const</span> TensorInfo& info, <span class="keyword">const</span> <span class="keywordtype">void</span>* data = <span class="keyword">nullptr</span>);</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> <span class="keyword">template</span><></div><div class="line"><a name="l00070"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#adb59a379c467b6d48874e946183b4d21"> 70</a></span> <span class="keyword">inline</span> std::unique_ptr<Decoder<float>> <a class="code" href="namespacearmnn.xhtml#a1545cb162c5a64d75d9c0c05e8ea387c">MakeDecoder</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& info, <span class="keyword">const</span> <span class="keywordtype">void</span>* data)</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> {</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordflow">switch</span>(info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>())</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>  <a class="code" href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a34346ec9593088efe3a29c0dad92166d">armnn::DataType::QuantizedSymm8PerAxis</a>:</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>  std::pair<unsigned int, std::vector<float>> params = <a class="code" href="namespacearmnn_utils.xhtml#a1826e433f7e6817976a8175b4ef8296c">armnnUtils::GetPerAxisParams</a>(info);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">return</span> std::make_unique<QSymm8PerAxisDecoder>(</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">static_cast<</span><span class="keyword">const </span>int8_t*<span class="keyword">></span>(data),</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  params.second,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  params.first);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  }</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">DataType::QAsymmS8</a>:</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  {</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordflow">return</span> std::make_unique<QASymmS8Decoder>(</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keyword">static_cast<</span><span class="keyword">const </span>int8_t*<span class="keyword">></span>(data),</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>(),</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>());</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  }</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>:</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  {</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordflow">return</span> std::make_unique<QASymm8Decoder>(</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keyword">static_cast<</span><span class="keyword">const </span>uint8_t*<span class="keyword">></span>(data),</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>(),</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>());</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  }</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>:</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  {</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordflow">return</span> std::make_unique<QSymm16Decoder>(</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">static_cast<</span><span class="keyword">const </span>int16_t*<span class="keyword">></span>(data),</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>(),</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>());</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="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>:</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>  <span class="keywordflow">return</span> std::make_unique<BFloat16Decoder>(<span class="keyword">static_cast<</span><span class="keyword">const </span><a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>*<span class="keyword">></span>(data));</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  }</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>:</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  {</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordflow">return</span> std::make_unique<Float16Decoder>(<span class="keyword">static_cast<</span><span class="keyword">const </span><a class="code" href="namespacearmnn.xhtml#a0f38fa92b2468d5378258a2b074c1a31">Half</a>*<span class="keyword">></span>(data));</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  }</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>:</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>  <span class="keywordflow">return</span> std::make_unique<Float32Decoder>(<span class="keyword">static_cast<</span><span class="keyword">const </span><span class="keywordtype">float</span>*<span class="keyword">></span>(data));</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>:</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>  <span class="keywordflow">return</span> MakeSigned32Decoder(info, data);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  }</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>:</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">if</span> (info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48">HasPerAxisQuantization</a>())</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  {</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  std::pair<unsigned int, std::vector<float>> params = <a class="code" href="namespacearmnn_utils.xhtml#a1826e433f7e6817976a8175b4ef8296c">armnnUtils::GetPerAxisParams</a>(info);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keywordflow">return</span> std::make_unique<QSymm8PerAxisDecoder>(</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keyword">static_cast<</span><span class="keyword">const </span>int8_t*<span class="keyword">></span>(data),</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  params.second,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  params.first);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  }</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  {</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordflow">return</span> std::make_unique<QSymmS8Decoder>(</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keyword">static_cast<</span><span class="keyword">const </span>int8_t*<span class="keyword">></span>(data),</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>(),</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>());</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  }</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  }</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a>:</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  {</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keywordflow">return</span> std::make_unique<BooleanDecoder>(<span class="keyword">static_cast<</span><span class="keyword">const </span>uint8_t*<span class="keyword">></span>(data));</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  }</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  {</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported Data Type!"</span>);</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  }</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  }</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> }</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="keyword">template</span><></div><div class="line"><a name="l00153"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a59c4fab5981602d8117d0b024eafd9ec"> 153</a></span> <span class="keyword">inline</span> std::unique_ptr<Decoder<bool>> <a class="code" href="namespacearmnn.xhtml#a1545cb162c5a64d75d9c0c05e8ea387c">MakeDecoder</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& info, <span class="keyword">const</span> <span class="keywordtype">void</span>* data)</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> {</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordflow">switch</span>(info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>())</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  {</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">DataType::Boolean</a>:</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  {</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keywordflow">return</span> std::make_unique<BooleanDecoderBool>(<span class="keyword">static_cast<</span><span class="keyword">const </span>uint8_t*<span class="keyword">></span>(data));</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  }</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  {</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported Data Type!"</span>);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  }</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  }</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> }</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> </div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> <span class="keyword">template</span><></div><div class="line"><a name="l00171"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a21c5697c38df92463d1e767db8a95267"> 171</a></span> <span class="keyword">inline</span> std::unique_ptr<Decoder<int32_t>> <a class="code" href="namespacearmnn.xhtml#a1545cb162c5a64d75d9c0c05e8ea387c">MakeDecoder</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& info, <span class="keyword">const</span> <span class="keywordtype">void</span>* data)</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> {</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keywordflow">switch</span>(info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>())</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  {</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>:</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  {</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keywordflow">return</span> std::make_unique<Int32ToInt32tDecoder>(<span class="keyword">static_cast<</span><span class="keyword">const </span>int32_t*<span class="keyword">></span>(data));</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  }</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  {</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported Data Type!"</span>);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  }</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  }</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> }</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> } <span class="comment">//namespace armnn</span></div><div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a></div></div>
<div class="ttc" id="_floating_point_converter_8hpp_xhtml"><div class="ttname"><a href="_floating_point_converter_8hpp.xhtml">FloatingPointConverter.hpp</a></div></div>
<div class="ttc" id="_deprecated_8hpp_xhtml_ab66a241a0ed3ee89c866e777b035d0ed"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_BEGIN</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00033">Deprecated.hpp:33</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a34346ec9593088efe3a29c0dad92166d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a34346ec9593088efe3a29c0dad92166d">armnn::DataType::QuantizedSymm8PerAxis</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_ab85cd8cc10c96a7c99c14042c251fc48"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48">armnn::TensorInfo::HasPerAxisQuantization</a></div><div class="ttdeci">bool HasPerAxisQuantization() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00437">Tensor.cpp:437</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div></div>
<div class="ttc" id="classarmnn_1_1_b_float16_xhtml"><div class="ttname"><a href="classarmnn_1_1_b_float16.xhtml">armnn::BFloat16</a></div><div class="ttdef"><b>Definition:</b> <a href="_b_float16_8hpp_source.xhtml#l00014">BFloat16.hpp:14</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div>
<div class="ttc" id="namespacearmnn_utils_xhtml_a1826e433f7e6817976a8175b4ef8296c"><div class="ttname"><a href="namespacearmnn_utils.xhtml#a1826e433f7e6817976a8175b4ef8296c">armnnUtils::GetPerAxisParams</a></div><div class="ttdeci">std::pair< unsigned int, std::vector< float > > GetPerAxisParams(const armnn::TensorInfo &info)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.xhtml#l00152">TensorUtils.cpp:152</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a1545cb162c5a64d75d9c0c05e8ea387c"><div class="ttname"><a href="namespacearmnn.xhtml#a1545cb162c5a64d75d9c0c05e8ea387c">armnn::MakeDecoder</a></div><div class="ttdeci">std::unique_ptr< Decoder< T > > MakeDecoder(const TensorInfo &info, const void *data=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_decoders_8hpp_source.xhtml#l00070">Decoders.hpp:70</a></div></div>
<div class="ttc" id="_base_iterator_8hpp_xhtml"><div class="ttname"><a href="_base_iterator_8hpp.xhtml">BaseIterator.hpp</a></div></div>
<div class="ttc" id="_deprecated_8hpp_xhtml_ad762b11b48e5c1d1c1743f529485728a"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_END</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00034">Deprecated.hpp:34</a></div></div>
<div class="ttc" id="_assert_8hpp_xhtml_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00015">Assert.hpp:15</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a770b51078da02f44a819e9f95d8058b5"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">armnn::TensorInfo::GetQuantizationOffset</a></div><div class="ttdeci">int32_t GetQuantizationOffset() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00469">Tensor.cpp:469</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a047ca888c43bd7fb5702853bf72410d0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">armnn::TensorInfo::GetQuantizationScale</a></div><div class="ttdeci">float GetQuantizationScale() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00452">Tensor.cpp:452</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00194">Tensor.hpp:194</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a></div></div>
<div class="ttc" id="_assert_8hpp_xhtml"><div class="ttname"><a href="_assert_8hpp.xhtml">Assert.hpp</a></div></div>
<div class="ttc" id="_tensor_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_utils_8hpp.xhtml">TensorUtils.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a0f38fa92b2468d5378258a2b074c1a31"><div class="ttname"><a href="namespacearmnn.xhtml#a0f38fa92b2468d5378258a2b074c1a31">armnn::Half</a></div><div class="ttdeci">half_float::half Half</div><div class="ttdef"><b>Definition:</b> <a href="_half_8hpp_source.xhtml#l00016">Half.hpp:16</a></div></div>
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