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<div class="title">TransposeConv2dOperator.cpp File Reference</div> </div>
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<div class="textblock"><code>#include &quot;<a class="el" href="_transpose_conv2d_operator_8hpp_source.html">TransposeConv2dOperator.hpp</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_transpose_convolution2d_layer_8hpp_source.html">layers/TransposeConvolution2dLayer.hpp</a>&quot;</code><br />
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<tr class="memitem:a6d30ef27a71abb69a0bb31d398759fda"><td class="memItemLeft" align="right" valign="top">TosaSerializationBasicBlock *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_transpose_conv2d_operator_8cpp.html#a6d30ef27a71abb69a0bb31d398759fda">ConvertTransposeConv2dToTosaOperator</a> (const <a class="el" href="classarmnn_1_1_layer.html">Layer</a> *layer, const std::vector&lt; const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> * &gt; &amp;inputs, const std::vector&lt; const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> * &gt; &amp;outputs, const <a class="el" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">TransposeConvolution2dDescriptor</a> *descriptor)</td></tr>
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<h2 class="memtitle"><span class="permalink"><a href="#a6d30ef27a71abb69a0bb31d398759fda">&#9670;&nbsp;</a></span>ConvertTransposeConv2dToTosaOperator()</h2>
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<td class="memname">TosaSerializationBasicBlock* ConvertTransposeConv2dToTosaOperator </td>
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<td class="paramtype">const <a class="el" href="classarmnn_1_1_layer.html">Layer</a> *&#160;</td>
<td class="paramname"><em>layer</em>, </td>
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<td class="paramtype">const std::vector&lt; const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> * &gt; &amp;&#160;</td>
<td class="paramname"><em>inputs</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">const std::vector&lt; const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> * &gt; &amp;&#160;</td>
<td class="paramname"><em>outputs</em>, </td>
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<td class="paramtype">const <a class="el" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">TransposeConvolution2dDescriptor</a> *&#160;</td>
<td class="paramname"><em>descriptor</em>&#160;</td>
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<p class="definition">Definition at line <a class="el" href="_transpose_conv2d_operator_8cpp_source.html#l00010">10</a> of file <a class="el" href="_transpose_conv2d_operator_8cpp_source.html">TransposeConv2dOperator.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;{</div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160; std::string input0Name = std::string(<span class="stringliteral">&quot;input0_&quot;</span>);</div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160; std::string input1Name = std::string(<span class="stringliteral">&quot;constant_&quot;</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160; std::string input2Name = std::string(<span class="stringliteral">&quot;constant_&quot;</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; std::string outputName = std::string(<span class="stringliteral">&quot;output0_&quot;</span>);</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; std::string blockName = std::string(<span class="stringliteral">&quot;Op_TRANSPOSE_CONV2D_block_&quot;</span>) + <a class="code" href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a>();</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; </div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; <span class="comment">// If a layer is present then the block will be used for execution, so input and output names need to be determined</span></div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; <span class="comment">// using the previous and following layers so the graph is connected correctly. For validation this doesn&#39;t matter.</span></div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; <span class="keywordflow">if</span>(layer != <span class="keyword">nullptr</span>)</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; {</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; <span class="comment">// Get the layers connected to the input slots and determine unique tensor names.</span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; <a class="code" href="classarmnn_1_1_layer.html">Layer</a>&amp; connectedInputLayer = layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">GetConnectedOutputSlot</a>()-&gt;<a class="code" href="classarmnn_1_1_output_slot.html#a7ddaf04177053a536f0e7be83a642bc6">GetOwningLayer</a>();</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; input0Name = <a class="code" href="_tosa_operator_utils_8hpp.html#a1640c964a461e8580837a79829a5c197">GenerateUniqueName</a>(connectedInputLayer, 0);</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; </div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <span class="comment">// Determine unique output tensor name.</span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; outputName = <a class="code" href="_tosa_operator_utils_8hpp.html#a246662c69dac647833be50ba6dcee024">GenerateUniqueOutputName</a>(*layer, 0);</div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; }</div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; </div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; std::vector&lt;TosaSerializationTensor*&gt; tensors;</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; std::vector&lt;TosaSerializationOperator*&gt; operators;</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; </div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="comment">// Setup input tensor</span></div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="comment">// Only add tensor if connected layer is an input layer.</span></div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <span class="comment">// As intermediate or constant tensors will be created separately.</span></div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="comment">// There also can&#39;t be duplicate tensors.</span></div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="keywordflow">if</span>(input0Name.find(<span class="stringliteral">&quot;input0_&quot;</span>) != std::string::npos)</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; {</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; std::vector&lt;int32_t&gt; inputShape0 = <a class="code" href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a>(inputs[0]-&gt;GetShape());</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; DType inputDType0 = <a class="code" href="_tosa_operator_utils_8hpp.html#a45d66f17ad6b0469e469f443b3e03226">ArmNNToDType</a>(inputs[0]-&gt;GetDataType());</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; </div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(input0Name, inputShape0, inputDType0, {}));</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; }</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; </div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="comment">// Setup weights tensor, constant data will get copied during SetConstantTensorData</span></div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; operators.push_back(<span class="keyword">new</span> TosaSerializationOperator(Op_CONST, Attribute_NONE, <span class="keyword">nullptr</span>, {}, {input1Name}));</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; </div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="comment">// During validation the TensorInfo can be retrieved from the inputs.</span></div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="comment">// During execution, it is only available through the layer so use m_Weight.</span></div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <span class="keywordflow">if</span>(layer == <span class="keyword">nullptr</span>)</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; {</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; std::vector&lt;int32_t&gt; inputShape1 = <a class="code" href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a>(inputs[1]-&gt;GetShape());</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; DType inputDType1 = <a class="code" href="_tosa_operator_utils_8hpp.html#a45d66f17ad6b0469e469f443b3e03226">ArmNNToDType</a>(inputs[1]-&gt;GetDataType());</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; </div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(input1Name, inputShape1, inputDType1, {}));</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; }</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; {</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="keyword">auto</span> transposeConv2dLayer = PolymorphicDowncast&lt;const TransposeConvolution2dLayer*&gt;(layer);</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; </div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; std::vector&lt;int32_t&gt; inputShape1 = <a class="code" href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a>(</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; transposeConv2dLayer-&gt;m_Weight-&gt;GetTensorInfo().GetShape());</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; DType inputDType1 = <a class="code" href="_tosa_operator_utils_8hpp.html#a45d66f17ad6b0469e469f443b3e03226">ArmNNToDType</a>(transposeConv2dLayer-&gt;m_Weight-&gt;GetTensorInfo().GetDataType());</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; </div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; std::vector&lt;uint8_t&gt; uint8Data = <a class="code" href="_tosa_operator_utils_8hpp.html#ae03fdd5482e75faa3b846bd021678f3b">ConvertConstantTensorDataToBuffer</a>(transposeConv2dLayer-&gt;m_Weight);</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(input1Name, inputShape1, inputDType1, uint8Data));</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; }</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; </div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <span class="comment">// Setup bias operator and tensor, constant data will get copied during SetConstantTensorData</span></div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; operators.push_back(<span class="keyword">new</span> TosaSerializationOperator(Op_CONST, Attribute_NONE, <span class="keyword">nullptr</span>, {}, {input2Name}));</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; </div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="comment">// During validation the TensorInfo can be retrieved from the inputs.</span></div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="comment">// During execution, it is only available through the layer so use m_Bias.</span></div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="keywordflow">if</span>(layer == <span class="keyword">nullptr</span> &amp;&amp; descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; {</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; std::vector&lt;int32_t&gt; inputShape2 = <a class="code" href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a>(inputs[2]-&gt;GetShape());</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; DType inputDType2 = <a class="code" href="_tosa_operator_utils_8hpp.html#a45d66f17ad6b0469e469f443b3e03226">ArmNNToDType</a>(inputs[2]-&gt;GetDataType());</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; </div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(input2Name, inputShape2, inputDType2, {}));</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; }</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span>(descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; {</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="keyword">auto</span> transposeConv2dLayer = PolymorphicDowncast&lt;const TransposeConvolution2dLayer*&gt;(layer);</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; </div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; std::vector&lt;int32_t&gt; inputShape2 = <a class="code" href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a>(</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; transposeConv2dLayer-&gt;m_Bias-&gt;GetTensorInfo().GetShape());</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; DType inputDType2 = <a class="code" href="_tosa_operator_utils_8hpp.html#a45d66f17ad6b0469e469f443b3e03226">ArmNNToDType</a>(transposeConv2dLayer-&gt;m_Bias-&gt;GetTensorInfo().GetDataType());</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; </div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; std::vector&lt;uint8_t&gt; uint8Data = <a class="code" href="_tosa_operator_utils_8hpp.html#ae03fdd5482e75faa3b846bd021678f3b">ConvertConstantTensorDataToBuffer</a>(transposeConv2dLayer-&gt;m_Bias);</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(input2Name, inputShape2, inputDType2, uint8Data));</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; }</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; {</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="comment">// If bias is disabled, create a constant bias tensor of 0&#39;s as three inputs are required.</span></div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <span class="comment">// The size of the bias must match the channels dimension, so get the correct index.</span></div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index = (descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == DataLayout::NHWC) ? 3 : 1;</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; </div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; std::vector&lt;uint8_t&gt; uint8Data;</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; std::vector&lt;float&gt; data(outputs[0]-&gt;GetShape()[index], 0.0f);</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; </div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; TosaSerializationHandler::ConvertF32toU8(data, uint8Data);</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; </div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(input2Name,</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; {<span class="keyword">static_cast&lt;</span>int32_t<span class="keyword">&gt;</span>(outputs[0]-&gt;GetShape()[index])},</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; DType_FP32,</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; uint8Data));</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; }</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; </div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="comment">// Setup Output Tensor</span></div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; std::vector&lt;int32_t&gt; outputShape0 = <a class="code" href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a>(outputs[0]-&gt;GetShape());</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; DType outputDType0 = <a class="code" href="_tosa_operator_utils_8hpp.html#a45d66f17ad6b0469e469f443b3e03226">ArmNNToDType</a>(outputs[0]-&gt;GetDataType());</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; </div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; tensors.push_back(<span class="keyword">new</span> TosaSerializationTensor(outputName, outputShape0, outputDType0, {}));</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; </div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="comment">// Set up TRANSPOSE_CONV2D operator</span></div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="comment">// The TOSA Reference Model pads the output shape, so it is added to output shape.</span></div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="comment">// In Arm NN we pad the input shape, so it is taken away.</span></div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="comment">// To offset this the negative padding value can be used.</span></div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; std::vector&lt;int&gt; pad = {-<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a>),</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; -<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>),</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; -<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>),</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; -<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>)};</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; std::vector&lt;int&gt; stride = {<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>),</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>)};</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; </div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; std::vector&lt;int&gt; outputShape;</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <span class="comment">// If available use shape in descriptor otherwise use output shape.</span></div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; <span class="keywordflow">if</span> (descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a78f5b213a603b55d0fabea389e89f203">m_OutputShape</a>.size() == 4)</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; {</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="keywordflow">for</span> (uint32_t i = 0; i &lt; descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a78f5b213a603b55d0fabea389e89f203">m_OutputShape</a>.size(); ++i)</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; {</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; outputShape.push_back(<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(descriptor-&gt;<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a78f5b213a603b55d0fabea389e89f203">m_OutputShape</a>[i]));</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; }</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; }</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; {</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <span class="keywordflow">for</span> (uint32_t i = 0; i &lt; outputs[0]-&gt;GetNumDimensions(); ++i)</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; {</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; outputShape.push_back(<span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(outputs[0]-&gt;GetShape()[i]));</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; }</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; }</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; </div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; TosaTransposeConvAttribute attribute(pad, stride, outputShape, 0, 0);</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; </div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; <span class="keyword">auto</span>* op = <span class="keyword">new</span> TosaSerializationOperator(Op_TRANSPOSE_CONV2D,</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; Attribute_TransposeConvAttribute,</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; &amp;attribute,</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; {input0Name, input1Name, input2Name},</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; {outputName});</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; operators.push_back(op);</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; </div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; <span class="comment">// operatorInputNames/operatorOutputNames ends up being the same as</span></div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <span class="comment">// blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings</span></div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; <span class="keywordflow">return</span> <span class="keyword">new</span> TosaSerializationBasicBlock(blockName, <span class="comment">// name</span></div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <a class="code" href="_tosa_operator_utils_8hpp.html#a28514b014a4fe0841044f1868064bc65">mainName</a>, <span class="comment">// region name</span></div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; operators, <span class="comment">// operators</span></div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; tensors, <span class="comment">// tensors</span></div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; {input0Name, input1Name, input2Name}, <span class="comment">// inputs</span></div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; {outputName}); <span class="comment">// outputs</span></div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160;}</div>
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<p class="reference">References <a class="el" href="_tosa_operator_utils_8hpp_source.html#l00063">GenerateUniqueName()</a>, <a class="el" href="_tosa_operator_utils_8hpp_source.html#l00082">GenerateUniqueOutputName()</a>, <a class="el" href="_layer_8hpp_source.html#l00056">InputSlot::GetConnectedOutputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00337">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00132">OutputSlot::GetOwningLayer()</a>, <a class="el" href="_tosa_operator_utils_8hpp_source.html#l00052">GetTosaTensorShape()</a>, and <a class="el" href="_tosa_operator_utils_8hpp_source.html#l00100">GetUniqueTosaMappingID()</a>.</p>
<p class="reference">Referenced by <a class="el" href="_tosa_mappings_8cpp_source.html#l00018">GetTosaMapping()</a>.</p>
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<div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::TransposeConvolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01469">Descriptors.hpp:1469</a></div></div>
<div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::TransposeConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01477">Descriptors.hpp:1477</a></div></div>
<div class="ttc" id="a_tosa_operator_utils_8hpp_html_ae03fdd5482e75faa3b846bd021678f3b"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#ae03fdd5482e75faa3b846bd021678f3b">ConvertConstantTensorDataToBuffer</a></div><div class="ttdeci">std::vector&lt; uint8_t &gt; ConvertConstantTensorDataToBuffer(const std::shared_ptr&lt; ConstTensorHandle &gt; &amp;tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00289">TosaOperatorUtils.hpp:289</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot &amp; GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00337">Layer.hpp:337</a></div></div>
<div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">armnn::TransposeConvolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01475">Descriptors.hpp:1475</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00230">Layer.hpp:230</a></div></div>
<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a28514b014a4fe0841044f1868064bc65"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a28514b014a4fe0841044f1868064bc65">mainName</a></div><div class="ttdeci">const std::string mainName</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00019">TosaOperatorUtils.hpp:19</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_output_slot_html_a7ddaf04177053a536f0e7be83a642bc6"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7ddaf04177053a536f0e7be83a642bc6">armnn::OutputSlot::GetOwningLayer</a></div><div class="ttdeci">Layer &amp; GetOwningLayer() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00132">Layer.hpp:132</a></div></div>
<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a45d66f17ad6b0469e469f443b3e03226"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a45d66f17ad6b0469e469f443b3e03226">ArmNNToDType</a></div><div class="ttdeci">DType ArmNNToDType(const DataType &amp;type)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00022">TosaOperatorUtils.hpp:22</a></div></div>
<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a246662c69dac647833be50ba6dcee024"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a246662c69dac647833be50ba6dcee024">GenerateUniqueOutputName</a></div><div class="ttdeci">std::string GenerateUniqueOutputName(const Layer &amp;layer, uint32_t layerSlot)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00082">TosaOperatorUtils.hpp:82</a></div></div>
<div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::TransposeConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01479">Descriptors.hpp:1479</a></div></div>
<div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_a78f5b213a603b55d0fabea389e89f203"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a78f5b213a603b55d0fabea389e89f203">armnn::TransposeConvolution2dDescriptor::m_OutputShape</a></div><div class="ttdeci">std::vector&lt; unsigned int &gt; m_OutputShape</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01486">Descriptors.hpp:1486</a></div></div>
<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a1640c964a461e8580837a79829a5c197"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a1640c964a461e8580837a79829a5c197">GenerateUniqueName</a></div><div class="ttdeci">std::string GenerateUniqueName(const Layer &amp;layer, uint32_t layerSlot)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00063">TosaOperatorUtils.hpp:63</a></div></div>
<div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">armnn::TransposeConvolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01473">Descriptors.hpp:1473</a></div></div>
<div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">armnn::TransposeConvolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01471">Descriptors.hpp:1471</a></div></div>
<div class="ttc" id="a_tosa_operator_utils_8hpp_html_a7d97964a65be4eb4a5b4109904f2e7f7"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#a7d97964a65be4eb4a5b4109904f2e7f7">GetTosaTensorShape</a></div><div class="ttdeci">std::vector&lt; int32_t &gt; GetTosaTensorShape(const TensorShape &amp;shape)</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00052">TosaOperatorUtils.hpp:52</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_input_slot_html_a9effd325a6d512a3f8ff4bd207d53255"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">armnn::InputSlot::GetConnectedOutputSlot</a></div><div class="ttdeci">const OutputSlot * GetConnectedOutputSlot() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00056">Layer.hpp:56</a></div></div>
<div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::TransposeConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01481">Descriptors.hpp:1481</a></div></div>
<div class="ttc" id="astructarmnn_1_1_transpose_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::TransposeConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01483">Descriptors.hpp:1483</a></div></div>
<div class="ttc" id="a_tosa_operator_utils_8hpp_html_aadc5d73bd0cb81999bcfdc62bce020e8"><div class="ttname"><a href="_tosa_operator_utils_8hpp.html#aadc5d73bd0cb81999bcfdc62bce020e8">GetUniqueTosaMappingID</a></div><div class="ttdeci">std::string GetUniqueTosaMappingID()</div><div class="ttdef"><b>Definition:</b> <a href="_tosa_operator_utils_8hpp_source.html#l00100">TosaOperatorUtils.hpp:100</a></div></div>
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