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<a href="_transpose_convolution2d_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 "<a class="code" href="_transpose_convolution2d_8hpp.html">TransposeConvolution2d.hpp</a>"</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="_data_layout_indexed_8hpp.html">armnnUtils/DataLayoutIndexed.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="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></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> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.html">armnnUtils</a>;</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"><a class="line" href="namespacearmnn.html#affec174d91f234497dfbceba5e251dee"> 15</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#affec174d91f234497dfbceba5e251dee">TransposeConvolution2dImpl</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html">TransposeConvolution2dDescriptor</a>& descriptor,</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& inputShape,</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <a class="code" href="classarmnn_1_1_decoder.html">Decoder<float></a>& inputDecoder,</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& outputShape,</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <a class="code" href="classarmnn_1_1_encoder.html">Encoder<float></a>& outputEncoder,</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& weightsShape,</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="classarmnn_1_1_decoder.html">Decoder<float></a>& weightsDecoder,</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <a class="code" href="classarmnn_1_1_decoder.html">Decoder<float></a>* biasesDecoder)</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> {</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> && !biasesDecoder)</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  {</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">"Biases enabled but no bias data provided"</span>);</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  }</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">DataLayoutIndexed</a> dataLayoutIndexed(descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channelsIndex = dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>();</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> heightIndex = dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>();</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> widthIndex = dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>();</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numBatches = inputShape[0];</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = inputShape[widthIndex];</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = inputShape[heightIndex];</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputDepth = inputShape[channelsIndex];</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsHeight = weightsShape[heightIndex];</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsWidth = weightsShape[widthIndex];</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = outputShape[heightIndex];</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = outputShape[widthIndex];</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputDepth = outputShape[channelsIndex];</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> paddingLeft = descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> paddingTop = descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a>;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> strideX = descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> strideY = descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  std::vector<float> outputBuffer(outputShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(), 0);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch = 0u; batch < numBatches; ++batch)</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yInput = 0u; yInput < inputHeight; ++yInput)</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  {</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> xInput = 0u; xInput < inputWidth; ++xInput)</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  {</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> xOutputOrigin = xInput * strideX - paddingLeft;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yOutputOrigin = yInput * strideY - paddingTop;</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dOutput = 0u; dOutput < outputDepth; ++dOutput)</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  {</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yWeights = 0u; yWeights < weightsHeight; ++yWeights)</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  {</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> xWeights = 0u; xWeights < weightsWidth; ++xWeights)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> yOutput = yOutputOrigin + yWeights;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> xOutput = xOutputOrigin + xWeights;</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">if</span> (yOutput < outputHeight && xOutput< outputWidth)</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dInput = 0u; dInput < inputDepth; dInput++)</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  {</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputIndex =</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(inputShape, batch, dInput, yInput, xInput);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  inputDecoder[inputIndex];</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsIndex =</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(weightsShape, dOutput, dInput, yWeights, xWeights);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  weightsDecoder.<a class="code" href="classarmnn_1_1_base_iterator.html#a1ec75b077d774dbfebf3662e8e4363c9">SetIndex</a>(weightsIndex, dOutput);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIndex =</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(outputShape, batch, dOutput, yOutput, xOutput);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  outputEncoder[outputIndex];</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordtype">float</span> output = outputBuffer[outputIndex];</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  output += inputDecoder.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>() * weightsDecoder.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  outputBuffer[outputIndex] = output;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  }</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>  }</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  }</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  }</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  }</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>  }</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="comment">// Apply bias (if enabled)</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</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>  outputEncoder[0];</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="classarmnn_1_1_decoder.html">Decoder<float></a>& rBiasesDecoder = *biasesDecoder;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch = 0u; batch < numBatches; ++batch)</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  {</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dOutput = 0u; dOutput < outputDepth; ++dOutput)</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  {</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  rBiasesDecoder.<a class="code" href="classarmnn_1_1_base_iterator.html#a1ec75b077d774dbfebf3662e8e4363c9">SetIndex</a>(dOutput, dOutput);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yOutput = 0u; yOutput < outputHeight; ++yOutput)</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">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> xOutput = 0u; xOutput < outputWidth; ++xOutput)</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="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIndex =</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">GetIndex</a>(outputShape, batch, dOutput, yOutput, xOutput);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  outputBuffer[outputIndex] += rBiasesDecoder.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</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>  }</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>  }</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>  outputEncoder[0];</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keywordflow">for</span> (<span class="keywordtype">float</span> output : outputBuffer)</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  {</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  outputEncoder.<a class="code" href="classarmnn_1_1_encoder.html#ae3b62b846a9c239f332830b9e36030eb">Set</a>(output);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  ++outputEncoder;</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> }</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="comment">// namespace armnn</span></div><div class="ttc" id="_transpose_convolution2d_8hpp_html"><div class="ttname"><a href="_transpose_convolution2d_8hpp.html">TransposeConvolution2d.hpp</a></div></div>
<div class="ttc" id="structarmnn_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#l01109">Descriptors.hpp:1109</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a61c00316c443adc233c24e85c6c5b740"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">armnnUtils::DataLayoutIndexed::GetHeightIndex</a></div><div class="ttdeci">unsigned int GetHeightIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00024">DataLayoutIndexed.hpp:24</a></div></div>
<div class="ttc" id="classarmnn_1_1_decoder_html"><div class="ttname"><a href="classarmnn_1_1_decoder.html">armnn::Decoder< float ></a></div></div>
<div class="ttc" id="classarmnn_1_1_invalid_argument_exception_html"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00080">Exceptions.hpp:80</a></div></div>
<div class="ttc" id="namespacearmnn_html_affec174d91f234497dfbceba5e251dee"><div class="ttname"><a href="namespacearmnn.html#affec174d91f234497dfbceba5e251dee">armnn::TransposeConvolution2dImpl</a></div><div class="ttdeci">void TransposeConvolution2dImpl(const TransposeConvolution2dDescriptor &descriptor, const TensorShape &inputShape, Decoder< float > &inputDecoder, const TensorShape &outputShape, Encoder< float > &outputEncoder, const TensorShape &weightsShape, Decoder< float > &weightsDecoder, Decoder< float > *biasesDecoder)</div><div class="ttdef"><b>Definition:</b> <a href="_transpose_convolution2d_8cpp_source.html#l00015">TransposeConvolution2d.cpp:15</a></div></div>
<div class="ttc" id="structarmnn_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#l01119">Descriptors.hpp:1119</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.html">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01079">Descriptors.hpp:1079</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_iterator_html_a1ec75b077d774dbfebf3662e8e4363c9"><div class="ttname"><a href="classarmnn_1_1_base_iterator.html#a1ec75b077d774dbfebf3662e8e4363c9">armnn::BaseIterator::SetIndex</a></div><div class="ttdeci">virtual BaseIterator & SetIndex(unsigned int index, unsigned int axisIndex=0)=0</div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a414e6f95548e6f7a01d5028b55ad3941"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">armnnUtils::DataLayoutIndexed::GetWidthIndex</a></div><div class="ttdeci">unsigned int GetWidthIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00025">DataLayoutIndexed.hpp:25</a></div></div>
<div class="ttc" id="namespacearmnn_utils_html"><div class="ttname"><a href="namespacearmnn_utils.html">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00013">DataLayoutIndexed.hpp:13</a></div></div>
<div class="ttc" id="structarmnn_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#l01115">Descriptors.hpp:1115</a></div></div>
<div class="ttc" id="classarmnn_1_1_encoder_html"><div class="ttname"><a href="classarmnn_1_1_encoder.html">armnn::Encoder< float ></a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_html_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorShape::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00106">Tensor.cpp:106</a></div></div>
<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a861b2621ee46e4b63379988b360b8cd9"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">armnnUtils::DataLayoutIndexed::GetChannelsIndex</a></div><div class="ttdeci">unsigned int GetChannelsIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00023">DataLayoutIndexed.hpp:23</a></div></div>
<div class="ttc" id="_data_layout_indexed_8hpp_html"><div class="ttname"><a href="_data_layout_indexed_8hpp.html">DataLayoutIndexed.hpp</a></div></div>
<div class="ttc" id="structarmnn_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#l01105">Descriptors.hpp:1105</a></div></div>
<div class="ttc" id="structarmnn_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#l01113">Descriptors.hpp:1113</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="classarmnn_1_1_decoder_html_ac729108381e2340bea12877971713ecb"><div class="ttname"><a href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">armnn::Decoder::Get</a></div><div class="ttdeci">virtual IType Get() const =0</div></div>
<div class="ttc" id="structarmnn_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#l01117">Descriptors.hpp:1117</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00017">DataLayoutIndexed.hpp:17</a></div></div>
<div class="ttc" id="classarmnn_1_1_encoder_html_ae3b62b846a9c239f332830b9e36030eb"><div class="ttname"><a href="classarmnn_1_1_encoder.html#ae3b62b846a9c239f332830b9e36030eb">armnn::Encoder::Set</a></div><div class="ttdeci">virtual void Set(IType right)=0</div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a1e25d8623da985a43597b5756c73b206"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a1e25d8623da985a43597b5756c73b206">armnnUtils::DataLayoutIndexed::GetIndex</a></div><div class="ttdeci">unsigned int GetIndex(const armnn::TensorShape &shape, unsigned int batchIndex, unsigned int channelIndex, unsigned int heightIndex, unsigned int widthIndex) const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00027">DataLayoutIndexed.hpp:27</a></div></div>
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