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<div class="title">BatchToSpaceNd.cpp</div> </div>
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<a href="_batch_to_space_nd_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>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2017-2020,2023 Arm Ltd and Contributors. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160; </div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_batch_to_space_nd_8hpp.html">BatchToSpaceNd.hpp</a>&quot;</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160; </div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_data_layout_indexed_8hpp.html">armnnUtils/DataLayoutIndexed.hpp</a>&gt;</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160; </div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.html">armnnUtils</a>;</div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160; </div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;{</div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160; </div>
<div class="line"><a name="l00015"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ac70a495c61526a0500b33b23db86ca27"> 15</a></span>&#160;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearmnn.html#ac70a495c61526a0500b33b23db86ca27">Offset</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; shape,</div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch,</div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height,</div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width,</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels,</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">DataLayoutIndexed</a>&amp; dataLayout)</div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;{</div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; <span class="comment">// 3D Tensors</span></div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channelDimension3D = dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a7d8b3d755b6ca8f5533657969efb06c4">GetDataLayout</a>() == DataLayout::NCHW ? 1 : 2;</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; <span class="keywordflow">if</span> (shape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() == 3)</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; {</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; <span class="keywordflow">return</span> (batch * shape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()] + height) * shape[channelDimension3D] + channels;</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; }</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; <span class="comment">// 4D Tensors</span></div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (shape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() == 4)</div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; {</div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keywordflow">if</span> (dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a7d8b3d755b6ca8f5533657969efb06c4">GetDataLayout</a>() == DataLayout::NHWC)</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; <span class="keywordflow">return</span> ((batch * shape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()] + height) *</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; shape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()] + width) *</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; shape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>()] + channels;</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; }</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; {</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="keywordflow">return</span> ((batch * shape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>()] + channels) *</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; shape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()] + height) *</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; shape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()] + width;</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; }</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; }</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; {</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Tensor rank must be either 3 or 4&quot;</span>, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</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;}</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; </div>
<div class="line"><a name="l00050"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ae97f6a405add803682188eecea9b021d"> 50</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#ae97f6a405add803682188eecea9b021d">BatchToSpaceNd</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; inputInfo,</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; outputInfo,</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html">BatchToSpaceNdDescriptor</a>&amp; params,</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <a class="code" href="classarmnn_1_1_decoder.html">Decoder&lt;float&gt;</a>&amp; inputData,</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <a class="code" href="classarmnn_1_1_encoder.html">Encoder&lt;float&gt;</a>&amp; outputData)</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;{</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> rank = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="keywordflow">if</span> (rank != 3 &amp;&amp; rank != 4 )</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; {</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Tensor rank must be either 3 or 4, but it is &quot;</span> + std::to_string(rank),</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</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; </div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">DataLayoutIndexed</a> dataLayout = params.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>;</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channelDimension3D = params.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == DataLayout::NCHW ? 1 : 2;</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; </div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputShape = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape = outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; </div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize = inputShape[0];</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputBatchSize = outputShape[0];</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="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = (rank == 3) ? inputShape[channelDimension3D]</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; : inputShape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>()];</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="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = inputShape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()];</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = (rank == 3) ? 1 : inputShape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()];</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = outputShape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()];</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = (rank == 3) ? 1 : outputShape[dataLayout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()];</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; </div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> blockHeight = params.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[0];</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> blockWidth = (rank == 3) ? 1 : params.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[1];</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; </div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> cropsTop = params.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a3941f674c071c9503e00d2b59e92e454">m_Crops</a>[0].first;</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> cropsLeft = (rank == 3) ? 0 : params.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a3941f674c071c9503e00d2b59e92e454">m_Crops</a>[1].first;</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inBatch = 0; inBatch &lt; inputBatchSize; ++inBatch)</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; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outBatch = inBatch % outputBatchSize;</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> spatialOffset = inBatch / outputBatchSize;</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; </div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inH = 0; inH &lt; inputHeight; ++inH)</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; {</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outH = inH * blockHeight + spatialOffset / blockWidth - cropsTop;</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">if</span> (outH &gt;= outputHeight)</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="keywordflow">continue</span>;</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; }</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; </div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inW = 0; inW &lt; inputWidth; ++inW)</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; {</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outW = inW * blockWidth + spatialOffset % blockWidth - cropsLeft;</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; <span class="keywordflow">if</span> (outW &gt;= outputWidth)</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; <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; }</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; </div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> c = 0; c &lt; channels; c++)</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; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outOffset = <a class="code" href="namespacearmnn.html#ac70a495c61526a0500b33b23db86ca27">Offset</a>(outputShape, outBatch, outH, outW, c, dataLayout);</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inOffset = <a class="code" href="namespacearmnn.html#ac70a495c61526a0500b33b23db86ca27">Offset</a>(inputShape, inBatch, inH, inW, c, dataLayout);</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; </div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; outputData[outOffset];</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; inputData[inOffset];</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; outputData.<a class="code" href="classarmnn_1_1_encoder.html#ae3b62b846a9c239f332830b9e36030eb">Set</a>(inputData.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>());</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; }</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; }</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; }</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160;}</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; </div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160;} <span class="comment">//namespace armnn</span></div>
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<div class="ttc" id="aclassarmnn_1_1_decoder_html"><div class="ttname"><a href="classarmnn_1_1_decoder.html">armnn::Decoder&lt; float &gt;</a></div></div>
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<div class="ttc" id="a_batch_to_space_nd_8hpp_html"><div class="ttname"><a href="_batch_to_space_nd_8hpp.html">BatchToSpaceNd.hpp</a></div></div>
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<div class="ttc" id="aclassarmnn_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="ttdoc">Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout.</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="aclassarmnn_utils_1_1_data_layout_indexed_html_a7d8b3d755b6ca8f5533657969efb06c4"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a7d8b3d755b6ca8f5533657969efb06c4">armnnUtils::DataLayoutIndexed::GetDataLayout</a></div><div class="ttdeci">armnn::DataLayout GetDataLayout() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00022">DataLayoutIndexed.hpp:22</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ae97f6a405add803682188eecea9b021d"><div class="ttname"><a href="namespacearmnn.html#ae97f6a405add803682188eecea9b021d">armnn::BatchToSpaceNd</a></div><div class="ttdeci">void BatchToSpaceNd(const TensorInfo &amp;inputInfo, const TensorInfo &amp;outputInfo, const BatchToSpaceNdDescriptor &amp;params, Decoder&lt; float &gt; &amp;inputData, Encoder&lt; float &gt; &amp;outputData)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_8cpp_source.html#l00050">BatchToSpaceNd.cpp:50</a></div></div>
<div class="ttc" id="astructarmnn_1_1_batch_to_space_nd_descriptor_html_a3941f674c071c9503e00d2b59e92e454"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a3941f674c071c9503e00d2b59e92e454">armnn::BatchToSpaceNdDescriptor::m_Crops</a></div><div class="ttdeci">std::vector&lt; std::pair&lt; unsigned int, unsigned int &gt; &gt; m_Crops</div><div class="ttdoc">The values to crop from the input dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00900">Descriptors.hpp:900</a></div></div>
<div class="ttc" id="aclassarmnn_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="aclassarmnn_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>
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<div class="ttc" id="astructarmnn_1_1_batch_to_space_nd_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.html">armnn::BatchToSpaceNdDescriptor</a></div><div class="ttdoc">A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00875">Descriptors.hpp:875</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape &amp; GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00193">Tensor.hpp:193</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ac70a495c61526a0500b33b23db86ca27"><div class="ttname"><a href="namespacearmnn.html#ac70a495c61526a0500b33b23db86ca27">armnn::Offset</a></div><div class="ttdeci">unsigned int Offset(const TensorShape &amp;shape, unsigned int batch, unsigned int height, unsigned int width, unsigned int channels, const DataLayoutIndexed &amp;dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_8cpp_source.html#l00015">BatchToSpaceNd.cpp:15</a></div></div>
<div class="ttc" id="anamespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors.</div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.html#l00006">01_00_quick_start.dox:6</a></div></div>
<div class="ttc" id="aclassarmnn_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>
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