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<div class="title">DepthToSpace.cpp</div> </div>
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<a href="_depth_to_space_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 © 2019 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="_depth_to_space_8hpp.html">DepthToSpace.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> <span class="preprocessor">#include <<a class="code" href="_permute_8hpp.html">armnnUtils/Permute.hpp</a>></span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>  </div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_assert_8hpp.html">armnn/utility/Assert.hpp</a>></span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>  </div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="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"> 15</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> {</div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  </div>
<div class="line"><a name="l00018"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ab023d9a7687e35c0f108458a094c1f56"> 18</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#ab023d9a7687e35c0f108458a094c1f56">DepthToSpace</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& inputInfo,</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html">DepthToSpaceDescriptor</a>& descriptor,</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keyword">const</span> <span class="keywordtype">void</span>* inputData,</div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <span class="keywordtype">void</span>* outputData,</div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dataTypeSize)</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="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> blockSize = descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a>;</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <a class="code" href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(blockSize != 0u);</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  </div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keyword">const</span> <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="l00028"></a><span class="lineno"> 28</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batches = inputShape[0];</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  </div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a> dataLayoutIndexed(descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</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> inDepth = inputShape[dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>()];</div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inHeight = inputShape[dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()];</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inWidth = inputShape[dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()];</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="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outDepth = inDepth / (blockSize * blockSize);</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  </div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="comment">// The 4D input data can be interpreted as 6D (implicitly reshaped) as follows:</span></div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="comment">// [batch, block size, block size, inDepth, inHeight, inWidth] for NCHW and</span></div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="comment">// [batch, inHeight, inWidth, blockSize, blockSize, outDepth] for NHWC.</span></div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="comment">// DepthToSpace can then be implemented as a permutation in 6D resulting in</span></div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="comment">// the following shapes:</span></div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="comment">// [batch, outDepth, inHeight, blockSize, inWidth, blockSize] for NCHW and</span></div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="comment">// [batch, inHeight, blockSize, inWidth, blockSize, outDepth] for NHWC.</span></div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="comment">//</span></div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="comment">// NOTE:</span></div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="comment">// Since 6D tensors are not currently supported, in practice we need to handle each</span></div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="comment">// batch separately and execute 5D permutations</span></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>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> permDestShape;</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a> permVector{};</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == DataLayout::NCHW)</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>  permDestShape = <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>({ outDepth, inHeight, blockSize, inWidth, blockSize });</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  permVector = { 2, 4, 0, 1, 3 };</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  }</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  {</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  permDestShape = <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>({ inHeight, blockSize, inWidth, blockSize, outDepth });</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  permVector = { 0, 2, 1, 3, 4 };</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  }</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  </div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numElementsPerBatch = inputShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>() / batches;</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> batchIndex = 0u; batchIndex < batches; ++batchIndex)</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">const</span> uintptr_t batchDataOffset = batchIndex * (numElementsPerBatch * dataTypeSize);</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  </div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(permDestShape,</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  permVector,</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">static_cast<</span><span class="keyword">const </span><span class="keywordtype">void</span>*<span class="keyword">></span>(<span class="keyword">reinterpret_cast<</span><span class="keyword">const </span>uint8_t*<span class="keyword">></span>(inputData) + batchDataOffset),</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">static_cast<</span><span class="keywordtype">void</span>*<span class="keyword">></span>(<span class="keyword">reinterpret_cast<</span>uint8_t*<span class="keyword">></span>(outputData) + batchDataOffset),</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  dataTypeSize);</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  }</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span> }</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  </div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span> } <span class="comment">// namespace armnn</span></div>
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<div class="ttc" id="a_assert_8hpp_html_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.html#l00014">Assert.hpp:14</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00152">Tensor.hpp:152</a></div></div>
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<div class="ttc" id="aclassarmnn_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>
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<div class="ttc" id="astructarmnn_1_1_space_to_depth_descriptor_html_a6c6b8957f1e176867e5fb05b1a1a1486"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.html#a6c6b8957f1e176867e5fb05b1a1a1486">armnn::SpaceToDepthDescriptor::m_BlockSize</a></div><div class="ttdeci">unsigned int m_BlockSize</div><div class="ttdoc">Scalar specifying the input block size. It must be >= 1.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01092">Descriptors.hpp:1092</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 & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00191">Tensor.hpp:191</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>
<div class="ttc" id="anamespacearmnn_html_ab023d9a7687e35c0f108458a094c1f56"><div class="ttname"><a href="namespacearmnn.html#ab023d9a7687e35c0f108458a094c1f56">armnn::DepthToSpace</a></div><div class="ttdeci">void DepthToSpace(const TensorInfo &inputInfo, const DepthToSpaceDescriptor &descriptor, const void *inputData, void *outputData, unsigned int dataTypeSize)</div><div class="ttdef"><b>Definition:</b> <a href="_depth_to_space_8cpp_source.html#l00018">DepthToSpace.cpp:18</a></div></div>
<div class="ttc" id="a_data_layout_indexed_8hpp_html"><div class="ttname"><a href="_data_layout_indexed_8hpp.html">DataLayoutIndexed.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_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="ttdoc">Function that calculates the tensor elements by multiplying all dimension size which are Specified.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00181">Tensor.cpp:181</a></div></div>
<div class="ttc" id="astructarmnn_1_1_space_to_depth_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.html">armnn::SpaceToDepthDescriptor</a></div><div class="ttdoc">A SpaceToDepthDescriptor for the SpaceToDepthLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01075">Descriptors.hpp:1075</a></div></div>
<div class="ttc" id="astructarmnn_1_1_space_to_depth_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::SpaceToDepthDescriptor::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#l01095">Descriptors.hpp:1095</a></div></div>
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