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<div class="title">ClBatchToSpaceNdWorkload.cpp</div> </div>
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<a href="_cl_batch_to_space_nd_workload_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, 2019-2023 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="_cl_batch_to_space_nd_workload_8hpp.html">ClBatchToSpaceNdWorkload.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="_polymorphic_downcast_8hpp.html">armnn/utility/PolymorphicDowncast.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="preprocessor">#include &lt;<a class="code" href="_cl_tensor_handle_8hpp.html">cl/ClTensorHandle.hpp</a>&gt;</span></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"> 15</span>&#160;<span class="keyword">using namespace </span>armcomputetensorutils;</div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160; </div>
<div class="line"><a name="l00017"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ae87476befb36d9cc4fb926337ba65b5d"> 17</a></span>&#160;<a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> <a class="code" href="namespacearmnn.html#ae87476befb36d9cc4fb926337ba65b5d">ClBatchToSpaceNdWorkloadValidate</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; input,</div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; output,</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html">BatchToSpaceNdDescriptor</a>&amp; descriptor)</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; arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; </div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> statusBatchToSpace = <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::OK);</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> statusReshapeInput = <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::OK);</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> statusReshapeOutput = <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::OK);</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; arm_compute::TensorInfo aclReshapeInputInfo = aclInputInfo;</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; arm_compute::TensorInfo aclReshapeOutputInfo = aclOutputInfo;</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="comment">// When a spacial dimension is missing (rank=3) set W to 1</span></div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> rank = input.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keywordflow">if</span> (rank == 3)</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; {</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; <span class="keyword">const</span> arm_compute::TensorShape inputShape = aclInputInfo.tensor_shape();</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="keyword">const</span> arm_compute::TensorShape outputShape = aclOutputInfo.tensor_shape();</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; </div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; {</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="comment">// In ACL dimensions are right to left: C, W, H, N</span></div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; aclInputInfo.set_tensor_shape({inputShape.x(), 1, inputShape.y(), inputShape.z()});</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; aclOutputInfo.set_tensor_shape({outputShape.x(), 1, outputShape.y(), outputShape.z()});</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> <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>)</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="comment">// In ACL dimensions are right to left: W, H, C, N</span></div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; aclInputInfo.set_tensor_shape({1, inputShape.x(), inputShape.y(), inputShape.z()});</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; aclOutputInfo.set_tensor_shape({1, outputShape.x(), outputShape.y(), outputShape.z()});</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"> 50</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; {</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Unsupported or unknown DataLayout&quot;</span>, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; }</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; statusReshapeInput = arm_compute::CLReshapeLayer::validate(&amp;aclInputInfo, &amp;aclReshapeInputInfo);</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; statusReshapeOutput = arm_compute::CLReshapeLayer::validate(&amp;aclReshapeOutputInfo, &amp;aclOutputInfo);</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; </div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <span class="comment">// ArmNN blockShape is [H, W] ACl asks for W, H</span></div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; int32_t blockHeight = armnn::numeric_cast&lt;int32_t&gt;(descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[0]);</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; int32_t blockWidth = (rank == 3) ? 1 : armnn::numeric_cast&lt;int32_t&gt;(descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[1]);</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; <span class="keyword">const</span> arm_compute::CropInfo cropInfo = BuildArmComputeCropInfo(descriptor, rank);</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; </div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; statusBatchToSpace = arm_compute::CLBatchToSpaceLayer::validate(rank == 3 ? &amp;aclReshapeInputInfo : &amp;aclInputInfo,</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; blockWidth,</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; blockHeight,</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; rank == 3 ? &amp;aclReshapeOutputInfo : &amp;aclOutputInfo,</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; cropInfo);</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; <span class="keywordflow">if</span> (statusReshapeInput.error_code() == arm_compute::ErrorCode::OK &amp;&amp;</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; statusReshapeOutput.error_code() == arm_compute::ErrorCode::OK &amp;&amp;</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; statusBatchToSpace.error_code() == arm_compute::ErrorCode::OK)</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="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::OK,</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="stringliteral">&quot;All BatchToSpace layers validate status OK.&quot;</span>);</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; }</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keywordflow">else</span></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="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::RUNTIME_ERROR,</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <span class="stringliteral">&quot;BatchToSpace layer validate status failed.&quot;</span></div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; + statusBatchToSpace.error_description()</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; + statusReshapeInput.error_description()</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; + statusReshapeOutput.error_description());</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;}</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"><a class="line" href="classarmnn_1_1_cl_batch_to_space_nd_workload.html#a4bcd4675749ac3d8890201c139d4e5c6"> 88</a></span>&#160;<a class="code" href="classarmnn_1_1_cl_batch_to_space_nd_workload.html#a4bcd4675749ac3d8890201c139d4e5c6">ClBatchToSpaceNdWorkload::ClBatchToSpaceNdWorkload</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_to_space_nd_queue_descriptor.html">BatchToSpaceNdQueueDescriptor</a>&amp; descriptor,</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.html">WorkloadInfo</a>&amp; info,</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <span class="keyword">const</span> arm_compute::CLCompileContext&amp; clCompileContext)</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; : <a class="code" href="classarmnn_1_1_cl_base_workload.html">ClBaseWorkload</a>&lt;<a class="code" href="structarmnn_1_1_batch_to_space_nd_queue_descriptor.html">BatchToSpaceNdQueueDescriptor</a>&gt;(descriptor, <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</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="comment">// Report Profiling Details</span></div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <a class="code" href="_profiling_8hpp.html#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>(<span class="stringliteral">&quot;ClBatchToSpaceWorkload_Construct&quot;</span>,</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>,</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>,</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; this-&gt;GetGuid());</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; <a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a765d2cee4ccce5b9467e0c2b6d25b84a">ValidateInputsOutputs</a>(<span class="stringliteral">&quot;ClBatchToSpaceNdWorkload&quot;</span>, 1, 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; arm_compute::ICLTensor&amp; input = <span class="keyword">static_cast&lt;</span><a class="code" href="classarmnn_1_1_i_cl_tensor_handle.html">IClTensorHandle</a>*<span class="keyword">&gt;</span>(<a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0])-&gt;GetTensor();</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; arm_compute::ICLTensor&amp; output = <span class="keyword">static_cast&lt;</span><a class="code" href="classarmnn_1_1_i_cl_tensor_handle.html">IClTensorHandle</a>*<span class="keyword">&gt;</span>(<a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0])-&gt;GetTensor();</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; <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a> aclDataLayout = ConvertDataLayout(<a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; input.info()-&gt;set_data_layout(aclDataLayout);</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; output.info()-&gt;set_data_layout(aclDataLayout);</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; arm_compute::TensorInfo aclReshapeInputInfo = BuildArmComputeTensorInfo(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos[0],</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; arm_compute::TensorInfo aclReshapeOutputInfo = BuildArmComputeTensorInfo(<a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_OutputTensorInfos[0],</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; </div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> rank = <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos[0].GetNumDimensions();</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; <span class="keywordflow">if</span> (rank == 3)</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; <span class="keyword">const</span> arm_compute::TensorShape inputShape = input.info()-&gt;tensor_shape();</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <span class="keyword">const</span> arm_compute::TensorShape outputShape = output.info()-&gt;tensor_shape();</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; <span class="comment">// When a spacial dimension is missing set W to 1</span></div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</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; <span class="comment">// In ACL dimensions are right to left: C, W, H, N</span></div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; aclReshapeInputInfo.set_tensor_shape({inputShape.x(), 1, inputShape.y(), inputShape.z()});</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; aclReshapeOutputInfo.set_tensor_shape({outputShape.x(), 1, outputShape.y(), outputShape.z()});</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; }</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>)</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; {</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <span class="comment">// In ACL dimensions are right to left: W, H, C, N</span></div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; aclReshapeInputInfo.set_tensor_shape({1, inputShape.x(), inputShape.y(), inputShape.z()});</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; aclReshapeOutputInfo.set_tensor_shape({1, outputShape.x(), outputShape.y(), outputShape.z()});</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; }</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; {</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Unsupported or unknown DataLayout&quot;</span>, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; }</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; m_ReshapeInputTensor.allocator()-&gt;init(aclReshapeInputInfo);</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; m_ReshapeOutputTensor.allocator()-&gt;init(aclReshapeOutputInfo);</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; InitialiseArmComputeTensorEmpty(m_ReshapeInputTensor);</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; InitialiseArmComputeTensorEmpty(m_ReshapeOutputTensor);</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; </div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; m_LayerReshapeInput.reset(<span class="keyword">new</span> arm_compute::CLReshapeLayer());</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; m_LayerReshapeOutput.reset(<span class="keyword">new</span> arm_compute::CLReshapeLayer());</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; m_LayerReshapeInput-&gt;configure(clCompileContext, &amp;input, &amp;m_ReshapeInputTensor);</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; m_LayerReshapeOutput-&gt;configure(clCompileContext, &amp;m_ReshapeOutputTensor, &amp;output);</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; }</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; </div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="comment">// ArmNN blockShape is [H, W] ACl asks for W, H</span></div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; int32_t blockHeight = armnn::numeric_cast&lt;int32_t&gt;(descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[0]);</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; int32_t blockWidth = (rank == 3) ? 1 : armnn::numeric_cast&lt;int32_t&gt;(descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[1]);</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; </div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <span class="keyword">const</span> arm_compute::CropInfo cropInfo = BuildArmComputeCropInfo(descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>);</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; </div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; {</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; <a class="code" href="_cl_workload_utils_8hpp.html#a2d57ef1645138f5f8a6dbd2ce92dc072">ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID</a>(<span class="stringliteral">&quot;ClBatchToSpaceNdWorkload_configure&quot;</span>);</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; m_Layer.configure(clCompileContext,</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; (rank == 3) ? &amp;m_ReshapeInputTensor : &amp;input,</div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; blockWidth,</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; blockHeight,</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; (rank == 3) ? &amp;m_ReshapeOutputTensor : &amp;output,</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; cropInfo);</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; }</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160;}</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; </div>
<div class="line"><a name="l00167"></a><span class="lineno"><a class="line" href="classarmnn_1_1_cl_batch_to_space_nd_workload.html#ae071e8822437c78baea75c3aef3a263a"> 167</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_cl_batch_to_space_nd_workload.html#ae071e8822437c78baea75c3aef3a263a">ClBatchToSpaceNdWorkload::Execute</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; <a class="code" href="_cl_workload_utils_8hpp.html#a2d57ef1645138f5f8a6dbd2ce92dc072">ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID</a>(<span class="stringliteral">&quot;ClBatchToSpaceNdWorkload_Execute&quot;</span>);</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; <span class="keywordflow">if</span> (m_LayerReshapeInput)</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; {</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; m_LayerReshapeInput-&gt;run();</div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; }</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; <a class="code" href="namespacearmnn.html#a52c299ca6a3884c609583a5a0663db80">RunClFunction</a>(m_Layer, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <span class="keywordflow">if</span> (m_LayerReshapeOutput)</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; {</div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; m_LayerReshapeOutput-&gt;run();</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; }</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160;}</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; </div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160;} <span class="comment">//namespace armnn</span></div>
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</div><!-- doc-content -->
<div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00062">Types.hpp:62</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div><div class="ttdeci">@ NHWC</div></div>
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<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>
<div class="ttc" id="anamespacearmnn_html_ae87476befb36d9cc4fb926337ba65b5d"><div class="ttname"><a href="namespacearmnn.html#ae87476befb36d9cc4fb926337ba65b5d">armnn::ClBatchToSpaceNdWorkloadValidate</a></div><div class="ttdeci">arm_compute::Status ClBatchToSpaceNdWorkloadValidate(const TensorInfo &amp;input, const TensorInfo &amp;output, const BatchToSpaceNdDescriptor &amp;descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_cl_batch_to_space_nd_workload_8cpp_source.html#l00017">ClBatchToSpaceNdWorkload.cpp:17</a></div></div>
<div class="ttc" id="astructarmnn_1_1_batch_to_space_nd_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_queue_descriptor.html">armnn::BatchToSpaceNdQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00462">WorkloadData.hpp:462</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00197">Tensor.hpp:197</a></div></div>
<div class="ttc" id="astructarmnn_1_1_batch_to_space_nd_descriptor_html_a02e143524aefddd40b485fcf7dea6696"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">armnn::BatchToSpaceNdDescriptor::m_BlockShape</a></div><div class="ttdeci">std::vector&lt; unsigned int &gt; m_BlockShape</div><div class="ttdoc">Block shape values.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00898">Descriptors.hpp:898</a></div></div>
<div class="ttc" id="a_exceptions_8hpp_html_aa3be76aec4ce713822a5ea1ecbb7bc61"><div class="ttname"><a href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a></div><div class="ttdeci">#define CHECK_LOCATION()</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00203">Exceptions.hpp:203</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_cl_base_workload_html"><div class="ttname"><a href="classarmnn_1_1_cl_base_workload.html">armnn::ClBaseWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_base_workload_8hpp_source.html#l00013">ClBaseWorkload.hpp:13</a></div></div>
<div class="ttc" id="a_cl_batch_to_space_nd_workload_8hpp_html"><div class="ttname"><a href="_cl_batch_to_space_nd_workload_8hpp.html">ClBatchToSpaceNdWorkload.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_cl_batch_to_space_nd_workload_html_ae071e8822437c78baea75c3aef3a263a"><div class="ttname"><a href="classarmnn_1_1_cl_batch_to_space_nd_workload.html#ae071e8822437c78baea75c3aef3a263a">armnn::ClBatchToSpaceNdWorkload::Execute</a></div><div class="ttdeci">virtual void Execute() const override</div><div class="ttdef"><b>Definition:</b> <a href="_cl_batch_to_space_nd_workload_8cpp_source.html#l00167">ClBatchToSpaceNdWorkload.cpp:167</a></div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_with_parameters_html_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00066">WorkloadData.hpp:66</a></div></div>
<div class="ttc" id="a_cl_workload_utils_8hpp_html_a2d57ef1645138f5f8a6dbd2ce92dc072"><div class="ttname"><a href="_cl_workload_utils_8hpp.html#a2d57ef1645138f5f8a6dbd2ce92dc072">ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID(label)</div><div class="ttdoc">Creates a profiling event that uses GetGuid() and GetName() from the calling class.</div><div class="ttdef"><b>Definition:</b> <a href="_cl_workload_utils_8hpp_source.html#l00036">ClWorkloadUtils.hpp:36</a></div></div>
<div class="ttc" id="astructarmnn_1_1_workload_info_html"><div class="ttname"><a href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer.</div><div class="ttdef"><b>Definition:</b> <a href="_workload_info_8hpp_source.html#l00016">WorkloadInfo.hpp:16</a></div></div>
<div class="ttc" id="a_polymorphic_downcast_8hpp_html"><div class="ttname"><a href="_polymorphic_downcast_8hpp.html">PolymorphicDowncast.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_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="anamespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div><div class="ttdeci">@ info</div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_html_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00027">WorkloadData.hpp:27</a></div></div>
<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="a_profiling_8hpp_html_a786492a3881a4c760ab1eec2149f4aba"><div class="ttname"><a href="_profiling_8hpp.html#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a></div><div class="ttdeci">#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.html#l00227">Profiling.hpp:227</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_i_cl_tensor_handle_html"><div class="ttname"><a href="classarmnn_1_1_i_cl_tensor_handle.html">armnn::IClTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_cl_tensor_handle_8hpp_source.html#l00013">IClTensorHandle.hpp:13</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a67a0db04d321a74b7e7fcfd3f1a3f70b"><div class="ttname"><a href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a></div><div class="ttdeci">Status</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00042">Types.hpp:42</a></div></div>
<div class="ttc" id="a_cl_tensor_handle_8hpp_html"><div class="ttname"><a href="_cl_tensor_handle_8hpp.html">ClTensorHandle.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_base_workload_html_afb8d2c8817c75de9d01a4c0e0d5c160b"><div class="ttname"><a href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">armnn::BaseWorkload&lt; BatchToSpaceNdQueueDescriptor &gt;::m_Data</a></div><div class="ttdeci">BatchToSpaceNdQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.html#l00089">Workload.hpp:89</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a52c299ca6a3884c609583a5a0663db80"><div class="ttname"><a href="namespacearmnn.html#a52c299ca6a3884c609583a5a0663db80">armnn::RunClFunction</a></div><div class="ttdeci">void RunClFunction(arm_compute::IFunction &amp;function, const CheckLocation &amp;location)</div><div class="ttdef"><b>Definition:</b> <a href="_cl_workload_utils_8hpp_source.html#l00167">ClWorkloadUtils.hpp:167</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_cl_batch_to_space_nd_workload_html_a4bcd4675749ac3d8890201c139d4e5c6"><div class="ttname"><a href="classarmnn_1_1_cl_batch_to_space_nd_workload.html#a4bcd4675749ac3d8890201c139d4e5c6">armnn::ClBatchToSpaceNdWorkload::ClBatchToSpaceNdWorkload</a></div><div class="ttdeci">ClBatchToSpaceNdWorkload(const BatchToSpaceNdQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info, const arm_compute::CLCompileContext &amp;clCompileContext)</div><div class="ttdef"><b>Definition:</b> <a href="_cl_batch_to_space_nd_workload_8cpp_source.html#l00088">ClBatchToSpaceNdWorkload.cpp:88</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="astructarmnn_1_1_batch_to_space_nd_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::BatchToSpaceNdDescriptor::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#l00902">Descriptors.hpp:902</a></div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_html_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00026">WorkloadData.hpp:26</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div><div class="ttdeci">@ NCHW</div></div>
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