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<div class="title">NeonSpaceToBatchNdWorkload.cpp</div> </div>
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<a href="_neon_space_to_batch_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 © 2020 Arm Ltd. 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="_neon_space_to_batch_nd_workload_8hpp.html">NeonSpaceToBatchNdWorkload.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 &quot;<a class="code" href="_neon_workload_utils_8hpp.html">NeonWorkloadUtils.hpp</a>&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_resolve_type_8hpp.html">ResolveType.hpp</a>&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;</div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;{</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;<span class="keyword">using namespace </span>armcomputetensorutils;</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;</div><div class="line"><a name="l00016"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ab29257da888af2c4971db1344d8a526c"> 16</a></span>&#160;<a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> <a class="code" href="namespacearmnn.html#ab29257da888af2c4971db1344d8a526c">NeonSpaceToBatchNdWorkloadValidate</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="l00017"></a><span class="lineno"> 17</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="l00018"></a><span class="lineno"> 18</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html">SpaceToBatchNdDescriptor</a>&amp; descriptor)</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;{</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; <span class="comment">// ArmNN blockShape is [H, W] Cl asks for W, H</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; int32_t blockHeight = boost::numeric_cast&lt;int32_t&gt;(descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[0]);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; int32_t blockWidth = boost::numeric_cast&lt;int32_t&gt;(descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[1]);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; arm_compute::Size2D paddingLeftTop = BuildArmComputeSize2D(</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a>[1].first, descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a>[0].first);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; arm_compute::Size2D paddingRightBottom = BuildArmComputeSize2D(</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a>[1].second, descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a>[0].second);</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; <span class="keywordflow">return</span> arm_compute::NESpaceToBatchLayer::validate(&amp;aclInputInfo,</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; blockWidth,</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; blockHeight,</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; paddingLeftTop,</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; paddingRightBottom,</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; &amp;aclOutputInfo);</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;</div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_space_to_batch_nd_workload.html#ad54e9fc1d5791024594d2c81975c9148"> 40</a></span>&#160;<a class="code" href="classarmnn_1_1_neon_space_to_batch_nd_workload.html#ad54e9fc1d5791024594d2c81975c9148">NeonSpaceToBatchNdWorkload::NeonSpaceToBatchNdWorkload</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_space_to_batch_nd_queue_descriptor.html">SpaceToBatchNdQueueDescriptor</a>&amp; desc,</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.html">WorkloadInfo</a>&amp; <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; : <a class="code" href="classarmnn_1_1_base_workload.html">BaseWorkload</a>&lt;<a class="code" href="structarmnn_1_1_space_to_batch_nd_queue_descriptor.html">SpaceToBatchNdQueueDescriptor</a>&gt;(desc, info)</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; <a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a765d2cee4ccce5b9467e0c2b6d25b84a">ValidateInputsOutputs</a>(<span class="stringliteral">&quot;NESpaceToBatchNdWorkload&quot;</span>, 1, 1);</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; arm_compute::ITensor&amp; input =</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; boost::polymorphic_pointer_downcast&lt;IAclTensorHandle&gt;(<a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">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="l00048"></a><span class="lineno"> 48</span>&#160; arm_compute::ITensor&amp; output =</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; boost::polymorphic_pointer_downcast&lt;IAclTensorHandle&gt;(<a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">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="l00050"></a><span class="lineno"> 50</span>&#160;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="comment">// ArmNN blockShape is [H, W] Cl asks for W, H</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; int32_t blockHeight = boost::numeric_cast&lt;int32_t&gt;(<a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">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_space_to_batch_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[0]);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; int32_t blockWidth = boost::numeric_cast&lt;int32_t&gt;(<a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">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_space_to_batch_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[1]);</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; arm_compute::Size2D paddingLeftTop = BuildArmComputeSize2D(</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">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_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a>[1].first, <a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">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_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a>[0].first);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; arm_compute::Size2D paddingRightBottom = BuildArmComputeSize2D(</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">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_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a>[1].second, <a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">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_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a>[0].second);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160;</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a> aclDataLayout = ConvertDataLayout(<a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">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_space_to_batch_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; input.info()-&gt;set_data_layout(aclDataLayout);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; output.info()-&gt;set_data_layout(aclDataLayout);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; m_Layer.reset(<span class="keyword">new</span> arm_compute::NESpaceToBatchLayer());</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; m_Layer-&gt;configure(&amp;input,</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; paddingLeftTop,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; paddingRightBottom,</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; &amp;output);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; m_Layer-&gt;prepare();</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160;}</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160;</div><div class="line"><a name="l00074"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_space_to_batch_nd_workload.html#ae071e8822437c78baea75c3aef3a263a"> 74</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_neon_space_to_batch_nd_workload.html#ae071e8822437c78baea75c3aef3a263a">NeonSpaceToBatchNdWorkload::Execute</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keywordflow">if</span> (m_Layer)</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; <a class="code" href="_neon_workload_utils_8hpp.html#a8bf91fd5e5875631bcf6abbcd97fe2f4">ARMNN_SCOPED_PROFILING_EVENT_NEON</a>(<span class="stringliteral">&quot;NeonSpaceToBatchNdWorkload_Execute&quot;</span>);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; m_Layer-&gt;run();</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; }</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160;}</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160;} <span class="comment">//namespace armnn</span></div><div class="ttc" id="namespacearmnn_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#l00026">Types.hpp:26</a></div></div>
<div class="ttc" id="_neon_workload_utils_8hpp_html_a8bf91fd5e5875631bcf6abbcd97fe2f4"><div class="ttname"><a href="_neon_workload_utils_8hpp.html#a8bf91fd5e5875631bcf6abbcd97fe2f4">ARMNN_SCOPED_PROFILING_EVENT_NEON</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_NEON(name)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.html#l00017">NeonWorkloadUtils.hpp:17</a></div></div>
<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_html_a85f98c94e11f65a6b73f831735c040f3"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a85f98c94e11f65a6b73f831735c040f3">armnn::SpaceToBatchNdDescriptor::m_PadList</a></div><div class="ttdeci">std::vector&lt; std::pair&lt; unsigned int, unsigned int &gt; &gt; m_PadList</div><div class="ttdoc">Specifies the padding values for the input dimension: heightPad{top, bottom} widthPad{left, right}. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00804">Descriptors.hpp:804</a></div></div>
<div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="structarmnn_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#l00049">WorkloadData.hpp:49</a></div></div>
<div class="ttc" id="classarmnn_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#l00053">Tensor.hpp:53</a></div></div>
<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::SpaceToBatchNdDescriptor::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#l00806">Descriptors.hpp:806</a></div></div>
<div class="ttc" id="_neon_workload_utils_8hpp_html"><div class="ttname"><a href="_neon_workload_utils_8hpp.html">NeonWorkloadUtils.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_html_a02e143524aefddd40b485fcf7dea6696"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">armnn::SpaceToBatchNdDescriptor::m_BlockShape</a></div><div class="ttdeci">std::vector&lt; unsigned int &gt; m_BlockShape</div><div class="ttdoc">Block shape value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00801">Descriptors.hpp:801</a></div></div>
<div class="ttc" id="structarmnn_1_1_workload_info_html"><div class="ttname"><a href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.html#l00016">WorkloadInfo.hpp:16</a></div></div>
<div class="ttc" id="_neon_space_to_batch_nd_workload_8hpp_html"><div class="ttname"><a href="_neon_space_to_batch_nd_workload_8hpp.html">NeonSpaceToBatchNdWorkload.hpp</a></div></div>
<div class="ttc" id="_resolve_type_8hpp_html"><div class="ttname"><a href="_resolve_type_8hpp.html">ResolveType.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_workload_html_a0a487c549c63319505095b855ea3c195"><div class="ttname"><a href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">armnn::BaseWorkload&lt; SpaceToBatchNdQueueDescriptor &gt;::m_Data</a></div><div class="ttdeci">const SpaceToBatchNdQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.html#l00046">Workload.hpp:46</a></div></div>
<div class="ttc" id="classarmnn_1_1_neon_space_to_batch_nd_workload_html_ae071e8822437c78baea75c3aef3a263a"><div class="ttname"><a href="classarmnn_1_1_neon_space_to_batch_nd_workload.html#ae071e8822437c78baea75c3aef3a263a">armnn::NeonSpaceToBatchNdWorkload::Execute</a></div><div class="ttdeci">virtual void Execute() const override</div><div class="ttdef"><b>Definition:</b> <a href="_neon_space_to_batch_nd_workload_8cpp_source.html#l00074">NeonSpaceToBatchNdWorkload.cpp:74</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="structarmnn_1_1_space_to_batch_nd_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_queue_descriptor.html">armnn::SpaceToBatchNdQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00343">WorkloadData.hpp:343</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_html_a765d2cee4ccce5b9467e0c2b6d25b84a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.html#a765d2cee4ccce5b9467e0c2b6d25b84a">armnn::QueueDescriptor::ValidateInputsOutputs</a></div><div class="ttdeci">void ValidateInputsOutputs(const std::string &amp;descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8cpp_source.html#l00459">WorkloadData.cpp:459</a></div></div>
<div class="ttc" id="namespacearmnn_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#l00048">Types.hpp:48</a></div></div>
<div class="ttc" id="classarmnn_1_1_neon_space_to_batch_nd_workload_html_ad54e9fc1d5791024594d2c81975c9148"><div class="ttname"><a href="classarmnn_1_1_neon_space_to_batch_nd_workload.html#ad54e9fc1d5791024594d2c81975c9148">armnn::NeonSpaceToBatchNdWorkload::NeonSpaceToBatchNdWorkload</a></div><div class="ttdeci">NeonSpaceToBatchNdWorkload(const SpaceToBatchNdQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_space_to_batch_nd_workload_8cpp_source.html#l00040">NeonSpaceToBatchNdWorkload.cpp:40</a></div></div>
<div class="ttc" id="structarmnn_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#l00031">WorkloadData.hpp:31</a></div></div>
<div class="ttc" id="structarmnn_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#l00030">WorkloadData.hpp:30</a></div></div>
<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.html">armnn::SpaceToBatchNdDescriptor</a></div><div class="ttdoc">A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00778">Descriptors.hpp:778</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_workload_html"><div class="ttname"><a href="classarmnn_1_1_base_workload.html">armnn::BaseWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.html#l00028">Workload.hpp:28</a></div></div>
<div class="ttc" id="namespacearmnn_html_ab29257da888af2c4971db1344d8a526c"><div class="ttname"><a href="namespacearmnn.html#ab29257da888af2c4971db1344d8a526c">armnn::NeonSpaceToBatchNdWorkloadValidate</a></div><div class="ttdeci">arm_compute::Status NeonSpaceToBatchNdWorkloadValidate(const TensorInfo &amp;input, const TensorInfo &amp;output, const SpaceToBatchNdDescriptor &amp;descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_space_to_batch_nd_workload_8cpp_source.html#l00016">NeonSpaceToBatchNdWorkload.cpp:16</a></div></div>
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