diff --git a/latest/classarmnn_1_1_batch_to_space_nd_layer.html b/latest/classarmnn_1_1_batch_to_space_nd_layer.html
index c40e309..5f7af07 100644
--- a/latest/classarmnn_1_1_batch_to_space_nd_layer.html
+++ b/latest/classarmnn_1_1_batch_to_space_nd_layer.html
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 <div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;}</div>
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-<p class="reference">References <a class="el" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a6ee06c6045d0c5b6565a247955ef0fc2">armnn::BatchToSpaceNd</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.html#a694a8411c8c799da95306034d274930b">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="_layer_with_parameters_8hpp_source.html#l00044">LayerWithParameters&lt; BatchToSpaceNdDescriptor &gt;::PrepInfoAndDesc()</a>, and <a class="el" href="_layer_8cpp_source.html#l00287">Layer::SetAdditionalInfo()</a>.</p>
+<p class="reference">References <a class="el" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a6ee06c6045d0c5b6565a247955ef0fc2">armnn::BatchToSpaceNd</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.html#a694a8411c8c799da95306034d274930b">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="_layer_with_parameters_8hpp_source.html#l00044">LayerWithParameters&lt; BatchToSpaceNdDescriptor &gt;::PrepInfoAndDesc()</a>, and <a class="el" href="_layer_8cpp_source.html#l00303">Layer::SetAdditionalInfo()</a>.</p>
 
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@@ -523,10 +523,10 @@
 
 <p>Reimplemented from <a class="el" href="classarmnn_1_1_layer.html#a46fc3fdd4b2a5dd6d184e57983cf20bc">Layer</a>.</p>
 
-<p class="definition">Definition at line <a class="el" href="_batch_to_space_nd_layer_8cpp_source.html#l00078">78</a> of file <a class="el" href="_batch_to_space_nd_layer_8cpp_source.html">BatchToSpaceNdLayer.cpp</a>.</p>
-<div class="fragment"><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;    strategy.<a class="code" href="classarmnn_1_1_i_strategy.html#ad4f8c9ff973cf6a603d26b56c5b34967">ExecuteStrategy</a>(<span class="keyword">this</span>, <a class="code" href="classarmnn_1_1_layer_with_parameters.html#afa3e8a8f23589b1eaddbe203825bbdcf">GetParameters</a>(), {}, <a class="code" href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</div>
-<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;}</div>
+<p class="definition">Definition at line <a class="el" href="_batch_to_space_nd_layer_8cpp_source.html#l00083">83</a> of file <a class="el" href="_batch_to_space_nd_layer_8cpp_source.html">BatchToSpaceNdLayer.cpp</a>.</p>
+<div class="fragment"><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;{</div>
+<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    strategy.<a class="code" href="classarmnn_1_1_i_strategy.html#ad4f8c9ff973cf6a603d26b56c5b34967">ExecuteStrategy</a>(<span class="keyword">this</span>, <a class="code" href="classarmnn_1_1_layer_with_parameters.html#afa3e8a8f23589b1eaddbe203825bbdcf">GetParameters</a>(), {}, <a class="code" href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</div>
+<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;}</div>
 </div><!-- fragment -->
 <p class="reference">References <a class="el" href="classarmnn_1_1_i_strategy.html#ad4f8c9ff973cf6a603d26b56c5b34967">IStrategy::ExecuteStrategy()</a>, <a class="el" href="_layer_8hpp_source.html#l00332">Layer::GetName()</a>, and <a class="el" href="_layer_with_parameters_8hpp_source.html#l00019">LayerWithParameters&lt; BatchToSpaceNdDescriptor &gt;::GetParameters()</a>.</p>
 
@@ -567,30 +567,30 @@
 
 <p>Reimplemented from <a class="el" href="classarmnn_1_1_layer.html#a65ca562c882ad619684445a1402f415a">Layer</a>.</p>
 
-<p class="definition">Definition at line <a class="el" href="_batch_to_space_nd_layer_8cpp_source.html#l00053">53</a> of file <a class="el" href="_batch_to_space_nd_layer_8cpp_source.html">BatchToSpaceNdLayer.cpp</a>.</p>
-<div class="fragment"><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;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; inputShape = inputShapes[0];</div>
-<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape(inputShape);</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;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> accumulatedBlockShape = std::accumulate(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>.begin(),</div>
-<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;                                                         <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>.end(),</div>
-<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;                                                         1U,</div>
-<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;                                                         std::multiplies&lt;&gt;());</div>
-<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    outputShape[0] = (inputShape[0] / accumulatedBlockShape) &lt; 1 ? 1 : (inputShape[0] / accumulatedBlockShape) ;</div>
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-<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <span class="comment">// In a 4D tensor, there will be 2 spatialDimensions (H and W), and the for loop will run twice.</span></div>
-<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    <span class="comment">// In a 3D tensor, there will be 1 spatialDimensions, and the for loop will run once.</span></div>
-<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> firstSpatialDimension = <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</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">DataLayout::NCHW</a> ? 2 : 1;</div>
-<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>.size(); ++i)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> spatialDimension = firstSpatialDimension + i;</div>
-<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> cropSize = <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a3941f674c071c9503e00d2b59e92e454">m_Crops</a>[i].first + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a3941f674c071c9503e00d2b59e92e454">m_Crops</a>[i].second;</div>
-<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = inputShape[spatialDimension] * <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[i];</div>
-<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        outputShape[spatialDimension] = outputSize - cropSize;</div>
-<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    }</div>
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-<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    <span class="keywordflow">return</span> std::vector&lt;TensorShape&gt;({ outputShape });</div>
-<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;}</div>
+<p class="definition">Definition at line <a class="el" href="_batch_to_space_nd_layer_8cpp_source.html#l00058">58</a> of file <a class="el" href="_batch_to_space_nd_layer_8cpp_source.html">BatchToSpaceNdLayer.cpp</a>.</p>
+<div class="fragment"><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;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; inputShape = inputShapes[0];</div>
+<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape(inputShape);</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> accumulatedBlockShape = std::accumulate(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>.begin(),</div>
+<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;                                                         <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>.end(),</div>
+<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;                                                         1U,</div>
+<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;                                                         std::multiplies&lt;&gt;());</div>
+<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    outputShape[0] = (inputShape[0] / accumulatedBlockShape) &lt; 1 ? 1 : (inputShape[0] / accumulatedBlockShape) ;</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="comment">// In a 4D tensor, there will be 2 spatialDimensions (H and W), and the for loop will run twice.</span></div>
+<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    <span class="comment">// In a 3D tensor, there will be 1 spatialDimensions, and the for loop will run once.</span></div>
+<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> firstSpatialDimension = <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</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">DataLayout::NCHW</a> ? 2 : 1;</div>
+<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>.size(); ++i)</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">   74</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> spatialDimension = firstSpatialDimension + i;</div>
+<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> cropSize = <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a3941f674c071c9503e00d2b59e92e454">m_Crops</a>[i].first + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a3941f674c071c9503e00d2b59e92e454">m_Crops</a>[i].second;</div>
+<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = inputShape[spatialDimension] * <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.html#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a>[i];</div>
+<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;        outputShape[spatialDimension] = outputSize - cropSize;</div>
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+<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;    <span class="keywordflow">return</span> std::vector&lt;TensorShape&gt;({ outputShape });</div>
+<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;}</div>
 </div><!-- fragment -->
 <p class="reference">References <a class="el" href="_descriptors_8hpp_source.html#l00898">BatchToSpaceNdDescriptor::m_BlockShape</a>, <a class="el" href="_descriptors_8hpp_source.html#l00900">BatchToSpaceNdDescriptor::m_Crops</a>, <a class="el" href="_descriptors_8hpp_source.html#l00902">BatchToSpaceNdDescriptor::m_DataLayout</a>, <a class="el" href="_layer_with_parameters_8hpp_source.html#l00052">LayerWithParameters&lt; BatchToSpaceNdDescriptor &gt;::m_Param</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p>
 
@@ -641,12 +641,17 @@
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-<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;    <a class="code" href="classarmnn_1_1_layer.html#aeb2d638cc0e02c10075e015100996f2d">ValidateAndCopyShape</a>(outputShape, inferredShapes[0], <a class="code" href="classarmnn_1_1_layer.html#afe508761cc8318b15329ba4acf7fbfec">m_ShapeInferenceMethod</a>, <span class="stringliteral">&quot;BatchToSpaceNdLayer&quot;</span>);</div>
-<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;}</div>
+<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;    <span class="keywordflow">if</span> (inferredShapes.size() != 1)</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">throw</span> <a class="code" href="classarmnn_1_1_layer_validation_exception.html">armnn::LayerValidationException</a>(<span class="stringliteral">&quot;inferredShapes has &quot;</span></div>
+<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;                                              + std::to_string(inferredShapes.size()) +</div>
+<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;                                              <span class="stringliteral">&quot; elements - should only have 1.&quot;</span>);</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;    <a class="code" href="classarmnn_1_1_layer.html#aeb2d638cc0e02c10075e015100996f2d">ValidateAndCopyShape</a>(outputShape, inferredShapes[0], <a class="code" href="classarmnn_1_1_layer.html#afe508761cc8318b15329ba4acf7fbfec">m_ShapeInferenceMethod</a>, <span class="stringliteral">&quot;BatchToSpaceNdLayer&quot;</span>);</div>
+<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;}</div>
 </div><!-- fragment -->
-<p class="reference">References <a class="el" href="_assert_8hpp_source.html#l00014">ARMNN_ASSERT</a>, <a class="el" href="_exceptions_8hpp_source.html#l00203">CHECK_LOCATION</a>, <a class="el" href="_layer_8hpp_source.html#l00337">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00339">Layer::GetOutputSlot()</a>, <a class="el" href="_tensor_8hpp_source.html#l00193">TensorInfo::GetShape()</a>, <a class="el" href="_layer_8cpp_source.html#l00592">InputSlot::GetTensorInfo()</a>, <a class="el" href="_layer_8cpp_source.html#l00092">OutputSlot::GetTensorInfo()</a>, <a class="el" href="_batch_to_space_nd_layer_8cpp_source.html#l00053">BatchToSpaceNdLayer::InferOutputShapes()</a>, <a class="el" href="_layer_8hpp_source.html#l00441">Layer::m_ShapeInferenceMethod</a>, <a class="el" href="_layer_8cpp_source.html#l00435">Layer::ValidateAndCopyShape()</a>, <a class="el" href="_layer_8cpp_source.html#l00391">Layer::VerifyLayerConnections()</a>, and <a class="el" href="_layer_8cpp_source.html#l00504">Layer::VerifyShapeInferenceType()</a>.</p>
+<p class="reference">References <a class="el" href="_exceptions_8hpp_source.html#l00203">CHECK_LOCATION</a>, <a class="el" href="_layer_8hpp_source.html#l00337">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00339">Layer::GetOutputSlot()</a>, <a class="el" href="_tensor_8hpp_source.html#l00193">TensorInfo::GetShape()</a>, <a class="el" href="_layer_8cpp_source.html#l00614">InputSlot::GetTensorInfo()</a>, <a class="el" href="_layer_8cpp_source.html#l00100">OutputSlot::GetTensorInfo()</a>, <a class="el" href="_batch_to_space_nd_layer_8cpp_source.html#l00058">BatchToSpaceNdLayer::InferOutputShapes()</a>, <a class="el" href="_layer_8hpp_source.html#l00441">Layer::m_ShapeInferenceMethod</a>, <a class="el" href="_layer_8cpp_source.html#l00457">Layer::ValidateAndCopyShape()</a>, <a class="el" href="_layer_8cpp_source.html#l00410">Layer::VerifyLayerConnections()</a>, and <a class="el" href="_layer_8cpp_source.html#l00526">Layer::VerifyShapeInferenceType()</a>.</p>
 
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@@ -656,27 +661,27 @@
 </ul>
 </div><!-- contents -->
 </div><!-- doc-content -->
-<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_output_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00092">Layer.cpp:92</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_output_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00100">Layer.cpp:100</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="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_layer_html_aeb2d638cc0e02c10075e015100996f2d"><div class="ttname"><a href="classarmnn_1_1_layer.html#aeb2d638cc0e02c10075e015100996f2d">armnn::Layer::ValidateAndCopyShape</a></div><div class="ttdeci">void ValidateAndCopyShape(const TensorShape &amp;outputShape, const TensorShape &amp;inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &amp;layerName, const unsigned int outputSlotIndex=0)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00435">Layer.cpp:435</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_layer_html_aeb2d638cc0e02c10075e015100996f2d"><div class="ttname"><a href="classarmnn_1_1_layer.html#aeb2d638cc0e02c10075e015100996f2d">armnn::Layer::ValidateAndCopyShape</a></div><div class="ttdeci">void ValidateAndCopyShape(const TensorShape &amp;outputShape, const TensorShape &amp;inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &amp;layerName, const unsigned int outputSlotIndex=0)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00457">Layer.cpp:457</a></div></div>
 <div class="ttc" id="aclassarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00339">Layer.hpp:339</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_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot &amp; GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00337">Layer.hpp:337</a></div></div>
 <div class="ttc" id="aclassarmnn_1_1_layer_with_parameters_html_afa3e8a8f23589b1eaddbe203825bbdcf"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#afa3e8a8f23589b1eaddbe203825bbdcf">armnn::LayerWithParameters&lt; BatchToSpaceNdDescriptor &gt;::GetParameters</a></div><div class="ttdeci">const BatchToSpaceNdDescriptor &amp; GetParameters() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00019">LayerWithParameters.hpp:19</a></div></div>
 <div class="ttc" id="aclassarmnn_1_1_layer_html_a7ddf0cf6f620d59c10e63495ace795d0"><div class="ttname"><a href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">armnn::Layer::GetName</a></div><div class="ttdeci">const char * GetName() const override</div><div class="ttdoc">Returns the name of the layer.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00332">Layer.hpp:332</a></div></div>
-<div class="ttc" id="aclassarmnn_1_1_input_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::InputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const override</div><div class="ttdoc">Gets the TensorInfo for this InputSlot.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00592">Layer.cpp:592</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_input_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::InputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const override</div><div class="ttdoc">Gets the TensorInfo for this InputSlot.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00614">Layer.cpp:614</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>
 <div class="ttc" id="aclassarmnn_1_1_layer_with_parameters_html_ad32ac22bc72e28dfd6b466d143c8e262"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">armnn::LayerWithParameters&lt; BatchToSpaceNdDescriptor &gt;::m_Param</a></div><div class="ttdeci">BatchToSpaceNdDescriptor m_Param</div><div class="ttdoc">The parameters for the layer (not including tensor-valued weights etc.).</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00052">LayerWithParameters.hpp:52</a></div></div>
 <div class="ttc" id="aclassarmnn_1_1_layer_with_parameters_html_a30a858b2b26d651a066537e499fbf40d"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#a30a858b2b26d651a066537e499fbf40d">armnn::LayerWithParameters&lt; BatchToSpaceNdDescriptor &gt;::PrepInfoAndDesc</a></div><div class="ttdeci">WorkloadInfo PrepInfoAndDesc(QueueDescriptor &amp;descriptor) const</div><div class="ttdoc">Helper function to reduce duplication in *Layer::CreateWorkload.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00044">LayerWithParameters.hpp:44</a></div></div>
-<div class="ttc" id="aclassarmnn_1_1_layer_html_a448afc716fda85394df1e8e5b7d530e8"><div class="ttname"><a href="classarmnn_1_1_layer.html#a448afc716fda85394df1e8e5b7d530e8">armnn::Layer::VerifyShapeInferenceType</a></div><div class="ttdeci">void VerifyShapeInferenceType(const TensorShape &amp;outputShape, ShapeInferenceMethod shapeInferenceMethod)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00504">Layer.cpp:504</a></div></div>
-<div class="ttc" id="aclassarmnn_1_1_layer_html_af7f0460d32511de0da525f1817d13e8c"><div class="ttname"><a href="classarmnn_1_1_layer.html#af7f0460d32511de0da525f1817d13e8c">armnn::Layer::SetAdditionalInfo</a></div><div class="ttdeci">void SetAdditionalInfo(QueueDescriptor &amp;descriptor) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00287">Layer.cpp:287</a></div></div>
-<div class="ttc" id="aclassarmnn_1_1_batch_to_space_nd_layer_html_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_batch_to_space_nd_layer.html#a65ca562c882ad619684445a1402f415a">armnn::BatchToSpaceNdLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector&lt; TensorShape &gt; InferOutputShapes(const std::vector&lt; TensorShape &gt; &amp;inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs,...</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_layer_8cpp_source.html#l00053">BatchToSpaceNdLayer.cpp:53</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_layer_validation_exception_html"><div class="ttname"><a href="classarmnn_1_1_layer_validation_exception.html">armnn::LayerValidationException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00105">Exceptions.hpp:105</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_layer_html_a448afc716fda85394df1e8e5b7d530e8"><div class="ttname"><a href="classarmnn_1_1_layer.html#a448afc716fda85394df1e8e5b7d530e8">armnn::Layer::VerifyShapeInferenceType</a></div><div class="ttdeci">void VerifyShapeInferenceType(const TensorShape &amp;outputShape, ShapeInferenceMethod shapeInferenceMethod)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00526">Layer.cpp:526</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_layer_html_af7f0460d32511de0da525f1817d13e8c"><div class="ttname"><a href="classarmnn_1_1_layer.html#af7f0460d32511de0da525f1817d13e8c">armnn::Layer::SetAdditionalInfo</a></div><div class="ttdeci">void SetAdditionalInfo(QueueDescriptor &amp;descriptor) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00303">Layer.cpp:303</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_batch_to_space_nd_layer_html_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_batch_to_space_nd_layer.html#a65ca562c882ad619684445a1402f415a">armnn::BatchToSpaceNdLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector&lt; TensorShape &gt; InferOutputShapes(const std::vector&lt; TensorShape &gt; &amp;inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs,...</div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_layer_8cpp_source.html#l00058">BatchToSpaceNdLayer.cpp:58</a></div></div>
 <div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a6ee06c6045d0c5b6565a247955ef0fc2"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a6ee06c6045d0c5b6565a247955ef0fc2">armnn::LayerType::BatchToSpaceNd</a></div><div class="ttdeci">@ BatchToSpaceNd</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="aclassarmnn_1_1_layer_html_a0607e36e88f38c34c71c663164b76776"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0607e36e88f38c34c71c663164b76776">armnn::Layer::VerifyLayerConnections</a></div><div class="ttdeci">void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &amp;location) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00391">Layer.cpp:391</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_layer_html_a0607e36e88f38c34c71c663164b76776"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0607e36e88f38c34c71c663164b76776">armnn::Layer::VerifyLayerConnections</a></div><div class="ttdeci">void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &amp;location) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00410">Layer.cpp:410</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>
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 <div class="ttc" id="aclassarmnn_1_1_layer_html_afe508761cc8318b15329ba4acf7fbfec"><div class="ttname"><a href="classarmnn_1_1_layer.html#afe508761cc8318b15329ba4acf7fbfec">armnn::Layer::m_ShapeInferenceMethod</a></div><div class="ttdeci">ShapeInferenceMethod m_ShapeInferenceMethod</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00441">Layer.hpp:441</a></div></div>
@@ -687,7 +692,7 @@
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