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author | Nikhil Raj <nikhil.raj@arm.com> | 2024-05-16 09:47:51 +0100 |
---|---|---|
committer | Nikhil Raj <nikhil.raj@arm.com> | 2024-05-16 09:47:51 +0100 |
commit | 1dc83febfb76d6a770bdf3ba16c4034a970c2320 (patch) | |
tree | 66d27e5587e9010f3db26a23a348df844c88f8e6 /latest/_convolution2d_layer_8cpp_source.html | |
parent | 38b600d8abb2c5f7a44511b5deddf441f975d51d (diff) | |
download | armnn-gh-pages.tar.gz |
IVGCVSW-8260 Update Doxgen Docu for 24.05gh-pages
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: If4bc983bf2793a27ded8e26ac2b29523fc1e4711
Diffstat (limited to 'latest/_convolution2d_layer_8cpp_source.html')
-rw-r--r-- | latest/_convolution2d_layer_8cpp_source.html | 184 |
1 files changed, 103 insertions, 81 deletions
diff --git a/latest/_convolution2d_layer_8cpp_source.html b/latest/_convolution2d_layer_8cpp_source.html index 63b0a10916..db5f7f4d6b 100644 --- a/latest/_convolution2d_layer_8cpp_source.html +++ b/latest/_convolution2d_layer_8cpp_source.html @@ -36,7 +36,7 @@ <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 15rem; margin-top: .5rem; margin-left 13px"/> <td id="projectalign" style="padding-left: 0.9em;"> <div id="projectname"> -  <span id="projectnumber">24.02</span> +  <span id="projectnumber">24.05</span> </div> </td> </tr> @@ -97,7 +97,7 @@ $(document).ready(function(){initNavTree('_convolution2d_layer_8cpp_source.html' </div><!--header--> <div class="contents"> <a href="_convolution2d_layer_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div> -<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.</span></div> +<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017-2024 Arm Ltd and Contributors. All rights reserved.</span></div> <div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div> <div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div> <div class="line"><a name="l00005"></a><span class="lineno"> 5</span>  </div> @@ -161,92 +161,112 @@ $(document).ready(function(){initNavTree('_convolution2d_layer_8cpp_source.html' <div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  </div> <div class="line"><a name="l00064"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a65ca562c882ad619684445a1402f415a"> 64</a></span> std::vector<TensorShape> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a65ca562c882ad619684445a1402f415a">Convolution2dLayer::InferOutputShapes</a>(<span class="keyword">const</span> std::vector<TensorShape>& inputShapes)<span class="keyword"> const</span></div> <div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="keyword"></span>{</div> -<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(inputShapes.size() == 2);</div> -<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& inputShape = inputShapes[0];</div> -<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> filterShape = inputShapes[1];</div> -<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  </div> -<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="comment">// If we support multiple batch dimensions in the future, then this assert will need to change.</span></div> -<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <a class="code" href="_assert_8hpp.html#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(inputShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() == 4, <span class="stringliteral">"Convolutions will always have 4D input."</span>);</div> -<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  </div> -<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <a class="code" href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>( <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> > 0);</div> -<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <a class="code" href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>( <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> > 0);</div> -<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  </div> -<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">DataLayoutIndexed</a> dataLayoutIndex(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div> -<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  </div> -<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inWidth = inputShape[dataLayoutIndex.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()];</div> -<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inHeight = inputShape[dataLayoutIndex.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()];</div> -<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inBatchSize = inputShape[0];</div> -<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  </div> -<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterWidth = filterShape[dataLayoutIndex.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()];</div> -<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dilatedFilterWidth = filterWidth + (<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> - 1) * (filterWidth - 1);</div> -<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> readWidth = (inWidth + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>) - dilatedFilterWidth;</div> -<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outWidth = 1 + (readWidth / <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>);</div> -<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  </div> -<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterHeight = filterShape[dataLayoutIndex.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()];</div> -<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dilatedFilterHeight = filterHeight + (<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> - 1) * (filterHeight - 1);</div> -<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> readHeight = (inHeight + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>) - dilatedFilterHeight;</div> -<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outHeight = 1 + (readHeight / <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>);</div> -<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  </div> -<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outChannels = filterShape[0];</div> -<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outBatchSize = inBatchSize;</div> -<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  </div> -<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> tensorShape = <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a> ?</div> -<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>( { outBatchSize, outHeight, outWidth, outChannels } ) :</div> -<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>( { outBatchSize, outChannels, outHeight, outWidth });</div> -<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  </div> -<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">return</span> std::vector<TensorShape>({ tensorShape });</div> -<div class="line"><a name="l00100"></a><span class="lineno"> 100</span> }</div> +<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordflow">if</span> (inputShapes.size() != 2)</div> +<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  {</div> +<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"inputShapes' size is \""</span> + std::to_string(inputShapes.size()) +</div> +<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="stringliteral">"\" - should be \"2\"."</span>);</div> +<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  }</div> +<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  </div> +<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& inputShape = inputShapes[0];</div> +<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> filterShape = inputShapes[1];</div> +<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  </div> +<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="comment">// If we support multiple batch dimensions in the future, then this assert will need to change.</span></div> +<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keywordflow">if</span> (inputShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() != 4)</div> +<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  {</div> +<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"Convolutions will always have 4D input."</span>);</div> +<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  }</div> +<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  </div> +<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> == 0)</div> +<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  {</div> +<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"m_StrideX cannot be 0."</span>);</div> +<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  }</div> +<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  </div> +<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> == 0)</div> +<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  {</div> +<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"m_StrideY cannot be 0."</span>);</div> +<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  }</div> +<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  </div> +<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">DataLayoutIndexed</a> dataLayoutIndex(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div> +<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  </div> +<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inWidth = inputShape[dataLayoutIndex.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()];</div> +<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inHeight = inputShape[dataLayoutIndex.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()];</div> +<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inBatchSize = inputShape[0];</div> +<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  </div> +<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterWidth = filterShape[dataLayoutIndex.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()];</div> +<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dilatedFilterWidth = filterWidth + (<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> - 1) * (filterWidth - 1);</div> +<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> readWidth = (inWidth + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>) - dilatedFilterWidth;</div> +<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outWidth = 1 + (readWidth / <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>);</div> <div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  </div> -<div class="line"><a name="l00102"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a8c8f543d7e9729362c266d12ec169966"> 102</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a8c8f543d7e9729362c266d12ec169966">Convolution2dLayer::ValidateTensorShapesFromInputs</a>()</div> -<div class="line"><a name="l00103"></a><span class="lineno"> 103</span> {</div> -<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="classarmnn_1_1_layer.html#a0607e36e88f38c34c71c663164b76776">VerifyLayerConnections</a>(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">GetNumInputs</a>(), <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div> -<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  </div> -<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& outputShape = <a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div> -<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  </div> -<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <a class="code" href="classarmnn_1_1_layer.html#a448afc716fda85394df1e8e5b7d530e8">VerifyShapeInferenceType</a>(outputShape, <a class="code" href="classarmnn_1_1_layer.html#afe508761cc8318b15329ba4acf7fbfec">m_ShapeInferenceMethod</a>);</div> +<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterHeight = filterShape[dataLayoutIndex.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()];</div> +<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dilatedFilterHeight = filterHeight + (<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> - 1) * (filterHeight - 1);</div> +<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> readHeight = (inHeight + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>) - dilatedFilterHeight;</div> +<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outHeight = 1 + (readHeight / <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>);</div> +<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  </div> +<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outChannels = filterShape[0];</div> +<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outBatchSize = inBatchSize;</div> <div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  </div> -<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <a class="code" href="_assert_8hpp.html#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).GetConnection(),</div> -<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="stringliteral">"Convolution2dLayer: Weights should be connected to input slot 1."</span>);</div> -<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  </div> -<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  std::vector<TensorShape> inferredShapes = <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>({</div> -<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div> -<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>() });</div> +<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> tensorShape = <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a> ?</div> +<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>( { outBatchSize, outHeight, outWidth, outChannels } ) :</div> +<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>( { outBatchSize, outChannels, outHeight, outWidth });</div> +<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  </div> +<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordflow">return</span> std::vector<TensorShape>({ tensorShape });</div> +<div class="line"><a name="l00115"></a><span class="lineno"> 115</span> }</div> <div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  </div> -<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(inferredShapes.size() == 1);</div> -<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  </div> -<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <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">"Convolution2dLayer"</span>);</div> -<div class="line"><a name="l00120"></a><span class="lineno"> 120</span> }</div> -<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  </div> -<div class="line"><a name="l00122"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a29cc31172f6ab16ac931f90c667c092d"> 122</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.html#aba5c20cadbebd2e7ba67e20a47e31472">Layer::ImmutableConstantTensors</a> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a29cc31172f6ab16ac931f90c667c092d">Convolution2dLayer::GetConstantTensorsByRef</a>()<span class="keyword"> const</span></div> -<div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="keyword"></span>{</div> -<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html#aba5c20cadbebd2e7ba67e20a47e31472">Layer::ImmutableConstantTensors</a> tensors = <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad588423ab0d55c8ec4860a7f0a21f5a0">GetConnectedConstantAsInputTensors</a>();</div> -<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keywordflow">return</span> tensors;</div> -<div class="line"><a name="l00126"></a><span class="lineno"> 126</span> }</div> -<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  </div> -<div class="line"><a name="l00128"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a46fc3fdd4b2a5dd6d184e57983cf20bc"> 128</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a46fc3fdd4b2a5dd6d184e57983cf20bc">Convolution2dLayer::ExecuteStrategy</a>(<a class="code" href="classarmnn_1_1_i_strategy.html">IStrategy</a>& strategy)<span class="keyword"> const</span></div> -<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="keyword"></span>{</div> -<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  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="l00131"></a><span class="lineno"> 131</span> }</div> -<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  </div> -<div class="line"><a name="l00133"></a><span class="lineno"> 133</span> } <span class="comment">// namespace armnn</span></div> +<div class="line"><a name="l00117"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a8c8f543d7e9729362c266d12ec169966"> 117</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a8c8f543d7e9729362c266d12ec169966">Convolution2dLayer::ValidateTensorShapesFromInputs</a>()</div> +<div class="line"><a name="l00118"></a><span class="lineno"> 118</span> {</div> +<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <a class="code" href="classarmnn_1_1_layer.html#a0607e36e88f38c34c71c663164b76776">VerifyLayerConnections</a>(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">GetNumInputs</a>(), <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div> +<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  </div> +<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& outputShape = <a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div> +<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  </div> +<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <a class="code" href="classarmnn_1_1_layer.html#a448afc716fda85394df1e8e5b7d530e8">VerifyShapeInferenceType</a>(outputShape, <a class="code" href="classarmnn_1_1_layer.html#afe508761cc8318b15329ba4acf7fbfec">m_ShapeInferenceMethod</a>);</div> +<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  </div> +<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).GetConnection())</div> +<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  {</div> +<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a>(<span class="stringliteral">"Convolution2dLayer: Weights should be connected to input slot 1."</span>);</div> +<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  }</div> +<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  </div> +<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  std::vector<TensorShape> inferredShapes = <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>({</div> +<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div> +<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>() });</div> +<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  </div> +<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keywordflow">if</span> (inferredShapes.size() != 1)</div> +<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  {</div> +<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">armnn::Exception</a>(<span class="stringliteral">"inferredShapes has "</span></div> +<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  + std::to_string(inferredShapes.size()) +</div> +<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="stringliteral">" elements - should only have 1."</span>);</div> +<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  }</div> +<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  </div> +<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <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">"Convolution2dLayer"</span>);</div> +<div class="line"><a name="l00142"></a><span class="lineno"> 142</span> }</div> +<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  </div> +<div class="line"><a name="l00144"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a29cc31172f6ab16ac931f90c667c092d"> 144</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.html#aba5c20cadbebd2e7ba67e20a47e31472">Layer::ImmutableConstantTensors</a> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a29cc31172f6ab16ac931f90c667c092d">Convolution2dLayer::GetConstantTensorsByRef</a>()<span class="keyword"> const</span></div> +<div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="keyword"></span>{</div> +<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html#aba5c20cadbebd2e7ba67e20a47e31472">Layer::ImmutableConstantTensors</a> tensors = <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad588423ab0d55c8ec4860a7f0a21f5a0">GetConnectedConstantAsInputTensors</a>();</div> +<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keywordflow">return</span> tensors;</div> +<div class="line"><a name="l00148"></a><span class="lineno"> 148</span> }</div> +<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  </div> +<div class="line"><a name="l00150"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a46fc3fdd4b2a5dd6d184e57983cf20bc"> 150</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a46fc3fdd4b2a5dd6d184e57983cf20bc">Convolution2dLayer::ExecuteStrategy</a>(<a class="code" href="classarmnn_1_1_i_strategy.html">IStrategy</a>& strategy)<span class="keyword"> const</span></div> +<div class="line"><a name="l00151"></a><span class="lineno"> 151</span> <span class="keyword"></span>{</div> +<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  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="l00153"></a><span class="lineno"> 153</span> }</div> +<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  </div> +<div class="line"><a name="l00155"></a><span class="lineno"> 155</span> } <span class="comment">// namespace armnn</span></div> </div><!-- fragment --></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="astructarmnn_1_1_convolution2d_descriptor_html_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">armnn::Convolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00570">Descriptors.hpp:570</a></div></div> <div class="ttc" id="anamespacearmnn_html_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div><div class="ttdeci">@ Undefined</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 & 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 & 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="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div><div class="ttdeci">@ NHWC</div></div> <div class="ttc" id="aclassarmnn_1_1_layer_with_parameters_html_a2ca654770a1890f15e3c7aab98e434a5"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#a2ca654770a1890f15e3c7aab98e434a5">armnn::LayerWithParameters::SerializeLayerParameters</a></div><div class="ttdeci">void SerializeLayerParameters(ParameterStringifyFunction &fn) const override</div><div class="ttdoc">Helper to serialize the layer parameters to string (currently used in DotSerializer and company).</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00023">LayerWithParameters.hpp:23</a></div></div> <div class="ttc" id="aclassarmnn_1_1_convolution2d_layer_html_a2ca654770a1890f15e3c7aab98e434a5"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a2ca654770a1890f15e3c7aab98e434a5">armnn::Convolution2dLayer::SerializeLayerParameters</a></div><div class="ttdeci">void SerializeLayerParameters(ParameterStringifyFunction &fn) const override</div><div class="ttdoc">Helper to serialize the layer parameters to string.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00029">Convolution2dLayer.cpp:29</a></div></div> <div class="ttc" id="a_types_utils_8hpp_html"><div class="ttname"><a href="_types_utils_8hpp.html">TypesUtils.hpp</a></div></div> -<div class="ttc" id="aclassarmnn_1_1_convolution2d_layer_html_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a8c8f543d7e9729362c266d12ec169966">armnn::Convolution2dLayer::ValidateTensorShapesFromInputs</a></div><div class="ttdeci">void ValidateTensorShapesFromInputs() override</div><div class="ttdoc">Check if the input tensor shape(s) will lead to a valid configuration of Convolution2dLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00102">Convolution2dLayer.cpp:102</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_convolution2d_layer_html_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a8c8f543d7e9729362c266d12ec169966">armnn::Convolution2dLayer::ValidateTensorShapesFromInputs</a></div><div class="ttdeci">void ValidateTensorShapesFromInputs() override</div><div class="ttdoc">Check if the input tensor shape(s) will lead to a valid configuration of Convolution2dLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00117">Convolution2dLayer.cpp:117</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_utils_1_1_data_layout_indexed_html"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a></div><div class="ttdoc">Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout.</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00017">DataLayoutIndexed.hpp:17</a></div></div> -<div class="ttc" id="aclassarmnn_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 &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &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 &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &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 & 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_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00576">Descriptors.hpp:576</a></div></div> <div class="ttc" id="aclassarmnn_1_1_i_strategy_html"><div class="ttname"><a href="classarmnn_1_1_i_strategy.html">armnn::IStrategy</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_strategy_8hpp_source.html#l00016">IStrategy.hpp:16</a></div></div> -<div class="ttc" id="a_assert_8hpp_html_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.html#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.html#l00015">Assert.hpp:15</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Convolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00566">Descriptors.hpp:566</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">armnn::Convolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation along y axis.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00580">Descriptors.hpp:580</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 & 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> @@ -258,29 +278,30 @@ $(document).ready(function(){initNavTree('_convolution2d_layer_8cpp_source.html' <div class="ttc" id="aclassarmnn_1_1_convolution2d_layer_html"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html">armnn::Convolution2dLayer</a></div><div class="ttdoc">This layer represents a convolution 2d operation.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00015">Convolution2dLayer.hpp:15</a></div></div> <div class="ttc" id="a_convolution2d_layer_8hpp_html"><div class="ttname"><a href="_convolution2d_layer_8hpp.html">Convolution2dLayer.hpp</a></div></div> <div class="ttc" id="aclassarmnn_1_1_i_connectable_layer_html_aba5c20cadbebd2e7ba67e20a47e31472"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html#aba5c20cadbebd2e7ba67e20a47e31472">armnn::IConnectableLayer::ImmutableConstantTensors</a></div><div class="ttdeci">std::vector< std::reference_wrapper< const std::shared_ptr< ConstTensorHandle > >> ImmutableConstantTensors</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00141">INetwork.hpp:141</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 & 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 & 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_layer_with_parameters_html_ad588423ab0d55c8ec4860a7f0a21f5a0"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#ad588423ab0d55c8ec4860a7f0a21f5a0">armnn::LayerWithParameters< Convolution2dDescriptor >::GetConnectedConstantAsInputTensors</a></div><div class="ttdeci">Layer::ImmutableConstantTensors GetConnectedConstantAsInputTensors() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00059">LayerWithParameters.hpp:59</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< Convolution2dDescriptor >::m_Param</a></div><div class="ttdeci">Convolution2dDescriptor 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="astructarmnn_1_1_convolution2d_descriptor_html_a62938964ffd34d5af3f2d56ca1183b18"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">armnn::Convolution2dDescriptor::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs() const</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00469">Descriptors.cpp:469</a></div></div> +<div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_a62938964ffd34d5af3f2d56ca1183b18"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a62938964ffd34d5af3f2d56ca1183b18">armnn::Convolution2dDescriptor::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs() const</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00470">Descriptors.cpp:470</a></div></div> <div class="ttc" id="aclassarmnn_1_1_tensor_shape_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdoc">Function that returns the tensor rank.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00174">Tensor.cpp:174</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.html">armnn::Convolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00210">WorkloadData.hpp:210</a></div></div> <div class="ttc" id="a_profiling_8hpp_html_a5ccc65e2c464ac05ce311fdae7ede03a"><div class="ttname"><a href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.html#l00220">Profiling.hpp:220</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< Convolution2dDescriptor >::PrepInfoAndDesc</a></div><div class="ttdeci">WorkloadInfo PrepInfoAndDesc(QueueDescriptor &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_convolution2d_layer_html_a29cc31172f6ab16ac931f90c667c092d"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a29cc31172f6ab16ac931f90c667c092d">armnn::Convolution2dLayer::GetConstantTensorsByRef</a></div><div class="ttdeci">ImmutableConstantTensors GetConstantTensorsByRef() const override</div><div class="ttdoc">Retrieve the handles to the constant values connected to the layer.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00122">Convolution2dLayer.cpp:122</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_convolution2d_layer_html_a29cc31172f6ab16ac931f90c667c092d"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a29cc31172f6ab16ac931f90c667c092d">armnn::Convolution2dLayer::GetConstantTensorsByRef</a></div><div class="ttdeci">ImmutableConstantTensors GetConstantTensorsByRef() const override</div><div class="ttdoc">Retrieve the handles to the constant values connected to the layer.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00144">Convolution2dLayer.cpp:144</a></div></div> <div class="ttc" id="aclassarmnn_1_1_i_workload_factory_html"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.html#l00022">WorkloadFactory.hpp:22</a></div></div> <div class="ttc" id="anamespacearmnn_utils_html"><div class="ttname"><a href="namespacearmnn_utils.html">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_compatible_types_8hpp_source.html#l00010">CompatibleTypes.hpp:10</a></div></div> <div class="ttc" id="anamespacearmnn_html_a8c42c6647e31ebe525aeba878d133e45"><div class="ttname"><a href="namespacearmnn.html#a8c42c6647e31ebe525aeba878d133e45">armnn::ParameterStringifyFunction</a></div><div class="ttdeci">std::function< void(const std::string &name, const std::string &value)> ParameterStringifyFunction</div><div class="ttdef"><b>Definition:</b> <a href="_serialize_layer_parameters_8hpp_source.html#l00014">SerializeLayerParameters.hpp:14</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 &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 &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_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 &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 &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="astructarmnn_1_1_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::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#l00584">Descriptors.hpp:584</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">armnn::Convolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00572">Descriptors.hpp:572</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_exception_html"><div class="ttname"><a href="classarmnn_1_1_exception.html">armnn::Exception</a></div><div class="ttdoc">Base class for all ArmNN exceptions so that users can filter to just those.</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00046">Exceptions.hpp:46</a></div></div> <div class="ttc" id="aclassarmnn_utils_1_1_data_layout_indexed_html_a414e6f95548e6f7a01d5028b55ad3941"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">armnnUtils::DataLayoutIndexed::GetWidthIndex</a></div><div class="ttdeci">unsigned int GetWidthIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00025">DataLayoutIndexed.hpp:25</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00574">Descriptors.hpp:574</a></div></div> <div class="ttc" id="aclassarmnn_1_1_convolution2d_layer_html_ad026ad183e8c182f60d22a6cc39ae873"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#ad026ad183e8c182f60d22a6cc39ae873">armnn::Convolution2dLayer::Convolution2dLayer</a></div><div class="ttdeci">Convolution2dLayer(const Convolution2dDescriptor &param, const char *name)</div><div class="ttdoc">Constructor to create a Convolution2dLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00023">Convolution2dLayer.cpp:23</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">armnn::Convolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00568">Descriptors.hpp:568</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00534">Descriptors.hpp:534</a></div></div> -<div class="ttc" id="anamespacearmnn_html_aed508ea8d7b3ef4e171cb6f178acf086"><div class="ttname"><a href="namespacearmnn.html#aed508ea8d7b3ef4e171cb6f178acf086">armnn::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs(bool biasEnabled)</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00454">Descriptors.cpp:454</a></div></div> +<div class="ttc" id="anamespacearmnn_html_aed508ea8d7b3ef4e171cb6f178acf086"><div class="ttname"><a href="namespacearmnn.html#aed508ea8d7b3ef4e171cb6f178acf086">armnn::GetNumInputs</a></div><div class="ttdeci">uint32_t GetNumInputs(bool biasEnabled)</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00455">Descriptors.cpp:455</a></div></div> <div class="ttc" id="a_tensor_handle_8hpp_html"><div class="ttname"><a href="_tensor_handle_8hpp.html">TensorHandle.hpp</a></div></div> <div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00193">Tensor.hpp:193</a></div></div> <div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::Convolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation along x axis.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00578">Descriptors.hpp:578</a></div></div> @@ -288,21 +309,22 @@ $(document).ready(function(){initNavTree('_convolution2d_layer_8cpp_source.html' <div class="ttc" id="aclassarmnn_1_1_convolution2d_layer_html_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a65ca562c882ad619684445a1402f415a">armnn::Convolution2dLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &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="_convolution2d_layer_8cpp_source.html#l00064">Convolution2dLayer.cpp:64</a></div></div> <div class="ttc" id="anamespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors.</div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.html#l00006">01_00_quick_start.dox:6</a></div></div> <div class="ttc" id="aclassarmnn_1_1_convolution2d_layer_html_acf7bec8b795447d4b23e0339a6561044"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#acf7bec8b795447d4b23e0339a6561044">armnn::Convolution2dLayer::Clone</a></div><div class="ttdeci">Convolution2dLayer * Clone(Graph &graph) const override</div><div class="ttdoc">Creates a dynamically-allocated copy of this layer.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00058">Convolution2dLayer.cpp:58</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 &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 &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="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">armnn::LayerType::Convolution2d</a></div><div class="ttdeci">@ Convolution2d</div></div> +<div class="ttc" id="aclassarmnn_1_1_null_pointer_exception_html"><div class="ttname"><a href="classarmnn_1_1_null_pointer_exception.html">armnn::NullPointerException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00146">Exceptions.hpp:146</a></div></div> <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> <div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdoc">When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below.</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00491">Types.hpp:491</a></div></div> <div class="ttc" id="a_data_layout_indexed_8hpp_html"><div class="ttname"><a href="_data_layout_indexed_8hpp.html">DataLayoutIndexed.hpp</a></div></div> <div class="ttc" id="aclassarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00030">Graph.hpp:30</a></div></div> <div class="ttc" id="aclassarmnn_1_1_i_workload_factory_html_a694a8411c8c799da95306034d274930b"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a694a8411c8c799da95306034d274930b">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const =0</div><div class="ttdoc">Backends should implement their own CreateWorkload function with a switch statement.</div></div> <div class="ttc" id="aclassarmnn_1_1_i_strategy_html_ad4f8c9ff973cf6a603d26b56c5b34967"><div class="ttname"><a href="classarmnn_1_1_i_strategy.html#ad4f8c9ff973cf6a603d26b56c5b34967">armnn::IStrategy::ExecuteStrategy</a></div><div class="ttdeci">virtual void ExecuteStrategy(const IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0</div></div> -<div class="ttc" id="aclassarmnn_1_1_convolution2d_layer_html_a46fc3fdd4b2a5dd6d184e57983cf20bc"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a46fc3fdd4b2a5dd6d184e57983cf20bc">armnn::Convolution2dLayer::ExecuteStrategy</a></div><div class="ttdeci">void ExecuteStrategy(IStrategy &strategy) const override</div><div class="ttdoc">Apply a visitor to this layer.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00128">Convolution2dLayer.cpp:128</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_convolution2d_layer_html_a46fc3fdd4b2a5dd6d184e57983cf20bc"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a46fc3fdd4b2a5dd6d184e57983cf20bc">armnn::Convolution2dLayer::ExecuteStrategy</a></div><div class="ttdeci">void ExecuteStrategy(IStrategy &strategy) const override</div><div class="ttdoc">Apply a visitor to this layer.</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00150">Convolution2dLayer.cpp:150</a></div></div> <div class="ttc" id="a_layer_clone_base_8hpp_html"><div 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