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<div class="title">GpuFsaConvolution2d.cpp</div> </div>
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<a href="_gpu_fsa_convolution2d_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2024 Arm Ltd and Contributors. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160; </div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_gpu_fsa_convolution2d_8hpp.html">GpuFsaConvolution2d.hpp</a>&quot;</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_utils_gpu_fsa_8hpp.html">UtilsGpuFsa.hpp</a>&quot;</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160; </div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_arm_compute_tensor_utils_8hpp.html">aclCommon/ArmComputeTensorUtils.hpp</a>&gt;</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160; </div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="preprocessor">#include &lt;arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadContext.h&gt;</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="preprocessor">#include &lt;arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h&gt;</span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="preprocessor">#include &lt;arm_compute/dynamic_fusion/sketch/gpu/operators/GpuConv2d.h&gt;</span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="preprocessor">#include &lt;arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h&gt;</span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160; </div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="preprocessor">#include &lt;vector&gt;</span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160; </div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="keyword">using namespace </span>arm_compute::experimental::dynamic_fusion;</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="keyword">using namespace </span>armnn::armcomputetensorutils;</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; </div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;{</div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; </div>
<div class="line"><a name="l00024"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a1c42ef784299460fb9db004dd395d5e1"> 24</a></span>&#160;<a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> <a class="code" href="namespacearmnn.html#a1c42ef784299460fb9db004dd395d5e1">GpuFsaConvolution2dValidate</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; input,</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.html">Convolution2dDescriptor</a>&amp; descriptor,</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; weights,</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.html">Optional&lt;TensorInfo&gt;</a>&amp; biases)</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;{</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <span class="comment">// Create a new workload sketch, for validation purposes</span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <span class="keyword">auto</span> compileCtx = arm_compute::CLKernelLibrary::get().get_compile_context();</div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keyword">auto</span> workloadContext = GpuWorkloadContext(&amp;compileCtx);</div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; GpuWorkloadSketch sketch{ &amp;workloadContext };</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; </div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; <span class="comment">// Build and create tensor infos using the sketch</span></div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; aclWeightsInfo.set_are_values_constant(weights.<a class="code" href="classarmnn_1_1_tensor_info.html#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>());</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; </div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="keyword">auto</span> inputInfo = workloadContext.create_tensor_info(aclInputInfo);</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="keyword">auto</span> weightInfo = workloadContext.create_tensor_info(aclWeightsInfo);</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; </div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="comment">// Only create the bias tensor info if enabled, otherwise pass nullptr to validate_op</span></div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; arm_compute::TensorInfo aclBiasInfo;</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; arm_compute::ITensorInfo* biasSketchInfoPtr = <span class="keyword">nullptr</span>;</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; </div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; {</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keywordflow">if</span>(!biases.<a class="code" href="classarmnn_1_1_optional_base.html#a86b749ce2c4bc627fa8a1fcfaf0e314f">has_value</a>())</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_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;GpuFsaConvolution2d::ValidateOp: No biases set when biases are enabled&quot;</span>);</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; }</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; aclBiasInfo = BuildArmComputeTensorInfo(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">value</a>(), descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; aclBiasInfo.set_are_values_constant(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">value</a>().IsConstant());</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; biasSketchInfoPtr = workloadContext.create_tensor_info(aclBiasInfo);</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; }</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; Conv2dAttributes conv2dAttributes = <a class="code" href="_utils_gpu_fsa_8cpp.html#a6fb30c0d325066e78619d5e5a5611973">CreateConv2dAttributes</a>(descriptor);</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; </div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <span class="comment">// Validate operator, check status and update reasonIfUnsupported</span></div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> aclStatus = GpuConv2d::validate_op(sketch,</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; inputInfo,</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; weightInfo,</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; biasSketchInfoPtr,</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; conv2dAttributes);</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; </div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="keywordflow">return</span> aclStatus;</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; </div>
<div class="line"><a name="l00070"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ab8a797269fd9db3b8832998f10ad9688"> 70</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#ab8a797269fd9db3b8832998f10ad9688">GpuFsaConvolution2dCreateOp</a>(<a class="code" href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html">GpuFsaPreCompiledBlob</a>* blob,</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; input,</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.html">Convolution2dDescriptor</a>&amp; descriptor,</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; weights,</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.html">Optional&lt;TensorInfo&gt;</a>&amp; biases)</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160;{</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160;<span class="comment"> * Creating an Op for the GpuFsa backend requires us to create and maintain quite a bit of data, which is then stored</span></div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;<span class="comment"> * in a GpuFsaPreCompiledBlob for execution later. Specifically we need:</span></div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160;<span class="comment"> * GpuWorkloadContext, this contains the TensorInfos and is unique to the Graph being executed</span></div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;<span class="comment"> * Sketch, this is similar to a subgraph and can contain one or more operations. Multiple ops can be &quot;fused&quot; together</span></div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160;<span class="comment"> * using a single sketch.</span></div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;<span class="comment"> * The inputTensorinfos / outputTensorInfos, these are pointers to the TensorInfos used when creating the sketch.</span></div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160;<span class="comment"> * They refer to the TensorInfos stored within the GpuWorkloadContext and are needed when executing the sketch</span></div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160;<span class="comment"> * as the TensorInfos used when creating the Tensors must match those used to create the Sketch. Otherwise the runtime</span></div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160;<span class="comment"> * doesn&#39;t know which Tensors to use.</span></div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; GpuWorkloadSketch* sketch = blob-&gt;<a class="code" href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html#a14f92a9f65e32c3da896e7b1d45abd02">sketch</a>.get();</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; GpuWorkloadContext* workloadContext = blob-&gt;<a class="code" href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html#a255c9012137b149ffb46d83c23f2df43">workloadContext</a>.get();</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; std::vector&lt;arm_compute::ITensorInfo*&gt; inputTensorInfos = {};</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; std::vector&lt;arm_compute::ITensorInfo*&gt; outputTensorInfos = {};</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; </div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; <span class="comment">// Build and create tensor infos using the sketch</span></div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; aclWeightsInfo.set_are_values_constant(weights.<a class="code" href="classarmnn_1_1_tensor_info.html#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>());</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; </div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; inputTensorInfos.emplace_back(workloadContext-&gt;create_tensor_info(aclInputInfo));</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; inputTensorInfos.emplace_back(workloadContext-&gt;create_tensor_info(aclWeightsInfo));</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; </div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="comment">// Only create the bias tensor info if enabled, otherwise pass nullptr to validate_op / create_op</span></div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; arm_compute::TensorInfo aclBiasInfo;</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; arm_compute::ITensorInfo* biasSketchInfoPtr = <span class="keyword">nullptr</span>;</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; </div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; {</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <span class="keywordflow">if</span>(!biases.<a class="code" href="classarmnn_1_1_optional_base.html#a86b749ce2c4bc627fa8a1fcfaf0e314f">has_value</a>())</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; {</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;GpuFsaConvolution2d::CreateOp: No biases set when biases are enabled&quot;</span>);</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; }</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; aclBiasInfo = BuildArmComputeTensorInfo(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">value</a>(), descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; aclBiasInfo.set_are_values_constant(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">value</a>().IsConstant());</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; </div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; inputTensorInfos.emplace_back(workloadContext-&gt;create_tensor_info(aclBiasInfo));</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; biasSketchInfoPtr = inputTensorInfos[2];</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; }</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; </div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; Conv2dAttributes conv2dAttributes = <a class="code" href="_utils_gpu_fsa_8cpp.html#a6fb30c0d325066e78619d5e5a5611973">CreateConv2dAttributes</a>(descriptor);</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; </div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="comment">// Validate operator, check status and update reasonIfUnsupported</span></div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> aclStatus = GpuConv2d::validate_op(*sketch,</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; inputTensorInfos[0],</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; inputTensorInfos[1],</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; biasSketchInfoPtr,</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; conv2dAttributes);</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; </div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="keyword">const</span> <span class="keywordtype">bool</span> supported = (aclStatus.error_code() == arm_compute::ErrorCode::OK);</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="keywordflow">if</span> (!supported)</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; {</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_backend_capability_exception.html">BackendCapabilityException</a>(<span class="stringliteral">&quot;\&quot;GpuFsa\&quot; backend failed during Convolution2D operation validation&quot;</span>);</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; }</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; </div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <span class="comment">// Create the Op within the Sketch using the TensorInfos we have stored</span></div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; arm_compute::ITensorInfo* convOutInfo = GpuConv2d::create_op(*sketch,</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; inputTensorInfos[0],</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; inputTensorInfos[1],</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; biasSketchInfoPtr,</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; conv2dAttributes);</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; </div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <span class="comment">// Create the Output</span></div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; outputTensorInfos.emplace_back(workloadContext-&gt;create_tensor_info());</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; GpuOutput::create_op(*sketch, convOutInfo, outputTensorInfos[0]);</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; </div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <span class="comment">// Store the TensorInfos within the blob as unique_ptrs to be used later</span></div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; blob-&gt;<a class="code" href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html#a479b90f0b24c427502d94b716117e034">inputTensorInfos</a> = std::make_unique&lt;std::vector&lt;arm_compute::ITensorInfo*&gt;&gt;(inputTensorInfos);</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; blob-&gt;<a class="code" href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html#ac49bf679a23aa84f06a6bde3440a4c40">outputTensorInfos</a> = std::make_unique&lt;std::vector&lt;arm_compute::ITensorInfo*&gt;&gt;(outputTensorInfos);</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160;}</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; </div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160;} <span class="comment">// namespace armnn</span></div>
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<div class="ttc" id="aclassarmnn_1_1_optional_html"><div class="ttname"><a href="classarmnn_1_1_optional.html">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.html#l00270">Optional.hpp:270</a></div></div>
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<div class="ttc" id="astructarmnn_1_1_gpu_fsa_pre_compiled_blob_html_a479b90f0b24c427502d94b716117e034"><div class="ttname"><a href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html#a479b90f0b24c427502d94b716117e034">armnn::GpuFsaPreCompiledBlob::inputTensorInfos</a></div><div class="ttdeci">std::unique_ptr&lt; std::vector&lt; arm_compute::ITensorInfo * &gt; &gt; inputTensorInfos</div><div class="ttdef"><b>Definition:</b> <a href="_gpu_fsa_backend_8hpp_source.html#l00037">GpuFsaBackend.hpp:37</a></div></div>
<div class="ttc" id="a_utils_gpu_fsa_8cpp_html_a6fb30c0d325066e78619d5e5a5611973"><div class="ttname"><a href="_utils_gpu_fsa_8cpp.html#a6fb30c0d325066e78619d5e5a5611973">CreateConv2dAttributes</a></div><div class="ttdeci">Conv2dAttributes CreateConv2dAttributes(const Convolution2dDescriptor &amp;descriptor)</div><div class="ttdoc">Utility function used to setup an arm_compute::Conv2dAttributes object from given descriptor.</div><div class="ttdef"><b>Definition:</b> <a href="_utils_gpu_fsa_8cpp_source.html#l00014">UtilsGpuFsa.cpp:14</a></div></div>
<div class="ttc" id="astructarmnn_1_1_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00582">Descriptors.hpp:582</a></div></div>
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<div class="ttc" id="a_gpu_fsa_convolution2d_8hpp_html"><div class="ttname"><a href="_gpu_fsa_convolution2d_8hpp.html">GpuFsaConvolution2d.hpp</a></div></div>
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<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"><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_a1c42ef784299460fb9db004dd395d5e1"><div class="ttname"><a href="namespacearmnn.html#a1c42ef784299460fb9db004dd395d5e1">armnn::GpuFsaConvolution2dValidate</a></div><div class="ttdeci">arm_compute::Status GpuFsaConvolution2dValidate(const TensorInfo &amp;input, const Convolution2dDescriptor &amp;descriptor, const TensorInfo &amp;weights, const Optional&lt; TensorInfo &gt; &amp;biases)</div><div class="ttdef"><b>Definition:</b> <a href="_gpu_fsa_convolution2d_8cpp_source.html#l00024">GpuFsaConvolution2d.cpp:24</a></div></div>
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<div class="ttc" id="aclassarmnn_1_1_backend_capability_exception_html"><div class="ttname"><a href="classarmnn_1_1_backend_capability_exception.html">armnn::BackendCapabilityException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00152">Exceptions.hpp:152</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="a_arm_compute_tensor_utils_8hpp_html"><div class="ttname"><a href="_arm_compute_tensor_utils_8hpp.html">ArmComputeTensorUtils.hpp</a></div></div>
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<div class="ttc" id="astructarmnn_1_1_gpu_fsa_pre_compiled_blob_html"><div class="ttname"><a href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html">armnn::GpuFsaPreCompiledBlob</a></div><div class="ttdoc">A structure which contains all the elements needed to execute a fused workload in the GpuFsa Backend.</div><div class="ttdef"><b>Definition:</b> <a href="_gpu_fsa_backend_8hpp_source.html#l00032">GpuFsaBackend.hpp:32</a></div></div>
<div class="ttc" id="a_utils_gpu_fsa_8hpp_html"><div class="ttname"><a href="_utils_gpu_fsa_8hpp.html">UtilsGpuFsa.hpp</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ab8a797269fd9db3b8832998f10ad9688"><div class="ttname"><a href="namespacearmnn.html#ab8a797269fd9db3b8832998f10ad9688">armnn::GpuFsaConvolution2dCreateOp</a></div><div class="ttdeci">void GpuFsaConvolution2dCreateOp(GpuFsaPreCompiledBlob *blob, const TensorInfo &amp;input, const Convolution2dDescriptor &amp;descriptor, const TensorInfo &amp;weights, const Optional&lt; TensorInfo &gt; &amp;biases)</div><div class="ttdef"><b>Definition:</b> <a href="_gpu_fsa_convolution2d_8cpp_source.html#l00070">GpuFsaConvolution2d.cpp:70</a></div></div>
<div class="ttc" id="astructarmnn_1_1_gpu_fsa_pre_compiled_blob_html_ac49bf679a23aa84f06a6bde3440a4c40"><div class="ttname"><a href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html#ac49bf679a23aa84f06a6bde3440a4c40">armnn::GpuFsaPreCompiledBlob::outputTensorInfos</a></div><div class="ttdeci">std::unique_ptr&lt; std::vector&lt; arm_compute::ITensorInfo * &gt; &gt; outputTensorInfos</div><div class="ttdef"><b>Definition:</b> <a href="_gpu_fsa_backend_8hpp_source.html#l00038">GpuFsaBackend.hpp:38</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_optional_reference_switch_html_a77c7d528ac063d870b8c8426ec81c1c3"><div class="ttname"><a href="classarmnn_1_1_optional_reference_switch.html#a77c7d528ac063d870b8c8426ec81c1c3">armnn::OptionalReferenceSwitch&lt; std::is_reference&lt; T &gt;::value, T &gt;::value</a></div><div class="ttdeci">const T &amp; value() const</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.html#l00146">Optional.hpp:146</a></div></div>
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