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+<div class="title">GpuFsaBatchMatMul.cpp</div>  </div>
+</div><!--header-->
+<div class="contents">
+<a href="_gpu_fsa_batch_mat_mul_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_batch_mat_mul_8hpp.html">GpuFsaBatchMatMul.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/GpuMatMul.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="keyword">using namespace </span>arm_compute::experimental::dynamic_fusion;</div>
+<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="keyword">using namespace </span>armnn::armcomputetensorutils;</div>
+<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160; </div>
+<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></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; </div>
+<div class="line"><a name="l00022"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a47e56eb9bcbb170dddd202d770ed2cd8">   22</a></span>&#160;<a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> <a class="code" href="namespacearmnn.html#a47e56eb9bcbb170dddd202d770ed2cd8">GpuFsaBatchMatMulValidate</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; input0,</div>
+<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;                                              <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; input1,</div>
+<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;                                              <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html">BatchMatMulDescriptor</a>&amp; descriptor)</div>
+<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;{</div>
+<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;    <span class="comment">// Create a new workload sketch, for validation purposes</span></div>
+<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;    <span class="keyword">auto</span> compileCtx         = arm_compute::CLKernelLibrary::get().get_compile_context();</div>
+<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;    <span class="keyword">auto</span> workloadContext    = GpuWorkloadContext(&amp;compileCtx);</div>
+<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    GpuWorkloadSketch sketch{ &amp;workloadContext };</div>
+<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160; </div>
+<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;    arm_compute::TensorInfo aclInput0Info = BuildArmComputeTensorInfo(input0, input0.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div>
+<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    arm_compute::TensorInfo aclInput1Info = BuildArmComputeTensorInfo(input1, input1.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div>
+<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160; </div>
+<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    aclInput0Info.set_are_values_constant(input0.<a class="code" href="classarmnn_1_1_tensor_info.html#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>());</div>
+<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    aclInput1Info.set_are_values_constant(input1.<a class="code" href="classarmnn_1_1_tensor_info.html#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>());</div>
+<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160; </div>
+<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    arm_compute::ITensorInfo*  inputInfo0 = workloadContext.create_tensor_info(aclInput0Info);</div>
+<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    arm_compute::ITensorInfo*  inputInfo1 = workloadContext.create_tensor_info(aclInput1Info);</div>
+<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160; </div>
+<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    MatMulAttributes matMulAttributes{};</div>
+<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    matMulAttributes.adj_lhs(descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#acb441bb8db19bcce78d15cdd8ceb5ea0">m_TransposeX</a>);</div>
+<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    matMulAttributes.adj_rhs(descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#a112b466e5d2ab9d1887178adbe3afa1c">m_TransposeY</a>);</div>
+<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    GpuMatMulSettings matmulSettings{};</div>
+<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    matmulSettings.m0(1);</div>
+<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    matmulSettings.n0(1);</div>
+<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    matmulSettings.k0(1);</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">return</span> GpuMatMul::validate_op(sketch, inputInfo0, inputInfo1, matMulAttributes, matmulSettings);</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; </div>
+<div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a1334119d4ee3de23f273ee91aa256cbd">   51</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#a1334119d4ee3de23f273ee91aa256cbd">GpuFsaBatchMatMulCreateOp</a>(<a class="code" href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html">GpuFsaPreCompiledBlob</a>* blob,</div>
+<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;                               <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; input0,</div>
+<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;                               <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; input1,</div>
+<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;                               <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html">BatchMatMulDescriptor</a>&amp; descriptor)</div>
+<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;{</div>
+<div class="line"><a name="l00056"></a><span class="lineno">   56</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="l00057"></a><span class="lineno">   57</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="l00058"></a><span class="lineno">   58</span>&#160;    std::vector&lt;arm_compute::ITensorInfo*&gt; inputTensorInfos  = {};</div>
+<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    std::vector&lt;arm_compute::ITensorInfo*&gt; outputTensorInfos = {};</div>
+<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160; </div>
+<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    arm_compute::TensorInfo aclInput0Info = BuildArmComputeTensorInfo(input0, input0.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div>
+<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    arm_compute::TensorInfo aclInput1Info = BuildArmComputeTensorInfo(input1, input1.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div>
+<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160; </div>
+<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    aclInput0Info.set_are_values_constant(input0.<a class="code" href="classarmnn_1_1_tensor_info.html#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>());</div>
+<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    aclInput1Info.set_are_values_constant(input1.<a class="code" href="classarmnn_1_1_tensor_info.html#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>());</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;    inputTensorInfos.emplace_back(workloadContext-&gt;create_tensor_info(aclInput0Info));</div>
+<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    inputTensorInfos.emplace_back(workloadContext-&gt;create_tensor_info(aclInput1Info));</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">   70</span>&#160;    MatMulAttributes matMulAttributes{};</div>
+<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    matMulAttributes.adj_lhs(descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#acb441bb8db19bcce78d15cdd8ceb5ea0">m_TransposeX</a>);</div>
+<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    matMulAttributes.adj_rhs(descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#a112b466e5d2ab9d1887178adbe3afa1c">m_TransposeY</a>);</div>
+<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    GpuMatMulSettings matmulSettings{};</div>
+<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;    matmulSettings.m0(1);</div>
+<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    matmulSettings.n0(1);</div>
+<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    matmulSettings.k0(1);</div>
+<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160; </div>
+<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    <span class="comment">// Validate operator, check status and update reasonIfUnsupported</span></div>
+<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> aclStatus = GpuMatMul::validate_op(*sketch,</div>
+<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;                                                           inputTensorInfos[0],</div>
+<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;                                                           inputTensorInfos[1],</div>
+<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;                                                           matMulAttributes,</div>
+<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;                                                           matmulSettings);</div>
+<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160; </div>
+<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">bool</span> supported = aclStatus.error_code() == arm_compute::ErrorCode::OK;</div>
+<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    <span class="keywordflow">if</span> (!supported)</div>
+<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    {</div>
+<div class="line"><a name="l00088"></a><span class="lineno">   88</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 elementwise binary add validation&quot;</span>);</div>
+<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    }</div>
+<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160; </div>
+<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    arm_compute::ITensorInfo* addOutputInfo = GpuMatMul::create_op(*sketch,</div>
+<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;                                                                   inputTensorInfos[0],</div>
+<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;                                                                   inputTensorInfos[1],</div>
+<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;                                                                   matMulAttributes,</div>
+<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;                                                                   matmulSettings);</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;    <span class="comment">// Temporary fix until fusing attempt is make for GpuFsa backend and Output layer workload is created.</span></div>
+<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    outputTensorInfos.emplace_back(workloadContext-&gt;create_tensor_info());</div>
+<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    GpuOutput::create_op(*sketch, addOutputInfo, outputTensorInfos[0]);</div>
+<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160; </div>
+<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    <span class="comment">// Store the TensorInfos within the blob as unique_ptrs to be used later</span></div>
+<div class="line"><a name="l00102"></a><span class="lineno">  102</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="l00103"></a><span class="lineno">  103</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="l00104"></a><span class="lineno">  104</span>&#160;}</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="comment">// namespace armnn</span></div>
+</div><!-- fragment --></div><!-- contents -->
+</div><!-- doc-content -->
+<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_html_acb441bb8db19bcce78d15cdd8ceb5ea0"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html#acb441bb8db19bcce78d15cdd8ceb5ea0">armnn::BatchMatMulDescriptor::m_TransposeX</a></div><div class="ttdeci">bool m_TransposeX</div><div class="ttdoc">Transpose the slices of each input tensor Transpose and Adjoint can not both be set to true for the s...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01612">Descriptors.hpp:1612</a></div></div>
+<div class="ttc" id="anamespacearmnn_html_a1334119d4ee3de23f273ee91aa256cbd"><div class="ttname"><a href="namespacearmnn.html#a1334119d4ee3de23f273ee91aa256cbd">armnn::GpuFsaBatchMatMulCreateOp</a></div><div class="ttdeci">void GpuFsaBatchMatMulCreateOp(GpuFsaPreCompiledBlob *blob, const TensorInfo &amp;input0, const TensorInfo &amp;input1, const BatchMatMulDescriptor &amp;descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_gpu_fsa_batch_mat_mul_8cpp_source.html#l00051">GpuFsaBatchMatMul.cpp:51</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00152">Tensor.hpp:152</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00197">Tensor.hpp:197</a></div></div>
+<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a945263e85c27f3216a8323cfc16d8919"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a945263e85c27f3216a8323cfc16d8919">armnn::TensorInfo::IsConstant</a></div><div class="ttdeci">bool IsConstant() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00509">Tensor.cpp:509</a></div></div>
+<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="astructarmnn_1_1_batch_mat_mul_descriptor_html_a112b466e5d2ab9d1887178adbe3afa1c"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html#a112b466e5d2ab9d1887178adbe3afa1c">armnn::BatchMatMulDescriptor::m_TransposeY</a></div><div class="ttdeci">bool m_TransposeY</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01613">Descriptors.hpp:1613</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_gpu_fsa_pre_compiled_blob_html_a14f92a9f65e32c3da896e7b1d45abd02"><div class="ttname"><a href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html#a14f92a9f65e32c3da896e7b1d45abd02">armnn::GpuFsaPreCompiledBlob::sketch</a></div><div class="ttdeci">std::unique_ptr&lt; arm_compute::experimental::dynamic_fusion::GpuWorkloadSketch &gt; sketch</div><div class="ttdef"><b>Definition:</b> <a href="_gpu_fsa_backend_8hpp_source.html#l00034">GpuFsaBackend.hpp:34</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html">armnn::BatchMatMulDescriptor</a></div><div class="ttdoc">A BatchMatMulDescriptor for the BatchMatMul operator.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01584">Descriptors.hpp:1584</a></div></div>
+<div class="ttc" id="anamespacearmnn_html_a67a0db04d321a74b7e7fcfd3f1a3f70b"><div class="ttname"><a href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a></div><div class="ttdeci">Status</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00042">Types.hpp:42</a></div></div>
+<div class="ttc" id="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>
+<div class="ttc" id="a_gpu_fsa_batch_mat_mul_8hpp_html"><div class="ttname"><a href="_gpu_fsa_batch_mat_mul_8hpp.html">GpuFsaBatchMatMul.hpp</a></div></div>
+<div class="ttc" id="astructarmnn_1_1_gpu_fsa_pre_compiled_blob_html_a255c9012137b149ffb46d83c23f2df43"><div class="ttname"><a href="structarmnn_1_1_gpu_fsa_pre_compiled_blob.html#a255c9012137b149ffb46d83c23f2df43">armnn::GpuFsaPreCompiledBlob::workloadContext</a></div><div class="ttdeci">std::shared_ptr&lt; arm_compute::experimental::dynamic_fusion::GpuWorkloadContext &gt; workloadContext</div><div class="ttdef"><b>Definition:</b> <a href="_gpu_fsa_backend_8hpp_source.html#l00035">GpuFsaBackend.hpp:35</a></div></div>
+<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="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="anamespacearmnn_html_a47e56eb9bcbb170dddd202d770ed2cd8"><div class="ttname"><a href="namespacearmnn.html#a47e56eb9bcbb170dddd202d770ed2cd8">armnn::GpuFsaBatchMatMulValidate</a></div><div class="ttdeci">arm_compute::Status GpuFsaBatchMatMulValidate(const TensorInfo &amp;input0, const TensorInfo &amp;input1, const BatchMatMulDescriptor &amp;descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_gpu_fsa_batch_mat_mul_8cpp_source.html#l00022">GpuFsaBatchMatMul.cpp:22</a></div></div>
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