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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/_batch_mat_mul_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/_batch_mat_mul_layer_8cpp_source.html')
| -rw-r--r-- | latest/_batch_mat_mul_layer_8cpp_source.html | 169 |
1 files changed, 89 insertions, 80 deletions
diff --git a/latest/_batch_mat_mul_layer_8cpp_source.html b/latest/_batch_mat_mul_layer_8cpp_source.html index d3bdc9bf10..15d9d79d16 100644 --- a/latest/_batch_mat_mul_layer_8cpp_source.html +++ b/latest/_batch_mat_mul_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('_batch_mat_mul_layer_8cpp_source.html' </div><!--header--> <div class="contents"> <a href="_batch_mat_mul_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 © 2022-2023 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 © 2022-2024 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> <span class="preprocessor">#include "<a class="code" href="_batch_mat_mul_layer_8hpp.html">BatchMatMulLayer.hpp</a>"</span></div> @@ -130,96 +130,104 @@ $(document).ready(function(){initNavTree('_batch_mat_mul_layer_8cpp_source.html' <div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  </div> <div class="line"><a name="l00033"></a><span class="lineno"><a class="line" href="classarmnn_1_1_batch_mat_mul_layer.html#a65ca562c882ad619684445a1402f415a"> 33</a></span> std::vector<TensorShape> <a class="code" href="classarmnn_1_1_batch_mat_mul_layer.html#a65ca562c882ad619684445a1402f415a">BatchMatMulLayer::InferOutputShapes</a>(<span class="keyword">const</span> std::vector<TensorShape>& inputShapes)<span class="keyword"> const</span></div> <div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword"></span>{</div> -<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <a class="code" href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(inputShapes.size() == 2);</div> -<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  </div> -<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputXShape = inputShapes[0];</div> -<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputYShape = inputShapes[1];</div> -<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  </div> -<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="comment">// Adjoint is assumed to be square, but we will apply the permute anyway</span></div> -<div class="line"><a name="l00041"></a><span class="lineno"> 41</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_batch_mat_mul_descriptor.html#acb441bb8db19bcce78d15cdd8ceb5ea0">m_TransposeX</a> || <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#a0cf8306be7d301de0f095fff9901a525">m_AdjointX</a>)</div> -<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  {</div> -<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keyword">auto</span> permuteVec = <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#a85e74c2aeaf6fc124e9582329a82d72b">BatchMatMulDescriptor::GetPermuteVec</a>(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#aedca000a005e091c23191e82d7e81b1d">m_DataLayoutX</a>,</div> -<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  inputXShape);</div> -<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  inputXShape = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(inputXShape, permuteVec);</div> -<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  }</div> -<div class="line"><a name="l00047"></a><span class="lineno"> 47</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_batch_mat_mul_descriptor.html#a112b466e5d2ab9d1887178adbe3afa1c">m_TransposeY</a> || <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#ad945fc98770356dd886a68e98a52e26b">m_AdjointY</a>)</div> -<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  {</div> -<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keyword">auto</span> permuteVec = <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#a85e74c2aeaf6fc124e9582329a82d72b">BatchMatMulDescriptor::GetPermuteVec</a>(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#aaf7828880989b4b9378d3e86aa6dc843">m_DataLayoutY</a>,</div> -<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  inputYShape);</div> -<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  inputYShape = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(inputYShape, permuteVec);</div> -<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  }</div> -<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  </div> -<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& longerInput = inputXShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() >= inputYShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()?</div> -<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  inputXShape : inputYShape;</div> -<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& shorterInput = inputXShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() >= inputYShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()?</div> -<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  inputYShape : inputXShape;</div> -<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  </div> -<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputNumDimsOffset = longerInput.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() - shorterInput.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div> -<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  </div> -<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputNumDimensions = longerInput.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div> +<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keywordflow">if</span> (inputShapes.size() != 2)</div> +<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  {</div> +<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_layer_validation_exception.html">armnn::LayerValidationException</a>(<span class="stringliteral">"inputShapes' size is \""</span> + std::to_string(inputShapes.size()) +</div> +<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="stringliteral">"\" - should be \"2\"."</span>);</div> +<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  }</div> +<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  </div> +<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputXShape = inputShapes[0];</div> +<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputYShape = inputShapes[1];</div> +<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  </div> +<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="comment">// Adjoint is assumed to be square, but we will apply the permute anyway</span></div> +<div class="line"><a name="l00045"></a><span class="lineno"> 45</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_batch_mat_mul_descriptor.html#acb441bb8db19bcce78d15cdd8ceb5ea0">m_TransposeX</a> || <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#a0cf8306be7d301de0f095fff9901a525">m_AdjointX</a>)</div> +<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  {</div> +<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keyword">auto</span> permuteVec = <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#a85e74c2aeaf6fc124e9582329a82d72b">BatchMatMulDescriptor::GetPermuteVec</a>(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#aedca000a005e091c23191e82d7e81b1d">m_DataLayoutX</a>,</div> +<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  inputXShape);</div> +<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  inputXShape = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(inputXShape, permuteVec);</div> +<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  }</div> +<div class="line"><a name="l00051"></a><span class="lineno"> 51</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_batch_mat_mul_descriptor.html#a112b466e5d2ab9d1887178adbe3afa1c">m_TransposeY</a> || <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#ad945fc98770356dd886a68e98a52e26b">m_AdjointY</a>)</div> +<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  {</div> +<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">auto</span> permuteVec = <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#a85e74c2aeaf6fc124e9582329a82d72b">BatchMatMulDescriptor::GetPermuteVec</a>(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#aaf7828880989b4b9378d3e86aa6dc843">m_DataLayoutY</a>,</div> +<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  inputYShape);</div> +<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  inputYShape = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(inputYShape, permuteVec);</div> +<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  }</div> +<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  </div> +<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& longerInput = inputXShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() >= inputYShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()?</div> +<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  inputXShape : inputYShape;</div> +<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& shorterInput = inputXShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() >= inputYShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()?</div> +<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  inputYShape : inputXShape;</div> <div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  </div> -<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  std::vector<unsigned int> tensorDimensions(outputNumDimensions, 0);</div> +<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputNumDimsOffset = longerInput.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() - shorterInput.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div> <div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  </div> -<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& longerInputDataLayout = inputXShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() >= inputYShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()?</div> -<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#aedca000a005e091c23191e82d7e81b1d">m_DataLayoutX</a> : <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#aaf7828880989b4b9378d3e86aa6dc843">m_DataLayoutY</a>;</div> -<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">auto</span> longerAxesToMul = <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#a58a8b597d58396266e06dd2c415154a2">BatchMatMulDescriptor::GetAxesToMul</a>(longerInputDataLayout,</div> -<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  longerInput);</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < outputNumDimensions; ++i)</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="keywordflow">if</span> (i == longerAxesToMul.first)</div> -<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  {</div> -<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  tensorDimensions[i] = &shorterInput == &inputXShape ? inputXShape[i - inputNumDimsOffset] : inputXShape[i];</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>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(i == longerAxesToMul.second)</div> +<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputNumDimensions = longerInput.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div> +<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  </div> +<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  std::vector<unsigned int> tensorDimensions(outputNumDimensions, 0);</div> +<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  </div> +<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& longerInputDataLayout = inputXShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() >= inputYShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>()?</div> +<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#aedca000a005e091c23191e82d7e81b1d">m_DataLayoutX</a> : <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#aaf7828880989b4b9378d3e86aa6dc843">m_DataLayoutY</a>;</div> +<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">auto</span> longerAxesToMul = <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.html#a58a8b597d58396266e06dd2c415154a2">BatchMatMulDescriptor::GetAxesToMul</a>(longerInputDataLayout,</div> +<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  longerInput);</div> +<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  </div> +<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < outputNumDimensions; ++i)</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>  <span class="keywordflow">if</span> (i == longerAxesToMul.first)</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>  tensorDimensions[i] = &shorterInput == &inputYShape ? inputYShape[i - inputNumDimsOffset] : inputYShape[i];</div> +<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  tensorDimensions[i] = &shorterInput == &inputXShape ? inputXShape[i - inputNumDimsOffset] : inputXShape[i];</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>  <span class="keywordflow">else</span> <span class="comment">// The other dimensions not to be multiplied (but may be broadcasted)</span></div> +<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(i == longerAxesToMul.second)</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="comment">// Does NOT validate whether it's a valid broadcast - that's done in the validate func in WorkloadData.cpp</span></div> -<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  tensorDimensions[i] = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(i) - <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(inputNumDimsOffset) < 0 ?</div> -<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  longerInput[i] :</div> -<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  std::max(longerInput[i], shorterInput[i - inputNumDimsOffset]);</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>  }</div> -<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  </div> -<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keyword">auto</span> outputShape = <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>(outputNumDimensions, tensorDimensions.data());</div> -<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keywordflow">return</span> std::vector<TensorShape>({ outputShape });</div> -<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> }</div> +<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  tensorDimensions[i] = &shorterInput == &inputYShape ? inputYShape[i - inputNumDimsOffset] : inputYShape[i];</div> +<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  }</div> +<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordflow">else</span> <span class="comment">// The other dimensions not to be multiplied (but may be broadcasted)</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="comment">// Does NOT validate whether it's a valid broadcast - that's done in the validate func in WorkloadData.cpp</span></div> +<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  tensorDimensions[i] = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(i) - <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(inputNumDimsOffset) < 0 ?</div> +<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  longerInput[i] :</div> +<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  std::max(longerInput[i], shorterInput[i - inputNumDimsOffset]);</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>  }</div> <div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  </div> -<div class="line"><a name="l00093"></a><span class="lineno"><a class="line" href="classarmnn_1_1_batch_mat_mul_layer.html#a8c8f543d7e9729362c266d12ec169966"> 93</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_batch_mat_mul_layer.html#a8c8f543d7e9729362c266d12ec169966">BatchMatMulLayer::ValidateTensorShapesFromInputs</a>()</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_layer.html#a0607e36e88f38c34c71c663164b76776">VerifyLayerConnections</a>(2, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div> +<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keyword">auto</span> outputShape = <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>(outputNumDimensions, tensorDimensions.data());</div> +<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keywordflow">return</span> std::vector<TensorShape>({ outputShape });</div> +<div class="line"><a name="l00095"></a><span class="lineno"> 95</span> }</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="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="l00098"></a><span class="lineno"> 98</span>  </div> -<div class="line"><a name="l00099"></a><span class="lineno"> 99</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="l00097"></a><span class="lineno"><a class="line" href="classarmnn_1_1_batch_mat_mul_layer.html#a8c8f543d7e9729362c266d12ec169966"> 97</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_batch_mat_mul_layer.html#a8c8f543d7e9729362c266d12ec169966">BatchMatMulLayer::ValidateTensorShapesFromInputs</a>()</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>  <a class="code" href="classarmnn_1_1_layer.html#a0607e36e88f38c34c71c663164b76776">VerifyLayerConnections</a>(2, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div> <div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  </div> -<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">auto</span> inferredShapes = <a class="code" href="classarmnn_1_1_batch_mat_mul_layer.html#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>({</div> -<div class="line"><a name="l00102"></a><span class="lineno"> 102</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="l00103"></a><span class="lineno"> 103</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="l00101"></a><span class="lineno"> 101</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="l00102"></a><span class="lineno"> 102</span>  </div> +<div class="line"><a name="l00103"></a><span class="lineno"> 103</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="l00104"></a><span class="lineno"> 104</span>  </div> -<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(inferredShapes.size() == 1);</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>  <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">"BatchMatMulLayer"</span>);</div> -<div class="line"><a name="l00108"></a><span class="lineno"> 108</span> }</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> } <span class="comment">// namespace armnn</span></div> +<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keyword">auto</span> inferredShapes = <a class="code" href="classarmnn_1_1_batch_mat_mul_layer.html#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>({</div> +<div class="line"><a name="l00106"></a><span class="lineno"> 106</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="l00107"></a><span class="lineno"> 107</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="l00108"></a><span class="lineno"> 108</span>  </div> +<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordflow">if</span> (inferredShapes.size() != 1)</div> +<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  {</div> +<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_layer_validation_exception.html">armnn::LayerValidationException</a>(<span class="stringliteral">"inferredShapes has "</span></div> +<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  + std::to_string(inferredShapes.size()) +</div> +<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="stringliteral">" elements - should only have 1."</span>);</div> +<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  }</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>  <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">"BatchMatMulLayer"</span>);</div> +<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> }</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> } <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_batch_mat_mul_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_queue_descriptor.html">armnn::BatchMatMulQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00753">WorkloadData.hpp:753</a></div></div> <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="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="astructarmnn_1_1_batch_mat_mul_descriptor_html_a0cf8306be7d301de0f095fff9901a525"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html#a0cf8306be7d301de0f095fff9901a525">armnn::BatchMatMulDescriptor::m_AdjointX</a></div><div class="ttdeci">bool m_AdjointX</div><div class="ttdoc">Adjoint the slices of each input tensor Transpose and Adjoint can not both be set to true for the sam...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01617">Descriptors.hpp:1617</a></div></div> -<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_html_a58a8b597d58396266e06dd2c415154a2"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html#a58a8b597d58396266e06dd2c415154a2">armnn::BatchMatMulDescriptor::GetAxesToMul</a></div><div class="ttdeci">static std::pair< unsigned int, unsigned int > GetAxesToMul(DataLayout dataLayout, const TensorShape &tensorShape)</div><div class="ttdoc">Static helper to get the two axes (for each input) for multiplication.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00484">Descriptors.cpp:484</a></div></div> -<div class="ttc" id="aclassarmnn_1_1_batch_mat_mul_layer_html_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_batch_mat_mul_layer.html#a8c8f543d7e9729362c266d12ec169966">armnn::BatchMatMulLayer::ValidateTensorShapesFromInputs</a></div><div class="ttdeci">void ValidateTensorShapesFromInputs() override</div><div class="ttdoc">Check if the input tensor shapes will lead to a valid configuration of BatchMatMulLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_batch_mat_mul_layer_8cpp_source.html#l00093">BatchMatMulLayer.cpp:93</a></div></div> +<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_html_a58a8b597d58396266e06dd2c415154a2"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html#a58a8b597d58396266e06dd2c415154a2">armnn::BatchMatMulDescriptor::GetAxesToMul</a></div><div class="ttdeci">static std::pair< unsigned int, unsigned int > GetAxesToMul(DataLayout dataLayout, const TensorShape &tensorShape)</div><div class="ttdoc">Static helper to get the two axes (for each input) for multiplication.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00485">Descriptors.cpp:485</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_batch_mat_mul_layer_html_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_batch_mat_mul_layer.html#a8c8f543d7e9729362c266d12ec169966">armnn::BatchMatMulLayer::ValidateTensorShapesFromInputs</a></div><div class="ttdeci">void ValidateTensorShapesFromInputs() override</div><div class="ttdoc">Check if the input tensor shapes will lead to a valid configuration of BatchMatMulLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_batch_mat_mul_layer_8cpp_source.html#l00097">BatchMatMulLayer.cpp:97</a></div></div> <div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_html_aedca000a005e091c23191e82d7e81b1d"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html#aedca000a005e091c23191e82d7e81b1d">armnn::BatchMatMulDescriptor::m_DataLayoutX</a></div><div class="ttdeci">DataLayout m_DataLayoutX</div><div class="ttdoc">Data layout of each input tensor, such as NHWC/NDHWC (leave as default for arbitrary layout)</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01621">Descriptors.hpp:1621</a></div></div> <div class="ttc" id="a_batch_mat_mul_layer_8hpp_html"><div class="ttname"><a href="_batch_mat_mul_layer_8hpp.html">BatchMatMulLayer.hpp</a></div></div> <div class="ttc" id="a_exceptions_8hpp_html_aa3be76aec4ce713822a5ea1ecbb7bc61"><div class="ttname"><a href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a></div><div class="ttdeci">#define CHECK_LOCATION()</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00203">Exceptions.hpp:203</a></div></div> -<div class="ttc" id="aclassarmnn_1_1_layer_html_aeb2d638cc0e02c10075e015100996f2d"><div class="ttname"><a href="classarmnn_1_1_layer.html#aeb2d638cc0e02c10075e015100996f2d">armnn::Layer::ValidateAndCopyShape</a></div><div class="ttdeci">void ValidateAndCopyShape(const TensorShape &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="astructarmnn_1_1_batch_mat_mul_descriptor_html_a85e74c2aeaf6fc124e9582329a82d72b"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html#a85e74c2aeaf6fc124e9582329a82d72b">armnn::BatchMatMulDescriptor::GetPermuteVec</a></div><div class="ttdeci">static PermutationVector GetPermuteVec(DataLayout dataLayout, const TensorShape &tensorShape)</div><div class="ttdoc">Static helper to get the axes which will be transposed.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00522">Descriptors.cpp:522</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="astructarmnn_1_1_batch_mat_mul_descriptor_html_a85e74c2aeaf6fc124e9582329a82d72b"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html#a85e74c2aeaf6fc124e9582329a82d72b">armnn::BatchMatMulDescriptor::GetPermuteVec</a></div><div class="ttdeci">static PermutationVector GetPermuteVec(DataLayout dataLayout, const TensorShape &tensorShape)</div><div class="ttdoc">Static helper to get the axes which will be transposed.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.html#l00523">Descriptors.cpp:523</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_batch_mat_mul_descriptor_html_ad945fc98770356dd886a68e98a52e26b"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html#ad945fc98770356dd886a68e98a52e26b">armnn::BatchMatMulDescriptor::m_AdjointY</a></div><div class="ttdeci">bool m_AdjointY</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01618">Descriptors.hpp:1618</a></div></div> <div class="ttc" id="aclassarmnn_1_1_batch_mat_mul_layer_html_a5a344fd448ac4673a1e63549b54bc181"><div class="ttname"><a href="classarmnn_1_1_batch_mat_mul_layer.html#a5a344fd448ac4673a1e63549b54bc181">armnn::BatchMatMulLayer::Clone</a></div><div class="ttdeci">BatchMatMulLayer * 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="_batch_mat_mul_layer_8cpp_source.html#l00026">BatchMatMulLayer.cpp:26</a></div></div> @@ -228,19 +236,20 @@ $(document).ready(function(){initNavTree('_batch_mat_mul_layer_8cpp_source.html' <div class="ttc" id="a_workload_factory_8hpp_html"><div class="ttname"><a href="_workload_factory_8hpp.html">WorkloadFactory.hpp</a></div></div> <div class="ttc" id="aclassarmnn_1_1_layer_with_parameters_html"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html">armnn::LayerWithParameters</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00014">LayerWithParameters.hpp:14</a></div></div> <div class="ttc" id="aclassarmnn_1_1_layer_html_a7ddf0cf6f620d59c10e63495ace795d0"><div class="ttname"><a href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">armnn::Layer::GetName</a></div><div class="ttdeci">const char * GetName() const override</div><div class="ttdoc">Returns the name of the layer.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00332">Layer.hpp:332</a></div></div> -<div class="ttc" id="aclassarmnn_1_1_input_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::InputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & 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_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< BatchMatMulDescriptor >::m_Param</a></div><div class="ttdeci">BatchMatMulDescriptor m_Param</div><div class="ttdoc">The parameters for the layer (not including tensor-valued weights etc.).</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00052">LayerWithParameters.hpp:52</a></div></div> <div class="ttc" id="aclassarmnn_1_1_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="aclassarmnn_1_1_layer_with_parameters_html_a30a858b2b26d651a066537e499fbf40d"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#a30a858b2b26d651a066537e499fbf40d">armnn::LayerWithParameters< BatchMatMulDescriptor >::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="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="aclassarmnn_1_1_layer_validation_exception_html"><div class="ttname"><a href="classarmnn_1_1_layer_validation_exception.html">armnn::LayerValidationException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00105">Exceptions.hpp:105</a></div></div> <div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_html_aaf7828880989b4b9378d3e86aa6dc843"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.html#aaf7828880989b4b9378d3e86aa6dc843">armnn::BatchMatMulDescriptor::m_DataLayoutY</a></div><div class="ttdeci">DataLayout m_DataLayoutY</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01622">Descriptors.hpp:1622</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="aclassarmnn_1_1_batch_mat_mul_layer_html_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_batch_mat_mul_layer.html#a65ca562c882ad619684445a1402f415a">armnn::BatchMatMulLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">Infers the output shape from the given input shapes.</div><div class="ttdef"><b>Definition:</b> <a href="_batch_mat_mul_layer_8cpp_source.html#l00033">BatchMatMulLayer.cpp:33</a></div></div> <div class="ttc" id="aclassarmnn_1_1_batch_mat_mul_layer_html_adfa912d0c4c6c00f1af2cbfa799572b7"><div class="ttname"><a href="classarmnn_1_1_batch_mat_mul_layer.html#adfa912d0c4c6c00f1af2cbfa799572b7">armnn::BatchMatMulLayer::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override</div><div class="ttdoc">Makes a workload for the BatchMatMul type.</div><div class="ttdef"><b>Definition:</b> <a href="_batch_mat_mul_layer_8cpp_source.html#l00018">BatchMatMulLayer.cpp:18</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_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="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="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_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="a_permute_8hpp_html"><div class="ttname"><a href="_permute_8hpp.html">Permute.hpp</a></div></div> <div class="ttc" id="aclassarmnn_1_1_batch_mat_mul_html"><div class="ttname"><a href="classarmnn_1_1_batch_mat_mul.html">armnn::BatchMatMul</a></div><div class="ttdef"><b>Definition:</b> <a href="_batch_mat_mul_impl_8hpp_source.html#l00016">BatchMatMulImpl.hpp:16</a></div></div> <div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a9882ff3cfed27d6161c20a305e7a3484"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a9882ff3cfed27d6161c20a305e7a3484">armnn::LayerType::BatchMatMul</a></div><div class="ttdeci">@ BatchMatMul</div></div> @@ -248,7 +257,7 @@ $(document).ready(function(){initNavTree('_batch_mat_mul_layer_8cpp_source.html' <div class="ttc" id="aclassarmnn_1_1_batch_mat_mul_layer_html"><div class="ttname"><a href="classarmnn_1_1_batch_mat_mul_layer.html">armnn::BatchMatMulLayer</a></div><div class="ttdef"><b>Definition:</b> <a href="_batch_mat_mul_layer_8hpp_source.html#l00013">BatchMatMulLayer.hpp:13</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_batch_mat_mul_layer_html_adaa2e073b65919375724109581b751c0"><div class="ttname"><a href="classarmnn_1_1_batch_mat_mul_layer.html#adaa2e073b65919375724109581b751c0">armnn::BatchMatMulLayer::BatchMatMulLayer</a></div><div class="ttdeci">BatchMatMulLayer(const BatchMatMulDescriptor &param, const char *name)</div><div class="ttdoc">Constructor to create a BatchMatMulLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_batch_mat_mul_layer_8cpp_source.html#l00014">BatchMatMulLayer.cpp:14</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="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="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> @@ -258,7 +267,7 @@ $(document).ready(function(){initNavTree('_batch_mat_mul_layer_8cpp_source.html' <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.html">src</a></li><li class="navelem"><a class="el" href="dir_e0a84d05c80a2ef4231141dcbbeac5c8.html">armnn</a></li><li class="navelem"><a class="el" href="dir_9da6642ce0fd5a8c83524f1b621275be.html">layers</a></li><li class="navelem"><a class="el" href="_batch_mat_mul_layer_8cpp.html">BatchMatMulLayer.cpp</a></li> - <li class="footer">Generated on Wed Feb 14 2024 16:36:14 for Arm NN by + <li class="footer">Generated on Thu May 16 2024 09:31:44 for Arm NN by <a href="http://www.doxygen.org/index.html"> <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.17 </li> </ul> |