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| <a href="#pub-methods">Public Member Functions</a> | |
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| <div class="title">CLWidthConcatenateLayer Class Reference</div> </div> |
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| |
| <p>Basic function to execute concatenate tensors along x axis. |
| <a href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml#details">More...</a></p> |
| |
| <p><code>#include <<a class="el" href="_c_l_width_concatenate_layer_8h_source.xhtml">CLWidthConcatenateLayer.h</a>></code></p> |
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| Collaboration diagram for CLWidthConcatenateLayer:</div> |
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| <table class="memberdecls"> |
| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a> |
| Public Member Functions</h2></td></tr> |
| <tr class="memitem:a13c4828072a7f8229748b08bf7e65a7c"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml#a13c4828072a7f8229748b08bf7e65a7c">CLWidthConcatenateLayer</a> ()</td></tr> |
| <tr class="memdesc:a13c4828072a7f8229748b08bf7e65a7c"><td class="mdescLeft"> </td><td class="mdescRight">Default constructor. <a href="#a13c4828072a7f8229748b08bf7e65a7c">More...</a><br /></td></tr> |
| <tr class="separator:a13c4828072a7f8229748b08bf7e65a7c"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ae1e594a6c6605fb33245f84722039eab"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml#ae1e594a6c6605fb33245f84722039eab">configure</a> (std::vector< <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * > inputs_vector, <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *output)</td></tr> |
| <tr class="memdesc:ae1e594a6c6605fb33245f84722039eab"><td class="mdescLeft"> </td><td class="mdescRight">Initialise the kernel's inputs vector and output. <a href="#ae1e594a6c6605fb33245f84722039eab">More...</a><br /></td></tr> |
| <tr class="separator:ae1e594a6c6605fb33245f84722039eab"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a> () override</td></tr> |
| <tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft"> </td><td class="mdescRight">Run the kernels contained in the function. <a href="#ad1717410afd0be936c6213a63c8005fb">More...</a><br /></td></tr> |
| <tr class="separator:ad1717410afd0be936c6213a63c8005fb"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="inherit_header pub_methods_classarm__compute_1_1_i_function"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_function')"><img src="closed.png" alt="-"/> Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></td></tr> |
| <tr class="memitem:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">~IFunction</a> ()=default</td></tr> |
| <tr class="memdesc:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft"> </td><td class="mdescRight">Destructor. <a href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">More...</a><br /></td></tr> |
| <tr class="separator:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">prepare</a> ()</td></tr> |
| <tr class="memdesc:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft"> </td><td class="mdescRight">Prepare the function for executing. <a href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">More...</a><br /></td></tr> |
| <tr class="separator:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2"> </td></tr> |
| </table><table class="memberdecls"> |
| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a> |
| Static Public Member Functions</h2></td></tr> |
| <tr class="memitem:af03a00ff6ac9807e1417ed25101e1102"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml#af03a00ff6ac9807e1417ed25101e1102">validate</a> (const std::vector< <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * > &inputs_vector, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output)</td></tr> |
| <tr class="memdesc:af03a00ff6ac9807e1417ed25101e1102"><td class="mdescLeft"> </td><td class="mdescRight">Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_c_l_depth_concatenate_layer_kernel.xhtml">CLDepthConcatenateLayerKernel</a>. <a href="#af03a00ff6ac9807e1417ed25101e1102">More...</a><br /></td></tr> |
| <tr class="separator:af03a00ff6ac9807e1417ed25101e1102"><td class="memSeparator" colspan="2"> </td></tr> |
| </table> |
| <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2> |
| <div class="textblock"><p>Basic function to execute concatenate tensors along x axis. </p> |
| <p>This function calls the following kernel:</p> |
| <dl class="deprecated"><dt><b><a class="el" href="deprecated.xhtml#_deprecated000005">Deprecated:</a></b></dt><dd>This function is deprecated and will be removed in release 19.08</dd></dl> |
| <ol type="1"> |
| <li><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer_kernel.xhtml">CLWidthConcatenateLayerKernel</a></li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_width_concatenate2_tensors_kernel.xhtml">CLWidthConcatenate2TensorsKernel</a> (if there are exactly 2 input tensors)</li> |
| <li><a class="el" href="classarm__compute_1_1_c_l_width_concatenate4_tensors_kernel.xhtml">CLWidthConcatenate4TensorsKernel</a> (if there are exactly 4 input tensors) </li> |
| </ol> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_width_concatenate_layer_8h_source.xhtml#l00052">52</a> of file <a class="el" href="_c_l_width_concatenate_layer_8h_source.xhtml">CLWidthConcatenateLayer.h</a>.</p> |
| </div><h2 class="groupheader">Constructor & Destructor Documentation</h2> |
| <a id="a13c4828072a7f8229748b08bf7e65a7c"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a13c4828072a7f8229748b08bf7e65a7c">◆ </a></span>CLWidthConcatenateLayer()</h2> |
| |
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| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml">CLWidthConcatenateLayer</a> </td> |
| <td>(</td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Default constructor. </p> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml#l00037">37</a> of file <a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml">CLWidthConcatenateLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  : _concat_kernels_vector(),</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  _concat_x2_kernel(),</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  _concat_x4_kernel(),</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  _num_inputs(0)</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> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <h2 class="groupheader">Member Function Documentation</h2> |
| <a id="ae1e594a6c6605fb33245f84722039eab"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ae1e594a6c6605fb33245f84722039eab">◆ </a></span>configure()</h2> |
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| <table class="memname"> |
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| <td class="memname">void configure </td> |
| <td>(</td> |
| <td class="paramtype">std::vector< <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * > </td> |
| <td class="paramname"><em>inputs_vector</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> * </td> |
| <td class="paramname"><em>output</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Initialise the kernel's inputs vector and output. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">inputs_vector</td><td>The vectors containing all the tensors to concatenate. Data types supported: QASYMM8/F16/F32. <a class="el" href="classarm__compute_1_1_dimensions.xhtml" title="Dimensions with dimensionality.">Dimensions</a> of all the inputs should match apart for the width which can differ. </td></tr> |
| <tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Output tensor. Data types supported: Same as <code>input</code>. Output tensor dimensions are the same with the inputs from the second dimension and above. The first dimension (width) is the sum of the input tensors' widths. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml#l00084">84</a> of file <a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml">CLWidthConcatenateLayer.cpp</a>.</p> |
| <div class="fragment"><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>  _num_inputs = inputs_vector.size();</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>  std::vector<ITensorInfo *> inputs_vector_info;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < _num_inputs; i++)</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>  inputs_vector_info.emplace_back(inputs_vector.at(i)->info());</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  }</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">output_shape</a> = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a6100aeb494088632647c3e0d639c99ab">arm_compute::misc::shape_calculator::calculate_concatenate_shape</a>(inputs_vector, <a class="code" href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">Window::DimX</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>  <span class="comment">// Output auto inizialitation if not yet initialized</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">output_shape</a>, 1, inputs_vector[0]->info()->data_type());</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> </div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(<a class="code" href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml#af03a00ff6ac9807e1417ed25101e1102">CLWidthConcatenateLayer::validate</a>(inputs_vector_info, output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()));</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordflow">switch</span>(_num_inputs)</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  {</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="comment">// Configure WidthConcatenate2Tensors kernel</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  _concat_x2_kernel.<a class="code" href="classarm__compute_1_1_c_l_width_concatenate2_tensors_kernel.xhtml#af53d66a8f8dd368d3c06b43c0c6a12f1">configure</a>(inputs_vector.at(0), inputs_vector.at(1), output);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">case</span> 4:</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="comment">// Configure WidthConcatenate4Tensors kernel</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  _concat_x4_kernel.<a class="code" href="classarm__compute_1_1_c_l_width_concatenate4_tensors_kernel.xhtml#ab830c43458598cdfd7d2f8751e2009b0">configure</a>(inputs_vector.at(0), inputs_vector.at(1), inputs_vector.at(2), inputs_vector.at(3), output);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="comment">// Configure generic case WidthConcatenate kernels</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  _concat_kernels_vector.resize(_num_inputs);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width_offset = 0;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < _num_inputs; ++i)</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  _concat_kernels_vector[i].configure(inputs_vector.at(i), width_offset, output);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  width_offset += inputs_vector.at(i)->info()->dimension(0);</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  }</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  }</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> }</div><div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_a6100aeb494088632647c3e0d639c99ab"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a6100aeb494088632647c3e0d639c99ab">arm_compute::misc::shape_calculator::calculate_concatenate_shape</a></div><div class="ttdeci">TensorShape calculate_concatenate_shape(const std::vector< T * > &input, size_t axis)</div><div class="ttdoc">Calculate the concatenate output shape of the concatenate operation along a single axis.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l01184">ShapeCalculator.h:1184</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_width_concatenate2_tensors_kernel_xhtml_af53d66a8f8dd368d3c06b43c0c6a12f1"><div class="ttname"><a href="classarm__compute_1_1_c_l_width_concatenate2_tensors_kernel.xhtml#af53d66a8f8dd368d3c06b43c0c6a12f1">arm_compute::CLWidthConcatenate2TensorsKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)</div><div class="ttdoc">Initialise the kernel's input1s and output.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_width_concatenate2_tensors_kernel_8cpp_source.xhtml#l00098">CLWidthConcatenate2TensorsKernel.cpp:98</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a938dcd406ce611ef5345ad2531cdb948"><div class="ttname"><a href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_THROW_ON(status)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00327">Error.h:327</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a47be6fa38308d0003c25b60b7dbc45ce"><div class="ttname"><a href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">arm_compute::auto_init_if_empty</a></div><div class="ttdeci">bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())</div><div class="ttdoc">Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00201">Helpers.inl:201</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml_aa96e81276ee4f87ab386cd05a5539a7d"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">arm_compute::Window::DimX</a></div><div class="ttdeci">static constexpr size_t DimX</div><div class="ttdoc">Alias for dimension 0 also known as X dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00043">Window.h:43</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_width_concatenate_layer_xhtml_af03a00ff6ac9807e1417ed25101e1102"><div class="ttname"><a href="classarm__compute_1_1_c_l_width_concatenate_layer.xhtml#af03a00ff6ac9807e1417ed25101e1102">arm_compute::CLWidthConcatenateLayer::validate</a></div><div class="ttdeci">static Status validate(const std::vector< ITensorInfo * > &inputs_vector, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLDepthConcatenateLayerK...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_width_concatenate_layer_8cpp_source.xhtml#l00045">CLWidthConcatenateLayer.cpp:45</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a7fc93f37dac131a1a40b7921f9df3a9a"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">arm_compute::test::validation::output_shape</a></div><div class="ttdeci">output_shape</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_width_concatenate4_tensors_kernel_xhtml_ab830c43458598cdfd7d2f8751e2009b0"><div class="ttname"><a href="classarm__compute_1_1_c_l_width_concatenate4_tensors_kernel.xhtml#ab830c43458598cdfd7d2f8751e2009b0">arm_compute::CLWidthConcatenate4TensorsKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input1, const ICLTensor *input2, const ICLTensor *input3, const ICLTensor *input4, ICLTensor *output)</div><div class="ttdoc">Initialise the kernel's input1s and output.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_width_concatenate4_tensors_kernel_8cpp_source.xhtml#l00116">CLWidthConcatenate4TensorsKernel.cpp:116</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_error_8h_source.xhtml#l00327">ARM_COMPUTE_ERROR_THROW_ON</a>, <a class="el" href="_helpers_8inl_source.xhtml#l00201">arm_compute::auto_init_if_empty()</a>, <a class="el" href="_shape_calculator_8h_source.xhtml#l01184">arm_compute::misc::shape_calculator::calculate_concatenate_shape()</a>, <a class="el" href="_c_l_width_concatenate2_tensors_kernel_8cpp_source.xhtml#l00098">CLWidthConcatenate2TensorsKernel::configure()</a>, <a class="el" href="_c_l_width_concatenate4_tensors_kernel_8cpp_source.xhtml#l00116">CLWidthConcatenate4TensorsKernel::configure()</a>, <a class="el" href="_window_8h_source.xhtml#l00043">Window::DimX</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::info()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::output_shape</a>, and <a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml#l00045">CLWidthConcatenateLayer::validate()</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_c_l_l_s_t_m_layer_8cpp_source.xhtml#l00054">CLLSTMLayer::configure()</a>.</p> |
| |
| </div> |
| </div> |
| <a id="ad1717410afd0be936c6213a63c8005fb"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#ad1717410afd0be936c6213a63c8005fb">◆ </a></span>run()</h2> |
| |
| <div class="memitem"> |
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| <td class="mlabels-left"> |
| <table class="memname"> |
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| <td class="memname">void run </td> |
| <td>(</td> |
| <td class="paramname"></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </td> |
| </tr> |
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| </div><div class="memdoc"> |
| |
| <p>Run the kernels contained in the function. </p> |
| <p>For NEON kernels:</p><ul> |
| <li>Multi-threading is used for the kernels which are parallelisable.</li> |
| <li>By default std::thread::hardware_concurrency() threads are used.</li> |
| </ul> |
| <dl class="section note"><dt>Note</dt><dd><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml#ae64eebaa07f4d2da6cc2ba538c3cb095">CPPScheduler::set_num_threads()</a> can be used to manually set the number of threads</dd></dl> |
| <p>For OpenCL kernels:</p><ul> |
| <li>All the kernels are enqueued on the queue associated with <a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" title="Provides global access to a CL context and command queue.">CLScheduler</a>.</li> |
| <li>The queue is then flushed.</li> |
| </ul> |
| <dl class="section note"><dt>Note</dt><dd>The function will not block until the kernels are executed. It is the user's responsibility to wait. </dd> |
| <dd> |
| Will call <a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26" title="Prepare the function for executing.">prepare()</a> on first run if hasn't been done </dd></dl> |
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| <p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml#l00124">124</a> of file <a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml">CLWidthConcatenateLayer.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> {</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  cl::CommandQueue q = <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ad381d1aed28b4b1e1f5a710633934580">queue</a>();</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keywordflow">switch</span>(_num_inputs)</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  {</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_concat_x2_kernel, <span class="keyword">true</span>);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordflow">case</span> 4:</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_concat_x4_kernel, <span class="keyword">true</span>);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < _num_inputs; ++i)</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  {</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_concat_kernels_vector[i], <span class="keyword">true</span>);</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  }</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  }</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> }</div><div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a9b58d0eb9a2af8e6d7908695e1557d6c"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">arm_compute::CLScheduler::get</a></div><div class="ttdeci">static CLScheduler & get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler.cpp:41</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_ae1a643e517f50bf0392fb6516dd7cf67"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">arm_compute::CLScheduler::enqueue</a></div><div class="ttdeci">void enqueue(ICLKernel &kernel, bool flush=true)</div><div class="ttdoc">Schedule the execution of the passed kernel if possible.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00095">CLScheduler.cpp:95</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_ad381d1aed28b4b1e1f5a710633934580"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#ad381d1aed28b4b1e1f5a710633934580">arm_compute::CLScheduler::queue</a></div><div class="ttdeci">cl::CommandQueue & queue()</div><div class="ttdoc">Accessor for the associated CL command queue.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8h_source.xhtml#l00102">CLScheduler.h:102</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00095">CLScheduler::enqueue()</a>, <a class="el" href="_c_l_scheduler_8cpp_source.xhtml#l00041">CLScheduler::get()</a>, and <a class="el" href="_c_l_scheduler_8h_source.xhtml#l00102">CLScheduler::queue()</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_c_l_l_s_t_m_layer_8cpp_source.xhtml#l00504">CLLSTMLayer::run()</a>.</p> |
| |
| </div> |
| </div> |
| <a id="af03a00ff6ac9807e1417ed25101e1102"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#af03a00ff6ac9807e1417ed25101e1102">◆ </a></span>validate()</h2> |
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| <table class="memname"> |
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| <td class="memname"><a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> validate </td> |
| <td>(</td> |
| <td class="paramtype">const std::vector< <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * > & </td> |
| <td class="paramname"><em>inputs_vector</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> * </td> |
| <td class="paramname"><em>output</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">static</span></span> </td> |
| </tr> |
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| </div><div class="memdoc"> |
| |
| <p>Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_c_l_depth_concatenate_layer_kernel.xhtml">CLDepthConcatenateLayerKernel</a>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">inputs_vector</td><td>The vectors containing all the tensors to concatenate. Data types supported: QASYMM8/F16/F32. <a class="el" href="classarm__compute_1_1_dimensions.xhtml" title="Dimensions with dimensionality.">Dimensions</a> of all the inputs should match apart for the width which can differ. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Output tensor. Data types supported: Same as <code>input</code>. Output tensor dimensions are the same with the inputs from the second dimension and above. The first dimension (width) is the sum of the input tensors' widths.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section return"><dt>Returns</dt><dd>a status </dd></dl> |
| |
| <p class="definition">Definition at line <a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml#l00045">45</a> of file <a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml">CLWidthConcatenateLayer.cpp</a>.</p> |
| <div class="fragment"><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">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_inputs = inputs_vector.size();</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>  <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>(output);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(num_inputs < 2);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="comment">// Output auto inizialitation if not yet initialized</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> tmp_output_info = *output-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>();</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">output_shape</a> = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a6100aeb494088632647c3e0d639c99ab">arm_compute::misc::shape_calculator::calculate_concatenate_shape</a>(inputs_vector, <a class="code" href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">Window::DimX</a>);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(tmp_output_info, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">output_shape</a>, 1, inputs_vector[0]-><a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">data_type</a>());</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>  <span class="keywordflow">switch</span>(num_inputs)</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="keywordflow">case</span> 2:</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="comment">// Validate WidthConcatenate2Tensors kernels if there are 2 inputs</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>(inputs_vector[0], inputs_vector[1]);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_width_concatenate2_tensors_kernel.xhtml#afe71126bef1735fe1613a6da30d2c0c4">CLWidthConcatenate2TensorsKernel::validate</a>(inputs_vector[0], inputs_vector[1], &tmp_output_info));</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordflow">case</span> 4:</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="comment">// Validate WidthConcatenate4Tensors kernels if there are 4 inputs</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>(inputs_vector[0], inputs_vector[1], inputs_vector[2], inputs_vector[3]);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_width_concatenate4_tensors_kernel.xhtml#a7a7d53bfb54f24863fcab9a046753c86">CLWidthConcatenate4TensorsKernel::validate</a>(inputs_vector[0], inputs_vector[1], inputs_vector[2], inputs_vector[3], &tmp_output_info));</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width_offset = 0;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="comment">// Validate generic case of WidthConcatenate kernel</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordflow">for</span>(<span class="keyword">const</span> <span class="keyword">auto</span> &input : inputs_vector)</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>  <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>(input);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_width_concatenate_layer_kernel.xhtml#adecdb3cc6b7b36f8bfbcd777ff021809">CLWidthConcatenateLayerKernel::validate</a>(input, width_offset, &tmp_output_info));</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  width_offset += input->dimension(0);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  }</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  }</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> }</div><div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_a6100aeb494088632647c3e0d639c99ab"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a6100aeb494088632647c3e0d639c99ab">arm_compute::misc::shape_calculator::calculate_concatenate_shape</a></div><div class="ttdeci">TensorShape calculate_concatenate_shape(const std::vector< T * > &input, size_t axis)</div><div class="ttdoc">Calculate the concatenate output shape of the concatenate operation along a single axis.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l01184">ShapeCalculator.h:1184</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_width_concatenate_layer_kernel_xhtml_adecdb3cc6b7b36f8bfbcd777ff021809"><div class="ttname"><a href="classarm__compute_1_1_c_l_width_concatenate_layer_kernel.xhtml#adecdb3cc6b7b36f8bfbcd777ff021809">arm_compute::CLWidthConcatenateLayerKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, unsigned int width_offset, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLWidthConcatenateLayerK...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_width_concatenate_layer_kernel_8cpp_source.xhtml#l00085">CLWidthConcatenateLayerKernel.cpp:85</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a8a1e1c105f0bdaf37db408c7cfcb77a4"><div class="ttname"><a href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ON_ERROR(status)</div><div class="ttdoc">Checks if a status contains an error and returns it.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00193">Error.h:193</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_status_xhtml"><div class="ttname"><a href="classarm__compute_1_1_status.xhtml">arm_compute::Status</a></div><div class="ttdoc">Status class.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00052">Error.h:52</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a206d6e247e0957ac3dee45d27756fc25"><div class="ttname"><a href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00244">Error.h:244</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a47be6fa38308d0003c25b60b7dbc45ce"><div class="ttname"><a href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">arm_compute::auto_init_if_empty</a></div><div class="ttdeci">bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())</div><div class="ttdoc">Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00201">Helpers.inl:201</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ac2ad7f431e3446fddcd9b6b9f93c4c14"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">arm_compute::test::validation::data_type</a></div><div class="ttdeci">data_type</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml_aa96e81276ee4f87ab386cd05a5539a7d"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#aa96e81276ee4f87ab386cd05a5539a7d">arm_compute::Window::DimX</a></div><div class="ttdeci">static constexpr size_t DimX</div><div class="ttdoc">Alias for dimension 0 also known as X dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00043">Window.h:43</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a7fc93f37dac131a1a40b7921f9df3a9a"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a7fc93f37dac131a1a40b7921f9df3a9a">arm_compute::test::validation::output_shape</a></div><div class="ttdeci">output_shape</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1misc_1_1_i_cloneable_xhtml_a4d10e5012a872e7f78f2b539b673049d"><div class="ttname"><a href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">arm_compute::misc::ICloneable::clone</a></div><div class="ttdeci">virtual std::unique_ptr< T > clone() const =0</div><div class="ttdoc">Provide a clone of the current object of class T.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_width_concatenate4_tensors_kernel_xhtml_a7a7d53bfb54f24863fcab9a046753c86"><div class="ttname"><a href="classarm__compute_1_1_c_l_width_concatenate4_tensors_kernel.xhtml#a7a7d53bfb54f24863fcab9a046753c86">arm_compute::CLWidthConcatenate4TensorsKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *input3, const ITensorInfo *input4, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLWidthConcatenate4Tenso...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_width_concatenate4_tensors_kernel_8cpp_source.xhtml#l00109">CLWidthConcatenate4TensorsKernel.cpp:109</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_aff911654521523937ff24372a870b89f"><div class="ttname"><a href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00163">Validate.h:163</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_width_concatenate2_tensors_kernel_xhtml_afe71126bef1735fe1613a6da30d2c0c4"><div class="ttname"><a href="classarm__compute_1_1_c_l_width_concatenate2_tensors_kernel.xhtml#afe71126bef1735fe1613a6da30d2c0c4">arm_compute::CLWidthConcatenate2TensorsKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLWidthConcatenate2Tenso...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_width_concatenate2_tensors_kernel_8cpp_source.xhtml#l00091">CLWidthConcatenate2TensorsKernel.cpp:91</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_error_8h_source.xhtml#l00244">ARM_COMPUTE_RETURN_ERROR_ON</a>, <a class="el" href="_validate_8h_source.xhtml#l00163">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00193">ARM_COMPUTE_RETURN_ON_ERROR</a>, <a class="el" href="_helpers_8inl_source.xhtml#l00201">arm_compute::auto_init_if_empty()</a>, <a class="el" href="_shape_calculator_8h_source.xhtml#l01184">arm_compute::misc::shape_calculator::calculate_concatenate_shape()</a>, <a class="el" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">ICloneable< T >::clone()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::data_type</a>, <a class="el" href="_window_8h_source.xhtml#l00043">Window::DimX</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::output_shape</a>, <a class="el" href="_c_l_width_concatenate2_tensors_kernel_8cpp_source.xhtml#l00091">CLWidthConcatenate2TensorsKernel::validate()</a>, <a class="el" href="_c_l_width_concatenate_layer_kernel_8cpp_source.xhtml#l00085">CLWidthConcatenateLayerKernel::validate()</a>, and <a class="el" href="_c_l_width_concatenate4_tensors_kernel_8cpp_source.xhtml#l00109">CLWidthConcatenate4TensorsKernel::validate()</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml#l00084">CLWidthConcatenateLayer::configure()</a>, and <a class="el" href="_c_l_l_s_t_m_layer_8cpp_source.xhtml#l00326">CLLSTMLayer::validate()</a>.</p> |
| |
| </div> |
| </div> |
| <hr/>The documentation for this class was generated from the following files:<ul> |
| <li>arm_compute/runtime/CL/functions/<a class="el" href="_c_l_width_concatenate_layer_8h_source.xhtml">CLWidthConcatenateLayer.h</a></li> |
| <li>src/runtime/CL/functions/<a class="el" href="_c_l_width_concatenate_layer_8cpp_source.xhtml">CLWidthConcatenateLayer.cpp</a></li> |
| </ul> |
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