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<a href="#pub-methods">Public Member Functions</a> </div>
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<div class="title">ICLKernel Class Reference<span class="mlabels"><span class="mlabel">abstract</span></span></div> </div>
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<p>Common interface for all the OpenCL kernels.
<a href="classarm__compute_1_1_i_c_l_kernel.xhtml#details">More...</a></p>
<p><code>#include &lt;<a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>&gt;</code></p>
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Collaboration diagram for ICLKernel:</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:a6b10e96ce90bf901d17def86b874b019"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6b10e96ce90bf901d17def86b874b019">ICLKernel</a> ()</td></tr>
<tr class="memdesc:a6b10e96ce90bf901d17def86b874b019"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor. <a href="#a6b10e96ce90bf901d17def86b874b019">More...</a><br/></td></tr>
<tr class="separator:a6b10e96ce90bf901d17def86b874b019"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae5121015ab09ece4d470f50c7ffe198e"><td class="memItemLeft" align="right" valign="top">cl::Kernel &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ae5121015ab09ece4d470f50c7ffe198e">kernel</a> ()</td></tr>
<tr class="memdesc:ae5121015ab09ece4d470f50c7ffe198e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns a reference to the OpenCL kernel of this object. <a href="#ae5121015ab09ece4d470f50c7ffe198e">More...</a><br/></td></tr>
<tr class="separator:ae5121015ab09ece4d470f50c7ffe198e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9331d385192a50adf74d3af40ce0fa20"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a9331d385192a50adf74d3af40ce0fa20"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a9331d385192a50adf74d3af40ce0fa20">add_1D_array_argument</a> (unsigned int &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml">ICLArray</a>&lt; T &gt; *array, const <a class="el" href="classarm__compute_1_1_strides.xhtml">Strides</a> &amp;strides, unsigned int num_dimensions, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:a9331d385192a50adf74d3af40ce0fa20"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed 1D array's parameters to the object's kernel's arguments starting from the index idx. <a href="#a9331d385192a50adf74d3af40ce0fa20">More...</a><br/></td></tr>
<tr class="separator:a9331d385192a50adf74d3af40ce0fa20"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a479e7043e65dc87de35d374e108510f7"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a479e7043e65dc87de35d374e108510f7">add_1D_tensor_argument</a> (unsigned int &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:a479e7043e65dc87de35d374e108510f7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx. <a href="#a479e7043e65dc87de35d374e108510f7">More...</a><br/></td></tr>
<tr class="separator:a479e7043e65dc87de35d374e108510f7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac74dad3e61f79334f5e73f3c3ac603cb"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac74dad3e61f79334f5e73f3c3ac603cb">add_2D_tensor_argument</a> (unsigned int &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:ac74dad3e61f79334f5e73f3c3ac603cb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx. <a href="#ac74dad3e61f79334f5e73f3c3ac603cb">More...</a><br/></td></tr>
<tr class="separator:ac74dad3e61f79334f5e73f3c3ac603cb"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a28f5847162f352444c6ac1825d0e99c7"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a28f5847162f352444c6ac1825d0e99c7">add_3D_tensor_argument</a> (unsigned int &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:a28f5847162f352444c6ac1825d0e99c7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx. <a href="#a28f5847162f352444c6ac1825d0e99c7">More...</a><br/></td></tr>
<tr class="separator:a28f5847162f352444c6ac1825d0e99c7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a33e09c946b338fbfc780a9d1c66e68ad"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a33e09c946b338fbfc780a9d1c66e68ad">add_4D_tensor_argument</a> (unsigned int &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
<tr class="memdesc:a33e09c946b338fbfc780a9d1c66e68ad"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx. <a href="#a33e09c946b338fbfc780a9d1c66e68ad">More...</a><br/></td></tr>
<tr class="separator:a33e09c946b338fbfc780a9d1c66e68ad"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a99fde125501fae43952af222c91236cd"><td class="memItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a99fde125501fae43952af222c91236cd">num_arguments_per_1D_array</a> () const </td></tr>
<tr class="memdesc:a99fde125501fae43952af222c91236cd"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of arguments enqueued per 1D array object. <a href="#a99fde125501fae43952af222c91236cd">More...</a><br/></td></tr>
<tr class="separator:a99fde125501fae43952af222c91236cd"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a770f45838881fc061294e56d64f34386"><td class="memItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a770f45838881fc061294e56d64f34386">num_arguments_per_1D_tensor</a> () const </td></tr>
<tr class="memdesc:a770f45838881fc061294e56d64f34386"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of arguments enqueued per 1D tensor object. <a href="#a770f45838881fc061294e56d64f34386">More...</a><br/></td></tr>
<tr class="separator:a770f45838881fc061294e56d64f34386"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac734502531e7f95e25b3bf688a304a59"><td class="memItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac734502531e7f95e25b3bf688a304a59">num_arguments_per_2D_tensor</a> () const </td></tr>
<tr class="memdesc:ac734502531e7f95e25b3bf688a304a59"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of arguments enqueued per 2D tensor object. <a href="#ac734502531e7f95e25b3bf688a304a59">More...</a><br/></td></tr>
<tr class="separator:ac734502531e7f95e25b3bf688a304a59"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4feaae9c860cddfa843d37c953674a22"><td class="memItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a4feaae9c860cddfa843d37c953674a22">num_arguments_per_3D_tensor</a> () const </td></tr>
<tr class="memdesc:a4feaae9c860cddfa843d37c953674a22"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of arguments enqueued per 3D tensor object. <a href="#a4feaae9c860cddfa843d37c953674a22">More...</a><br/></td></tr>
<tr class="separator:a4feaae9c860cddfa843d37c953674a22"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af24df23a978e1a46ff6714e9b9d3eef9"><td class="memItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#af24df23a978e1a46ff6714e9b9d3eef9">num_arguments_per_4D_tensor</a> () const </td></tr>
<tr class="memdesc:af24df23a978e1a46ff6714e9b9d3eef9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Returns the number of arguments enqueued per 4D tensor object. <a href="#af24df23a978e1a46ff6714e9b9d3eef9">More...</a><br/></td></tr>
<tr class="separator:af24df23a978e1a46ff6714e9b9d3eef9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af6a174d47571f51f199ffc27ecc10f51"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#af6a174d47571f51f199ffc27ecc10f51">run</a> (const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>, cl::CommandQueue &amp;queue)=0</td></tr>
<tr class="memdesc:af6a174d47571f51f199ffc27ecc10f51"><td class="mdescLeft">&#160;</td><td class="mdescRight">Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue. <a href="#af6a174d47571f51f199ffc27ecc10f51">More...</a><br/></td></tr>
<tr class="separator:af6a174d47571f51f199ffc27ecc10f51"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a50f427a1d9419800972b9e03c4034311"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a50f427a1d9419800972b9e03c4034311"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a50f427a1d9419800972b9e03c4034311">add_argument</a> (unsigned int &amp;idx, T <a class="el" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>)</td></tr>
<tr class="memdesc:a50f427a1d9419800972b9e03c4034311"><td class="mdescLeft">&#160;</td><td class="mdescRight">Add the passed parameters to the object's kernel's arguments starting from the index idx. <a href="#a50f427a1d9419800972b9e03c4034311">More...</a><br/></td></tr>
<tr class="separator:a50f427a1d9419800972b9e03c4034311"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a44c701b9dbd01a171de4928254d1ecbf"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a44c701b9dbd01a171de4928254d1ecbf">set_lws_hint</a> (cl::NDRange &amp;lws_hint)</td></tr>
<tr class="memdesc:a44c701b9dbd01a171de4928254d1ecbf"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the Local-Workgroup-Size hint. <a href="#a44c701b9dbd01a171de4928254d1ecbf">More...</a><br/></td></tr>
<tr class="separator:a44c701b9dbd01a171de4928254d1ecbf"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a226d2e9e6d3c42d681666566fe950b2d"><td class="memItemLeft" align="right" valign="top">const std::string &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a226d2e9e6d3c42d681666566fe950b2d">config_id</a> () const </td></tr>
<tr class="memdesc:a226d2e9e6d3c42d681666566fe950b2d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the configuration ID. <a href="#a226d2e9e6d3c42d681666566fe950b2d">More...</a><br/></td></tr>
<tr class="separator:a226d2e9e6d3c42d681666566fe950b2d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad5ba9d34a3a855bf1dd2e36316ff550a"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ad5ba9d34a3a855bf1dd2e36316ff550a">set_target</a> (<a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> target)</td></tr>
<tr class="memdesc:ad5ba9d34a3a855bf1dd2e36316ff550a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the targeted GPU architecture. <a href="#ad5ba9d34a3a855bf1dd2e36316ff550a">More...</a><br/></td></tr>
<tr class="separator:ad5ba9d34a3a855bf1dd2e36316ff550a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a57e5f498fcbfc25c28b8496dfa3fc33c"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a57e5f498fcbfc25c28b8496dfa3fc33c">set_target</a> (cl::Device &amp;device)</td></tr>
<tr class="memdesc:a57e5f498fcbfc25c28b8496dfa3fc33c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the targeted GPU architecture according to the CL device. <a href="#a57e5f498fcbfc25c28b8496dfa3fc33c">More...</a><br/></td></tr>
<tr class="separator:a57e5f498fcbfc25c28b8496dfa3fc33c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a646cd535a16835b246c3367a63d96250"><td class="memItemLeft" align="right" valign="top"><a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a646cd535a16835b246c3367a63d96250">get_target</a> () const </td></tr>
<tr class="memdesc:a646cd535a16835b246c3367a63d96250"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the targeted GPU architecture. <a href="#a646cd535a16835b246c3367a63d96250">More...</a><br/></td></tr>
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<tr class="memitem:abca336f832d730e8494049bd714df60a"><td class="memItemLeft" align="right" valign="top">size_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#abca336f832d730e8494049bd714df60a">get_max_workgroup_size</a> ()</td></tr>
<tr class="memdesc:abca336f832d730e8494049bd714df60a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the maximum workgroup size for the device the <a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml" title="CLKernelLibrary class. ">CLKernelLibrary</a> uses. <a href="#abca336f832d730e8494049bd714df60a">More...</a><br/></td></tr>
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<tr class="memitem:a2d7c6b5f3332604ad6a637457f65c342"><td class="memTemplParams" colspan="2">template&lt;typename T , unsigned int dimension_size&gt; </td></tr>
<tr class="memitem:a2d7c6b5f3332604ad6a637457f65c342"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a2d7c6b5f3332604ad6a637457f65c342">add_array_argument</a> (unsigned &amp;idx, const <a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml">ICLArray</a>&lt; T &gt; *array, const <a class="el" href="classarm__compute_1_1_strides.xhtml">Strides</a> &amp;strides, unsigned int num_dimensions, const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;<a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>)</td></tr>
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<tr class="inherit_header pub_methods_classarm__compute_1_1_i_kernel"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_kernel')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_kernel.xhtml">IKernel</a></td></tr>
<tr class="memitem:a7250cb8cbaa4104a93a2d77155085507 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a7250cb8cbaa4104a93a2d77155085507">IKernel</a> ()</td></tr>
<tr class="memdesc:a7250cb8cbaa4104a93a2d77155085507 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor. <a href="#a7250cb8cbaa4104a93a2d77155085507">More...</a><br/></td></tr>
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<tr class="memitem:a341b60d15a5e12a5b8f3825194dd3b12 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a341b60d15a5e12a5b8f3825194dd3b12">~IKernel</a> ()=default</td></tr>
<tr class="memdesc:a341b60d15a5e12a5b8f3825194dd3b12 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <a href="#a341b60d15a5e12a5b8f3825194dd3b12">More...</a><br/></td></tr>
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<tr class="memitem:abfab8f0d4928e1081d9f65b77933e24a inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">virtual bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#abfab8f0d4928e1081d9f65b77933e24a">is_parallelisable</a> () const </td></tr>
<tr class="memdesc:abfab8f0d4928e1081d9f65b77933e24a inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">Indicates whether or not the kernel is parallelisable. <a href="#abfab8f0d4928e1081d9f65b77933e24a">More...</a><br/></td></tr>
<tr class="separator:abfab8f0d4928e1081d9f65b77933e24a inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa6daa9b04e2035bf007e5e5c3c4396a8 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">virtual <a class="el" href="structarm__compute_1_1_border_size.xhtml">BorderSize</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#aa6daa9b04e2035bf007e5e5c3c4396a8">border_size</a> () const </td></tr>
<tr class="memdesc:aa6daa9b04e2035bf007e5e5c3c4396a8 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">The size of the border for that kernel. <a href="#aa6daa9b04e2035bf007e5e5c3c4396a8">More...</a><br/></td></tr>
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<tr class="memitem:a3f5646133956f06348b310ccc3d36353 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a> () const </td></tr>
<tr class="memdesc:a3f5646133956f06348b310ccc3d36353 inherit pub_methods_classarm__compute_1_1_i_kernel"><td class="mdescLeft">&#160;</td><td class="mdescRight">The maximum window the kernel can be executed on. <a href="#a3f5646133956f06348b310ccc3d36353">More...</a><br/></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Common interface for all the OpenCL kernels. </p>
<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00042">42</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
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<td class="memname"><a class="el" href="classarm__compute_1_1_i_c_l_kernel.xhtml">ICLKernel</a> </td>
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<p>Constructor. </p>
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<h2 class="groupheader">Member Function Documentation</h2>
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<td class="memname">void add_1D_array_argument </td>
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<td class="paramtype">unsigned int &amp;&#160;</td>
<td class="paramname"><em>idx</em>, </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml">ICLArray</a>&lt; T &gt; *&#160;</td>
<td class="paramname"><em>array</em>, </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_strides.xhtml">Strides</a> &amp;&#160;</td>
<td class="paramname"><em>strides</em>, </td>
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<td class="paramtype">unsigned int&#160;</td>
<td class="paramname"><em>num_dimensions</em>, </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td>
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<p>Add the passed 1D array's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the array's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">array</td><td><a class="el" href="classarm__compute_1_1_array.xhtml" title="Basic implementation of the IArray interface which allocates a static number of T values...">Array</a> to set as an argument of the object's kernel. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">strides</td><td><a class="el" href="classarm__compute_1_1_strides.xhtml">Strides</a> object containing stride of each dimension in bytes. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">num_dimensions</td><td>Number of dimensions of the <code>array</code>. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00267">267</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<p>References <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">IKernel::window()</a>.</p>
<div class="fragment"><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160;{</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; add_array_argument&lt;T, 1&gt;(idx, array, strides, num_dimensions, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>);</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160;}</div>
<div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_a3f5646133956f06348b310ccc3d36353"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window &amp; window() const </div><div class="ttdoc">The maximum window the kernel can be executed on. </div></div>
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<td class="memname">void add_1D_tensor_argument </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td>
<td class="paramname"><em>window</em>&#160;</td>
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<p>Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">tensor</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> to set as an argument of the object's kernel. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<td class="memname">void add_2D_tensor_argument </td>
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<td class="paramtype">unsigned int &amp;&#160;</td>
<td class="paramname"><em>idx</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
<td class="paramname"><em>tensor</em>, </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td>
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<p>Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">tensor</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> to set as an argument of the object's kernel. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<td class="memname">void add_3D_tensor_argument </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
<td class="paramname"><em>tensor</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td>
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<p>Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">tensor</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> to set as an argument of the object's kernel. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<td class="memname">void add_4D_tensor_argument </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *&#160;</td>
<td class="paramname"><em>tensor</em>, </td>
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<td></td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td>
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<p>Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">tensor</td><td><a class="el" href="classarm__compute_1_1_tensor.xhtml" title="Basic implementation of the tensor interface. ">Tensor</a> to set as an argument of the object's kernel. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">window</td><td><a class="el" href="classarm__compute_1_1_window.xhtml" title="Describe a multidimensional execution window. ">Window</a> the kernel will be executed on. </td></tr>
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<td class="memname">void add_argument </td>
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<p>Add the passed parameters to the object's kernel's arguments starting from the index idx. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in,out]</td><td class="paramname">idx</td><td>Index at which to start adding the arguments. Will be incremented by the number of kernel arguments set. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">value</td><td>Value to set as an argument of the object's kernel. </td></tr>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00129">129</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; {</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; _kernel.setArg(idx++, <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>);</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; }</div>
<div class="ttc" id="hwc_8hpp_xhtml_a0f61d63b009d0880a89c843bd50d8d76"><div class="ttname"><a href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a></div><div class="ttdeci">void * value</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00269">hwc.hpp:269</a></div></div>
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<td class="memname">void add_array_argument </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml">ICLArray</a>&lt; T &gt; *&#160;</td>
<td class="paramname"><em>array</em>, </td>
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<td class="paramtype">const <a class="el" href="classarm__compute_1_1_strides.xhtml">Strides</a> &amp;&#160;</td>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00240">240</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<p>References <a class="el" href="_error_8h_source.xhtml#l00115">ARM_COMPUTE_ERROR_ON_MSG</a>, <a class="el" href="_error_8h_source.xhtml#l00049">ARM_COMPUTE_UNUSED</a>, and <a class="el" href="classarm__compute_1_1_i_c_l_array.xhtml#a1fb4c50755a0ef424652246838ed91a6">ICLArray&lt; T &gt;::cl_buffer()</a>.</p>
<div class="fragment"><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160;{</div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; <span class="comment">// Calculate offset to the start of the window</span></div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> offset_first_element = 0;</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160;</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 0; n &lt; num_dimensions; ++n)</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; {</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; offset_first_element += <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>[n].start() * strides[n];</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; }</div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160;</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx_start = idx;</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; _kernel.setArg(idx++, array-&gt;cl_buffer());</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160;</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimension = 0; dimension &lt; dimension_size; dimension++)</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; {</div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; _kernel.setArg&lt;cl_uint&gt;(idx++, strides[dimension]);</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; _kernel.setArg&lt;cl_uint&gt;(idx++, strides[dimension] * <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">window</a>[dimension].step());</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; }</div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160;</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; _kernel.setArg&lt;cl_uint&gt;(idx++, offset_first_element);</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160;</div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(idx_start + num_arguments_per_array&lt;dimension_size&gt;() != idx,</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; <span class="stringliteral">&quot;add_%dD_array_argument() is supposed to add exactly %d arguments to the kernel&quot;</span>, dimension_size, num_arguments_per_array&lt;dimension_size&gt;());</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; <a class="code" href="_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a>(idx_start);</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160;}</div>
<div class="ttc" id="_error_8h_xhtml_a4103adbb45806b2f2002d44b91d0d206"><div class="ttname"><a href="_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(var)</div><div class="ttdoc">To avoid unused variables warnings. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00049">Error.h:49</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_a3f5646133956f06348b310ccc3d36353"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window &amp; window() const </div><div class="ttdoc">The maximum window the kernel can be executed on. </div></div>
<div class="ttc" id="_error_8h_xhtml_a5bbdcf574d3f5e412fa6a1117911e67b"><div class="ttname"><a href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond,...)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00115">Error.h:115</a></div></div>
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<p>Get the configuration ID. </p>
<dl class="section note"><dt>Note</dt><dd>The configuration ID can be used by the caller to distinguish different calls of the same OpenCL kernel In particular, this method can be used by <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> to keep track of the best LWS for each configuration of the same kernel. The configuration ID should be provided only for the kernels potentially affected by the LWS geometry</dd>
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This method should be called after the configuration of the kernel</dd></dl>
<dl class="section return"><dt>Returns</dt><dd>configuration id string </dd></dl>
<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00155">155</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; {</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; <span class="keywordflow">return</span> _config_id;</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; }</div>
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<td class="memname">size_t get_max_workgroup_size </td>
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<p>Get the maximum workgroup size for the device the <a class="el" href="classarm__compute_1_1_c_l_kernel_library.xhtml" title="CLKernelLibrary class. ">CLKernelLibrary</a> uses. </p>
<dl class="section return"><dt>Returns</dt><dd>The maximum workgroup size value. </dd></dl>
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<td class="memname"><a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> get_target </td>
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<p>Get the targeted GPU architecture. </p>
<dl class="section return"><dt>Returns</dt><dd>The targeted GPU architecture. </dd></dl>
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<td class="memname">cl::Kernel&amp; kernel </td>
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<p>Returns a reference to the OpenCL kernel of this object. </p>
<dl class="section return"><dt>Returns</dt><dd>A reference to the OpenCL kernel of this object. </dd></dl>
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<td class="memname">unsigned int num_arguments_per_1D_array </td>
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<p>Returns the number of arguments enqueued per 1D array object. </p>
<dl class="section return"><dt>Returns</dt><dd>The number of arguments enqueues per 1D array object. </dd></dl>
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<td class="memname">unsigned int num_arguments_per_1D_tensor </td>
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<p>Returns the number of arguments enqueued per 1D tensor object. </p>
<dl class="section return"><dt>Returns</dt><dd>The number of arguments enqueues per 1D tensor object. </dd></dl>
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<td class="memname">unsigned int num_arguments_per_2D_tensor </td>
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<p>Returns the number of arguments enqueued per 2D tensor object. </p>
<dl class="section return"><dt>Returns</dt><dd>The number of arguments enqueues per 2D tensor object. </dd></dl>
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<p>Returns the number of arguments enqueued per 3D tensor object. </p>
<dl class="section return"><dt>Returns</dt><dd>The number of arguments enqueues per 3D tensor object. </dd></dl>
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<td class="memname">unsigned int num_arguments_per_4D_tensor </td>
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<p>Returns the number of arguments enqueued per 4D tensor object. </p>
<dl class="section return"><dt>Returns</dt><dd>The number of arguments enqueues per 4D tensor object. </dd></dl>
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<td class="memname">virtual void run </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_window.xhtml">Window</a> &amp;&#160;</td>
<td class="paramname"><em>window</em>, </td>
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<td class="paramtype">cl::CommandQueue &amp;&#160;</td>
<td class="paramname"><em>queue</em>&#160;</td>
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<p>Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue. </p>
<dl class="section note"><dt>Note</dt><dd>The queue is <em>not</em> flushed by this method, and therefore the kernel will not have been executed by the time this method returns.</dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
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<tr><td class="paramdir">[in]</td><td class="paramname">window</td><td>Region on which to execute the kernel. (Must be a valid region of the window returned by <a class="el" href="classarm__compute_1_1_i_kernel.xhtml#a3f5646133956f06348b310ccc3d36353" title="The maximum window the kernel can be executed on. ">window()</a>). </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">queue</td><td>Command queue on which to enqueue the kernel. </td></tr>
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<p>Implemented in <a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_stage1_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLKTrackerStage1Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_convolution_rectangle_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLConvolutionRectangleKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_stage0_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLKTrackerStage0Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_edge_trace_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLEdgeTraceKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_copy_to_array_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLCopyToArrayKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_finalize_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLKTrackerFinalizeKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_sobel5x5_vert_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLSobel5x5VertKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_sobel7x7_vert_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLSobel7x7VertKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_logits1_d_norm_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLogits1DNormKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_h_o_g_block_normalization_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLHOGBlockNormalizationKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_min_max_location_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLMinMaxLocationKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_edge_non_max_suppression_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLEdgeNonMaxSuppressionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_vert_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGaussianPyramidVertKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_histogram_border_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLHistogramBorderKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_l_k_tracker_init_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLKTrackerInitKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_im2_col_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLIm2ColKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_color_convert_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLColorConvertKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_transpose1x_w_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMTranspose1xWKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_col2_im_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLCol2ImKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_scharr3x3_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLScharr3x3Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_direct_convolution_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDirectConvolutionLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_channel_combine_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLChannelCombineKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_interleave4x4_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMInterleave4x4Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_lowp_matrix_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMLowpMatrixMultiplyKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_h_o_g_detector_kernel.xhtml#ac8f1ca778b425c6408a93b672b041dd0">CLHOGDetectorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_harris_score_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLHarrisScoreKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_fast_corners_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLFastCornersKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_channel_extract_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLChannelExtractKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_fill_border_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLFillBorderKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_logits1_d_shift_exp_sum_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLogits1DShiftExpSumKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_batch_normalization_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLBatchNormalizationLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_integral_image_vert_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLIntegralImageVertKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_r_o_i_pooling_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLROIPoolingLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_arithmetic_subtraction_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLArithmeticSubtractionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depth_concatenate_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthConcatenateKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMMatrixMultiplyKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_magnitude_phase_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLMagnitudePhaseKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_arithmetic_addition_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLArithmeticAdditionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_mean_std_dev_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLMeanStdDevKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_pixel_wise_multiplication_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLPixelWiseMultiplicationKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_absolute_difference_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLAbsoluteDifferenceKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_im2_col_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthwiseIm2ColKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_vector_to_tensor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthwiseVectorToTensorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDequantizationLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_min_max_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLMinMaxLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_addition_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMMatrixAdditionKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_h_o_g_orientation_binning_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLHOGOrientationBinningKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_l2_normalize_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLL2NormalizeKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_quantization_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLQuantizationLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_sobel5x5_hor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLSobel5x5HorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_sobel7x7_hor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLSobel7x7HorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_activation_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLActivationLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_derivative_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDerivativeKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_pooling_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLPoolingLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_reduction_operation_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLReductionOperationKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_sobel3x3_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLSobel3x3Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_bitwise_and_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLBitwiseAndKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_bitwise_or_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLBitwiseOrKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_bitwise_xor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLBitwiseXorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_locally_connected_matrix_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLLocallyConnectedMatrixMultiplyKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_min_max_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLMinMaxKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_remap_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLRemapKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_gradient_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGradientKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_weights_reshape_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthwiseWeightsReshapeKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_gaussian_pyramid_hor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGaussianPyramidHorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_histogram_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLHistogramKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_normalization_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLNormalizationLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_depthwise_convolution3x3_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLDepthwiseConvolution3x3Kernel</a>, <a class="el" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLReshapeLayerKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_weights_reshape_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLWeightsReshapeKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_floor_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLFloorKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_vector_multiply_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMMatrixVectorMultiplyKernel</a>, <a class="el" href="classarm__compute_1_1_c_l_g_e_m_m_matrix_accumulate_biases_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">CLGEMMMatrixAccumulateBiasesKernel</a>, <a class="el" href="classarm__compute_1_1_i_c_l_simple3_d_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">ICLSimple3DKernel</a>, and <a class="el" href="classarm__compute_1_1_i_c_l_simple2_d_kernel.xhtml#a493987e85723a8000eb26d1f00e2ad0e">ICLSimple2DKernel</a>.</p>
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<td class="memname">void set_lws_hint </td>
<td>(</td>
<td class="paramtype">cl::NDRange &amp;&#160;</td>
<td class="paramname"><em>lws_hint</em></td><td>)</td>
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<p>Set the Local-Workgroup-Size hint. </p>
<dl class="section note"><dt>Note</dt><dd>This method should be called after the configuration of the kernel</dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
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<tr><td class="paramdir">[in]</td><td class="paramname">lws_hint</td><td>Local-Workgroup-Size to use </td></tr>
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<p>Definition at line <a class="el" href="_i_c_l_kernel_8h_source.xhtml#l00140">140</a> of file <a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a>.</p>
<div class="fragment"><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; {</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; _lws_hint = lws_hint;</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; }</div>
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<td class="memname">void set_target </td>
<td>(</td>
<td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a>&#160;</td>
<td class="paramname"><em>target</em></td><td>)</td>
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<p>Set the targeted GPU architecture. </p>
<dl class="params"><dt>Parameters</dt><dd>
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<tr><td class="paramdir">[in]</td><td class="paramname">target</td><td>The targeted GPU architecture </td></tr>
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<td class="memname">void set_target </td>
<td>(</td>
<td class="paramtype">cl::Device &amp;&#160;</td>
<td class="paramname"><em>device</em></td><td>)</td>
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<p>Set the targeted GPU architecture according to the CL device. </p>
<dl class="params"><dt>Parameters</dt><dd>
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<tr><td class="paramdir">[in]</td><td class="paramname">device</td><td>A CL device </td></tr>
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<hr/>The documentation for this class was generated from the following file:<ul>
<li>arm_compute/core/CL/<a class="el" href="_i_c_l_kernel_8h_source.xhtml">ICLKernel.h</a></li>
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