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| <a href="_i_c_l_kernel_8h.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2016-2019 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * of this software and associated documentation files (the "Software"), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#ifndef ARM_COMPUTE_ICLKERNEL_H</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define ARM_COMPUTE_ICLKERNEL_H</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="_c_l_kernel_library_8h.xhtml">arm_compute/core/CL/CLKernelLibrary.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_c_l_types_8h.xhtml">arm_compute/core/CL/CLTypes.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="_open_c_l_8h.xhtml">arm_compute/core/CL/OpenCL.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_g_p_u_target_8h.xhtml">arm_compute/core/GPUTarget.h</a>"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="_i_kernel_8h.xhtml">arm_compute/core/IKernel.h</a>"</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="keyword">class </span>ICLArray;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="keyword">class </span>ICLTensor;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="keyword">class </span>Window;</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment"></span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="comment">/** Common interface for all the OpenCL kernels */</span></div><div class="line"><a name="l00043"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml"> 43</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml">ICLKernel</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1_i_kernel.xhtml">IKernel</a></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> {</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">private</span>:<span class="comment"></span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="comment"> /** Returns the number of arguments enqueued per array object.</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"> *</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="comment"> * @return The number of arguments enqueued per array object.</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="comment"> */</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="keyword">template</span> <<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimension_size></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_arguments_per_array()</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keywordflow">return</span> num_arguments_per_tensor<dimension_size>();</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  }<span class="comment"></span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="comment"> /** Returns the number of arguments enqueued per tensor object.</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"> *</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> * @return The number of arguments enqueued per tensor object.</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"> */</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">template</span> <<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimension_size></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_arguments_per_tensor()</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  {</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keywordflow">return</span> 2 + 2 * dimension_size;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keyword">using</span> IKernel::configure; <span class="comment">//Prevent children from calling IKernel::configure() directly</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="keyword">protected</span>:<span class="comment"></span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="comment"> /** Configure the kernel's window and local workgroup size hint.</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="comment"> *</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="comment"> * @param[in] window The maximum window which will be returned by window()</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="comment"> * @param[in] lws_hint (Optional) Local-Workgroup-Size to use.</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="comment"> */</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordtype">void</span> configure_internal(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, cl::NDRange <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55">lws_hint</a> = <a class="code" href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">CLKernelLibrary::get</a>().default_ndrange())</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  _lws_hint = <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55">lws_hint</a>;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  IKernel::configure(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  }</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="comment"> /** Constructor */</span></div><div class="line"><a name="l00079"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6b10e96ce90bf901d17def86b874b019"> 79</a></span>  <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6b10e96ce90bf901d17def86b874b019">ICLKernel</a>()</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  : _kernel(nullptr), _target(<a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a>::<a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afa362f4daec88442a387ff7cda411a38">MIDGARD</a>), _config_id(<a class="code" href="namespacearm__compute.xhtml">arm_compute</a>::default_config_id), _max_workgroup_size(0), _lws_hint()</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  {</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  }<span class="comment"></span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="comment"> /** Returns a reference to the OpenCL kernel of this object.</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="comment"> *</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="comment"> * @return A reference to the OpenCL kernel of this object.</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="comment"> */</span></div><div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ae5121015ab09ece4d470f50c7ffe198e"> 87</a></span>  cl::Kernel &<a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ae5121015ab09ece4d470f50c7ffe198e">kernel</a>()</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  {</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordflow">return</span> _kernel;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  }<span class="comment"></span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="comment"> /** Add the passed 1D array's parameters to the object's kernel's arguments starting from the index idx.</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="comment"> *</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the array's arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="comment"> * @param[in] array Array to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="comment"> * @param[in] strides @ref Strides object containing stride of each dimension in bytes.</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="comment"> * @param[in] num_dimensions Number of dimensions of the @p array.</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="comment"> * @param[in] window Window the kernel will be executed on.</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="comment"> */</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00100"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a9331d385192a50adf74d3af40ce0fa20"> 100</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a9331d385192a50adf74d3af40ce0fa20">add_1D_array_argument</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &idx, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_array.xhtml">ICLArray<T></a> *array, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> &strides, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_dimensions, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>)</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>  add_array_argument<T, 1>(idx, array, strides, num_dimensions, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  }<span class="comment"></span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="comment"> /** Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx.</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="comment"> *</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="comment"> * @param[in] tensor Tensor to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="comment"> * @param[in] window Window the kernel will be executed on.</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="comment"> */</span></div><div class="line"><a name="l00110"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a479e7043e65dc87de35d374e108510f7"> 110</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a479e7043e65dc87de35d374e108510f7">add_1D_tensor_argument</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &idx, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>)</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  {</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  add_tensor_argument<1>(idx, tensor, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  }<span class="comment"></span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="comment"> /** Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx if the condition is true.</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment"> *</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="comment"> * @param[in] cond Condition to check</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="comment"> * @param[in] tensor Tensor to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="comment"> * @param[in] window Window the kernel will be executed on.</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="comment"> */</span></div><div class="line"><a name="l00121"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a25965a58d98e44856da286925792a2f7"> 121</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a25965a58d98e44856da286925792a2f7">add_1D_tensor_argument_if</a>(<span class="keywordtype">bool</span> cond, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &idx, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>)</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">if</span>(cond)</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  {</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a479e7043e65dc87de35d374e108510f7">add_1D_tensor_argument</a>(idx, tensor, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  }</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  }<span class="comment"></span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="comment"> /** Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx.</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="comment"> *</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="comment"> * @param[in] tensor Tensor to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="comment"> * @param[in] window Window the kernel will be executed on.</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="comment"> */</span></div><div class="line"><a name="l00134"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac74dad3e61f79334f5e73f3c3ac603cb"> 134</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac74dad3e61f79334f5e73f3c3ac603cb">add_2D_tensor_argument</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &idx, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>)</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  add_tensor_argument<2>(idx, tensor, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  }<span class="comment"></span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="comment"> /** Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx if the condition is true.</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="comment"> *</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="comment"> * @param[in] cond Condition to check</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment"> * @param[in] tensor Tensor to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment"> * @param[in] window Window the kernel will be executed on.</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="comment"> */</span></div><div class="line"><a name="l00145"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a2ada6044648832c64532588f75303b44"> 145</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a2ada6044648832c64532588f75303b44">add_2D_tensor_argument_if</a>(<span class="keywordtype">bool</span> cond, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &idx, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>)</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  {</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keywordflow">if</span>(cond)</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  {</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac74dad3e61f79334f5e73f3c3ac603cb">add_2D_tensor_argument</a>(idx, tensor, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  }</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  }<span class="comment"></span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="comment"> /** Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx.</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> <span class="comment"> *</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="comment"> * @param[in] tensor Tensor to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="comment"> * @param[in] window Window the kernel will be executed on.</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="comment"> */</span></div><div class="line"><a name="l00158"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a28f5847162f352444c6ac1825d0e99c7"> 158</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a28f5847162f352444c6ac1825d0e99c7">add_3D_tensor_argument</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &idx, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>)</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  {</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  add_tensor_argument<3>(idx, tensor, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  }<span class="comment"></span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="comment"> /** Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx.</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> <span class="comment"> *</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> <span class="comment"> * @param[in] tensor Tensor to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> <span class="comment"> * @param[in] window Window the kernel will be executed on.</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> <span class="comment"> */</span></div><div class="line"><a name="l00168"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a33e09c946b338fbfc780a9d1c66e68ad"> 168</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a33e09c946b338fbfc780a9d1c66e68ad">add_4D_tensor_argument</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &idx, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>)</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  {</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  add_tensor_argument<4>(idx, tensor, <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  }<span class="comment"></span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> <span class="comment"> /** Returns the number of arguments enqueued per 1D array object.</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> <span class="comment"> *</span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> <span class="comment"> * @return The number of arguments enqueues per 1D array object.</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> <span class="comment"> */</span></div><div class="line"><a name="l00176"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a278f0e6c68ca17e71f4c4ff82f360aa0"> 176</a></span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a278f0e6c68ca17e71f4c4ff82f360aa0">num_arguments_per_1D_array</a>()</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  {</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordflow">return</span> num_arguments_per_array<1>();</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  }<span class="comment"></span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> <span class="comment"> /** Returns the number of arguments enqueued per 1D tensor object.</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> <span class="comment"> *</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> <span class="comment"> * @return The number of arguments enqueues per 1D tensor object.</span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> <span class="comment"> */</span></div><div class="line"><a name="l00184"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a43b6c5e4b57069c5f61e96dff24c212d"> 184</a></span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a43b6c5e4b57069c5f61e96dff24c212d">num_arguments_per_1D_tensor</a>()</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  {</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="keywordflow">return</span> num_arguments_per_tensor<1>();</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  }<span class="comment"></span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> <span class="comment"> /** Returns the number of arguments enqueued per 2D tensor object.</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> <span class="comment"> *</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> <span class="comment"> * @return The number of arguments enqueues per 2D tensor object.</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="comment"> */</span></div><div class="line"><a name="l00192"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a45601e0d46621a5b6f2e417d60e5c800"> 192</a></span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a45601e0d46621a5b6f2e417d60e5c800">num_arguments_per_2D_tensor</a>()</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  {</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordflow">return</span> num_arguments_per_tensor<2>();</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  }<span class="comment"></span></div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> <span class="comment"> /** Returns the number of arguments enqueued per 3D tensor object.</span></div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> <span class="comment"> *</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> <span class="comment"> * @return The number of arguments enqueues per 3D tensor object.</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> <span class="comment"> */</span></div><div class="line"><a name="l00200"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c9c1e7a7d96743375ca40847f0f12e2"> 200</a></span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c9c1e7a7d96743375ca40847f0f12e2">num_arguments_per_3D_tensor</a>()</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  {</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">return</span> num_arguments_per_tensor<3>();</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  }<span class="comment"></span></div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> <span class="comment"> /** Returns the number of arguments enqueued per 4D tensor object.</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> <span class="comment"> *</span></div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> <span class="comment"> * @return The number of arguments enqueues per 4D tensor object.</span></div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> <span class="comment"> */</span></div><div class="line"><a name="l00208"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a184fdf37587a9314cf12623accea6c73"> 208</a></span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a184fdf37587a9314cf12623accea6c73">num_arguments_per_4D_tensor</a>()</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  {</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">return</span> num_arguments_per_tensor<4>();</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  }<span class="comment"></span></div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> <span class="comment"> /** Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> <span class="comment"> *</span></div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> <span class="comment"> * @note The queue is *not* flushed by this method, and therefore the kernel will not have been executed by the time this method returns.</span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> <span class="comment"> *</span></div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> <span class="comment"> * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> <span class="comment"> * @param[in,out] queue Command queue on which to enqueue the kernel.</span></div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> <span class="comment"> */</span></div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#af6a174d47571f51f199ffc27ecc10f51">run</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, cl::CommandQueue &queue) = 0;<span class="comment"></span></div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> <span class="comment"> /** Add the passed parameters to the object's kernel's arguments starting from the index idx.</span></div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> <span class="comment"> *</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="comment"> * @param[in] value Value to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> <span class="comment"> */</span></div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00226"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a50f427a1d9419800972b9e03c4034311"> 226</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a50f427a1d9419800972b9e03c4034311">add_argument</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &idx, T value)</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  {</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  _kernel.setArg(idx++, value);</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  }</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <span class="comment"></span></div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> <span class="comment"> /** Set the Local-Workgroup-Size hint</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> <span class="comment"> *</span></div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> <span class="comment"> * @note This method should be called after the configuration of the kernel</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> <span class="comment"> *</span></div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> <span class="comment"> * @param[in] lws_hint Local-Workgroup-Size to use</span></div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> <span class="comment"> */</span></div><div class="line"><a name="l00237"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ad356b88c8f61267d593d9ed99835bde9"> 237</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ad356b88c8f61267d593d9ed99835bde9">set_lws_hint</a>(<span class="keyword">const</span> cl::NDRange &<a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55">lws_hint</a>)</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  {</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <a class="code" href="_validate_8h.xhtml#a1b35b0d258183cf9ef36adf684d0b88c">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a>(<span class="keyword">this</span>); <span class="comment">// lws_hint will be overwritten by configure()</span></div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  _lws_hint = <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55">lws_hint</a>;</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  }</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> <span class="comment"></span></div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> <span class="comment"> /** Return the Local-Workgroup-Size hint</span></div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> <span class="comment"> *</span></div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> <span class="comment"> * @return Current lws hint</span></div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> <span class="comment"> */</span></div><div class="line"><a name="l00247"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55"> 247</a></span>  cl::NDRange <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55">lws_hint</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordflow">return</span> _lws_hint;</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  }</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <span class="comment"></span></div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> <span class="comment"> /** Get the configuration ID</span></div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> <span class="comment"> *</span></div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> <span class="comment"> * @note The configuration ID can be used by the caller to distinguish different calls of the same OpenCL kernel</span></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> <span class="comment"> * In particular, this method can be used by CLScheduler to keep track of the best LWS for each configuration of the same kernel.</span></div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> <span class="comment"> * The configuration ID should be provided only for the kernels potentially affected by the LWS geometry</span></div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> <span class="comment"> *</span></div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> <span class="comment"> * @note This method should be called after the configuration of the kernel</span></div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> <span class="comment"> *</span></div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> <span class="comment"> * @return configuration id string</span></div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> <span class="comment"> */</span></div><div class="line"><a name="l00262"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a8f7f6ab59fc0e601d750b83e75a398eb"> 262</a></span>  <span class="keyword">const</span> std::string &<a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a8f7f6ab59fc0e601d750b83e75a398eb">config_id</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">return</span> _config_id;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  }</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> <span class="comment"></span></div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> <span class="comment"> /** Set the targeted GPU architecture</span></div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> <span class="comment"> *</span></div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> <span class="comment"> * @param[in] target The targeted GPU architecture</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> <span class="comment"> */</span></div><div class="line"><a name="l00271"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ad5ba9d34a3a855bf1dd2e36316ff550a"> 271</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ad5ba9d34a3a855bf1dd2e36316ff550a">set_target</a>(<a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> target)</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  {</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  _target = target;</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  }</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> <span class="comment"></span></div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> <span class="comment"> /** Set the targeted GPU architecture according to the CL device</span></div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> <span class="comment"> *</span></div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> <span class="comment"> * @param[in] device A CL device</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> <span class="comment"> */</span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#ad5ba9d34a3a855bf1dd2e36316ff550a">set_target</a>(cl::Device &device);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="comment"></span></div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> <span class="comment"> /** Get the targeted GPU architecture</span></div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> <span class="comment"> *</span></div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> <span class="comment"> * @return The targeted GPU architecture.</span></div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> <span class="comment"> */</span></div><div class="line"><a name="l00286"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#aa550ff0352ff2388e02f7b0a41bf5fe7"> 286</a></span>  <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#aa550ff0352ff2388e02f7b0a41bf5fe7">get_target</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <span class="keywordflow">return</span> _target;</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  }</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> <span class="comment"></span></div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> <span class="comment"> /** Get the maximum workgroup size for the device the CLKernelLibrary uses.</span></div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> <span class="comment"> *</span></div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> <span class="comment"> * @return The maximum workgroup size value.</span></div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> <span class="comment"> */</span></div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#abca336f832d730e8494049bd714df60a">get_max_workgroup_size</a>();<span class="comment"></span></div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span> <span class="comment"> /** Get the global work size given an execution window</span></div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> <span class="comment"> *</span></div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> <span class="comment"> * @param[in] window Execution window</span></div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> <span class="comment"> *</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> <span class="comment"> * @return Global work size of the given execution window</span></div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> <span class="comment"> */</span></div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keyword">static</span> cl::NDRange <a class="code" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c01790e4e3f22f70f69002f0cb1b913">gws_from_window</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span> </div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> <span class="keyword">private</span>:<span class="comment"></span></div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> <span class="comment"> /** Add the passed array's parameters to the object's kernel's arguments starting from the index idx.</span></div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> <span class="comment"> *</span></div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the array's arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="comment"> * @param[in] array Array to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> <span class="comment"> * @param[in] strides @ref Strides object containing stride of each dimension in bytes.</span></div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> <span class="comment"> * @param[in] num_dimensions Number of dimensions of the @p array.</span></div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> <span class="comment"> * @param[in] window Window the kernel will be executed on.</span></div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="comment"> */</span></div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimension_size></div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordtype">void</span> add_array_argument(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &idx, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_array.xhtml">ICLArray<T></a> *array, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> &strides, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_dimensions, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);<span class="comment"></span></div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> <span class="comment"> /** Add the passed tensor's parameters to the object's kernel's arguments starting from the index idx.</span></div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> <span class="comment"> *</span></div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the tensor's arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="comment"> * @param[in] tensor Tensor to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> <span class="comment"> * @param[in] window Window the kernel will be executed on.</span></div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> <span class="comment"> */</span></div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keyword">template</span> <<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimension_size></div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keywordtype">void</span> add_tensor_argument(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> &idx, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *tensor, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> </div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> <span class="keyword">protected</span>:</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  cl::Kernel _kernel; <span class="comment">/**< OpenCL kernel to run */</span></div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <a class="code" href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">GPUTarget</a> _target; <span class="comment">/**< The targeted GPU */</span></div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  std::string _config_id; <span class="comment">/**< Configuration ID */</span></div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keywordtype">size_t</span> _max_workgroup_size; <span class="comment">/**< The maximum workgroup size for this kernel */</span></div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  cl::NDRange _lws_hint; <span class="comment">/**< Local workgroup size hint for the OpenCL kernel */</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> };</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> <span class="comment"></span></div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> <span class="comment">/** Add the kernel to the command queue with the given window.</span></div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> <span class="comment"> *</span></div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> <span class="comment"> * @note Depending on the size of the window, this might translate into several jobs being enqueued.</span></div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> <span class="comment"> *</span></div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> <span class="comment"> * @note If kernel->kernel() is empty then the function will return without adding anything to the queue.</span></div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> <span class="comment"> *</span></div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> <span class="comment"> * @param[in,out] queue OpenCL command queue.</span></div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span> <span class="comment"> * @param[in] kernel Kernel to enqueue</span></div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> <span class="comment"> * @param[in] window Window the kernel has to process.</span></div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span> <span class="comment"> * @param[in] lws_hint (Optional) Local workgroup size requested. Default is based on the device target.</span></div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span> <span class="comment"> * @param[in] use_dummy_work_items (Optional) Use dummy work items in order to have two dimensional power of two NDRange. Default is false</span></div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span> <span class="comment"> * Note: it is kernel responsibility to check if the work-item is out-of-range</span></div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> <span class="comment"> *</span></div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span> <span class="comment"> * @note If any dimension of the lws is greater than the global workgroup size then no lws will be passed.</span></div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> <span class="comment"> */</span></div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute.xhtml#a6e51ab3789678d3e0b0b72178dd6c4c6">enqueue</a>(cl::CommandQueue &queue, ICLKernel &kernel, <span class="keyword">const</span> Window &window, <span class="keyword">const</span> cl::NDRange &lws_hint = <a class="code" href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">CLKernelLibrary::get</a>().default_ndrange(), <span class="keywordtype">bool</span> use_dummy_work_items = <span class="keyword">false</span>);</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> <span class="comment"></span></div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span> <span class="comment">/** Add the passed array's parameters to the object's kernel's arguments starting from the index idx.</span></div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> <span class="comment"> *</span></div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> <span class="comment"> * @param[in,out] idx Index at which to start adding the array's arguments. Will be incremented by the number of kernel arguments set.</span></div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> <span class="comment"> * @param[in] array Array to set as an argument of the object's kernel.</span></div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> <span class="comment"> * @param[in] strides @ref Strides object containing stride of each dimension in bytes.</span></div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> <span class="comment"> * @param[in] num_dimensions Number of dimensions of the @p array.</span></div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> <span class="comment"> * @param[in] window Window the kernel will be executed on.</span></div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> <span class="comment"> */</span></div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimension_size></div><div class="line"><a name="l00359"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_i_c_l_kernel.xhtml#a2d7c6b5f3332604ad6a637457f65c342"> 359</a></span> <span class="keywordtype">void</span> ICLKernel::add_array_argument(<span class="keywordtype">unsigned</span> &idx, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_array.xhtml">ICLArray<T></a> *array, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> &strides, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_dimensions, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &window)</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span> {</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(array == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span> </div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="comment">// Calculate offset to the start of the window</span></div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> offset_first_element = 0;</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span> </div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 0; n < num_dimensions; ++n)</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  {</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  offset_first_element += <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>[n].start() * strides[n];</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  }</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> </div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx_start = idx;</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  _kernel.setArg(idx++, array-><a class="code" href="classarm__compute_1_1_i_c_l_array.xhtml#a1fb4c50755a0ef424652246838ed91a6">cl_buffer</a>());</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> </div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimension = 0; dimension < dimension_size; dimension++)</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  {</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  _kernel.setArg<cl_uint>(idx++, strides[dimension]);</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  _kernel.setArg<cl_uint>(idx++, strides[dimension] * <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>[dimension].step());</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  }</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> </div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  _kernel.setArg<cl_uint>(idx++, offset_first_element);</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span> </div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <a class="code" href="_error_8h.xhtml#acaa348bf0c7eb9493c72092b7293d45f">ARM_COMPUTE_ERROR_ON_MSG_VAR</a>(idx_start + num_arguments_per_array<dimension_size>() != idx,</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="stringliteral">"add_%dD_array_argument() is supposed to add exactly %d arguments to the kernel"</span>, dimension_size, num_arguments_per_array<dimension_size>());</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(idx_start);</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> }</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span> }</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> <span class="preprocessor">#endif </span><span class="comment">/*ARM_COMPUTE_ICLKERNEL_H */</span><span class="preprocessor"></span></div><div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a43b6c5e4b57069c5f61e96dff24c212d"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a43b6c5e4b57069c5f61e96dff24c212d">arm_compute::ICLKernel::num_arguments_per_1D_tensor</a></div><div class="ttdeci">static constexpr unsigned int num_arguments_per_1D_tensor()</div><div class="ttdoc">Returns the number of arguments enqueued per 1D tensor object.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00184">ICLKernel.h:184</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a6c01790e4e3f22f70f69002f0cb1b913"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c01790e4e3f22f70f69002f0cb1b913">arm_compute::ICLKernel::gws_from_window</a></div><div class="ttdeci">static cl::NDRange gws_from_window(const Window &window)</div><div class="ttdoc">Get the global work size given an execution window.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8cpp_source.xhtml#l00141">ICLKernel.cpp:141</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml">arm_compute::IKernel</a></div><div class="ttdoc">Common information for all the kernels.</div><div class="ttdef"><b>Definition:</b> <a href="_i_kernel_8h_source.xhtml#l00033">IKernel.h:33</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a25965a58d98e44856da286925792a2f7"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a25965a58d98e44856da286925792a2f7">arm_compute::ICLKernel::add_1D_tensor_argument_if</a></div><div class="ttdeci">void add_1D_tensor_argument_if(bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)</div><div class="ttdoc">Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx ...</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00121">ICLKernel.h:121</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_ad34a46f53686c12a5c5e717cc9617fb6"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window & window() const</div><div class="ttdoc">The maximum window the kernel can be executed on.</div><div class="ttdef"><b>Definition:</b> <a href="_i_kernel_8cpp_source.xhtml#l00028">IKernel.cpp:28</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a278f0e6c68ca17e71f4c4ff82f360aa0"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a278f0e6c68ca17e71f4c4ff82f360aa0">arm_compute::ICLKernel::num_arguments_per_1D_array</a></div><div class="ttdeci">static constexpr unsigned int num_arguments_per_1D_array()</div><div class="ttdoc">Returns the number of arguments enqueued per 1D array object.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00176">ICLKernel.h:176</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a2ada6044648832c64532588f75303b44"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a2ada6044648832c64532588f75303b44">arm_compute::ICLKernel::add_2D_tensor_argument_if</a></div><div class="ttdeci">void add_2D_tensor_argument_if(bool cond, unsigned int &idx, const ICLTensor *tensor, const Window &window)</div><div class="ttdoc">Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx ...</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00145">ICLKernel.h:145</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a6e51ab3789678d3e0b0b72178dd6c4c6"><div class="ttname"><a href="namespacearm__compute.xhtml#a6e51ab3789678d3e0b0b72178dd6c4c6">arm_compute::enqueue</a></div><div class="ttdeci">void enqueue(cl::CommandQueue &queue, ICLKernel &kernel, const Window &window, const cl::NDRange &lws_hint=CLKernelLibrary::get().default_ndrange(), bool use_dummy_work_items=false)</div><div class="ttdoc">Add the kernel to the command queue with the given window.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8cpp_source.xhtml#l00039">ICLKernel.cpp:39</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_ae5121015ab09ece4d470f50c7ffe198e"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#ae5121015ab09ece4d470f50c7ffe198e">arm_compute::ICLKernel::kernel</a></div><div class="ttdeci">cl::Kernel & kernel()</div><div class="ttdoc">Returns a reference to the OpenCL kernel of this object.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00087">ICLKernel.h:87</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_ab9f813c25ed75ea7b7ac2fa3926a8f55"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#ab9f813c25ed75ea7b7ac2fa3926a8f55">arm_compute::ICLKernel::lws_hint</a></div><div class="ttdeci">cl::NDRange lws_hint() const</div><div class="ttdoc">Return the Local-Workgroup-Size hint.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00247">ICLKernel.h:247</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_ad356b88c8f61267d593d9ed99835bde9"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#ad356b88c8f61267d593d9ed99835bde9">arm_compute::ICLKernel::set_lws_hint</a></div><div class="ttdeci">void set_lws_hint(const cl::NDRange &lws_hint)</div><div class="ttdoc">Set the Local-Workgroup-Size hint.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00237">ICLKernel.h:237</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a50f427a1d9419800972b9e03c4034311"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a50f427a1d9419800972b9e03c4034311">arm_compute::ICLKernel::add_argument</a></div><div class="ttdeci">void add_argument(unsigned int &idx, T value)</div><div class="ttdoc">Add the passed parameters to the object's kernel's arguments starting from the index idx.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00226">ICLKernel.h:226</a></div></div> |
| <div class="ttc" id="_c_l_types_8h_xhtml"><div class="ttname"><a href="_c_l_types_8h.xhtml">CLTypes.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a9331d385192a50adf74d3af40ce0fa20"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a9331d385192a50adf74d3af40ce0fa20">arm_compute::ICLKernel::add_1D_array_argument</a></div><div class="ttdeci">void add_1D_array_argument(unsigned int &idx, const ICLArray< T > *array, const Strides &strides, unsigned int num_dimensions, const Window &window)</div><div class="ttdoc">Add the passed 1D array's parameters to the object's kernel's arguments starting from the index idx.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00100">ICLKernel.h:100</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00466">Error.h:466</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_kernel_library_xhtml_acba005f5ce2c62cbf3f94d074d9007aa"><div class="ttname"><a href="classarm__compute_1_1_c_l_kernel_library.xhtml#acba005f5ce2c62cbf3f94d074d9007aa">arm_compute::CLKernelLibrary::get</a></div><div class="ttdeci">static CLKernelLibrary & get()</div><div class="ttdoc">Access the KernelLibrary singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_kernel_library_8cpp_source.xhtml#l01072">CLKernelLibrary.cpp:1072</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_acaa348bf0c7eb9493c72092b7293d45f"><div class="ttname"><a href="_error_8h.xhtml#acaa348bf0c7eb9493c72092b7293d45f">ARM_COMPUTE_ERROR_ON_MSG_VAR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG_VAR(cond, msg,...)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00457">Error.h:457</a></div></div> |
| <div class="ttc" id="_i_kernel_8h_xhtml"><div class="ttname"><a href="_i_kernel_8h.xhtml">IKernel.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml">arm_compute::ICLKernel</a></div><div class="ttdoc">Common interface for all the OpenCL kernels.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00043">ICLKernel.h:43</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a28f5847162f352444c6ac1825d0e99c7"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a28f5847162f352444c6ac1825d0e99c7">arm_compute::ICLKernel::add_3D_tensor_argument</a></div><div class="ttdeci">void add_3D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)</div><div class="ttdoc">Add the passed 3D tensor's parameters to the object's kernel's arguments starting from the index idx.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00158">ICLKernel.h:158</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2020 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a8f7f6ab59fc0e601d750b83e75a398eb"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a8f7f6ab59fc0e601d750b83e75a398eb">arm_compute::ICLKernel::config_id</a></div><div class="ttdeci">const std::string & config_id() const</div><div class="ttdoc">Get the configuration ID.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00262">ICLKernel.h:262</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_array_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_array.xhtml">arm_compute::ICLArray</a></div><div class="ttdoc">Interface for OpenCL Array.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_array_8h_source.xhtml#l00035">ICLArray.h:35</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a6c9c1e7a7d96743375ca40847f0f12e2"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6c9c1e7a7d96743375ca40847f0f12e2">arm_compute::ICLKernel::num_arguments_per_3D_tensor</a></div><div class="ttdeci">static constexpr unsigned int num_arguments_per_3D_tensor()</div><div class="ttdoc">Returns the number of arguments enqueued per 3D tensor object.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00200">ICLKernel.h:200</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00152">Error.h:152</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_aa550ff0352ff2388e02f7b0a41bf5fe7"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#aa550ff0352ff2388e02f7b0a41bf5fe7">arm_compute::ICLKernel::get_target</a></div><div class="ttdeci">GPUTarget get_target() const</div><div class="ttdoc">Get the targeted GPU architecture.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00286">ICLKernel.h:286</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a45601e0d46621a5b6f2e417d60e5c800"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a45601e0d46621a5b6f2e417d60e5c800">arm_compute::ICLKernel::num_arguments_per_2D_tensor</a></div><div class="ttdeci">static constexpr unsigned int num_arguments_per_2D_tensor()</div><div class="ttdoc">Returns the number of arguments enqueued per 2D tensor object.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00192">ICLKernel.h:192</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a184fdf37587a9314cf12623accea6c73"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a184fdf37587a9314cf12623accea6c73">arm_compute::ICLKernel::num_arguments_per_4D_tensor</a></div><div class="ttdeci">static constexpr unsigned int num_arguments_per_4D_tensor()</div><div class="ttdoc">Returns the number of arguments enqueued per 4D tensor object.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00208">ICLKernel.h:208</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_strides_xhtml"><div class="ttname"><a href="classarm__compute_1_1_strides.xhtml">arm_compute::Strides</a></div><div class="ttdoc">Strides of an item in bytes.</div><div class="ttdef"><b>Definition:</b> <a href="_strides_8h_source.xhtml#l00037">Strides.h:37</a></div></div> |
| <div class="ttc" id="_g_p_u_target_8h_xhtml"><div class="ttname"><a href="_g_p_u_target_8h.xhtml">GPUTarget.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_af6a174d47571f51f199ffc27ecc10f51"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#af6a174d47571f51f199ffc27ecc10f51">arm_compute::ICLKernel::run</a></div><div class="ttdeci">virtual void run(const Window &window, cl::CommandQueue &queue)=0</div><div class="ttdoc">Enqueue the OpenCL kernel to process the given window on the passed OpenCL command queue.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_ac74dad3e61f79334f5e73f3c3ac603cb"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#ac74dad3e61f79334f5e73f3c3ac603cb">arm_compute::ICLKernel::add_2D_tensor_argument</a></div><div class="ttdeci">void add_2D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)</div><div class="ttdoc">Add the passed 2D tensor's parameters to the object's kernel's arguments starting from the index idx.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00134">ICLKernel.h:134</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_tensor.xhtml">arm_compute::ICLTensor</a></div><div class="ttdoc">Interface for OpenCL tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_tensor_8h_source.xhtml#l00042">ICLTensor.h:42</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a6b10e96ce90bf901d17def86b874b019"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a6b10e96ce90bf901d17def86b874b019">arm_compute::ICLKernel::ICLKernel</a></div><div class="ttdeci">ICLKernel()</div><div class="ttdoc">Constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00079">ICLKernel.h:79</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3">arm_compute::GPUTarget</a></div><div class="ttdeci">GPUTarget</div><div class="ttdoc">Available GPU Targets.</div><div class="ttdef"><b>Definition:</b> <a href="_g_p_u_target_8h_source.xhtml#l00034">GPUTarget.h:34</a></div></div> |
| <div class="ttc" id="_c_l_kernel_library_8h_xhtml"><div class="ttname"><a href="_c_l_kernel_library_8h.xhtml">CLKernelLibrary.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a735ac6c2a02e320969625308810444f3afa362f4daec88442a387ff7cda411a38"><div class="ttname"><a href="namespacearm__compute.xhtml#a735ac6c2a02e320969625308810444f3afa362f4daec88442a387ff7cda411a38">arm_compute::GPUTarget::MIDGARD</a></div></div> |
| <div class="ttc" id="_open_c_l_8h_xhtml"><div class="ttname"><a href="_open_c_l_8h.xhtml">OpenCL.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_abca336f832d730e8494049bd714df60a"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#abca336f832d730e8494049bd714df60a">arm_compute::ICLKernel::get_max_workgroup_size</a></div><div class="ttdeci">size_t get_max_workgroup_size()</div><div class="ttdoc">Get the maximum workgroup size for the device the CLKernelLibrary uses.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8cpp_source.xhtml#l00132">ICLKernel.cpp:132</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_ad5ba9d34a3a855bf1dd2e36316ff550a"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#ad5ba9d34a3a855bf1dd2e36316ff550a">arm_compute::ICLKernel::set_target</a></div><div class="ttdeci">void set_target(GPUTarget target)</div><div class="ttdoc">Set the targeted GPU architecture.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00271">ICLKernel.h:271</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a479e7043e65dc87de35d374e108510f7"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a479e7043e65dc87de35d374e108510f7">arm_compute::ICLKernel::add_1D_tensor_argument</a></div><div class="ttdeci">void add_1D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)</div><div class="ttdoc">Add the passed 1D tensor's parameters to the object's kernel's arguments starting from the index idx.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00110">ICLKernel.h:110</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_kernel_xhtml_a33e09c946b338fbfc780a9d1c66e68ad"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_kernel.xhtml#a33e09c946b338fbfc780a9d1c66e68ad">arm_compute::ICLKernel::add_4D_tensor_argument</a></div><div class="ttdeci">void add_4D_tensor_argument(unsigned int &idx, const ICLTensor *tensor, const Window &window)</div><div class="ttdoc">Add the passed 4D tensor's parameters to the object's kernel's arguments starting from the index idx.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_kernel_8h_source.xhtml#l00168">ICLKernel.h:168</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_array_xhtml_a1fb4c50755a0ef424652246838ed91a6"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_array.xhtml#a1fb4c50755a0ef424652246838ed91a6">arm_compute::ICLArray::cl_buffer</a></div><div class="ttdeci">virtual const cl::Buffer & cl_buffer() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return a reference to the OpenCL buffer containing ...</div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml">arm_compute::Window</a></div><div class="ttdoc">Describe a multidimensional execution window.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00039">Window.h:39</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a1b35b0d258183cf9ef36adf684d0b88c"><div class="ttname"><a href="_validate_8h.xhtml#a1b35b0d258183cf9ef36adf684d0b88c">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00941">Validate.h:941</a></div></div> |
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