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| <a href="_c_l_accumulate_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_CLACCUMULATEKERNEL_H</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define ARM_COMPUTE_CLACCUMULATEKERNEL_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="_i_c_l_simple2_d_kernel_8h.xhtml">arm_compute/core/CL/ICLSimple2DKernel.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include <cstdint></span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></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="keyword">class </span>ICLTensor;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"></span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment">/** Interface for the accumulate kernel.</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment"> *</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"> * Accumulation is computed by:</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="comment"> * @f[ accum(x,y) = accum(x,y) + input(x,y) @f]</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="comment"> */</span></div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml"> 40</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml">CLAccumulateKernel</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1_i_c_l_simple2_d_kernel.xhtml">ICLSimple2DKernel</a></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment"> /** Set the input and accumulation tensors.</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment"> *</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment"> * @param[in] input Source tensor. Data types supported: U8.</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="comment"> * @param[out] accum Destination tensor. Data types supported: S16.</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="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml#a04e027a7698e425da35a2d1a4adf6c3c">configure</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *accum);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> };</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="comment"></span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment">/** Interface for the accumulate weighted kernel.</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment"> *</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"> * Weighted accumulation is computed:</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="comment"> * @f[ accum(x,y) = (1 - \alpha)*accum(x,y) + \alpha*input(x,y) @f]</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="comment"> *</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"> * Where @f$ 0 \le \alpha \le 1 @f$</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> * Conceptually, the rounding for this is defined as:</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"> * @f[ output(x,y)= uint8( (1 - \alpha) * float32( int32( output(x,y) ) ) + \alpha * float32( int32( input(x,y) ) ) ) @f]</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="comment">*/</span></div><div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml"> 60</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml">CLAccumulateWeightedKernel</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1_i_c_l_simple2_d_kernel.xhtml">ICLSimple2DKernel</a></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="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="comment"> /** Set the input and accumulation images, and the scale value.</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment"> *</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="comment"> * @param[in] input Source tensor. Data types supported: U8.</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="comment"> * @param[in] alpha Scalar value in the range [0, 1.0]. Data types supported: F32.</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="comment"> * @param[in,out] accum Accumulated tensor. Data types supported: U8.</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="comment"> */</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml#a480232581dba02e630dd045e2f80ae87">configure</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, <span class="keywordtype">float</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3161c2c93c655dd30953372064ec627b">alpha</a>, <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *accum);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> };</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="comment"></span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="comment">/** Interface for the accumulate squared kernel.</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="comment"> *</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="comment"> * The accumulation of squares is computed:</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="comment"> * @f[ accum(x,y) = saturate_{int16} ( (uint16) accum(x,y) + (((uint16)(input(x,y)^2)) >> (shift)) ) @f]</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="comment"> *</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="comment"> * Where @f$ 0 \le shift \le 15 @f$</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="comment">*/</span></div><div class="line"><a name="l00079"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_accumulate_squared_kernel.xhtml"> 79</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_c_l_accumulate_squared_kernel.xhtml">CLAccumulateSquaredKernel</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1_i_c_l_simple2_d_kernel.xhtml">ICLSimple2DKernel</a></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> {</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="comment"> /** Set the input and accumulation tensors and the shift value.</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="comment"> *</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="comment"> * @param[in] input Source tensor. Data types supported: U8.</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="comment"> * @param[in] shift Shift value in the range of [0, 15]. Data types supported: U32.</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="comment"> * @param[in,out] accum Accumulated tensor. Data types supported: S16.</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="comment"> */</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_c_l_accumulate_squared_kernel.xhtml#ade36d9a0c92807caac072618a6d9a643">configure</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, uint32_t <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a979a54caef6e77ce0259e427136847e8">shift</a>, <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *accum);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> };</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> } <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="preprocessor">#endif </span><span class="comment">/*ARM_COMPUTE_CLACCUMULATEKERNEL_H */</span><span class="preprocessor"></span></div><div class="ttc" id="_i_c_l_simple2_d_kernel_8h_xhtml"><div class="ttname"><a href="_i_c_l_simple2_d_kernel_8h.xhtml">ICLSimple2DKernel.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_accumulate_weighted_kernel_xhtml_a480232581dba02e630dd045e2f80ae87"><div class="ttname"><a href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml#a480232581dba02e630dd045e2f80ae87">arm_compute::CLAccumulateWeightedKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, float alpha, ICLTensor *accum)</div><div class="ttdoc">Set the input and accumulation images, and the scale value.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_accumulate_kernel_8cpp_source.xhtml#l00053">CLAccumulateKernel.cpp:53</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a979a54caef6e77ce0259e427136847e8"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a979a54caef6e77ce0259e427136847e8">arm_compute::test::validation::shift</a></div><div class="ttdeci">shift</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_depth_convert_layer_8cpp_source.xhtml#l00155">DepthConvertLayer.cpp:155</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_accumulate_squared_kernel_xhtml_ade36d9a0c92807caac072618a6d9a643"><div class="ttname"><a href="classarm__compute_1_1_c_l_accumulate_squared_kernel.xhtml#ade36d9a0c92807caac072618a6d9a643">arm_compute::CLAccumulateSquaredKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, uint32_t shift, ICLTensor *accum)</div><div class="ttdoc">Set the input and accumulation tensors and the shift value.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_accumulate_kernel_8cpp_source.xhtml#l00070">CLAccumulateKernel.cpp:70</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_accumulate_weighted_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_l_accumulate_weighted_kernel.xhtml">arm_compute::CLAccumulateWeightedKernel</a></div><div class="ttdoc">Interface for the accumulate weighted kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_accumulate_kernel_8h_source.xhtml#l00060">CLAccumulateKernel.h:60</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="namespacearm__compute_1_1test_1_1validation_xhtml_a8fcf2ddd9a1d58b1b280f5c0aed71845"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">arm_compute::test::validation::input</a></div><div class="ttdeci">auto input</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_l_s_t_m_layer_quantized_8cpp_source.xhtml#l00487">LSTMLayerQuantized.cpp:487</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_accumulate_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml">arm_compute::CLAccumulateKernel</a></div><div class="ttdoc">Interface for the accumulate kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_accumulate_kernel_8h_source.xhtml#l00040">CLAccumulateKernel.h:40</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a3161c2c93c655dd30953372064ec627b"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a3161c2c93c655dd30953372064ec627b">arm_compute::test::validation::alpha</a></div><div class="ttdeci">const float alpha</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_accumulate_8cpp_source.xhtml#l00103">Accumulate.cpp:103</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_simple2_d_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_simple2_d_kernel.xhtml">arm_compute::ICLSimple2DKernel</a></div><div class="ttdoc">Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_simple2_d_kernel_8h_source.xhtml#l00034">ICLSimple2DKernel.h:34</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_accumulate_squared_kernel_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_l_accumulate_squared_kernel.xhtml">arm_compute::CLAccumulateSquaredKernel</a></div><div class="ttdoc">Interface for the accumulate squared kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_accumulate_kernel_8h_source.xhtml#l00079">CLAccumulateKernel.h:79</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_c_l_accumulate_kernel_xhtml_a04e027a7698e425da35a2d1a4adf6c3c"><div class="ttname"><a href="classarm__compute_1_1_c_l_accumulate_kernel.xhtml#a04e027a7698e425da35a2d1a4adf6c3c">arm_compute::CLAccumulateKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *accum)</div><div class="ttdoc">Set the input and accumulation tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_accumulate_kernel_8cpp_source.xhtml#l00041">CLAccumulateKernel.cpp:41</a></div></div> |
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