arm_compute v19.11
diff --git a/documentation/dequantization__layer_8cl_source.xhtml b/documentation/dequantization__layer_8cl_source.xhtml
index c873fcd..f873a73 100644
--- a/documentation/dequantization__layer_8cl_source.xhtml
+++ b/documentation/dequantization__layer_8cl_source.xhtml
@@ -40,7 +40,7 @@
<img alt="Compute Library" src="https://raw.githubusercontent.com/ARM-software/ComputeLibrary/gh-pages/ACL_logo.png" style="max-width: 100%;margin-top: 15px;margin-left: 10px"/>
<td style="padding-left: 0.5em;">
<div id="projectname">
-  <span id="projectnumber">19.08</span>
+  <span id="projectnumber">19.11</span>
</div>
</td>
</tr>
@@ -100,23 +100,26 @@
<div class="title">dequantization_layer.cl</div> </div>
</div><!--header-->
<div class="contents">
-<a href="dequantization__layer_8cl.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) 2017-2019 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">#include "<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml">helpers.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#if defined(VEC_SIZE) && defined(DATA_TYPE_SRC) && defined(DATA_TYPE_DST) && defined(SCALE) && defined(OFFSET)</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> __kernel <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#abd43030e06efec1c26997107b7bd184d">dequantization_layer</a>(</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(input),</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(output))</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> {</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// Get pixels pointer</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> input = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(input);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> output = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(output);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="preprocessor">#if defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// Check if access on width gets out of bounds</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// If it does shift access vector to access elements within bounds</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> xi = (int)(get_global_id(0) * VEC_SIZE);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  input.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * input_stride_x;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * output_stride_x;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="comment">// Load data</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, VEC_SIZE)</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  val = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>(<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a287e2fc366c312b468382c95bb90f91f">VLOAD</a>(VEC_SIZE)(0, (__global DATA_TYPE_SRC *)input.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>), <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, VEC_SIZE));</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="comment">// Create scale and offset vectors</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">const</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, VEC_SIZE)</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  vscale = SCALE;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keyword">const</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, VEC_SIZE)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  voffset = OFFSET;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="comment">// Dequantize</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, VEC_SIZE)</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  res = vscale * <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>((val - voffset), <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, VEC_SIZE));</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="comment">// Store result</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#acb282042d1edeeaa3cc979a206f78b54">VSTORE</a>(VEC_SIZE)</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  (<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>(res, <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(DATA_TYPE_DST, VEC_SIZE)), 0, (__global DATA_TYPE_DST *)output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="preprocessor">#else // !defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  *((__global DATA_TYPE_DST *)(output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>)) = (DATA_TYPE_DST)((float)((<span class="keywordtype">int</span>)(*((__global DATA_TYPE_SRC *)(input.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>))) - (int)(OFFSET)) * (<span class="keywordtype">float</span>)(SCALE));</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="preprocessor">#endif // defined(LAST_ACCESSED_X)</span></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> </div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="preprocessor">#endif // defined(VEC_SIZE) && defined(DATA_TYPE_SRC) && defined(DATA_TYPE_DST) && defined(SCALE) && defined(OFFSET)</span></div><div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_aa8d95ba04fc73845abc6045952cae5be"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a></div><div class="ttdeci">#define CONVERT(x, type)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00079">helpers.h:79</a></div></div>
-<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_abd43030e06efec1c26997107b7bd184d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#abd43030e06efec1c26997107b7bd184d">arm_compute::test::validation::reference::dequantization_layer</a></div><div class="ttdeci">SimpleTensor< TOut > dequantization_layer(const SimpleTensor< TIn > &src)</div><div class="ttdef"><b>Definition:</b> <a href="validation_2reference_2_dequantization_layer_8cpp_source.xhtml#l00100">DequantizationLayer.cpp:100</a></div></div>
-<div class="ttc" id="struct_tensor3_d_xhtml"><div class="ttname"><a href="struct_tensor3_d.xhtml">Tensor3D</a></div><div class="ttdoc">Structure to hold 3D tensor information.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00176">helpers.h:176</a></div></div>
-<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a31c8c760f08fb1a331b16b7c204321dc"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a></div><div class="ttdeci">#define CONVERT_TO_TENSOR3D_STRUCT(name)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00144">helpers.h:144</a></div></div>
+<a href="dequantization__layer_8cl.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) 2017-2019 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">#include "<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml">helpers.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#if defined(VEC_SIZE) && defined(DATA_TYPE_SRC) && defined(DATA_TYPE_DST) && defined(SCALE) && defined(OFFSET)</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="comment"></span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment">/** This performs the dequantization of 8-bit unsigned integers to floating point.</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment"> *</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="comment"> * @note Source datatype should be given as a preprocessor argument using -DDATA_TYPE_SRC=type. e.g. -DDATA_TYPE_SRC=char</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"> * @note Destination datatype should be given as a preprocessor argument using -DDATA_TYPE_DST=type. e.g. -DDATA_TYPE_DST=float</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"> * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> * @note Quantization scale of input tensor is passed in with -DSCALE=scale.</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"> * @note Quantization offset of input tensor is passed in with -DOFFSET=offset.</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment"> *</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment"> * @param[in] input_ptr Pointer to the source tensor. Supported data types: QASYMM8/QSYMM8</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"> * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes)</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="comment"> * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="comment"> * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes)</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment"> * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment"> * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="comment"> * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment"> * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment"> * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F16/F32</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment"> * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="comment"> * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"> * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="comment"> * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="comment"> * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="comment"> * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"> * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor</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> __kernel <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#abd43030e06efec1c26997107b7bd184d">dequantization_layer</a>(</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>),</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(output))</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> {</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// Get pixels pointer</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a> = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> output = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(output);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="preprocessor">#if defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// Check if access on width gets out of bounds</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// If it does shift access vector to access elements within bounds</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> xi = (int)(get_global_id(0) * <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * input_stride_x;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * output_stride_x;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="comment">// Load data</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  val = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>(<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a287e2fc366c312b468382c95bb90f91f">VLOAD</a>(<a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)(0, (__global DATA_TYPE_SRC *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr), <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>));</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="comment">// Create scale and offset vectors</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">const</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  vscale = SCALE;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keyword">const</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  voffset = OFFSET;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="comment">// Dequantize</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  res = vscale * <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>((val - voffset), <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>));</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="comment">// Store result</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#acb282042d1edeeaa3cc979a206f78b54">VSTORE</a>(<a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  (<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>(res, <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(DATA_TYPE_DST, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)), 0, (__global DATA_TYPE_DST *)output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="preprocessor">#else // !defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  *((__global DATA_TYPE_DST *)(output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>)) = (DATA_TYPE_DST)((float)((<span class="keywordtype">int</span>)(*((__global DATA_TYPE_SRC *)(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr))) - (int)(OFFSET)) * (<span class="keywordtype">float</span>)(SCALE));</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="preprocessor">#endif // defined(LAST_ACCESSED_X)</span></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="preprocessor">#endif // defined(VEC_SIZE) && defined(DATA_TYPE_SRC) && defined(DATA_TYPE_DST) && defined(SCALE) && defined(OFFSET)</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="preprocessor">#if defined(VEC_SIZE) && defined(DATA_TYPE_SRC) && defined(DATA_TYPE_DST)</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="comment">/** This performs per channel dequantization of 8-bit signed integers to floating point. (NCHW)</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="comment"> *</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="comment"> * @note Source datatype should be given as a preprocessor argument using -DDATA_TYPE_SRC=type. e.g. -DDATA_TYPE_SRC=char</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="comment"> * @note Destination datatype should be given as a preprocessor argument using -DDATA_TYPE_DST=type. e.g. -DDATA_TYPE_DST=float</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="comment"> * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16</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="comment"> * @param[in] input_ptr Pointer to the source tensor. Supported data types: QSYMM8_PER_CHANNEL</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="comment"> * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes)</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="comment"> * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="comment"> * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes)</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="comment"> * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="comment"> * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="comment"> * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="comment"> * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="comment"> * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F16/F32</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="comment"> * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="comment"> * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="comment"> * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="comment"> * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="comment"> * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="comment"> * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="comment"> * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment"> * @param[in] scale Pointer to buffer with the per channel quantized scales</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="comment"> */</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> __kernel <span class="keywordtype">void</span> dequantization_layer_per_channel_nchw(</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>),</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(output),</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  __global <span class="keywordtype">float</span> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>)</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> {</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="comment">// Get pixels pointer</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a> = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>);</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> output = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(output);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="preprocessor">#if defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="comment">// Check if access on width gets out of bounds</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="comment">// If it does shift access vector to access elements within bounds</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> xi = (int)(get_global_id(0) * <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * input_stride_x;</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * output_stride_x;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> </div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="comment">// Load data</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  val = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>(<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a287e2fc366c312b468382c95bb90f91f">VLOAD</a>(<a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)(0, (__global DATA_TYPE_SRC *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr), <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>));</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="comment">// Create scale vectors</span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keyword">const</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  vscale = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>[get_global_id(2)];</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="comment">// Dequantize</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  res = vscale * <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>((val), <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>));</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="comment">// Store result</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#acb282042d1edeeaa3cc979a206f78b54">VSTORE</a>(<a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  (<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>(res, <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(DATA_TYPE_DST, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)), 0, (__global DATA_TYPE_DST *)output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="preprocessor">#else // !defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  *((__global DATA_TYPE_DST *)(output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>)) = (DATA_TYPE_DST)((float)((<span class="keywordtype">int</span>)(*((__global DATA_TYPE_SRC *)(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr)))) * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>[get_global_id(2)]);</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> <span class="preprocessor">#endif // defined(LAST_ACCESSED_X)</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">/** This performs per channel dequantization of 8-bit signed integers to floating point. (NHWC)</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"> * @note Source datatype should be given as a preprocessor argument using -DDATA_TYPE_SRC=type. e.g. -DDATA_TYPE_SRC=char</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="comment"> * @note Destination datatype should be given as a preprocessor argument using -DDATA_TYPE_DST=type. e.g. -DDATA_TYPE_DST=float</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="comment"> * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16</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"> 158</span> <span class="comment"> * @param[in] input_ptr Pointer to the source tensor. Supported data types: QSYMM8_PER_CHANNEL</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="comment"> * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes)</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> <span class="comment"> * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="comment"> * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes)</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="comment"> * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> <span class="comment"> * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> <span class="comment"> * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> <span class="comment"> * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source tensor</span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> <span class="comment"> * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F16/F32</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> <span class="comment"> * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="comment"> * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> <span class="comment"> * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> <span class="comment"> * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> <span class="comment"> * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> <span class="comment"> * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> <span class="comment"> * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor</span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> <span class="comment"> * @param[in] scale Pointer to buffer with the per channel quantized scales</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"> 176</span> __kernel <span class="keywordtype">void</span> dequantization_layer_per_channel_nhwc(</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>),</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(output),</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  __global <span class="keywordtype">float</span> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>)</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> {</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="comment">// Get pixels pointer</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a> = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> output = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(output);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> <span class="preprocessor">#if defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="comment">// Check if access on width gets out of bounds</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="comment">// If it does shift access vector to access elements within bounds</span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> xi = (int)(get_global_id(0) * <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * input_stride_x;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * output_stride_x;</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a> -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0);</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> </div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="comment">// Load data</span></div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  val = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>(<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a287e2fc366c312b468382c95bb90f91f">VLOAD</a>(<a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)(0, (__global DATA_TYPE_SRC *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr), <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">int</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>));</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// Create scale vectors</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keyword">const</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  vscale = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a287e2fc366c312b468382c95bb90f91f">VLOAD</a>(<a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)(0, &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>[xi]);</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="comment">// Dequantize</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  res = vscale * <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>((val), <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<span class="keywordtype">float</span>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>));</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="comment">// Store result</span></div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#acb282042d1edeeaa3cc979a206f78b54">VSTORE</a>(<a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  (<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a>(res, <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(DATA_TYPE_DST, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)), 0, (__global DATA_TYPE_DST *)output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> <span class="preprocessor">#else // !defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  *((__global DATA_TYPE_DST *)(output.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>)) = (DATA_TYPE_DST)((float)((<span class="keywordtype">int</span>)(*((__global DATA_TYPE_SRC *)(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr)))) * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>[get_global_id(0)]);</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> <span class="preprocessor">#endif // defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> }</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> <span class="preprocessor">#endif // defined(VEC_SIZE) && defined(DATA_TYPE_SRC) && defined(DATA_TYPE_DST)</span></div><div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_aa8d95ba04fc73845abc6045952cae5be"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#aa8d95ba04fc73845abc6045952cae5be">CONVERT</a></div><div class="ttdeci">#define CONVERT(x, type)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00261">helpers.h:261</a></div></div>
+<div class="ttc" id="depthwise__convolution__quantized_8cl_xhtml_a3fffea119c04c7680f2e9cf3fadf63b4"><div class="ttname"><a href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a></div><div class="ttdeci">#define VEC_SIZE</div><div class="ttdef"><b>Definition:</b> <a href="depthwise__convolution__quantized_8cl_source.xhtml#l00031">depthwise_convolution_quantized.cl:31</a></div></div>
+<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_abd43030e06efec1c26997107b7bd184d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#abd43030e06efec1c26997107b7bd184d">arm_compute::test::validation::reference::dequantization_layer</a></div><div class="ttdeci">SimpleTensor< TOut > dequantization_layer(const SimpleTensor< TIn > &src)</div><div class="ttdef"><b>Definition:</b> <a href="validation_2reference_2_dequantization_layer_8cpp_source.xhtml#l00055">DequantizationLayer.cpp:55</a></div></div>
+<div class="ttc" id="struct_tensor3_d_xhtml"><div class="ttname"><a href="struct_tensor3_d.xhtml">Tensor3D</a></div><div class="ttdoc">Structure to hold 3D tensor information.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00358">helpers.h:358</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="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a31c8c760f08fb1a331b16b7c204321dc"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a></div><div class="ttdeci">#define CONVERT_TO_TENSOR3D_STRUCT(name)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00326">helpers.h:326</a></div></div>
+<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_acec6d8ad52a28972fa74e071c1a63b6a"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">arm_compute::test::validation::scale</a></div><div class="ttdeci">scale</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_pixel_wise_multiplication_8cpp_source.xhtml#l00317">PixelWiseMultiplication.cpp:317</a></div></div>
<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml">helpers.h</a></div></div>
-<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_acb282042d1edeeaa3cc979a206f78b54"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#acb282042d1edeeaa3cc979a206f78b54">VSTORE</a></div><div class="ttdeci">#define VSTORE(size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00056">helpers.h:56</a></div></div>
-<div class="ttc" id="struct_tensor3_d_xhtml_acf52c23cbd7424606c10a606524e3e32"><div class="ttname"><a href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">Tensor3D::ptr</a></div><div class="ttdeci">__global uchar * ptr</div><div class="ttdoc">Pointer to the starting postion of the buffer.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00178">helpers.h:178</a></div></div>
-<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a287e2fc366c312b468382c95bb90f91f"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a287e2fc366c312b468382c95bb90f91f">VLOAD</a></div><div class="ttdeci">#define VLOAD(size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00053">helpers.h:53</a></div></div>
-<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a6b83038822d1ae7ab619b684ed3b7fc0"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a></div><div class="ttdeci">#define TENSOR3D_DECLARATION(name)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00101">helpers.h:101</a></div></div>
-<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a36f754c05b6fddf6df0d8d0a74f8159f"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a></div><div class="ttdeci">#define VEC_DATA_TYPE(type, size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00073">helpers.h:73</a></div></div>
+<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_acb282042d1edeeaa3cc979a206f78b54"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#acb282042d1edeeaa3cc979a206f78b54">VSTORE</a></div><div class="ttdeci">#define VSTORE(size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00198">helpers.h:198</a></div></div>
+<div class="ttc" id="struct_tensor3_d_xhtml_acf52c23cbd7424606c10a606524e3e32"><div class="ttname"><a href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">Tensor3D::ptr</a></div><div class="ttdeci">__global uchar * ptr</div><div class="ttdoc">Pointer to the starting postion of the buffer.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00360">helpers.h:360</a></div></div>
+<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a287e2fc366c312b468382c95bb90f91f"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a287e2fc366c312b468382c95bb90f91f">VLOAD</a></div><div class="ttdeci">#define VLOAD(size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00195">helpers.h:195</a></div></div>
+<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a6b83038822d1ae7ab619b684ed3b7fc0"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a></div><div class="ttdeci">#define TENSOR3D_DECLARATION(name)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00283">helpers.h:283</a></div></div>
+<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a36f754c05b6fddf6df0d8d0a74f8159f"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a></div><div class="ttdeci">#define VEC_DATA_TYPE(type, size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00255">helpers.h:255</a></div></div>
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