arm_compute v19.11
diff --git a/documentation/upsample__layer_8cl_source.xhtml b/documentation/upsample__layer_8cl_source.xhtml
index e9badfc..e16f4e4 100644
--- a/documentation/upsample__layer_8cl_source.xhtml
+++ b/documentation/upsample__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">
-   &#160;<span id="projectnumber">19.08</span>
+   &#160;<span id="projectnumber">19.11</span>
    </div>
   </td>
  </tr>
@@ -100,24 +100,24 @@
 <div class="title">upsample_layer.cl</div>  </div>
 </div><!--header-->
 <div class="contents">
-<a href="upsample__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>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<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>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<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>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml">helpers.h</a>&quot;</span></div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="upsample__layer_8cl.xhtml#a4f89158c7add6565fb016b46d3a5c33b">   52</a></span>&#160;__kernel <span class="keywordtype">void</span> <a class="code" href="upsample__layer_8cl.xhtml#a4f89158c7add6565fb016b46d3a5c33b">upsample_layer_nchw</a>(</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    <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#a989ab3e96426615bb98e04e0235088ca">src</a>),</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    <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#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>))</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;{</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</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#a989ab3e96426615bb98e04e0235088ca">src</a>);</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</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#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>);</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;<span class="preprocessor">#if defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <span class="comment">// Check if access on width gets out of bounds</span></div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <span class="comment">// If it does shift access vector to access elements within bounds</span></div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> xi_in  = (int)(get_global_id(0) * VEC_SIZE_IN);</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> xi_out = (int)(get_global_id(0) * VEC_SIZE_OUT);</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr -= max(xi_in - (<span class="keywordtype">int</span>)LAST_ACCESSED_X_IN, 0) * src_stride_x;</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.ptr -= max(xi_out - (<span class="keywordtype">int</span>)LAST_ACCESSED_X_OUT, 0) * dst_stride_x;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, 8)</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    data = vload8(0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, 16)</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    data_out = (<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, 16))(data.s0, data.s0, data.s1, data.s1, data.s2, data.s2, data.s3, data.s3, data.s4, data.s4, data.s5, data.s5, data.s6, data.s6, data.s7, data.s7);</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    vstore16(data_out, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.ptr);</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;    vstore16(data_out, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 0));</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;<span class="preprocessor">#else  // !defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 0, 0)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 0)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;<span class="preprocessor">#endif // defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;}</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno"><a class="line" href="upsample__layer_8cl.xhtml#a72ea02685fbca407f07ae495159e5b2b">  107</a></span>&#160;__kernel <span class="keywordtype">void</span> <a class="code" href="upsample__layer_8cl.xhtml#a72ea02685fbca407f07ae495159e5b2b">upsample_layer_nhwc</a>(</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    <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#a989ab3e96426615bb98e04e0235088ca">src</a>),</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    <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#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>))</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;{</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</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#a989ab3e96426615bb98e04e0235088ca">src</a>);</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</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#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>);</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;<span class="preprocessor">#if defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    <span class="comment">// Check if access on width gets out of bounds</span></div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    <span class="comment">// If it does shift access vector to access elements within bounds</span></div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> xi_in  = (int)(get_global_id(0) * VEC_SIZE_IN);</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> xi_out = (int)(get_global_id(0) * VEC_SIZE_OUT);</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr -= max(xi_in - (<span class="keywordtype">int</span>)LAST_ACCESSED_X_IN, 0) * src_stride_x;</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.ptr -= max(xi_out - (<span class="keywordtype">int</span>)LAST_ACCESSED_X_OUT, 0) * dst_stride_x;</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;    <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, 16)</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    data = vload16(0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    vstore16(data, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 0, 0));</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    vstore16(data, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 0));</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    vstore16(data, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 0, 1));</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    vstore16(data, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 1));</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;<span class="preprocessor">#else  // !defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 0, 0)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 0)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 0, 1)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 1)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;<span class="preprocessor">#endif // defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;}</div><div class="ttc" id="convolution3x3_8cl_xhtml_afb8c72ce35c4a1f4a2588d6573e54aa1"><div class="ttname"><a href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a></div><div class="ttdeci">#define DATA_TYPE</div><div class="ttdef"><b>Definition:</b> <a href="convolution3x3_8cl_source.xhtml#l00027">convolution3x3.cl:27</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>
+<a href="upsample__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>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<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>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<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>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<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>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml">helpers.h</a>&quot;</span></div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="comment"></span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="comment">/** This function applies upsample on an input image. (NCHW)</span></div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="comment"> * @attention The following variables must be passed at compile time:</span></div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="comment"> * -# -DDATA_TYPE = Tensor data type. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32</span></div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="comment"> * -# -DVEC_SIZE_IN = Input vector size</span></div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="comment"> * -# -DVEC_SIZE_OUT = Output vector size</span></div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="comment"> * -# -DLAST_ACCESSED_X_IN = The input element that is on the X border (threads trying to set this, might need to step back a bit)</span></div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="comment"> * -# -DLAST_ACCESSED_X_OUT = The output element that is on the X border (threads trying to set this, might need to step back a bit)</span></div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="comment"> * @param[in]  src_ptr                           Pointer to the source image. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32</span></div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="comment"> * @param[in]  src_stride_x                      Stride of the source image in X dimension (in bytes)</span></div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="comment"> * @param[in]  src_step_x                        src_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="comment"> * @param[in]  src_stride_y                      Stride of the source image in Y dimension (in bytes)</span></div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="comment"> * @param[in]  src_step_y                        src_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="comment"> * @param[in]  src_stride_z                      Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="comment"> * @param[in]  src_step_z                        src_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="comment"> * @param[in]  src_offset_first_element_in_bytes The offset of the first element in the source image</span></div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="comment"> * @param[out] dst_ptr                           Pointer to the destination image. Supported data types: same as @p src_ptr</span></div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="comment"> * @param[in]  dst_stride_x                      Stride of the destination image in X dimension (in bytes)</span></div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="comment"> * @param[in]  dst_step_x                        dst_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="comment"> * @param[in]  dst_stride_y                      Stride of the destination image in Y dimension (in bytes)</span></div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="comment"> * @param[in]  dst_step_y                        dst_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;<span class="comment"> * @param[in]  dst_stride_z                      Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;<span class="comment"> * @param[in]  dst_step_z                        dst_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;<span class="comment"> * @param[in]  dst_offset_first_element_in_bytes The offset of the first element in the destination image</span></div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="upsample__layer_8cl.xhtml#a4f89158c7add6565fb016b46d3a5c33b">   52</a></span>&#160;__kernel <span class="keywordtype">void</span> <a class="code" href="upsample__layer_8cl.xhtml#a4f89158c7add6565fb016b46d3a5c33b">upsample_layer_nchw</a>(</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    <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#a989ab3e96426615bb98e04e0235088ca">src</a>),</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    <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#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>))</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;{</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</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#a989ab3e96426615bb98e04e0235088ca">src</a>);</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</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#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>);</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;<span class="preprocessor">#if defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <span class="comment">// Check if access on width gets out of bounds</span></div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <span class="comment">// If it does shift access vector to access elements within bounds</span></div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> xi_in  = (int)(get_global_id(0) * VEC_SIZE_IN);</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> xi_out = (int)(get_global_id(0) * VEC_SIZE_OUT);</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr -= max(xi_in - (<span class="keywordtype">int</span>)LAST_ACCESSED_X_IN, 0) * src_stride_x;</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.ptr -= max(xi_out - (<span class="keywordtype">int</span>)LAST_ACCESSED_X_OUT, 0) * dst_stride_x;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, 8)</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    data = vload8(0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, 16)</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    data_out = (<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, 16))(data.s0, data.s0, data.s1, data.s1, data.s2, data.s2, data.s3, data.s3, data.s4, data.s4, data.s5, data.s5, data.s6, data.s6, data.s7, data.s7);</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    vstore16(data_out, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.ptr);</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;    vstore16(data_out, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 0));</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;<span class="preprocessor">#else  // !defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 0, 0)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 0)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;<span class="preprocessor">#endif // defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;}</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;<span class="comment"></span></div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;<span class="comment">/** This function applies upsample on an input image. (NHWC)</span></div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;<span class="comment"> * @attention The following variables must be passed at compile time:</span></div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;<span class="comment"> * -# -DDATA_TYPE = Tensor data type. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32</span></div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;<span class="comment"> * -# -DVEC_SIZE_IN = Input vector size</span></div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;<span class="comment"> * -# -DVEC_SIZE_OUT = Output vector size</span></div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;<span class="comment"> * -# -DLAST_ACCESSED_X_IN = The input element that is on the X border (threads trying to set this, might need to step back a bit)</span></div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;<span class="comment"> * -# -DLAST_ACCESSED_X_OUT = The output element that is on the X border (threads trying to set this, might need to step back a bit)</span></div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;<span class="comment"> * @param[in]  src_ptr                           Pointer to the source image. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32</span></div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;<span class="comment"> * @param[in]  src_stride_x                      Stride of the source image in X dimension (in bytes)</span></div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;<span class="comment"> * @param[in]  src_step_x                        src_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;<span class="comment"> * @param[in]  src_stride_y                      Stride of the source image in Y dimension (in bytes)</span></div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;<span class="comment"> * @param[in]  src_step_y                        src_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;<span class="comment"> * @param[in]  src_stride_z                      Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;<span class="comment"> * @param[in]  src_step_z                        src_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;<span class="comment"> * @param[in]  src_offset_first_element_in_bytes The offset of the first element in the source image</span></div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;<span class="comment"> * @param[out] dst_ptr                           Pointer to the destination image. Supported data types: same as @p src_ptr</span></div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;<span class="comment"> * @param[in]  dst_stride_x                      Stride of the destination image in X dimension (in bytes)</span></div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;<span class="comment"> * @param[in]  dst_step_x                        dst_stride_x * number of elements along X processed per workitem(in bytes)</span></div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;<span class="comment"> * @param[in]  dst_stride_y                      Stride of the destination image in Y dimension (in bytes)</span></div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;<span class="comment"> * @param[in]  dst_step_y                        dst_stride_y * number of elements along Y processed per workitem(in bytes)</span></div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;<span class="comment"> * @param[in]  dst_stride_z                      Stride of the source tensor in Z dimension (in bytes)</span></div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;<span class="comment"> * @param[in]  dst_step_z                        dst_stride_z * number of elements along Z processed per workitem(in bytes)</span></div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;<span class="comment"> * @param[in]  dst_offset_first_element_in_bytes The offset of the first element in the destination image</span></div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00107"></a><span class="lineno"><a class="line" href="upsample__layer_8cl.xhtml#a72ea02685fbca407f07ae495159e5b2b">  107</a></span>&#160;__kernel <span class="keywordtype">void</span> <a class="code" href="upsample__layer_8cl.xhtml#a72ea02685fbca407f07ae495159e5b2b">upsample_layer_nhwc</a>(</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    <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#a989ab3e96426615bb98e04e0235088ca">src</a>),</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    <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#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>))</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;{</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</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#a989ab3e96426615bb98e04e0235088ca">src</a>);</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</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#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>);</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;<span class="preprocessor">#if defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    <span class="comment">// Check if access on width gets out of bounds</span></div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    <span class="comment">// If it does shift access vector to access elements within bounds</span></div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> xi_in  = (int)(get_global_id(0) * VEC_SIZE_IN);</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">int</span> xi_out = (int)(get_global_id(0) * VEC_SIZE_OUT);</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr -= max(xi_in - (<span class="keywordtype">int</span>)LAST_ACCESSED_X_IN, 0) * src_stride_x;</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.ptr -= max(xi_out - (<span class="keywordtype">int</span>)LAST_ACCESSED_X_OUT, 0) * dst_stride_x;</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;    <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, 16)</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    data = vload16(0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    vstore16(data, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 0, 0));</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    vstore16(data, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 0));</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    vstore16(data, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 0, 1));</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    vstore16(data, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 1));</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;<span class="preprocessor">#else  // !defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 0, 0)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 0)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 0, 1)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>, 0, 1, 1)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.ptr);</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;<span class="preprocessor">#endif // defined(VEC_SIZE_IN) &amp;&amp; defined(VEC_SIZE_OUT) &amp;&amp; defined(LAST_ACCESSED_X_IN) &amp;&amp; defined(LAST_ACCESSED_X_OUT)</span></div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;}</div><div class="ttc" id="convolution3x3_8cl_xhtml_afb8c72ce35c4a1f4a2588d6573e54aa1"><div class="ttname"><a href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a></div><div class="ttdeci">#define DATA_TYPE</div><div class="ttdef"><b>Definition:</b> <a href="convolution3x3_8cl_source.xhtml#l00027">convolution3x3.cl:27</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="upsample__layer_8cl_xhtml_a72ea02685fbca407f07ae495159e5b2b"><div class="ttname"><a href="upsample__layer_8cl.xhtml#a72ea02685fbca407f07ae495159e5b2b">upsample_layer_nhwc</a></div><div class="ttdeci">__kernel void upsample_layer_nhwc(__global uchar *src_ptr, uint src_stride_x, uint src_step_x, uint src_stride_y, uint src_step_y, uint src_stride_z, uint src_step_z, uint src_offset_first_element_in_bytes, __global uchar *dst_ptr, uint dst_stride_x, uint dst_step_x, uint dst_stride_y, uint dst_step_y, uint dst_stride_z, uint dst_step_z, uint dst_offset_first_element_in_bytes)</div><div class="ttdoc">This function applies upsample on an input image.</div><div class="ttdef"><b>Definition:</b> <a href="upsample__layer_8cl_source.xhtml#l00107">upsample_layer.cl:107</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_adbf67dcee294e673cf796f1ed8aeb6a4"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">arm_compute::test::validation::dst</a></div><div class="ttdeci">CLTensor dst</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00102">AbsoluteDifference.cpp:102</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>
+<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="upsample__layer_8cl_xhtml_a4f89158c7add6565fb016b46d3a5c33b"><div class="ttname"><a href="upsample__layer_8cl.xhtml#a4f89158c7add6565fb016b46d3a5c33b">upsample_layer_nchw</a></div><div class="ttdeci">__kernel void upsample_layer_nchw(__global uchar *src_ptr, uint src_stride_x, uint src_step_x, uint src_stride_y, uint src_step_y, uint src_stride_z, uint src_step_z, uint src_offset_first_element_in_bytes, __global uchar *dst_ptr, uint dst_stride_x, uint dst_step_x, uint dst_stride_y, uint dst_step_y, uint dst_stride_z, uint dst_step_z, uint dst_offset_first_element_in_bytes)</div><div class="ttdoc">This function applies upsample on an input image.</div><div class="ttdef"><b>Definition:</b> <a href="upsample__layer_8cl_source.xhtml#l00052">upsample_layer.cl:52</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_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_a2101b2fe0193ce227ae4e0945e321d85"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a></div><div class="ttdeci">__global const uchar * tensor3D_offset(const Tensor3D *tensor, int x, int y, int z)</div><div class="ttdoc">Get the pointer position of a Tensor3D.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00340">helpers.h:340</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_a2101b2fe0193ce227ae4e0945e321d85"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a></div><div class="ttdeci">__global const uchar * tensor3D_offset(const Tensor3D *tensor, int x, int y, int z)</div><div class="ttdoc">Get the pointer position of a Tensor3D.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00522">helpers.h:522</a></div></div>
 <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a989ab3e96426615bb98e04e0235088ca"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">arm_compute::test::validation::src</a></div><div class="ttdeci">cast configure &amp; src</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_cast_8cpp_source.xhtml#l00169">Cast.cpp:169</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_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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