arm_compute v19.11
diff --git a/documentation/tile_8cl_source.xhtml b/documentation/tile_8cl_source.xhtml
index ae12fc5..2b9eb48 100644
--- a/documentation/tile_8cl_source.xhtml
+++ b/documentation/tile_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>
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</tr>
@@ -100,25 +100,27 @@
<div class="title">tile.cl</div> </div>
</div><!--header-->
<div class="contents">
-<a href="tile_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) 2018 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> <span class="preprocessor">#if defined(DATA_TYPE) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(SRC_DEPTH) && defined(DST_DEPTH)</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> __kernel <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a3744347976f5c2cb8f3ecd016a588454">tile</a>(</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a481bdc6d61b3df9dcdbdb244f0f97790">TENSOR4D_DECLARATION</a>(input),</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a481bdc6d61b3df9dcdbdb244f0f97790">TENSOR4D_DECLARATION</a>(output))</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="struct_tensor4_d.xhtml">Tensor4D</a> output = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a23b9032d1b9d59547545e457f82ee478">CONVERT_TO_TENSOR4D_STRUCT</a>(output, DST_DEPTH);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="struct_tensor4_d.xhtml">Tensor4D</a> input = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a302e05cc5f90bd76a9d0812c4be8b5eb">CONVERT_TO_TENSOR4D_STRUCT_NO_STEP</a>(input, SRC_DEPTH);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">// For all coordinates but x, each tile copies from the input</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> y = get_global_id(1);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> z = get_global_id(2) % DST_DEPTH;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> batch = get_global_id(2) / DST_DEPTH;</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(VEC_SIZE) && defined(OFFSET)</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// If we are loading/storing multiple elements at time, we need to</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// not exceed the input boundaries. The last threads need to backtrack</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// of OFFSET elements. Those elements cumulates for previous tiles</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> <span class="keywordtype">id</span> = (int)(get_global_id(0));</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordtype">int</span> x = <span class="keywordtype">id</span> * VEC_SIZE;</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">// Shift x based on the previous offsets</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> tile_number = x / SRC_WIDTH;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  x -= (tile_number) * OFFSET;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordtype">int</span> x_input = x % SRC_WIDTH;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// Shift x based on being the last tile</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> last_tile = (int)(x_input + VEC_SIZE > SRC_WIDTH);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  x -= last_tile * OFFSET;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  x_input = x % SRC_WIDTH;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  output.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> -= (tile_number + last_tile) * OFFSET * output_stride_x;</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">// Update the input pointer</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  input.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#ad442fb5ec8be1fff97f543150de5d822">tensor4D_offset</a>(&input, x_input, y % SRC_HEIGHT, z % SRC_DEPTH, batch % SRC_BATCHES);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="comment">// Copy the data</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <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>, VEC_SIZE)</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  data = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a287e2fc366c312b468382c95bb90f91f">VLOAD</a>(VEC_SIZE)(0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)input.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div><div class="line"><a name="l00086"></a><span class="lineno"> 86</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="l00087"></a><span class="lineno"> 87</span>  (data, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)output.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="preprocessor">#else // !defined(VEC_SIZE) || !defined(OFFSET)</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> x = get_global_id(0);</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="comment">// Update the input pointer</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  input.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#ad442fb5ec8be1fff97f543150de5d822">tensor4D_offset</a>(&input, x % SRC_WIDTH, y % SRC_HEIGHT, z % SRC_DEPTH, batch % SRC_BATCHES);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(output.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(input.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>));</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="preprocessor">#endif // defined(VEC_SIZE) && defined(OFFSET)</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> }</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="preprocessor">#endif // defined(DATA_TYPE) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(SRC_DEPTH) && defined(DST_DEPTH)</span></div><div class="ttc" id="struct_tensor4_d_xhtml_acf52c23cbd7424606c10a606524e3e32"><div class="ttname"><a href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">Tensor4D::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#l00188">helpers.h:188</a></div></div>
+<a href="tile_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) 2018 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> <span class="preprocessor">#if defined(DATA_TYPE) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(SRC_DEPTH) && defined(DST_DEPTH)</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="comment">/** Perform a floor operation on an input tensor.</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"> * @attention Data type can be passed using the -DDATA_TYPE compile flag, e.g. -DDATA_TYPE=float</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment"> * @attention 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="l00030"></a><span class="lineno"> 30</span> <span class="comment"> * @note Can only take floating point data types.</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"> *</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"> * @param[in] input_ptr Pointer to the source image. Supported data types: F16/F32</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> * @param[in] input_stride_x Stride of the source image in X dimension (in bytes)</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</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="l00035"></a><span class="lineno"> 35</span> <span class="comment"> * @param[in] input_stride_y Stride of the source image in Y dimension (in bytes)</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</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="l00037"></a><span class="lineno"> 37</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="l00038"></a><span class="lineno"> 38</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="l00039"></a><span class="lineno"> 39</span> <span class="comment"> * @param[in] input_offset_first_element_in_bytes The offset of the first element in the source image</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment"> * @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment"> * @param[in] output_stride_x Stride of the destination image in X dimension (in bytes)</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</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="l00043"></a><span class="lineno"> 43</span> <span class="comment"> * @param[in] output_stride_y Stride of the destination image in Y dimension (in bytes)</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</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="l00045"></a><span class="lineno"> 45</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="l00046"></a><span class="lineno"> 46</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="l00047"></a><span class="lineno"> 47</span> <span class="comment"> * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination image</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="comment"> */</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> __kernel <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a3744347976f5c2cb8f3ecd016a588454">tile</a>(</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a481bdc6d61b3df9dcdbdb244f0f97790">TENSOR4D_DECLARATION</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>),</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a481bdc6d61b3df9dcdbdb244f0f97790">TENSOR4D_DECLARATION</a>(output))</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="struct_tensor4_d.xhtml">Tensor4D</a> output = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a23b9032d1b9d59547545e457f82ee478">CONVERT_TO_TENSOR4D_STRUCT</a>(output, DST_DEPTH);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="struct_tensor4_d.xhtml">Tensor4D</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#a302e05cc5f90bd76a9d0812c4be8b5eb">CONVERT_TO_TENSOR4D_STRUCT_NO_STEP</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, SRC_DEPTH);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">// For all coordinates but x, each tile copies from the input</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> y = get_global_id(1);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> z = get_global_id(2) % DST_DEPTH;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> batch = get_global_id(2) / DST_DEPTH;</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(VEC_SIZE) && defined(OFFSET)</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// If we are loading/storing multiple elements at time, we need to</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// not exceed the input boundaries. The last threads need to backtrack</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// of OFFSET elements. Those elements cumulates for previous tiles</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> <span class="keywordtype">id</span> = (int)(get_global_id(0));</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordtype">int</span> x = <span class="keywordtype">id</span> * <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>;</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">// Shift x based on the previous offsets</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> tile_number = x / SRC_WIDTH;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  x -= (tile_number) * OFFSET;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordtype">int</span> x_input = x % SRC_WIDTH;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// Shift x based on being the last tile</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> last_tile = (int)(x_input + <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a> > SRC_WIDTH);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  x -= last_tile * OFFSET;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  x_input = x % SRC_WIDTH;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  output.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> -= (tile_number + last_tile) * OFFSET * output_stride_x;</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">// Update the input pointer</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <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#ad442fb5ec8be1fff97f543150de5d822">tensor4D_offset</a>(&<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, x_input, y % SRC_HEIGHT, z % SRC_DEPTH, batch % SRC_BATCHES);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="comment">// Copy the data</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <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>, <a class="code" href="depthwise__convolution__quantized_8cl.xhtml#a3fffea119c04c7680f2e9cf3fadf63b4">VEC_SIZE</a>)</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  data = <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 <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div><div class="line"><a name="l00086"></a><span class="lineno"> 86</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="l00087"></a><span class="lineno"> 87</span>  (data, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)output.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="preprocessor">#else // !defined(VEC_SIZE) || !defined(OFFSET)</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> x = get_global_id(0);</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="comment">// Update the input pointer</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <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#ad442fb5ec8be1fff97f543150de5d822">tensor4D_offset</a>(&<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>, x % SRC_WIDTH, y % SRC_HEIGHT, z % SRC_DEPTH, batch % SRC_BATCHES);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(output.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>)) = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8fcf2ddd9a1d58b1b280f5c0aed71845">input</a>.ptr));</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="preprocessor">#endif // defined(VEC_SIZE) && defined(OFFSET)</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> }</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="preprocessor">#endif // defined(DATA_TYPE) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(SRC_DEPTH) && defined(DST_DEPTH)</span></div><div class="ttc" id="struct_tensor4_d_xhtml_acf52c23cbd7424606c10a606524e3e32"><div class="ttname"><a href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">Tensor4D::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#l00370">helpers.h:370</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="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_tensor4_d_xhtml"><div class="ttname"><a href="struct_tensor4_d.xhtml">Tensor4D</a></div><div class="ttdoc">Structure to hold 4D tensor information.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00186">helpers.h:186</a></div></div>
-<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a302e05cc5f90bd76a9d0812c4be8b5eb"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a302e05cc5f90bd76a9d0812c4be8b5eb">CONVERT_TO_TENSOR4D_STRUCT_NO_STEP</a></div><div class="ttdeci">#define CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(name, mod_size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00155">helpers.h:155</a></div></div>
-<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_ad442fb5ec8be1fff97f543150de5d822"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#ad442fb5ec8be1fff97f543150de5d822">tensor4D_offset</a></div><div class="ttdeci">__global const uchar * tensor4D_offset(const Tensor4D *tensor, int x, int y, int z, int w)</div><div class="ttdoc">Get the pointer position of a Tensor4D.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00353">helpers.h:353</a></div></div>
-<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a23b9032d1b9d59547545e457f82ee478"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a23b9032d1b9d59547545e457f82ee478">CONVERT_TO_TENSOR4D_STRUCT</a></div><div class="ttdeci">#define CONVERT_TO_TENSOR4D_STRUCT(name, mod_size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00151">helpers.h:151</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="struct_tensor4_d_xhtml"><div class="ttname"><a href="struct_tensor4_d.xhtml">Tensor4D</a></div><div class="ttdoc">Structure to hold 4D tensor information.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00368">helpers.h:368</a></div></div>
+<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a302e05cc5f90bd76a9d0812c4be8b5eb"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a302e05cc5f90bd76a9d0812c4be8b5eb">CONVERT_TO_TENSOR4D_STRUCT_NO_STEP</a></div><div class="ttdeci">#define CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(name, mod_size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00337">helpers.h:337</a></div></div>
+<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_ad442fb5ec8be1fff97f543150de5d822"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#ad442fb5ec8be1fff97f543150de5d822">tensor4D_offset</a></div><div class="ttdeci">__global const uchar * tensor4D_offset(const Tensor4D *tensor, int x, int y, int z, int w)</div><div class="ttdoc">Get the pointer position of a Tensor4D.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00535">helpers.h:535</a></div></div>
+<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a23b9032d1b9d59547545e457f82ee478"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a23b9032d1b9d59547545e457f82ee478">CONVERT_TO_TENSOR4D_STRUCT</a></div><div class="ttdeci">#define CONVERT_TO_TENSOR4D_STRUCT(name, mod_size)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00333">helpers.h:333</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_a3744347976f5c2cb8f3ecd016a588454"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#a3744347976f5c2cb8f3ecd016a588454">arm_compute::test::validation::reference::tile</a></div><div class="ttdeci">SimpleTensor< T > tile(const SimpleTensor< T > &src, const Multiples &multiples)</div><div class="ttdef"><b>Definition:</b> <a href="reference_2_tile_8cpp_source.xhtml#l00038">Tile.cpp:38</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="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a481bdc6d61b3df9dcdbdb244f0f97790"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a481bdc6d61b3df9dcdbdb244f0f97790">TENSOR4D_DECLARATION</a></div><div class="ttdeci">#define TENSOR4D_DECLARATION(name)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00111">helpers.h:111</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_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="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a481bdc6d61b3df9dcdbdb244f0f97790"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a481bdc6d61b3df9dcdbdb244f0f97790">TENSOR4D_DECLARATION</a></div><div class="ttdeci">#define TENSOR4D_DECLARATION(name)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00293">helpers.h:293</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_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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