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gerrit-public.fairphone.software / platform / external / ComputeLibrary / 8938bd3f40ea62ff56d6ed4e2db0a8aee34dd64a / . / documentation / direct__convolution5x5_8cl_source.xhtml
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115<div class="title">direct_convolution5x5.cl</div> </div>
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117<div class="contents">
118<a href="direct__convolution5x5_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>
119<div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment"> * Copyright (c) 2016, 2017 ARM Limited.</span></div>
120<div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div>
121<div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div>
122<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> *</span></div>
123<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>
124<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>
125<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>
126<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>
127<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>
128<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>
129<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> *</span></div>
130<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>
131<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>
132<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> *</span></div>
133<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>
134<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>
135<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>
136<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>
137<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>
138<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>
139<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"> * SOFTWARE.</span></div>
140<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> */</span></div>
141<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="helpers_8h.xhtml">helpers.h</a>&quot;</span></div>
142<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;</div>
143<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="preprocessor">#undef CONVERT_SAT</span></div>
144<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="preprocessor"></span></div>
145<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="preprocessor">#if defined(DATA_TYPE) &amp;&amp; defined(STRIDE_X) &amp;&amp; defined(WEIGHTS_DEPTH)</span></div>
146<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;<span class="preprocessor"></span></div>
147<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="preprocessor">#if STRIDE_X == 1</span></div>
148<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#define CONVOLUTION1x5(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x5_STRIDE1(acc, src_row_ptr, weights_row_ptr)</span></div>
149<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#elif STRIDE_X == 2 </span><span class="comment">/* STRIDE_X == 1 */</span><span class="preprocessor"></span></div>
150<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#define CONVOLUTION1x5(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x5_STRIDE2(acc, src_row_ptr, weights_row_ptr)</span></div>
151<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#else </span><span class="comment">/* STRIDE_X not equals 1 or 2 */</span><span class="preprocessor"></span></div>
152<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#error &quot;STRIDE_X larger than 2 is not supported&quot;</span></div>
153<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#endif </span><span class="comment">/* STRIDE_X == 2 */</span><span class="preprocessor"></span></div>
154<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;<span class="preprocessor"></span></div>
155<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;<span class="preprocessor">#define CONVOLUTION1x5_STRIDE1(acc, src_row_ptr, weights_row_ptr) \</span></div>
156<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;<span class="preprocessor"> ({ \</span></div>
157<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;<span class="preprocessor"> VEC_DATA_TYPE(DATA_TYPE, 4) \</span></div>
158<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160;<span class="preprocessor"> weights_values0 = vload4(0, weights_row_ptr); \</span></div>
159<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160;<span class="preprocessor"> DATA_TYPE weights_value1 = *(weights_row_ptr + 4); \</span></div>
160<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;<span class="preprocessor"> VEC_DATA_TYPE(DATA_TYPE, 8) \</span></div>
161<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;<span class="preprocessor"> src0 = vload8(0, src_row_ptr); \</span></div>
162<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160;<span class="preprocessor"> VEC_DATA_TYPE(DATA_TYPE, 4) \</span></div>
163<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;<span class="preprocessor"> src1 = vload4(0, src_row_ptr + 8); \</span></div>
164<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160;<span class="preprocessor"> \</span></div>
165<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160;<span class="preprocessor"> acc += src0 * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s0; \</span></div>
166<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;<span class="preprocessor"> acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s1234, src0.s567, src1.s0) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s1; \</span></div>
167<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160;<span class="preprocessor"> acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s234, src0.s567, src1.s01) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s2; \</span></div>
168<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;<span class="preprocessor"> acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s345, src0.s67, src1.s012) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s3; \</span></div>
169<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160;<span class="preprocessor"> acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s45, src0.s67, src1.s0123) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_value1; \</span></div>
170<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160;<span class="preprocessor"> })</span></div>
171<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160;<span class="preprocessor"></span></div>
172<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;<span class="preprocessor">#define CONVOLUTION1x5_STRIDE2(acc, src_row_ptr, weights_row_ptr) \</span></div>
173<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160;<span class="preprocessor"> ({ \</span></div>
174<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;<span class="preprocessor"> VEC_DATA_TYPE(DATA_TYPE, 4) \</span></div>
175<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160;<span class="preprocessor"> weights_values0 = vload4(0, weights_row_ptr); \</span></div>
176<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160;<span class="preprocessor"> DATA_TYPE weights_value1 = *(weights_row_ptr + 4); \</span></div>
177<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160;<span class="preprocessor"> VEC_DATA_TYPE(DATA_TYPE, 16) \</span></div>
178<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160;<span class="preprocessor"> src0 = vload16(0, src_row_ptr); \</span></div>
179<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160;<span class="preprocessor"> VEC_DATA_TYPE(DATA_TYPE, 4) \</span></div>
180<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160;<span class="preprocessor"> src1 = vload4(0, src_row_ptr + 16); \</span></div>
181<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160;<span class="preprocessor"> acc += src0.even * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s0; \</span></div>
182<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160;<span class="preprocessor"> acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s1357, src0.s9BDF) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s1; \</span></div>
183<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160;<span class="preprocessor"> acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s2468, src0.sACE, src1.s0) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s2; \</span></div>
184<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160;<span class="preprocessor"> \</span></div>
185<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160;<span class="preprocessor"> acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s3579, src0.sBDF, src1.s1) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s3; \</span></div>
186<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160;<span class="preprocessor"> acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s468a, src0.sCE, src1.s02) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_value1; \</span></div>
187<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;<span class="preprocessor"> })</span></div>
188<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160;<span class="preprocessor"></span></div>
189<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160;__kernel <span class="keywordtype">void</span> direct_convolution5x5(</div>
190<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <a class="code" href="helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(src),</div>
191<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <a class="code" href="helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(dst),</div>
192<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <a class="code" href="helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(weights),</div>
193<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160;#ifdef HAS_BIAS</div>
194<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <a class="code" href="helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(biases),</div>
195<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160;#endif <span class="comment">/* defined(HAS_BIAS) */</span></div>
196<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weights_stride_w)</div>
197<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160;{</div>
198<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <a class="code" href="struct_image.xhtml">Image</a> src = <a class="code" href="helpers_8h.xhtml#aebe814363556c244be043b13e7969197">CONVERT_TO_IMAGE_STRUCT</a>(src);</div>
199<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> weights = <a class="code" href="helpers_8h.xhtml#a79e8e562daa6599317d2d1cd86ef1bf2">CONVERT_TO_TENSOR3D_STRUCT_NO_STEP</a>(weights);</div>
200<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> dst = <a class="code" href="helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(dst);</div>
201<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;</div>
202<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <a class="code" href="fixed__point_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, 8)</div>
203<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; pixels0 = 0;</div>
204<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160;</div>
205<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; __global uchar *weights_addr = (__global uchar *)<a class="code" href="helpers_8h.xhtml#a2101b2fe0193ce227ae4e0945e321d85">tensor3D_offset</a>(&amp;weights, 0, 0, 0);</div>
206<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; __global uchar *src_addr = (__global uchar *)<a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>(&amp;src, 0, 0);</div>
207<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160;</div>
208<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; const <span class="keywordtype">int</span> kernel_index = get_global_id(2);</div>
209<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; weights_addr += kernel_index * weights_stride_w;</div>
210<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160;</div>
211<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; for(<span class="keywordtype">int</span> d = 0; d &lt; WEIGHTS_DEPTH; ++d)</div>
212<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; {</div>
213<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; CONVOLUTION1x5(pixels0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)src_addr, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)weights_addr);</div>
214<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; CONVOLUTION1x5(pixels0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(src_addr + 1 * src_stride_y), (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(weights_addr + 1 * weights_stride_y));</div>
215<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; CONVOLUTION1x5(pixels0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(src_addr + 2 * src_stride_y), (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(weights_addr + 2 * weights_stride_y));</div>
216<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; CONVOLUTION1x5(pixels0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(src_addr + 3 * src_stride_y), (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(weights_addr + 3 * weights_stride_y));</div>
217<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; CONVOLUTION1x5(pixels0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(src_addr + 4 * src_stride_y), (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(weights_addr + 4 * weights_stride_y));</div>
218<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160;</div>
219<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; src_addr += src_stride_z;</div>
220<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; weights_addr += weights_stride_z;</div>
221<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; }</div>
222<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160;</div>
223<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160;<span class="preprocessor">#ifdef HAS_BIAS</span></div>
224<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160;<span class="preprocessor"></span> <a class="code" href="struct_vector.xhtml">Vector</a> biases = <a class="code" href="helpers_8h.xhtml#a64d779f80eeb923e0ab2313433f7b40b">CONVERT_TO_VECTOR_STRUCT_NO_STEP</a>(biases);</div>
225<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160;</div>
226<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; pixels0 += (<a class="code" href="fixed__point_8h.xhtml#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, 8)) * ((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(<a class="code" href="helpers_8h.xhtml#a7e4940407322d6f0ccb8b6b86b856019">vector_offset</a>(&amp;biases, kernel_index)));</div>
227<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* defined(HAS_BIAS) */</span><span class="preprocessor"></span></div>
228<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160;<span class="preprocessor"></span></div>
229<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; vstore8(pixels0, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)dst.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div>
230<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160;}</div>
231<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160;<span class="preprocessor">#endif // defined(DATA_TYPE) &amp;&amp; defined(STRIDE_X) &amp;&amp; defined(WEIGHTS_DEPTH)</span></div>
232<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160;<span class="preprocessor"></span></div>
233<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160;<span class="preprocessor">#if defined(WEIGHTS_DEPTH)</span></div>
234<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160;<span class="preprocessor"></span></div>
235<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160;<span class="preprocessor">#define CONVOLUTION1x5_BIFROST(acc, src0, weights_row00, weights_row01) \</span></div>
236<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160;<span class="preprocessor"> ({ \</span></div>
237<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160;<span class="preprocessor"> acc.s0 = mad(src0.s0, weights_row00.s0, acc.s0); \</span></div>
238<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160;<span class="preprocessor"> acc.s1 = mad(src0.s1, weights_row00.s0, acc.s1); \</span></div>
239<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160;<span class="preprocessor"> acc.s2 = mad(src0.s2, weights_row00.s0, acc.s2); \</span></div>
240<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160;<span class="preprocessor"> acc.s3 = mad(src0.s3, weights_row00.s0, acc.s3); \</span></div>
241<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160;<span class="preprocessor"> acc.s0 = mad(src0.s1, weights_row00.s1, acc.s0); \</span></div>
242<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160;<span class="preprocessor"> acc.s1 = mad(src0.s2, weights_row00.s1, acc.s1); \</span></div>
243<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160;<span class="preprocessor"> acc.s2 = mad(src0.s3, weights_row00.s1, acc.s2); \</span></div>
244<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160;<span class="preprocessor"> acc.s3 = mad(src0.s4, weights_row00.s1, acc.s3); \</span></div>
245<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160;<span class="preprocessor"> acc.s0 = mad(src0.s2, weights_row00.s2, acc.s0); \</span></div>
246<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160;<span class="preprocessor"> acc.s1 = mad(src0.s3, weights_row00.s2, acc.s1); \</span></div>
247<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160;<span class="preprocessor"> acc.s2 = mad(src0.s4, weights_row00.s2, acc.s2); \</span></div>
248<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160;<span class="preprocessor"> acc.s3 = mad(src0.s5, weights_row00.s2, acc.s3); \</span></div>
249<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160;<span class="preprocessor"> acc.s0 = mad(src0.s3, weights_row00.s3, acc.s0); \</span></div>
250<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160;<span class="preprocessor"> acc.s1 = mad(src0.s4, weights_row00.s3, acc.s1); \</span></div>
251<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160;<span class="preprocessor"> acc.s2 = mad(src0.s5, weights_row00.s3, acc.s2); \</span></div>
252<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160;<span class="preprocessor"> acc.s3 = mad(src0.s6, weights_row00.s3, acc.s3); \</span></div>
253<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160;<span class="preprocessor"> acc.s0 = mad(src0.s4, weights_row01, acc.s0); \</span></div>
254<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160;<span class="preprocessor"> acc.s1 = mad(src0.s5, weights_row01, acc.s1); \</span></div>
255<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160;<span class="preprocessor"> acc.s2 = mad(src0.s6, weights_row01, acc.s2); \</span></div>
256<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160;<span class="preprocessor"> acc.s3 = mad(src0.s7, weights_row01, acc.s3); \</span></div>
257<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160;<span class="preprocessor"> })</span></div>
258<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160;<span class="preprocessor"></span></div>
259<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160;__kernel <span class="keywordtype">void</span> direct_convolution5x5_f32_bifrost(</div>
260<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; <a class="code" href="helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(src),</div>
261<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; <a class="code" href="helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(dst),</div>
262<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; <a class="code" href="helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(weights),</div>
263<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160;#ifdef HAS_BIAS</div>
264<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; <a class="code" href="helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(biases),</div>
265<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160;#endif <span class="comment">/* defined(HAS_BIAS) */</span></div>
266<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weights_stride_w)</div>
267<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160;{</div>
268<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; <span class="comment">// Get the kernel index</span></div>
269<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> kernel_index = get_global_id(2);</div>
270<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160;</div>
271<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; <a class="code" href="struct_image.xhtml">Image</a> src = <a class="code" href="helpers_8h.xhtml#aebe814363556c244be043b13e7969197">CONVERT_TO_IMAGE_STRUCT</a>(src);</div>
272<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> dst = <a class="code" href="helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(dst);</div>
273<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160;</div>
274<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; float4 pixels0 = 0.0f;</div>
275<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; float4 pixels1 = 0.0f;</div>
276<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160;</div>
277<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160; __global uchar *weights_addr = (__global uchar *)(weights_ptr + weights_offset_first_element_in_bytes + kernel_index * weights_stride_w);</div>
278<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; __global uchar *src_addr = (__global uchar *)<a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>(&amp;src, 0, 0);</div>
279<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160;</div>
280<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; <span class="comment">// Note: Since each work-item computes 4x2 elements, we need to load 6 rows from the input tensor</span></div>
281<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160;</div>
282<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160; <span class="keywordflow">for</span>(ushort d = 0; d &lt; (ushort)WEIGHTS_DEPTH; ++d)</div>
283<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; {</div>
284<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; <span class="comment">// Load the weights from row0 and row1</span></div>
285<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; float4 weights_row00 = vload4(0, (__global <span class="keywordtype">float</span> *)(weights_addr + 0 * weights_stride_y));</div>
286<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; <span class="keywordtype">float</span> weights_row01 = *((__global <span class="keywordtype">float</span> *)(weights_addr + 0 * weights_stride_y) + 4);</div>
287<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; float4 weights_row10 = vload4(0, (__global <span class="keywordtype">float</span> *)(weights_addr + 1 * weights_stride_y));</div>
288<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; <span class="keywordtype">float</span> weights_row11 = *((__global <span class="keywordtype">float</span> *)(weights_addr + 1 * weights_stride_y) + 4);</div>
289<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; float8 src0;</div>
290<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160;</div>
291<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; <span class="comment">// Load values from row0 of input tensor</span></div>
292<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; src0 = vload8(0, (__global <span class="keywordtype">float</span> *)(src_addr + 0 * src_stride_y));</div>
293<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160;</div>
294<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; <span class="comment">// Accumulate</span></div>
295<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; CONVOLUTION1x5_BIFROST(pixels0, src0, weights_row00, weights_row01);</div>
296<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160;</div>
297<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; <span class="comment">// Load values from row1 of input tensor</span></div>
298<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; src0 = vload8(0, (__global <span class="keywordtype">float</span> *)(src_addr + 1 * src_stride_y));</div>
299<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160;</div>
300<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; <span class="comment">// Accumulate</span></div>
301<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; CONVOLUTION1x5_BIFROST(pixels0, src0, weights_row10, weights_row11);</div>
302<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; CONVOLUTION1x5_BIFROST(pixels1, src0, weights_row00, weights_row01);</div>
303<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160;</div>
304<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; <span class="comment">// Load values from row2 of input tensor</span></div>
305<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; src0 = vload8(0, (__global <span class="keywordtype">float</span> *)(src_addr + 2 * src_stride_y));</div>
306<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160;</div>
307<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; <span class="comment">// Load weights from row2</span></div>
308<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; weights_row00 = vload4(0, (__global <span class="keywordtype">float</span> *)(weights_addr + 2 * weights_stride_y));</div>
309<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; weights_row01 = *((__global <span class="keywordtype">float</span> *)(weights_addr + 2 * weights_stride_y) + 4);</div>
310<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160;</div>
311<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; <span class="comment">// Accumulate</span></div>
312<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; CONVOLUTION1x5_BIFROST(pixels0, src0, weights_row00, weights_row01);</div>
313<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; CONVOLUTION1x5_BIFROST(pixels1, src0, weights_row10, weights_row11);</div>
314<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160;</div>
315<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; <span class="comment">// Load values from row3 of input tensor</span></div>
316<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; src0 = vload8(0, (__global <span class="keywordtype">float</span> *)(src_addr + 3 * src_stride_y));</div>
317<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160;</div>
318<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; <span class="comment">// Load weights from row3</span></div>
319<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; weights_row10 = vload4(0, (__global <span class="keywordtype">float</span> *)(weights_addr + 3 * weights_stride_y));</div>
320<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; weights_row11 = *((__global <span class="keywordtype">float</span> *)(weights_addr + 3 * weights_stride_y) + 4);</div>
321<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160;</div>
322<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160; <span class="comment">// Accumulate</span></div>
323<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; CONVOLUTION1x5_BIFROST(pixels0, src0, weights_row10, weights_row11);</div>
324<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; CONVOLUTION1x5_BIFROST(pixels1, src0, weights_row00, weights_row01);</div>
325<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160;</div>
326<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; <span class="comment">// Load values from row4 of input tensor</span></div>
327<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; src0 = vload8(0, (__global <span class="keywordtype">float</span> *)(src_addr + 4 * src_stride_y));</div>
328<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160;</div>
329<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; <span class="comment">// Load weights from row4</span></div>
330<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; weights_row00 = vload4(0, (__global <span class="keywordtype">float</span> *)(weights_addr + 4 * weights_stride_y));</div>
331<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; weights_row01 = *((__global <span class="keywordtype">float</span> *)(weights_addr + 4 * weights_stride_y) + 4);</div>
332<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160;</div>
333<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; CONVOLUTION1x5_BIFROST(pixels0, src0, weights_row00, weights_row01);</div>
334<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; CONVOLUTION1x5_BIFROST(pixels1, src0, weights_row10, weights_row11);</div>
335<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160;</div>
336<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; <span class="comment">// Load values from row5 of input tensor</span></div>
337<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; src0 = vload8(0, (__global <span class="keywordtype">float</span> *)(src_addr + 5 * src_stride_y));</div>
338<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160;</div>
339<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; <span class="comment">// Accumulate</span></div>
340<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; CONVOLUTION1x5_BIFROST(pixels1, src0, weights_row00, weights_row01);</div>
341<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160;</div>
342<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; src_addr += src_stride_z;</div>
343<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; weights_addr += weights_stride_z;</div>
344<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; }</div>
345<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160;</div>
346<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160;<span class="preprocessor">#ifdef HAS_BIAS</span></div>
347<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160;<span class="preprocessor"></span> <a class="code" href="struct_vector.xhtml">Vector</a> biases = <a class="code" href="helpers_8h.xhtml#a64d779f80eeb923e0ab2313433f7b40b">CONVERT_TO_VECTOR_STRUCT_NO_STEP</a>(biases);</div>
348<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160;</div>
349<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; float4 bias = (float4) * ((__global <span class="keywordtype">float</span> *)(<a class="code" href="helpers_8h.xhtml#a7e4940407322d6f0ccb8b6b86b856019">vector_offset</a>(&amp;biases, kernel_index)));</div>
350<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160;</div>
351<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; pixels0 += bias;</div>
352<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; pixels1 += bias;</div>
353<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* defined(HAS_BIAS) */</span><span class="preprocessor"></span></div>
354<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160;<span class="preprocessor"></span></div>
355<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160; vstore4(pixels0, 0, (__global <span class="keywordtype">float</span> *)(dst.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + 0 * dst_stride_y));</div>
356<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160; vstore4(pixels1, 0, (__global <span class="keywordtype">float</span> *)(dst.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + 1 * dst_stride_y));</div>
357<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160;}</div>
358<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160;<span class="preprocessor">#endif // defined(WEIGHTS_DEPTH)</span></div>
359<div class="ttc" id="struct_vector_xhtml"><div class="ttname"><a href="struct_vector.xhtml">Vector</a></div><div class="ttdoc">Structure to hold Vector information. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00123">helpers.h:123</a></div></div>
360<div class="ttc" id="helpers_8h_xhtml_a31c8c760f08fb1a331b16b7c204321dc"><div class="ttname"><a href="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="helpers_8h_source.xhtml#l00108">helpers.h:108</a></div></div>
361<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>
362<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="helpers_8h_source.xhtml#l00140">helpers.h:140</a></div></div>
363<div class="ttc" id="helpers_8h_xhtml_a009469e4d9b8fce3b6d5e97d2077827d"><div class="ttname"><a href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a></div><div class="ttdeci">__global uchar * offset(const Image *img, int x, int y)</div><div class="ttdoc">Get the pointer position of a Image. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00292">helpers.h:292</a></div></div>
364<div class="ttc" id="helpers_8h_xhtml"><div class="ttname"><a href="helpers_8h.xhtml">helpers.h</a></div></div>
365<div class="ttc" id="helpers_8h_xhtml_aebe814363556c244be043b13e7969197"><div class="ttname"><a href="helpers_8h.xhtml#aebe814363556c244be043b13e7969197">CONVERT_TO_IMAGE_STRUCT</a></div><div class="ttdeci">#define CONVERT_TO_IMAGE_STRUCT(name)</div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00093">helpers.h:93</a></div></div>
366<div class="ttc" id="helpers_8h_xhtml_a2101b2fe0193ce227ae4e0945e321d85"><div class="ttname"><a href="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="helpers_8h_source.xhtml#l00304">helpers.h:304</a></div></div>
367<div class="ttc" id="helpers_8h_xhtml_a40a6eb9f2a7712f08d6bb8ff6c9e6ca7"><div class="ttname"><a href="helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a></div><div class="ttdeci">#define VECTOR_DECLARATION(name)</div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00051">helpers.h:51</a></div></div>
368<div class="ttc" id="struct_image_xhtml"><div class="ttname"><a href="struct_image.xhtml">Image</a></div><div class="ttdoc">Structure to hold Image information. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00131">helpers.h:131</a></div></div>
369<div class="ttc" id="helpers_8h_xhtml_a6b83038822d1ae7ab619b684ed3b7fc0"><div class="ttname"><a href="helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a></div><div class="ttdeci">#define TENSOR3D_DECLARATION(name)</div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00065">helpers.h:65</a></div></div>
370<div class="ttc" id="fixed__point_8h_xhtml_a36f754c05b6fddf6df0d8d0a74f8159f"><div class="ttname"><a href="fixed__point_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="fixed__point_8h_source.xhtml#l00093">fixed_point.h:93</a></div></div>
371<div class="ttc" id="helpers_8h_xhtml_a79e8e562daa6599317d2d1cd86ef1bf2"><div class="ttname"><a href="helpers_8h.xhtml#a79e8e562daa6599317d2d1cd86ef1bf2">CONVERT_TO_TENSOR3D_STRUCT_NO_STEP</a></div><div class="ttdeci">#define CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(name)</div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00112">helpers.h:112</a></div></div>
372<div class="ttc" id="helpers_8h_xhtml_a64d779f80eeb923e0ab2313433f7b40b"><div class="ttname"><a href="helpers_8h.xhtml#a64d779f80eeb923e0ab2313433f7b40b">CONVERT_TO_VECTOR_STRUCT_NO_STEP</a></div><div class="ttdeci">#define CONVERT_TO_VECTOR_STRUCT_NO_STEP(name)</div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00090">helpers.h:90</a></div></div>
373<div class="ttc" id="helpers_8h_xhtml_a7e4940407322d6f0ccb8b6b86b856019"><div class="ttname"><a href="helpers_8h.xhtml#a7e4940407322d6f0ccb8b6b86b856019">vector_offset</a></div><div class="ttdeci">__global const uchar * vector_offset(const Vector *vec, int x)</div><div class="ttdoc">Get the pointer position of a Vector. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00281">helpers.h:281</a></div></div>
374<div class="ttc" id="struct_tensor3_d_xhtml_acf52c23cbd7424606c10a606524e3e32"><div class="ttname"><a href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">Tensor3D::ptr</a></div><div class="ttdeci">__global uchar * ptr</div><div class="ttdoc">Pointer to the starting postion of the buffer. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00142">helpers.h:142</a></div></div>
375</div><!-- fragment --></div><!-- contents -->
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379 <ul>
380 <li class="navelem"><a class="el" href="dir_55b5a5006e943fb664ff8cff3cfe7768.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_f6c3ae42d7e27145d0a3c3e38ca1c000.xhtml">core</a></li><li class="navelem"><a class="el" href="dir_1b7ae9123c88e650426d50d95c19d414.xhtml">CL</a></li><li class="navelem"><a class="el" href="dir_b7c3d80b0dadb2139bc73b7161751c12.xhtml">cl_kernels</a></li><li class="navelem"><a class="el" href="direct__convolution5x5_8cl.xhtml">direct_convolution5x5.cl</a></li>
381 <li class="footer">Generated on Thu Sep 28 2017 14:37:50 for Compute Library by
382 <a href="http://www.doxygen.org/index.html">
383 <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.6 </li>
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