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<a href="batchnormalization__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) 2017-2018 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="l00026"></a><span class="lineno"><a class="line" href="batchnormalization__layer_8cl.xhtml#aebbeb1f22eca3a3f4c3e019e8f419f39"> 26</a></span>&#160;<span class="preprocessor">#define ADD_OP(a, b) ((a) + (b))</span></div><div class="line"><a name="l00027"></a><span class="lineno"><a class="line" href="batchnormalization__layer_8cl.xhtml#ad778425e4131c4731f17d7e6e3499a07"> 27</a></span>&#160;<span class="preprocessor">#define SUB_OP(a, b) ((a) - (b))</span></div><div class="line"><a name="l00028"></a><span class="lineno"><a class="line" href="batchnormalization__layer_8cl.xhtml#ad3cc858846806e6b1d3694b9d0a2e6da"> 28</a></span>&#160;<span class="preprocessor">#define MUL_OP(a, b) ((a) * (b))</span></div><div class="line"><a name="l00029"></a><span class="lineno"><a class="line" href="batchnormalization__layer_8cl.xhtml#acbe0869c7899bc8d9f0e91a6249fa970"> 29</a></span>&#160;<span class="preprocessor">#define INVSQRT_OP(a) rsqrt((a))</span></div><div class="line"><a name="l00030"></a><span class="lineno"><a class="line" href="batchnormalization__layer_8cl.xhtml#a107d847044e677b01e9bd3d5251b39d9"> 30</a></span>&#160;<span class="preprocessor">#define SQCVT_SAT(a) (a)</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="preprocessor">#if defined(VEC_SIZE) &amp;&amp; defined(DATA_TYPE)</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="preprocessor">#if defined(FUSED_ACTIVATION)</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="activation__layer_8cl.xhtml">activation_layer.cl</a>&quot;</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;<span class="preprocessor">#define ACTIVATION_FUNC(x) ACTIVATION_OP(FUSED_ACTIVATION, x)</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;<span class="preprocessor">#else </span><span class="comment">/* defined(FUSED_ACTIVATION) */</span><span class="preprocessor"></span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;<span class="preprocessor">#define ACTIVATION_FUNC(x) (x)</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* defined(FUSED_ACTIVATION) */</span><span class="preprocessor"></span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160;__kernel <span class="keywordtype">void</span> batchnormalization_layer_nchw(<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(input),</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;#ifndef IN_PLACE</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(output),</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;#endif <span class="comment">/* not IN_PLACE */</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(mean),</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(var),</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160;#ifndef USE_DEFAULT_BETA</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(beta),</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160;#endif <span class="comment">/* USE_DEFAULT_BETA */</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160;#ifndef USE_DEFAULT_GAMMA</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(gamma),</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160;#endif <span class="comment">/* USE_DEFAULT_GAMMA */</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <span class="keywordtype">float</span> <a class="code" href="_asymm_helpers_8cpp.xhtml#a552dc3787d7ea1675f3e4e8993501d58">epsilon</a>)</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160;{</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> in = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(input);</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160;<span class="preprocessor">#ifdef IN_PLACE</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> out = in;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160;<span class="preprocessor">#else </span><span class="comment">/* IN_PLACE */</span><span class="preprocessor"></span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> out = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(output);</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* IN_PLACE */</span><span class="preprocessor"></span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> mean = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a527bfdf5eeb306f1cf01c4a8e29f38e0">CONVERT_TO_VECTOR_STRUCT</a>(mean);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> var = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a527bfdf5eeb306f1cf01c4a8e29f38e0">CONVERT_TO_VECTOR_STRUCT</a>(var);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_BETA</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> beta = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a527bfdf5eeb306f1cf01c4a8e29f38e0">CONVERT_TO_VECTOR_STRUCT</a>(beta);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_BETA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_GAMMA</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> gamma = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a527bfdf5eeb306f1cf01c4a8e29f38e0">CONVERT_TO_VECTOR_STRUCT</a>(gamma);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_GAMMA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</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>, VEC_SIZE)</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; data = 0;</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#a36f754c05b6fddf6df0d8d0a74f8159f">VEC_DATA_TYPE</a>(<a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a>, VEC_SIZE)</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; denominator = 0;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</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>, VEC_SIZE)</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; numerator = 0;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</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>, VEC_SIZE)</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; x_bar = 0;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</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>, VEC_SIZE)</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; res = 0;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> current_slice = get_global_id(2);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; 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> *)in.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; denominator = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(var.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * var.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; denominator = <a class="code" href="batchnormalization__layer_8cl.xhtml#acbe0869c7899bc8d9f0e91a6249fa970">INVSQRT_OP</a>(<a class="code" href="batchnormalization__layer_8cl.xhtml#aebbeb1f22eca3a3f4c3e019e8f419f39">ADD_OP</a>(denominator, ((<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))<a class="code" href="batchnormalization__layer_8cl.xhtml#a107d847044e677b01e9bd3d5251b39d9">SQCVT_SAT</a>(<a class="code" href="_asymm_helpers_8cpp.xhtml#a552dc3787d7ea1675f3e4e8993501d58">epsilon</a>))));</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="comment">// Calculate x bar and store results</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; numerator = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(mean.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * mean.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; numerator = <a class="code" href="batchnormalization__layer_8cl.xhtml#ad778425e4131c4731f17d7e6e3499a07">SUB_OP</a>(data, numerator);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; x_bar = <a class="code" href="batchnormalization__layer_8cl.xhtml#ad3cc858846806e6b1d3694b9d0a2e6da">MUL_OP</a>(numerator, denominator);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160;</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_GAMMA</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</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>, VEC_SIZE)</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; gamma_vec = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(gamma.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * gamma.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; res = <a class="code" href="batchnormalization__layer_8cl.xhtml#ad3cc858846806e6b1d3694b9d0a2e6da">MUL_OP</a>(gamma_vec, x_bar);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160;<span class="preprocessor">#else </span><span class="comment">/* USE_DEFAULT_GAMMA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <span class="comment">// gamma is equal to 1, no need to perform multiplications</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; res = x_bar;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_GAMMA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_BETA</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</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>, VEC_SIZE)</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; beta_vec = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(beta.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * beta.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; <span class="comment">// beta is not zero, hence we need to perform the addition</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; res = <a class="code" href="batchnormalization__layer_8cl.xhtml#aebbeb1f22eca3a3f4c3e019e8f419f39">ADD_OP</a>(res, beta_vec);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_BETA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; res = <a class="code" href="winograd__output__transform_8cl.xhtml#a150fbfa48767f3bf602b812f8ecb3ad9">ACTIVATION_FUNC</a>(res);</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; <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="l00148"></a><span class="lineno"> 148</span>&#160; (res, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)out.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160;}</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160;</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160;__kernel <span class="keywordtype">void</span> batchnormalization_layer_nhwc(<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(input),</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160;#ifndef IN_PLACE</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a6b83038822d1ae7ab619b684ed3b7fc0">TENSOR3D_DECLARATION</a>(output),</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160;#endif <span class="comment">/* not IN_PLACE */</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(mean),</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(var),</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160;#ifndef USE_DEFAULT_BETA</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(beta),</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160;#endif <span class="comment">/* USE_DEFAULT_BETA */</span></div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160;#ifndef USE_DEFAULT_GAMMA</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(gamma),</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160;#endif <span class="comment">/* USE_DEFAULT_GAMMA */</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; <span class="keywordtype">float</span> <a class="code" href="_asymm_helpers_8cpp.xhtml#a552dc3787d7ea1675f3e4e8993501d58">epsilon</a>)</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160;{</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> in = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(input);</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160;<span class="preprocessor">#ifdef IN_PLACE</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> out = in;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160;<span class="preprocessor">#else </span><span class="comment">/* IN_PLACE */</span><span class="preprocessor"></span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; <a class="code" href="struct_tensor3_d.xhtml">Tensor3D</a> out = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a31c8c760f08fb1a331b16b7c204321dc">CONVERT_TO_TENSOR3D_STRUCT</a>(output);</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* IN_PLACE */</span><span class="preprocessor"></span></div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> mean = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a527bfdf5eeb306f1cf01c4a8e29f38e0">CONVERT_TO_VECTOR_STRUCT</a>(mean);</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> var = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a527bfdf5eeb306f1cf01c4a8e29f38e0">CONVERT_TO_VECTOR_STRUCT</a>(var);</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_BETA</span></div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> beta = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a527bfdf5eeb306f1cf01c4a8e29f38e0">CONVERT_TO_VECTOR_STRUCT</a>(beta);</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_BETA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_GAMMA</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> gamma = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a527bfdf5eeb306f1cf01c4a8e29f38e0">CONVERT_TO_VECTOR_STRUCT</a>(gamma);</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_GAMMA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160;</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</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>, VEC_SIZE)</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; data = 0;</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</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>, VEC_SIZE)</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; denominator = 0;</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</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>, VEC_SIZE)</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; numerator = 0;</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</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>, VEC_SIZE)</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; x_bar = 0;</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</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>, VEC_SIZE)</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; res = 0;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160;</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> current_slice = get_global_id(0);</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160;</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; 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> *)in.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; denominator = <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> *)(var.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * VEC_SIZE * var.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; denominator = <a class="code" href="batchnormalization__layer_8cl.xhtml#acbe0869c7899bc8d9f0e91a6249fa970">INVSQRT_OP</a>(<a class="code" href="batchnormalization__layer_8cl.xhtml#aebbeb1f22eca3a3f4c3e019e8f419f39">ADD_OP</a>(denominator, ((<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))<a class="code" href="batchnormalization__layer_8cl.xhtml#a107d847044e677b01e9bd3d5251b39d9">SQCVT_SAT</a>(<a class="code" href="_asymm_helpers_8cpp.xhtml#a552dc3787d7ea1675f3e4e8993501d58">epsilon</a>))));</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160;</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; <span class="comment">// Calculate x bar and store results</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; numerator = <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> *)(mean.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * VEC_SIZE * mean.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; numerator = <a class="code" href="batchnormalization__layer_8cl.xhtml#ad778425e4131c4731f17d7e6e3499a07">SUB_OP</a>(data, numerator);</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; x_bar = <a class="code" href="batchnormalization__layer_8cl.xhtml#ad3cc858846806e6b1d3694b9d0a2e6da">MUL_OP</a>(numerator, denominator);</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160;</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_GAMMA</span></div><div class="line"><a name="l00239"></a><span class="lineno"> 239</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>, VEC_SIZE)</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; gamma_vec = <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> *)(gamma.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * VEC_SIZE * gamma.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; res = <a class="code" href="batchnormalization__layer_8cl.xhtml#ad3cc858846806e6b1d3694b9d0a2e6da">MUL_OP</a>(gamma_vec, x_bar);</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160;<span class="preprocessor">#else </span><span class="comment">/* USE_DEFAULT_GAMMA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; <span class="comment">// gamma is equal to 1, no need to perform multiplications</span></div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; res = x_bar;</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_GAMMA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160;</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_BETA</span></div><div class="line"><a name="l00249"></a><span class="lineno"> 249</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>, VEC_SIZE)</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; beta_vec = <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> *)(beta.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * VEC_SIZE * beta.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; <span class="comment">// beta is not zero, hence we need to perform the addition</span></div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; res = <a class="code" href="batchnormalization__layer_8cl.xhtml#aebbeb1f22eca3a3f4c3e019e8f419f39">ADD_OP</a>(res, beta_vec);</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_BETA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160;</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; res = <a class="code" href="winograd__output__transform_8cl.xhtml#a150fbfa48767f3bf602b812f8ecb3ad9">ACTIVATION_FUNC</a>(res);</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160;</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; <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="l00258"></a><span class="lineno"> 258</span>&#160; (res, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)out.<a class="code" href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160;}</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* defined(VEC_SIZE) &amp;&amp; defined(DATA_TYPE) */</span><span class="preprocessor"></span></div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160;</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160;<span class="preprocessor">#if defined(NUM_CHANNELS) &amp;&amp; defined(DATA_TYPE) &amp;&amp; defined(EPSILON)</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160;</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160;__kernel <span class="keywordtype">void</span> fuse_batchnormalization_layer(<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a481bdc6d61b3df9dcdbdb244f0f97790">TENSOR4D_DECLARATION</a>(conv_w),</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(bn_mean),</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(bn_var)</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160;#ifndef IN_PLACE_W</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160; ,</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a481bdc6d61b3df9dcdbdb244f0f97790">TENSOR4D_DECLARATION</a>(fused_w)</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160;#endif <span class="comment">/* not IN_PLACE_W */</span></div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160;#ifndef IN_PLACE_B</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; ,</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(fused_b)</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160;#endif <span class="comment">/* not IN_PLACE_B */</span></div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160;#ifdef HAS_BIAS</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; ,</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(conv_b)</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160;#endif <span class="comment">/* HAS_BIAS */</span></div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160;#ifndef USE_DEFAULT_BETA</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160; ,</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(bn_beta)</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160;#endif <span class="comment">/* USE_DEFAULT_BETA */</span></div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160;#ifndef USE_DEFAULT_GAMMA</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; ,</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160; <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a>(bn_gamma)</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160;#endif <span class="comment">/* USE_DEFAULT_GAMMA */</span></div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; )</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160;{</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; <a class="code" href="struct_tensor4_d.xhtml">Tensor4D</a> conv_w = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a23b9032d1b9d59547545e457f82ee478">CONVERT_TO_TENSOR4D_STRUCT</a>(conv_w, NUM_CHANNELS);</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> bn_mean = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a64d779f80eeb923e0ab2313433f7b40b">CONVERT_TO_VECTOR_STRUCT_NO_STEP</a>(bn_mean);</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> bn_var = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a64d779f80eeb923e0ab2313433f7b40b">CONVERT_TO_VECTOR_STRUCT_NO_STEP</a>(bn_var);</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160;</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160; <span class="comment">// In-place ops</span></div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160;<span class="preprocessor">#ifdef IN_PLACE_W</span></div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160; <a class="code" href="struct_tensor4_d.xhtml">Tensor4D</a> fused_w = conv_w;</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160;<span class="preprocessor">#else </span><span class="comment">/* IN_PLACE_W */</span><span class="preprocessor"></span></div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>&#160; <a class="code" href="struct_tensor4_d.xhtml">Tensor4D</a> fused_w = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a23b9032d1b9d59547545e457f82ee478">CONVERT_TO_TENSOR4D_STRUCT</a>(fused_w, NUM_CHANNELS);</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* IN_PLACE */</span><span class="preprocessor"></span></div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160;<span class="preprocessor">#ifdef IN_PLACE_B</span></div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> fused_b = conv_b;</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>&#160;<span class="preprocessor">#else </span><span class="comment">/* IN_PLACE_W */</span><span class="preprocessor"></span></div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> fused_b = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a64d779f80eeb923e0ab2313433f7b40b">CONVERT_TO_VECTOR_STRUCT_NO_STEP</a>(fused_b);</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* IN_PLACE */</span><span class="preprocessor"></span></div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>&#160;</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>&#160; <span class="comment">// Conditional ops</span></div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>&#160;<span class="preprocessor">#ifdef HAS_BIAS</span></div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> conv_b = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a64d779f80eeb923e0ab2313433f7b40b">CONVERT_TO_VECTOR_STRUCT_NO_STEP</a>(conv_b);</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_BETA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_BETA</span></div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> bn_beta = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a64d779f80eeb923e0ab2313433f7b40b">CONVERT_TO_VECTOR_STRUCT_NO_STEP</a>(bn_beta);</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_BETA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_GAMMA</span></div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>&#160; <a class="code" href="struct_vector.xhtml">Vector</a> bn_gamma = <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a64d779f80eeb923e0ab2313433f7b40b">CONVERT_TO_VECTOR_STRUCT_NO_STEP</a>(bn_gamma);</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_GAMMA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>&#160;</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> current_slice = get_global_id(2) / NUM_CHANNELS;</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>&#160;</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>&#160;<span class="preprocessor">#if defined(VEC_SIZE) &amp;&amp; defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>&#160; <span class="comment">// Check if access on width gets out of bounds</span></div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>&#160; <span class="comment">// If it does shift access vector to access elements within bounds</span></div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> xi = (int)(get_global_id(0) * VEC_SIZE);</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>&#160; conv_w.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * conv_w_stride_x;</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>&#160; fused_w.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> -= max(xi - (<span class="keywordtype">int</span>)LAST_ACCESSED_X, 0) * fused_w_stride_x;</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>&#160;</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>&#160; <span class="comment">// Load W</span></div><div class="line"><a name="l00377"></a><span class="lineno"> 377</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>, VEC_SIZE)</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>&#160; wn = <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> *)conv_w.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>&#160;<span class="preprocessor">#else // !defined(VEC_SIZE) || !defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>&#160; <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> wn = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(conv_w.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>));</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>&#160;<span class="preprocessor">#endif // defined(VEC_SIZE) &amp;&amp; defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>&#160;</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>&#160; <span class="comment">// rvar = 1 / sqrt(var + epsilon)</span></div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>&#160; <span class="keyword">const</span> <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> var = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(bn_var.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * bn_var.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>&#160; <span class="keyword">const</span> <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> rvar = <a class="code" href="batchnormalization__layer_8cl.xhtml#acbe0869c7899bc8d9f0e91a6249fa970">INVSQRT_OP</a>(<a class="code" href="batchnormalization__layer_8cl.xhtml#aebbeb1f22eca3a3f4c3e019e8f419f39">ADD_OP</a>(var, <a class="code" href="batchnormalization__layer_8cl.xhtml#a107d847044e677b01e9bd3d5251b39d9">SQCVT_SAT</a>((<span class="keywordtype">float</span>)EPSILON)));</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>&#160; wn *= rvar;</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>&#160;</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>&#160; <span class="comment">// Load b</span></div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>&#160; <span class="keyword">const</span> <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> mean = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(bn_mean.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * bn_mean.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>&#160; <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> bn = 0;</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>&#160;<span class="preprocessor">#ifdef HAS_BIAS</span></div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>&#160; bn = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(conv_b.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * conv_b.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* HAS_BIAS */</span><span class="preprocessor"></span></div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>&#160; bn = (bn - mean) * rvar;</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>&#160;</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_GAMMA</span></div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>&#160; <span class="keyword">const</span> <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> gamma_scalar = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(bn_gamma.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * bn_gamma.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>&#160; wn *= gamma_scalar;</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>&#160; bn *= gamma_scalar;</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_GAMMA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>&#160;</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>&#160;<span class="preprocessor">#ifndef USE_DEFAULT_BETA</span></div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>&#160; <span class="keyword">const</span> <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> beta_scalar = *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(bn_beta.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * bn_beta.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>));</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>&#160; bn += beta_scalar;</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* USE_DEFAULT_BETA */</span><span class="preprocessor"></span></div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>&#160;</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>&#160;<span class="preprocessor">#if defined(VEC_SIZE) &amp;&amp; defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>&#160; <span class="comment">// Store updated weights</span></div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>&#160; <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="l00410"></a><span class="lineno"> 410</span>&#160; (wn, 0, (__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)fused_w.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>);</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>&#160;<span class="preprocessor">#else // !defined(VEC_SIZE) || !defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>&#160; *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(fused_w.<a class="code" href="struct_tensor4_d.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a>)) = wn;</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>&#160;<span class="preprocessor">#endif // defined(VEC_SIZE) &amp;&amp; defined(LAST_ACCESSED_X)</span></div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>&#160;</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>&#160; <span class="comment">// Store updated bias</span></div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>&#160; *((__global <a class="code" href="convolution3x3_8cl.xhtml#afb8c72ce35c4a1f4a2588d6573e54aa1">DATA_TYPE</a> *)(fused_b.<a class="code" href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">ptr</a> + current_slice * fused_b.<a class="code" href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">stride_x</a>)) = bn;</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>&#160;}</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* defined(NUM_CHANNELS) &amp;&amp; defined(DATA_TYPE) &amp;&amp; defined(EPSILON) */</span><span class="preprocessor"></span></div><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="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00143">helpers.h:143</a></div></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#l00172">helpers.h:172</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="_asymm_helpers_8cpp_xhtml_a552dc3787d7ea1675f3e4e8993501d58"><div class="ttname"><a href="_asymm_helpers_8cpp.xhtml#a552dc3787d7ea1675f3e4e8993501d58">epsilon</a></div><div class="ttdeci">constexpr float epsilon</div><div class="ttdef"><b>Definition:</b> <a href="_asymm_helpers_8cpp_source.xhtml#l00033">AsymmHelpers.cpp:33</a></div></div>
<div class="ttc" id="batchnormalization__layer_8cl_xhtml_ad778425e4131c4731f17d7e6e3499a07"><div class="ttname"><a href="batchnormalization__layer_8cl.xhtml#ad778425e4131c4731f17d7e6e3499a07">SUB_OP</a></div><div class="ttdeci">#define SUB_OP(a, b)</div><div class="ttdef"><b>Definition:</b> <a href="batchnormalization__layer_8cl_source.xhtml#l00027">batchnormalization_layer.cl:27</a></div></div>
<div class="ttc" id="winograd__output__transform_8cl_xhtml_a150fbfa48767f3bf602b812f8ecb3ad9"><div class="ttname"><a href="winograd__output__transform_8cl.xhtml#a150fbfa48767f3bf602b812f8ecb3ad9">ACTIVATION_FUNC</a></div><div class="ttdeci">#define ACTIVATION_FUNC(x)</div><div class="ttdef"><b>Definition:</b> <a href="winograd__output__transform_8cl_source.xhtml#l00030">winograd_output_transform.cl:30</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#l00160">helpers.h:160</a></div></div>
<div class="ttc" id="batchnormalization__layer_8cl_xhtml_acbe0869c7899bc8d9f0e91a6249fa970"><div class="ttname"><a href="batchnormalization__layer_8cl.xhtml#acbe0869c7899bc8d9f0e91a6249fa970">INVSQRT_OP</a></div><div class="ttdeci">#define INVSQRT_OP(a)</div><div class="ttdef"><b>Definition:</b> <a href="batchnormalization__layer_8cl_source.xhtml#l00029">batchnormalization_layer.cl:29</a></div></div>
<div class="ttc" id="activation__layer_8cl_xhtml"><div class="ttname"><a href="activation__layer_8cl.xhtml">activation_layer.cl</a></div></div>
<div class="ttc" id="batchnormalization__layer_8cl_xhtml_ad3cc858846806e6b1d3694b9d0a2e6da"><div class="ttname"><a href="batchnormalization__layer_8cl.xhtml#ad3cc858846806e6b1d3694b9d0a2e6da">MUL_OP</a></div><div class="ttdeci">#define MUL_OP(a, b)</div><div class="ttdef"><b>Definition:</b> <a href="batchnormalization__layer_8cl_source.xhtml#l00028">batchnormalization_layer.cl:28</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#l00170">helpers.h:170</a></div></div>
<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a527bfdf5eeb306f1cf01c4a8e29f38e0"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a527bfdf5eeb306f1cf01c4a8e29f38e0">CONVERT_TO_VECTOR_STRUCT</a></div><div class="ttdeci">#define CONVERT_TO_VECTOR_STRUCT(name)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00107">helpers.h:107</a></div></div>
<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a40a6eb9f2a7712f08d6bb8ff6c9e6ca7"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a40a6eb9f2a7712f08d6bb8ff6c9e6ca7">VECTOR_DECLARATION</a></div><div class="ttdeci">#define VECTOR_DECLARATION(name)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00071">helpers.h:71</a></div></div>
<div class="ttc" id="struct_vector_xhtml_ae01febbfd0689ef709f3ff6fdd2abc7e"><div class="ttname"><a href="struct_vector.xhtml#ae01febbfd0689ef709f3ff6fdd2abc7e">Vector::stride_x</a></div><div class="ttdeci">int stride_x</div><div class="ttdoc">Stride of the image in X dimension (in bytes)</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00147">helpers.h:147</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#l00135">helpers.h:135</a></div></div>
<div class="ttc" id="struct_vector_xhtml_acf52c23cbd7424606c10a606524e3e32"><div class="ttname"><a href="struct_vector.xhtml#acf52c23cbd7424606c10a606524e3e32">Vector::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#l00145">helpers.h:145</a></div></div>
<div class="ttc" id="batchnormalization__layer_8cl_xhtml_aebbeb1f22eca3a3f4c3e019e8f419f39"><div class="ttname"><a href="batchnormalization__layer_8cl.xhtml#aebbeb1f22eca3a3f4c3e019e8f419f39">ADD_OP</a></div><div class="ttdeci">#define ADD_OP(a, b)</div><div class="ttdef"><b>Definition:</b> <a href="batchnormalization__layer_8cl_source.xhtml#l00026">batchnormalization_layer.cl:26</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#l00128">helpers.h:128</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#l00051">helpers.h:51</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#l00095">helpers.h:95</a></div></div>
<div class="ttc" id="struct_tensor3_d_xhtml_acf52c23cbd7424606c10a606524e3e32"><div class="ttname"><a href="struct_tensor3_d.xhtml#acf52c23cbd7424606c10a606524e3e32">Tensor3D::ptr</a></div><div class="ttdeci">__global uchar * ptr</div><div class="ttdoc">Pointer to the starting postion of the buffer.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00162">helpers.h:162</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#l00048">helpers.h:48</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#l00085">helpers.h:85</a></div></div>
<div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a64d779f80eeb923e0ab2313433f7b40b"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_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="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00110">helpers.h:110</a></div></div>
<div class="ttc" id="batchnormalization__layer_8cl_xhtml_a107d847044e677b01e9bd3d5251b39d9"><div class="ttname"><a href="batchnormalization__layer_8cl.xhtml#a107d847044e677b01e9bd3d5251b39d9">SQCVT_SAT</a></div><div class="ttdeci">#define SQCVT_SAT(a)</div><div class="ttdef"><b>Definition:</b> <a href="batchnormalization__layer_8cl_source.xhtml#l00030">batchnormalization_layer.cl:30</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#l00057">helpers.h:57</a></div></div>
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