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<div class="title">device/kernel/tensor_foreach.h</div> </div>
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<a href="device_2kernel_2tensor__foreach_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/***************************************************************************************************</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * Redistribution and use in source and binary forms, with or without modification, are permitted</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> * provided that the following conditions are met:</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * * Redistributions of source code must retain the above copyright notice, this list of</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * conditions and the following disclaimer.</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * * Redistributions in binary form must reproduce the above copyright notice, this list of</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> * conditions and the following disclaimer in the documentation and/or other materials</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * provided with the distribution.</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> * * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> * to endorse or promote products derived from this software without specific prior written</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * permission.</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> *</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"> * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"> * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"> * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> *</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="comment"> **************************************************************************************************/</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="cutlass_8h.html">cutlass/cutlass.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="coord_8h.html">cutlass/coord.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="keyword">namespace </span><a class="code" href="namespacecutlass.html">cutlass</a> {</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keyword">namespace </span>reference {</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="keyword">namespace </span>device {</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">namespace </span>kernel {</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> </div><div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reference_1_1device_1_1kernel_1_1detail.html"> 39</a></span> <span class="keyword">namespace </span>detail {</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="keyword">template</span> <<span class="keyword">typename</span> Func, <span class="keywordtype">int</span> Rank, <span class="keywordtype">int</span> RankRemaining></div><div class="line"><a name="l00043"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper.html"> 43</a></span> <span class="keyword">struct </span><a class="code" href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper.html">TensorForEachHelper</a> {</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  __inline__ __device__</div><div class="line"><a name="l00047"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper.html#a3f3002a3173247d60a18298ef3ff9dbf"> 47</a></span>  <a class="code" href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper.html#a3f3002a3173247d60a18298ef3ff9dbf">TensorForEachHelper</a>(Func &func, <a class="code" href="structcutlass_1_1Coord.html">Coord<Rank></a> <span class="keyword">const</span> &size, <a class="code" href="structcutlass_1_1Coord.html">Coord<Rank></a> &coord, int64_t index) {</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  int64_t product = 1;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = Rank - RankRemaining; i < Rank; ++i) {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  product *= size[i];</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  }</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  coord[Rank - 1 - RankRemaining] = index / product;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  int64_t remaining = index % product;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper.html">TensorForEachHelper</a><Func, Rank, RankRemaining-1>(func, size, coord, remaining);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  }</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> };</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="keyword">template</span> <<span class="keyword">typename</span> Func, <span class="keywordtype">int</span> Rank></div><div class="line"><a name="l00065"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4.html"> 65</a></span> <span class="keyword">struct </span><a class="code" href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper.html">TensorForEachHelper</a><Func, Rank, 0> {</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  __inline__ __device__</div><div class="line"><a name="l00069"></a><span class="lineno"><a class="line" href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4.html#a89e10e059c3ffcfe2640cf6291353937"> 69</a></span>  <a class="code" href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4.html#a89e10e059c3ffcfe2640cf6291353937">TensorForEachHelper</a>(Func &func, <a class="code" href="structcutlass_1_1Coord.html">Coord<Rank></a> <span class="keyword">const</span> &size, <a class="code" href="structcutlass_1_1Coord.html">Coord<Rank></a> &coord, int64_t index) {</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  coord[Rank - 1] = index;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordflow">if</span> (coord < size) {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  func(coord);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  }</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  }</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> };</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> } <span class="comment">// namespace detail</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="keyword">template</span> <<span class="keyword">typename</span> Func, <span class="keywordtype">int</span> Rank, <span class="keyword">typename</span> Params></div><div class="line"><a name="l00085"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#ae22a592321cef9a9f586d3f094933e3f"> 85</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#ae22a592321cef9a9f586d3f094933e3f">TensorForEach</a>(<a class="code" href="structcutlass_1_1Coord.html">Coord<Rank></a> size, Params params = Params()) {</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  Func func(params);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  int64_t index = threadIdx.x + blockIdx.x * blockDim.x;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  int64_t max_index = 1;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < Rank; ++i) {</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  max_index *= size[i];</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  }</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="cutlass_8h.html#adb3bc73d74b4a4bf13099d5696db3352">CUTLASS_PRAGMA_NO_UNROLL</a></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">while</span> (index < max_index) {</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="structcutlass_1_1Coord.html">Coord<Rank></a> coord;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper.html">detail::TensorForEachHelper</a><Func, Rank, Rank - 1>(func, size, coord, index); </div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  index += blockDim.x * gridDim.x;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  }</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> }</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="keyword">template</span> <<span class="keyword">typename</span> Func, <span class="keywordtype">int</span> Rank, <span class="keyword">typename</span> Params></div><div class="line"><a name="l00110"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#ab3b42b1c0e6f28c3b62b65a373db5fd7"> 110</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#ab3b42b1c0e6f28c3b62b65a373db5fd7">TensorDiagonalForEach</a>(<a class="code" href="structcutlass_1_1Coord.html">Coord<Rank></a> size, Params params, <span class="keywordtype">int</span> start, <span class="keywordtype">int</span> end) {</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  Func func(params);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  int64_t index = threadIdx.x + blockIdx.x * blockDim.x + start;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> </div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keywordflow">if</span> (index < end) {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="structcutlass_1_1Coord.html">Coord<Rank></a> coord;</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <a class="code" href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < Rank; ++i) {</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  coord[i] = index;</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  }</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  func(coord);</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  }</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> }</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="keyword">template</span> <<span class="keyword">typename</span> Element, <span class="keyword">typename</span> Func></div><div class="line"><a name="l00131"></a><span class="lineno"><a class="line" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a0100d78891f9e00e75453ef8dc24daa6"> 131</a></span> __global__ <span class="keywordtype">void</span> <a class="code" href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a0100d78891f9e00e75453ef8dc24daa6">BlockForEach</a>(</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  Element *ptr, </div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordtype">size_t</span> capacity, </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keyword">typename</span> Func::Params params) {</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  Func func(params);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> </div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keywordtype">size_t</span> index = threadIdx.x + blockIdx.x * blockDim.x;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keywordflow">for</span> (; index < capacity; index += blockDim.x * gridDim.x) {</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  ptr[index] = func();</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  }</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> }</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> </div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> } <span class="comment">// namespace kernel</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> } <span class="comment">// namespace device</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> } <span class="comment">// namespace reference</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> } <span class="comment">// namespace cutlass</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div><div class="ttc" id="namespacecutlass_html"><div class="ttname"><a href="namespacecutlass.html">cutlass</a></div><div class="ttdef"><b>Definition:</b> aligned_buffer.h:35</div></div>
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<div class="ttc" id="coord_8h_html"><div class="ttname"><a href="coord_8h.html">coord.h</a></div><div class="ttdoc">A Coord is a coordinate of arbitrary rank into a tensor or matrix. </div></div>
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<div class="ttc" id="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4_html_a89e10e059c3ffcfe2640cf6291353937"><div class="ttname"><a href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper_3_01Func_00_01Rank_00_010_01_4.html#a89e10e059c3ffcfe2640cf6291353937">cutlass::reference::device::kernel::detail::TensorForEachHelper< Func, Rank, 0 >::TensorForEachHelper</a></div><div class="ttdeci">__inline__ __device__ TensorForEachHelper(Func &func, Coord< Rank > const &size, Coord< Rank > &coord, int64_t index)</div><div class="ttdoc">Constructor for fastest changing rank. </div><div class="ttdef"><b>Definition:</b> device/kernel/tensor_foreach.h:69</div></div>
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<div class="ttc" id="cutlass_8h_html_a4b1c9f25ab6eaa25e1f2258dd63e6ce4"><div class="ttname"><a href="cutlass_8h.html#a4b1c9f25ab6eaa25e1f2258dd63e6ce4">CUTLASS_PRAGMA_UNROLL</a></div><div class="ttdeci">#define CUTLASS_PRAGMA_UNROLL</div><div class="ttdef"><b>Definition:</b> cutlass.h:110</div></div>
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<div class="ttc" id="namespacecutlass_1_1reference_1_1device_1_1kernel_html_a0100d78891f9e00e75453ef8dc24daa6"><div class="ttname"><a href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#a0100d78891f9e00e75453ef8dc24daa6">cutlass::reference::device::kernel::BlockForEach</a></div><div class="ttdeci">__global__ void BlockForEach(Element *ptr, size_t capacity, typename Func::Params params)</div><div class="ttdef"><b>Definition:</b> device/kernel/tensor_foreach.h:131</div></div>
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<div class="ttc" id="cutlass_8h_html_adb3bc73d74b4a4bf13099d5696db3352"><div class="ttname"><a href="cutlass_8h.html#adb3bc73d74b4a4bf13099d5696db3352">CUTLASS_PRAGMA_NO_UNROLL</a></div><div class="ttdeci">#define CUTLASS_PRAGMA_NO_UNROLL</div><div class="ttdef"><b>Definition:</b> cutlass.h:111</div></div>
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<div class="ttc" id="structcutlass_1_1Coord_html"><div class="ttname"><a href="structcutlass_1_1Coord.html">cutlass::Coord</a></div><div class="ttdoc">Statically-sized array specifying Coords within a tensor. </div><div class="ttdef"><b>Definition:</b> coord.h:43</div></div>
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<div class="ttc" id="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper_html_a3f3002a3173247d60a18298ef3ff9dbf"><div class="ttname"><a href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper.html#a3f3002a3173247d60a18298ef3ff9dbf">cutlass::reference::device::kernel::detail::TensorForEachHelper::TensorForEachHelper</a></div><div class="ttdeci">__inline__ __device__ TensorForEachHelper(Func &func, Coord< Rank > const &size, Coord< Rank > &coord, int64_t index)</div><div class="ttdoc">Constructor for general rank. </div><div class="ttdef"><b>Definition:</b> device/kernel/tensor_foreach.h:47</div></div>
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<div class="ttc" id="namespacecutlass_1_1reference_1_1device_1_1kernel_html_ab3b42b1c0e6f28c3b62b65a373db5fd7"><div class="ttname"><a href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#ab3b42b1c0e6f28c3b62b65a373db5fd7">cutlass::reference::device::kernel::TensorDiagonalForEach</a></div><div class="ttdeci">__global__ void TensorDiagonalForEach(Coord< Rank > size, Params params, int start, int end)</div><div class="ttdoc">Kernel calls a functor for each element along a tensor&#39;s diagonal. </div><div class="ttdef"><b>Definition:</b> device/kernel/tensor_foreach.h:110</div></div>
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<div class="ttc" id="namespacecutlass_1_1reference_1_1device_1_1kernel_html_ae22a592321cef9a9f586d3f094933e3f"><div class="ttname"><a href="namespacecutlass_1_1reference_1_1device_1_1kernel.html#ae22a592321cef9a9f586d3f094933e3f">cutlass::reference::device::kernel::TensorForEach</a></div><div class="ttdeci">__global__ void TensorForEach(Coord< Rank > size, Params params=Params())</div><div class="ttdoc">Kernel calls a functor for each element in a tensor&#39;s index space. </div><div class="ttdef"><b>Definition:</b> device/kernel/tensor_foreach.h:85</div></div>
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<div class="ttc" id="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper_html"><div class="ttname"><a href="structcutlass_1_1reference_1_1device_1_1kernel_1_1detail_1_1TensorForEachHelper.html">cutlass::reference::device::kernel::detail::TensorForEachHelper</a></div><div class="ttdoc">Helper to perform for-each operation. </div><div class="ttdef"><b>Definition:</b> device/kernel/tensor_foreach.h:43</div></div>
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<div class="ttc" id="cutlass_8h_html"><div class="ttname"><a href="cutlass_8h.html">cutlass.h</a></div><div class="ttdoc">Basic include for CUTLASS. </div></div>
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