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| <li class="navelem"><a class="el" href="dir_8cab8f464681f7cc51cee77e79a434cd.html">3rdparty</a></li><li class="navelem"><a class="el" href="dir_3e48ced36faa4eaa1b41f6d960bf0edb.html">mshadow</a></li><li class="navelem"><a class="el" href="dir_00b035bb2ad81894e6ad291054ea5f82.html">mshadow</a></li> </ul> |
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| <div class="title">random.h</div> </div> |
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| <div class="contents"> |
| <a href="random_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"> * Licensed to the Apache Software Foundation (ASF) under one</span></div> |
| <div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * or more contributor license agreements. See the NOTICE file</span></div> |
| <div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * distributed with this work for additional information</span></div> |
| <div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> * regarding copyright ownership. The ASF licenses this file</span></div> |
| <div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * to you under the Apache License, Version 2.0 (the</span></div> |
| <div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * "License"); you may not use this file except in compliance</span></div> |
| <div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * with the License. You may obtain a copy of the License at</span></div> |
| <div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> *</span></div> |
| <div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * http://www.apache.org/licenses/LICENSE-2.0</span></div> |
| <div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> *</span></div> |
| <div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> * Unless required by applicable law or agreed to in writing,</span></div> |
| <div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * software distributed under the License is distributed on an</span></div> |
| <div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span></div> |
| <div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> * KIND, either express or implied. See the License for the</span></div> |
| <div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * specific language governing permissions and limitations</span></div> |
| <div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * under the License.</span></div> |
| <div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> */</span></div> |
| <div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  </div> |
| <div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#ifndef MSHADOW_RANDOM_H_</span></div> |
| <div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#define MSHADOW_RANDOM_H_</span></div> |
| <div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  </div> |
| <div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include <cstdlib></span></div> |
| <div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include <algorithm></span></div> |
| <div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include <random></span></div> |
| <div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="3rdparty_2mshadow_2mshadow_2base_8h.html">./base.h</a>"</span></div> |
| <div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="tensor_8h.html">./tensor.h</a>"</span></div> |
| <div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include "<a class="code" href="tensor__container_8h.html">./tensor_container.h</a>"</span></div> |
| <div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include <random></span></div> |
| <div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  </div> |
| <div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  </div> |
| <div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="keyword">namespace </span><a class="code" href="namespacemshadow.html">mshadow</a> {</div> |
| <div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="keyword">template</span><<span class="keyword">typename</span> Device, <span class="keyword">typename</span> DType MSHADOW_DEFAULT_DTYPE></div> |
| <div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random.html"> 45</a></span> <span class="keyword">class </span><a class="code" href="classmshadow_1_1Random.html">Random</a> {};</div> |
| <div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  </div> |
| <div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="keyword">template</span><<span class="keyword">typename</span> DType></div> |
| <div class="line"><a name="l00049"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html"> 49</a></span> <span class="keyword">class </span><a class="code" href="classmshadow_1_1Random.html">Random</a><<a class="code" href="structmshadow_1_1cpu.html">cpu</a>, DType> {</div> |
| <div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="keyword">public</span>:</div> |
| <div class="line"><a name="l00055"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a468829a8a58919ec4aadb1e75a6174ff"> 55</a></span>  <span class="keyword">explicit</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a468829a8a58919ec4aadb1e75a6174ff">Random</a>(<span class="keywordtype">int</span> seed) {</div> |
| <div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  this->Seed(seed);</div> |
| <div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  buffer_.Resize(<a class="code" href="namespacemshadow.html#a05e468ef4d8882fccce53ae951b7bdbd">Shape1</a>(<a class="code" href="namespacemshadow.html#ac4cba6b672478463350f7d84b47e99e3">kRandBufferSize</a>));</div> |
| <div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  }</div> |
| <div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a37b7e8cbe08d7c0f6699039cc0bad8b2"> 59</a></span>  <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a37b7e8cbe08d7c0f6699039cc0bad8b2">~Random</a>(<span class="keywordtype">void</span>) {</div> |
| <div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  }</div> |
| <div class="line"><a name="l00065"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#aff2ec8923288cea076f5fa94897c0bfe"> 65</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#aff2ec8923288cea076f5fa94897c0bfe">Seed</a>(<span class="keywordtype">int</span> seed) {</div> |
| <div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  rnd_engine_.seed(seed);</div> |
| <div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  this->rseed_ = <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span><span class="keyword">></span>(seed);</div> |
| <div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  }</div> |
| <div class="line"><a name="l00073"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a41b3d2a322bbd6fc2679275b80c27342"> 73</a></span>  <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a41b3d2a322bbd6fc2679275b80c27342">GetSeed</a>()<span class="keyword"> const </span>{</div> |
| <div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordflow">return</span> rseed_;</div> |
| <div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  }</div> |
| <div class="line"><a name="l00080"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a0096231388917db869409e0f587b1cf3"> 80</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a0096231388917db869409e0f587b1cf3">set_stream</a>(<a class="code" href="structmshadow_1_1Stream.html">Stream<cpu></a> *stream) {</div> |
| <div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  }</div> |
| <div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  </div> |
| <div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a874c3496e212241ae5b127c9f26d17ad"> 87</a></span>  <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a874c3496e212241ae5b127c9f26d17ad">GetRandInt</a>() {</div> |
| <div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordflow">return</span> rnd_engine_();</div> |
| <div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  }</div> |
| <div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  </div> |
| <div class="line"><a name="l00094"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a7afa2530a465aadc5151b6841cbf34d6"> 94</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a7afa2530a465aadc5151b6841cbf34d6">GetRandInt</a>(<span class="keyword">const</span> <a class="code" href="structmshadow_1_1Tensor.html">Tensor<cpu, 1, unsigned></a>& dst) {</div> |
| <div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  std::generate_n(dst.<a class="code" href="structmshadow_1_1Tensor.html#ad86d6759c585efb5229b3a0659973838">dptr_</a>, dst.<a class="code" href="structmshadow_1_1Tensor.html#a88cbcae11653307bfa4c99804320b638">size</a>(0), [&](){ return rnd_engine_(); });</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>  </div> |
| <div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim, <span class="keyword">class</span> Sampler></div> |
| <div class="line"><a name="l00105"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a3ff7a0fd2fdaa4bcc166a73fbd1f2a10"> 105</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a3ff7a0fd2fdaa4bcc166a73fbd1f2a10">SampleDistribution</a>(<a class="code" href="structmshadow_1_1Tensor.html">Tensor<cpu, dim, DType></a> *dst, Sampler sampler) {</div> |
| <div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">if</span> (dst-><a class="code" href="structmshadow_1_1Tensor.html#a9cc7d01a1eb0825d7a3fcdabc8e58f07">CheckContiguous</a>()) {</div> |
| <div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  std::generate_n(dst-><a class="code" href="structmshadow_1_1Tensor.html#ad86d6759c585efb5229b3a0659973838">dptr_</a>, dst-><a class="code" href="structmshadow_1_1Tensor.html#ad10c7414c5948e789e8761df2083c4e5">shape_</a>.Size(), sampler);</div> |
| <div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  } <span class="keywordflow">else</span> {</div> |
| <div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <a class="code" href="structmshadow_1_1Tensor.html">Tensor<cpu, 2, DType></a> mat = dst-><a class="code" href="structmshadow_1_1Tensor.html#a48a5927e810fbc45e43e92cfe397d9f2">FlatTo2D</a>();</div> |
| <div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordflow">for</span> (<a class="code" href="namespacemshadow.html#adcbc2e1131386fccb1474b0bdf045926">index_t</a> i = 0; i < mat.<a class="code" href="structmshadow_1_1Tensor.html#a88cbcae11653307bfa4c99804320b638">size</a>(0); ++i) {</div> |
| <div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  std::generate_n(mat[i].dptr_, mat.<a class="code" href="structmshadow_1_1Tensor.html#a88cbcae11653307bfa4c99804320b638">size</a>(1), sampler);</div> |
| <div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  }</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>  }</div> |
| <div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  </div> |
| <div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim, <span class="keyword">typename</span> PType></div> |
| <div class="line"><a name="l00124"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#aa93ebb9587b5876ad99953733119377b"> 124</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#aa93ebb9587b5876ad99953733119377b">SampleUniform</a>(<a class="code" href="structmshadow_1_1Tensor.html">Tensor<cpu, dim, DType></a> *dst,</div> |
| <div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  PType a = 0.0f , PType b = 1.0f ) {</div> |
| <div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="comment">// Ensure that half_t is handled correctly.</span></div> |
| <div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> std::conditional<std::is_floating_point<DType>::value,</div> |
| <div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  DType, <span class="keywordtype">double</span>>::type FType;</div> |
| <div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> std::conditional<std::is_integral<DType>::value,</div> |
| <div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  std::uniform_int_distribution<DType>,</div> |
| <div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  std::uniform_real_distribution<FType>>::type GType;</div> |
| <div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  GType dist_uniform(a, b);</div> |
| <div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  SampleDistribution(dst, [&](){ <span class="keywordflow">return</span> dist_uniform(rnd_engine_);});</div> |
| <div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  }</div> |
| <div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  </div> |
| <div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim, <span class="keyword">typename</span> PType></div> |
| <div class="line"><a name="l00144"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a6fbb05ba7472a75c6b9fbc68903e0713"> 144</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a6fbb05ba7472a75c6b9fbc68903e0713">SampleGaussian</a>(<a class="code" href="structmshadow_1_1Tensor.html">Tensor<cpu, dim, DType></a> *dst,</div> |
| <div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  PType mu = 0.0f, PType sigma = 1.0f ) {</div> |
| <div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keywordflow">if</span> (sigma <= 0) {</div> |
| <div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  *dst = mu; <span class="keywordflow">return</span>;</div> |
| <div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  }</div> |
| <div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> std::conditional<std::is_floating_point<DType>::value,</div> |
| <div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  DType, <span class="keywordtype">double</span>>::type GType;</div> |
| <div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  std::normal_distribution<GType> dist_normal(mu, sigma);</div> |
| <div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  SampleDistribution(dst, [&](){ <span class="keywordflow">return</span> dist_normal(rnd_engine_);});</div> |
| <div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  }</div> |
| <div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  </div> |
| <div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim, <span class="keyword">typename</span> PType></div> |
| <div class="line"><a name="l00163"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a7cbab012322f309825387633c0c0406d"> 163</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a7cbab012322f309825387633c0c0406d">SampleGamma</a>(<a class="code" href="structmshadow_1_1Tensor.html">Tensor<cpu, dim, DType></a> *dst,</div> |
| <div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  PType alpha, PType beta) {</div> |
| <div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> std::conditional<std::is_floating_point<DType>::value,</div> |
| <div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  DType, <span class="keywordtype">double</span>>::type GType;</div> |
| <div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  std::gamma_distribution<GType> dist_gamma(alpha, beta);</div> |
| <div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  SampleDistribution(dst, [&](){ <span class="keywordflow">return</span> dist_gamma(rnd_engine_);});</div> |
| <div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  }</div> |
| <div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  </div> |
| <div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim, <span class="keyword">typename</span> PType></div> |
| <div class="line"><a name="l00178"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a95a7e32484bfb144d355bda1abf7bb83"> 178</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a95a7e32484bfb144d355bda1abf7bb83">SampleExponential</a>(<a class="code" href="structmshadow_1_1Tensor.html">Tensor<cpu, dim, DType></a> *dst, PType lambda ) {</div> |
| <div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> std::conditional<std::is_floating_point<DType>::value,</div> |
| <div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  DType, <span class="keywordtype">double</span>>::type GType;</div> |
| <div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  std::exponential_distribution<GType> dist_exp(lambda);</div> |
| <div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  SampleDistribution(dst, [&](){ <span class="keywordflow">return</span> dist_exp(rnd_engine_);});</div> |
| <div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  }</div> |
| <div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  </div> |
| <div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim, <span class="keyword">typename</span> PType></div> |
| <div class="line"><a name="l00192"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a1737028fbdf8a8226ad5e6d37356ba66"> 192</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a1737028fbdf8a8226ad5e6d37356ba66">SamplePoisson</a>(<a class="code" href="structmshadow_1_1Tensor.html">Tensor<cpu, dim, DType></a> *dst, PType lambda) {</div> |
| <div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> std::conditional<std::is_integral<DType>::value, DType, <span class="keywordtype">int</span>>::type GType;</div> |
| <div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  std::poisson_distribution<GType> dist_poisson(lambda);</div> |
| <div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  SampleDistribution(dst, [&](){ <span class="keywordflow">return</span> <span class="keyword">static_cast<</span>DType<span class="keyword">></span>(dist_poisson(rnd_engine_));});</div> |
| <div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  }</div> |
| <div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  </div> |
| <div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim, <span class="keyword">typename</span> PType1, <span class="keyword">typename</span> PType2></div> |
| <div class="line"><a name="l00206"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#aedf6b0f62b92f0b57184733c6cc36bb2"> 206</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#aedf6b0f62b92f0b57184733c6cc36bb2">SampleNegativeBinomial</a>(<a class="code" href="structmshadow_1_1Tensor.html">Tensor<cpu, dim, DType></a> *dst, PType1 k, PType2 p) {</div> |
| <div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> std::conditional<std::is_integral<DType>::value, DType, <span class="keywordtype">int</span>>::type GType;</div> |
| <div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  std::negative_binomial_distribution<GType> dist_negbinomial(k, p);</div> |
| <div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  SampleDistribution(dst, [&](){ <span class="keywordflow">return</span> <span class="keyword">static_cast<</span>DType<span class="keyword">></span>(dist_negbinomial(rnd_engine_));});</div> |
| <div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  }</div> |
| <div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  </div> |
| <div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim, <span class="keyword">typename</span> PType></div> |
| <div class="line"><a name="l00221"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a432b0770283d3fa0292b30a9dceaaccc"> 221</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a432b0770283d3fa0292b30a9dceaaccc">SampleGeneralizedNegativeBinomial</a>(<a class="code" href="structmshadow_1_1Tensor.html">Tensor<cpu, dim, DType></a> *dst,</div> |
| <div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  PType mu, PType alpha) {</div> |
| <div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <span class="keywordflow">if</span> (alpha == PType(0)) {</div> |
| <div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <a class="code" href="namespacemxnet.html#aed55e8197182b7c66126902b2a43739a">SamplePoisson</a>(dst, mu); <span class="comment">// limit of Poisson</span></div> |
| <div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  } <span class="keywordflow">else</span> {</div> |
| <div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  PType r(PType(1) / alpha);</div> |
| <div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  PType beta = mu * alpha;</div> |
| <div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  std::gamma_distribution<> dist_gamma(r, beta);</div> |
| <div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> std::conditional<std::is_integral<DType>::value, DType, <span class="keywordtype">int</span>>::type GType;</div> |
| <div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  SampleDistribution(dst,</div> |
| <div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  [&](){ std::poisson_distribution<GType> dist_poisson(dist_gamma(rnd_engine_));</div> |
| <div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keywordflow">return</span> <span class="keyword">static_cast<</span>DType<span class="keyword">></span>(dist_poisson(rnd_engine_));});</div> |
| <div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  }</div> |
| <div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  }</div> |
| <div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  </div> |
| <div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim></div> |
| <div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="keyword">inline</span> <a class="code" href="structmshadow_1_1expr_1_1ReshapeExp.html">expr::ReshapeExp<Tensor<cpu, 1, DType></a>, DType, dim, 1></div> |
| <div class="line"><a name="l00249"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a4ca9b27ca3752795017372a05cfce5c3"> 249</a></span>  <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a4ca9b27ca3752795017372a05cfce5c3">gaussian</a>(<a class="code" href="structmshadow_1_1Shape.html">Shape<dim></a> shape) {</div> |
| <div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  buffer_.Resize(<a class="code" href="namespacemshadow.html#a05e468ef4d8882fccce53ae951b7bdbd">Shape1</a>(shape.<a class="code" href="structmshadow_1_1Shape.html#ac6d667fde1a8180b64f475f5d33ea58f">Size</a>()));</div> |
| <div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  this-><a class="code" href="namespacemxnet.html#a5a28062f52ca576a126599e7ad487077">SampleGaussian</a>(&buffer_, 0.0f, 1.0f);</div> |
| <div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">return</span> <a class="code" href="namespacemshadow_1_1expr.html#a73862619baed02a20e49897decf13fc2">expr::reshape</a>(buffer_, shape);</div> |
| <div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  }</div> |
| <div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim></div> |
| <div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keyword">inline</span> <a class="code" href="structmshadow_1_1expr_1_1ReshapeExp.html">expr::ReshapeExp<Tensor<cpu, 1, DType></a>, DType, dim, 1></div> |
| <div class="line"><a name="l00267"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a4eae04b06525d65b839f2c9c5428c436"> 267</a></span>  <a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a4eae04b06525d65b839f2c9c5428c436">uniform</a>(<a class="code" href="structmshadow_1_1Shape.html">Shape<dim></a> shape) {</div> |
| <div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  buffer_.Resize(<a class="code" href="namespacemshadow.html#a05e468ef4d8882fccce53ae951b7bdbd">Shape1</a>(shape.<a class="code" href="structmshadow_1_1Shape.html#ac6d667fde1a8180b64f475f5d33ea58f">Size</a>()));</div> |
| <div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  this-><a class="code" href="namespacemxnet.html#a2846f4556c9ca9bd0f567504ce60f274">SampleUniform</a>(&buffer_, 0.0f, 1.0f);</div> |
| <div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="keywordflow">return</span> <a class="code" href="namespacemshadow_1_1expr.html#a73862619baed02a20e49897decf13fc2">expr::reshape</a>(buffer_, shape);</div> |
| <div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  }</div> |
| <div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  </div> |
| <div class="line"><a name="l00273"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a02bf4cce9c068da452494452432fcf7f"> 273</a></span>  std::mt19937 &<a class="code" href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a02bf4cce9c068da452494452432fcf7f">GetRndEngine</a>() {</div> |
| <div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keywordflow">return</span> rnd_engine_;</div> |
| <div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  }</div> |
| <div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  </div> |
| <div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="keyword">private</span>:</div> |
| <div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  std::mt19937 rnd_engine_;</div> |
| <div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keywordtype">unsigned</span> rseed_;</div> |
| <div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <a class="code" href="classmshadow_1_1TensorContainer.html">TensorContainer<cpu, 1, DType></a> buffer_;</div> |
| <div class="line"><a name="l00284"></a><span class="lineno"> 284</span> }; <span class="comment">// class Random<cpu, DType></span></div> |
| <div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  </div> |
| <div class="line"><a name="l00286"></a><span class="lineno"> 286</span> <span class="comment">// only allow GPU PRNG when cuda is enabled</span></div> |
| <div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="preprocessor">#if MSHADOW_USE_CUDA</span></div> |
| <div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  </div> |
| <div class="line"><a name="l00289"></a><span class="lineno"> 289</span> <span class="keyword">template</span><<span class="keyword">typename</span> DType></div> |
| <div class="line"><a name="l00290"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html"> 290</a></span> <span class="keyword">class </span><a class="code" href="classmshadow_1_1Random.html">Random</a><<a class="code" href="structmshadow_1_1gpu.html">gpu</a>, DType> {</div> |
| <div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keyword">public</span>:</div> |
| <div class="line"><a name="l00296"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a47236e16630bfafbf207d1ac57547b18"> 296</a></span>  <span class="keyword">explicit</span> <a class="code" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a47236e16630bfafbf207d1ac57547b18">Random</a>(<span class="keywordtype">int</span> seed) : gen_(NULL) {</div> |
| <div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  this->Seed(seed);</div> |
| <div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  buffer_.Resize(<a class="code" href="namespacemshadow.html#a05e468ef4d8882fccce53ae951b7bdbd">Shape1</a>(<a class="code" href="namespacemshadow.html#ac4cba6b672478463350f7d84b47e99e3">kRandBufferSize</a>));</div> |
| <div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  }</div> |
| <div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a6600fb034b3c840dd568458b9cea397c"> 300</a></span>  <a class="code" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a6600fb034b3c840dd568458b9cea397c">~Random</a>(<span class="keywordtype">void</span>) <a class="code" href="3rdparty_2mshadow_2mshadow_2base_8h.html#a53a342d1f8cc22d36ed49e4c51c19f0c">MSHADOW_THROW_EXCEPTION</a> {</div> |
| <div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  DeleteGenerator();</div> |
| <div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  }</div> |
| <div class="line"><a name="l00307"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#ac813f60f1d2d7c7e5cd4a4cc15068667"> 307</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#ac813f60f1d2d7c7e5cd4a4cc15068667">set_stream</a>(<a class="code" href="structmshadow_1_1Stream_3_01gpu_01_4.html">Stream<gpu></a> *stream) {</div> |
| <div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  curandStatus_t status;</div> |
| <div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  status = curandSetStream(gen_, <a class="code" href="structmshadow_1_1Stream.html">Stream<gpu>::GetStream</a>(stream));</div> |
| <div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  </div> |
| <div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  CHECK_EQ(status, CURAND_STATUS_SUCCESS) << <span class="stringliteral">"set_stream CURAND failed"</span>;</div> |
| <div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  }</div> |
| <div class="line"><a name="l00317"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a997d28fe4cfa9a1f36b88160ce61ec9a"> 317</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a997d28fe4cfa9a1f36b88160ce61ec9a">Seed</a>(<span class="keywordtype">int</span> seed) {</div> |
| <div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="comment">// Create a new rng, either initially or if the RNG type can't reset its offset.</span></div> |
| <div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keywordflow">if</span> (gen_ == NULL || (curandSetGeneratorOffset(gen_, 0ULL) != CURAND_STATUS_SUCCESS))</div> |
| <div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  CreateGenerator();</div> |
| <div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="comment">// Now set the seed.</span></div> |
| <div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  curandStatus_t status;</div> |
| <div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  status = curandSetPseudoRandomGeneratorSeed(gen_, <span class="keyword">static_cast<</span>uint64_t<span class="keyword">></span>(seed));</div> |
| <div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  CHECK_EQ(status, CURAND_STATUS_SUCCESS) << <span class="stringliteral">"Set CURAND seed failed."</span>;</div> |
| <div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  }</div> |
| <div class="line"><a name="l00329"></a><span class="lineno"><a class="line" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a8c3a2f7df5bc62093b4a55b9d42bb60e"> 329</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a8c3a2f7df5bc62093b4a55b9d42bb60e">GetRandInt</a>(<span class="keyword">const</span> <a class="code" href="structmshadow_1_1Tensor.html">Tensor<gpu, 1, unsigned></a>& dst) {</div> |
| <div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  curandStatus_t status;</div> |
| <div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  status = curandGenerate(gen_, dst.<a class="code" href="structmshadow_1_1Tensor.html#ad86d6759c585efb5229b3a0659973838">dptr_</a>, dst.<a class="code" href="structmshadow_1_1Tensor.html#a88cbcae11653307bfa4c99804320b638">size</a>(0));</div> |
| <div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  CHECK_EQ(status, CURAND_STATUS_SUCCESS) << <span class="stringliteral">"CURAND Gen rand ints failed."</span></div> |
| <div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  << <span class="stringliteral">" size = "</span> << dst.<a class="code" href="structmshadow_1_1Tensor.html#a88cbcae11653307bfa4c99804320b638">size</a>(0);</div> |
| <div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  }</div> |
| <div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim></div> |
| <div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespacemxnet.html#a2846f4556c9ca9bd0f567504ce60f274">SampleUniform</a>(<a class="code" href="structmshadow_1_1Tensor.html">Tensor<gpu, dim, DType></a> *dst,</div> |
| <div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  DType a = 0.0f, DType b = 1.0f);</div> |
| <div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  </div> |
| <div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim></div> |
| <div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespacemxnet.html#a5a28062f52ca576a126599e7ad487077">SampleGaussian</a>(<a class="code" href="structmshadow_1_1Tensor.html">Tensor<gpu, dim, DType></a> *dst,</div> |
| <div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  DType mu = 0.0f, DType sigma = 1.0f);</div> |
| <div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim></div> |
| <div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="keyword">inline</span> <a class="code" href="structmshadow_1_1expr_1_1ReshapeExp.html">expr::ReshapeExp<Tensor<gpu, 1, DType></a>, DType, dim, 1></div> |
| <div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  gaussian(<a class="code" href="structmshadow_1_1Shape.html">Shape<dim></a> shape, DType mu = 0.0f, DType sigma = 1.0f);</div> |
| <div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keyword">template</span><<span class="keywordtype">int</span> dim></div> |
| <div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="keyword">inline</span> <a class="code" href="structmshadow_1_1expr_1_1ReshapeExp.html">expr::ReshapeExp<Tensor<gpu, 1, DType></a>, DType, dim, 1></div> |
| <div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  uniform(<a class="code" href="structmshadow_1_1Shape.html">Shape<dim></a> shape);</div> |
| <div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  </div> |
| <div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keyword">private</span>:</div> |
| <div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> GenGaussian(<span class="keywordtype">float</span> *dptr, <span class="keywordtype">size_t</span> size, <span class="keywordtype">float</span> mu, <span class="keywordtype">float</span> sigma) {</div> |
| <div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  curandStatus_t status;</div> |
| <div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  status = curandGenerateNormal(gen_, dptr, size, mu, sigma);</div> |
| <div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  CHECK_EQ(status, CURAND_STATUS_SUCCESS) << <span class="stringliteral">"CURAND Gen Normal float failed."</span></div> |
| <div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  << <span class="stringliteral">" size = "</span> << size</div> |
| <div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  << <span class="stringliteral">",mu = "</span> << mu</div> |
| <div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  << <span class="stringliteral">",sigma = "</span> << sigma;</div> |
| <div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  }</div> |
| <div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> GenGaussian(<span class="keywordtype">double</span> *dptr, <span class="keywordtype">size_t</span> size, <span class="keywordtype">double</span> mu, <span class="keywordtype">double</span> sigma) {</div> |
| <div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  curandStatus_t status;</div> |
| <div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  status = curandGenerateNormalDouble(gen_, dptr, size, mu, sigma);</div> |
| <div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  CHECK_EQ(status, CURAND_STATUS_SUCCESS) << <span class="stringliteral">"CURAND Gen Normal double failed."</span></div> |
| <div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  << <span class="stringliteral">" size = "</span> << size</div> |
| <div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  << <span class="stringliteral">",mu = "</span> << mu</div> |
| <div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  << <span class="stringliteral">",sigma = "</span> << sigma;</div> |
| <div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  }</div> |
| <div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> GenUniform(<span class="keywordtype">float</span> *dptr, <span class="keywordtype">size_t</span> size) {</div> |
| <div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  curandStatus_t status;</div> |
| <div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  status = curandGenerateUniform(gen_, dptr, size);</div> |
| <div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  CHECK_EQ(status, CURAND_STATUS_SUCCESS) << <span class="stringliteral">"CURAND Gen Uniform float failed."</span></div> |
| <div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  << <span class="stringliteral">" size = "</span> << size;</div> |
| <div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  }</div> |
| <div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> GenUniform(<span class="keywordtype">double</span> *dptr, <span class="keywordtype">size_t</span> size) {</div> |
| <div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  curandStatus_t status;</div> |
| <div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  status = curandGenerateUniformDouble(gen_, dptr, size);</div> |
| <div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  CHECK_EQ(status, CURAND_STATUS_SUCCESS) << <span class="stringliteral">"CURAND Gen Uniform double failed."</span></div> |
| <div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  << <span class="stringliteral">" size = "</span> << size;</div> |
| <div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  }</div> |
| <div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> CreateGenerator() {</div> |
| <div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keywordflow">if</span> (gen_ != NULL)</div> |
| <div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  DeleteGenerator();</div> |
| <div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  curandStatus_t status;</div> |
| <div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  status = curandCreateGenerator(&gen_, CURAND_RNG_PSEUDO_DEFAULT);</div> |
| <div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  CHECK_EQ(status, CURAND_STATUS_SUCCESS) << <span class="stringliteral">"Cannot create CURAND Generator"</span>;</div> |
| <div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  }</div> |
| <div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> DeleteGenerator() {</div> |
| <div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <span class="keywordflow">if</span> (gen_ != NULL) {</div> |
| <div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  curandStatus_t status;</div> |
| <div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  status = curandDestroyGenerator(gen_);</div> |
| <div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  CHECK_EQ(status, CURAND_STATUS_SUCCESS) << <span class="stringliteral">"Destory CURAND Gen failed"</span>;</div> |
| <div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  gen_ = NULL;</div> |
| <div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  }</div> |
| <div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  }</div> |
| <div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  curandGenerator_t gen_;</div> |
| <div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  TensorContainer<gpu, 1, DType> buffer_;</div> |
| <div class="line"><a name="l00435"></a><span class="lineno"> 435</span> }; <span class="comment">// class Random<gpu, DType></span></div> |
| <div class="line"><a name="l00436"></a><span class="lineno"> 436</span> <span class="preprocessor">#endif // MSHADOW_USE_CUDA</span></div> |
| <div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  </div> |
| <div class="line"><a name="l00438"></a><span class="lineno"> 438</span> <span class="preprocessor">#ifdef __CUDACC__</span></div> |
| <div class="line"><a name="l00439"></a><span class="lineno"> 439</span> <span class="comment">// implementations that depends on cuda kernels</span></div> |
| <div class="line"><a name="l00440"></a><span class="lineno"> 440</span> <span class="keyword">template</span><<span class="keyword">typename</span> DType></div> |
| <div class="line"><a name="l00441"></a><span class="lineno"> 441</span> <span class="keyword">template</span><<span class="keywordtype">int</span> dim></div> |
| <div class="line"><a name="l00442"></a><span class="lineno"> 442</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespacemxnet.html#a2846f4556c9ca9bd0f567504ce60f274">Random<gpu, DType>::SampleUniform</a>(</div> |
| <div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  Tensor<gpu, dim, DType> *dst, DType a, DType b) {</div> |
| <div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <span class="keywordflow">if</span> (a == 0.0f && b == 1.0f) {</div> |
| <div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="keywordflow">if</span> (dst->CheckContiguous()) {</div> |
| <div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  this->GenUniform(dst->dptr_, dst->shape_.Size());</div> |
| <div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  } <span class="keywordflow">else</span> {</div> |
| <div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  *dst = this->uniform(dst->shape_);</div> |
| <div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  }</div> |
| <div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  } <span class="keywordflow">else</span> {</div> |
| <div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  *dst = this->uniform(dst->shape_) * (b - a) + a;</div> |
| <div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  }</div> |
| <div class="line"><a name="l00453"></a><span class="lineno"> 453</span> }</div> |
| <div class="line"><a name="l00454"></a><span class="lineno"> 454</span> <span class="keyword">template</span><<span class="keyword">typename</span> DType></div> |
| <div class="line"><a name="l00455"></a><span class="lineno"> 455</span> <span class="keyword">template</span><<span class="keywordtype">int</span> dim></div> |
| <div class="line"><a name="l00456"></a><span class="lineno"> 456</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespacemxnet.html#a5a28062f52ca576a126599e7ad487077">Random<gpu, DType>::SampleGaussian</a>(</div> |
| <div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  Tensor<gpu, dim, DType> *dst, DType mu, DType sigma) {</div> |
| <div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="comment">// We need to check whether the shape size is even since CuRand supports only normal distribution</span></div> |
| <div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <span class="comment">// generation of even number of elements.</span></div> |
| <div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <span class="keywordflow">if</span> (dst->CheckContiguous() && (dst->shape_.Size() % 2 == 0)) {</div> |
| <div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  this->GenGaussian(dst->dptr_, dst->shape_.Size(), mu, sigma);</div> |
| <div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  } <span class="keywordflow">else</span> {</div> |
| <div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  *dst = this->gaussian(dst->shape_, mu, sigma);</div> |
| <div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  }</div> |
| <div class="line"><a name="l00465"></a><span class="lineno"> 465</span> }</div> |
| <div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  </div> |
| <div class="line"><a name="l00467"></a><span class="lineno"> 467</span> <span class="keyword">template</span><<span class="keyword">typename</span> DType></div> |
| <div class="line"><a name="l00468"></a><span class="lineno"> 468</span> <span class="keyword">template</span><<span class="keywordtype">int</span> dim></div> |
| <div class="line"><a name="l00469"></a><span class="lineno"> 469</span> <span class="keyword">inline</span> expr::ReshapeExp<Tensor<gpu, 1, DType>, DType, dim, 1></div> |
| <div class="line"><a name="l00470"></a><span class="lineno"> 470</span> <a class="code" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a01b9b81f9ef61fddf8a2fc40adfd32a9">Random<gpu, DType>::gaussian</a>(Shape<dim> shape, DType mu, DType sigma) {</div> |
| <div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keywordtype">size_t</span> aligned_sz = ((shape.Size() + 1UL) >> 1) << 1;</div> |
| <div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <span class="comment">// allocate alligned size</span></div> |
| <div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  buffer_.Resize(<a class="code" href="namespacemshadow.html#a05e468ef4d8882fccce53ae951b7bdbd">Shape1</a>(aligned_sz));</div> |
| <div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  buffer_.Resize(<a class="code" href="namespacemshadow.html#a05e468ef4d8882fccce53ae951b7bdbd">Shape1</a>(shape.Size()));</div> |
| <div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  this->GenGaussian(buffer_.dptr_, aligned_sz, mu, sigma);</div> |
| <div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  <span class="keywordflow">return</span> <a class="code" href="namespacemshadow_1_1expr.html#a73862619baed02a20e49897decf13fc2">expr::reshape</a>(buffer_, shape);</div> |
| <div class="line"><a name="l00477"></a><span class="lineno"> 477</span> }</div> |
| <div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  </div> |
| <div class="line"><a name="l00479"></a><span class="lineno"> 479</span> <span class="keyword">template</span><<span class="keyword">typename</span> DType></div> |
| <div class="line"><a name="l00480"></a><span class="lineno"> 480</span> <span class="keyword">template</span><<span class="keywordtype">int</span> dim></div> |
| <div class="line"><a name="l00481"></a><span class="lineno"> 481</span> <span class="keyword">inline</span> expr::ReshapeExp<Tensor<gpu, 1, DType>, DType, dim, 1></div> |
| <div class="line"><a name="l00482"></a><span class="lineno"> 482</span> <a class="code" href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#ac46b0e134798166fc9d7abd92e8511ed">Random<gpu, DType>::uniform</a>(Shape<dim> shape) {</div> |
| <div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  buffer_.Resize(<a class="code" href="namespacemshadow.html#a05e468ef4d8882fccce53ae951b7bdbd">Shape1</a>(shape.Size()));</div> |
| <div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  this->GenUniform(buffer_.dptr_, buffer_.size(0));</div> |
| <div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <span class="keywordflow">return</span> <a class="code" href="namespacemshadow_1_1expr.html#a73862619baed02a20e49897decf13fc2">expr::reshape</a>(buffer_, shape);</div> |
| <div class="line"><a name="l00486"></a><span class="lineno"> 486</span> }</div> |
| <div class="line"><a name="l00487"></a><span class="lineno"> 487</span> <span class="preprocessor">#endif // __CUDACC__</span></div> |
| <div class="line"><a name="l00488"></a><span class="lineno"> 488</span> } <span class="comment">// namespace mshadow</span></div> |
| <div class="line"><a name="l00489"></a><span class="lineno"> 489</span> <span class="preprocessor">#endif // MSHADOW_RANDOM_H_</span></div> |
| </div><!-- fragment --></div><!-- contents --> |
| <div class="ttc" id="a3rdparty_2mshadow_2mshadow_2base_8h_html_a53a342d1f8cc22d36ed49e4c51c19f0c"><div class="ttname"><a href="3rdparty_2mshadow_2mshadow_2base_8h.html#a53a342d1f8cc22d36ed49e4c51c19f0c">MSHADOW_THROW_EXCEPTION</a></div><div class="ttdeci">#define MSHADOW_THROW_EXCEPTION</div><div class="ttdef"><b>Definition:</b> base.h:250</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a7cbab012322f309825387633c0c0406d"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a7cbab012322f309825387633c0c0406d">mshadow::Random< cpu, DType >::SampleGamma</a></div><div class="ttdeci">void SampleGamma(Tensor< cpu, dim, DType > *dst, PType alpha, PType beta)</div><div class="ttdoc">generate data from a gamma distribution</div><div class="ttdef"><b>Definition:</b> random.h:163</div></div> |
| <div class="ttc" id="astructmshadow_1_1Shape_html_ac6d667fde1a8180b64f475f5d33ea58f"><div class="ttname"><a href="structmshadow_1_1Shape.html#ac6d667fde1a8180b64f475f5d33ea58f">mshadow::Shape::Size</a></div><div class="ttdeci">MSHADOW_XINLINE index_t Size(void) const</div><div class="ttdef"><b>Definition:</b> tensor.h:158</div></div> |
| <div class="ttc" id="anamespacemxnet_html_a5a28062f52ca576a126599e7ad487077"><div class="ttname"><a href="namespacemxnet.html#a5a28062f52ca576a126599e7ad487077">mxnet::SampleGaussian</a></div><div class="ttdeci">void SampleGaussian(real_t mu, real_t sigma, NDArray *out)</div><div class="ttdoc">Sample gaussian distribution for each elements of out.</div></div> |
| <div class="ttc" id="astructmshadow_1_1Stream_html"><div class="ttname"><a href="structmshadow_1_1Stream.html">mshadow::Stream</a></div><div class="ttdoc">computaion stream structure, used for asynchronous computations</div><div class="ttdef"><b>Definition:</b> tensor.h:488</div></div> |
| <div class="ttc" id="anamespacemxnet_html_aed55e8197182b7c66126902b2a43739a"><div class="ttname"><a href="namespacemxnet.html#aed55e8197182b7c66126902b2a43739a">mxnet::SamplePoisson</a></div><div class="ttdeci">void SamplePoisson(real_t lambda, NDArray *out)</div><div class="ttdoc">Sample Poisson distribution for each elements of out.</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01gpu_00_01DType_01_4_html_a47236e16630bfafbf207d1ac57547b18"><div class="ttname"><a href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a47236e16630bfafbf207d1ac57547b18">mshadow::Random< gpu, DType >::Random</a></div><div class="ttdeci">Random(int seed)</div><div class="ttdoc">constructor of random engine</div><div class="ttdef"><b>Definition:</b> random.h:296</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a432b0770283d3fa0292b30a9dceaaccc"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a432b0770283d3fa0292b30a9dceaaccc">mshadow::Random< cpu, DType >::SampleGeneralizedNegativeBinomial</a></div><div class="ttdeci">void SampleGeneralizedNegativeBinomial(Tensor< cpu, dim, DType > *dst, PType mu, PType alpha)</div><div class="ttdoc">generate data from a generalized negative binomial distribution</div><div class="ttdef"><b>Definition:</b> random.h:221</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_html"><div class="ttname"><a href="classmshadow_1_1Random.html">mshadow::Random</a></div><div class="ttdoc">random number generator</div><div class="ttdef"><b>Definition:</b> random.h:45</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a874c3496e212241ae5b127c9f26d17ad"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a874c3496e212241ae5b127c9f26d17ad">mshadow::Random< cpu, DType >::GetRandInt</a></div><div class="ttdeci">unsigned GetRandInt()</div><div class="ttdoc">get some random integer</div><div class="ttdef"><b>Definition:</b> random.h:87</div></div> |
| <div class="ttc" id="astructmshadow_1_1Tensor_html"><div class="ttname"><a href="structmshadow_1_1Tensor.html">mshadow::Tensor</a></div><div class="ttdoc">general tensor</div><div class="ttdef"><b>Definition:</b> tensor.h:525</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_aa93ebb9587b5876ad99953733119377b"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#aa93ebb9587b5876ad99953733119377b">mshadow::Random< cpu, DType >::SampleUniform</a></div><div class="ttdeci">void SampleUniform(Tensor< cpu, dim, DType > *dst, PType a=0.0f, PType b=1.0f)</div><div class="ttdoc">generate data from uniform [a,b)</div><div class="ttdef"><b>Definition:</b> random.h:124</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a37b7e8cbe08d7c0f6699039cc0bad8b2"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a37b7e8cbe08d7c0f6699039cc0bad8b2">mshadow::Random< cpu, DType >::~Random</a></div><div class="ttdeci">~Random(void)</div><div class="ttdef"><b>Definition:</b> random.h:59</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_aedf6b0f62b92f0b57184733c6cc36bb2"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#aedf6b0f62b92f0b57184733c6cc36bb2">mshadow::Random< cpu, DType >::SampleNegativeBinomial</a></div><div class="ttdeci">void SampleNegativeBinomial(Tensor< cpu, dim, DType > *dst, PType1 k, PType2 p)</div><div class="ttdoc">generate data from a negative binomial distribution</div><div class="ttdef"><b>Definition:</b> random.h:206</div></div> |
| <div class="ttc" id="astructmshadow_1_1gpu_html"><div class="ttname"><a href="structmshadow_1_1gpu.html">mshadow::gpu</a></div><div class="ttdoc">device name GPU</div><div class="ttdef"><b>Definition:</b> tensor.h:46</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01gpu_00_01DType_01_4_html_a997d28fe4cfa9a1f36b88160ce61ec9a"><div class="ttname"><a href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a997d28fe4cfa9a1f36b88160ce61ec9a">mshadow::Random< gpu, DType >::Seed</a></div><div class="ttdeci">void Seed(int seed)</div><div class="ttdoc">seed random number generator using this seed</div><div class="ttdef"><b>Definition:</b> random.h:317</div></div> |
| <div class="ttc" id="astructmshadow_1_1cpu_html"><div class="ttname"><a href="structmshadow_1_1cpu.html">mshadow::cpu</a></div><div class="ttdoc">device name CPU</div><div class="ttdef"><b>Definition:</b> tensor.h:39</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_aff2ec8923288cea076f5fa94897c0bfe"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#aff2ec8923288cea076f5fa94897c0bfe">mshadow::Random< cpu, DType >::Seed</a></div><div class="ttdeci">void Seed(int seed)</div><div class="ttdoc">seed random number generator using this seed</div><div class="ttdef"><b>Definition:</b> random.h:65</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01gpu_00_01DType_01_4_html_a8c3a2f7df5bc62093b4a55b9d42bb60e"><div class="ttname"><a href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a8c3a2f7df5bc62093b4a55b9d42bb60e">mshadow::Random< gpu, DType >::GetRandInt</a></div><div class="ttdeci">void GetRandInt(const Tensor< gpu, 1, unsigned > &dst)</div><div class="ttdoc">get a set of random integers</div><div class="ttdef"><b>Definition:</b> random.h:329</div></div> |
| <div class="ttc" id="atensor_8h_html"><div class="ttname"><a href="tensor_8h.html">tensor.h</a></div><div class="ttdoc">header file of tensor data structure and functions This lib requires explicit memory allocation and d...</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a7afa2530a465aadc5151b6841cbf34d6"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a7afa2530a465aadc5151b6841cbf34d6">mshadow::Random< cpu, DType >::GetRandInt</a></div><div class="ttdeci">void GetRandInt(const Tensor< cpu, 1, unsigned > &dst)</div><div class="ttdoc">get a set of random integers</div><div class="ttdef"><b>Definition:</b> random.h:94</div></div> |
| <div class="ttc" id="anamespacemshadow_1_1expr_html_a73862619baed02a20e49897decf13fc2"><div class="ttname"><a href="namespacemshadow_1_1expr.html#a73862619baed02a20e49897decf13fc2">mshadow::expr::reshape</a></div><div class="ttdeci">ReshapeExp< SrcExp, DType, dimdst, ExpInfo< SrcExp >::kDim > reshape(const Exp< SrcExp, DType, etype > &src, Shape< dimdst > oshape)</div><div class="ttdoc">a expression that reshapes a tensor to another shape</div><div class="ttdef"><b>Definition:</b> reshape.h:66</div></div> |
| <div class="ttc" id="astructmshadow_1_1Stream_3_01gpu_01_4_html"><div class="ttname"><a href="structmshadow_1_1Stream_3_01gpu_01_4.html">mshadow::Stream< gpu ></a></div><div class="ttdef"><b>Definition:</b> stream_gpu-inl.h:37</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01gpu_00_01DType_01_4_html_a6600fb034b3c840dd568458b9cea397c"><div class="ttname"><a href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a6600fb034b3c840dd568458b9cea397c">mshadow::Random< gpu, DType >::~Random</a></div><div class="ttdeci">~Random(void) MSHADOW_THROW_EXCEPTION</div><div class="ttdef"><b>Definition:</b> random.h:300</div></div> |
| <div class="ttc" id="anamespacemshadow_html_ac4cba6b672478463350f7d84b47e99e3"><div class="ttname"><a href="namespacemshadow.html#ac4cba6b672478463350f7d84b47e99e3">mshadow::kRandBufferSize</a></div><div class="ttdeci">const unsigned kRandBufferSize</div><div class="ttdoc">buffer size for each random number generator</div><div class="ttdef"><b>Definition:</b> base.h:321</div></div> |
| <div class="ttc" id="astructmshadow_1_1Tensor_html_a9cc7d01a1eb0825d7a3fcdabc8e58f07"><div class="ttname"><a href="structmshadow_1_1Tensor.html#a9cc7d01a1eb0825d7a3fcdabc8e58f07">mshadow::Tensor::CheckContiguous</a></div><div class="ttdeci">MSHADOW_XINLINE bool CheckContiguous(void) const</div><div class="ttdef"><b>Definition:</b> tensor.h:596</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a3ff7a0fd2fdaa4bcc166a73fbd1f2a10"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a3ff7a0fd2fdaa4bcc166a73fbd1f2a10">mshadow::Random< cpu, DType >::SampleDistribution</a></div><div class="ttdeci">void SampleDistribution(Tensor< cpu, dim, DType > *dst, Sampler sampler)</div><div class="ttdoc">generate data from a distribution</div><div class="ttdef"><b>Definition:</b> random.h:105</div></div> |
| <div class="ttc" id="astructmshadow_1_1Tensor_html_ad10c7414c5948e789e8761df2083c4e5"><div class="ttname"><a href="structmshadow_1_1Tensor.html#ad10c7414c5948e789e8761df2083c4e5">mshadow::Tensor::shape_</a></div><div class="ttdeci">Shape< dimension > shape_</div><div class="ttdoc">shape of the tensor</div><div class="ttdef"><b>Definition:</b> tensor.h:541</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a0096231388917db869409e0f587b1cf3"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a0096231388917db869409e0f587b1cf3">mshadow::Random< cpu, DType >::set_stream</a></div><div class="ttdeci">void set_stream(Stream< cpu > *stream)</div><div class="ttdoc">set the stream of computation</div><div class="ttdef"><b>Definition:</b> random.h:80</div></div> |
| <div class="ttc" id="astructmshadow_1_1expr_1_1ReshapeExp_html"><div class="ttname"><a href="structmshadow_1_1expr_1_1ReshapeExp.html">mshadow::expr::ReshapeExp</a></div><div class="ttdoc">reshape the content to another shape input: Tensor<Device,dimsrc>: ishape output: Tensor<Device,...</div><div class="ttdef"><b>Definition:</b> reshape.h:39</div></div> |
| <div class="ttc" id="anamespacemshadow_html_adcbc2e1131386fccb1474b0bdf045926"><div class="ttname"><a href="namespacemshadow.html#adcbc2e1131386fccb1474b0bdf045926">mshadow::index_t</a></div><div class="ttdeci">int32_t index_t</div><div class="ttdoc">type that will be used for index</div><div class="ttdef"><b>Definition:</b> base.h:328</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a95a7e32484bfb144d355bda1abf7bb83"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a95a7e32484bfb144d355bda1abf7bb83">mshadow::Random< cpu, DType >::SampleExponential</a></div><div class="ttdeci">void SampleExponential(Tensor< cpu, dim, DType > *dst, PType lambda)</div><div class="ttdoc">generate data from an exponential distribution</div><div class="ttdef"><b>Definition:</b> random.h:178</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a4ca9b27ca3752795017372a05cfce5c3"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a4ca9b27ca3752795017372a05cfce5c3">mshadow::Random< cpu, DType >::gaussian</a></div><div class="ttdeci">expr::ReshapeExp< Tensor< cpu, 1, DType >, DType, dim, 1 > gaussian(Shape< dim > shape)</div><div class="ttdoc">return a temporal expression storing standard gaussian random variables the temporal tensor is only v...</div><div class="ttdef"><b>Definition:</b> random.h:249</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a41b3d2a322bbd6fc2679275b80c27342"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a41b3d2a322bbd6fc2679275b80c27342">mshadow::Random< cpu, DType >::GetSeed</a></div><div class="ttdeci">unsigned GetSeed() const</div><div class="ttdoc">get random seed used in random generator</div><div class="ttdef"><b>Definition:</b> random.h:73</div></div> |
| <div class="ttc" id="anamespacemshadow_html"><div class="ttname"><a href="namespacemshadow.html">mshadow</a></div><div class="ttdoc">overloaded + operator between half_t and bf16_t</div><div class="ttdef"><b>Definition:</b> base.h:319</div></div> |
| <div class="ttc" id="astructmshadow_1_1Tensor_html_a48a5927e810fbc45e43e92cfe397d9f2"><div class="ttname"><a href="structmshadow_1_1Tensor.html#a48a5927e810fbc45e43e92cfe397d9f2">mshadow::Tensor::FlatTo2D</a></div><div class="ttdeci">MSHADOW_XINLINE Tensor< Device, 2, DType > FlatTo2D(void) const</div><div class="ttdoc">flatten the tensor to 2 dimension, collapse the higher dimensions together</div><div class="ttdef"><b>Definition:</b> tensor.h:624</div></div> |
| <div class="ttc" id="aclassmshadow_1_1TensorContainer_html"><div class="ttname"><a href="classmshadow_1_1TensorContainer.html">mshadow::TensorContainer</a></div><div class="ttdoc">tensor container that does memory allocation and resize like STL, use it to save the lines of FreeSpa...</div><div class="ttdef"><b>Definition:</b> tensor_container.h:40</div></div> |
| <div class="ttc" id="anamespacemxnet_html_a2846f4556c9ca9bd0f567504ce60f274"><div class="ttname"><a href="namespacemxnet.html#a2846f4556c9ca9bd0f567504ce60f274">mxnet::SampleUniform</a></div><div class="ttdeci">void SampleUniform(real_t begin, real_t end, NDArray *out)</div><div class="ttdoc">Sample uniform distribution for each elements of out.</div></div> |
| <div class="ttc" id="astructmshadow_1_1Shape_html"><div class="ttname"><a href="structmshadow_1_1Shape.html">mshadow::Shape< dim ></a></div></div> |
| <div class="ttc" id="astructmshadow_1_1Tensor_html_ad86d6759c585efb5229b3a0659973838"><div class="ttname"><a href="structmshadow_1_1Tensor.html#ad86d6759c585efb5229b3a0659973838">mshadow::Tensor::dptr_</a></div><div class="ttdeci">DType * dptr_</div><div class="ttdoc">pointer to the data</div><div class="ttdef"><b>Definition:</b> tensor.h:539</div></div> |
| <div class="ttc" id="atensor__container_8h_html"><div class="ttname"><a href="tensor__container_8h.html">tensor_container.h</a></div><div class="ttdoc">tensor container that does memory allocation and resize like STL</div></div> |
| <div class="ttc" id="anamespacemshadow_html_a05e468ef4d8882fccce53ae951b7bdbd"><div class="ttname"><a href="namespacemshadow.html#a05e468ef4d8882fccce53ae951b7bdbd">mshadow::Shape1</a></div><div class="ttdeci">MSHADOW_XINLINE Shape< 1 > Shape1(index_t s0)</div><div class="ttdoc">construct a one dimension shape, stride will equal s0</div><div class="ttdef"><b>Definition:</b> tensor.h:220</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a6fbb05ba7472a75c6b9fbc68903e0713"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a6fbb05ba7472a75c6b9fbc68903e0713">mshadow::Random< cpu, DType >::SampleGaussian</a></div><div class="ttdeci">void SampleGaussian(Tensor< cpu, dim, DType > *dst, PType mu=0.0f, PType sigma=1.0f)</div><div class="ttdoc">generate data from standard gaussian</div><div class="ttdef"><b>Definition:</b> random.h:144</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a1737028fbdf8a8226ad5e6d37356ba66"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a1737028fbdf8a8226ad5e6d37356ba66">mshadow::Random< cpu, DType >::SamplePoisson</a></div><div class="ttdeci">void SamplePoisson(Tensor< cpu, dim, DType > *dst, PType lambda)</div><div class="ttdoc">generate data from a poisson distribution</div><div class="ttdef"><b>Definition:</b> random.h:192</div></div> |
| <div class="ttc" id="astructmshadow_1_1Tensor_html_a88cbcae11653307bfa4c99804320b638"><div class="ttname"><a href="structmshadow_1_1Tensor.html#a88cbcae11653307bfa4c99804320b638">mshadow::Tensor::size</a></div><div class="ttdeci">MSHADOW_XINLINE index_t size(int idx) const</div><div class="ttdoc">return size of i-th dimension, start counting from highest dimension</div><div class="ttdef"><b>Definition:</b> tensor.h:610</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a02bf4cce9c068da452494452432fcf7f"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a02bf4cce9c068da452494452432fcf7f">mshadow::Random< cpu, DType >::GetRndEngine</a></div><div class="ttdeci">std::mt19937 & GetRndEngine()</div><div class="ttdef"><b>Definition:</b> random.h:273</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01gpu_00_01DType_01_4_html_a01b9b81f9ef61fddf8a2fc40adfd32a9"><div class="ttname"><a href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#a01b9b81f9ef61fddf8a2fc40adfd32a9">mshadow::Random< gpu, DType >::gaussian</a></div><div class="ttdeci">expr::ReshapeExp< Tensor< gpu, 1, DType >, DType, dim, 1 > gaussian(Shape< dim > shape, DType mu=0.0f, DType sigma=1.0f)</div><div class="ttdoc">return a temporal expression storing standard gaussian random variables the temporal tensor is only v...</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a4eae04b06525d65b839f2c9c5428c436"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a4eae04b06525d65b839f2c9c5428c436">mshadow::Random< cpu, DType >::uniform</a></div><div class="ttdeci">expr::ReshapeExp< Tensor< cpu, 1, DType >, DType, dim, 1 > uniform(Shape< dim > shape)</div><div class="ttdoc">return a temporal expression storing standard uniform [0,1) the temporal tensor is only valid before ...</div><div class="ttdef"><b>Definition:</b> random.h:267</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01gpu_00_01DType_01_4_html_ac46b0e134798166fc9d7abd92e8511ed"><div class="ttname"><a href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#ac46b0e134798166fc9d7abd92e8511ed">mshadow::Random< gpu, DType >::uniform</a></div><div class="ttdeci">expr::ReshapeExp< Tensor< gpu, 1, DType >, DType, dim, 1 > uniform(Shape< dim > shape)</div><div class="ttdoc">return a temporal expression storing standard uniform [0,1) the temporal tensor is only valid before ...</div></div> |
| <div class="ttc" id="a3rdparty_2mshadow_2mshadow_2base_8h_html"><div class="ttname"><a href="3rdparty_2mshadow_2mshadow_2base_8h.html">base.h</a></div><div class="ttdoc">definitions of base types, operators, macros functions</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01cpu_00_01DType_01_4_html_a468829a8a58919ec4aadb1e75a6174ff"><div class="ttname"><a href="classmshadow_1_1Random_3_01cpu_00_01DType_01_4.html#a468829a8a58919ec4aadb1e75a6174ff">mshadow::Random< cpu, DType >::Random</a></div><div class="ttdeci">Random(int seed)</div><div class="ttdoc">constructor of random engine</div><div class="ttdef"><b>Definition:</b> random.h:55</div></div> |
| <div class="ttc" id="aclassmshadow_1_1Random_3_01gpu_00_01DType_01_4_html_ac813f60f1d2d7c7e5cd4a4cc15068667"><div class="ttname"><a href="classmshadow_1_1Random_3_01gpu_00_01DType_01_4.html#ac813f60f1d2d7c7e5cd4a4cc15068667">mshadow::Random< gpu, DType >::set_stream</a></div><div class="ttdeci">void set_stream(Stream< gpu > *stream)</div><div class="ttdoc">set the stream of computation</div><div class="ttdef"><b>Definition:</b> random.h:307</div></div> |
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