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<a href="_tensor_8hpp.html">浏览该文件的文档.</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">// Tensor.hpp</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// MNN</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment">// Created by MNN on 2018/08/14.</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment">// Copyright © 2018, Alibaba Group Holding Limited</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment">//</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#ifndef Tensor_hpp</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#define Tensor_hpp</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include "<a class="code" href="_halide_runtime_8h.html">HalideRuntime.h</a>"</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include "<a class="code" href="_m_n_n_define_8h.html">MNNDefine.h</a>"</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="keyword">namespace </span><a class="code" href="namespace_m_n_n.html">MNN</a> {</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00025"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html"> 25</a></span> <span class="keyword">class </span><a class="code" href="_m_n_n_define_8h.html#a692428e2a0af8ffb79376d223a0695ab">MNN_PUBLIC</a> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a> {</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keyword">struct </span>InsideDescribe;</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00030"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56"> 30</a></span>  <span class="keyword">enum</span> <a class="code" href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56">DimensionType</a> {</div><div class="line"><a name="l00032"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56a2e15384aba40fa633bdac31ea6114ff0"> 32</a></span>  <a class="code" href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56a2e15384aba40fa633bdac31ea6114ff0">TENSORFLOW</a>,</div><div class="line"><a name="l00034"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56a0075eb881e1bf0f0e4e47b6d2c09c409"> 34</a></span>  <a class="code" href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56a0075eb881e1bf0f0e4e47b6d2c09c409">CAFFE</a>,</div><div class="line"><a name="l00036"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56aee9d6efa4285615bbb6a799ea831f62e"> 36</a></span>  CAFFE_C4</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> </div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1a7b058a27868208a3a10a61ae74051c"> 40</a></span>  <span class="keyword">enum</span> <a class="code" href="class_m_n_n_1_1_tensor.html#a1a7b058a27868208a3a10a61ae74051c">HandleDataType</a> {</div><div class="line"><a name="l00042"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1a7b058a27868208a3a10a61ae74051ca2f46c5fa96e1f0de21aaf29bc2e0421b"> 42</a></span>  HANDLE_NONE = 0,</div><div class="line"><a name="l00044"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1a7b058a27868208a3a10a61ae74051ca27a049e2f1db85abc9f803addb518a52"> 44</a></span>  HANDLE_STRING = 1</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  };</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00048"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1fa4cb1d96822754ca18a838fdc3ad03"> 48</a></span>  <span class="keyword">enum</span> <a class="code" href="class_m_n_n_1_1_tensor.html#a1fa4cb1d96822754ca18a838fdc3ad03">DataReorderType</a> {</div><div class="line"><a name="l00050"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1fa4cb1d96822754ca18a838fdc3ad03a68b82f5cd23f37cdfcf966667c09b44e"> 50</a></span>  NO_REORDER = 0,</div><div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1fa4cb1d96822754ca18a838fdc3ad03af77dd834f695e8ece3d80a6d21fe5b0d"> 52</a></span>  REORDER_4 = 1,</div><div class="line"><a name="l00054"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a1fa4cb1d96822754ca18a838fdc3ad03a25762a64b006ba9584a919a74bd7b49f"> 54</a></span>  REORDER_8</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> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>(<span class="keywordtype">int</span> dimSize = 4, DimensionType type = CAFFE);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>(<span class="keyword">const</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>* tensor, DimensionType type = CAFFE, <span class="keywordtype">bool</span> allocMemory = <span class="keyword">true</span>);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  ~<a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>();</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> <span class="keyword">private</span>:</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="comment">// remove all assignment operator</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>(<span class="keyword">const</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>& tensor) = <span class="keyword">delete</span>;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>(<span class="keyword">const</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>&& tensor) = <span class="keyword">delete</span>;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>& operator=(<span class="keyword">const</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>&) = <span class="keyword">delete</span>;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>& operator=(<span class="keyword">const</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>&&) = <span class="keyword">delete</span>;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keyword">static</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>* createDevice(<span class="keyword">const</span> std::vector<int>& shape, <a class="code" href="structhalide__type__t.html">halide_type_t</a> type, DimensionType dimType = TENSORFLOW);</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> </div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00103"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#aa279b55e3b5d0e2dabbaaf74e3da3e3b"> 103</a></span>  <span class="keyword">static</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>* <a class="code" href="class_m_n_n_1_1_tensor.html#aa279b55e3b5d0e2dabbaaf74e3da3e3b">createDevice</a>(<span class="keyword">const</span> std::vector<int>& shape, <a class="code" href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56">DimensionType</a> dimType = TENSORFLOW) {</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordflow">return</span> createDevice(shape, halide_type_of<T>(), dimType);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  }</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keyword">static</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>* create(<span class="keyword">const</span> std::vector<int>& shape, <a class="code" href="structhalide__type__t.html">halide_type_t</a> type, <span class="keywordtype">void</span>* data = NULL,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  DimensionType dimType = TENSORFLOW);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00126"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#aea2d0916fda8cef1fa641c23807a3b5c"> 126</a></span>  <span class="keyword">static</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>* <a class="code" href="class_m_n_n_1_1_tensor.html#aea2d0916fda8cef1fa641c23807a3b5c">create</a>(<span class="keyword">const</span> std::vector<int>& shape, <span class="keywordtype">void</span>* data = NULL, <a class="code" href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56">DimensionType</a> dimType = TENSORFLOW) {</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">return</span> create(shape, halide_type_of<T>(), data, dimType);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</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">public</span>:</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keywordtype">bool</span> copyFromHostTensor(<span class="keyword">const</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>* hostTensor);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keywordtype">bool</span> copyToHostTensor(<a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>* hostTensor) <span class="keyword">const</span>;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="keyword">static</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>* createHostTensorFromDevice(<span class="keyword">const</span> <a class="code" href="class_m_n_n_1_1_tensor.html">Tensor</a>* deviceTensor, <span class="keywordtype">bool</span> copyData = <span class="keyword">true</span>);</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> </div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00154"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#aa26783eaf35d8a554a4221f37d06e70a"> 154</a></span>  <span class="keyword">const</span> <a class="code" href="structhalide__buffer__t.html">halide_buffer_t</a>& <a class="code" href="class_m_n_n_1_1_tensor.html#aa26783eaf35d8a554a4221f37d06e70a">buffer</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordflow">return</span> mBuffer;</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  }</div><div class="line"><a name="l00157"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#ab08fdc1ae9e677da39a9e23497ab34a1"> 157</a></span>  <a class="code" href="structhalide__buffer__t.html">halide_buffer_t</a>& <a class="code" href="class_m_n_n_1_1_tensor.html#ab08fdc1ae9e677da39a9e23497ab34a1">buffer</a>() {</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keywordflow">return</span> mBuffer;</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  }</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  DimensionType getDimensionType() <span class="keyword">const</span>;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  HandleDataType getHandleDataType() <span class="keyword">const</span>;</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keywordtype">void</span> setType(<span class="keywordtype">int</span> type);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00183"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a8c1a87ef0b47e372f42fe627747acf76"> 183</a></span>  <span class="keyword">inline</span> <a class="code" href="structhalide__type__t.html">halide_type_t</a> <a class="code" href="class_m_n_n_1_1_tensor.html#a8c1a87ef0b47e372f42fe627747acf76">getType</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordflow">return</span> mBuffer.type;</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  }</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00192"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#abc30b060584e20059369acc3cb88d073"> 192</a></span>  T* <a class="code" href="class_m_n_n_1_1_tensor.html#abc30b060584e20059369acc3cb88d073">host</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keywordflow">return</span> (T*)mBuffer.host;</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  }</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div><div class="line"><a name="l00200"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a79200212a531a64e861f87f394077889"> 200</a></span>  uint64_t <a class="code" href="class_m_n_n_1_1_tensor.html#a79200212a531a64e861f87f394077889">deviceId</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keywordflow">return</span> mBuffer.device;</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  }</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> </div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00205"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a048c5b3e7287526a825948fc1d9bf8fb"> 205</a></span>  <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#a048c5b3e7287526a825948fc1d9bf8fb">dimensions</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keywordflow">return</span> mBuffer.dimensions;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  }</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  std::vector<int> shape() <span class="keyword">const</span>;</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> </div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordtype">int</span> size() <span class="keyword">const</span>;</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> </div><div class="line"><a name="l00225"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a324f5b9156ba3994afbf355255db1b85"> 225</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#a324f5b9156ba3994afbf355255db1b85">elementSize</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="keywordflow">return</span> size() / mBuffer.type.bytes();</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  }</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> </div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="comment">// for CAFFE tensors only.</span></div><div class="line"><a name="l00231"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#ad55d96559751d5eabc5de9776b5d9151"> 231</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#ad55d96559751d5eabc5de9776b5d9151">width</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keywordflow">return</span> mBuffer.dim[3].extent;</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  }</div><div class="line"><a name="l00234"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a10f9cd60e6c5423d90dfb3025d4d60c7"> 234</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#a10f9cd60e6c5423d90dfb3025d4d60c7">height</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordflow">return</span> mBuffer.dim[2].extent;</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  }</div><div class="line"><a name="l00237"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#abbf49c308f681e0f9e416476b72be0d9"> 237</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#abbf49c308f681e0f9e416476b72be0d9">channel</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="keywordflow">return</span> mBuffer.dim[1].extent;</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  }</div><div class="line"><a name="l00240"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#abf36a5bb25335dcfab95c687b4090bee"> 240</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#abf36a5bb25335dcfab95c687b4090bee">batch</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keywordflow">return</span> mBuffer.dim[0].extent;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  }</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <span class="comment">// for TENSORFLOW tensors only.</span></div><div class="line"><a name="l00245"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a4996312c75e4e664af9e8b93369ae3b6"> 245</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#a4996312c75e4e664af9e8b93369ae3b6">tfWidth</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keywordflow">return</span> mBuffer.dim[2].extent;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  }</div><div class="line"><a name="l00248"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#aed0c48473214bf9596bab3235918497f"> 248</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#aed0c48473214bf9596bab3235918497f">tfHeight</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordflow">return</span> mBuffer.dim[1].extent;</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  }</div><div class="line"><a name="l00251"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a24be036d72e6680b92513090d541804f"> 251</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#a24be036d72e6680b92513090d541804f">tfChannel</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">return</span> mBuffer.dim[3].extent;</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  }</div><div class="line"><a name="l00254"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a3fc95b1ca0cdf43aa6a77890c52a86a6"> 254</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#a3fc95b1ca0cdf43aa6a77890c52a86a6">tfBatch</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keywordflow">return</span> mBuffer.dim[0].extent;</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  }</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> </div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="comment">// visit dimension's extent & stride</span></div><div class="line"><a name="l00259"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#aae201441d5f9ddbc6311f7945e1b71e5"> 259</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#aae201441d5f9ddbc6311f7945e1b71e5">stride</a>(<span class="keywordtype">int</span> index)<span class="keyword"> const </span>{</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keywordflow">return</span> mBuffer.dim[index].stride;</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  }</div><div class="line"><a name="l00262"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#ad815d5e2ffc23a7133de6f68feff28ee"> 262</a></span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="class_m_n_n_1_1_tensor.html#ad815d5e2ffc23a7133de6f68feff28ee">length</a>(<span class="keywordtype">int</span> index)<span class="keyword"> const </span>{</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="keywordflow">return</span> mBuffer.dim[index].extent;</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  }</div><div class="line"><a name="l00265"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#acbfb65c02f4f7b031dac80aa7dc8f9a1"> 265</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="class_m_n_n_1_1_tensor.html#acbfb65c02f4f7b031dac80aa7dc8f9a1">setStride</a>(<span class="keywordtype">int</span> index, <span class="keywordtype">int</span> stride) {</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  mBuffer.dim[index].stride = stride;</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  }</div><div class="line"><a name="l00268"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#ab45e71dd654c30ede21032db4331100a"> 268</a></span>  <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="class_m_n_n_1_1_tensor.html#ab45e71dd654c30ede21032db4331100a">setLength</a>(<span class="keywordtype">int</span> index, <span class="keywordtype">int</span> length) {</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  mBuffer.dim[index].extent = length;</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  }</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> <span class="keyword">public</span>:</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <span class="keywordtype">void</span> print() <span class="keyword">const</span>;</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> </div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="structhalide__buffer__t.html">halide_buffer_t</a> mBuffer;</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keyword">struct </span>InsideDescribe* mDescribe;</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> </div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00283"></a><span class="lineno"><a class="line" href="class_m_n_n_1_1_tensor.html#a64e8396ba37ccf60ea12a4c481609dca"> 283</a></span>  <span class="keyword">friend</span> <span class="keyword">class </span>TensorUtils;</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> };</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> } <span class="comment">// namespace MNN</span></div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="preprocessor">#endif </span><span class="comment">/* Tensor_hpp */</span><span class="preprocessor"></span></div><div class="ttc" id="class_m_n_n_1_1_tensor_html_a324f5b9156ba3994afbf355255db1b85"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a324f5b9156ba3994afbf355255db1b85">MNN::Tensor::elementSize</a></div><div class="ttdeci">int elementSize() const</div><div class="ttdoc">calculate number of elements needed to store data taking reordering flag into account.</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:225</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_abf36a5bb25335dcfab95c687b4090bee"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#abf36a5bb25335dcfab95c687b4090bee">MNN::Tensor::batch</a></div><div class="ttdeci">int batch() const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:240</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_aa279b55e3b5d0e2dabbaaf74e3da3e3b"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#aa279b55e3b5d0e2dabbaaf74e3da3e3b">MNN::Tensor::createDevice</a></div><div class="ttdeci">static Tensor * createDevice(const std::vector< int > &shape, DimensionType dimType=TENSORFLOW)</div><div class="ttdoc">create tensor with shape and dimension type. data type is represented by T.</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:103</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a1a270092aad286acb9b3112a395ebd56a0075eb881e1bf0f0e4e47b6d2c09c409"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56a0075eb881e1bf0f0e4e47b6d2c09c409">MNN::Tensor::CAFFE</a></div><div class="ttdef"><b>Definition:</b> Tensor.hpp:34</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a1fa4cb1d96822754ca18a838fdc3ad03"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a1fa4cb1d96822754ca18a838fdc3ad03">MNN::Tensor::DataReorderType</a></div><div class="ttdeci">DataReorderType</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:48</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a3fc95b1ca0cdf43aa6a77890c52a86a6"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a3fc95b1ca0cdf43aa6a77890c52a86a6">MNN::Tensor::tfBatch</a></div><div class="ttdeci">int tfBatch() const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:254</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a1a270092aad286acb9b3112a395ebd56a2e15384aba40fa633bdac31ea6114ff0"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56a2e15384aba40fa633bdac31ea6114ff0">MNN::Tensor::TENSORFLOW</a></div><div class="ttdef"><b>Definition:</b> Tensor.hpp:32</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_ad55d96559751d5eabc5de9776b5d9151"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#ad55d96559751d5eabc5de9776b5d9151">MNN::Tensor::width</a></div><div class="ttdeci">int width() const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:231</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_ab08fdc1ae9e677da39a9e23497ab34a1"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#ab08fdc1ae9e677da39a9e23497ab34a1">MNN::Tensor::buffer</a></div><div class="ttdeci">halide_buffer_t & buffer()</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:157</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_ad815d5e2ffc23a7133de6f68feff28ee"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#ad815d5e2ffc23a7133de6f68feff28ee">MNN::Tensor::length</a></div><div class="ttdeci">int length(int index) const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:262</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_ab45e71dd654c30ede21032db4331100a"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#ab45e71dd654c30ede21032db4331100a">MNN::Tensor::setLength</a></div><div class="ttdeci">void setLength(int index, int length)</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:268</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a10f9cd60e6c5423d90dfb3025d4d60c7"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a10f9cd60e6c5423d90dfb3025d4d60c7">MNN::Tensor::height</a></div><div class="ttdeci">int height() const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:234</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a4996312c75e4e664af9e8b93369ae3b6"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a4996312c75e4e664af9e8b93369ae3b6">MNN::Tensor::tfWidth</a></div><div class="ttdeci">int tfWidth() const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:245</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_aae201441d5f9ddbc6311f7945e1b71e5"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#aae201441d5f9ddbc6311f7945e1b71e5">MNN::Tensor::stride</a></div><div class="ttdeci">int stride(int index) const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:259</div></div>
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<div class="ttc" id="_halide_runtime_8h_html"><div class="ttname"><a href="_halide_runtime_8h.html">HalideRuntime.h</a></div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html">MNN::Tensor</a></div><div class="ttdef"><b>Definition:</b> Tensor.hpp:25</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_abc30b060584e20059369acc3cb88d073"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#abc30b060584e20059369acc3cb88d073">MNN::Tensor::host</a></div><div class="ttdeci">T * host() const</div><div class="ttdoc">visit host memory, data type is represented by T.</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:192</div></div>
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<div class="ttc" id="_m_n_n_define_8h_html_a692428e2a0af8ffb79376d223a0695ab"><div class="ttname"><a href="_m_n_n_define_8h.html#a692428e2a0af8ffb79376d223a0695ab">MNN_PUBLIC</a></div><div class="ttdeci">#define MNN_PUBLIC</div><div class="ttdef"><b>Definition:</b> MNNDefine.h:53</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_aa26783eaf35d8a554a4221f37d06e70a"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#aa26783eaf35d8a554a4221f37d06e70a">MNN::Tensor::buffer</a></div><div class="ttdeci">const halide_buffer_t & buffer() const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:154</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a1a270092aad286acb9b3112a395ebd56"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a1a270092aad286acb9b3112a395ebd56">MNN::Tensor::DimensionType</a></div><div class="ttdeci">DimensionType</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:30</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a24be036d72e6680b92513090d541804f"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a24be036d72e6680b92513090d541804f">MNN::Tensor::tfChannel</a></div><div class="ttdeci">int tfChannel() const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:251</div></div>
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<div class="ttc" id="structhalide__type__t_html"><div class="ttname"><a href="structhalide__type__t.html">halide_type_t</a></div><div class="ttdef"><b>Definition:</b> HalideRuntime.h:82</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a8c1a87ef0b47e372f42fe627747acf76"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a8c1a87ef0b47e372f42fe627747acf76">MNN::Tensor::getType</a></div><div class="ttdeci">halide_type_t getType() const</div><div class="ttdoc">get data type.</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:183</div></div>
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<div class="ttc" id="namespace_m_n_n_html"><div class="ttname"><a href="namespace_m_n_n.html">MNN</a></div><div class="ttdef"><b>Definition:</b> AutoTime.hpp:16</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_acbfb65c02f4f7b031dac80aa7dc8f9a1"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#acbfb65c02f4f7b031dac80aa7dc8f9a1">MNN::Tensor::setStride</a></div><div class="ttdeci">void setStride(int index, int stride)</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:265</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a048c5b3e7287526a825948fc1d9bf8fb"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a048c5b3e7287526a825948fc1d9bf8fb">MNN::Tensor::dimensions</a></div><div class="ttdeci">int dimensions() const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:205</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_abbf49c308f681e0f9e416476b72be0d9"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#abbf49c308f681e0f9e416476b72be0d9">MNN::Tensor::channel</a></div><div class="ttdeci">int channel() const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:237</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_aed0c48473214bf9596bab3235918497f"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#aed0c48473214bf9596bab3235918497f">MNN::Tensor::tfHeight</a></div><div class="ttdeci">int tfHeight() const</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:248</div></div>
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<div class="ttc" id="structhalide__buffer__t_html"><div class="ttname"><a href="structhalide__buffer__t.html">halide_buffer_t</a></div><div class="ttdef"><b>Definition:</b> HalideRuntime.h:203</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a79200212a531a64e861f87f394077889"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a79200212a531a64e861f87f394077889">MNN::Tensor::deviceId</a></div><div class="ttdeci">uint64_t deviceId() const</div><div class="ttdoc">visit device memory.</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:200</div></div>
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<div class="ttc" id="_m_n_n_define_8h_html"><div class="ttname"><a href="_m_n_n_define_8h.html">MNNDefine.h</a></div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_aea2d0916fda8cef1fa641c23807a3b5c"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#aea2d0916fda8cef1fa641c23807a3b5c">MNN::Tensor::create</a></div><div class="ttdeci">static Tensor * create(const std::vector< int > &shape, void *data=NULL, DimensionType dimType=TENSORFLOW)</div><div class="ttdoc">create tensor with shape, data and dimension type. data type is represented by T.</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:126</div></div>
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<div class="ttc" id="class_m_n_n_1_1_tensor_html_a1a7b058a27868208a3a10a61ae74051c"><div class="ttname"><a href="class_m_n_n_1_1_tensor.html#a1a7b058a27868208a3a10a61ae74051c">MNN::Tensor::HandleDataType</a></div><div class="ttdeci">HandleDataType</div><div class="ttdef"><b>Definition:</b> Tensor.hpp:40</div></div>
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