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<li class="navelem"><a class="el" href="dir_6b3ae6988449b0834e9596fad5d75199.html">gpu</a></li><li class="navelem"><a class="el" href="dir_498271007b03b2a0521055e88776887b.html">utils</a></li> </ul>
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<div class="title">HostTensor-inl.cuh</div> </div>
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</div><!--header-->
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<div class="contents">
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment"></span></div>
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<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">/**</span></div>
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<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * Copyright (c) 2015-present, Facebook, Inc.</span></div>
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<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * All rights reserved.</span></div>
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<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div>
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<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * This source code is licensed under the CC-by-NC license found in the</span></div>
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<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * LICENSE file in the root directory of this source tree.</span></div>
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<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> */</span></div>
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<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div>
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<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment">// Copyright 2004-present Facebook. All Rights Reserved.</span></div>
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<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div>
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<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
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<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div>
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<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> Contig,</div>
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<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>  <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> <<span class="keyword">typename</span> U> <span class="keyword">class </span>PtrTraits></div>
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<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> __host__</div>
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<div class="line"><a name="l00017"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#ae5c1a2f1eee3e72ee77d5b5bac5769e3"> 17</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#ae5c1a2f1eee3e72ee77d5b5bac5769e3">HostTensor<T, Dim, Contig, IndexT, PtrTraits>::HostTensor</a>() :</div>
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<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, Contig, IndexT, PtrTraits>(),</div>
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<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  state_(AllocState::NotOwner) {</div>
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<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> }</div>
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<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> </div>
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<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> Contig,</div>
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<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> <<span class="keyword">typename</span> U> <span class="keyword">class </span>PtrTraits></div>
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<div class="line"><a name="l00024"></a><span class="lineno"> 24</span> __host__</div>
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<div class="line"><a name="l00025"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#a5dab0d97255fed9b1da4fc7c33a89621"> 25</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a5dab0d97255fed9b1da4fc7c33a89621">HostTensor<T, Dim, Contig, IndexT, PtrTraits>::~HostTensor</a>() {</div>
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<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keywordflow">if</span> (state_ == AllocState::Owner) {</div>
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<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  FAISS_ASSERT(this->data_ != <span class="keyword">nullptr</span>);</div>
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<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keyword">delete</span>[] this->data_;</div>
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<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  this->data_ = <span class="keyword">nullptr</span>;</div>
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<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  }</div>
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<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> }</div>
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<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div>
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<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> Contig,</div>
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<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> <<span class="keyword">typename</span> U> <span class="keyword">class </span>PtrTraits></div>
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<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> __host__</div>
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<div class="line"><a name="l00036"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#add0b28c9c2e751a7678b8111382f2e13"> 36</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#ae5c1a2f1eee3e72ee77d5b5bac5769e3">HostTensor<T, Dim, Contig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keyword">const</span> IndexT sizes[Dim]) :</div>
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<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, Contig, IndexT, PtrTraits>(nullptr, sizes),</div>
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<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  state_(AllocState::Owner) {</div>
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<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div>
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<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a08024dbcaed3c1235cac62b476f14509">data_</a> = <span class="keyword">new</span> T[this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a41f7f08246bf8584929693bb1896205f">numElements</a>()];</div>
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<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  FAISS_ASSERT(this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a08024dbcaed3c1235cac62b476f14509">data_</a> != <span class="keyword">nullptr</span>);</div>
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<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> }</div>
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<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div>
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<div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> Contig,</div>
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<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> <<span class="keyword">typename</span> U> <span class="keyword">class </span>PtrTraits></div>
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<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> __host__</div>
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<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#ae5c1a2f1eee3e72ee77d5b5bac5769e3">HostTensor<T, Dim, Contig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  std::initializer_list<IndexT> sizes) :</div>
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<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, Contig, IndexT, PtrTraits>(nullptr, sizes),</div>
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<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  state_(AllocState::Owner) {</div>
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<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a08024dbcaed3c1235cac62b476f14509">data_</a> = <span class="keyword">new</span> T[this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a41f7f08246bf8584929693bb1896205f">numElements</a>()];</div>
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<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  FAISS_ASSERT(this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a08024dbcaed3c1235cac62b476f14509">data_</a> != <span class="keyword">nullptr</span>);</div>
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<div class="line"><a name="l00054"></a><span class="lineno"> 54</span> }</div>
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<div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div>
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<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> Contig,</div>
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<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> <<span class="keyword">typename</span> U> <span class="keyword">class </span>PtrTraits></div>
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<div class="line"><a name="l00058"></a><span class="lineno"> 58</span> __host__</div>
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<div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#acc4f6ae853a8cd28d08b9ad91f896f85"> 59</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#ae5c1a2f1eee3e72ee77d5b5bac5769e3">HostTensor<T, Dim, Contig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  DataPtrType data,</div>
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<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">const</span> IndexT sizes[Dim]) :</div>
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<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, Contig, IndexT, PtrTraits>(data, sizes),</div>
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<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  state_(AllocState::NotOwner) {</div>
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<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> }</div>
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<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div>
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<div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> Contig,</div>
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<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> <<span class="keyword">typename</span> U> <span class="keyword">class </span>PtrTraits></div>
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<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> __host__</div>
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<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#ae5c1a2f1eee3e72ee77d5b5bac5769e3">HostTensor<T, Dim, Contig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  DataPtrType data,</div>
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<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  std::initializer_list<IndexT> sizes) :</div>
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<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, Contig, IndexT, PtrTraits>(data, sizes),</div>
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<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  state_(AllocState::NotOwner) {</div>
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<div class="line"><a name="l00074"></a><span class="lineno"> 74</span> }</div>
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<div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div>
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<div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> Contig,</div>
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<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> <<span class="keyword">typename</span> U> <span class="keyword">class </span>PtrTraits></div>
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<div class="line"><a name="l00078"></a><span class="lineno"> 78</span> __host__</div>
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<div class="line"><a name="l00079"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#afe5178310ff522481331356c0625d2da"> 79</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#ae5c1a2f1eee3e72ee77d5b5bac5769e3">HostTensor<T, Dim, Contig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  DataPtrType data,</div>
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<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">const</span> IndexT sizes[Dim],</div>
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<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keyword">const</span> IndexT strides[Dim]) :</div>
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<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, Contig, IndexT, PtrTraits>(data, sizes, strides),</div>
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<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  state_(AllocState::NotOwner) {</div>
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<div class="line"><a name="l00085"></a><span class="lineno"> 85</span> }</div>
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<div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div>
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<div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> Contig,</div>
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<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> <<span class="keyword">typename</span> U> <span class="keyword">class </span>PtrTraits></div>
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<div class="line"><a name="l00089"></a><span class="lineno"> 89</span> __host__</div>
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<div class="line"><a name="l00090"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#ae1e3a74af4ae1f3c9db3ab79da805dd3"> 90</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#ae5c1a2f1eee3e72ee77d5b5bac5769e3">HostTensor<T, Dim, Contig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<T, Dim, Contig, IndexT, PtrTraits></a>& t,</div>
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<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  cudaStream_t stream) :</div>
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<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, Contig, IndexT, PtrTraits>(nullptr, t.sizes(), t.strides()),</div>
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<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  state_(AllocState::Owner) {</div>
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<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="comment">// Only contiguous arrays handled for now</span></div>
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<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  FAISS_ASSERT(t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#acd445331bcc0373cf925f7a02660107c">isContiguous</a>());</div>
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<div class="line"><a name="l00097"></a><span class="lineno"> 97</span> </div>
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<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a08024dbcaed3c1235cac62b476f14509">data_</a> = <span class="keyword">new</span> T[t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a41f7f08246bf8584929693bb1896205f">numElements</a>()];</div>
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<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#ae981a94263044f38be89d690dd958426">copyFrom</a>(t, stream);</div>
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<div class="line"><a name="l00100"></a><span class="lineno"> 100</span> }</div>
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<div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="comment"></span></div>
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<div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="comment">/// Call to zero out memory</span></div>
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<div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="comment"></span><span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> Contig,</div>
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<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> <<span class="keyword">typename</span> U> <span class="keyword">class </span>PtrTraits></div>
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<div class="line"><a name="l00105"></a><span class="lineno"> 105</span> __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<T, Dim, Contig, IndexT, PtrTraits></a>&</div>
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<div class="line"><a name="l00106"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#a2d5c663fc9f28312a794615e38501cc0"> 106</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a2d5c663fc9f28312a794615e38501cc0">HostTensor<T, Dim, Contig, IndexT, PtrTraits>::zero</a>() {</div>
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<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="comment">// Region must be contiguous</span></div>
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<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  FAISS_ASSERT(this->isContiguous());</div>
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<div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div>
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<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordflow">if</span> (this->data_ != <span class="keyword">nullptr</span>) {</div>
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<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  memset(this->data_, 0, this->getSizeInBytes());</div>
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<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  }</div>
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<div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div>
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<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
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<div class="line"><a name="l00115"></a><span class="lineno"> 115</span> }</div>
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<div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div>
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<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> Contig,</div>
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<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keyword">typename</span> IndexT, <span class="keyword">template</span> <<span class="keyword">typename</span> U> <span class="keyword">class </span>PtrTraits></div>
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<div class="line"><a name="l00119"></a><span class="lineno"> 119</span> __host__ T</div>
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<div class="line"><a name="l00120"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#a61823ac9c1cfcf296357c383b50d9010"> 120</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a61823ac9c1cfcf296357c383b50d9010">HostTensor<T, Dim, Contig, IndexT, PtrTraits>::maxDiff</a>(</div>
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<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keyword">const</span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<T, Dim, Contig, IndexT, PtrTraits></a>& t)<span class="keyword"> const </span>{</div>
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<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keyword">auto</span> size = this->numElements();</div>
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<div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div>
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<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  FAISS_ASSERT(size == t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a41f7f08246bf8584929693bb1896205f">numElements</a>());</div>
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<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  FAISS_ASSERT(size > 0);</div>
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<div class="line"><a name="l00126"></a><span class="lineno"> 126</span> </div>
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<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">if</span> (Contig) {</div>
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<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keyword">auto</span> a = this->data();</div>
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<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">auto</span> b = t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a37d3ac0dffcaad29f09d6e85fb07b335">data</a>();</div>
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<div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div>
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<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  T maxDiff = a[0] - b[0];</div>
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<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="comment">// FIXME: type-specific abs()</span></div>
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|
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  maxDiff = maxDiff < 0 ? maxDiff * (T) -1 : maxDiff;</div>
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<div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div>
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<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordflow">for</span> (IndexT i = 1; i < size; ++i) {</div>
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<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keyword">auto</span> diff = a[i] - b[i];</div>
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<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="comment">// FIXME: type-specific abs</span></div>
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|
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  diff = diff < 0 ? diff * (T) -1 : diff;</div>
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<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keywordflow">if</span> (diff > maxDiff) {</div>
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<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  maxDiff = diff;</div>
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<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  }</div>
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<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  }</div>
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<div class="line"><a name="l00143"></a><span class="lineno"> 143</span> </div>
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<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordflow">return</span> maxDiff;</div>
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<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  } <span class="keywordflow">else</span> {</div>
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<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="comment">// non-contiguous</span></div>
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<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="comment">// FIXME</span></div>
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<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  FAISS_ASSERT(<span class="keyword">false</span>);</div>
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<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">return</span> (T) 0;</div>
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<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  }</div>
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<div class="line"><a name="l00151"></a><span class="lineno"> 151</span> }</div>
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<div class="line"><a name="l00152"></a><span class="lineno"> 152</span> </div>
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<div class="line"><a name="l00153"></a><span class="lineno"> 153</span> } } <span class="comment">// namespace</span></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a37d3ac0dffcaad29f09d6e85fb07b335"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a37d3ac0dffcaad29f09d6e85fb07b335">faiss::gpu::Tensor::data</a></div><div class="ttdeci">__host__ __device__ DataPtrType data()</div><div class="ttdoc">Returns a raw pointer to the start of our data. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00162">Tensor.cuh:162</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a08024dbcaed3c1235cac62b476f14509"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a08024dbcaed3c1235cac62b476f14509">faiss::gpu::Tensor::data_</a></div><div class="ttdeci">DataPtrType data_</div><div class="ttdoc">Raw pointer to where the tensor data begins. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00331">Tensor.cuh:331</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1HostTensor_html_a2d5c663fc9f28312a794615e38501cc0"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html#a2d5c663fc9f28312a794615e38501cc0">faiss::gpu::HostTensor::zero</a></div><div class="ttdeci">__host__ HostTensor< T, Dim, Contig, IndexT, PtrTraits > & zero()</div><div class="ttdoc">Call to zero out memory. </div><div class="ttdef"><b>Definition:</b> <a href="HostTensor-inl_8cuh_source.html#l00106">HostTensor-inl.cuh:106</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1HostTensor_html_ae5c1a2f1eee3e72ee77d5b5bac5769e3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html#ae5c1a2f1eee3e72ee77d5b5bac5769e3">faiss::gpu::HostTensor::HostTensor</a></div><div class="ttdeci">__host__ HostTensor()</div><div class="ttdoc">Default constructor. </div><div class="ttdef"><b>Definition:</b> <a href="HostTensor-inl_8cuh_source.html#l00017">HostTensor-inl.cuh:17</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a41f7f08246bf8584929693bb1896205f"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a41f7f08246bf8584929693bb1896205f">faiss::gpu::Tensor::numElements</a></div><div class="ttdeci">__host__ __device__ IndexT numElements() const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00285">Tensor-inl.cuh:285</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html">faiss::gpu::Tensor</a></div><div class="ttdoc">Our tensor type. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00031">Tensor.cuh:31</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_ae981a94263044f38be89d690dd958426"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#ae981a94263044f38be89d690dd958426">faiss::gpu::Tensor::copyFrom</a></div><div class="ttdeci">__host__ void copyFrom(Tensor< T, Dim, Contig, IndexT, PtrTraits > &t, cudaStream_t stream)</div><div class="ttdoc">Copies a tensor into ourselves; sizes must match. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00101">Tensor-inl.cuh:101</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1HostTensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html">faiss::gpu::HostTensor</a></div><div class="ttdef"><b>Definition:</b> <a href="HostTensor_8cuh_source.html#l00023">HostTensor.cuh:23</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1HostTensor_html_a5dab0d97255fed9b1da4fc7c33a89621"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html#a5dab0d97255fed9b1da4fc7c33a89621">faiss::gpu::HostTensor::~HostTensor</a></div><div class="ttdeci">__host__ ~HostTensor()</div><div class="ttdoc">Destructor. </div><div class="ttdef"><b>Definition:</b> <a href="HostTensor-inl_8cuh_source.html#l00025">HostTensor-inl.cuh:25</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_acd445331bcc0373cf925f7a02660107c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#acd445331bcc0373cf925f7a02660107c">faiss::gpu::Tensor::isContiguous</a></div><div class="ttdeci">__host__ __device__ bool isContiguous() const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00298">Tensor-inl.cuh:298</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1HostTensor_html_a61823ac9c1cfcf296357c383b50d9010"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html#a61823ac9c1cfcf296357c383b50d9010">faiss::gpu::HostTensor::maxDiff</a></div><div class="ttdeci">__host__ T maxDiff(const HostTensor< T, Dim, Contig, IndexT, PtrTraits > &t) const </div><div class="ttdoc">Returns the maximum difference seen between two tensors. </div><div class="ttdef"><b>Definition:</b> <a href="HostTensor-inl_8cuh_source.html#l00120">HostTensor-inl.cuh:120</a></div></div>
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