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0df3f646fc
various bugfixes from github issues kmean with some frozen centroids GPU better tiling for large flat datasets default AVX for vector ops
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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 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"> * Copyright (c) 2015-present, Facebook, Inc.</span></div>
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<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * All rights reserved.</span></div>
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<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> *</span></div>
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<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> * This source code is licensed under the BSD+Patents license found in the</span></div>
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<div class="line"><a name="l00006"></a><span class="lineno"> 6</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="l00007"></a><span class="lineno"> 7</span> <span class="comment"> */</span></div>
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<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div>
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<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment">// Copyright 2004-present Facebook. All Rights Reserved.</span></div>
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<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div>
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<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
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<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div>
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<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
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<div class="line"><a name="l00014"></a><span class="lineno"> 14</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="l00015"></a><span class="lineno"> 15</span> __host__</div>
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<div class="line"><a name="l00016"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165"> 16</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits>::HostTensor</a>() :</div>
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<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, InnerContig, IndexT, PtrTraits>(),</div>
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<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  state_(AllocState::NotOwner) {</div>
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<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> }</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> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
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<div class="line"><a name="l00022"></a><span class="lineno"> 22</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="l00023"></a><span class="lineno"> 23</span> __host__</div>
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<div class="line"><a name="l00024"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#ab24605e0ecd9ef9892ac33ce7d763cef"> 24</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#ab24605e0ecd9ef9892ac33ce7d763cef">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits>::~HostTensor</a>() {</div>
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<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keywordflow">if</span> (state_ == AllocState::Owner) {</div>
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<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  FAISS_ASSERT(this->data_ != <span class="keyword">nullptr</span>);</div>
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<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keyword">delete</span>[] this->data_;</div>
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<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  this->data_ = <span class="keyword">nullptr</span>;</div>
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<div class="line"><a name="l00029"></a><span class="lineno"> 29</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> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
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<div class="line"><a name="l00033"></a><span class="lineno"> 33</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="l00034"></a><span class="lineno"> 34</span> __host__</div>
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<div class="line"><a name="l00035"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#a6aa9dc08df68655ff666a8b24aa0c2f4"> 35</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">const</span> IndexT sizes[Dim]) :</div>
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<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, InnerContig, IndexT, PtrTraits>(nullptr, sizes),</div>
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<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  state_(AllocState::Owner) {</div>
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<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div>
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<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a2ec506a25e46cf7001060a6ba5ae3b94">data_</a> = <span class="keyword">new</span> T[this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">numElements</a>()];</div>
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<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  FAISS_ASSERT(this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a2ec506a25e46cf7001060a6ba5ae3b94">data_</a> != <span class="keyword">nullptr</span>);</div>
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<div class="line"><a name="l00042"></a><span class="lineno"> 42</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> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
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<div class="line"><a name="l00045"></a><span class="lineno"> 45</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="l00046"></a><span class="lineno"> 46</span> __host__</div>
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<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  std::initializer_list<IndexT> sizes) :</div>
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<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, InnerContig, IndexT, PtrTraits>(nullptr, sizes),</div>
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<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  state_(AllocState::Owner) {</div>
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<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a2ec506a25e46cf7001060a6ba5ae3b94">data_</a> = <span class="keyword">new</span> T[this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">numElements</a>()];</div>
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<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  FAISS_ASSERT(this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a2ec506a25e46cf7001060a6ba5ae3b94">data_</a> != <span class="keyword">nullptr</span>);</div>
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<div class="line"><a name="l00053"></a><span class="lineno"> 53</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> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
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<div class="line"><a name="l00056"></a><span class="lineno"> 56</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="l00057"></a><span class="lineno"> 57</span> __host__</div>
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<div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#a2b703685aea24d432f4d7ccf535e3ca6"> 58</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  DataPtrType data,</div>
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<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keyword">const</span> IndexT sizes[Dim]) :</div>
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<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, InnerContig, IndexT, PtrTraits>(data, sizes),</div>
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<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  state_(AllocState::NotOwner) {</div>
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<div class="line"><a name="l00063"></a><span class="lineno"> 63</span> }</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> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
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<div class="line"><a name="l00066"></a><span class="lineno"> 66</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="l00067"></a><span class="lineno"> 67</span> __host__</div>
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<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  DataPtrType data,</div>
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<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  std::initializer_list<IndexT> sizes) :</div>
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<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, InnerContig, IndexT, PtrTraits>(data, sizes),</div>
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<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  state_(AllocState::NotOwner) {</div>
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<div class="line"><a name="l00073"></a><span class="lineno"> 73</span> }</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> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
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<div class="line"><a name="l00076"></a><span class="lineno"> 76</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="l00077"></a><span class="lineno"> 77</span> __host__</div>
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<div class="line"><a name="l00078"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#a05a4f8a8b45c865f1bcf40ff7e3c95a1"> 78</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  DataPtrType data,</div>
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<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">const</span> IndexT sizes[Dim],</div>
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<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">const</span> IndexT strides[Dim]) :</div>
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<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, InnerContig, IndexT, PtrTraits>(data, sizes, strides),</div>
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<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  state_(AllocState::NotOwner) {</div>
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<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> }</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> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
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<div class="line"><a name="l00087"></a><span class="lineno"> 87</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="l00088"></a><span class="lineno"> 88</span> __host__</div>
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<div class="line"><a name="l00089"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#a5a55bceb878e941192f8fc7bf400208a"> 89</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits>::HostTensor</a>(</div>
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<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<T, Dim, InnerContig, IndexT, PtrTraits></a>& t,</div>
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<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  cudaStream_t stream) :</div>
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<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor</a><T, Dim, InnerContig, IndexT, PtrTraits>(nullptr, t.sizes(), t.strides()),</div>
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<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  state_(AllocState::Owner) {</div>
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<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="comment">// Only contiguous arrays handled for now</span></div>
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<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  FAISS_ASSERT(t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a09019c54911db891c9321fd3b34509c2">isContiguous</a>());</div>
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<div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div>
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<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  this-><a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a2ec506a25e46cf7001060a6ba5ae3b94">data_</a> = <span class="keyword">new</span> T[t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">numElements</a>()];</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#a6dc00c182a92389b74c89ba7fcab40d3">copyFrom</a>(t, stream);</div>
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<div class="line"><a name="l00099"></a><span class="lineno"> 99</span> }</div>
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<div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="comment"></span></div>
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<div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="comment">/// Call to zero out memory</span></div>
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<div class="line"><a name="l00102"></a><span class="lineno"> 102</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> InnerContig,</div>
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<div class="line"><a name="l00103"></a><span class="lineno"> 103</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="l00104"></a><span class="lineno"> 104</span> __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits></a>&</div>
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<div class="line"><a name="l00105"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#afb34d344157ea0905d2d76d4081da052"> 105</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#afb34d344157ea0905d2d76d4081da052">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits>::zero</a>() {</div>
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<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="comment">// Region must be contiguous</span></div>
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<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  FAISS_ASSERT(this->isContiguous());</div>
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<div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div>
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<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordflow">if</span> (this->data_ != <span class="keyword">nullptr</span>) {</div>
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<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  memset(this->data_, 0, this->getSizeInBytes());</div>
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<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  }</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>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
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<div class="line"><a name="l00114"></a><span class="lineno"> 114</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> <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">int</span> Dim, <span class="keywordtype">bool</span> InnerContig,</div>
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<div class="line"><a name="l00117"></a><span class="lineno"> 117</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="l00118"></a><span class="lineno"> 118</span> __host__ T</div>
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<div class="line"><a name="l00119"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#a4f8c1a0467513d62277b693dd65238c5"> 119</a></span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a4f8c1a0467513d62277b693dd65238c5">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits>::maxDiff</a>(</div>
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<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keyword">const</span> <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits></a>& t)<span class="keyword"> const </span>{</div>
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<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keyword">auto</span> size = this->numElements();</div>
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<div class="line"><a name="l00122"></a><span class="lineno"> 122</span> </div>
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<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  FAISS_ASSERT(size == t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">numElements</a>());</div>
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<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  FAISS_ASSERT(size > 0);</div>
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<div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div>
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<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keywordflow">if</span> (InnerContig) {</div>
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<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keyword">auto</span> a = this->data();</div>
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<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keyword">auto</span> b = t.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>();</div>
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<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div>
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<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  T maxDiff = a[0] - b[0];</div>
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<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="comment">// FIXME: type-specific abs()</span></div>
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<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  maxDiff = maxDiff < 0 ? maxDiff * (T) -1 : maxDiff;</div>
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<div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div>
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<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keywordflow">for</span> (IndexT i = 1; i < size; ++i) {</div>
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<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keyword">auto</span> diff = a[i] - b[i];</div>
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<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="comment">// FIXME: type-specific abs</span></div>
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|
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  diff = diff < 0 ? diff * (T) -1 : diff;</div>
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<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keywordflow">if</span> (diff > maxDiff) {</div>
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<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  maxDiff = diff;</div>
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<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  }</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>  <span class="keywordflow">return</span> maxDiff;</div>
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<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  } <span class="keywordflow">else</span> {</div>
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<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="comment">// non-contiguous</span></div>
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<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="comment">// FIXME</span></div>
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<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  FAISS_ASSERT(<span class="keyword">false</span>);</div>
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<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="keywordflow">return</span> (T) 0;</div>
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<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  }</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> } } <span class="comment">// namespace</span></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a0ba9ab7c1676b7a41a6e6b2e5a490d2f"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a0ba9ab7c1676b7a41a6e6b2e5a490d2f">faiss::gpu::Tensor::numElements</a></div><div class="ttdeci">__host__ __device__ size_t numElements() const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00352">Tensor-inl.cuh:352</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1HostTensor_html_ab24605e0ecd9ef9892ac33ce7d763cef"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html#ab24605e0ecd9ef9892ac33ce7d763cef">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#l00024">HostTensor-inl.cuh:24</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1HostTensor_html_afb34d344157ea0905d2d76d4081da052"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html#afb34d344157ea0905d2d76d4081da052">faiss::gpu::HostTensor::zero</a></div><div class="ttdeci">__host__ HostTensor< T, Dim, InnerContig, 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#l00105">HostTensor-inl.cuh:105</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a2ec506a25e46cf7001060a6ba5ae3b94"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a2ec506a25e46cf7001060a6ba5ae3b94">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#l00346">Tensor.cuh:346</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a09019c54911db891c9321fd3b34509c2"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a09019c54911db891c9321fd3b34509c2">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#l00365">Tensor-inl.cuh:365</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a6dc00c182a92389b74c89ba7fcab40d3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a6dc00c182a92389b74c89ba7fcab40d3">faiss::gpu::Tensor::copyFrom</a></div><div class="ttdeci">__host__ void copyFrom(Tensor< T, Dim, InnerContig, 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_a8e7c2b93a26a168a7adcb1c49492e165"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">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#l00016">HostTensor-inl.cuh:16</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a50411ce4d0fa32ef715e3321b6e33212"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">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#l00178">Tensor.cuh:178</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#l00030">Tensor.cuh:30</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#l00022">HostTensor.cuh:22</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1HostTensor_html_a4f8c1a0467513d62277b693dd65238c5"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html#a4f8c1a0467513d62277b693dd65238c5">faiss::gpu::HostTensor::maxDiff</a></div><div class="ttdeci">__host__ T maxDiff(const HostTensor< T, Dim, InnerContig, 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#l00119">HostTensor-inl.cuh:119</a></div></div>
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