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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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195 lines
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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.cuh</div> </div>
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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"> * 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="preprocessor">#pragma once</span></div>
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<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor"></span></div>
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<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include "Tensor.cuh"</span></div>
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<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div>
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<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
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<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div>
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<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T,</div>
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<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="keywordtype">int</span> Dim,</div>
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<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="keywordtype">bool</span> InnerContig = <span class="keyword">false</span>,</div>
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<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keyword">typename</span> IndexT = int,</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> U> <span class="keyword">class </span>PtrTraits = traits::DefaultPtrTraits></div>
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<div class="line"><a name="l00022"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html"> 22</a></span> <span class="keyword">class </span><a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor</a> : <span class="keyword">public</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="l00023"></a><span class="lineno"> 23</span>  <span class="keyword">public</span>:</div>
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<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keyword">typedef</span> IndexT IndexType;</div>
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<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keyword">typedef</span> <span class="keyword">typename</span> PtrTraits<T>::PtrType DataPtrType;</div>
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<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="comment"></span></div>
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<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="comment"> /// Default constructor</span></div>
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<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment"></span> __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor</a>();</div>
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<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment"></span></div>
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<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="comment"> /// Destructor</span></div>
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<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"></span> __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#ab24605e0ecd9ef9892ac33ce7d763cef">~HostTensor</a>();</div>
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<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"></span></div>
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<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> /// Constructs a tensor of the given size, allocating memory for it</span></div>
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<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"> /// locally</span></div>
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<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment"></span> __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor</a>(<span class="keyword">const</span> IndexT <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#abc0ecc4f882ee09632b5a06be0619adb">sizes</a>[Dim]);</div>
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<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor</a>(std::initializer_list<IndexT> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#abc0ecc4f882ee09632b5a06be0619adb">sizes</a>);</div>
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<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"></span></div>
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<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="comment"> /// Constructs a tensor of the given size and stride, referencing a</span></div>
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<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="comment"> /// memory region we do not own</span></div>
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<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment"></span> __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor</a>(DataPtrType <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>,</div>
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<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keyword">const</span> IndexT sizes[Dim]);</div>
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<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor</a>(DataPtrType data,</div>
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<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  std::initializer_list<IndexT> sizes);</div>
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<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment"></span></div>
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<div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment"> /// Constructs a tensor of the given size and stride, referencing a</span></div>
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<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="comment"> /// memory region we do not own</span></div>
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<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"></span> __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor</a>(DataPtrType data,</div>
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<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keyword">const</span> IndexT sizes[Dim],</div>
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<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keyword">const</span> IndexT <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a87a777247486756e99060547a3cc833a">strides</a>[Dim]);</div>
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<div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="comment"></span></div>
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<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"> /// Copies a tensor into ourselves, allocating memory for it</span></div>
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<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment"> /// locally. If the tensor is on the GPU, then we will copy it to</span></div>
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<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"> /// ourselves wrt the given stream.</span></div>
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<div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="comment"></span> __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a8e7c2b93a26a168a7adcb1c49492e165">HostTensor</a>(<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="l00055"></a><span class="lineno"> 55</span>  cudaStream_t stream);</div>
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<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"></span></div>
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<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> /// Call to zero out memory</span></div>
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<div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"></span> __host__ <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<T, Dim, InnerContig, IndexT, PtrTraits></a>& <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#afb34d344157ea0905d2d76d4081da052">zero</a>();</div>
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<div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="comment"></span></div>
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<div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="comment"> /// Returns the maximum difference seen between two tensors</span></div>
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<div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="comment"></span> __host__ T</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_1HostTensor.html#a4f8c1a0467513d62277b693dd65238c5">maxDiff</a>(<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="l00063"></a><span class="lineno"> 63</span> <span class="comment"></span></div>
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<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment"> /// Are the two tensors exactly equal?</span></div>
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<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="comment"></span> __host__ <span class="keywordtype">bool</span></div>
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<div class="line"><a name="l00066"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1HostTensor.html#a9fe67a44876b83965a6195d11a38a22b"> 66</a></span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a9fe67a44876b83965a6195d11a38a22b">equal</a>(<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="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">return</span> (<a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html#a4f8c1a0467513d62277b693dd65238c5">maxDiff</a>(t) == (T) 0);</div>
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<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  }</div>
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<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div>
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<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keyword">private</span>:</div>
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<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">enum</span> AllocState {<span class="comment"></span></div>
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<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="comment"> /// This tensor itself owns the memory, which must be freed via</span></div>
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<div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="comment"> /// cudaFree</span></div>
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<div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="comment"></span> Owner,</div>
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<div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="comment"></span></div>
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<div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="comment"> /// This tensor itself is not an owner of the memory; there is</span></div>
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<div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="comment"> /// nothing to free</span></div>
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<div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="comment"></span> NotOwner,</div>
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<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  };</div>
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<div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div>
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<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  AllocState state_;</div>
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<div class="line"><a name="l00082"></a><span class="lineno"> 82</span> };</div>
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<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div>
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<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> } } <span class="comment">// namespace</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="preprocessor">#include "HostTensor-inl.cuh"</span></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_abc0ecc4f882ee09632b5a06be0619adb"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#abc0ecc4f882ee09632b5a06be0619adb">faiss::gpu::Tensor::sizes</a></div><div class="ttdeci">__host__ __device__ const IndexT * sizes() const </div><div class="ttdoc">Returns the size array. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00247">Tensor.cuh:247</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_a87a777247486756e99060547a3cc833a"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a87a777247486756e99060547a3cc833a">faiss::gpu::Tensor::strides</a></div><div class="ttdeci">__host__ __device__ const IndexT * strides() const </div><div class="ttdoc">Returns the stride array. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00252">Tensor.cuh:252</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_a9fe67a44876b83965a6195d11a38a22b"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html#a9fe67a44876b83965a6195d11a38a22b">faiss::gpu::HostTensor::equal</a></div><div class="ttdeci">__host__ bool equal(const HostTensor< T, Dim, InnerContig, IndexT, PtrTraits > &t) const </div><div class="ttdoc">Are the two tensors exactly equal? </div><div class="ttdef"><b>Definition:</b> <a href="HostTensor_8cuh_source.html#l00066">HostTensor.cuh:66</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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