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<li class="navelem"><a class="el" href="dir_20697b8f204bdfcab31e6b1a416f3ab8.html">caffe2</a></li><li class="navelem"><a class="el" href="dir_05c92498e25fa977790f551ff793f1b1.html">mkl</a></li><li class="navelem"><a class="el" href="dir_9a8f178644e12033403db01c04c605e4.html">utils</a></li> </ul>
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<div class="title">mkl_memory.h</div> </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="preprocessor">#ifndef CAFFE2_UTILS_MKL_MKL_MEMORY_H_</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#define CAFFE2_UTILS_MKL_MKL_MEMORY_H_</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> </div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include <mutex></span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="flags_8h.html">caffe2/core/flags.h</a>"</span> <span class="comment">// for TIndex</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "caffe2/core/tensor.h"</span> <span class="comment">// for TIndex</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include "caffe2/mkl/utils/mkl_dnn_cppwrapper.h"</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment">// A global boolean variable that controls the behavior when we call View() on</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment">// an MKLMemory: if it is set true, then the View() function will actually</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment">// change the underlying storage. If it is set false, an implicit copy is</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment">// triggered but the original storage is not affected.</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> CAFFE2_DECLARE_bool(caffe2_mkl_implicit_layout_change);</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="keyword">namespace </span><a class="code" href="namespacecaffe2.html">caffe2</a> {</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="keyword">namespace </span>mkl {</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00022"></a><span class="lineno"><a class="line" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html"> 22</a></span> <span class="keyword">class </span><a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper</a> {</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keyword">public</span>:</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper</a>() {}</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="comment">// Creates a primitive wrapper from an existing primitive. The wrapper</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="comment">// takes over ownership.</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keyword">explicit</span> <a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper</a>(dnnPrimitive_t primitive) : primitive_(primitive) {}</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Creator, <span class="keyword">typename</span> FirstArg, <span class="keyword">typename</span>... Args></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper</a>(Creator creator, FirstArg&& arg, Args&&... args) {</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  creator(&primitive_, arg, args...);</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  }</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  ~<a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper</a>() {</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keywordflow">if</span> (primitive_) {</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  MKLDNN_CHECK(dnnDelete<T>(primitive_));</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  }</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  }</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Creator, <span class="keyword">typename</span>... Args></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">void</span> Reset(Creator creator, Args&&... args) {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordflow">if</span> (primitive_) {</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  MKLDNN_SAFE_CALL(dnnDelete<T>(primitive_));</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  }</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  creator(&primitive_, args...);</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  }</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> </div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordtype">void</span> Reset() {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keywordflow">if</span> (primitive_) {</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  MKLDNN_SAFE_CALL(dnnDelete<T>(primitive_));</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  primitive_ = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  }</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  }</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> </div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keyword">operator</span> dnnPrimitive_t()<span class="keyword"> const </span>{</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keywordflow">return</span> primitive_;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  }</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">private</span>:</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  dnnPrimitive_t primitive_ = 0;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  DISABLE_COPY_AND_ASSIGN(<a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper</a>);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> };</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00065"></a><span class="lineno"><a class="line" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html"> 65</a></span> <span class="keyword">class </span><a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper</a> {</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keyword">public</span>:</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper</a>() {}</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="comment">// Create a user layout from a TensorCPU with the given shapes.</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">explicit</span> <a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper</a>(<span class="keyword">const</span> <a class="code" href="classcaffe2_1_1_tensor.html">TensorCPU</a>& tensor) {</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  Reset(tensor);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  }</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// Create an internal layout from the primitive and type.</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper</a>(<span class="keyword">const</span> dnnPrimitive_t primitive, <span class="keyword">const</span> dnnResourceType_t type) {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  Reset(primitive, type);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  }</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="comment">// Create a user layout from the given dimension, size and strides.</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper</a>(</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> dimension,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> size[],</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> strides[]) {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  Reset(dimension, size, strides);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  }</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="comment">// Destructs the layout wrapper.</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  ~<a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper</a>() {</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordflow">if</span> (layout_)</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  MKLDNN_CHECK(dnnLayoutDelete<T>(layout_));</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  }</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="comment">// Create a user layout from a TensorCPU with the given shapes.</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordtype">void</span> Reset(<span class="keyword">const</span> <a class="code" href="classcaffe2_1_1_tensor.html">TensorCPU</a>& tensor) {</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keywordflow">if</span> (layout_)</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  MKLDNN_CHECK(dnnLayoutDelete<T>(layout_));</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  CAFFE_ENFORCE(tensor.<a class="code" href="classcaffe2_1_1_tensor.html#a87087b9548e9bad215d663389abda32e">size</a>(), <span class="stringliteral">"Cannot reset with an empty tensor."</span>);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordtype">size_t</span> dimension = tensor.<a class="code" href="classcaffe2_1_1_tensor.html#aea51c872873f4db0abad47713315e81f">ndim</a>();</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordtype">size_t</span> size[dimension];</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordtype">size_t</span> strides[dimension];</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < dimension; ++i) {</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  size[i] = tensor.<a class="code" href="classcaffe2_1_1_tensor.html#abec0a0587f4afb6baf486bb0659ec47d">dim</a>(dimension - i - 1);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  strides[i] = (i == 0) ? 1 : strides[i - 1] * size[i - 1];</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  }</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  MKLDNN_SAFE_CALL(dnnLayoutCreate<T>(&layout_, dimension, size, strides));</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  }</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="comment">// Create an internal layout from the primitive and type.</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordtype">void</span> Reset(<span class="keyword">const</span> dnnPrimitive_t primitive, <span class="keyword">const</span> dnnResourceType_t type) {</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  CAFFE_ENFORCE(primitive, <span class="stringliteral">"Cannot reset with an unknwon primitive."</span>);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  type != dnnResourceNumber,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="stringliteral">"Cannot reset with an unknown resource number."</span>);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keywordflow">if</span> (layout_) {</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  MKLDNN_CHECK(dnnLayoutDelete<T>(layout_));</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  }</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  MKLDNN_SAFE_CALL(</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  dnnLayoutCreateFromPrimitive<T>(&layout_, primitive, type));</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  }</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="comment">// Create a user layout from the given dimension, size and strides.</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordtype">void</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  Reset(<span class="keyword">const</span> <span class="keywordtype">size_t</span> dimension, <span class="keyword">const</span> <span class="keywordtype">size_t</span> size[], <span class="keyword">const</span> <span class="keywordtype">size_t</span> strides[]) {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">if</span> (layout_)</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  MKLDNN_CHECK(dnnLayoutDelete<T>(layout_));</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  MKLDNN_SAFE_CALL(dnnLayoutCreate<T>(&layout_, dimension, size, strides));</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  }</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keywordtype">void</span> Reset() {</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">if</span> (layout_) {</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  MKLDNN_CHECK(dnnLayoutDelete<T>(layout_));</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  layout_ = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  }</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  }</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keyword">operator</span> dnnLayout_t()<span class="keyword"> const </span>{</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keywordflow">return</span> layout_;</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  }</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keyword">private</span>:</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  dnnLayout_t layout_ = 0;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  DISABLE_COPY_AND_ASSIGN(<a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper</a>);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> };</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> </div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00151"></a><span class="lineno"><a class="line" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html"> 151</a></span> <span class="keyword">class </span><a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">MKLMemory</a> {</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keyword">public</span>:</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="comment">// Initializes an empty MKLMemory.</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">MKLMemory</a>() {}</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="comment">// Initialize an MKLMemory with the given size, strides, dnn</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="comment">// primitive and type.</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">MKLMemory</a>(</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> dimension,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> size[],</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> strides[],</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="keyword">const</span> dnnPrimitive_t primitive = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">const</span> dnnResourceType_t type = dnnResourceNumber,</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keywordtype">bool</span> share_mem_if_possible = <span class="keyword">false</span>) {</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  Reset(dimension, size, strides, primitive, type, share_mem_if_possible);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  }</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="comment">// Initialize an MKLMemory, with the given dimension assuming a C-contiguous</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="comment">// storage.</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> IndexType></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keyword">explicit</span> <a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">MKLMemory</a>(</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keyword">const</span> vector<IndexType>& dims,</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keyword">const</span> dnnPrimitive_t primitive = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keyword">const</span> dnnResourceType_t type = dnnResourceNumber,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordtype">bool</span> share_mem_if_possible = <span class="keyword">false</span>) {</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  Reset(dims, primitive, type, share_mem_if_possible);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  }</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> </div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="comment">// Initialize an MKLMemory with the given size, strides, dnn</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="comment">// primitive and type.</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordtype">void</span> Reset(</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> dimension,</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> size[],</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> strides[],</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keyword">const</span> dnnPrimitive_t primitive = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keyword">const</span> dnnResourceType_t type = dnnResourceNumber,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="keywordtype">bool</span> share_mem_if_possible = <span class="keyword">false</span>) {</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  buffer_.reset();</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  dims_.resize(dimension);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  size_ = 1;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < dimension; ++i) {</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  dims_[i] = size[dimension - 1 - i];</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  size_ *= dims_[i];</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  }</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  user_layout_.Reset(dimension, size, strides);</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keywordflow">if</span> (primitive) {</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  layout_.Reset(primitive, type);</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  layout_.Reset(dimension, size, strides);</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  }</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  convert_in_.Reset(dnnConversionCreate<T>, user_layout_, layout_);</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  convert_out_.Reset(dnnConversionCreate<T>, layout_, user_layout_);</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  share_mem_if_possible_ = share_mem_if_possible;</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  layout_is_user_layout_ = dnnLayoutCompare<T>(layout_, user_layout_);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  VLOG(2) << <span class="stringliteral">"layout is user layout? "</span> << layout_is_user_layout_;</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordflow">if</span> (!share_mem_if_possible_) {</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="comment">// If we are not going to share memory, we will simply allocate</span></div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="comment">// memory upfront.</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  buffer();</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  }</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  }</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> </div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="comment">// Initialize an MKLMemory, with the given dimension assuming a C-contiguous</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="comment">// storage.</span></div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> IndexType></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <span class="keywordtype">void</span> Reset(</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keyword">const</span> vector<IndexType>& dims,</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="keyword">const</span> dnnPrimitive_t primitive = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keyword">const</span> dnnResourceType_t type = dnnResourceNumber,</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordtype">bool</span> share_mem_if_possible = <span class="keyword">false</span>) {</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  buffer_.reset();</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  dims_.resize(dims.size());</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  size_ = 1;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < dims.size(); ++i) {</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  dims_[i] = dims[i];</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  size_ *= dims_[i];</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  }</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordtype">size_t</span> dimension = dims.size();</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  vector<size_t> size(dimension);</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  vector<size_t> strides(dimension);</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < dimension; ++i) {</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  size[i] = dims[dimension - i - 1];</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  strides[i] = (i == 0) ? 1 : strides[i - 1] * size[i - 1];</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  }</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  user_layout_.Reset(dims.size(), size.data(), strides.data());</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keywordflow">if</span> (primitive) {</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  layout_.Reset(primitive, type);</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  layout_.Reset(dimension, size.data(), strides.data());</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  }</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  convert_in_.Reset(dnnConversionCreate<T>, user_layout_, layout_);</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  convert_out_.Reset(dnnConversionCreate<T>, layout_, user_layout_);</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  share_mem_if_possible_ = share_mem_if_possible;</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  layout_is_user_layout_ = dnnLayoutCompare<T>(layout_, user_layout_);</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  VLOG(2) << <span class="stringliteral">"layout is user layout? "</span> << layout_is_user_layout_;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <span class="keywordflow">if</span> (!share_mem_if_possible_) {</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="comment">// If we are not going to share memory, we will simply allocate</span></div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="comment">// memory upfront.</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  buffer();</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  }</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  }</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> </div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordtype">void</span> Reset() {</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  buffer_.reset();</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  dims_.clear();</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  size_ = 0;</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  user_layout_.Reset();</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  layout_.Reset();</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  convert_in_.Reset();</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  convert_out_.Reset();</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  }</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> </div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> IndexType></div><div class="line"><a name="l00267"></a><span class="lineno"><a class="line" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html#aa0beaf56414f73aabac95fac6e1ac1aa"> 267</a></span>  <span class="keywordtype">void</span> <a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html#aa0beaf56414f73aabac95fac6e1ac1aa">Reshape</a>(<span class="keyword">const</span> vector<IndexType>& dims) {</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  layout_is_user_layout_,</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="stringliteral">"Reshape is not allowed for custom layouts. "</span></div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <span class="stringliteral">"Convert to plain layout before invoking Reshape()."</span>);</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> </div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  TIndex new_size = 1;</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> i = 0; i < dims.size(); ++i) {</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  CAFFE_ENFORCE_GE_WITH_CALLER(dims[i], 0);</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  new_size *= dims[i];</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  }</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  CAFFE_ENFORCE_WITH_CALLER(</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  new_size == size_,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="stringliteral">"New size and old size are not equal. Reshape is not possible."</span>);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> </div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  vector<TIndex> new_dims(dims.size());</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  vector<size_t> size(dims.size());</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  vector<size_t> strides(dims.size());</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < dims.size(); ++i) {</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  new_dims[i] = dims[i];</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  size[i] = dims[dims.size() - i - 1];</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  strides[i] = (i == 0) ? 1 : strides[i - 1] * size[i - 1];</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  }</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  dims_ = new_dims;</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  user_layout_.Reset(dims.size(), size.data(), strides.data());</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  layout_.Reset(dims.size(), size.data(), strides.data());</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  convert_in_.Reset(dnnConversionCreate<T>, user_layout_, layout_);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  convert_out_.Reset(dnnConversionCreate<T>, layout_, user_layout_);</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  }</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span> </div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="comment">// Destructs the MKLMemory.</span></div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  ~<a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">MKLMemory</a>() {}</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> </div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="keywordtype">void</span> CopyFrom(<span class="keyword">const</span> <span class="keywordtype">void</span>* ptr) {</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordflow">if</span> (share_mem_if_possible_ && layout_is_user_layout_) {</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  VLOG(2) << <span class="stringliteral">"Sharing underlying memory and skip copy."</span>;</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  buffer_.reset(const_cast<void*>(ptr), [](<span class="keywordtype">void</span>*) -> <span class="keywordtype">void</span> {});</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (size_ == 0) {</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  VLOG(2) << <span class="stringliteral">"Cannot copy into empty MKL buffer."</span>;</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  VLOG(2) << <span class="stringliteral">"Copying external content."</span>;</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  MKLDNN_SAFE_CALL(dnnConversionExecute<T>(</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  convert_in_, const_cast<void*>(ptr), buffer()));</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  }</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  }</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keywordtype">void</span> CopyFrom(<span class="keyword">const</span> <a class="code" href="classcaffe2_1_1_tensor.html">TensorCPU</a>& tensor) {</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  CAFFE_ENFORCE_EQ(</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  tensor.<a class="code" href="classcaffe2_1_1_tensor.html#abd0ea7906b6610956dcbc71bbd9120bf">dims</a>(),</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  dims_,</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="stringliteral">"Dims does not match the expected dims of the resource."</span>);</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  CopyFrom(tensor.template data<T>());</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  }</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> </div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keywordtype">void</span> CopyFrom(<span class="keyword">const</span> <a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">MKLMemory<T></a>& other) {</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  CAFFE_ENFORCE_EQ(</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  other.dims(),</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  dims_,</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="stringliteral">"Dims does not match the expected dims of the resource."</span>);</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> </div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keywordflow">if</span> (share_mem_if_possible_ && dnnLayoutCompare<T>(other.layout_, layout_)) {</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  buffer_ = other.buffer_;</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (size_ == 0) {</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  VLOG(2) << <span class="stringliteral">"Cannot copy between empty MKL buffers"</span>;</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper<T></a> convert(</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  dnnConversionCreate<T>, other.layout_, layout_);</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  MKLDNN_SAFE_CALL(</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  dnnConversionExecute<T>(convert, other.buffer(), buffer()));</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  }</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  }</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> </div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordtype">bool</span> ShareFromRaw(<span class="keyword">const</span> <span class="keywordtype">void</span>* ptr) {</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">if</span> (share_mem_if_possible_ && layout_is_user_layout_) {</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  buffer_.reset(const_cast<void*>(ptr), [](<span class="keywordtype">void</span>*) -> <span class="keywordtype">void</span> {});</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  }</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  }</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> </div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordtype">bool</span> ShareFromTensor(<span class="keyword">const</span> <a class="code" href="classcaffe2_1_1_tensor.html">TensorCPU</a>& tensor) {</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  CAFFE_ENFORCE_EQ(</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  tensor.<a class="code" href="classcaffe2_1_1_tensor.html#abd0ea7906b6610956dcbc71bbd9120bf">dims</a>(),</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  dims_,</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="stringliteral">"Dims does not match the expected dims of the resource."</span>);</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keywordflow">return</span> ShareFromRaw(tensor.template data<T>());</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  }</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> </div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keywordtype">bool</span> ShareFrom(<span class="keyword">const</span> <a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">MKLMemory<T></a>& other) {</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="keywordflow">if</span> (share_mem_if_possible_ && dnnLayoutCompare<T>(other.layout_, layout_)) {</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  VLOG(2) << <span class="stringliteral">"Sharing underlying memory."</span>;</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  buffer_ = other.buffer_;</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">if</span> (!buffer_.get()) {</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  VLOG(2) << <span class="stringliteral">"Warning: the source MKLMemory has no content yet, so the "</span></div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="stringliteral">"sharing actually has no effect."</span>;</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  }</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  VLOG(2) << <span class="stringliteral">"Not sharing underlying memory."</span>;</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  }</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  }</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> </div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keywordtype">void</span> CopyTo(<span class="keywordtype">void</span>* ptr)<span class="keyword"> const </span>{</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keywordflow">if</span> (buffer_.get() == ptr) {</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="comment">// This is already mapping to the same memory region. Skip copy.</span></div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  VLOG(2) << <span class="stringliteral">"CopyTo does not need actual copying, as we are sharing "</span></div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="stringliteral">"memory with the output."</span>;</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordflow">return</span>;</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  }</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  buffer_.get(), <span class="stringliteral">"Canot copy out from an uninitialized MKLMemory."</span>);</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  VLOG(2) << <span class="stringliteral">"Copy to external memory."</span>;</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  MKLDNN_SAFE_CALL(dnnConversionExecute<T>(convert_out_, buffer_.get(), ptr));</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  }</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> </div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="keywordtype">void</span> CopyTo(<a class="code" href="classcaffe2_1_1_tensor.html">TensorCPU</a>* tensor)<span class="keyword"> const </span>{</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keywordflow">if</span> (tensor-><a class="code" href="classcaffe2_1_1_tensor.html#a87087b9548e9bad215d663389abda32e">size</a>() > 0 && buffer_.get() == tensor-><a class="code" href="classcaffe2_1_1_tensor.html#a5fbe65f2d062db6f1f5ab319b0f811fd">mutable_data</a><T>()) {</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="comment">// This is already mapping to the same memory region. Skip copy.</span></div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  VLOG(2) << <span class="stringliteral">"CopyTo does not need actual copying, as we are sharing "</span></div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="stringliteral">"memory with the output."</span>;</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="keywordflow">return</span>;</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  }</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  tensor-><a class="code" href="classcaffe2_1_1_tensor.html#a359b5ed5cfd9beaf7f62a5561d939c3b">Resize</a>(dims_);</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  CopyTo(tensor-><a class="code" href="classcaffe2_1_1_tensor.html#a5fbe65f2d062db6f1f5ab319b0f811fd">mutable_data</a><T>());</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  }</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> </div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="comment">// Copies to another MKL memory.</span></div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="comment">//</span></div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="comment">// This function</span></div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keywordtype">void</span> CopyTo(</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">MKLMemory<T></a>* other,</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keyword">const</span> dnnPrimitive_t primitive = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keyword">const</span> dnnResourceType_t type = dnnResourceNumber) {</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keywordflow">if</span> (buffer_ && buffer_.get() == other->buffer_.get()) {</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  dnnLayoutCompare<T>(other->layout_, layout_),</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="stringliteral">"MKLMemory layout does not match, despite in-place buffers"</span>);</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  other->dims() == dims(),</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="stringliteral">"MKLMemory dimensions do not match, despite in-place buffers"</span>);</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  VLOG(2) << <span class="stringliteral">"CopyTo does not need actual copying, as we are sharing "</span></div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <span class="stringliteral">"memory with the output."</span>;</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <span class="comment">// This is already mapping to the same memory region. Skip copy.</span></div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <span class="keywordflow">return</span>;</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  }</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <span class="comment">// TODO(jiayq): if primitive creation is a big overhead and we will be</span></div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="comment">// consistently copying stuff with fixed src and dst layouts, consider</span></div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="comment">// making a cache for the primitive below.</span></div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  VLOG(2) << <span class="stringliteral">"CopyTo requires copying. Performing direct copy."</span>;</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <span class="keywordflow">if</span> (dims() != other->dims()) {</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  other->Reset(dims(), primitive, type);</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  }</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="keywordflow">if</span> (size_ == 0) {</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  VLOG(2) << <span class="stringliteral">"Cannot copy between empty MKL buffers."</span>;</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keywordflow">return</span>;</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  }</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  buffer_.get(), <span class="stringliteral">"Cannot copy out from an uninitialized MKLMemory."</span>);</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper<T></a> convert(</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  dnnConversionCreate<T>, layout_, other->layout_);</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  MKLDNN_SAFE_CALL(</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  dnnConversionExecute<T>(convert, buffer_.get(), other->buffer()));</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  }</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span> </div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="keyword">inline</span> <span class="keywordtype">void</span>* buffer() {</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="keywordflow">if</span> (buffer_ == <span class="keyword">nullptr</span>) {</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  layout_ != <span class="keyword">nullptr</span>, <span class="stringliteral">"Trying to allocate buffer but layout is empty."</span>);</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keywordflow">if</span> (size_ == 0) {</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  VLOG(2) << <span class="stringliteral">"Cannot allocate empty MKL buffer."</span>;</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="keywordflow">return</span> buffer_.get();</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  }</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="keywordtype">void</span>* allocated = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  MKLDNN_SAFE_CALL(dnnAllocateBuffer<T>(&allocated, layout_));</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  buffer_.reset(allocated, [](<span class="keywordtype">void</span>* ptr) -> <span class="keywordtype">void</span> {</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  MKLDNN_CHECK(dnnReleaseBuffer<T>(ptr));</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  });</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  }</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <span class="keywordflow">return</span> buffer_.get();</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  }</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span> </div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <span class="comment">// MKLDNN does not use const void* even for the inputs, so we will</span></div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <span class="comment">// have to use void* and rely on the underlying implementation to make</span></div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="comment">// sure that the buffer is actually not changed.</span></div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="keyword">inline</span> <span class="keywordtype">void</span>* buffer()<span class="keyword"> const </span>{</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  buffer_ != <span class="keyword">nullptr</span>, <span class="stringliteral">"Trying to refer to an unallocated buffer."</span>);</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="keywordflow">return</span> buffer_.get();</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  }</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span> </div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <span class="keyword">inline</span> <span class="keyword">const</span> vector<TIndex>& dims()<span class="keyword"> const </span>{</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <span class="keywordflow">return</span> dims_;</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  }</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span> </div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">int</span> ndim()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> dims_.size(); }</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span> </div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="keyword">inline</span> <span class="keywordtype">int</span> dim32(<span class="keyword">const</span> <span class="keywordtype">int</span> i)<span class="keyword"> const </span>{</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  CAFFE_ENFORCE_LT(dims_.at(i), std::numeric_limits<int>::max());</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="keywordflow">return</span> <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(dims_[i]);</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  }</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span> </div><div class="line"><a name="l00473"></a><span class="lineno"><a class="line" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html#ab203f62d8ad712b00e805950e5707ca7"> 473</a></span>  <span class="keyword">inline</span> TIndex <a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html#ab203f62d8ad712b00e805950e5707ca7">size</a>()<span class="keyword"> const </span>{</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="keywordflow">return</span> size_;</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  }</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span> </div><div class="line"><a name="l00482"></a><span class="lineno"><a class="line" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html#ad5702260a1fce3219b5a8a6427ed99e6"> 482</a></span>  <span class="keyword">inline</span> TIndex <a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html#ad5702260a1fce3219b5a8a6427ed99e6">dim</a>(<span class="keyword">const</span> <span class="keywordtype">int</span> i)<span class="keyword"> const </span>{</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <span class="keywordflow">return</span> dims_.at(i);</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  }</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span> </div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <span class="keyword">inline</span> <span class="keyword">const</span> <a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper<T></a>& layout()<span class="keyword"> const </span>{</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <span class="keywordflow">return</span> layout_;</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  }</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> </div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <span class="keyword">inline</span> <span class="keywordtype">bool</span> is_user_layout()<span class="keyword"> const </span>{</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="keywordflow">return</span> layout_is_user_layout_;</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  }</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span> </div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <span class="comment">// Returns a view of the content. We mark this function const, but be noted</span></div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="comment">// that the returned std::shared_ptr is not const protected - user discretion</span></div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="comment">// is recommended for correctness.</span></div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  std::shared_ptr<void> View(</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  dnnLayout_t layout_wanted,</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  dnnPrimitive_t primitive = <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  dnnResourceType_t type = dnnResourceNumber)<span class="keyword"> const </span>{</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  std::lock_guard<std::mutex> lock(buffer_lock_);</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="keywordflow">if</span> (dnnLayoutCompare<T>(layout_wanted, layout_)) {</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <span class="comment">// If they are the same, return the original content.</span></div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  VLOG(2) << <span class="stringliteral">"Creating a view without the need of copying."</span>;</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <span class="keywordflow">return</span> std::shared_ptr<void>(buffer_);</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <span class="keywordtype">void</span>* temp_buffer;</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  VLOG(2) << <span class="stringliteral">"Creating a view with copying."</span>;</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  MKLDNN_SAFE_CALL(dnnAllocateBuffer<T>(&temp_buffer, layout_wanted));</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper<T></a> convert(</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  dnnConversionCreate<T>, layout_, layout_wanted);</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  MKLDNN_SAFE_CALL(dnnConversionExecute<T>(</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  convert, buffer_.get(), temp_buffer));</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <span class="keywordflow">if</span> (primitive && FLAGS_caffe2_mkl_implicit_layout_change) {</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  VLOG(2) << <span class="stringliteral">"Implicit layout change set. "</span></div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  <span class="stringliteral">"Changing the underlying storage."</span>;</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <span class="comment">// We will need to call Reset to set up all the member variables.</span></div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="comment">// This is not thread safe, so we might want to double check if this</span></div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="comment">// makes sense in actual use cases.</span></div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <span class="keyword">const_cast<</span><a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">MKLMemory<T></a>*<span class="keyword">></span>(<span class="keyword">this</span>)->Reset(</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  dims_, primitive, type, share_mem_if_possible_);</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  CAFFE_ENFORCE(dnnLayoutCompare<T>(layout_wanted, layout_),</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  <span class="stringliteral">"You passed in a target layout that is not "</span></div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  <span class="stringliteral">"generated by the given primitive and type."</span>);</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  buffer_.reset(temp_buffer, [](<span class="keywordtype">void</span>* ptr) -> <span class="keywordtype">void</span> {</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  MKLDNN_CHECK(dnnReleaseBuffer<T>(ptr));</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  });</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <span class="keywordflow">return</span> std::shared_ptr<void>(buffer_);</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <span class="keywordflow">return</span> std::shared_ptr<void>(temp_buffer, [](<span class="keywordtype">void</span>* ptr) -> <span class="keywordtype">void</span> {</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  MKLDNN_CHECK(dnnReleaseBuffer<T>(ptr));</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  });</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  }</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  }</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  }</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span> </div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  <span class="keyword">private</span>:</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <span class="keywordtype">bool</span> share_mem_if_possible_;</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  <span class="keywordtype">bool</span> layout_is_user_layout_;</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <span class="comment">// The internal buffer in the specific dnn layout.</span></div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  <span class="comment">// It is marked mutable but any modification in a const function should</span></div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  <span class="comment">// be accompanied by the buffer lock, see the View() function.</span></div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  <span class="keyword">mutable</span> std::shared_ptr<void> buffer_;</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  <span class="comment">// A mutex to control the access of buffer in the View() function.</span></div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  <span class="keyword">mutable</span> std::mutex buffer_lock_;</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <span class="comment">// The dimensions in the same order as Caffe2 does. This is used to</span></div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  <span class="comment">// interface with C2.</span></div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  vector<TIndex> dims_;</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <span class="comment">// Number of items in the buffer.</span></div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  TIndex size_ = -1;</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  <span class="comment">// The user dnn layout.</span></div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper<T></a> user_layout_;</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <span class="comment">// The internal dnn layout.</span></div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper<T></a> layout_;</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <span class="comment">// The primitive to use to convert from user layout to internal layout</span></div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper<T></a> convert_in_;</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <span class="comment">// The primitive to use to convert from internal layout to user layout</span></div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">PrimitiveWrapper<T></a> convert_out_;</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span> </div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  DISABLE_COPY_AND_ASSIGN(<a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">MKLMemory</a>);</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span> };</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span> </div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00564"></a><span class="lineno"><a class="line" href="classcaffe2_1_1mkl_1_1_m_k_l_workspace.html"> 564</a></span> <span class="keyword">class </span><a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_workspace.html">MKLWorkspace</a> {</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <span class="keyword">public</span>:</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_workspace.html">MKLWorkspace</a>(<span class="keyword">const</span> <a class="code" href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">LayoutWrapper<T></a>& layout) {</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  MKLDNN_SAFE_CALL(mkl::dnnAllocateBuffer<T>(&buffer_, layout));</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  }</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  ~<a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_workspace.html">MKLWorkspace</a>() {</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  dnnReleaseBuffer<T>(buffer_);</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  }</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  T* buffer() {</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="keywordflow">return</span> <span class="keyword">reinterpret_cast<</span>T*<span class="keyword">></span>(buffer_);</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  }</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span> </div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="keyword">private</span>:</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  <span class="keywordtype">void</span>* buffer_;</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  DISABLE_COPY_AND_ASSIGN(<a class="code" href="classcaffe2_1_1mkl_1_1_m_k_l_workspace.html">MKLWorkspace</a>);</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span> };</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span> </div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span> } <span class="comment">// namespace mkl</span></div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span> } <span class="comment">// namespace caffe2</span></div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span> </div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span> <span class="preprocessor">#endif // CAFFE2_UTILS_MKL_MKL_MEMORY_H_</span></div><div class="ttc" id="classcaffe2_1_1mkl_1_1_m_k_l_workspace_html"><div class="ttname"><a href="classcaffe2_1_1mkl_1_1_m_k_l_workspace.html">caffe2::mkl::MKLWorkspace</a></div><div class="ttdef"><b>Definition:</b> <a href="mkl__memory_8h_source.html#l00564">mkl_memory.h:564</a></div></div>
<div class="ttc" id="classcaffe2_1_1_tensor_html_abec0a0587f4afb6baf486bb0659ec47d"><div class="ttname"><a href="classcaffe2_1_1_tensor.html#abec0a0587f4afb6baf486bb0659ec47d">caffe2::Tensor::dim</a></div><div class="ttdeci">TIndex dim(const int i) const </div><div class="ttdoc">Returns the i-th dimension of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="tensor_8h_source.html#l00671">tensor.h:671</a></div></div>
<div class="ttc" id="classcaffe2_1_1mkl_1_1_primitive_wrapper_html"><div class="ttname"><a href="classcaffe2_1_1mkl_1_1_primitive_wrapper.html">caffe2::mkl::PrimitiveWrapper</a></div><div class="ttdef"><b>Definition:</b> <a href="mkl__memory_8h_source.html#l00022">mkl_memory.h:22</a></div></div>
<div class="ttc" id="classcaffe2_1_1_tensor_html"><div class="ttname"><a href="classcaffe2_1_1_tensor.html">caffe2::Tensor< CPUContext ></a></div></div>
<div class="ttc" id="classcaffe2_1_1mkl_1_1_m_k_l_memory_html_ad5702260a1fce3219b5a8a6427ed99e6"><div class="ttname"><a href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html#ad5702260a1fce3219b5a8a6427ed99e6">caffe2::mkl::MKLMemory::dim</a></div><div class="ttdeci">TIndex dim(const int i) const </div><div class="ttdoc">Returns the i-th dimension of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="mkl__memory_8h_source.html#l00482">mkl_memory.h:482</a></div></div>
<div class="ttc" id="classcaffe2_1_1_tensor_html_a87087b9548e9bad215d663389abda32e"><div class="ttname"><a href="classcaffe2_1_1_tensor.html#a87087b9548e9bad215d663389abda32e">caffe2::Tensor::size</a></div><div class="ttdeci">TIndex size() const </div><div class="ttdoc">Returns the size (i.e. </div><div class="ttdef"><b>Definition:</b> <a href="tensor_8h_source.html#l00593">tensor.h:593</a></div></div>
<div class="ttc" id="classcaffe2_1_1_tensor_html_a5fbe65f2d062db6f1f5ab319b0f811fd"><div class="ttname"><a href="classcaffe2_1_1_tensor.html#a5fbe65f2d062db6f1f5ab319b0f811fd">caffe2::Tensor::mutable_data</a></div><div class="ttdeci">T * mutable_data()</div><div class="ttdoc">Returns a typed pointer of the underlying storage. </div><div class="ttdef"><b>Definition:</b> <a href="tensor_8h_source.html#l00578">tensor.h:578</a></div></div>
<div class="ttc" id="classcaffe2_1_1_tensor_html_abd0ea7906b6610956dcbc71bbd9120bf"><div class="ttname"><a href="classcaffe2_1_1_tensor.html#abd0ea7906b6610956dcbc71bbd9120bf">caffe2::Tensor::dims</a></div><div class="ttdeci">const vector< TIndex > & dims() const </div><div class="ttdoc">Returns the dimensions of the tensor as a vector. </div><div class="ttdef"><b>Definition:</b> <a href="tensor_8h_source.html#l00611">tensor.h:611</a></div></div>
<div class="ttc" id="classcaffe2_1_1_tensor_html_a359b5ed5cfd9beaf7f62a5561d939c3b"><div class="ttname"><a href="classcaffe2_1_1_tensor.html#a359b5ed5cfd9beaf7f62a5561d939c3b">caffe2::Tensor::Resize</a></div><div class="ttdeci">void Resize(Ts...dim_source)</div><div class="ttdoc">Resizes a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="tensor_8h_source.html#l00288">tensor.h:288</a></div></div>
<div class="ttc" id="namespacecaffe2_html"><div class="ttname"><a href="namespacecaffe2.html">caffe2</a></div><div class="ttdoc">A global dictionary that holds information about what Caffe2 modules have been loaded in the current ...</div><div class="ttdef"><b>Definition:</b> <a href="convert__encoded__to__raw__leveldb_8cc_source.html#l00047">convert_encoded_to_raw_leveldb.cc:47</a></div></div>
<div class="ttc" id="classcaffe2_1_1mkl_1_1_m_k_l_memory_html"><div class="ttname"><a href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html">caffe2::mkl::MKLMemory</a></div><div class="ttdoc">A wrapper around an opaque MKL internal resource that has certain layouts and convertion primitives s...</div><div class="ttdef"><b>Definition:</b> <a href="mkl__memory_8h_source.html#l00151">mkl_memory.h:151</a></div></div>
<div class="ttc" id="classcaffe2_1_1mkl_1_1_m_k_l_memory_html_aa0beaf56414f73aabac95fac6e1ac1aa"><div class="ttname"><a href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html#aa0beaf56414f73aabac95fac6e1ac1aa">caffe2::mkl::MKLMemory::Reshape</a></div><div class="ttdeci">void Reshape(const vector< IndexType > &dims)</div><div class="ttdoc">Resizes the tensor without touching underlying storage. </div><div class="ttdef"><b>Definition:</b> <a href="mkl__memory_8h_source.html#l00267">mkl_memory.h:267</a></div></div>
<div class="ttc" id="classcaffe2_1_1mkl_1_1_layout_wrapper_html"><div class="ttname"><a href="classcaffe2_1_1mkl_1_1_layout_wrapper.html">caffe2::mkl::LayoutWrapper</a></div><div class="ttdef"><b>Definition:</b> <a href="mkl__memory_8h_source.html#l00065">mkl_memory.h:65</a></div></div>
<div class="ttc" id="classcaffe2_1_1mkl_1_1_m_k_l_memory_html_ab203f62d8ad712b00e805950e5707ca7"><div class="ttname"><a href="classcaffe2_1_1mkl_1_1_m_k_l_memory.html#ab203f62d8ad712b00e805950e5707ca7">caffe2::mkl::MKLMemory::size</a></div><div class="ttdeci">TIndex size() const </div><div class="ttdoc">Returns the size (i.e., the number of items) in the buffer. </div><div class="ttdef"><b>Definition:</b> <a href="mkl__memory_8h_source.html#l00473">mkl_memory.h:473</a></div></div>
<div class="ttc" id="flags_8h_html"><div class="ttname"><a href="flags_8h.html">flags.h</a></div><div class="ttdoc">Commandline flags support for Caffe2. </div></div>
<div class="ttc" id="classcaffe2_1_1_tensor_html_aea51c872873f4db0abad47713315e81f"><div class="ttname"><a href="classcaffe2_1_1_tensor.html#aea51c872873f4db0abad47713315e81f">caffe2::Tensor::ndim</a></div><div class="ttdeci">int ndim() const </div><div class="ttdoc">Returns the number of dimensions of the data. </div><div class="ttdef"><b>Definition:</b> <a href="tensor_8h_source.html#l00589">tensor.h:589</a></div></div>
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