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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="preprocessor">#include <fstream></span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="preprocessor">#include <iterator></span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> </div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#include "caffe2/core/blob_serialization.h"</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "caffe2/core/init.h"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "caffe2/core/logging.h"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "caffe2/core/operator.h"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "caffe2/proto/caffe2.pb.h"</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include "caffe2/utils/proto_utils.h"</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include "caffe2/utils/string_utils.h"</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include "observers/observer_config.h"</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> CAFFE2_DEFINE_string(</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>  backend,</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <span class="stringliteral">"builtin"</span>,</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="stringliteral">"The backend to use when running the model. The allowed "</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="stringliteral">"backend choices are: builtin, default, nnpack, eigen, mkl"</span>);</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> CAFFE2_DEFINE_string(</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  init_net,</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="stringliteral">""</span>,</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="stringliteral">"The given net to initialize any parameters."</span>);</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> CAFFE2_DEFINE_string(</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  input,</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="stringliteral">""</span>,</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="stringliteral">"Input that is needed for running the network. If "</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="stringliteral">"multiple input needed, use comma separated string."</span>);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> CAFFE2_DEFINE_string(</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  input_dims,</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="stringliteral">""</span>,</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="stringliteral">"Alternate to input_files, if all inputs are simple "</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="stringliteral">"float TensorCPUs, specify the dimension using comma "</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="stringliteral">"separated numbers. If multiple input needed, use "</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="stringliteral">"semicolon to separate the dimension of different "</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="stringliteral">"tensors."</span>);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> CAFFE2_DEFINE_string(</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  input_file,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="stringliteral">""</span>,</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="stringliteral">"Input file that contain the serialized protobuf for "</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="stringliteral">"the input blobs. If multiple input needed, use comma "</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="stringliteral">"separated string. Must have the same number of items "</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="stringliteral">"as input does."</span>);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> CAFFE2_DEFINE_string(</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  input_type,</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="stringliteral">"float"</span>,</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="stringliteral">"Input type when specifying the input dimension."</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="stringliteral">"The supported types are float, uint8_t."</span>);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> CAFFE2_DEFINE_int(iter, 10, <span class="stringliteral">"The number of iterations to run."</span>);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> CAFFE2_DEFINE_string(net, <span class="stringliteral">""</span>, <span class="stringliteral">"The given net to benchmark."</span>);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> CAFFE2_DEFINE_string(</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  output,</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="stringliteral">""</span>,</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="stringliteral">"Output that should be dumped after the execution "</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="stringliteral">"finishes. If multiple outputs are needed, use comma "</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="stringliteral">"separated string. If you want to dump everything, pass "</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="stringliteral">"'*' as the output value."</span>);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> CAFFE2_DEFINE_string(</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  output_folder,</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="stringliteral">""</span>,</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="stringliteral">"The folder that the output should be written to. This "</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="stringliteral">"folder must already exist in the file system."</span>);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> CAFFE2_DEFINE_bool(</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  run_individual,</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">false</span>,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="stringliteral">"Whether to benchmark individual operators."</span>);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> CAFFE2_DEFINE_bool(</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  text_output,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">false</span>,</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="stringliteral">"Whether to write out output in text format for regression purpose."</span>);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> CAFFE2_DEFINE_int(warmup, 0, <span class="stringliteral">"The number of iterations to warm up."</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="keyword">using</span> std::string;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="keyword">using</span> std::unique_ptr;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="keyword">using</span> std::vector;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="keyword">static</span> <span class="keywordtype">void</span> writeTextOutput(</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="classcaffe2_1_1_tensor.html">caffe2::TensorCPU</a>* tensor,</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">const</span> <span class="keywordtype">string</span>& output_prefix,</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">const</span> <span class="keywordtype">string</span>& name) {</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordtype">string</span> output_name = output_prefix + <span class="stringliteral">"/"</span> + name + <span class="stringliteral">".txt"</span>;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="classcaffe2_1_1_tensor_serializer.html">caffe2::TensorSerializer<caffe2::CPUContext></a> ser;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  caffe2::BlobProto blob_proto;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  ser.<a class="code" href="classcaffe2_1_1_tensor_serializer.html#a5946d70063bdf3a892b94a65a2cf8fe1">Serialize</a>(</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  *tensor, output_name, blob_proto.mutable_tensor(), 0, tensor-><a class="code" href="classcaffe2_1_1_tensor.html#a87087b9548e9bad215d663389abda32e">size</a>());</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  blob_proto.set_name(output_name);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  blob_proto.set_type(<span class="stringliteral">"Tensor"</span>);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  CAFFE_ENFORCE(blob_proto.has_tensor());</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  caffe2::TensorProto tensor_proto = blob_proto.tensor();</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  vector<float> data;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordflow">switch</span> (tensor_proto.data_type()) {</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keywordflow">case</span> caffe2::TensorProto::FLOAT: {</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  std::copy(</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  tensor_proto.float_data().begin(),</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  tensor_proto.float_data().end(),</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  std::back_inserter(data));</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  }</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">case</span> caffe2::TensorProto::INT32: {</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  std::copy(</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  tensor_proto.int32_data().begin(),</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  tensor_proto.int32_data().end(),</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  std::back_inserter(data));</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordflow">break</span>;</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>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  CAFFE_THROW(<span class="stringliteral">"Unimplemented Blob type."</span>);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  }</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  std::ofstream output_file(output_name);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  std::ostream_iterator<float> output_iterator(output_file, <span class="stringliteral">"\n"</span>);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  std::copy(data.begin(), data.end(), output_iterator);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> }</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="keywordtype">int</span> main(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>** argv) {</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="namespacecaffe2.html#af70b04a01a1779ddd61f9ef1e0a141b7">caffe2::GlobalInit</a>(&argc, &argv);</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <a class="code" href="namespacecaffe2.html#a3123faf5c57e6b67b0d01cd2daa05bf1">caffe2::ShowLogInfoToStderr</a>();</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  unique_ptr<caffe2::Workspace> workspace(<span class="keyword">new</span> <a class="code" href="classcaffe2_1_1_workspace.html">caffe2::Workspace</a>());</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>  <span class="comment">// Run initialization network.</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  caffe2::NetDef init_net_def;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  CAFFE_ENFORCE(ReadProtoFromFile(caffe2::FLAGS_init_net, &init_net_def));</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  CAFFE_ENFORCE(workspace->RunNetOnce(init_net_def));</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="comment">// Load input.</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keywordflow">if</span> (caffe2::FLAGS_input.size()) {</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  vector<string> input_names = caffe2::split(<span class="charliteral">','</span>, caffe2::FLAGS_input);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">if</span> (caffe2::FLAGS_input_file.size()) {</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  vector<string> input_files = caffe2::split(<span class="charliteral">','</span>, caffe2::FLAGS_input_file);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  CAFFE_ENFORCE_EQ(</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  input_names.size(),</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  input_files.size(),</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="stringliteral">"Input name and file should have the same number."</span>);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < input_names.size(); ++i) {</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  caffe2::BlobProto blob_proto;</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  CAFFE_ENFORCE(caffe2::ReadProtoFromFile(input_files[i], &blob_proto));</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  workspace->CreateBlob(input_names[i])->Deserialize(blob_proto);</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>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (caffe2::FLAGS_input_dims.size()) {</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  vector<string> input_dims_list =</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  caffe2::split(<span class="charliteral">';'</span>, caffe2::FLAGS_input_dims);</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  CAFFE_ENFORCE_EQ(</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  input_names.size(),</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  input_dims_list.size(),</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="stringliteral">"Input name and dims should have the same number of items."</span>);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < input_names.size(); ++i) {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  vector<string> input_dims_str = caffe2::split(<span class="charliteral">','</span>, input_dims_list[i]);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  vector<int> input_dims;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keywordtype">string</span>& s : input_dims_str) {</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  input_dims.push_back(caffe2::stoi(s));</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  }</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="keywordflow">if</span> (!workspace->HasBlob(input_names[i])) {</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  workspace->CreateBlob(input_names[i]);</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  }</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="classcaffe2_1_1_tensor.html">caffe2::TensorCPU</a>* tensor =</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  workspace->GetBlob(input_names[i])->GetMutable<<a class="code" href="classcaffe2_1_1_tensor.html">caffe2::TensorCPU</a>>();</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  tensor-><a class="code" href="classcaffe2_1_1_tensor.html#a359b5ed5cfd9beaf7f62a5561d939c3b">Resize</a>(input_dims);</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keywordflow">if</span> (caffe2::FLAGS_input_type == <span class="stringliteral">"float"</span>) {</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  tensor-><a class="code" href="classcaffe2_1_1_tensor.html#a5fbe65f2d062db6f1f5ab319b0f811fd">mutable_data</a><<span class="keywordtype">float</span>>();</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  caffe2::FLAGS_input_type == <span class="stringliteral">"uint8_t"</span>,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="stringliteral">"Only supported input types are: float, uint8_t"</span>);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  tensor-><a class="code" href="classcaffe2_1_1_tensor.html#a5fbe65f2d062db6f1f5ab319b0f811fd">mutable_data</a><uint8_t>();</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  }</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>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  CAFFE_THROW(</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="stringliteral">"You requested input tensors, but neither input_file nor "</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="stringliteral">"input_dims is set."</span>);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  }</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  }</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="comment">// Run main network.</span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  caffe2::NetDef net_def;</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  CAFFE_ENFORCE(ReadProtoFromFile(caffe2::FLAGS_net, &net_def));</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordflow">if</span> (caffe2::FLAGS_backend != <span class="stringliteral">"builtin"</span>) {</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  std::string engine = caffe2::FLAGS_backend == <span class="stringliteral">"nnpack"</span></div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  ? <span class="stringliteral">"NNPACK"</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  : caffe2::FLAGS_backend == <span class="stringliteral">"eigen"</span> ? <span class="stringliteral">"EIGEN"</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  : caffe2::FLAGS_backend == <span class="stringliteral">"mkl"</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  ? <span class="stringliteral">"MKLDNN"</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  : caffe2::FLAGS_backend == <span class="stringliteral">"default"</span> ? <span class="stringliteral">""</span> : <span class="stringliteral">"NONE"</span>;</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  CAFFE_ENFORCE(engine != <span class="stringliteral">"NONE"</span>, <span class="stringliteral">"Backend is not supported"</span>);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < net_def.op_size(); i++) {</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  caffe2::OperatorDef* op_def = net_def.mutable_op(i);</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  op_def->set_engine(engine);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  }</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  }</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> </div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <a class="code" href="classcaffe2_1_1_net_base.html">caffe2::NetBase</a>* net = workspace->CreateNet(net_def);</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  CHECK_NOTNULL(net);</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> </div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  LOG(INFO) << <span class="stringliteral">"Starting benchmark."</span>;</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  caffe2::ObserverConfig::initSampleRate(</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  1, 1, 1, caffe2::FLAGS_run_individual, caffe2::FLAGS_warmup);</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  LOG(INFO) << <span class="stringliteral">"Running warmup runs."</span>;</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < caffe2::FLAGS_warmup; ++i) {</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  CAFFE_ENFORCE(net->Run(), <span class="stringliteral">"Warmup run "</span>, i, <span class="stringliteral">" has failed."</span>);</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> </div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  LOG(INFO) << <span class="stringliteral">"Main runs."</span>;</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  caffe2::FLAGS_iter >= 0,</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="stringliteral">"Number of main runs should be non negative, provided "</span>,</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  caffe2::FLAGS_iter,</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="stringliteral">"."</span>);</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < caffe2::FLAGS_iter; ++i) {</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  caffe2::ObserverConfig::initSampleRate(1, 1, 1, 0, caffe2::FLAGS_warmup);</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  CAFFE_ENFORCE(net->Run(), <span class="stringliteral">"Main run "</span>, i, <span class="stringliteral">" has failed."</span>);</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">if</span> (caffe2::FLAGS_run_individual) {</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  caffe2::ObserverConfig::initSampleRate(1, 1, 1, 1, caffe2::FLAGS_warmup);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  CAFFE_ENFORCE(net->Run(), <span class="stringliteral">"Main run "</span>, i, <span class="stringliteral">" with operator has failed."</span>);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  }</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  }</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordtype">string</span> output_prefix = caffe2::FLAGS_output_folder.size()</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  ? caffe2::FLAGS_output_folder + <span class="stringliteral">"/"</span></div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  : <span class="stringliteral">""</span>;</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordflow">if</span> (caffe2::FLAGS_output.size()) {</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  vector<string> output_names = caffe2::split(<span class="charliteral">','</span>, caffe2::FLAGS_output);</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keywordflow">if</span> (caffe2::FLAGS_output == <span class="stringliteral">"*"</span>) {</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  output_names = workspace->Blobs();</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  }</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keywordtype">string</span>& name : output_names) {</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  CAFFE_ENFORCE(</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  workspace->HasBlob(name),</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="stringliteral">"You requested a non-existing blob: "</span>,</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  name);</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="keywordflow">if</span> (caffe2::FLAGS_text_output) {</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keyword">auto</span> blob = workspace->GetBlob(name)->GetMutable<<a class="code" href="classcaffe2_1_1_tensor.html">caffe2::TensorCPU</a>>();</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  writeTextOutput(blob, output_prefix, name);</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="keywordtype">string</span> serialized = workspace->GetBlob(name)->Serialize(name);</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <span class="keywordtype">string</span> output_filename = output_prefix + name;</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  caffe2::WriteStringToFile(serialized, output_filename.c_str());</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  }</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  }</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  }</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>  <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> }</div><div class="ttc" id="namespacecaffe2_html_af70b04a01a1779ddd61f9ef1e0a141b7"><div class="ttname"><a href="namespacecaffe2.html#af70b04a01a1779ddd61f9ef1e0a141b7">caffe2::GlobalInit</a></div><div class="ttdeci">bool GlobalInit(int *pargc, char ***pargv)</div><div class="ttdoc">Initialize the global environment of caffe2. </div><div class="ttdef"><b>Definition:</b> <a href="init_8cc_source.html#l00018">init.cc:18</a></div></div>
<div class="ttc" id="classcaffe2_1_1_tensor_serializer_html"><div class="ttname"><a href="classcaffe2_1_1_tensor_serializer.html">caffe2::TensorSerializer</a></div><div class="ttdoc">TensorSerializer is the serializer for Tensors. </div><div class="ttdef"><b>Definition:</b> <a href="blob__serialization_8h_source.html#l00046">blob_serialization.h:46</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_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_workspace_html"><div class="ttname"><a href="classcaffe2_1_1_workspace.html">caffe2::Workspace</a></div><div class="ttdoc">Workspace is a class that holds all the related objects created during runtime: (1) all blobs...</div><div class="ttdef"><b>Definition:</b> <a href="workspace_8h_source.html#l00047">workspace.h:47</a></div></div>
<div class="ttc" id="classcaffe2_1_1_tensor_serializer_html_a5946d70063bdf3a892b94a65a2cf8fe1"><div class="ttname"><a href="classcaffe2_1_1_tensor_serializer.html#a5946d70063bdf3a892b94a65a2cf8fe1">caffe2::TensorSerializer::Serialize</a></div><div class="ttdeci">void Serialize(const Blob &blob, const string &name, SerializationAcceptor acceptor) override</div><div class="ttdoc">Serializes a Blob. </div><div class="ttdef"><b>Definition:</b> <a href="blob__serialization_8h_source.html#l00186">blob_serialization.h:186</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_a3123faf5c57e6b67b0d01cd2daa05bf1"><div class="ttname"><a href="namespacecaffe2.html#a3123faf5c57e6b67b0d01cd2daa05bf1">caffe2::ShowLogInfoToStderr</a></div><div class="ttdeci">void ShowLogInfoToStderr()</div><div class="ttdoc">A utility to allow one to show log info to stderr after the program starts. </div><div class="ttdef"><b>Definition:</b> <a href="logging_8cc_source.html#l00196">logging.cc:196</a></div></div>
<div class="ttc" id="classcaffe2_1_1_net_base_html"><div class="ttname"><a href="classcaffe2_1_1_net_base.html">caffe2::NetBase</a></div><div class="ttdef"><b>Definition:</b> <a href="net_8h_source.html#l00035">net.h:35</a></div></div>
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