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<a href="iteration__stats_8cc.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno"> 1</span><span class="comment">// Copyright 2010-2021 Google LLC</span></div>
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<div class="line"><a id="l00002" name="l00002"></a><span class="lineno"> 2</span><span class="comment">// Licensed under the Apache License, Version 2.0 (the "License");</span></div>
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<div class="line"><a id="l00003" name="l00003"></a><span class="lineno"> 3</span><span class="comment">// you may not use this file except in compliance with the License.</span></div>
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<div class="line"><a id="l00004" name="l00004"></a><span class="lineno"> 4</span><span class="comment">// You may obtain a copy of the License at</span></div>
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<div class="line"><a id="l00005" name="l00005"></a><span class="lineno"> 5</span><span class="comment">//</span></div>
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<div class="line"><a id="l00006" name="l00006"></a><span class="lineno"> 6</span><span class="comment">// http://www.apache.org/licenses/LICENSE-2.0</span></div>
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<div class="line"><a id="l00007" name="l00007"></a><span class="lineno"> 7</span><span class="comment">//</span></div>
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<div class="line"><a id="l00008" name="l00008"></a><span class="lineno"> 8</span><span class="comment">// Unless required by applicable law or agreed to in writing, software</span></div>
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<div class="line"><a id="l00009" name="l00009"></a><span class="lineno"> 9</span><span class="comment">// distributed under the License is distributed on an "AS IS" BASIS,</span></div>
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<div class="line"><a id="l00010" name="l00010"></a><span class="lineno"> 10</span><span class="comment">// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span></div>
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<div class="line"><a id="l00011" name="l00011"></a><span class="lineno"> 11</span><span class="comment">// See the License for the specific language governing permissions and</span></div>
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<div class="line"><a id="l00012" name="l00012"></a><span class="lineno"> 12</span><span class="comment">// limitations under the License.</span></div>
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||
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno"> 13</span> </div>
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<div class="line"><a id="l00014" name="l00014"></a><span class="lineno"> 14</span><span class="preprocessor">#include "<a class="code" href="iteration__stats_8h.html">ortools/pdlp/iteration_stats.h</a>"</span></div>
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<div class="line"><a id="l00015" name="l00015"></a><span class="lineno"> 15</span> </div>
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<div class="line"><a id="l00016" name="l00016"></a><span class="lineno"> 16</span><span class="preprocessor">#include <algorithm></span></div>
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<div class="line"><a id="l00017" name="l00017"></a><span class="lineno"> 17</span><span class="preprocessor">#include <cmath></span></div>
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<div class="line"><a id="l00018" name="l00018"></a><span class="lineno"> 18</span><span class="preprocessor">#include <cstdint></span></div>
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<div class="line"><a id="l00019" name="l00019"></a><span class="lineno"> 19</span><span class="preprocessor">#include <limits></span></div>
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<div class="line"><a id="l00020" name="l00020"></a><span class="lineno"> 20</span><span class="preprocessor">#include <random></span></div>
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<div class="line"><a id="l00021" name="l00021"></a><span class="lineno"> 21</span><span class="preprocessor">#include <string></span></div>
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<div class="line"><a id="l00022" name="l00022"></a><span class="lineno"> 22</span><span class="preprocessor">#include <utility></span></div>
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<div class="line"><a id="l00023" name="l00023"></a><span class="lineno"> 23</span><span class="preprocessor">#include <vector></span></div>
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<div class="line"><a id="l00024" name="l00024"></a><span class="lineno"> 24</span> </div>
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<div class="line"><a id="l00025" name="l00025"></a><span class="lineno"> 25</span><span class="preprocessor">#include "Eigen/Core"</span></div>
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<div class="line"><a id="l00026" name="l00026"></a><span class="lineno"> 26</span><span class="preprocessor">#include "Eigen/SparseCore"</span></div>
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<div class="line"><a id="l00027" name="l00027"></a><span class="lineno"> 27</span><span class="preprocessor">#include "absl/random/distributions.h"</span></div>
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<div class="line"><a id="l00028" name="l00028"></a><span class="lineno"> 28</span><span class="preprocessor">#include "absl/strings/str_cat.h"</span></div>
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<div class="line"><a id="l00029" name="l00029"></a><span class="lineno"> 29</span><span class="preprocessor">#include "absl/strings/str_format.h"</span></div>
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<div class="line"><a id="l00030" name="l00030"></a><span class="lineno"> 30</span><span class="preprocessor">#include "absl/strings/string_view.h"</span></div>
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||
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno"> 31</span><span class="preprocessor">#include "absl/types/optional.h"</span></div>
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<div class="line"><a id="l00032" name="l00032"></a><span class="lineno"> 32</span><span class="preprocessor">#include "<a class="code" href="base_2logging_8h.html">ortools/base/logging.h</a>"</span></div>
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||
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno"> 33</span><span class="preprocessor">#include "<a class="code" href="mathutil_8h.html">ortools/base/mathutil.h</a>"</span></div>
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<div class="line"><a id="l00034" name="l00034"></a><span class="lineno"> 34</span><span class="preprocessor">#include "<a class="code" href="quadratic__program_8h.html">ortools/pdlp/quadratic_program.h</a>"</span></div>
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<div class="line"><a id="l00035" name="l00035"></a><span class="lineno"> 35</span><span class="preprocessor">#include "<a class="code" href="sharded__quadratic__program_8h.html">ortools/pdlp/sharded_quadratic_program.h</a>"</span></div>
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<div class="line"><a id="l00036" name="l00036"></a><span class="lineno"> 36</span><span class="preprocessor">#include "<a class="code" href="sharder_8h.html">ortools/pdlp/sharder.h</a>"</span></div>
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<div class="line"><a id="l00037" name="l00037"></a><span class="lineno"> 37</span><span class="preprocessor">#include "ortools/pdlp/solve_log.pb.h"</span></div>
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||
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno"> 38</span><span class="preprocessor">#include "ortools/pdlp/solvers.pb.h"</span></div>
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<div class="line"><a id="l00039" name="l00039"></a><span class="lineno"> 39</span> </div>
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<div class="line"><a id="l00040" name="l00040"></a><span class="lineno"><a class="line" href="namespaceoperations__research_1_1pdlp.html"> 40</a></span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceoperations__research_1_1pdlp.html">operations_research::pdlp</a> {</div>
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||
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno"> 41</span><span class="keyword">namespace </span>{</div>
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<div class="line"><a id="l00042" name="l00042"></a><span class="lineno"> 42</span> </div>
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||
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno"> 43</span>using ::Eigen::VectorXd;</div>
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||
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno"> 44</span> </div>
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||
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno"> 45</span><span class="comment">// ResidualNorms contains four measures of the infeasibility of a primal or</span></div>
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||
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno"> 46</span><span class="comment">// dual solution. "objective_correction" is the (additive) adjustment to the</span></div>
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||
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno"> 47</span><span class="comment">// objective function from the reduced costs. "objective_full_correction" is the</span></div>
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||
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno"> 48</span><span class="comment">// (additive) adjustment to the objective function if all dual residuals were</span></div>
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||
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno"> 49</span><span class="comment">// set to zero, while l_inf_residual and l_2_residual are the L_infinity and L_2</span></div>
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||
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno"> 50</span><span class="comment">// norms of the residuals (portions of the primal gradient not included in the</span></div>
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||
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno"> 51</span><span class="comment">// reduced costs).</span></div>
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||
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno"> 52</span><span class="keyword">struct </span>ResidualNorms {</div>
|
||
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno"><a class="line" href="iteration__stats_8cc.html#a28460a7fdcd91c3a3a95b2b74aff7bb7"> 53</a></span> <span class="keywordtype">double</span> <a class="code hl_variable" href="iteration__stats_8cc.html#a28460a7fdcd91c3a3a95b2b74aff7bb7">objective_correction</a>;</div>
|
||
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno"><a class="line" href="iteration__stats_8cc.html#a16e7df0f7c2a47748aaf9004258c6b13"> 54</a></span> <span class="keywordtype">double</span> <a class="code hl_variable" href="iteration__stats_8cc.html#a16e7df0f7c2a47748aaf9004258c6b13">objective_full_correction</a>;</div>
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||
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno"><a class="line" href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f"> 55</a></span> <span class="keywordtype">double</span> <a class="code hl_variable" href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f">l_inf_residual</a>;</div>
|
||
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno"><a class="line" href="iteration__stats_8cc.html#a16548fbf63af658d61de20a71baded7a"> 56</a></span> <span class="keywordtype">double</span> <a class="code hl_variable" href="iteration__stats_8cc.html#a16548fbf63af658d61de20a71baded7a">l_2_residual</a>;</div>
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||
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno"> 57</span>};</div>
|
||
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno"> 58</span> </div>
|
||
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno"> 59</span><span class="comment">// Computes norms of the primal residual infeasibilities (b - A x) of the</span></div>
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||
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno"> 60</span><span class="comment">// unscaled problem. Note the primal residuals of the unscaled problem are equal</span></div>
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||
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno"> 61</span><span class="comment">// to those of the scaled problem divided by row_scaling_vec. Does not perform</span></div>
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||
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno"> 62</span><span class="comment">// any corrections (so the returned .correction == 0.0). sharded_qp is assumed</span></div>
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||
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno"> 63</span><span class="comment">// to be the scaled problem. If use_homogeneous_primal_bounds is set to true</span></div>
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||
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno"> 64</span><span class="comment">// the residuals are computed with upper and lower bounds zeroed out (note that</span></div>
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||
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno"> 65</span><span class="comment">// we only zero out the bounds that are finite in the original problem).</span></div>
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||
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno"> 66</span>ResidualNorms PrimalResidualNorms(</div>
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<div class="line"><a id="l00067" name="l00067"></a><span class="lineno"> 67</span> <span class="keyword">const</span> ShardedQuadraticProgram& sharded_qp, <span class="keyword">const</span> VectorXd& row_scaling_vec,</div>
|
||
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno"> 68</span> <span class="keyword">const</span> VectorXd& scaled_primal_solution,</div>
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||
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno"> 69</span> <span class="keywordtype">bool</span> use_homogeneous_constraint_bounds = <span class="keyword">false</span>) {</div>
|
||
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno"> 70</span> <span class="keyword">const</span> QuadraticProgram& qp = sharded_qp.Qp();</div>
|
||
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno"> 71</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(row_scaling_vec.size(), sharded_qp.DualSize());</div>
|
||
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno"> 72</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(scaled_primal_solution.size(), sharded_qp.PrimalSize());</div>
|
||
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno"> 73</span> </div>
|
||
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno"> 74</span> VectorXd primal_product = <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a463586ded0a114d3ca4b97a048d37d8a">TransposedMatrixVectorProduct</a>(</div>
|
||
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno"> 75</span> sharded_qp.TransposedConstraintMatrix(), scaled_primal_solution,</div>
|
||
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno"> 76</span> sharded_qp.TransposedConstraintMatrixSharder());</div>
|
||
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno"> 77</span> VectorXd local_l_inf_residual(sharded_qp.DualSharder().NumShards());</div>
|
||
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno"> 78</span> VectorXd local_sumsq_residual(sharded_qp.DualSharder().NumShards());</div>
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||
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno"> 79</span> sharded_qp.DualSharder().ParallelForEachShard(</div>
|
||
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno"> 80</span> [&](<span class="keyword">const</span> Sharder::Shard& shard) {</div>
|
||
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno"> 81</span> <span class="keyword">const</span> <span class="keyword">auto</span> lower_bound_shard = shard(qp.constraint_lower_bounds);</div>
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||
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno"> 82</span> <span class="keyword">const</span> <span class="keyword">auto</span> upper_bound_shard = shard(qp.constraint_upper_bounds);</div>
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||
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno"> 83</span> <span class="keyword">const</span> <span class="keyword">auto</span> row_scaling_shard = shard(row_scaling_vec);</div>
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<div class="line"><a id="l00084" name="l00084"></a><span class="lineno"> 84</span> <span class="keyword">const</span> <span class="keyword">auto</span> primal_product_shard = shard(primal_product);</div>
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||
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno"> 85</span> <span class="keywordtype">double</span> <a class="code hl_variable" href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f">l_inf_residual</a> = 0.0;</div>
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||
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno"> 86</span> <span class="keywordtype">double</span> sumsq_residual = 0.0;</div>
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<div class="line"><a id="l00087" name="l00087"></a><span class="lineno"> 87</span> <span class="keywordflow">for</span> (int64_t i = 0; i < primal_product_shard.size(); ++i) {</div>
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<div class="line"><a id="l00088" name="l00088"></a><span class="lineno"> 88</span> <span class="keyword">const</span> <span class="keywordtype">double</span> <a class="code hl_variable" href="gscip__solver_8cc.html#a1ba5ca0f61f2fa13bd23bf0f89004f35">upper_bound</a> = (use_homogeneous_constraint_bounds &&</div>
|
||
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno"> 89</span> std::isfinite(upper_bound_shard[i]))</div>
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<div class="line"><a id="l00090" name="l00090"></a><span class="lineno"> 90</span> ? 0.0</div>
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<div class="line"><a id="l00091" name="l00091"></a><span class="lineno"> 91</span> : upper_bound_shard[i];</div>
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||
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno"> 92</span> <span class="keyword">const</span> <span class="keywordtype">double</span> <a class="code hl_variable" href="gscip__solver_8cc.html#a1e2f9a2352c1d9a6cada9544898fceec">lower_bound</a> = (use_homogeneous_constraint_bounds &&</div>
|
||
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno"> 93</span> std::isfinite(lower_bound_shard[i]))</div>
|
||
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno"> 94</span> ? 0.0</div>
|
||
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno"> 95</span> : lower_bound_shard[i];</div>
|
||
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno"> 96</span> <span class="keywordtype">double</span> scaled_residual = 0.0;</div>
|
||
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno"> 97</span> <span class="keywordflow">if</span> (primal_product_shard[i] > <a class="code hl_variable" href="gscip__solver_8cc.html#a1ba5ca0f61f2fa13bd23bf0f89004f35">upper_bound</a>) {</div>
|
||
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno"> 98</span> scaled_residual = primal_product_shard[i] - <a class="code hl_variable" href="gscip__solver_8cc.html#a1ba5ca0f61f2fa13bd23bf0f89004f35">upper_bound</a>;</div>
|
||
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno"> 99</span> </div>
|
||
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno"> 100</span> } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (primal_product_shard[i] < <a class="code hl_variable" href="gscip__solver_8cc.html#a1e2f9a2352c1d9a6cada9544898fceec">lower_bound</a>) {</div>
|
||
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno"> 101</span> scaled_residual = <a class="code hl_variable" href="gscip__solver_8cc.html#a1e2f9a2352c1d9a6cada9544898fceec">lower_bound</a> - primal_product_shard[i];</div>
|
||
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno"> 102</span> }</div>
|
||
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno"> 103</span> <span class="keyword">const</span> <span class="keywordtype">double</span> residual = scaled_residual / row_scaling_shard[i];</div>
|
||
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno"> 104</span> <a class="code hl_variable" href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f">l_inf_residual</a> = <a class="code hl_variable" href="alldiff__cst_8cc.html#a26e6db9bcc64b584051ecc28171ed11f">std::max</a>(<a class="code hl_variable" href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f">l_inf_residual</a>, residual);</div>
|
||
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno"> 105</span> sumsq_residual += residual * residual;</div>
|
||
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno"> 106</span> }</div>
|
||
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno"> 107</span> local_l_inf_residual[shard.Index()] = <a class="code hl_variable" href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f">l_inf_residual</a>;</div>
|
||
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno"> 108</span> local_sumsq_residual[shard.Index()] = sumsq_residual;</div>
|
||
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno"> 109</span> });</div>
|
||
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno"> 110</span> <span class="keywordflow">return</span> ResidualNorms{</div>
|
||
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno"> 111</span> .objective_correction = 0.0,</div>
|
||
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno"> 112</span> .objective_full_correction = 0.0,</div>
|
||
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno"> 113</span> .l_inf_residual = local_l_inf_residual.lpNorm<Eigen::Infinity>(),</div>
|
||
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno"> 114</span> .<a class="code hl_variable" href="iteration__stats_8cc.html#a16548fbf63af658d61de20a71baded7a">l_2_residual</a> = std::sqrt(local_sumsq_residual.sum()),</div>
|
||
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno"> 115</span> };</div>
|
||
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno"> 116</span>}</div>
|
||
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno"> 117</span> </div>
|
||
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno"> 118</span><span class="comment">// Decides whether a primal gradient term should be handled as a reduced cost or</span></div>
|
||
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno"> 119</span><span class="comment">// as a dual residual.</span></div>
|
||
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno"> 120</span><span class="keywordtype">bool</span> HandlePrimalGradientTermAsReducedCost(<span class="keywordtype">double</span> primal_gradient,</div>
|
||
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno"> 121</span> <span class="keywordtype">double</span> primal_value,</div>
|
||
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno"> 122</span> <span class="keywordtype">double</span> <a class="code hl_variable" href="gscip__solver_8cc.html#a1e2f9a2352c1d9a6cada9544898fceec">lower_bound</a>,</div>
|
||
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno"> 123</span> <span class="keywordtype">double</span> <a class="code hl_variable" href="gscip__solver_8cc.html#a1ba5ca0f61f2fa13bd23bf0f89004f35">upper_bound</a>) {</div>
|
||
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno"> 124</span> <span class="keywordflow">if</span> (primal_gradient == 0.0) <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
|
||
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno"> 125</span> <span class="keywordflow">return</span> std::abs(primal_value -</div>
|
||
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno"> 126</span> (primal_gradient > 0.0 ? <a class="code hl_variable" href="gscip__solver_8cc.html#a1e2f9a2352c1d9a6cada9544898fceec">lower_bound</a> : <a class="code hl_variable" href="gscip__solver_8cc.html#a1ba5ca0f61f2fa13bd23bf0f89004f35">upper_bound</a>)) <=</div>
|
||
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno"> 127</span> std::abs(primal_value);</div>
|
||
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno"> 128</span>}</div>
|
||
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno"> 129</span> </div>
|
||
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno"> 130</span><span class="comment">// Computes norms of the dual residuals and reduced costs of the unscaled</span></div>
|
||
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno"> 131</span><span class="comment">// problem. Note the primal gradient of the unscaled problem is equal to the</span></div>
|
||
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno"> 132</span><span class="comment">// scaled primal gradient divided by col_scaling_vec. sharded_qp is assumed to</span></div>
|
||
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno"> 133</span><span class="comment">// be the scaled problem. See</span></div>
|
||
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno"> 134</span><span class="comment">// https://developers.google.com/optimization/lp/pdlp_math for details and</span></div>
|
||
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno"> 135</span><span class="comment">// notation. Primal gradients that have corresponding (finite) bounds (the</span></div>
|
||
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno"> 136</span><span class="comment">// finite terms from (l^v)^T[r]_+ − (u^v)^T[r]_− in the dual objective), and</span></div>
|
||
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno"> 137</span><span class="comment">// have |x - b| <= |x| (where x is the variable's value and b is the</span></div>
|
||
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno"> 138</span><span class="comment">// corresponding bound) are treated as reduced costs and accumulated in</span></div>
|
||
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno"> 139</span><span class="comment">// objective_correction, while the other primal gradient terms are handled as</span></div>
|
||
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno"> 140</span><span class="comment">// residual infeasibilities in l_inf_residual and l_2_residual.</span></div>
|
||
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno"> 141</span>ResidualNorms DualResidualNorms(<span class="keyword">const</span> ShardedQuadraticProgram& sharded_qp,</div>
|
||
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno"> 142</span> <span class="keyword">const</span> VectorXd& col_scaling_vec,</div>
|
||
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno"> 143</span> <span class="keyword">const</span> VectorXd& scaled_primal_solution,</div>
|
||
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno"> 144</span> <span class="keyword">const</span> VectorXd& scaled_primal_gradient) {</div>
|
||
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno"> 145</span> <span class="keyword">const</span> QuadraticProgram& qp = sharded_qp.Qp();</div>
|
||
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno"> 146</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(col_scaling_vec.size(), sharded_qp.PrimalSize());</div>
|
||
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno"> 147</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(scaled_primal_gradient.size(), sharded_qp.PrimalSize());</div>
|
||
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno"> 148</span> VectorXd local_dual_correction(sharded_qp.PrimalSharder().NumShards());</div>
|
||
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno"> 149</span> VectorXd local_dual_full_correction(sharded_qp.PrimalSharder().NumShards());</div>
|
||
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno"> 150</span> VectorXd local_l_inf_residual(sharded_qp.PrimalSharder().NumShards());</div>
|
||
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno"> 151</span> VectorXd local_sumsq_residual(sharded_qp.PrimalSharder().NumShards());</div>
|
||
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno"> 152</span> sharded_qp.PrimalSharder().ParallelForEachShard(</div>
|
||
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno"> 153</span> [&](<span class="keyword">const</span> Sharder::Shard& shard) {</div>
|
||
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno"> 154</span> <span class="keyword">const</span> <span class="keyword">auto</span> lower_bound_shard = shard(qp.variable_lower_bounds);</div>
|
||
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno"> 155</span> <span class="keyword">const</span> <span class="keyword">auto</span> upper_bound_shard = shard(qp.variable_upper_bounds);</div>
|
||
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno"> 156</span> <span class="keyword">const</span> <span class="keyword">auto</span> primal_gradient_shard = shard(scaled_primal_gradient);</div>
|
||
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno"> 157</span> <span class="keyword">const</span> <span class="keyword">auto</span> col_scaling_shard = shard(col_scaling_vec);</div>
|
||
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno"> 158</span> <span class="keyword">const</span> <span class="keyword">auto</span> primal_solution_shard = shard(scaled_primal_solution);</div>
|
||
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno"> 159</span> <span class="keywordtype">double</span> dual_correction = 0.0;</div>
|
||
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno"> 160</span> <span class="keywordtype">double</span> dual_full_correction = 0.0;</div>
|
||
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno"> 161</span> <span class="keywordtype">double</span> <a class="code hl_variable" href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f">l_inf_residual</a> = 0.0;</div>
|
||
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno"> 162</span> <span class="keywordtype">double</span> sumsq_residual = 0.0;</div>
|
||
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno"> 163</span> <span class="keywordflow">for</span> (int64_t i = 0; i < primal_gradient_shard.size(); ++i) {</div>
|
||
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno"> 164</span> <span class="comment">// The corrections use the scaled values because</span></div>
|
||
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno"> 165</span> <span class="comment">// unscaled_lower_bound = lower_bound * scale and</span></div>
|
||
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno"> 166</span> <span class="comment">// unscaled_primal_gradient = primal_gradient / scale, so the scales</span></div>
|
||
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno"> 167</span> <span class="comment">// cancel out.</span></div>
|
||
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno"> 168</span> <span class="keywordflow">if</span> (primal_gradient_shard[i] == 0.0) <span class="keywordflow">continue</span>;</div>
|
||
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno"> 169</span> <span class="keyword">const</span> <span class="keywordtype">double</span> bound_for_rc = primal_gradient_shard[i] > 0.0</div>
|
||
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno"> 170</span> ? lower_bound_shard[i]</div>
|
||
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno"> 171</span> : upper_bound_shard[i];</div>
|
||
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno"> 172</span> dual_full_correction += bound_for_rc * primal_gradient_shard[i];</div>
|
||
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno"> 173</span> <span class="keywordflow">if</span> (HandlePrimalGradientTermAsReducedCost(</div>
|
||
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno"> 174</span> primal_gradient_shard[i], primal_solution_shard[i],</div>
|
||
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno"> 175</span> lower_bound_shard[i], upper_bound_shard[i])) {</div>
|
||
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno"> 176</span> dual_correction += bound_for_rc * primal_gradient_shard[i];</div>
|
||
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno"> 177</span> } <span class="keywordflow">else</span> {</div>
|
||
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno"> 178</span> <span class="keyword">const</span> <span class="keywordtype">double</span> scaled_residual = std::abs(primal_gradient_shard[i]);</div>
|
||
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno"> 179</span> <span class="keyword">const</span> <span class="keywordtype">double</span> residual = scaled_residual / col_scaling_shard[i];</div>
|
||
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno"> 180</span> <a class="code hl_variable" href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f">l_inf_residual</a> = <a class="code hl_variable" href="alldiff__cst_8cc.html#a26e6db9bcc64b584051ecc28171ed11f">std::max</a>(<a class="code hl_variable" href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f">l_inf_residual</a>, residual);</div>
|
||
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno"> 181</span> sumsq_residual += residual * residual;</div>
|
||
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno"> 182</span> }</div>
|
||
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno"> 183</span> }</div>
|
||
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno"> 184</span> local_dual_correction[shard.Index()] = dual_correction;</div>
|
||
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno"> 185</span> local_dual_full_correction[shard.Index()] = dual_full_correction;</div>
|
||
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno"> 186</span> local_l_inf_residual[shard.Index()] = <a class="code hl_variable" href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f">l_inf_residual</a>;</div>
|
||
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno"> 187</span> local_sumsq_residual[shard.Index()] = sumsq_residual;</div>
|
||
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno"> 188</span> });</div>
|
||
<div class="line"><a id="l00189" name="l00189"></a><span class="lineno"> 189</span> <span class="keywordflow">return</span> ResidualNorms{</div>
|
||
<div class="line"><a id="l00190" name="l00190"></a><span class="lineno"> 190</span> .objective_correction = local_dual_correction.sum(),</div>
|
||
<div class="line"><a id="l00191" name="l00191"></a><span class="lineno"> 191</span> .objective_full_correction = local_dual_full_correction.sum(),</div>
|
||
<div class="line"><a id="l00192" name="l00192"></a><span class="lineno"> 192</span> .l_inf_residual = local_l_inf_residual.lpNorm<Eigen::Infinity>(),</div>
|
||
<div class="line"><a id="l00193" name="l00193"></a><span class="lineno"> 193</span> .<a class="code hl_variable" href="iteration__stats_8cc.html#a16548fbf63af658d61de20a71baded7a">l_2_residual</a> = std::sqrt(local_sumsq_residual.sum()),</div>
|
||
<div class="line"><a id="l00194" name="l00194"></a><span class="lineno"> 194</span> };</div>
|
||
<div class="line"><a id="l00195" name="l00195"></a><span class="lineno"> 195</span>}</div>
|
||
<div class="line"><a id="l00196" name="l00196"></a><span class="lineno"> 196</span> </div>
|
||
<div class="line"><a id="l00197" name="l00197"></a><span class="lineno"> 197</span><span class="comment">// Returns Qx.</span></div>
|
||
<div class="line"><a id="l00198" name="l00198"></a><span class="lineno"> 198</span>VectorXd ObjectiveProduct(<span class="keyword">const</span> ShardedQuadraticProgram& sharded_qp,</div>
|
||
<div class="line"><a id="l00199" name="l00199"></a><span class="lineno"> 199</span> <span class="keyword">const</span> VectorXd& primal_solution) {</div>
|
||
<div class="line"><a id="l00200" name="l00200"></a><span class="lineno"> 200</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(primal_solution.size(), sharded_qp.PrimalSize());</div>
|
||
<div class="line"><a id="l00201" name="l00201"></a><span class="lineno"> 201</span> VectorXd result(primal_solution.size());</div>
|
||
<div class="line"><a id="l00202" name="l00202"></a><span class="lineno"> 202</span> <span class="keywordflow">if</span> (<a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a850865b3deabb2a623e130691df99f15">IsLinearProgram</a>(sharded_qp.Qp())) {</div>
|
||
<div class="line"><a id="l00203" name="l00203"></a><span class="lineno"> 203</span> result.setZero();</div>
|
||
<div class="line"><a id="l00204" name="l00204"></a><span class="lineno"> 204</span> } <span class="keywordflow">else</span> {</div>
|
||
<div class="line"><a id="l00205" name="l00205"></a><span class="lineno"> 205</span> sharded_qp.PrimalSharder().ParallelForEachShard(</div>
|
||
<div class="line"><a id="l00206" name="l00206"></a><span class="lineno"> 206</span> [&](<span class="keyword">const</span> Sharder::Shard& shard) {</div>
|
||
<div class="line"><a id="l00207" name="l00207"></a><span class="lineno"> 207</span> shard(result) =</div>
|
||
<div class="line"><a id="l00208" name="l00208"></a><span class="lineno"> 208</span> shard(*sharded_qp.Qp().objective_matrix) * shard(primal_solution);</div>
|
||
<div class="line"><a id="l00209" name="l00209"></a><span class="lineno"> 209</span> });</div>
|
||
<div class="line"><a id="l00210" name="l00210"></a><span class="lineno"> 210</span> }</div>
|
||
<div class="line"><a id="l00211" name="l00211"></a><span class="lineno"> 211</span> <span class="keywordflow">return</span> result;</div>
|
||
<div class="line"><a id="l00212" name="l00212"></a><span class="lineno"> 212</span>}</div>
|
||
<div class="line"><a id="l00213" name="l00213"></a><span class="lineno"> 213</span> </div>
|
||
<div class="line"><a id="l00214" name="l00214"></a><span class="lineno"> 214</span><span class="comment">// Returns 1/2 x^T Q x (the quadratic term in the objective).</span></div>
|
||
<div class="line"><a id="l00215" name="l00215"></a><span class="lineno"> 215</span><span class="keywordtype">double</span> QuadraticObjective(<span class="keyword">const</span> ShardedQuadraticProgram& sharded_qp,</div>
|
||
<div class="line"><a id="l00216" name="l00216"></a><span class="lineno"> 216</span> <span class="keyword">const</span> VectorXd& primal_solution,</div>
|
||
<div class="line"><a id="l00217" name="l00217"></a><span class="lineno"> 217</span> <span class="keyword">const</span> VectorXd& objective_product) {</div>
|
||
<div class="line"><a id="l00218" name="l00218"></a><span class="lineno"> 218</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(primal_solution.size(), sharded_qp.PrimalSize());</div>
|
||
<div class="line"><a id="l00219" name="l00219"></a><span class="lineno"> 219</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(objective_product.size(), sharded_qp.PrimalSize());</div>
|
||
<div class="line"><a id="l00220" name="l00220"></a><span class="lineno"> 220</span> <span class="keywordflow">return</span> 0.5 *</div>
|
||
<div class="line"><a id="l00221" name="l00221"></a><span class="lineno"> 221</span> <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a11831586b99d28a708bc103bce1a945e">Dot</a>(objective_product, primal_solution, sharded_qp.PrimalSharder());</div>
|
||
<div class="line"><a id="l00222" name="l00222"></a><span class="lineno"> 222</span>}</div>
|
||
<div class="line"><a id="l00223" name="l00223"></a><span class="lineno"> 223</span> </div>
|
||
<div class="line"><a id="l00224" name="l00224"></a><span class="lineno"> 224</span><span class="comment">// Returns objective_product + c − A^T y when use_zero_primal_objective =</span></div>
|
||
<div class="line"><a id="l00225" name="l00225"></a><span class="lineno"> 225</span><span class="comment">// false, and returns − A^T y when use_zero_primal_objective = true.</span></div>
|
||
<div class="line"><a id="l00226" name="l00226"></a><span class="lineno"> 226</span><span class="comment">// objective_product is passed by copy, and modified in place.</span></div>
|
||
<div class="line"><a id="l00227" name="l00227"></a><span class="lineno"> 227</span>VectorXd PrimalGradientFromObjectiveProduct(</div>
|
||
<div class="line"><a id="l00228" name="l00228"></a><span class="lineno"> 228</span> <span class="keyword">const</span> ShardedQuadraticProgram& sharded_qp, <span class="keyword">const</span> VectorXd& dual_solution,</div>
|
||
<div class="line"><a id="l00229" name="l00229"></a><span class="lineno"> 229</span> VectorXd objective_product, <span class="keywordtype">bool</span> use_zero_primal_objective = <span class="keyword">false</span>) {</div>
|
||
<div class="line"><a id="l00230" name="l00230"></a><span class="lineno"> 230</span> <span class="keyword">const</span> QuadraticProgram& qp = sharded_qp.Qp();</div>
|
||
<div class="line"><a id="l00231" name="l00231"></a><span class="lineno"> 231</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(dual_solution.size(), sharded_qp.DualSize());</div>
|
||
<div class="line"><a id="l00232" name="l00232"></a><span class="lineno"> 232</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(objective_product.size(), sharded_qp.PrimalSize());</div>
|
||
<div class="line"><a id="l00233" name="l00233"></a><span class="lineno"> 233</span> </div>
|
||
<div class="line"><a id="l00234" name="l00234"></a><span class="lineno"> 234</span> <span class="comment">// Note that this modifies objective_product, replacing its entries with</span></div>
|
||
<div class="line"><a id="l00235" name="l00235"></a><span class="lineno"> 235</span> <span class="comment">// the primal gradient.</span></div>
|
||
<div class="line"><a id="l00236" name="l00236"></a><span class="lineno"> 236</span> sharded_qp.ConstraintMatrixSharder().ParallelForEachShard(</div>
|
||
<div class="line"><a id="l00237" name="l00237"></a><span class="lineno"> 237</span> [&](<span class="keyword">const</span> Sharder::Shard& shard) {</div>
|
||
<div class="line"><a id="l00238" name="l00238"></a><span class="lineno"> 238</span> <span class="keywordflow">if</span> (use_zero_primal_objective) {</div>
|
||
<div class="line"><a id="l00239" name="l00239"></a><span class="lineno"> 239</span> shard(objective_product) =</div>
|
||
<div class="line"><a id="l00240" name="l00240"></a><span class="lineno"> 240</span> -shard(qp.constraint_matrix).transpose() * dual_solution;</div>
|
||
<div class="line"><a id="l00241" name="l00241"></a><span class="lineno"> 241</span> } <span class="keywordflow">else</span> {</div>
|
||
<div class="line"><a id="l00242" name="l00242"></a><span class="lineno"> 242</span> shard(objective_product) +=</div>
|
||
<div class="line"><a id="l00243" name="l00243"></a><span class="lineno"> 243</span> shard(qp.objective_vector) -</div>
|
||
<div class="line"><a id="l00244" name="l00244"></a><span class="lineno"> 244</span> shard(qp.constraint_matrix).transpose() * dual_solution;</div>
|
||
<div class="line"><a id="l00245" name="l00245"></a><span class="lineno"> 245</span> }</div>
|
||
<div class="line"><a id="l00246" name="l00246"></a><span class="lineno"> 246</span> });</div>
|
||
<div class="line"><a id="l00247" name="l00247"></a><span class="lineno"> 247</span> <span class="keywordflow">return</span> objective_product;</div>
|
||
<div class="line"><a id="l00248" name="l00248"></a><span class="lineno"> 248</span>}</div>
|
||
<div class="line"><a id="l00249" name="l00249"></a><span class="lineno"> 249</span> </div>
|
||
<div class="line"><a id="l00250" name="l00250"></a><span class="lineno"> 250</span><span class="comment">// Returns the value of y term in the objective of the dual problem, see</span></div>
|
||
<div class="line"><a id="l00251" name="l00251"></a><span class="lineno"> 251</span><span class="comment">// (l^c)^T[y]_+ − (u^c)^T[y]_− in the dual objective from</span></div>
|
||
<div class="line"><a id="l00252" name="l00252"></a><span class="lineno"> 252</span><span class="comment">// https://developers.google.com/optimization/lp/pdlp_math.</span></div>
|
||
<div class="line"><a id="l00253" name="l00253"></a><span class="lineno"> 253</span><span class="keywordtype">double</span> DualObjectiveBoundsTerm(<span class="keyword">const</span> ShardedQuadraticProgram& sharded_qp,</div>
|
||
<div class="line"><a id="l00254" name="l00254"></a><span class="lineno"> 254</span> <span class="keyword">const</span> VectorXd& dual_solution) {</div>
|
||
<div class="line"><a id="l00255" name="l00255"></a><span class="lineno"> 255</span> <span class="keyword">const</span> QuadraticProgram& qp = sharded_qp.Qp();</div>
|
||
<div class="line"><a id="l00256" name="l00256"></a><span class="lineno"> 256</span> <span class="keywordflow">return</span> sharded_qp.DualSharder().ParallelSumOverShards(</div>
|
||
<div class="line"><a id="l00257" name="l00257"></a><span class="lineno"> 257</span> [&](<span class="keyword">const</span> Sharder::Shard& shard) {</div>
|
||
<div class="line"><a id="l00258" name="l00258"></a><span class="lineno"> 258</span> <span class="comment">// This assumes that the dual variables are feasible, that is, that</span></div>
|
||
<div class="line"><a id="l00259" name="l00259"></a><span class="lineno"> 259</span> <span class="comment">// the term corresponding to the "y" variables in the dual objective</span></div>
|
||
<div class="line"><a id="l00260" name="l00260"></a><span class="lineno"> 260</span> <span class="comment">// in https://developers.google.com/optimization/lp/pdlp_math is finite.</span></div>
|
||
<div class="line"><a id="l00261" name="l00261"></a><span class="lineno"> 261</span> <span class="keyword">const</span> <span class="keyword">auto</span> lower_bound_shard = shard(qp.constraint_lower_bounds);</div>
|
||
<div class="line"><a id="l00262" name="l00262"></a><span class="lineno"> 262</span> <span class="keyword">const</span> <span class="keyword">auto</span> upper_bound_shard = shard(qp.constraint_upper_bounds);</div>
|
||
<div class="line"><a id="l00263" name="l00263"></a><span class="lineno"> 263</span> <span class="keyword">const</span> <span class="keyword">auto</span> dual_shard = shard(dual_solution);</div>
|
||
<div class="line"><a id="l00264" name="l00264"></a><span class="lineno"> 264</span> <span class="comment">// Can't use .dot(.cwiseMin()) because that gives 0 * inf = NaN.</span></div>
|
||
<div class="line"><a id="l00265" name="l00265"></a><span class="lineno"> 265</span> <span class="keywordtype">double</span> sum = 0.0;</div>
|
||
<div class="line"><a id="l00266" name="l00266"></a><span class="lineno"> 266</span> <span class="keywordflow">for</span> (int64_t i = 0; i < dual_shard.size(); ++i) {</div>
|
||
<div class="line"><a id="l00267" name="l00267"></a><span class="lineno"> 267</span> <span class="keywordflow">if</span> (dual_shard[i] > 0.0) {</div>
|
||
<div class="line"><a id="l00268" name="l00268"></a><span class="lineno"> 268</span> sum += lower_bound_shard[i] * dual_shard[i];</div>
|
||
<div class="line"><a id="l00269" name="l00269"></a><span class="lineno"> 269</span> } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (dual_shard[i] < 0.0) {</div>
|
||
<div class="line"><a id="l00270" name="l00270"></a><span class="lineno"> 270</span> sum += upper_bound_shard[i] * dual_shard[i];</div>
|
||
<div class="line"><a id="l00271" name="l00271"></a><span class="lineno"> 271</span> }</div>
|
||
<div class="line"><a id="l00272" name="l00272"></a><span class="lineno"> 272</span> }</div>
|
||
<div class="line"><a id="l00273" name="l00273"></a><span class="lineno"> 273</span> <span class="keywordflow">return</span> sum;</div>
|
||
<div class="line"><a id="l00274" name="l00274"></a><span class="lineno"> 274</span> });</div>
|
||
<div class="line"><a id="l00275" name="l00275"></a><span class="lineno"> 275</span>}</div>
|
||
<div class="line"><a id="l00276" name="l00276"></a><span class="lineno"> 276</span> </div>
|
||
<div class="line"><a id="l00277" name="l00277"></a><span class="lineno"> 277</span><span class="comment">// Computes the projection of the vector onto a pseudo-random vector determined</span></div>
|
||
<div class="line"><a id="l00278" name="l00278"></a><span class="lineno"> 278</span><span class="comment">// by seed_generator. seed_generator is used as the source of a random seed for</span></div>
|
||
<div class="line"><a id="l00279" name="l00279"></a><span class="lineno"> 279</span><span class="comment">// each shard's portion of the vector.</span></div>
|
||
<div class="line"><a id="l00280" name="l00280"></a><span class="lineno"> 280</span><span class="keywordtype">double</span> RandomProjection(<span class="keyword">const</span> VectorXd& vector, <span class="keyword">const</span> Sharder& sharder,</div>
|
||
<div class="line"><a id="l00281" name="l00281"></a><span class="lineno"> 281</span> std::mt19937& seed_generator) {</div>
|
||
<div class="line"><a id="l00282" name="l00282"></a><span class="lineno"> 282</span> std::vector<std::mt19937> shard_seeds;</div>
|
||
<div class="line"><a id="l00283" name="l00283"></a><span class="lineno"> 283</span> shard_seeds.reserve(sharder.NumShards());</div>
|
||
<div class="line"><a id="l00284" name="l00284"></a><span class="lineno"> 284</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> shard = 0; shard < sharder.NumShards(); ++shard) {</div>
|
||
<div class="line"><a id="l00285" name="l00285"></a><span class="lineno"> 285</span> shard_seeds.emplace_back((seed_generator)());</div>
|
||
<div class="line"><a id="l00286" name="l00286"></a><span class="lineno"> 286</span> }</div>
|
||
<div class="line"><a id="l00287" name="l00287"></a><span class="lineno"> 287</span> <span class="comment">// Computes vector * gaussian_random_vector and</span></div>
|
||
<div class="line"><a id="l00288" name="l00288"></a><span class="lineno"> 288</span> <span class="comment">// ||gaussian_random_vector||^2 to normalize by afterwards.</span></div>
|
||
<div class="line"><a id="l00289" name="l00289"></a><span class="lineno"> 289</span> VectorXd dot_product(sharder.NumShards());</div>
|
||
<div class="line"><a id="l00290" name="l00290"></a><span class="lineno"> 290</span> VectorXd gaussian_norm_squared(sharder.NumShards());</div>
|
||
<div class="line"><a id="l00291" name="l00291"></a><span class="lineno"> 291</span> sharder.ParallelForEachShard([&](<span class="keyword">const</span> Sharder::Shard& shard) {</div>
|
||
<div class="line"><a id="l00292" name="l00292"></a><span class="lineno"> 292</span> <span class="keyword">const</span> <span class="keyword">auto</span> vector_shard = shard(vector);</div>
|
||
<div class="line"><a id="l00293" name="l00293"></a><span class="lineno"> 293</span> <span class="keywordtype">double</span> shard_dot_product = 0.0;</div>
|
||
<div class="line"><a id="l00294" name="l00294"></a><span class="lineno"> 294</span> <span class="keywordtype">double</span> shard_norm_squared = 0.0;</div>
|
||
<div class="line"><a id="l00295" name="l00295"></a><span class="lineno"> 295</span> std::mt19937 random{shard_seeds[shard.Index()]};</div>
|
||
<div class="line"><a id="l00296" name="l00296"></a><span class="lineno"> 296</span> <span class="keywordflow">for</span> (int64_t i = 0; i < vector_shard.size(); ++i) {</div>
|
||
<div class="line"><a id="l00297" name="l00297"></a><span class="lineno"> 297</span> <span class="keyword">const</span> <span class="keywordtype">double</span> projection_element = absl::Gaussian(random, 0.0, 1.0);</div>
|
||
<div class="line"><a id="l00298" name="l00298"></a><span class="lineno"> 298</span> shard_dot_product += projection_element * vector_shard[i];</div>
|
||
<div class="line"><a id="l00299" name="l00299"></a><span class="lineno"> 299</span> shard_norm_squared += <a class="code hl_function" href="classoperations__research_1_1_math_util.html#aac72849250cdf23aefdd991eb0fc0385">MathUtil::Square</a>(projection_element);</div>
|
||
<div class="line"><a id="l00300" name="l00300"></a><span class="lineno"> 300</span> }</div>
|
||
<div class="line"><a id="l00301" name="l00301"></a><span class="lineno"> 301</span> dot_product[shard.Index()] = shard_dot_product;</div>
|
||
<div class="line"><a id="l00302" name="l00302"></a><span class="lineno"> 302</span> gaussian_norm_squared[shard.Index()] = shard_norm_squared;</div>
|
||
<div class="line"><a id="l00303" name="l00303"></a><span class="lineno"> 303</span> });</div>
|
||
<div class="line"><a id="l00304" name="l00304"></a><span class="lineno"> 304</span> <span class="keywordflow">return</span> dot_product.sum() / std::sqrt(gaussian_norm_squared.sum());</div>
|
||
<div class="line"><a id="l00305" name="l00305"></a><span class="lineno"> 305</span>}</div>
|
||
<div class="line"><a id="l00306" name="l00306"></a><span class="lineno"> 306</span>} <span class="comment">// namespace</span></div>
|
||
<div class="line"><a id="l00307" name="l00307"></a><span class="lineno"> 307</span> </div>
|
||
<div class="line"><a id="l00308" name="l00308"></a><span class="lineno"><a class="line" href="namespaceoperations__research_1_1pdlp.html#ac77694ebaac0adfa0fce8422782c48c8"> 308</a></span>ConvergenceInformation <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#ac77694ebaac0adfa0fce8422782c48c8">ComputeConvergenceInformation</a>(</div>
|
||
<div class="line"><a id="l00309" name="l00309"></a><span class="lineno"> 309</span> <span class="keyword">const</span> <a class="code hl_class" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html">ShardedQuadraticProgram</a>& scaled_sharded_qp,</div>
|
||
<div class="line"><a id="l00310" name="l00310"></a><span class="lineno"> 310</span> <span class="keyword">const</span> Eigen::VectorXd& col_scaling_vec,</div>
|
||
<div class="line"><a id="l00311" name="l00311"></a><span class="lineno"> 311</span> <span class="keyword">const</span> Eigen::VectorXd& row_scaling_vec,</div>
|
||
<div class="line"><a id="l00312" name="l00312"></a><span class="lineno"> 312</span> <span class="keyword">const</span> Eigen::VectorXd& scaled_primal_solution,</div>
|
||
<div class="line"><a id="l00313" name="l00313"></a><span class="lineno"> 313</span> <span class="keyword">const</span> Eigen::VectorXd& scaled_dual_solution, PointType candidate_type) {</div>
|
||
<div class="line"><a id="l00314" name="l00314"></a><span class="lineno"> 314</span> <span class="keyword">const</span> <a class="code hl_struct" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html">QuadraticProgram</a>& qp = scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#abfdc79e4b2325ff283b7d2333d40fffe">Qp</a>();</div>
|
||
<div class="line"><a id="l00315" name="l00315"></a><span class="lineno"> 315</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(col_scaling_vec.size(), scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab945b88f1937277a896d4c7c7935d605">PrimalSize</a>());</div>
|
||
<div class="line"><a id="l00316" name="l00316"></a><span class="lineno"> 316</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(row_scaling_vec.size(), scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#afcafa95b1a351212291c7a030deec52a">DualSize</a>());</div>
|
||
<div class="line"><a id="l00317" name="l00317"></a><span class="lineno"> 317</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(scaled_primal_solution.size(), scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab945b88f1937277a896d4c7c7935d605">PrimalSize</a>());</div>
|
||
<div class="line"><a id="l00318" name="l00318"></a><span class="lineno"> 318</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(scaled_dual_solution.size(), scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#afcafa95b1a351212291c7a030deec52a">DualSize</a>());</div>
|
||
<div class="line"><a id="l00319" name="l00319"></a><span class="lineno"> 319</span> </div>
|
||
<div class="line"><a id="l00320" name="l00320"></a><span class="lineno"> 320</span> <span class="comment">// See https://developers.google.com/optimization/lp/pdlp_math#rescaling for</span></div>
|
||
<div class="line"><a id="l00321" name="l00321"></a><span class="lineno"> 321</span> <span class="comment">// notes describing the connection between the scaled and unscaled problem.</span></div>
|
||
<div class="line"><a id="l00322" name="l00322"></a><span class="lineno"> 322</span> </div>
|
||
<div class="line"><a id="l00323" name="l00323"></a><span class="lineno"> 323</span> ConvergenceInformation result;</div>
|
||
<div class="line"><a id="l00324" name="l00324"></a><span class="lineno"> 324</span> ResidualNorms primal_residuals = PrimalResidualNorms(</div>
|
||
<div class="line"><a id="l00325" name="l00325"></a><span class="lineno"> 325</span> scaled_sharded_qp, row_scaling_vec, scaled_primal_solution);</div>
|
||
<div class="line"><a id="l00326" name="l00326"></a><span class="lineno"> 326</span> result.set_l_inf_primal_residual(primal_residuals.l_inf_residual);</div>
|
||
<div class="line"><a id="l00327" name="l00327"></a><span class="lineno"> 327</span> result.set_l2_primal_residual(primal_residuals.l_2_residual);</div>
|
||
<div class="line"><a id="l00328" name="l00328"></a><span class="lineno"> 328</span> </div>
|
||
<div class="line"><a id="l00329" name="l00329"></a><span class="lineno"> 329</span> result.set_l_inf_primal_variable(</div>
|
||
<div class="line"><a id="l00330" name="l00330"></a><span class="lineno"> 330</span> <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a55b8c43a5adfafddb030074c75aeef70">ScaledLInfNorm</a>(scaled_primal_solution, col_scaling_vec,</div>
|
||
<div class="line"><a id="l00331" name="l00331"></a><span class="lineno"> 331</span> scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">PrimalSharder</a>()));</div>
|
||
<div class="line"><a id="l00332" name="l00332"></a><span class="lineno"> 332</span> result.set_l2_primal_variable(<a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a0b812156619599417e29521a41b7a734">ScaledNorm</a>(scaled_primal_solution,</div>
|
||
<div class="line"><a id="l00333" name="l00333"></a><span class="lineno"> 333</span> col_scaling_vec,</div>
|
||
<div class="line"><a id="l00334" name="l00334"></a><span class="lineno"> 334</span> scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">PrimalSharder</a>()));</div>
|
||
<div class="line"><a id="l00335" name="l00335"></a><span class="lineno"> 335</span> result.set_l_inf_dual_variable(<a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a55b8c43a5adfafddb030074c75aeef70">ScaledLInfNorm</a>(</div>
|
||
<div class="line"><a id="l00336" name="l00336"></a><span class="lineno"> 336</span> scaled_dual_solution, row_scaling_vec, scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#a101ca40b60dd25bbf6271bef1370e8d1">DualSharder</a>()));</div>
|
||
<div class="line"><a id="l00337" name="l00337"></a><span class="lineno"> 337</span> result.set_l2_dual_variable(<a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a0b812156619599417e29521a41b7a734">ScaledNorm</a>(scaled_dual_solution, row_scaling_vec,</div>
|
||
<div class="line"><a id="l00338" name="l00338"></a><span class="lineno"> 338</span> scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#a101ca40b60dd25bbf6271bef1370e8d1">DualSharder</a>()));</div>
|
||
<div class="line"><a id="l00339" name="l00339"></a><span class="lineno"> 339</span> </div>
|
||
<div class="line"><a id="l00340" name="l00340"></a><span class="lineno"> 340</span> VectorXd scaled_objective_product =</div>
|
||
<div class="line"><a id="l00341" name="l00341"></a><span class="lineno"> 341</span> ObjectiveProduct(scaled_sharded_qp, scaled_primal_solution);</div>
|
||
<div class="line"><a id="l00342" name="l00342"></a><span class="lineno"> 342</span> <span class="keyword">const</span> <span class="keywordtype">double</span> quadratic_objective = QuadraticObjective(</div>
|
||
<div class="line"><a id="l00343" name="l00343"></a><span class="lineno"> 343</span> scaled_sharded_qp, scaled_primal_solution, scaled_objective_product);</div>
|
||
<div class="line"><a id="l00344" name="l00344"></a><span class="lineno"> 344</span> VectorXd scaled_primal_gradient = PrimalGradientFromObjectiveProduct(</div>
|
||
<div class="line"><a id="l00345" name="l00345"></a><span class="lineno"> 345</span> scaled_sharded_qp, scaled_dual_solution,</div>
|
||
<div class="line"><a id="l00346" name="l00346"></a><span class="lineno"> 346</span> std::move(scaled_objective_product));</div>
|
||
<div class="line"><a id="l00347" name="l00347"></a><span class="lineno"> 347</span> result.set_primal_objective(qp.<a class="code hl_function" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html#a2d3828418aef02f4f8897c2d3db75b2f">ApplyObjectiveScalingAndOffset</a>(</div>
|
||
<div class="line"><a id="l00348" name="l00348"></a><span class="lineno"> 348</span> quadratic_objective + <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a11831586b99d28a708bc103bce1a945e">Dot</a>(qp.<a class="code hl_variable" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html#afdb3e07cd380793e1b265c1fded94edd">objective_vector</a>, scaled_primal_solution,</div>
|
||
<div class="line"><a id="l00349" name="l00349"></a><span class="lineno"> 349</span> scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">PrimalSharder</a>())));</div>
|
||
<div class="line"><a id="l00350" name="l00350"></a><span class="lineno"> 350</span> </div>
|
||
<div class="line"><a id="l00351" name="l00351"></a><span class="lineno"> 351</span> <span class="comment">// This is the dual objective from</span></div>
|
||
<div class="line"><a id="l00352" name="l00352"></a><span class="lineno"> 352</span> <span class="comment">// https://developers.google.com/optimization/lp/pdlp_math minus the last term</span></div>
|
||
<div class="line"><a id="l00353" name="l00353"></a><span class="lineno"> 353</span> <span class="comment">// (involving r). All scaling terms cancel out.</span></div>
|
||
<div class="line"><a id="l00354" name="l00354"></a><span class="lineno"> 354</span> <span class="keyword">const</span> <span class="keywordtype">double</span> dual_objective_piece =</div>
|
||
<div class="line"><a id="l00355" name="l00355"></a><span class="lineno"> 355</span> -quadratic_objective +</div>
|
||
<div class="line"><a id="l00356" name="l00356"></a><span class="lineno"> 356</span> DualObjectiveBoundsTerm(scaled_sharded_qp, scaled_dual_solution);</div>
|
||
<div class="line"><a id="l00357" name="l00357"></a><span class="lineno"> 357</span> </div>
|
||
<div class="line"><a id="l00358" name="l00358"></a><span class="lineno"> 358</span> ResidualNorms dual_residuals =</div>
|
||
<div class="line"><a id="l00359" name="l00359"></a><span class="lineno"> 359</span> DualResidualNorms(scaled_sharded_qp, col_scaling_vec,</div>
|
||
<div class="line"><a id="l00360" name="l00360"></a><span class="lineno"> 360</span> scaled_primal_solution, scaled_primal_gradient);</div>
|
||
<div class="line"><a id="l00361" name="l00361"></a><span class="lineno"> 361</span> result.set_dual_objective(qp.<a class="code hl_function" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html#a2d3828418aef02f4f8897c2d3db75b2f">ApplyObjectiveScalingAndOffset</a>(</div>
|
||
<div class="line"><a id="l00362" name="l00362"></a><span class="lineno"> 362</span> dual_objective_piece + dual_residuals.objective_correction));</div>
|
||
<div class="line"><a id="l00363" name="l00363"></a><span class="lineno"> 363</span> result.set_corrected_dual_objective(qp.<a class="code hl_function" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html#a2d3828418aef02f4f8897c2d3db75b2f">ApplyObjectiveScalingAndOffset</a>(</div>
|
||
<div class="line"><a id="l00364" name="l00364"></a><span class="lineno"> 364</span> dual_objective_piece + dual_residuals.objective_full_correction));</div>
|
||
<div class="line"><a id="l00365" name="l00365"></a><span class="lineno"> 365</span> result.set_l_inf_dual_residual(dual_residuals.l_inf_residual);</div>
|
||
<div class="line"><a id="l00366" name="l00366"></a><span class="lineno"> 366</span> result.set_l2_dual_residual(dual_residuals.l_2_residual);</div>
|
||
<div class="line"><a id="l00367" name="l00367"></a><span class="lineno"> 367</span> </div>
|
||
<div class="line"><a id="l00368" name="l00368"></a><span class="lineno"> 368</span> result.set_candidate_type(candidate_type);</div>
|
||
<div class="line"><a id="l00369" name="l00369"></a><span class="lineno"> 369</span> <span class="keywordflow">return</span> result;</div>
|
||
<div class="line"><a id="l00370" name="l00370"></a><span class="lineno"> 370</span>}</div>
|
||
<div class="line"><a id="l00371" name="l00371"></a><span class="lineno"> 371</span> </div>
|
||
<div class="line"><a id="l00372" name="l00372"></a><span class="lineno"><a class="line" href="namespaceoperations__research_1_1pdlp.html#a74af5ceb7b6e37fbfca92e2c59b99e3e"> 372</a></span>InfeasibilityInformation <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a74af5ceb7b6e37fbfca92e2c59b99e3e">ComputeInfeasibilityInformation</a>(</div>
|
||
<div class="line"><a id="l00373" name="l00373"></a><span class="lineno"> 373</span> <span class="keyword">const</span> <a class="code hl_class" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html">ShardedQuadraticProgram</a>& scaled_sharded_qp,</div>
|
||
<div class="line"><a id="l00374" name="l00374"></a><span class="lineno"> 374</span> <span class="keyword">const</span> Eigen::VectorXd& col_scaling_vec,</div>
|
||
<div class="line"><a id="l00375" name="l00375"></a><span class="lineno"> 375</span> <span class="keyword">const</span> Eigen::VectorXd& row_scaling_vec,</div>
|
||
<div class="line"><a id="l00376" name="l00376"></a><span class="lineno"> 376</span> <span class="keyword">const</span> Eigen::VectorXd& scaled_primal_ray,</div>
|
||
<div class="line"><a id="l00377" name="l00377"></a><span class="lineno"> 377</span> <span class="keyword">const</span> Eigen::VectorXd& scaled_dual_ray, PointType candidate_type) {</div>
|
||
<div class="line"><a id="l00378" name="l00378"></a><span class="lineno"> 378</span> <span class="keyword">const</span> <a class="code hl_struct" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html">QuadraticProgram</a>& qp = scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#abfdc79e4b2325ff283b7d2333d40fffe">Qp</a>();</div>
|
||
<div class="line"><a id="l00379" name="l00379"></a><span class="lineno"> 379</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(col_scaling_vec.size(), scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab945b88f1937277a896d4c7c7935d605">PrimalSize</a>());</div>
|
||
<div class="line"><a id="l00380" name="l00380"></a><span class="lineno"> 380</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(row_scaling_vec.size(), scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#afcafa95b1a351212291c7a030deec52a">DualSize</a>());</div>
|
||
<div class="line"><a id="l00381" name="l00381"></a><span class="lineno"> 381</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(scaled_primal_ray.size(), scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab945b88f1937277a896d4c7c7935d605">PrimalSize</a>());</div>
|
||
<div class="line"><a id="l00382" name="l00382"></a><span class="lineno"> 382</span> <a class="code hl_define" href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a>(scaled_dual_ray.size(), scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#afcafa95b1a351212291c7a030deec52a">DualSize</a>());</div>
|
||
<div class="line"><a id="l00383" name="l00383"></a><span class="lineno"> 383</span> </div>
|
||
<div class="line"><a id="l00384" name="l00384"></a><span class="lineno"> 384</span> <span class="keywordtype">double</span> l_inf_primal = <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a55b8c43a5adfafddb030074c75aeef70">ScaledLInfNorm</a>(scaled_primal_ray, col_scaling_vec,</div>
|
||
<div class="line"><a id="l00385" name="l00385"></a><span class="lineno"> 385</span> scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">PrimalSharder</a>());</div>
|
||
<div class="line"><a id="l00386" name="l00386"></a><span class="lineno"> 386</span> <span class="keywordtype">double</span> l_inf_dual = <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a55b8c43a5adfafddb030074c75aeef70">ScaledLInfNorm</a>(scaled_dual_ray, row_scaling_vec,</div>
|
||
<div class="line"><a id="l00387" name="l00387"></a><span class="lineno"> 387</span> scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#a101ca40b60dd25bbf6271bef1370e8d1">DualSharder</a>());</div>
|
||
<div class="line"><a id="l00388" name="l00388"></a><span class="lineno"> 388</span> InfeasibilityInformation result;</div>
|
||
<div class="line"><a id="l00389" name="l00389"></a><span class="lineno"> 389</span> <span class="comment">// Compute primal infeasibility information.</span></div>
|
||
<div class="line"><a id="l00390" name="l00390"></a><span class="lineno"> 390</span> VectorXd scaled_primal_gradient = PrimalGradientFromObjectiveProduct(</div>
|
||
<div class="line"><a id="l00391" name="l00391"></a><span class="lineno"> 391</span> scaled_sharded_qp, scaled_dual_ray,</div>
|
||
<div class="line"><a id="l00392" name="l00392"></a><span class="lineno"> 392</span> <a class="code hl_function" href="namespaceoperations__research.html#a5a9881f8a07b166ef2cbde572cea27b6">VectorXd::Zero</a>(scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab945b88f1937277a896d4c7c7935d605">PrimalSize</a>()),</div>
|
||
<div class="line"><a id="l00393" name="l00393"></a><span class="lineno"> 393</span> <span class="comment">/*use_zero_primal_objective=*/</span><span class="keyword">true</span>);</div>
|
||
<div class="line"><a id="l00394" name="l00394"></a><span class="lineno"> 394</span> ResidualNorms dual_residuals =</div>
|
||
<div class="line"><a id="l00395" name="l00395"></a><span class="lineno"> 395</span> DualResidualNorms(scaled_sharded_qp, col_scaling_vec, scaled_primal_ray,</div>
|
||
<div class="line"><a id="l00396" name="l00396"></a><span class="lineno"> 396</span> scaled_primal_gradient);</div>
|
||
<div class="line"><a id="l00397" name="l00397"></a><span class="lineno"> 397</span> </div>
|
||
<div class="line"><a id="l00398" name="l00398"></a><span class="lineno"> 398</span> <span class="keywordtype">double</span> dual_ray_objective =</div>
|
||
<div class="line"><a id="l00399" name="l00399"></a><span class="lineno"> 399</span> DualObjectiveBoundsTerm(scaled_sharded_qp, scaled_dual_ray) +</div>
|
||
<div class="line"><a id="l00400" name="l00400"></a><span class="lineno"> 400</span> dual_residuals.objective_correction;</div>
|
||
<div class="line"><a id="l00401" name="l00401"></a><span class="lineno"> 401</span> <span class="keywordflow">if</span> (l_inf_dual > 0) {</div>
|
||
<div class="line"><a id="l00402" name="l00402"></a><span class="lineno"> 402</span> result.set_dual_ray_objective(dual_ray_objective / l_inf_dual);</div>
|
||
<div class="line"><a id="l00403" name="l00403"></a><span class="lineno"> 403</span> result.set_max_dual_ray_infeasibility(dual_residuals.l_inf_residual /</div>
|
||
<div class="line"><a id="l00404" name="l00404"></a><span class="lineno"> 404</span> l_inf_dual);</div>
|
||
<div class="line"><a id="l00405" name="l00405"></a><span class="lineno"> 405</span> } <span class="keywordflow">else</span> {</div>
|
||
<div class="line"><a id="l00406" name="l00406"></a><span class="lineno"> 406</span> result.set_dual_ray_objective(0.0);</div>
|
||
<div class="line"><a id="l00407" name="l00407"></a><span class="lineno"> 407</span> result.set_max_dual_ray_infeasibility(0.0);</div>
|
||
<div class="line"><a id="l00408" name="l00408"></a><span class="lineno"> 408</span> }</div>
|
||
<div class="line"><a id="l00409" name="l00409"></a><span class="lineno"> 409</span> </div>
|
||
<div class="line"><a id="l00410" name="l00410"></a><span class="lineno"> 410</span> <span class="comment">// Compute dual infeasibility information.</span></div>
|
||
<div class="line"><a id="l00411" name="l00411"></a><span class="lineno"> 411</span> ResidualNorms primal_residuals =</div>
|
||
<div class="line"><a id="l00412" name="l00412"></a><span class="lineno"> 412</span> PrimalResidualNorms(scaled_sharded_qp, row_scaling_vec, scaled_primal_ray,</div>
|
||
<div class="line"><a id="l00413" name="l00413"></a><span class="lineno"> 413</span> <span class="comment">/*use_homogeneous_constraint_bounds=*/</span><span class="keyword">true</span>);</div>
|
||
<div class="line"><a id="l00414" name="l00414"></a><span class="lineno"> 414</span> <span class="comment">// primal_residuals contains the violations of the linear constraints. The</span></div>
|
||
<div class="line"><a id="l00415" name="l00415"></a><span class="lineno"> 415</span> <span class="comment">// signs of the components are also constrained by the presence or absence</span></div>
|
||
<div class="line"><a id="l00416" name="l00416"></a><span class="lineno"> 416</span> <span class="comment">// of variable bounds.</span></div>
|
||
<div class="line"><a id="l00417" name="l00417"></a><span class="lineno"> 417</span> VectorXd primal_ray_local_sign_max_violation(</div>
|
||
<div class="line"><a id="l00418" name="l00418"></a><span class="lineno"> 418</span> scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">PrimalSharder</a>().<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharder.html#aa6c18d04d5fcbe7a9343768b8b66be7f">NumShards</a>());</div>
|
||
<div class="line"><a id="l00419" name="l00419"></a><span class="lineno"> 419</span> scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">PrimalSharder</a>().<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharder.html#a5bbfc4ed3da7a0815ba5f6c7ddee320b">ParallelForEachShard</a>(</div>
|
||
<div class="line"><a id="l00420" name="l00420"></a><span class="lineno"> 420</span> [&](<span class="keyword">const</span> <a class="code hl_class" href="classoperations__research_1_1pdlp_1_1_sharder_1_1_shard.html">Sharder::Shard</a>& shard) {</div>
|
||
<div class="line"><a id="l00421" name="l00421"></a><span class="lineno"> 421</span> <span class="keyword">const</span> <span class="keyword">auto</span> lower_bound_shard =</div>
|
||
<div class="line"><a id="l00422" name="l00422"></a><span class="lineno"> 422</span> shard(scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#abfdc79e4b2325ff283b7d2333d40fffe">Qp</a>().<a class="code hl_variable" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html#a0f72e7b49f91d0b980f5a54a18c06964">variable_lower_bounds</a>);</div>
|
||
<div class="line"><a id="l00423" name="l00423"></a><span class="lineno"> 423</span> <span class="keyword">const</span> <span class="keyword">auto</span> upper_bound_shard =</div>
|
||
<div class="line"><a id="l00424" name="l00424"></a><span class="lineno"> 424</span> shard(scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#abfdc79e4b2325ff283b7d2333d40fffe">Qp</a>().<a class="code hl_variable" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html#a097d329b7af662bea9b5a8e310a22726">variable_upper_bounds</a>);</div>
|
||
<div class="line"><a id="l00425" name="l00425"></a><span class="lineno"> 425</span> <span class="keyword">const</span> <span class="keyword">auto</span> ray_shard = shard(scaled_primal_ray);</div>
|
||
<div class="line"><a id="l00426" name="l00426"></a><span class="lineno"> 426</span> <span class="keyword">const</span> <span class="keyword">auto</span> scale_shard = shard(col_scaling_vec);</div>
|
||
<div class="line"><a id="l00427" name="l00427"></a><span class="lineno"> 427</span> <span class="keywordtype">double</span> local_max = 0.0;</div>
|
||
<div class="line"><a id="l00428" name="l00428"></a><span class="lineno"> 428</span> <span class="keywordflow">for</span> (int64_t i = 0; i < ray_shard.size(); ++i) {</div>
|
||
<div class="line"><a id="l00429" name="l00429"></a><span class="lineno"> 429</span> <span class="keywordflow">if</span> (std::isfinite(lower_bound_shard[i])) {</div>
|
||
<div class="line"><a id="l00430" name="l00430"></a><span class="lineno"> 430</span> local_max = <a class="code hl_variable" href="alldiff__cst_8cc.html#a26e6db9bcc64b584051ecc28171ed11f">std::max</a>(local_max, -ray_shard[i] * scale_shard[i]);</div>
|
||
<div class="line"><a id="l00431" name="l00431"></a><span class="lineno"> 431</span> }</div>
|
||
<div class="line"><a id="l00432" name="l00432"></a><span class="lineno"> 432</span> <span class="keywordflow">if</span> (std::isfinite(upper_bound_shard[i])) {</div>
|
||
<div class="line"><a id="l00433" name="l00433"></a><span class="lineno"> 433</span> local_max = <a class="code hl_variable" href="alldiff__cst_8cc.html#a26e6db9bcc64b584051ecc28171ed11f">std::max</a>(local_max, ray_shard[i] * scale_shard[i]);</div>
|
||
<div class="line"><a id="l00434" name="l00434"></a><span class="lineno"> 434</span> }</div>
|
||
<div class="line"><a id="l00435" name="l00435"></a><span class="lineno"> 435</span> }</div>
|
||
<div class="line"><a id="l00436" name="l00436"></a><span class="lineno"> 436</span> primal_ray_local_sign_max_violation[shard.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharder_1_1_shard.html#a8ef12397d1682615bc3108c397734179">Index</a>()] = local_max;</div>
|
||
<div class="line"><a id="l00437" name="l00437"></a><span class="lineno"> 437</span> });</div>
|
||
<div class="line"><a id="l00438" name="l00438"></a><span class="lineno"> 438</span> <span class="keyword">const</span> <span class="keywordtype">double</span> primal_ray_sign_max_violation =</div>
|
||
<div class="line"><a id="l00439" name="l00439"></a><span class="lineno"> 439</span> primal_ray_local_sign_max_violation.lpNorm<Eigen::Infinity>();</div>
|
||
<div class="line"><a id="l00440" name="l00440"></a><span class="lineno"> 440</span> </div>
|
||
<div class="line"><a id="l00441" name="l00441"></a><span class="lineno"> 441</span> <span class="keywordflow">if</span> (l_inf_primal > 0.0) {</div>
|
||
<div class="line"><a id="l00442" name="l00442"></a><span class="lineno"> 442</span> VectorXd scaled_objective_product =</div>
|
||
<div class="line"><a id="l00443" name="l00443"></a><span class="lineno"> 443</span> ObjectiveProduct(scaled_sharded_qp, scaled_primal_ray);</div>
|
||
<div class="line"><a id="l00444" name="l00444"></a><span class="lineno"> 444</span> result.set_primal_ray_quadratic_norm(</div>
|
||
<div class="line"><a id="l00445" name="l00445"></a><span class="lineno"> 445</span> <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a33a42241df5501b0165ee77c3de54d7f">LInfNorm</a>(scaled_objective_product, scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">PrimalSharder</a>()) /</div>
|
||
<div class="line"><a id="l00446" name="l00446"></a><span class="lineno"> 446</span> l_inf_primal);</div>
|
||
<div class="line"><a id="l00447" name="l00447"></a><span class="lineno"> 447</span> result.set_max_primal_ray_infeasibility(</div>
|
||
<div class="line"><a id="l00448" name="l00448"></a><span class="lineno"> 448</span> <a class="code hl_variable" href="alldiff__cst_8cc.html#a26e6db9bcc64b584051ecc28171ed11f">std::max</a>(primal_residuals.l_inf_residual,</div>
|
||
<div class="line"><a id="l00449" name="l00449"></a><span class="lineno"> 449</span> primal_ray_sign_max_violation) /</div>
|
||
<div class="line"><a id="l00450" name="l00450"></a><span class="lineno"> 450</span> l_inf_primal);</div>
|
||
<div class="line"><a id="l00451" name="l00451"></a><span class="lineno"> 451</span> result.set_primal_ray_linear_objective(</div>
|
||
<div class="line"><a id="l00452" name="l00452"></a><span class="lineno"> 452</span> <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a11831586b99d28a708bc103bce1a945e">Dot</a>(scaled_primal_ray, qp.<a class="code hl_variable" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html#afdb3e07cd380793e1b265c1fded94edd">objective_vector</a>,</div>
|
||
<div class="line"><a id="l00453" name="l00453"></a><span class="lineno"> 453</span> scaled_sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">PrimalSharder</a>()) /</div>
|
||
<div class="line"><a id="l00454" name="l00454"></a><span class="lineno"> 454</span> l_inf_primal);</div>
|
||
<div class="line"><a id="l00455" name="l00455"></a><span class="lineno"> 455</span> } <span class="keywordflow">else</span> {</div>
|
||
<div class="line"><a id="l00456" name="l00456"></a><span class="lineno"> 456</span> result.set_primal_ray_quadratic_norm(0.0);</div>
|
||
<div class="line"><a id="l00457" name="l00457"></a><span class="lineno"> 457</span> result.set_max_primal_ray_infeasibility(0.0);</div>
|
||
<div class="line"><a id="l00458" name="l00458"></a><span class="lineno"> 458</span> result.set_primal_ray_linear_objective(0.0);</div>
|
||
<div class="line"><a id="l00459" name="l00459"></a><span class="lineno"> 459</span> }</div>
|
||
<div class="line"><a id="l00460" name="l00460"></a><span class="lineno"> 460</span> </div>
|
||
<div class="line"><a id="l00461" name="l00461"></a><span class="lineno"> 461</span> result.set_candidate_type(candidate_type);</div>
|
||
<div class="line"><a id="l00462" name="l00462"></a><span class="lineno"> 462</span> <span class="keywordflow">return</span> result;</div>
|
||
<div class="line"><a id="l00463" name="l00463"></a><span class="lineno"> 463</span>}</div>
|
||
<div class="line"><a id="l00464" name="l00464"></a><span class="lineno"> 464</span> </div>
|
||
<div class="line"><a id="l00465" name="l00465"></a><span class="lineno"><a class="line" href="namespaceoperations__research_1_1pdlp.html#a31aa44a967ce3e99c705e97da796aea0"> 465</a></span>ConvergenceInformation <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a31aa44a967ce3e99c705e97da796aea0">ComputeScaledConvergenceInformation</a>(</div>
|
||
<div class="line"><a id="l00466" name="l00466"></a><span class="lineno"> 466</span> <span class="keyword">const</span> <a class="code hl_class" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html">ShardedQuadraticProgram</a>& sharded_qp, <span class="keyword">const</span> VectorXd& primal_solution,</div>
|
||
<div class="line"><a id="l00467" name="l00467"></a><span class="lineno"> 467</span> <span class="keyword">const</span> VectorXd& dual_solution, PointType candidate_type) {</div>
|
||
<div class="line"><a id="l00468" name="l00468"></a><span class="lineno"> 468</span> <span class="keywordflow">return</span> <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#ac77694ebaac0adfa0fce8422782c48c8">ComputeConvergenceInformation</a>(</div>
|
||
<div class="line"><a id="l00469" name="l00469"></a><span class="lineno"> 469</span> sharded_qp, VectorXd::Ones(sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab945b88f1937277a896d4c7c7935d605">PrimalSize</a>()),</div>
|
||
<div class="line"><a id="l00470" name="l00470"></a><span class="lineno"> 470</span> VectorXd::Ones(sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#afcafa95b1a351212291c7a030deec52a">DualSize</a>()), primal_solution, dual_solution,</div>
|
||
<div class="line"><a id="l00471" name="l00471"></a><span class="lineno"> 471</span> candidate_type);</div>
|
||
<div class="line"><a id="l00472" name="l00472"></a><span class="lineno"> 472</span>}</div>
|
||
<div class="line"><a id="l00473" name="l00473"></a><span class="lineno"> 473</span> </div>
|
||
<div class="line"><a id="l00474" name="l00474"></a><span class="lineno"><a class="line" href="namespaceoperations__research_1_1pdlp.html#a64bfea523f69cba6f7be8ac302c18f2f"> 474</a></span>VectorXd <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a64bfea523f69cba6f7be8ac302c18f2f">ReducedCosts</a>(<span class="keyword">const</span> <a class="code hl_class" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html">ShardedQuadraticProgram</a>& sharded_qp,</div>
|
||
<div class="line"><a id="l00475" name="l00475"></a><span class="lineno"> 475</span> <span class="keyword">const</span> VectorXd& primal_solution,</div>
|
||
<div class="line"><a id="l00476" name="l00476"></a><span class="lineno"> 476</span> <span class="keyword">const</span> VectorXd& dual_solution,</div>
|
||
<div class="line"><a id="l00477" name="l00477"></a><span class="lineno"> 477</span> <span class="keywordtype">bool</span> use_zero_primal_objective) {</div>
|
||
<div class="line"><a id="l00478" name="l00478"></a><span class="lineno"> 478</span> VectorXd objective_product;</div>
|
||
<div class="line"><a id="l00479" name="l00479"></a><span class="lineno"> 479</span> <span class="keywordflow">if</span> (use_zero_primal_objective) {</div>
|
||
<div class="line"><a id="l00480" name="l00480"></a><span class="lineno"> 480</span> objective_product = <a class="code hl_function" href="namespaceoperations__research.html#a5a9881f8a07b166ef2cbde572cea27b6">VectorXd::Zero</a>(sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab945b88f1937277a896d4c7c7935d605">PrimalSize</a>());</div>
|
||
<div class="line"><a id="l00481" name="l00481"></a><span class="lineno"> 481</span> } <span class="keywordflow">else</span> {</div>
|
||
<div class="line"><a id="l00482" name="l00482"></a><span class="lineno"> 482</span> objective_product = ObjectiveProduct(sharded_qp, primal_solution);</div>
|
||
<div class="line"><a id="l00483" name="l00483"></a><span class="lineno"> 483</span> }</div>
|
||
<div class="line"><a id="l00484" name="l00484"></a><span class="lineno"> 484</span> VectorXd reduced_costs = PrimalGradientFromObjectiveProduct(</div>
|
||
<div class="line"><a id="l00485" name="l00485"></a><span class="lineno"> 485</span> sharded_qp, dual_solution, std::move(objective_product),</div>
|
||
<div class="line"><a id="l00486" name="l00486"></a><span class="lineno"> 486</span> use_zero_primal_objective);</div>
|
||
<div class="line"><a id="l00487" name="l00487"></a><span class="lineno"> 487</span> sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">PrimalSharder</a>().<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharder.html#a5bbfc4ed3da7a0815ba5f6c7ddee320b">ParallelForEachShard</a>(</div>
|
||
<div class="line"><a id="l00488" name="l00488"></a><span class="lineno"> 488</span> [&](<span class="keyword">const</span> <a class="code hl_class" href="classoperations__research_1_1pdlp_1_1_sharder_1_1_shard.html">Sharder::Shard</a>& shard) {</div>
|
||
<div class="line"><a id="l00489" name="l00489"></a><span class="lineno"> 489</span> <span class="keyword">auto</span> rc_shard = shard(reduced_costs);</div>
|
||
<div class="line"><a id="l00490" name="l00490"></a><span class="lineno"> 490</span> <span class="keyword">const</span> <span class="keyword">auto</span> lower_bound_shard =</div>
|
||
<div class="line"><a id="l00491" name="l00491"></a><span class="lineno"> 491</span> shard(sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#abfdc79e4b2325ff283b7d2333d40fffe">Qp</a>().<a class="code hl_variable" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html#a0f72e7b49f91d0b980f5a54a18c06964">variable_lower_bounds</a>);</div>
|
||
<div class="line"><a id="l00492" name="l00492"></a><span class="lineno"> 492</span> <span class="keyword">const</span> <span class="keyword">auto</span> upper_bound_shard =</div>
|
||
<div class="line"><a id="l00493" name="l00493"></a><span class="lineno"> 493</span> shard(sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#abfdc79e4b2325ff283b7d2333d40fffe">Qp</a>().<a class="code hl_variable" href="structoperations__research_1_1pdlp_1_1_quadratic_program.html#a097d329b7af662bea9b5a8e310a22726">variable_upper_bounds</a>);</div>
|
||
<div class="line"><a id="l00494" name="l00494"></a><span class="lineno"> 494</span> <span class="keyword">const</span> <span class="keyword">auto</span> primal_solution_shard = shard(primal_solution);</div>
|
||
<div class="line"><a id="l00495" name="l00495"></a><span class="lineno"> 495</span> <span class="keywordflow">for</span> (int64_t i = 0; i < rc_shard.size(); ++i) {</div>
|
||
<div class="line"><a id="l00496" name="l00496"></a><span class="lineno"> 496</span> <span class="keywordflow">if</span> (rc_shard[i] != 0.0 &&</div>
|
||
<div class="line"><a id="l00497" name="l00497"></a><span class="lineno"> 497</span> !HandlePrimalGradientTermAsReducedCost(</div>
|
||
<div class="line"><a id="l00498" name="l00498"></a><span class="lineno"> 498</span> rc_shard[i], primal_solution_shard[i], lower_bound_shard[i],</div>
|
||
<div class="line"><a id="l00499" name="l00499"></a><span class="lineno"> 499</span> upper_bound_shard[i])) {</div>
|
||
<div class="line"><a id="l00500" name="l00500"></a><span class="lineno"> 500</span> rc_shard[i] = 0.0;</div>
|
||
<div class="line"><a id="l00501" name="l00501"></a><span class="lineno"> 501</span> }</div>
|
||
<div class="line"><a id="l00502" name="l00502"></a><span class="lineno"> 502</span> }</div>
|
||
<div class="line"><a id="l00503" name="l00503"></a><span class="lineno"> 503</span> });</div>
|
||
<div class="line"><a id="l00504" name="l00504"></a><span class="lineno"> 504</span> <span class="keywordflow">return</span> reduced_costs;</div>
|
||
<div class="line"><a id="l00505" name="l00505"></a><span class="lineno"> 505</span>}</div>
|
||
<div class="line"><a id="l00506" name="l00506"></a><span class="lineno"> 506</span> </div>
|
||
<div class="line"><a id="l00507" name="l00507"></a><span class="lineno"><a class="line" href="namespaceoperations__research_1_1pdlp.html#a7b93e1d980b7d8112423361ac15a0c28"> 507</a></span>absl::optional<ConvergenceInformation> <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a7b93e1d980b7d8112423361ac15a0c28">GetConvergenceInformation</a>(</div>
|
||
<div class="line"><a id="l00508" name="l00508"></a><span class="lineno"> 508</span> <span class="keyword">const</span> IterationStats& stats, PointType candidate_type) {</div>
|
||
<div class="line"><a id="l00509" name="l00509"></a><span class="lineno"> 509</span> <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& convergence_information : stats.convergence_information()) {</div>
|
||
<div class="line"><a id="l00510" name="l00510"></a><span class="lineno"> 510</span> <span class="keywordflow">if</span> (convergence_information.candidate_type() == candidate_type) {</div>
|
||
<div class="line"><a id="l00511" name="l00511"></a><span class="lineno"> 511</span> <span class="keywordflow">return</span> convergence_information;</div>
|
||
<div class="line"><a id="l00512" name="l00512"></a><span class="lineno"> 512</span> }</div>
|
||
<div class="line"><a id="l00513" name="l00513"></a><span class="lineno"> 513</span> }</div>
|
||
<div class="line"><a id="l00514" name="l00514"></a><span class="lineno"> 514</span> <span class="keywordflow">return</span> absl::nullopt;</div>
|
||
<div class="line"><a id="l00515" name="l00515"></a><span class="lineno"> 515</span>}</div>
|
||
<div class="line"><a id="l00516" name="l00516"></a><span class="lineno"> 516</span> </div>
|
||
<div class="line"><a id="l00517" name="l00517"></a><span class="lineno"><a class="line" href="namespaceoperations__research_1_1pdlp.html#a99ed15089cb2d18e7abb0d146aa5f487"> 517</a></span>absl::optional<InfeasibilityInformation> <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a99ed15089cb2d18e7abb0d146aa5f487">GetInfeasibilityInformation</a>(</div>
|
||
<div class="line"><a id="l00518" name="l00518"></a><span class="lineno"> 518</span> <span class="keyword">const</span> IterationStats& stats, PointType candidate_type) {</div>
|
||
<div class="line"><a id="l00519" name="l00519"></a><span class="lineno"> 519</span> <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& infeasibility_information :</div>
|
||
<div class="line"><a id="l00520" name="l00520"></a><span class="lineno"> 520</span> stats.infeasibility_information()) {</div>
|
||
<div class="line"><a id="l00521" name="l00521"></a><span class="lineno"> 521</span> <span class="keywordflow">if</span> (infeasibility_information.candidate_type() == candidate_type) {</div>
|
||
<div class="line"><a id="l00522" name="l00522"></a><span class="lineno"> 522</span> <span class="keywordflow">return</span> infeasibility_information;</div>
|
||
<div class="line"><a id="l00523" name="l00523"></a><span class="lineno"> 523</span> }</div>
|
||
<div class="line"><a id="l00524" name="l00524"></a><span class="lineno"> 524</span> }</div>
|
||
<div class="line"><a id="l00525" name="l00525"></a><span class="lineno"> 525</span> <span class="keywordflow">return</span> absl::nullopt;</div>
|
||
<div class="line"><a id="l00526" name="l00526"></a><span class="lineno"> 526</span>}</div>
|
||
<div class="line"><a id="l00527" name="l00527"></a><span class="lineno"> 527</span> </div>
|
||
<div class="line"><a id="l00528" name="l00528"></a><span class="lineno"><a class="line" href="namespaceoperations__research_1_1pdlp.html#a67c368ee96f024040259d5278775c1aa"> 528</a></span>absl::optional<PointMetadata> <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a67c368ee96f024040259d5278775c1aa">GetPointMetadata</a>(<span class="keyword">const</span> IterationStats& stats,</div>
|
||
<div class="line"><a id="l00529" name="l00529"></a><span class="lineno"> 529</span> <span class="keyword">const</span> PointType point_type) {</div>
|
||
<div class="line"><a id="l00530" name="l00530"></a><span class="lineno"> 530</span> <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& metadata : stats.point_metadata()) {</div>
|
||
<div class="line"><a id="l00531" name="l00531"></a><span class="lineno"> 531</span> <span class="keywordflow">if</span> (metadata.point_type() == point_type) {</div>
|
||
<div class="line"><a id="l00532" name="l00532"></a><span class="lineno"> 532</span> <span class="keywordflow">return</span> metadata;</div>
|
||
<div class="line"><a id="l00533" name="l00533"></a><span class="lineno"> 533</span> }</div>
|
||
<div class="line"><a id="l00534" name="l00534"></a><span class="lineno"> 534</span> }</div>
|
||
<div class="line"><a id="l00535" name="l00535"></a><span class="lineno"> 535</span> <span class="keywordflow">return</span> absl::nullopt;</div>
|
||
<div class="line"><a id="l00536" name="l00536"></a><span class="lineno"> 536</span>}</div>
|
||
<div class="line"><a id="l00537" name="l00537"></a><span class="lineno"> 537</span> </div>
|
||
<div class="line"><a id="l00538" name="l00538"></a><span class="lineno"><a class="line" href="namespaceoperations__research_1_1pdlp.html#a85cd9828e35e9f00a622d0376bc81325"> 538</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="namespaceoperations__research_1_1pdlp.html#a85cd9828e35e9f00a622d0376bc81325">SetRandomProjections</a>(<span class="keyword">const</span> <a class="code hl_class" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html">ShardedQuadraticProgram</a>& sharded_qp,</div>
|
||
<div class="line"><a id="l00539" name="l00539"></a><span class="lineno"> 539</span> <span class="keyword">const</span> Eigen::VectorXd& primal_solution,</div>
|
||
<div class="line"><a id="l00540" name="l00540"></a><span class="lineno"> 540</span> <span class="keyword">const</span> Eigen::VectorXd& dual_solution,</div>
|
||
<div class="line"><a id="l00541" name="l00541"></a><span class="lineno"> 541</span> <span class="keyword">const</span> std::vector<int>& random_projection_seeds,</div>
|
||
<div class="line"><a id="l00542" name="l00542"></a><span class="lineno"> 542</span> PointMetadata& metadata) {</div>
|
||
<div class="line"><a id="l00543" name="l00543"></a><span class="lineno"> 543</span> <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keywordtype">int</span> random_projection_seed : random_projection_seeds) {</div>
|
||
<div class="line"><a id="l00544" name="l00544"></a><span class="lineno"> 544</span> std::mt19937 seed_generator(random_projection_seed);</div>
|
||
<div class="line"><a id="l00545" name="l00545"></a><span class="lineno"> 545</span> metadata.mutable_random_primal_projections()->Add(RandomProjection(</div>
|
||
<div class="line"><a id="l00546" name="l00546"></a><span class="lineno"> 546</span> primal_solution, sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">PrimalSharder</a>(), seed_generator));</div>
|
||
<div class="line"><a id="l00547" name="l00547"></a><span class="lineno"> 547</span> metadata.mutable_random_dual_projections()->Add(RandomProjection(</div>
|
||
<div class="line"><a id="l00548" name="l00548"></a><span class="lineno"> 548</span> dual_solution, sharded_qp.<a class="code hl_function" href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#a101ca40b60dd25bbf6271bef1370e8d1">DualSharder</a>(), seed_generator));</div>
|
||
<div class="line"><a id="l00549" name="l00549"></a><span class="lineno"> 549</span> }</div>
|
||
<div class="line"><a id="l00550" name="l00550"></a><span class="lineno"> 550</span>}</div>
|
||
<div class="line"><a id="l00551" name="l00551"></a><span class="lineno"> 551</span> </div>
|
||
<div class="line"><a id="l00552" name="l00552"></a><span class="lineno"> 552</span>} <span class="comment">// namespace operations_research::pdlp</span></div>
|
||
<div class="ttc" id="aalldiff__cst_8cc_html_a26e6db9bcc64b584051ecc28171ed11f"><div class="ttname"><a href="alldiff__cst_8cc.html#a26e6db9bcc64b584051ecc28171ed11f">max</a></div><div class="ttdeci">int64_t max</div><div class="ttdef"><b>Definition:</b> <a href="alldiff__cst_8cc_source.html#l00140">alldiff_cst.cc:140</a></div></div>
|
||
<div class="ttc" id="abase_2logging_8h_html"><div class="ttname"><a href="base_2logging_8h.html">logging.h</a></div></div>
|
||
<div class="ttc" id="abase_2logging_8h_html_a7c0ce053b28d53aa4eaf3eb7fb71663b"><div class="ttname"><a href="base_2logging_8h.html#a7c0ce053b28d53aa4eaf3eb7fb71663b">CHECK_EQ</a></div><div class="ttdeci">#define CHECK_EQ(val1, val2)</div><div class="ttdef"><b>Definition:</b> <a href="base_2logging_8h_source.html#l00703">base/logging.h:703</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1_math_util_html_aac72849250cdf23aefdd991eb0fc0385"><div class="ttname"><a href="classoperations__research_1_1_math_util.html#aac72849250cdf23aefdd991eb0fc0385">operations_research::MathUtil::Square</a></div><div class="ttdeci">static T Square(const T x)</div><div class="ttdef"><b>Definition:</b> <a href="mathutil_8h_source.html#l00101">mathutil.h:101</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1pdlp_1_1_sharded_quadratic_program_html"><div class="ttname"><a href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html">operations_research::pdlp::ShardedQuadraticProgram</a></div><div class="ttdef"><b>Definition:</b> <a href="sharded__quadratic__program_8h_source.html#l00033">sharded_quadratic_program.h:33</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1pdlp_1_1_sharded_quadratic_program_html_a101ca40b60dd25bbf6271bef1370e8d1"><div class="ttname"><a href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#a101ca40b60dd25bbf6271bef1370e8d1">operations_research::pdlp::ShardedQuadraticProgram::DualSharder</a></div><div class="ttdeci">const Sharder & DualSharder() const</div><div class="ttdef"><b>Definition:</b> <a href="sharded__quadratic__program_8h_source.html#l00064">sharded_quadratic_program.h:64</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1pdlp_1_1_sharded_quadratic_program_html_ab7ab55f549e3f9c1a1c8c8d2b766f75b"><div class="ttname"><a href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab7ab55f549e3f9c1a1c8c8d2b766f75b">operations_research::pdlp::ShardedQuadraticProgram::PrimalSharder</a></div><div class="ttdeci">const Sharder & PrimalSharder() const</div><div class="ttdef"><b>Definition:</b> <a href="sharded__quadratic__program_8h_source.html#l00062">sharded_quadratic_program.h:62</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1pdlp_1_1_sharded_quadratic_program_html_ab945b88f1937277a896d4c7c7935d605"><div class="ttname"><a href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#ab945b88f1937277a896d4c7c7935d605">operations_research::pdlp::ShardedQuadraticProgram::PrimalSize</a></div><div class="ttdeci">int64_t PrimalSize() const</div><div class="ttdef"><b>Definition:</b> <a href="sharded__quadratic__program_8h_source.html#l00066">sharded_quadratic_program.h:66</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1pdlp_1_1_sharded_quadratic_program_html_abfdc79e4b2325ff283b7d2333d40fffe"><div class="ttname"><a href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#abfdc79e4b2325ff283b7d2333d40fffe">operations_research::pdlp::ShardedQuadraticProgram::Qp</a></div><div class="ttdeci">const QuadraticProgram & Qp() const</div><div class="ttdef"><b>Definition:</b> <a href="sharded__quadratic__program_8h_source.html#l00045">sharded_quadratic_program.h:45</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1pdlp_1_1_sharded_quadratic_program_html_afcafa95b1a351212291c7a030deec52a"><div class="ttname"><a href="classoperations__research_1_1pdlp_1_1_sharded_quadratic_program.html#afcafa95b1a351212291c7a030deec52a">operations_research::pdlp::ShardedQuadraticProgram::DualSize</a></div><div class="ttdeci">int64_t DualSize() const</div><div class="ttdef"><b>Definition:</b> <a href="sharded__quadratic__program_8h_source.html#l00067">sharded_quadratic_program.h:67</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1pdlp_1_1_sharder_1_1_shard_html"><div class="ttname"><a href="classoperations__research_1_1pdlp_1_1_sharder_1_1_shard.html">operations_research::pdlp::Sharder::Shard</a></div><div class="ttdef"><b>Definition:</b> <a href="sharder_8h_source.html#l00055">sharder.h:55</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1pdlp_1_1_sharder_1_1_shard_html_a8ef12397d1682615bc3108c397734179"><div class="ttname"><a href="classoperations__research_1_1pdlp_1_1_sharder_1_1_shard.html#a8ef12397d1682615bc3108c397734179">operations_research::pdlp::Sharder::Shard::Index</a></div><div class="ttdeci">int Index() const</div><div class="ttdef"><b>Definition:</b> <a href="sharder_8h_source.html#l00127">sharder.h:127</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1pdlp_1_1_sharder_html_a5bbfc4ed3da7a0815ba5f6c7ddee320b"><div class="ttname"><a href="classoperations__research_1_1pdlp_1_1_sharder.html#a5bbfc4ed3da7a0815ba5f6c7ddee320b">operations_research::pdlp::Sharder::ParallelForEachShard</a></div><div class="ttdeci">void ParallelForEachShard(const std::function< void(const Shard &)> &func) const</div><div class="ttdef"><b>Definition:</b> <a href="sharder_8cc_source.html#l00097">sharder.cc:97</a></div></div>
|
||
<div class="ttc" id="aclassoperations__research_1_1pdlp_1_1_sharder_html_aa6c18d04d5fcbe7a9343768b8b66be7f"><div class="ttname"><a href="classoperations__research_1_1pdlp_1_1_sharder.html#aa6c18d04d5fcbe7a9343768b8b66be7f">operations_research::pdlp::Sharder::NumShards</a></div><div class="ttdeci">int NumShards() const</div><div class="ttdef"><b>Definition:</b> <a href="sharder_8h_source.html#l00181">sharder.h:181</a></div></div>
|
||
<div class="ttc" id="agscip__solver_8cc_html_a1ba5ca0f61f2fa13bd23bf0f89004f35"><div class="ttname"><a href="gscip__solver_8cc.html#a1ba5ca0f61f2fa13bd23bf0f89004f35">upper_bound</a></div><div class="ttdeci">double upper_bound</div><div class="ttdef"><b>Definition:</b> <a href="gscip__solver_8cc_source.html#l00137">gscip_solver.cc:137</a></div></div>
|
||
<div class="ttc" id="agscip__solver_8cc_html_a1e2f9a2352c1d9a6cada9544898fceec"><div class="ttname"><a href="gscip__solver_8cc.html#a1e2f9a2352c1d9a6cada9544898fceec">lower_bound</a></div><div class="ttdeci">double lower_bound</div><div class="ttdef"><b>Definition:</b> <a href="gscip__solver_8cc_source.html#l00136">gscip_solver.cc:136</a></div></div>
|
||
<div class="ttc" id="aiteration__stats_8cc_html_a16548fbf63af658d61de20a71baded7a"><div class="ttname"><a href="iteration__stats_8cc.html#a16548fbf63af658d61de20a71baded7a">l_2_residual</a></div><div class="ttdeci">double l_2_residual</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00056">iteration_stats.cc:56</a></div></div>
|
||
<div class="ttc" id="aiteration__stats_8cc_html_a16e7df0f7c2a47748aaf9004258c6b13"><div class="ttname"><a href="iteration__stats_8cc.html#a16e7df0f7c2a47748aaf9004258c6b13">objective_full_correction</a></div><div class="ttdeci">double objective_full_correction</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00054">iteration_stats.cc:54</a></div></div>
|
||
<div class="ttc" id="aiteration__stats_8cc_html_a28460a7fdcd91c3a3a95b2b74aff7bb7"><div class="ttname"><a href="iteration__stats_8cc.html#a28460a7fdcd91c3a3a95b2b74aff7bb7">objective_correction</a></div><div class="ttdeci">double objective_correction</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00053">iteration_stats.cc:53</a></div></div>
|
||
<div class="ttc" id="aiteration__stats_8cc_html_aa731e3486184edfd00ea54e3a288175f"><div class="ttname"><a href="iteration__stats_8cc.html#aa731e3486184edfd00ea54e3a288175f">l_inf_residual</a></div><div class="ttdeci">double l_inf_residual</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00055">iteration_stats.cc:55</a></div></div>
|
||
<div class="ttc" id="aiteration__stats_8h_html"><div class="ttname"><a href="iteration__stats_8h.html">iteration_stats.h</a></div></div>
|
||
<div class="ttc" id="amathutil_8h_html"><div class="ttname"><a href="mathutil_8h.html">mathutil.h</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html">operations_research::pdlp</a></div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00040">iteration_stats.cc:40</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a0b812156619599417e29521a41b7a734"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a0b812156619599417e29521a41b7a734">operations_research::pdlp::ScaledNorm</a></div><div class="ttdeci">double ScaledNorm(const VectorXd &vector, const VectorXd &scale, const Sharder &sharder)</div><div class="ttdef"><b>Definition:</b> <a href="sharder_8cc_source.html#l00253">sharder.cc:253</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a11831586b99d28a708bc103bce1a945e"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a11831586b99d28a708bc103bce1a945e">operations_research::pdlp::Dot</a></div><div class="ttdeci">double Dot(const VectorXd &v1, const VectorXd &v2, const Sharder &sharder)</div><div class="ttdef"><b>Definition:</b> <a href="sharder_8cc_source.html#l00197">sharder.cc:197</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a31aa44a967ce3e99c705e97da796aea0"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a31aa44a967ce3e99c705e97da796aea0">operations_research::pdlp::ComputeScaledConvergenceInformation</a></div><div class="ttdeci">ConvergenceInformation ComputeScaledConvergenceInformation(const ShardedQuadraticProgram &sharded_qp, const VectorXd &primal_solution, const VectorXd &dual_solution, PointType candidate_type)</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00465">iteration_stats.cc:465</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a33a42241df5501b0165ee77c3de54d7f"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a33a42241df5501b0165ee77c3de54d7f">operations_research::pdlp::LInfNorm</a></div><div class="ttdeci">double LInfNorm(const VectorXd &vector, const Sharder &sharder)</div><div class="ttdef"><b>Definition:</b> <a href="sharder_8cc_source.html#l00202">sharder.cc:202</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a463586ded0a114d3ca4b97a048d37d8a"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a463586ded0a114d3ca4b97a048d37d8a">operations_research::pdlp::TransposedMatrixVectorProduct</a></div><div class="ttdeci">VectorXd TransposedMatrixVectorProduct(const Eigen::SparseMatrix< double, Eigen::ColMajor, int64_t > &matrix, const VectorXd &vector, const Sharder &sharder)</div><div class="ttdef"><b>Definition:</b> <a href="sharder_8cc_source.html#l00151">sharder.cc:151</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a55b8c43a5adfafddb030074c75aeef70"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a55b8c43a5adfafddb030074c75aeef70">operations_research::pdlp::ScaledLInfNorm</a></div><div class="ttdeci">double ScaledLInfNorm(const VectorXd &vector, const VectorXd &scale, const Sharder &sharder)</div><div class="ttdef"><b>Definition:</b> <a href="sharder_8cc_source.html#l00236">sharder.cc:236</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a64bfea523f69cba6f7be8ac302c18f2f"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a64bfea523f69cba6f7be8ac302c18f2f">operations_research::pdlp::ReducedCosts</a></div><div class="ttdeci">VectorXd ReducedCosts(const ShardedQuadraticProgram &sharded_qp, const VectorXd &primal_solution, const VectorXd &dual_solution, bool use_zero_primal_objective)</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00474">iteration_stats.cc:474</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a67c368ee96f024040259d5278775c1aa"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a67c368ee96f024040259d5278775c1aa">operations_research::pdlp::GetPointMetadata</a></div><div class="ttdeci">absl::optional< PointMetadata > GetPointMetadata(const IterationStats &stats, const PointType point_type)</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00528">iteration_stats.cc:528</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a74af5ceb7b6e37fbfca92e2c59b99e3e"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a74af5ceb7b6e37fbfca92e2c59b99e3e">operations_research::pdlp::ComputeInfeasibilityInformation</a></div><div class="ttdeci">InfeasibilityInformation ComputeInfeasibilityInformation(const ShardedQuadraticProgram &scaled_sharded_qp, const Eigen::VectorXd &col_scaling_vec, const Eigen::VectorXd &row_scaling_vec, const Eigen::VectorXd &scaled_primal_ray, const Eigen::VectorXd &scaled_dual_ray, PointType candidate_type)</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00372">iteration_stats.cc:372</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a7b93e1d980b7d8112423361ac15a0c28"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a7b93e1d980b7d8112423361ac15a0c28">operations_research::pdlp::GetConvergenceInformation</a></div><div class="ttdeci">absl::optional< ConvergenceInformation > GetConvergenceInformation(const IterationStats &stats, PointType candidate_type)</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00507">iteration_stats.cc:507</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a850865b3deabb2a623e130691df99f15"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a850865b3deabb2a623e130691df99f15">operations_research::pdlp::IsLinearProgram</a></div><div class="ttdeci">bool IsLinearProgram(const QuadraticProgram &qp)</div><div class="ttdef"><b>Definition:</b> <a href="quadratic__program_8h_source.html#l00150">quadratic_program.h:150</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a85cd9828e35e9f00a622d0376bc81325"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a85cd9828e35e9f00a622d0376bc81325">operations_research::pdlp::SetRandomProjections</a></div><div class="ttdeci">void SetRandomProjections(const ShardedQuadraticProgram &sharded_qp, const Eigen::VectorXd &primal_solution, const Eigen::VectorXd &dual_solution, const std::vector< int > &random_projection_seeds, PointMetadata &metadata)</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00538">iteration_stats.cc:538</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_a99ed15089cb2d18e7abb0d146aa5f487"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#a99ed15089cb2d18e7abb0d146aa5f487">operations_research::pdlp::GetInfeasibilityInformation</a></div><div class="ttdeci">absl::optional< InfeasibilityInformation > GetInfeasibilityInformation(const IterationStats &stats, PointType candidate_type)</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00517">iteration_stats.cc:517</a></div></div>
|
||
<div class="ttc" id="anamespaceoperations__research_1_1pdlp_html_ac77694ebaac0adfa0fce8422782c48c8"><div class="ttname"><a href="namespaceoperations__research_1_1pdlp.html#ac77694ebaac0adfa0fce8422782c48c8">operations_research::pdlp::ComputeConvergenceInformation</a></div><div class="ttdeci">ConvergenceInformation ComputeConvergenceInformation(const ShardedQuadraticProgram &scaled_sharded_qp, const Eigen::VectorXd &col_scaling_vec, const Eigen::VectorXd &row_scaling_vec, const Eigen::VectorXd &scaled_primal_solution, const Eigen::VectorXd &scaled_dual_solution, PointType candidate_type)</div><div class="ttdef"><b>Definition:</b> <a href="iteration__stats_8cc_source.html#l00308">iteration_stats.cc:308</a></div></div>
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