Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase
This is a network apply the following layout:
LayerTests.java:203 executed in 0.07 seconds (0.000 gc):
return Graphviz.fromGraph((Graph) TestUtil.toGraph(((DAGNetwork) layer).addRef())).height(400).width(600)
.render(Format.PNG).toImage();
executing command [/bin/sh, -c, dot -Tsvg /tmp/GraphvizJava/DotEngine220576634708435773/dotfile.dot -ooutfile.svg]
Returns
Using Seed 4846182932205448192
In this apply, we use a network to learn this target input, given it's pre-evaluated output:
TrainingTester.java:332 executed in 0.01 seconds (0.000 gc):
return RefArrays.stream(RefUtil.addRef(input_target)).flatMap(RefArrays::stream).map(x -> {
try {
return x.prettyPrint();
} finally {
x.freeRef();
}
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
[ [ -0.388, 0.736, -0.52, -0.92, -1.02, 1.764, 0.936 ], [ 1.888, -0.596, -0.932, -1.88, -0.004, 0.9, 1.536 ], [ -0.42, -1.712, -1.316, 1.268, 1.884, -1.612, 0.084 ], [ -1.56, 0.112, -0.632, -1.184, 1.148, 0.952, 1.468 ], [ -0.784, -0.028, -1.196, 1.032, 1.94, 1.52, 0.74 ], [ 0.396, -0.036, 1.04, -1.724, -0.612, 0.036, -0.376 ], [ -0.392, -1.932, 1.832, -0.204, -1.904, 0.496, 1.688 ], [ 0.996, 1.028, 1.608, -1.148, 1.924, -0.804, -0.24 ], ... ],
[ [ -0.14, 0.78, 0.912, -0.908, -0.24, -1.744, -1.104 ], [ 1.576, -0.416, -1.716, 1.812, -1.22, 1.232, -0.404 ], [ 1.188, -0.604, -0.316, -0.112, -1.432, -1.168, 2.0 ], [ -1.18, 1.696, 1.004, 0.52, 1.072, 1.52, -1.068 ], [ 1.724, -1.636, -0.86, -0.84, 1.828, -1.748, 0.12 ], [ -0.824, 0.28, 0.596, -1.596, 1.1, -0.948, -1.668 ], [ 1.312, 1.592, -1.884, -1.944, 0.632, 0.64, 1.792 ], [ 0.76, -0.692, -0.248, -0.86, -1.116, -0.404, 0.872 ], ... ],
[ [ -1.528, -1.5, 1.996, -0.192, -0.8, 0.888, 1.8 ], [ -1.368, -0.016, -0.5, 0.2, -1.456, -0.904, -1.824 ], [ -1.212, -0.472, -0.76, -0.216, -0.428, 0.528, -0.728 ], [ -1.436, -0.992, -0.276, -1.044, -1.328, 1.912, 1.78 ], [ 0.556, 0.088, 1.28, -1.544, -1.576, -1.492, 1.296 ], [ 1.948, 1.304, 0.808, 0.136, 1.676, -0.968, -1.476 ], [ -1.096, -0.124, -1.104, 0.008, -1.572, -0.288, -1.772 ], [ -0.856, 1.744, 1.588, 1.652, 1.116, 0.56, -1.164 ], ... ],
[ [ -0.912, 0.456, 1.14, -1.572, 0.376, 0.284, -0.764 ], [ -1.376, 1.184, -1.52, -1.336, 1.428, -0.24, 0.832 ], [ -0.336, -1.236, -0.6, -1.828, -0.9, -0.492, -0.132 ], [ 0.02, 0.888, 1.952, 0.508, 1.128, -1.772, 0.86 ], [ -1.2, -1.808, 1.636, 0.08, -1.508, 1.056, 0.664 ], [ 1.336, -0.24, 0.224, 0.98, 1.824, 1.26, 0.12 ], [ -0.036, -1.248, 1.312, -0.4, -1.168, -0.396, -1.16 ], [ 1.304, -0.328, -1.852, 0.148, 0.764, -0.384, -1.388 ], ... ],
[ [ -0.84, 1.996, -0.088, 1.624, 0.892, 1.34, -1.548 ], [ -1.444, 1.172, -0.992, -0.548, 1.612, -0.624, 1.44 ], [ 1.216, 1.544, -0.868, 1.816, -1.636, 0.116, 1.488 ], [ 0.92, 0.436, -1.056, 1.736, 0.968, 0.732, -0.232 ], [ -1.144, 0.6, -0.96, -0.124, 1.896, 1.328, -0.4 ], [ 0.76, 0.404, 0.488, 0.508, -0.432, 1.124, -0.308 ], [ 1.892, 0.468, -1.772, -0.424, -1.176, 1.192, -1.94 ], [ -0.316, -0.248, 1.876, 0.588, -1.604, 0.92, 0.728 ], ... ],
[ [ -0.424, 0.72, 0.524, 1.936, -1.74, 1.82, -1.232 ], [ -0.308, -1.5, -1.868, 1.1, -1.16, -1.004, -1.656 ], [ 0.912, -0.316, 0.04, 1.344, 1.528, 0.644, -1.712 ], [ -0.676, -0.296, -1.508, -1.348, 1.76, -0.444, -1.636 ], [ -0.296, 1.78, -0.204, -0.64, 0.46, -0.648, -0.964 ], [ 0.992, -0.772, -0.08, -0.588, 1.744, 1.748, -1.908 ], [ 0.992, 0.432, -1.936, 0.212, -1.688, 1.224, 0.512 ], [ 1.62, 0.072, -0.824, 0.46, 0.736, -0.484, -1.624 ], ... ],
[ [ -1.508, 0.46, 0.052, -1.552, -1.072, -1.572, 1.42 ], [ 1.844, -0.604, 1.012, 0.72, 0.384, 0.024, 0.632 ], [ -0.016, -1.044, -1.844, 1.456, -1.576, 1.892, -1.856 ], [ 0.536, -0.448, -1.924, -0.868, -0.932, -0.16, 0.48 ], [ -1.884, 0.612, -0.748, 1.048, 0.992, -1.092, 0.156 ], [ -1.052, 0.836, 0.1, -0.992, 0.94, -1.432, -0.204 ], [ 0.48, 1.688, 1.628, -0.948, -0.072, 0.26, 1.244 ], [ -0.196, -1.228, 0.172, 1.456, -0.84, 1.512, -0.068 ], ... ],
[ [ -0.848, 1.676, -0.964, -0.58, -0.996, 1.492, 0.324 ], [ 1.316, -1.48, -0.856, -0.092, -0.092, -1.988, 0.98 ], [ -1.144, -1.332, -0.956, -1.356, 0.872, 1.472, -0.064 ], [ -0.036, 0.284, -1.62, -1.56, 0.388, 1.424, -0.42 ], [ -0.596, -0.268, -1.952, -0.02, -1.2, -0.72, 0.572 ], [ 1.828, 1.876, 1.408, 0.348, 0.308, 1.988, 1.98 ], [ -1.096, -1.9, -1.296, -1.248, -1.828, -1.5, -1.028 ], [ -0.276, -1.016, -0.224, -1.144, -0.764, -0.2, 1.436 ], ... ],
...
]
[
[ [ -1.764, -1.608, -1.336, -1.224, -0.836, -0.376, 0.564 ], [ 1.688, 1.116, 1.28, -1.268, 0.592, 0.784, 1.48 ], [ 1.664, 0.832, 0.5, 0.264, 1.928, 1.336, -0.932 ], [ -0.848, -1.988, 0.588, -1.772, -0.172, -1.752, 1.524 ], [ 1.1, -1.108, 0.492, -1.396, 0.976, 0.172, -0.244 ], [ -1.572, -0.168, 1.06, -1.836, -1.804, 0.484, 0.976 ], [ -0.876, -1.104, -1.104, -0.068, 1.8, -1.9, -1.688 ], [ -0.896, 0.648, -1.864, 0.684, -0.112, -0.984, -1.992 ], ... ],
[ [ 1.02, -1.12, -0.88, 1.28, -1.0, -0.908, -0.264 ], [ -0.188, -0.7, -0.56, -0.364, 0.52, -1.576, -0.188 ], [ 0.744, -0.624, -1.252, -1.04, -1.808, 1.604, 0.156 ], [ -1.296, 1.948, 1.192, -0.748, -0.788, -1.772, -1.388 ], [ 0.152, 1.932, -0.4, -1.644, 0.208, 1.788, 1.528 ], [ 1.816, 0.48, 1.524, 0.052, 0.048, 0.612, -0.9 ], [ -1.64, -0.288, 0.368, 0.64, 1.98, 0.008, 0.772 ], [ 0.756, 1.048, -0.356, 0.528, 0.448, -1.244, 0.352 ], ... ],
[ [ 0.484, -1.756, -1.184, 1.688, 0.188, -1.276, -0.724 ], [ -1.192, 0.136, -1.88, -0.56, 0.516, 0.168, -0.192 ], [ 0.736, 1.436, 1.432, 1.8, 1.172, -0.088, 1.412 ], [ 1.44, 1.14, -0.752, -1.192, 0.336, 0.236, -0.492 ], [ 1.048, 1.584, 0.096, -0.928, 1.648, 0.796, -1.66 ], [ 1.732, 0.348, 0.496, -1.644, -0.316, 1.068, 1.6 ], [ -0.812, -1.056, -0.464, 1.488, 1.012, -1.952, 0.996 ], [ 0.136, 0.532, 1.98, 1.728, 1.108, 1.728, -1.332 ], ... ],
[ [ 1.204, 1.572, 1.436, 0.516, 0.74, 1.192, 1.588 ], [ -1.608, 0.248, 1.484, -1.424, 1.976, -1.784, -0.38 ], [ 0.312, -1.004, -1.088, 0.396, -0.812, 0.68, -0.68 ], [ 0.98, 1.64, -0.448, 1.016, 0.904, 1.312, 1.244 ], [ -1.42, -1.272, -1.94, -0.596, -1.712, -0.964, 1.22 ], [ -1.268, -1.272, 1.7, 0.396, 0.66, 1.928, 0.62 ], [ -1.768, -0.336, 0.928, -0.648, -1.656, 0.652, -1.704 ], [ -1.36, -0.768, 1.404, 1.548, 1.616, -0.376, -0.324 ], ... ],
[ [ -0.792, 0.208, 0.848, 1.972, -1.268, -0.992, 0.948 ], [ 0.816, -0.036, 1.404, -1.384, 0.644, 0.092, -0.304 ], [ -0.172, 0.728, 1.056, -1.236, -0.18, -0.9, -1.316 ], [ -0.952, -1.224, 0.068, 1.344, -0.864, 0.828, -0.392 ], [ 1.652, 1.46, 0.196, -0.076, -1.916, -1.756, -1.292 ], [ -1.32, 1.396, 1.52, -0.236, -0.408, -0.376, 1.152 ], [ 0.744, 0.536, -1.944, 0.704, -0.768, -0.028, -1.212 ], [ -1.872, -0.492, 0.516, -0.332, 0.284, -0.9, 1.724 ], ... ],
[ [ -0.828, -1.08, -0.008, -0.764, -0.104, -1.244, -0.804 ], [ -0.592, 1.284, 1.944, 1.264, 1.4, -1.904, 0.06 ], [ -1.292, 1.752, -0.852, 1.636, -1.3, -0.324, -0.316 ], [ 0.948, 1.54, 0.52, 0.256, 0.348, -1.876, -1.928 ], [ -1.58, -0.344, 0.992, 0.824, -1.448, 1.98, -0.388 ], [ 1.52, 1.384, -0.764, 1.56, -0.948, 0.068, 0.104 ], [ -0.848, -0.928, -0.824, 1.472, -1.144, -0.116, -0.604 ], [ -1.64, 0.52, 0.016, -0.744, -1.556, -1.94, -1.784 ], ... ],
[ [ 0.652, -0.784, 0.332, -1.332, 1.524, 1.932, 0.56 ], [ -1.676, 0.884, 1.08, 0.024, 0.74, 0.944, -1.24 ], [ -1.34, 0.572, 1.608, -0.568, 1.464, -1.46, -0.656 ], [ -0.624, 1.384, 1.592, -0.884, 1.632, -1.412, -1.132 ], [ -0.456, -1.624, 0.26, 0.556, 1.672, -1.708, -0.944 ], [ -0.62, 0.56, 1.5, 0.128, 1.504, 1.988, 1.516 ], [ -0.876, -1.492, -1.06, -0.876, -0.116, 1.988, -0.376 ], [ -1.832, -0.064, 0.524, -0.436, 1.896, 0.404, 0.592 ], ... ],
[ [ -0.444, -1.564, 1.592, -0.148, 1.064, 1.392, 0.032 ], [ 0.84, 1.312, -1.872, -1.792, -0.976, -0.144, 1.176 ], [ 0.728, -1.8, -1.68, 1.896, -1.212, -0.18, 0.984 ], [ -0.84, -0.232, 1.996, -0.884, -1.324, 1.284, -0.208 ], [ 1.532, -0.892, -0.896, -1.372, 0.896, -1.044, 0.968 ], [ -0.564, 1.3, -1.716, -0.212, -0.1, 0.952, -0.26 ], [ -0.12, 0.604, -1.128, 0.744, 1.872, 0.156, 0.164 ], [ 0.152, -0.812, -1.176, -1.32, 0.832, 0.804, 1.5 ], ... ],
...
]
First, we train using basic gradient descent method apply weak line search conditions.
TrainingTester.java:480 executed in 30.15 seconds (0.848 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new ArmijoWolfeSearch());
iterativeTrainer.setOrientation(new GradientDescent());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 13116631800683
Reset training subject: 13117639776919
Constructing line search parameters: GD
th(0)=233.5098803469944;dx=-0.03930302224877376
New Minimum: 233.5098803469944 > 233.42521413839194
WOLFE (weak): th(2.154434690031884)=233.42521413839194; dx=-0.03929411251682438 evalInputDelta=0.08466620860247076
New Minimum: 233.42521413839194 > 233.3405671044129
WOLFE (weak): th(4.308869380063768)=233.3405671044129; dx=-0.039285202788745414 evalInputDelta=0.16931324258149516
New Minimum: 233.3405671044129 > 233.00217102729454
WOLFE (weak): th(12.926608140191302)=233.00217102729454; dx=-0.03924956387768884 evalInputDelta=0.5077093196998703
New Minimum: 233.00217102729454 > 231.483189526702
WOLFE (weak): th(51.70643256076521)=231.483189526702; dx=-0.03908918878541733 evalInputDelta=2.0266908202924014
New Minimum: 231.483189526702 > 223.48699200965726
WOLFE (weak): th(258.53216280382605)=223.48699200965726; dx=-0.03823385494231532 evalInputDelta=10.02288833733715
New Minimum: 223.48699200965726 > 177.51876262366807
END: th(1551.1929768229563)=177.51876262366807; dx=-0.03288801843500125 evalInputDelta=55.99111772332634
Fitness changed from 233.5098803469944 to 177.51876262366807
Iteration 1 complete. Error: 177.51876262366807 Total: 6.8521; Orientation: 0.2813; Line Search: 4.6999
th(0)=177.51876262366807;dx=-0.02765497530407833
New Minimum: 177.51876262366807 > 100.52900140451678
END: th(3341.943960201201)=100.52900140451678; dx=-0.01841986147522871 evalInputDelta=76.98976121915129
Fitness changed from 177.51876262366807 to 100.52900140451678
Iteration 2 complete. Error: 100.52900140451678 Total: 1.8358; Orientation: 0.1694; Line Search: 1.2586
th(0)=100.52900140451678;dx=-0.012715176321054763
New Minimum: 100.52900140451678 > 37.25789902553923
END: th(7200.000000000001)=37.25789902553923; dx=-0.004860129895987405 evalInputDelta=63.271102378977545
Fitness changed from 100.52900140451678 to 37.25789902553923
Iteration 3 complete. Error: 37.25789902553923 Total: 1.6445; Orientation: 0.1702; Line Search: 1.0564
th(0)=37.25789902553923;dx=-0.002757376835940536
New Minimum: 37.25789902553923 > 12.025062391381375
END: th(15511.929768229566)=12.025062391381375; dx=-4.959690730636268E-4 evalInputDelta=25.232836634157856
Fitness changed from 37.25789902553923 to 12.025062391381375
Iteration 4 complete. Error: 12.025062391381375 Total: 1.6639; Orientation: 0.1659; Line Search: 1.0946
th(0)=12.025062391381375;dx=-5.57312907837305E-4
New Minimum: 12.025062391381375 > 9.479934901699483
WOLF (strong): th(33419.43960201202)=9.479934901699483; dx=4.0499871452084906E-4 evalInputDelta=2.5451274896818923
New Minimum: 9.479934901699483 > 6.732509262550369
END: th(16709.71980100601)=6.732509262550369; dx=-7.61570963491977E-5 evalInputDelta=5.292553128831006
Fitness changed from 12.025062391381375 to 6.732509262550369
Iteration 5 complete. Error: 6.732509262550369 Total: 2.2143; Orientation: 0.1676; Line Search: 1.5928
th(0)=6.732509262550369;dx=-3.708985639383824E-4
Armijo: th(36000.000000000015)=17.627869413121893; dx=9.761963501137485E-4 evalInputDelta=-10.895360150571523
New Minimum: 6.732509262550369 > 6.118262224089012
WOLF (strong): th(18000.000000000007)=6.118262224089012; dx=3.0264889350489137E-4 evalInputDelta=0.6142470384613574
New Minimum: 6.118262224089012 > 5.180665327870138
END: th(6000.000000000003)=5.180665327870138; dx=-1.4638274440097236E-4 evalInputDelta=1.5518439346802317
Fitness changed from 6.732509262550369 to 5.180665327870138
Iteration 6 complete. Error: 5.180665327870138 Total: 2.9684; Orientation: 0.1744; Line Search: 2.4041
th(0)=5.180665327870138;dx=-1.278459813885635E-4
New Minimum: 5.180665327870138 > 3.764550061030847
END: th(12926.608140191309)=3.764550061030847; dx=-9.125484598932206E-5 evalInputDelta=1.4161152668392907
Fitness changed from 5.180665327870138 to 3.764550061030847
Iteration 7 complete. Error: 3.764550061030847 Total: 1.6445; Orientation: 0.1752; Line Search: 1.0618
th(0)=3.764550061030847;dx=-7.66679616610984E-5
New Minimum: 3.764550061030847 > 2.1522184246023484
END: th(27849.53300167669)=2.1522184246023484; dx=-3.9120812403577E-5 evalInputDelta=1.6123316364284985
Fitness changed from 3.764550061030847 to 2.1522184246023484
Iteration 8 complete. Error: 2.1522184246023484 Total: 1.7459; Orientation: 0.1672; Line Search: 1.1707
th(0)=2.1522184246023484;dx=-4.845127679790078E-5
Armijo: th(60000.00000000004)=5.229461883743897; dx=1.510260588971959E-4 evalInputDelta=-3.077243459141549
Armijo: th(30000.00000000002)=2.1947601298777704; dx=5.128739107574831E-5 evalInputDelta=-0.042541705275422004
New Minimum: 2.1522184246023484 > 1.8339367638919448
END: th(10000.000000000005)=1.8339367638919448; dx=-1.5205054196029235E-5 evalInputDelta=0.31828166071040354
Fitness changed from 2.1522184246023484 to 1.8339367638919448
Iteration 9 complete. Error: 1.8339367638919448 Total: 2.7190; Orientation: 0.1779; Line Search: 2.1206
th(0)=1.8339367638919448;dx=-3.3462913134051946E-5
New Minimum: 1.8339367638919448 > 1.5380680077573579
WOLF (strong): th(21544.34690031885)=1.5380680077573579; dx=5.996890585611136E-6 evalInputDelta=0.29586875613458696
END: th(10772.173450159426)=1.5797354240755923; dx=-1.3733011279018845E-5 evalInputDelta=0.2542013398163525
Fitness changed from 1.8339367638919448 to 1.5380680077573579
Iteration 10 complete. Error: 1.5380680077573579 Total: 2.2696; Orientation: 0.1667; Line Search: 1.6997
th(0)=1.5380680077573579;dx=-8.81429905100117E-5
Armijo: th(23207.94416806391)=3.0069214773606454; dx=2.1472494527437636E-4 evalInputDelta=-1.4688534696032876
New Minimum: 1.5380680077573579 > 1.3938769718746378
WOLF (strong): th(11603.972084031955)=1.3938769718746378; dx=6.329097748241504E-5 evalInputDelta=0.1441910358827201
New Minimum: 1.3938769718746378 > 1.2947559358973326
END: th(3867.9906946773185)=1.2947559358973326; dx=-3.766500133958117E-5 evalInputDelta=0.24331207186002524
Fitness changed from 1.5380680077573579 to 1.2947559358973326
Iteration 11 complete. Error: 1.2947559358973326 Total: 2.9469; Orientation: 0.1854; Line Search: 2.2840
th(0)=1.2947559358973326;dx=-2.1769733223180584E-5
New Minimum: 1.2947559358973326 > 1.1603302883392659
END: th(8333.33333333334)=1.1603302883392659; dx=-1.0492421948665055E-5 evalInputDelta=0.13442564755806674
Fitness changed from 1.2947559358973326 to 1.1603302883392659
Iteration 12 complete. Error: 1.1603302883392659 Total: 1.6372; Orientation: 0.1661; Line Search: 1.0549
Final threshold in iteration 12: 1.1603302883392659 (> 0.0) after 30.143s (< 30.000s)
Returns
1.1603302883392659
This training apply resulted in the following configuration:
TrainingTester.java:610 executed in 0.00 seconds (0.000 gc):
RefList<double[]> state = network.state();
assert state != null;
String description = state.stream().map(RefArrays::toString).reduce((a, b) -> a + "\n" + b)
.orElse("");
state.freeRef();
return description;
Returns
TrainingTester.java:622 executed in 0.01 seconds (0.000 gc):
return RefArrays.stream(RefUtil.addRef(data)).flatMap(x -> {
return RefArrays.stream(x);
}).limit(1).map(x -> {
String temp_18_0015 = x.prettyPrint();
x.freeRef();
return temp_18_0015;
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
[ [ -0.4459620963186723, 1.2795631461234898, -0.5241346109082422, -0.02798742782299276, -1.449306827919305, -0.7295060360405917, 0.5460811281956766 ], [ 1.2412406073904783, -2.071632499866307, 0.5842171418378787, -0.4204855172782283, -1.0124687930459964, 0.4705335052184897, 1.174320335772175 ], [ 0.1447758065230151, -0.6475993401289676, -1.213758718959628, -0.716893219301835, -1.3696891698592202, -2.0031086982654527, 0.5136346221847892 ], [ -1.9410841880930734, -0.9491428247409194, -3.0530756140765885, 0.22604317599374224, -1.2084870335942584, 0.7110198299169272, 1.8513835669660295 ], [ -1.766512323331841, 0.03741025963427052, -0.94597176113576, 0.9412632782987461, -0.02772777703999505, 0.5100531665728726, 2.102586133111382 ], [ -0.06002928252587371, -0.8941075237248092, 0.36865343008909407, 0.06888948707169205, -1.4294546781950785, -0.23534728863664933, -0.8746072595597023 ], [ 0.3431909987893688, -1.4288523330311098, 1.3411613798922435, 0.09987552386740008, 0.19597007270998515, -1.3820028331559826, 0.6488873974956817 ], [ -0.6197355373873434, -0.5919608397854097, 2.3307444742938124, -0.16490450772851284, 0.8479042338903242, 0.46307174808556895, -0.13433989606776706 ], ... ],
[ [ 0.19677291402042962, -0.5210095411943574, 1.2860303636336106, -0.6128105650816271, 0.2999941023167736, -1.4900582619017475, -0.5943513870034897 ], [ 0.11057022899243273, 0.003039613856921107, -1.1959319895182705, 1.2393866787623156, -0.8181453435692412, 0.8034206576981021, -1.838021219203026 ], [ -0.4770604632713114, -1.6473738465489414, 0.831898706576038, -2.1028136654998, -0.9891223423338716, -0.6954384662560107, 1.6695403492095164 ], [ -1.4006817364621247, 0.83132694819974, 0.9581951793333058, 0.61869233851422, 0.47680917945584583, 0.3317933802552279, -1.3844864718447627 ], [ -0.46374149262313213, -2.428912521494755, -0.9644082959037865, -1.5356401951222889, 0.5483389235420943, -0.9449709650153597, -0.33822220732061475 ], [ -1.5024095319868631, -0.8679350281985914, -0.35029853926402604, -2.563397151519158, -0.10176124694137732, -1.006717370039761, -1.2322283448777924 ], [ 0.255987047976963, 1.2578374460990105, -1.9246323036438089, -0.3879013305488075, 0.5435285131064493, -0.25376635721710494, 2.35880381056936 ], [ 1.0001893364014365, -0.5187611465911682, -0.8036438731495082, -1.2178713889585953, -0.45861086398240725, 0.07611154462084456, 0.3930628875885727 ], ... ],
[ [ 0.37851418380768576, 0.35206320142633507, 2.018485919344864, -0.455791728579281, 1.0916673193926656, 1.3791003009858087, 1.4728784836040312 ], [ 0.29746234791815995, 0.3334176702338196, -0.3285470580740216, 0.34282157714116146, -1.341391049191293, -1.089655346908986, -2.1395819550562245 ], [ -1.549863401191155, -0.9589352654353274, -0.0032229160262305344, -0.43756802665432026, 0.3709285745794081, -0.09689019149999112, 0.5342439809515526 ], [ 0.1569554031025826, -0.10703757453851347, 0.6239419003375766, -0.8921482644196341, -0.350141936256413, 2.3003232449601074, 1.3479854175904789 ], [ 1.4435470508640502, 0.34147687102671054, 0.05284310430351192, -0.5175724409914354, -0.519097772770962, 0.08912644408165796, 1.9962470579866602 ], [ 0.5524742614643385, 0.8076452392056861, 2.2244162741187563, 0.11269498096323573, 1.306866339543819, -0.4791810252588749, -1.5945706492876432 ], [ -0.6150271993254336, -0.5135982737945697, -1.4079868655107826, 0.20280559102477927, -0.28926084203381025, 0.9104456971838766, -1.6435839228013707 ], [ -2.6522403245286, 1.3731851930093462, 0.35907911874063, -0.28064338023391894, -0.4887637303079294, 0.21873755243060428, -2.5684710321216087 ], ... ],
[ [ 0.869363461932135, 0.466219874534083, 1.4481273057297028, -1.5270206984423917, -0.5664808687868176, 0.34654888576408727, -1.23486602601961 ], [ -0.5951848723232759, 0.9983909685381754, -2.5823334261169526, 0.2811703982785426, 1.6888105245065426, -1.646995722230852, 1.3339231588351868 ], [ 0.4709492140085167, -1.0506123803385177, -0.17256030883569923, -1.8010552815993708, 0.7693559579394608, -2.4535715644886804, -0.7908287676035359 ], [ 0.054296097222654716, 1.3495014507573722, 2.246056622663497, 0.5675034589818145, 0.5235505246619653, 0.2780409490248793, 0.9820578801160234 ], [ -0.21051472239514776, 0.49786024648414484, -0.8980675257606111, 0.8891053968711561, -0.05542479620875611, 0.6268643972891217, 1.1126384667901266 ], [ 1.812101300106731, 0.07150792253544247, -0.038505546299264115, 1.477910323745351, 1.1542469432196196, 2.0266382475402946, 1.1761271143337249 ], [ 0.24642075280974743, -1.0594810954063851, 0.8115689609311582, -0.09702014040743077, 0.41992077092470814, -0.2795772024676163, -0.5243384053544039 ], [ 1.7408468925278366, -0.7222832514621867, -0.3489225521217555, 1.3395631908312131, -0.7669294145834151, -1.308858738207464, -0.64464923035273 ], ... ],
[ [ -1.7568268973302203, 0.22656133150560784, 1.0588487699179803, 0.8446879632762206, 0.406485804117276, -0.5566901277627007, 1.0299882676093755 ], [ -1.3827428038071343, 1.7665706852410143, -0.6839446984323274, 1.1769454255139726, 1.2873229833877506, -1.3702341262025746, 1.0214761031821187 ], [ 1.5371333909757146, 0.7158093628734139, -0.7558392296087986, 1.1465234948278868, 0.464785952050218, 0.927014390381333, 0.09442247901911424 ], [ 1.0843224479905318, 1.2370537255459109, -1.0152257419715986, 0.9140486612828241, 1.4557997611078473, 0.25724907231178995, 1.5870416590948844 ], [ -0.859448789840939, 0.7957767970137138, -0.4517537690571634, 0.7998724547937143, 0.5554756964618033, 1.5719028872065335, -0.7544048386295793 ], [ 0.7579425823057707, 0.44346833188292384, 0.15860657248764756, 0.3804405309413347, -1.2944075476853731, -0.10752282910563948, 0.5900937733445614 ], [ 0.504523240766075, 0.3001403296829896, 0.05133026599407828, 1.0554528003597639, -2.5734917898823175, 0.37431362294788845, -1.8171544025496558 ], [ -0.3266633679403602, 0.0049529314537115786, 0.420790674833112, -0.5005317711479882, -1.1296110069073535, 0.7879671704437406, 0.21143614631823132 ], ... ],
[ [ 0.14240834109670109, 1.2776363761699479, 2.2711162312145423, 1.3921538939099831, -0.8683104054921374, -0.8152191520257714, 0.12960023494845094 ], [ -0.20010329588648224, 0.21856267760751072, -0.3824984466187471, 1.6748481207973442, -0.08114700772484645, 0.4810186254875454, -2.9200748363528892 ], [ 0.2824702077297537, -0.13285628323279305, -1.5917376419803746, 2.0723729426104067, 0.5348870270516746, 0.45104934823818277, -0.61752192387534 ], [ -0.32500355732011355, 0.17116649804183937, 0.12028024372637452, -1.8194961799874307, 0.9034121692157386, -1.6317644280631205, -2.337850335899223 ], [ 0.4788529667372088, 2.158289854597658, 0.323367742351827, -0.247902693827733, 0.44852947933308757, -0.001875826219186645, -0.8182257332734084 ], [ 1.3012247750448707, 0.3901843869001607, 0.27038255561563107, 0.31094820637922277, 0.837666195724867, 0.4713446301230788, -1.2695657734032062 ], [ 0.38851418371983804, 0.567758586797451, -1.6518811282039831, 0.25300812137154305, -0.8694066536792033, 0.046535795854264504, 0.9505981067887102 ], [ -1.7044850800069837, -1.0584923491956464, 0.24310285331228795, 0.16466645638345048, -0.9169861911221553, -0.9555529107818619, -0.7016670479081663 ], ... ],
[ [ 1.5897719191687616, 1.165521932307027, -1.399356944237108, -2.8475986558661703, 0.03085289767470945, -1.9263862220135404, 1.1542249099064683 ], [ 0.34516448082121975, -0.7487156745846366, 1.0926936456017258, 0.7677595599758301, 0.015522058873601577, 0.7808428063842232, 1.7675140883813998 ], [ -0.7709893978539111, 0.24823545201883918, -1.841290618762778, 2.6733814367766806, -0.4729169440259706, -0.2557509782924923, -1.8249180877949185 ], [ 0.13722270951404433, 0.5520550002698736, 0.06401240934157047, -1.0172057278714906, -0.8034437726567721, -0.7291473126782366, 0.39324025687238634 ], [ -1.1484194641348369, -0.04992699289778919, -0.4126384715178877, 0.36916027849342653, -0.2440140022494366, -1.9759581238385449, 0.0798167837671223 ], [ -1.0317609971280106, 0.9163896578473024, 0.7451008628169933, 0.12014128010995652, 1.0819496299142635, -1.5671251907461456, -0.21921028857833574 ], [ 0.7325488912092648, 0.360021662184028, 1.8530773141978543, -0.24072898542463816, 0.44135344749164757, 0.5278334348572207, 2.255973463789927 ], [ 1.168704220995519, -0.11159015634197307, -0.8268115657529326, 1.1945002612720776, -0.027206711555278557, 0.6413264044790856, -0.44461873120624906 ], ... ],
[ [ 1.2011842489870719, 2.1240568108359983, 0.6196129169295054, -0.2891251473266568, -0.707112279997478, 1.4754904786392402, -0.5997330239976548 ], [ 2.2358870101255706, -1.7754982683837237, -1.9129753611789253, 0.6811484888184128, 0.14386415298316096, -2.629909939010665, 0.8169063054281684 ], [ 0.8459549555201561, -1.340972250001936, -1.1172580825309288, -1.8894121565122264, 0.9807338375644842, 1.279864419565684, -0.22163528792734735 ], [ -0.9173966285418678, 0.8668159003642515, 0.48041004742392157, -0.4504891745213825, 1.3176498416437792, 0.6670643458065619, -0.47055742950748936 ], [ 1.3255937883356703, -0.552242823477735, 0.05223109104656489, -0.6657861118868238, -0.9036915499305181, -0.07994370402789631, 0.2534118357128408 ], [ 0.9037440656332079, 0.949904969114421, 0.5016506001029154, 0.3492715459259561, -0.28623590291035644, 0.8462004936931253, 2.046996591997735 ], [ -2.256206473318365, -0.8121693096992507, -0.8324126712380231, -0.0519706257700042, -1.01849428953778, -2.1025062427048415, -1.0395650755814791 ], [ -0.9829177364848993, -0.08152637176519927, -0.6133121958269042, 0.6385156725197095, 0.14398326192083374, -0.5954773948083788, 0.8742932762596949 ], ... ],
...
]
To produce the following output:
TrainingTester.java:633 executed in 0.17 seconds (0.000 gc):
Result[] array = ConstantResult.batchResultArray(pop(RefUtil.addRef(data)));
@Nullable
Result eval = layer.eval(array);
assert eval != null;
TensorList tensorList = Result.getData(eval);
String temp_18_0016 = tensorList.stream().limit(1).map(x -> {
String temp_18_0017 = x.prettyPrint();
x.freeRef();
return temp_18_0017;
}).reduce((a, b) -> a + "\n" + b).orElse("");
tensorList.freeRef();
return temp_18_0016;
Returns
[
[ [ -6.7027482986450195, -3.460630416870117, 0.33659666776657104, -9.568424224853516, 1.57184636592865 ], [ 7.399273872375488, -4.263027191162109, 5.127710819244385, -4.595834255218506, 2.0985429286956787 ], [ -1.0169320106506348, 12.64914608001709, -2.585261344909668, -6.233014106750488, -7.371077537536621 ], [ 4.67346715927124, -3.7553303241729736, -5.263850212097168, 13.36671257019043, -6.505373477935791 ], [ 11.351330757141113, -13.184979438781738, 4.514247417449951, -11.43898868560791, 2.99819278717041 ], [ 3.2528321743011475, -8.853670120239258, 9.665589332580566, -9.016194343566895, 6.533965110778809 ], [ -6.510373115539551, 7.178611755371094, 8.91153335571289, -4.958842754364014, 1.9341208934783936 ], [ -2.2072837352752686, 7.995555400848389, 2.8155758380889893, -7.695056438446045, 11.934414863586426 ], ... ],
[ [ -0.23056933283805847, 10.70459270477295, -16.031997680664062, 5.191644668579102, -20.99563980102539 ], [ 9.072686195373535, -6.766602516174316, 2.750983953475952, -4.8769049644470215, -10.231955528259277 ], [ -3.4071872234344482, -12.187495231628418, 8.632875442504883, 1.8007582426071167, 16.905006408691406 ], [ 18.347938537597656, 4.353494644165039, 19.076457977294922, -4.22767448425293, -2.9344277381896973 ], [ 7.7079057693481445, -1.445499062538147, 5.931585788726807, 0.2583519220352173, -15.18983268737793 ], [ 4.551599979400635, 4.636972904205322, -10.512900352478027, 12.789074897766113, -33.00521469116211 ], [ 11.19114875793457, -5.666370868682861, 8.406420707702637, -8.203885078430176, -13.062529563903809 ], [ 9.469767570495605, 1.5189998149871826, -2.0989065170288086, -2.4581265449523926, 0.3980444669723511 ], ... ],
[ [ 1.2847309112548828, -2.160459280014038, 0.27193683385849, 10.117429733276367, 4.133318901062012 ], [ -0.9828230738639832, 2.7305006980895996, -10.93364429473877, -10.102508544921875, -8.021013259887695 ], [ -11.408740997314453, 0.29444724321365356, 9.63527774810791, 6.341127872467041, 15.652510643005371 ], [ 10.599784851074219, -12.937950134277344, 20.407793045043945, -2.901918411254883, -6.129191875457764 ], [ -6.528850078582764, -0.3620871305465698, 9.91987133026123, -4.348082065582275, 6.824220657348633 ], [ 10.64875602722168, -0.13031728565692902, -13.551607131958008, 15.330726623535156, -0.20539575815200806 ], [ -0.02041839435696602, -16.942293167114258, -10.128985404968262, 9.892562866210938, -5.302027225494385 ], [ 1.4044407606124878, -10.692537307739258, 11.614710807800293, 8.501543045043945, 3.4764604568481445 ], ... ],
[ [ 13.405065536499023, 3.5737709999084473, 5.883342742919922, 20.752967834472656, -10.795114517211914 ], [ -11.679001808166504, -4.831206321716309, -1.9866441488265991, 12.17142105102539, 1.0919318199157715 ], [ -7.904871463775635, -10.881635665893555, 0.48584863543510437, 5.554669380187988, -6.721153736114502 ], [ 2.7440409660339355, 1.856793761253357, 5.172661781311035, 2.3021814823150635, -9.572249412536621 ], [ -8.661955833435059, 13.289034843444824, -5.769183158874512, 3.230158805847168, 11.894346237182617 ], [ 2.0634605884552, 7.202840805053711, 3.0453031063079834, -9.260065078735352, 15.56387996673584 ], [ -7.477766990661621, 22.150619506835938, 1.510024905204773, 0.4454067647457123, 4.043114185333252 ], [ -9.015790939331055, 15.549656867980957, 0.851070761680603, 2.372589111328125, 0.12065093219280243 ], ... ],
[ [ 6.81417179107666, 3.423884868621826, -2.60962176322937, 21.75011444091797, -14.485238075256348 ], [ -6.698502063751221, -20.462589263916016, -9.511069297790527, 6.887683868408203, -5.893391132354736 ], [ 16.277236938476562, -6.688841342926025, -8.923450469970703, -12.493741989135742, -2.07850980758667 ], [ 11.300228118896484, -13.613240242004395, -3.5484769344329834, -3.3852035999298096, 10.327169418334961 ], [ -3.7351455688476562, 5.348568439483643, 1.98663330078125, -19.287214279174805, -5.26731014251709 ], [ -15.98887825012207, -3.636242628097534, 5.394049167633057, -10.83456802368164, -0.7612074613571167 ], [ -11.902006149291992, 16.548397064208984, -17.462467193603516, -14.352395057678223, 5.39129638671875 ], [ 1.9665849208831787, -2.2318389415740967, 2.0003206729888916, -8.262446403503418, 7.145226001739502 ], ... ],
[ [ -20.61429786682129, 6.4640793800354, -0.32691720128059387, -6.407567977905273, 10.700239181518555 ], [ -26.8924560546875, 10.315019607543945, -13.968664169311523, -8.341763496398926, -5.220002174377441 ], [ 7.660732269287109, -9.277942657470703, 3.0905301570892334, -8.441445350646973, -4.9627366065979 ], [ -11.094647407531738, -2.648695230484009, -9.731330871582031, 8.594316482543945, 4.464332580566406 ], [ 2.7961103916168213, 0.02928807958960533, -12.203869819641113, 4.872021198272705, 6.5662126541137695 ], [ -10.714338302612305, 1.5542194843292236, -9.716134071350098, 9.58432388305664, 10.945630073547363 ], [ -12.816468238830566, 2.016815662384033, 4.799051761627197, 3.335911512374878, 3.4139833450317383 ], [ 11.097762107849121, 10.073404312133789, 0.1352212131023407, 8.878497123718262, -33.42695236206055 ], ... ],
[ [ -10.799118041992188, 2.503023624420166, -14.801082611083984, 8.747838020324707, 2.0837414264678955 ], [ -17.681692123413086, 10.806960105895996, -21.174663543701172, -16.768476486206055, 17.69919776916504 ], [ -20.620466232299805, 5.181473255157471, -6.1837286949157715, -12.649867057800293, 9.32844066619873 ], [ 1.6774309873580933, -1.2142411470413208, -0.8777747750282288, 25.27364158630371, -3.4862046241760254 ], [ 1.0207922458648682, -11.92831039428711, 13.627257347106934, 14.92259407043457, -2.2573111057281494 ], [ -0.946707546710968, -0.8849620223045349, -11.058878898620605, 8.730231285095215, -12.972736358642578 ], [ -0.018986210227012634, -13.268807411193848, -10.44686508178711, 7.19279146194458, 15.116413116455078 ], [ -5.128870487213135, 9.114394187927246, -14.021891593933105, -8.766364097595215, -1.6122055053710938 ], ... ],
[ [ 6.073870658874512, -1.5185856819152832, 5.113387107849121, -12.7799711227417, -4.01752233505249 ], [ -7.591983795166016, 3.323171615600586, 3.297327995300293, -14.274462699890137, 4.835238933563232 ], [ 1.9797202348709106, 13.20138931274414, -22.834020614624023, -3.1815099716186523, -13.304792404174805 ], [ -3.557997941970825, 4.0606513023376465, -10.845544815063477, -1.9283888339996338, -9.44731330871582 ], [ -20.42689323425293, 6.115471839904785, -7.6629228591918945, -11.807260513305664, -7.38478422164917 ], [ 4.527833461761475, -9.692190170288086, 3.9056198596954346, -4.221725940704346, -6.477119445800781 ], [ -24.786941528320312, 2.938234567642212, 1.0818243026733398, -17.63804817199707, -3.3606035709381104 ], [ -12.389277458190918, -1.9213967323303223, -7.646297931671143, -5.423928737640381, 8.04869556427002 ], ... ],
...
]
First, we use a conjugate gradient descent method, which converges the fastest for purely linear functions.
TrainingTester.java:452 executed in 31.16 seconds (0.790 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new QuadraticSearch());
iterativeTrainer.setOrientation(new GradientDescent());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 13147009537276
Reset training subject: 13147482184116
Constructing line search parameters: GD
F(0.0) = LineSearchPoint{point=PointSample{avg=233.5098803469944}, derivative=-0.03930302224877376}
New Minimum: 233.5098803469944 > 233.50988034699327
F(1.0E-10) = LineSearchPoint{point=PointSample{avg=233.50988034699327}, derivative=-0.03930302224877205}, evalInputDelta = -1.1368683772161603E-12
F(7.000000000000001E-10) = LineSearchPoint{point=PointSample{avg=233.50988034699327}, derivative=-0.03930302224877205}, evalInputDelta = -1.1368683772161603E-12
F(4.900000000000001E-9) = LineSearchPoint{point=PointSample{avg=233.50988034699327}, derivative=-0.03930302224877205}, evalInputDelta = -1.1368683772161603E-12
F(3.430000000000001E-8) = LineSearchPoint{point=PointSample{avg=233.50988034699327}, derivative=-0.03930302224877205}, evalInputDelta = -1.1368683772161603E-12
New Minimum: 233.50988034699327 > 233.5098803459686
F(2.4010000000000004E-7) = LineSearchPoint{point=PointSample{avg=233.5098803459686}, derivative=-0.03930302224861591}, evalInputDelta = -1.0257963367621414E-9
New Minimum: 233.5098803459686 > 233.50988031732732
F(1.6807000000000003E-6) = LineSearchPoint{point=PointSample{avg=233.50988031732732}, derivative=-0.039303022245569294}, evalInputDelta = -2.966709189422545E-8
New Minimum: 233.50988031732732 > 233.50987988003808
F(1.1764900000000001E-5) = LineSearchPoint{point=PointSample{avg=233.50987988003808}, derivative=-0.03930302220054368}, evalInputDelta = -4.669563224979356E-7
New Minimum: 233.50987988003808 > 233.50987711071485
F(8.235430000000001E-5) = LineSearchPoint{point=PointSample{avg=233.50987711071485}, derivative=-0.039303021912026045}, evalInputDelta = -3.2362795536755584E-6
New Minimum: 233.50987711071485 > 233.50985764422109
F(5.764801000000001E-4) = LineSearchPoint{point=PointSample{avg=233.50985764422109}, derivative=-0.039303019866191495}, evalInputDelta = -2.2702773321725545E-5
New Minimum: 233.50985764422109 > 233.5097217690348
F(0.004035360700000001) = LineSearchPoint{point=PointSample{avg=233.5097217690348}, derivative=-0.039303005563699776}, evalInputDelta = -1.5857795960982912E-4
New Minimum: 233.5097217690348 > 233.5087701241863
F(0.028247524900000005) = LineSearchPoint{point=PointSample{avg=233.5087701241863}, derivative=-0.039302905429882795}, evalInputDelta = -0.001110222808108574
New Minimum: 233.5087701241863 > 233.50210891520297
F(0.19773267430000002) = LineSearchPoint{point=PointSample{avg=233.50210891520297}, derivative=-0.039302204522809706}, evalInputDelta = -0.007771431791439909
New Minimum: 233.50210891520297 > 233.4554838524159
F(1.3841287201) = LineSearchPoint{point=PointSample{avg=233.4554838524159}, derivative=-0.03929729814296322}, evalInputDelta = -0.05439649457849782
New Minimum: 233.4554838524159 > 233.1292713036557
F(9.688901040700001) = LineSearchPoint{point=PointSample{avg=233.1292713036557}, derivative=-0.03926295351428024}, evalInputDelta = -0.38060904333869416
New Minimum: 233.1292713036557 > 230.85377007409141
F(67.8223072849) = LineSearchPoint{point=PointSample{avg=230.85377007409141}, derivative=-0.03902254111633957}, evalInputDelta = -2.6561102729029926
New Minimum: 230.85377007409141 > 215.3165892786102
F(474.7561509943) = LineSearchPoint{point=PointSample{avg=215.3165892786102}, derivative=-0.03733965433502465}, evalInputDelta = -18.193291068384212
New Minimum: 215.3165892786102 > 125.73138367106998
F(3323.2930569601003) = LineSearchPoint{point=PointSample{avg=125.73138367106998}, derivative=-0.025559446859260787}, evalInputDelta = -107.77849667592443
F(23263.0513987207) = LineSearchPoint{point=PointSample{avg=438.2129058461891}, derivative=0.0569020054609391}, evalInputDelta = 204.70302549919467
F(1789.4654922092848) = LineSearchPoint{point=PointSample{avg=169.79984660449117}, derivative=-0.03190263550045281}, evalInputDelta = -63.71003374250324
New Minimum: 125.73138367106998 > 65.63711544622775
F(12526.258445464993) = LineSearchPoint{point=PointSample{avg=65.63711544622775}, derivative=0.012499684981447691}, evalInputDelta = -167.87276490076664
65.63711544622775 <= 233.5098803469944
New Minimum: 65.63711544622775 > 46.74689384776194
F(9503.74682520036) = LineSearchPoint{point=PointSample{avg=46.74689384776194}, derivative=3.3827327874588753E-12}, evalInputDelta = -186.76298649923245
Right bracket at 9503.74682520036
Converged to right
Fitness changed from 233.5098803469944 to 46.74689384776194
Iteration 1 complete. Error: 46.74689384776194 Total: 14.8117; Orientation: 0.1781; Line Search: 13.2654
F(0.0) = LineSearchPoint{point=PointSample{avg=46.74689384776194}, derivative=-0.005064082287010914}
New Minimum: 46.74689384776194 > 21.065076065296267
F(9503.74682520036) = LineSearchPoint{point=PointSample{avg=21.065076065296267}, derivative=-3.4048462201805057E-4}, evalInputDelta = -25.68181778246567
F(66526.22777640252) = LineSearchPoint{point=PointSample{avg=809.7035723837622}, derivative=0.028001101383939388}, evalInputDelta = 762.9566785360003
F(5117.402136646348) = LineSearchPoint{point=PointSample{avg=27.33994225024063}, derivative=-0.002520606622503783}, evalInputDelta = -19.40695159752131
F(35821.81495652443) = LineSearchPoint{point=PointSample{avg=184.23397655315625}, derivative=0.012740247377175731}, evalInputDelta = 137.4870827053943
F(2755.5242274249563) = LineSearchPoint{point=PointSample{avg=34.67962557694659}, derivative=-0.0036945184669901028}, evalInputDelta = -12.067268270815347
F(19288.669591974693) = LineSearchPoint{point=PointSample{avg=41.52720788920597}, derivative=0.004522864456612595}, evalInputDelta = -5.219685958555971
41.52720788920597 <= 46.74689384776194
New Minimum: 21.065076065296267 > 20.948452329367385
F(10188.792389578446) = LineSearchPoint{point=PointSample{avg=20.948452329367385}, derivative=-6.644383529702882E-13}, evalInputDelta = -25.798441518394554
Left bracket at 10188.792389578446
Converged to left
Fitness changed from 46.74689384776194 to 20.948452329367385
Iteration 2 complete. Error: 20.948452329367385 Total: 5.4122; Orientation: 0.1626; Line Search: 4.8510
F(0.0) = LineSearchPoint{point=PointSample{avg=20.948452329367385}, derivative=-0.001772593274104537}
New Minimum: 20.948452329367385 > 12.226355065709498
F(10188.792389578446) = LineSearchPoint{point=PointSample{avg=12.226355065709498}, derivative=6.049689962698144E-5}, evalInputDelta = -8.722097263657886
12.226355065709498 <= 20.948452329367385
New Minimum: 12.226355065709498 > 12.216183802860481
F(9852.534872438562) = LineSearchPoint{point=PointSample{avg=12.216183802860481}, derivative=-1.193296729604023E-12}, evalInputDelta = -8.732268526506903
Left bracket at 9852.534872438562
Converged to left
Fitness changed from 20.948452329367385 to 12.216183802860481
Iteration 3 complete. Error: 12.216183802860481 Total: 2.6645; Orientation: 0.1672; Line Search: 2.0925
F(0.0) = LineSearchPoint{point=PointSample{avg=12.216183802860481}, derivative=-7.915675510563101E-4}
New Minimum: 12.216183802860481 > 8.130413893867889
F(9852.534872438562) = LineSearchPoint{point=PointSample{avg=8.130413893867889}, derivative=-3.781695892765573E-5}, evalInputDelta = -4.085769908992592
F(68967.74410706994) = LineSearchPoint{point=PointSample{avg=139.5692283956882}, derivative=0.004484686594791491}, evalInputDelta = 127.35304459282773
F(5305.211085159226) = LineSearchPoint{point=PointSample{avg=9.093352472324154}, derivative=-3.8570184828251456E-4}, evalInputDelta = -3.122831330536327
F(37136.47759611458) = LineSearchPoint{point=PointSample{avg=35.57363230735177}, derivative=0.0020494923742358034}, evalInputDelta = 23.35744850449129
F(2856.6521227780445) = LineSearchPoint{point=PointSample{avg=10.267101442609812}, derivative=-5.73024480630436E-4}, evalInputDelta = -1.949082360250669
F(19996.564859446313) = LineSearchPoint{point=PointSample{avg=11.682939354128319}, derivative=7.382339466460488E-4}, evalInputDelta = -0.5332444487321624
11.682939354128319 <= 12.216183802860481
New Minimum: 8.130413893867889 > 8.121067081304648
F(10346.85343105229) = LineSearchPoint{point=PointSample{avg=8.121067081304648}, derivative=3.7732071292298844E-13}, evalInputDelta = -4.095116721555833
Right bracket at 10346.85343105229
Converged to right
Fitness changed from 12.216183802860481 to 8.121067081304648
Iteration 4 complete. Error: 8.121067081304648 Total: 5.5958; Orientation: 0.1691; Line Search: 5.0215
F(0.0) = LineSearchPoint{point=PointSample{avg=8.121067081304648}, derivative=-4.535020536581535E-4}
New Minimum: 8.121067081304648 > 5.847637758624293
F(10346.85343105229) = LineSearchPoint{point=PointSample{avg=5.847637758624293}, derivative=1.405844185203733E-5}, evalInputDelta = -2.2734293226803555
5.847637758624293 <= 8.121067081304648
New Minimum: 5.847637758624293 > 5.845450932939826
F(10035.747940514048) = LineSearchPoint{point=PointSample{avg=5.845450932939826}, derivative=6.374809940990975E-14}, evalInputDelta = -2.275616148364822
Right bracket at 10035.747940514048
Converged to right
Fitness changed from 8.121067081304648 to 5.845450932939826
Iteration 5 complete. Error: 5.845450932939826 Total: 2.6779; Orientation: 0.1725; Line Search: 2.0901
Final threshold in iteration 5: 5.845450932939826 (> 0.0) after 31.162s (< 30.000s)
Returns
5.845450932939826
This training apply resulted in the following configuration:
TrainingTester.java:610 executed in 0.00 seconds (0.000 gc):
RefList<double[]> state = network.state();
assert state != null;
String description = state.stream().map(RefArrays::toString).reduce((a, b) -> a + "\n" + b)
.orElse("");
state.freeRef();
return description;
Returns
TrainingTester.java:622 executed in 0.01 seconds (0.000 gc):
return RefArrays.stream(RefUtil.addRef(data)).flatMap(x -> {
return RefArrays.stream(x);
}).limit(1).map(x -> {
String temp_18_0015 = x.prettyPrint();
x.freeRef();
return temp_18_0015;
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
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[ [ 0.6587197959433404, 0.45636917268339827, 1.3297303760511965, -0.9054363017736555, 1.3309510861385483, 1.2361877051804653, 1.726676352229036 ], [ 0.4923609561918109, 0.09548954395464516, -0.15477725318571345, -0.10548993703490825, -1.318794058777317, -1.1900936592197435, -1.8523934540611457 ], [ -1.9807519738497403, -0.9065928741582115, -0.48059484857360224, -0.6916923538102193, 0.28594535474589033, -0.22948689507971512, 0.5353668787395461 ], [ 0.08968944652748628, -0.10894293574551041, 0.8471941651686524, -1.061725174195054, -0.6379811834289322, 2.577199349222928, 1.6510206734220054 ], [ 0.5952297137438192, 0.8699710329509994, 0.10164442420821375, -0.32878897842496396, -0.6287982249743619, 0.5554033605757042, 2.244970053675204 ], [ 0.13953166729488184, 0.8640922616989335, 2.01962659810291, 0.7828403193587601, 0.7727191467967576, -0.3597821228028235, -0.8164092185050209 ], [ -0.6893660711963255, -0.4464394236298984, -1.369808758758794, 0.2526512837194875, 0.16599836850365798, 0.6286770109205861, -1.5269006378828849 ], [ -2.6496689610116855, 1.354063747297639, 0.351904034824995, -0.4348331184567407, -0.6952398401594861, -0.26456501877623395, -2.3850240788303605 ], ... ],
[ [ 1.0341255919392172, 0.5198543575295971, 1.0534815793741006, -1.3753383474638914, -0.8836696523857404, 0.06643969360599639, -1.2186152390753224 ], [ -0.17648465943130143, 1.1327240094360493, -2.5321990921792263, 0.6244144532518726, 1.4668761319847023, -1.6491304730416723, 1.075238384456206 ], [ 0.058236804189426936, -0.8963395433877273, -0.02496246325054246, -1.438143289809238, 0.90009011518545, -2.156481954686649, -0.9200629583940783 ], [ 0.15422103120655936, 1.3679214093497498, 2.0459211416323804, 0.6195440810854271, 0.23378360315025565, 0.40080095017924966, 1.478587523499846 ], [ -0.05746258766299778, 0.7718902890066606, -0.9846293915917333, 1.1695491318075601, 0.16836853678364705, 0.461709668673617, 0.8986492525979995 ], [ 1.8120311288450868, -0.27731391131834265, 0.009022779929818661, 1.5202568690492835, 1.2390004606390173, 1.7489248249510772, 0.9833777075023207 ], [ 0.6372235237440347, -0.7635867695966925, 1.13377536794208, -0.005966857346588, 0.5719578566980197, -0.35175950485316587, -0.38313559059984786 ], [ 1.9245372745685942, -0.8622806926136293, -0.6735970273036126, 1.2481986956803002, -0.7363390375272938, -0.5988182277070866, -0.5023633299103198 ], ... ],
[ [ -1.4677490694732875, -0.21337967694958318, 1.31462875725485, 0.3666383150363957, 0.4826688486527233, -1.048953206090752, 1.0830470249379887 ], [ -1.622918641045149, 1.6465058907983332, -0.49198010295983174, 1.1954788869645245, 0.9794151533061157, -1.3608827586620922, 0.8792966353868494 ], [ 1.7211179679321769, 0.702968374675885, -0.9010388593061358, 0.8563328283012945, 0.530527076868667, 1.311626489848587, -0.037599687427470635 ], [ 1.2339785752730663, 1.4483682084262697, -1.3628271485576586, 0.21053748994896254, 1.5508982307316326, 0.7304953572186161, 1.729429053467949 ], [ -0.5289491321613602, 0.7020307229567418, -0.7124580763880602, 0.9160486963694364, 0.32265337451261167, 1.3325060018141432, -0.8763882050719589 ], [ 0.6778728322882549, 0.005853792877361874, 0.25937251845661774, 0.1922000331115702, -1.534590674121199, -0.16643199651773866, 0.735994641965851 ], [ 0.227791353096445, 0.4307799733810832, 0.4155833463190468, 0.8889655093251844, -2.6226258668282227, 0.3020870397621487, -1.743440073027973 ], [ -0.47517032487965993, 0.08659065206884232, 0.10696478105712533, -0.15137031576102178, -0.8425816675921725, 0.8573324620195569, 0.2804022858460766 ], ... ],
[ [ 0.36243632752276805, 1.1774583640443368, 2.307538810837203, 1.0746242009792668, -0.6755921050554559, -0.6624425319700519, 0.5394042049706553 ], [ 0.01693923352209946, 0.5740492114634552, -0.029577963865649648, 2.006770128079062, -0.7921834685548423, -0.1592083925961968, -2.708132747141566 ], [ -0.02825764155477148, 0.3994879280933629, -1.8177183633779477, 2.3469886946891445, 0.30919324159755196, 0.7203918789899263, -0.3421433004922523 ], [ -0.5035121984116336, 0.24593406461234046, -0.15204736872025282, -1.6493703796131252, 1.1719864132807922, -1.5794306352589709, -1.825649199265293 ], [ 0.5655191978060913, 2.445319536012251, 0.23500961547577437, 0.11134735814006269, 2.962616208173757E-4, -0.18201199916466926, -0.45233346566433585 ], [ 1.5360532200550192, 0.6495659615730623, 0.5609357534640123, 0.5158238769135188, 0.05298047911131254, 0.4353671448576828, -0.9663201394657843 ], [ -0.011218623824667637, 0.5514030522173816, -1.8157517639403333, 0.6598886150974885, -0.9215803413607315, 0.16046920554982047, 1.1464078665189363 ], [ -1.9191980090980327, -1.4973415147658058, 0.10296239030281415, 0.29044446459911466, -1.1718122762679353, -1.4593920856343627, -0.5379238223900675 ], ... ],
[ [ 1.1358693699224789, 1.1330915846690854, -1.7104973054627126, -2.802015353206761, 0.19431162874479593, -1.6295180049989106, 1.005751691576917 ], [ -0.0743011300271284, -0.9696423937053661, 0.8496971743218998, 0.4549834322581599, -0.5043583387177024, 0.8573612036536274, 1.650287654248413 ], [ -0.5432811207041804, 0.3255879964323766, -1.195185680186779, 2.245023470943858, -0.3147209522559119, -0.5892132048311837, -1.5607637148296296 ], [ 0.21366895287810359, 0.7766771118587316, -0.33472216150751466, -1.0488048360568334, -0.6465967417691072, -0.5321529563808516, -0.16569986238042284 ], [ -0.8112428508921248, 0.003946022201541378, -0.15330574565552962, -0.30979987410491433, 0.27851784047410094, -2.0607465134800265, 0.18699178317958037 ], [ -0.9346795740937806, 1.381628645173923, 1.2784529525869175, 0.06812209660772502, 1.5742561420758863, -1.4607432993695937, -0.5246563955629119 ], [ 0.9108850667301858, 0.45456666572202886, 1.8774605305572971, -0.17237531917190366, 0.9371864018769409, 0.8215066257147882, 2.449398140419873 ], [ 1.3198531199042738, -0.2316694811314551, -0.5815160254348424, 1.3889968854110022, 0.29684063811773836, 0.6128561462833028, -0.31269788970236134 ], ... ],
[ [ 1.5728825965091726, 1.8556825591598833, 1.0065668143448034, -0.1764446314071962, -0.8006354623077119, 1.3443095867325945, -0.435044908084117 ], [ 2.487504481051949, -1.4124278886418917, -1.8969721675551239, 0.8171843903472197, 0.5350105981332667, -1.8405082894867604, 1.3259563510454018 ], [ 1.0386963958199507, -1.6701901783444517, -1.0108409965705152, -1.9390110187732403, 0.5091033631527181, 1.0007091679286595, 0.08281055060190193 ], [ -0.8709610073254687, 0.6301295656381541, 0.7493079366739043, 0.1269343213055896, 0.5992927533784422, 0.32418985801801226, -0.35212998006342533 ], [ 1.4597271615250793, -0.3948264394348808, 0.08914699005370146, -0.6335889147066903, -0.4916894381426903, 0.06337047236884237, 0.345829815770976 ], [ 1.07150805761104, 1.3156745016803904, 0.33082230082659925, 0.16742653462301965, -0.5296859606624498, 0.6191045493903437, 1.8412160735166079 ], [ -2.4739501272355424, -0.19468311451358086, -0.3400983332347074, 0.30828074500721364, -0.7569894154415914, -1.98077004426667, -0.8584891439969662 ], [ -1.220139069529788, -0.1265682317144296, -0.6791048050819238, 0.9068090903280313, 0.36910963173572486, -0.5099218371103447, 1.1489590053247896 ], ... ],
...
]
To produce the following output:
TrainingTester.java:633 executed in 0.15 seconds (0.000 gc):
Result[] array = ConstantResult.batchResultArray(pop(RefUtil.addRef(data)));
@Nullable
Result eval = layer.eval(array);
assert eval != null;
TensorList tensorList = Result.getData(eval);
String temp_18_0016 = tensorList.stream().limit(1).map(x -> {
String temp_18_0017 = x.prettyPrint();
x.freeRef();
return temp_18_0017;
}).reduce((a, b) -> a + "\n" + b).orElse("");
tensorList.freeRef();
return temp_18_0016;
Returns
[
[ [ -4.830136775970459, -0.4906982481479645, 4.138763427734375, -6.51487398147583, 0.3776671588420868 ], [ 4.972843170166016, -6.380191326141357, 8.480533599853516, -5.100482940673828, 3.4943268299102783 ], [ 1.199517846107483, 11.097468376159668, -0.021680649369955063, -2.679926872253418, -4.596068859100342 ], [ 1.8382320404052734, -3.3384947776794434, -0.9023476243019104, 12.267203330993652, -6.625454425811768 ], [ 7.768226623535156, -10.561980247497559, 7.42688512802124, -8.618616104125977, 3.295660972595215 ], [ 3.973410129547119, -6.389438629150391, 8.306645393371582, -6.823248386383057, 5.843715190887451 ], [ -2.8148531913757324, 4.838764667510986, 6.3853864669799805, -8.166762351989746, 0.20190100371837616 ], [ -1.1963391304016113, 9.58494758605957, 6.761702537536621, -9.153046607971191, 9.902667045593262 ], ... ],
[ [ -1.6727066040039062, 11.77029800415039, -16.903724670410156, 4.145473957061768, -19.441011428833008 ], [ 10.752523422241211, -7.026506423950195, 2.7723984718322754, -2.390063762664795, -12.30584716796875 ], [ -4.912228107452393, -13.985764503479004, 7.239348888397217, 2.582416296005249, 18.01471710205078 ], [ 15.45032787322998, 3.867239236831665, 18.34817123413086, -0.7717382907867432, -3.6445348262786865 ], [ 6.178481101989746, 0.537889838218689, 8.0255126953125, 3.3815860748291016, -15.600467681884766 ], [ 3.116564989089966, 6.7546281814575195, -7.957201957702637, 15.620030403137207, -34.00122833251953 ], [ 12.549667358398438, -3.18501353263855, 7.577359676361084, -5.672163009643555, -12.386828422546387 ], [ 11.92068862915039, 2.1788461208343506, -1.812854290008545, -1.60513174533844, 1.6609777212142944 ], ... ],
[ [ 1.4614050388336182, -4.92780876159668, -1.7006009817123413, 7.331750392913818, 2.3968288898468018 ], [ -2.792769193649292, 1.8886960744857788, -10.062499046325684, -7.799509525299072, -6.719012260437012 ], [ -13.520735740661621, 0.8757811188697815, 8.984885215759277, 4.72123384475708, 13.951862335205078 ], [ 8.088143348693848, -11.514585494995117, 21.377521514892578, -1.5780587196350098, -4.418961048126221 ], [ -5.426804065704346, 0.3565980792045593, 9.346514701843262, -3.3897783756256104, 7.171016216278076 ], [ 10.898232460021973, 0.3385617434978485, -11.10733413696289, 11.209970474243164, 1.2082418203353882 ], [ -1.0401406288146973, -19.384445190429688, -8.57618522644043, 7.862715721130371, -6.456948280334473 ], [ -0.5022002458572388, -11.319355010986328, 10.387504577636719, 6.399225234985352, 0.9309375882148743 ], ... ],
[ [ 12.937220573425293, 0.7718073129653931, 5.103743076324463, 18.674518585205078, -12.07349967956543 ], [ -10.351140975952148, -5.718214511871338, -0.23084934055805206, 12.469084739685059, 2.64439058303833 ], [ -7.810425281524658, -9.869714736938477, 4.394267559051514, 5.334882736206055, -7.998237133026123 ], [ 0.6759011149406433, 3.5505788326263428, 6.809964179992676, 2.5486838817596436, -10.02545166015625 ], [ -5.043296813964844, 14.031866073608398, -8.336387634277344, 1.8468791246414185, 12.201967239379883 ], [ 1.2583709955215454, 8.686885833740234, 2.0220634937286377, -12.376644134521484, 11.341581344604492 ], [ -7.473458290100098, 21.488779067993164, -0.5096638202667236, -0.2891603410243988, 3.449552297592163 ], [ -9.232336044311523, 14.326984405517578, 1.5604597330093384, 0.13576646149158478, -2.1042919158935547 ], ... ],
[ [ 7.825238227844238, 5.256662368774414, -4.958898544311523, 23.464778900146484, -16.156360626220703 ], [ -8.372669219970703, -17.025930404663086, -9.164267539978027, 6.497179985046387, -4.5822367668151855 ], [ 12.071906089782715, -5.388167381286621, -10.53956413269043, -16.288267135620117, -3.1470987796783447 ], [ 10.212541580200195, -12.33619213104248, -6.382325649261475, -1.94770085811615, 7.745968818664551 ], [ -5.096182823181152, 7.636875629425049, -0.09876537322998047, -19.770069122314453, -5.1872711181640625 ], [ -18.85666275024414, -2.003628730773926, 6.061254024505615, -11.723865509033203, -3.982842445373535 ], [ -14.353340148925781, 17.670438766479492, -17.964506149291992, -12.614676475524902, 5.088711261749268 ], [ 2.963282346725464, -2.3696868419647217, -1.3734779357910156, -11.994251251220703, 9.114258766174316 ], ... ],
[ [ -20.06222915649414, 6.388875484466553, -1.7984241247177124, -4.424342632293701, 8.886012077331543 ], [ -24.394542694091797, 14.768649101257324, -13.809510231018066, -7.739821910858154, -3.3691165447235107 ], [ 7.304210186004639, -8.737829208374023, 5.0170979499816895, -7.9781813621521, -4.493625164031982 ], [ -7.8306803703308105, -5.737408638000488, -9.409481048583984, 10.930912971496582, 3.8881912231445312 ], [ 3.407257556915283, -1.9263230562210083, -11.729265213012695, 3.519233226776123, 7.2802605628967285 ], [ -9.53577709197998, 2.1079633235931396, -5.5302510261535645, 11.360454559326172, 12.593252182006836 ], [ -13.557212829589844, 1.285426378250122, 9.414204597473145, 4.82962703704834, 4.667144298553467 ], [ 9.935282707214355, 9.44067096710205, 0.22892318665981293, 9.43217945098877, -31.496185302734375 ], ... ],
[ [ -10.529705047607422, -0.34768515825271606, -12.004892349243164, 6.42225980758667, 0.7602946162223816 ], [ -20.333066940307617, 11.630742073059082, -19.47908592224121, -15.644511222839355, 16.669485092163086 ], [ -18.174367904663086, 6.3946309089660645, -8.734291076660156, -12.537808418273926, 8.21900463104248 ], [ 3.7141165733337402, -0.25941571593284607, -4.115673065185547, 19.415273666381836, -3.3987619876861572 ], [ 3.636732578277588, -12.82479190826416, 9.859188079833984, 15.647636413574219, -3.897859573364258 ], [ 1.080289363861084, 0.9927239418029785, -12.647271156311035, 10.454005241394043, -9.591835975646973 ], [ -0.11586202681064606, -13.513854026794434, -11.114405632019043, 8.2339506149292, 14.482269287109375 ], [ -6.626807689666748, 8.039277076721191, -12.77708625793457, -4.625524997711182, -0.9251836538314819 ], ... ],
[ [ 4.430471897125244, 0.587419331073761, 3.499919891357422, -12.275713920593262, -1.7615541219711304 ], [ -4.43597412109375, 1.7886468172073364, 2.8125529289245605, -12.562210083007812, 4.20783805847168 ], [ 1.157119870185852, 12.191911697387695, -22.841182708740234, 0.39942672848701477, -10.09329605102539 ], [ -2.1760785579681396, 5.098329067230225, -10.209705352783203, -0.2831675112247467, -7.910750389099121 ], [ -18.502092361450195, 3.517098903656006, -6.605823040008545, -11.163217544555664, -5.7245097160339355 ], [ 7.304137706756592, -11.114872932434082, 3.1088972091674805, -4.4462361335754395, -3.270202398300171 ], [ -22.12782096862793, 2.7982938289642334, 3.1962292194366455, -17.704004287719727, -2.397679090499878 ], [ -12.825724601745605, -3.83402156829834, -6.384393215179443, -4.928298473358154, 9.130496978759766 ], ... ],
...
]
Next, we apply the same optimization using L-BFGS, which is nearly ideal for purely second-order or quadratic functions.
TrainingTester.java:509 executed in 35.59 seconds (0.806 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new ArmijoWolfeSearch());
iterativeTrainer.setOrientation(new LBFGS());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setIterationsPerSample(100);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 13178381107763
Reset training subject: 13178789302660
Adding measurement 13074e1e to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD
Non-optimal measurement 233.5098803469944 < 233.5098803469944. Total: 1
th(0)=233.5098803469944;dx=-0.03930302224877376
Adding measurement 78dc7747 to history. Total: 1
New Minimum: 233.5098803469944 > 233.42521413839194
WOLFE (weak): th(2.154434690031884)=233.42521413839194; dx=-0.03929411251682438 evalInputDelta=0.08466620860247076
Adding measurement 4f4483f to history. Total: 2
New Minimum: 233.42521413839194 > 233.3405671044129
WOLFE (weak): th(4.308869380063768)=233.3405671044129; dx=-0.039285202788745414 evalInputDelta=0.16931324258149516
Adding measurement 62e2f433 to history. Total: 3
New Minimum: 233.3405671044129 > 233.00217102729454
WOLFE (weak): th(12.926608140191302)=233.00217102729454; dx=-0.03924956387768884 evalInputDelta=0.5077093196998703
Adding measurement 1c8c73ae to history. Total: 4
New Minimum: 233.00217102729454 > 231.483189526702
WOLFE (weak): th(51.70643256076521)=231.483189526702; dx=-0.03908918878541733 evalInputDelta=2.0266908202924014
Adding measurement 2fd7cf02 to history. Total: 5
New Minimum: 231.483189526702 > 223.48699200965726
WOLFE (weak): th(258.53216280382605)=223.48699200965726; dx=-0.03823385494231532 evalInputDelta=10.02288833733715
Adding measurement 540ff487 to history. Total: 6
New Minimum: 223.48699200965726 > 177.51876262366807
END: th(1551.1929768229563)=177.51876262366807; dx=-0.03288801843500125 evalInputDelta=55.99111772332634
Fitness changed from 233.5098803469944 to 177.51876262366807
Iteration 1 complete. Error: 177.51876262366807 Total: 6.6003; Orientation: 0.2034; Line Search: 5.1804
Non-optimal measurement 177.51876262366807 < 177.51876262366807. Total: 7
Rejected: LBFGS Orientation magnitude: 1.889e+03, gradient 1.663e-01, dot -0.968; [e34ef500-025b-42d1-9ff0-b2d60c724ca0 = 1.000/1.000e+00, 5c775c2c-0584-41e0-987b-e7a370111acd = 1.000/1.000e+00]
Orientation rejected. Popping history element from 177.51876262366807, 223.48699200965726, 231.483189526702, 233.00217102729454, 233.3405671044129, 233.42521413839194, 233.5098803469944
Rejected: LBFGS Orientation magnitude: 1.889e+03, gradient 1.663e-01, dot -0.968; [5c775c2c-0584-41e0-987b-e7a370111acd = 1.000/1.000e+00, e34ef500-025b-42d1-9ff0-b2d60c724ca0 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 177.51876262366807, 223.48699200965726, 231.483189526702, 233.00217102729454, 233.3405671044129, 233.42521413839194
Rejected: LBFGS Orientation magnitude: 1.889e+03, gradient 1.663e-01, dot -0.968; [5c775c2c-0584-41e0-987b-e7a370111acd = 1.000/1.000e+00, e34ef500-025b-42d1-9ff0-b2d60c724ca0 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 177.51876262366807, 223.48699200965726, 231.483189526702, 233.00217102729454, 233.3405671044129
Rejected: LBFGS Orientation magnitude: 1.889e+03, gradient 1.663e-01, dot -0.968; [5c775c2c-0584-41e0-987b-e7a370111acd = 1.000/1.000e+00, e34ef500-025b-42d1-9ff0-b2d60c724ca0 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 177.51876262366807, 223.48699200965726, 231.483189526702, 233.00217102729454
LBFGS Accumulation History: 3 points
Removed measurement 540ff487 to history. Total: 6
Removed measurement 2fd7cf02 to history. Total: 5
Removed measurement 1c8c73ae to history. Total: 4
Removed measurement 62e2f433 to history. Total: 3
Adding measurement 23e182c2 to history. Total: 3
th(0)=177.51876262366807;dx=-0.02765497530407833
Adding measurement a31e226 to history. Total: 4
New Minimum: 177.51876262366807 > 100.52900140451678
END: th(3341.943960201201)=100.52900140451678; dx=-0.01841986147522871 evalInputDelta=76.98976121915129
Fitness changed from 177.51876262366807 to 100.52900140451678
Iteration 2 complete. Error: 100.52900140451678 Total: 28.9913; Orientation: 27.2832; Line Search: 1.2691
Final threshold in iteration 2: 100.52900140451678 (> 0.0) after 35.592s (< 30.000s)
Returns
100.52900140451678
This training apply resulted in the following configuration:
TrainingTester.java:610 executed in 0.00 seconds (0.000 gc):
RefList<double[]> state = network.state();
assert state != null;
String description = state.stream().map(RefArrays::toString).reduce((a, b) -> a + "\n" + b)
.orElse("");
state.freeRef();
return description;
Returns
TrainingTester.java:622 executed in 0.00 seconds (0.000 gc):
return RefArrays.stream(RefUtil.addRef(data)).flatMap(x -> {
return RefArrays.stream(x);
}).limit(1).map(x -> {
String temp_18_0015 = x.prettyPrint();
x.freeRef();
return temp_18_0015;
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
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[ [ 1.3310418156684094, 1.00293714994012, 0.6769897269388762, -1.8107051810778847, 1.7951634976779596, 1.512444388289324, 1.8334260547959003 ], [ 0.32751539513200356, -0.5419295715463289, 0.8144892176094853, -1.0793307854979322, -1.1427979429596236, -0.0424224451937289, -1.6380000478367172 ], [ -2.0499517100000215, -0.041798576646730035, -0.38584385319002, 0.3573433394499081, -0.6350051879275501, -0.7083239644791656, 0.8852475771485657 ], [ -0.008229933690428876, 0.5663993248611245, -0.10647315569417348, -1.5078488185379424, -1.5895052273275068, 2.1620425105298677, 1.229431192643607 ], [ -1.2961199743797638, 1.4254849942256318, -0.6444861423211904, 1.0163137558083002, -1.0750316399890631, 1.6571511132438792, 1.89159062989633 ], [ 0.2595454245789684, 0.4320026890894467, 1.3462776326608734, 1.5110639606585803, 0.2688539764548597, -0.21538867590877664, 0.9310436401616863 ], [ -0.8356050348433356, -1.262434562965982, -1.313029679046752, 0.21902122543711414, 1.4442173127585831, -0.15314449864400737, -0.4853147420056654 ], [ -1.8998840660923202, 0.9443041753489674, -0.5374919680517658, -1.2896596861170768, 0.04484497495900261, -1.5240239044925348, -0.8365336250398676 ], ... ],
[ [ 1.575493506995113, 0.4278549338197925, 0.768291907175808, -0.21492875840389894, -1.2576220019015232, -0.3927814785505671, -0.31300490767430367 ], [ 0.8346920595357251, 1.582202630688362, -1.734348999996501, 1.3178381069949074, 1.0834427709207777, -0.7195830971688453, 0.8430119886481569 ], [ -0.8316900772153902, -0.47740676699622525, 0.5119877970768179, 0.3529592112632224, 0.9991708692614354, -0.4913964099198004, 0.35650624855680424 ], [ -0.08991221946613104, 1.0199149984900455, 1.0846866658804342, -0.392642680654382, -0.10365449473133004, 1.3196515657597474, 1.3762082410473433 ], [ 0.5480903618522266, 0.6594495100572595, -0.6457758531712886, 1.409788019917343, 1.0103541908811233, 0.5362051351335619, 0.20284080945762875 ], [ 2.0697812396721975, -1.2865127665871021, -0.9597669987639537, 0.06680975862068467, 1.3815361986946355, -0.04001352154281773, 1.3481349169505599 ], [ 1.4830676209510159, 0.12845609266298025, 0.9165560273782972, -1.1188193101428623, 1.5109331254644542, 0.5243111282897849, 0.5349541873240382 ], [ 2.07463535970642, -0.5129996107650091, -1.6166268750346824, 1.0058784103519594, -1.1060508672118303, -0.2761071294169326, -1.0842177768439545 ], ... ],
[ [ -1.6416174123891372, -1.2717560098123262, 1.6647594954340164, -1.075613738604918, -0.15848042566997386, -1.126890883413603, 1.6909813344958933 ], [ -1.552698650192558, 0.027488389936328572, 0.32892853733410665, 1.479266135890761, 0.18822586421474113, -0.07759381839912594, 0.6426840228858445 ], [ 1.8666475778691551, -0.9568959602921477, -0.6372008227690562, 0.8560451546409199, 0.4841364224447282, 0.6267886708649896, -1.3673555605809187 ], [ 0.6098634178323095, 0.8440692319411605, -1.852707087038555, -1.5413331474012526, 1.7988018812469235, 1.3377123043487076, 1.1192775206283065 ], [ -0.0014025225191477975, -0.9519143806246002, 0.2522842618102743, 1.2837966519385706, 0.7759280566034821, 0.7926417551533168, -0.08883157034650557 ], [ 0.3252885516659678, -0.9228582342555527, 0.7756820898172248, -0.06804821534986627, -1.0504234961405734, -1.0252272378467846, 1.2903145357970258 ], [ 0.08807781254020926, 0.8812863260558936, 1.2832483045435834, 1.1468254064630423, -2.137508714836512, 1.0524954348195357, -1.217015666274619 ], [ -0.7682153206978657, 0.05067663307781026, -0.2489891469546683, 0.36044320759508736, 0.43984532861714143, 1.1492444885744861, 0.1474458140979634 ], ... ],
[ [ 0.7600334814717155, 0.27481919542153277, 1.584321168236293, 0.23841702191144346, 0.009315100911064737, -0.8954864468068792, 1.6424876688036636 ], [ 0.791751943447528, 0.7087740960693846, 0.2729726746642453, 0.35854010646228757, -1.0875753182790713, -0.6367668582738332, -1.9238342306414242 ], [ -0.31072213829327644, 1.5476481706693332, -1.3153647271090525, 1.7018038579248247, 0.6370353893702546, 0.9661622441450068, 1.2248087096115894 ], [ -0.8364026433249317, -0.11478536796884845, 0.14268935758797674, -1.726661215771974, 1.743050385255079, -0.5708879353720714, -0.18811696391587943 ], [ 0.8694838088773488, 2.251430633674529, 1.0100039709564028, 1.3657767945396013, -1.0913968476444709, -0.8717789899166886, 0.6876087308223208 ], [ 1.3833108973681705, 1.1996968647082211, 1.5329521020004921, 1.3143203909016634, -1.4091989025484606, 0.5941577822426054, -0.260208620699017 ], [ -1.00796153224123, -0.3499068051607006, -0.3088916222646639, 0.776299991623546, -1.4331397021960084, 0.7592798436229766, 0.8408538503919526 ], [ -1.6980007264639643, -1.8208824909886383, 0.948690566468743, 0.7098434721160134, -1.70338245845628, -1.798620422446515, 0.41114367563694737 ], ... ],
[ [ 0.597787265117212, 0.15333663232281428, -1.6721528272482138, -1.990833666308952, 0.41777983490367254, -0.698790379871139, -0.7186959599467122 ], [ -1.4012793082386419, -0.8539156544500562, 1.143305589464528, -0.26535748147331367, -0.7099027982335072, -0.26560974936212284, 1.38856080578258 ], [ -1.2919871041948712, 1.0212336056374005, 0.6889135118916544, -0.3853694177717366, 0.9623495421036231, -1.4163118192341573, 0.5792830394905125 ], [ 0.5632590236287986, 0.3760657745905212, 0.029129232547851547, -1.4381340478758535, -0.7948364960485799, 0.8822650843285272, -0.7539259270397244 ], [ -0.09250956018853877, 0.9390639383354507, 1.0291642342822733, -1.316227755280949, -0.28645625698985877, -1.896584404528023, 0.049922322351550835 ], [ -0.1736712090379038, 1.8120566434357464, 1.8704940439653803, -1.2699458426606811, 1.1631037322651923, -1.5359953890067686, -0.7426176520668062 ], [ 1.257112257584566, 0.6402498740857983, 1.2926986849949262, -0.027452721212208563, 1.9882084421563797, 1.453351734474205, 1.7310641423466075 ], [ 1.550276972683613, 0.2628643749507422, -1.4430890606256108, 1.1282959462100808, 1.2929194758181752, 0.46146844929472985, 1.2486285687906074 ], ... ],
[ [ 1.9473213564222567, 1.7163616375126818, 1.0347134760236836, -0.7606757540021727, -0.8279016496426882, 1.3994601141735832, -1.0860071297199672 ], [ 2.030141211829334, -0.15152735960909763, -1.1620843497062157, 1.5091471382766055, 1.1421233167925147, 0.42963122779944857, 0.9514028029838901 ], [ 1.789968201652119, -1.4325661132202259, -0.7027244391157583, -1.149194363043851, -0.7795636670775239, -0.028610676164419258, 0.8942928723823022 ], [ -1.2185669910483443, 0.03205307194220393, 1.4932556438693316, 1.0893791095893135, -0.8945691624682958, 0.20493776838487202, 0.92146766846016 ], [ 1.7276630782470648, -0.30738888234978007, 1.1811683361547187, -1.29499833574402, -0.08570831944657695, -0.2595409884811322, -0.8755678901613375 ], [ 1.142660049824925, 1.3287655036830548, -0.03566018254930167, 0.2797236936836818, -1.2718691801869502, -0.25074284900413096, 1.2196747979247025 ], [ -2.0709982731668504, 1.3825692840564563, 0.5235489160349792, 0.5130470867325443, -0.07359025844099028, -1.6125837899152582, 0.19306583482380843 ], [ -1.258364239344745, -0.08539112357963191, -1.2713702189297658, 0.6808899411575849, 1.3044923081982995, -0.8312172042690379, 1.3924998145045075 ], ... ],
...
]
To produce the following output:
TrainingTester.java:633 executed in 0.15 seconds (0.000 gc):
Result[] array = ConstantResult.batchResultArray(pop(RefUtil.addRef(data)));
@Nullable
Result eval = layer.eval(array);
assert eval != null;
TensorList tensorList = Result.getData(eval);
String temp_18_0016 = tensorList.stream().limit(1).map(x -> {
String temp_18_0017 = x.prettyPrint();
x.freeRef();
return temp_18_0017;
}).reduce((a, b) -> a + "\n" + b).orElse("");
tensorList.freeRef();
return temp_18_0016;
Returns
[
[ [ -1.4169015884399414, 3.76940655708313, 0.8129848837852478, 4.519199371337891, -6.033269882202148 ], [ 5.346821308135986, -11.79140567779541, 14.073600769042969, -5.156574726104736, 2.837238073348999 ], [ -4.593950271606445, 5.240475654602051, 2.945300340652466, 2.942014217376709, -0.8286041617393494 ], [ 0.8117560148239136, 4.853083610534668, 10.933928489685059, 1.3255707025527954, -10.409122467041016 ], [ -3.7062437534332275, -1.0230398178100586, 4.674731731414795, -4.339968204498291, 2.7601163387298584 ], [ 2.6146769523620605, 5.03061580657959, -6.045822620391846, -5.040892124176025, -1.2707297801971436 ], [ 10.263934135437012, 3.0157129764556885, -2.787393093109131, -11.048837661743164, -0.4546162784099579 ], [ -3.2383761405944824, 11.079598426818848, 4.803217887878418, -3.723062515258789, -0.5552049875259399 ], ... ],
[ [ -3.1087825298309326, 16.104488372802734, -11.968643188476562, 7.448033809661865, -6.38150691986084 ], [ 14.206689834594727, -9.89914321899414, 3.8585469722747803, 15.061013221740723, -17.427648544311523 ], [ 0.4726817309856415, -4.449858665466309, -4.376092910766602, 6.197392463684082, -1.808113932609558 ], [ -3.348722457885742, -0.9423646926879883, 5.71425724029541, -1.2238918542861938, -12.574297904968262 ], [ -2.700993776321411, 3.6028168201446533, 5.211673736572266, 3.0039663314819336, -7.14092493057251 ], [ -5.720832347869873, 1.1441631317138672, -0.15312542021274567, 20.117666244506836, -12.172350883483887 ], [ 1.9413741827011108, 0.9218690395355225, 2.479633331298828, 3.0836563110351562, 2.3064277172088623 ], [ 1.5571757555007935, 6.118165969848633, -2.157440185546875, -0.37468159198760986, 11.321825981140137 ], ... ],
[ [ 6.333922863006592, -10.018071174621582, -0.6585673093795776, -2.634768486022949, 5.812380313873291 ], [ -16.44011688232422, 2.402808666229248, -8.727031707763672, 3.3901641368865967, 2.361579179763794 ], [ -16.63518524169922, 13.690567016601562, 7.217922210693359, -2.2613792419433594, 3.81825590133667 ], [ -6.809658527374268, -8.813924789428711, 4.857486724853516, 6.997920513153076, 14.041790962219238 ], [ -2.8460609912872314, 1.5726230144500732, 4.277740955352783, 3.198918342590332, 5.748520374298096 ], [ 8.58016300201416, -2.9703197479248047, 1.4837324619293213, -3.624356746673584, 7.473264694213867 ], [ -5.268238544464111, -3.606221914291382, -10.97559642791748, 9.261290550231934, -15.528953552246094 ], [ 4.180130481719971, -20.264928817749023, -4.680329322814941, 9.54037857055664, -4.285459041595459 ], ... ],
[ [ 2.525221109390259, -1.669504165649414, 10.461073875427246, 10.114701271057129, -4.289375305175781 ], [ 3.4472506046295166, 0.3528594970703125, -3.7058706283569336, 12.53512191772461, 6.953105926513672 ], [ -0.9305309653282166, -13.221975326538086, 2.2732419967651367, 3.6559977531433105, 3.8332297801971436 ], [ -0.4192737340927124, -1.8390158414840698, 3.951833486557007, -5.055587291717529, 13.897205352783203 ], [ 15.019669532775879, 5.434608459472656, -5.682614803314209, 4.727840423583984, 1.559346318244934 ], [ 3.779585361480713, -0.8901846408843994, -0.7164658308029175, -16.4370059967041, -0.1294098198413849 ], [ 2.973186492919922, 9.59716796875, -5.448002338409424, 1.482192873954773, -2.6918842792510986 ], [ -8.575474739074707, 10.83873176574707, 4.073602676391602, -6.522492408752441, -6.641970157623291 ], ... ],
[ [ 2.4245879650115967, 8.861689567565918, -5.121151924133301, 9.496804237365723, -6.64105749130249 ], [ -10.849782943725586, -4.066709995269775, 4.148456573486328, -9.457317352294922, 11.0277099609375 ], [ -3.752159833908081, 10.425621032714844, 1.1276674270629883, -20.799467086791992, -7.166077136993408 ], [ 9.431096076965332, -3.8982157707214355, 4.056943416595459, 6.512454509735107, 2.9451582431793213 ], [ 4.6031174659729, 3.9816787242889404, 5.738747596740723, -6.693378925323486, -15.242815971374512 ], [ -18.69875717163086, 5.956905364990234, 9.19052791595459, -12.126609802246094, -7.883736610412598 ], [ 0.7452488541603088, 9.070865631103516, -2.9059338569641113, -4.197089672088623, 10.961734771728516 ], [ 11.87488079071045, -5.892179012298584, -7.912520885467529, -12.480504035949707, 9.705492973327637 ], ... ],
[ [ -1.4606106281280518, 2.3331446647644043, 2.968780517578125, -4.432085037231445, 0.7768747210502625 ], [ 6.834470748901367, 11.62291431427002, -3.8530731201171875, -7.280429840087891, -5.2049689292907715 ], [ 0.41080644726753235, -5.2982354164123535, 11.230376243591309, -1.5668505430221558, 3.726102352142334 ], [ 11.77730941772461, -10.049306869506836, 2.303394317626953, 11.994407653808594, -5.2760186195373535 ], [ 9.641277313232422, 7.634456157684326, -4.708236217498779, -6.48115348815918, -8.462885856628418 ], [ -14.707440376281738, 7.0389404296875, 12.245138168334961, -7.729076862335205, 19.3679256439209 ], [ -18.21405029296875, 0.16088831424713135, 26.341262817382812, 0.43544337153434753, 8.873884201049805 ], [ -5.619102478027344, 20.22032928466797, 5.474679470062256, 6.176106929779053, -9.763333320617676 ], ... ],
[ [ -9.898612022399902, -3.7357916831970215, 1.1550613641738892, 4.001819133758545, -4.875189781188965 ], [ -6.797828197479248, 6.446767807006836, 3.830106735229492, 3.2204668521881104, -1.0845344066619873 ], [ -6.423888206481934, -8.63782024383545, -0.35956501960754395, -6.301672458648682, 8.544650077819824 ], [ 11.2760648727417, 13.225611686706543, -11.74068546295166, -8.895263671875, -6.094000339508057 ], [ 8.279397010803223, -6.080476760864258, 5.670790672302246, 11.00087833404541, -5.228362083435059 ], [ 2.461059093475342, 7.986584663391113, -9.161605834960938, 1.2927751541137695, -0.27346721291542053 ], [ -2.1255526542663574, 2.595723867416382, -15.322360038757324, 5.157702445983887, -1.3591541051864624 ], [ -11.44586181640625, -1.2360984086990356, -3.3680145740509033, 1.6704025268554688, 1.5867581367492676 ], ... ],
[ [ 1.0276355743408203, 2.661139726638794, -8.418978691101074, -9.541488647460938, 5.856823921203613 ], [ -13.93701457977295, -2.645026206970215, 0.7905817031860352, -4.08648681640625, -0.7064436078071594 ], [ 3.366255521774292, 5.686392307281494, -0.8574430346488953, -2.3933839797973633, -4.329869270324707 ], [ 8.321517944335938, 7.536793231964111, 2.94215989112854, 1.949153184890747, -3.983405828475952 ], [ -11.66950511932373, 4.842898368835449, -10.968990325927734, 0.34366375207901, -8.348389625549316 ], [ 6.4641337394714355, 0.18572355806827545, 2.1599137783050537, -0.33023327589035034, -2.768118143081665 ], [ -3.753218412399292, -2.8865456581115723, 8.949625968933105, -13.771734237670898, 2.3689727783203125 ], [ -9.178694725036621, -11.454024314880371, -7.338710308074951, 1.4638092517852783, 5.534765720367432 ], ... ],
...
]
TrainingTester.java:432 executed in 0.14 seconds (0.000 gc):
return TestUtil.compare(title + " vs Iteration", runs);
Plotting range=[1.0, 0.0645816288698347], [12.0, 2.249244262029349]; valueStats=DoubleSummaryStatistics{count=19, sum=722.913572, min=1.160330, average=38.048083, max=177.518763}
Plotting 12 points for GD
Plotting 5 points for CjGD
Plotting 2 points for LBFGS
Returns
TrainingTester.java:435 executed in 0.02 seconds (0.000 gc):
return TestUtil.compareTime(title + " vs Time", runs);
Plotting range=[0.0, 0.0645816288698347], [28.991, 2.249244262029349]; valueStats=DoubleSummaryStatistics{count=19, sum=722.913572, min=1.160330, average=38.048083, max=177.518763}
Plotting 12 points for GD
Plotting 5 points for CjGD
Plotting 2 points for LBFGS
Returns
In this apply, attempt to train a network to emulate a randomized network given an example input/output. The target state is:
TrainingTester.java:370 executed in 0.00 seconds (0.000 gc):
RefList<double[]> temp_18_0042 = network_target.state();
assert temp_18_0042 != null;
String temp_18_0041 = temp_18_0042.stream().map(RefArrays::toString).reduce((a, b) -> a + "\n" + b).orElse("");
temp_18_0042.freeRef();
return temp_18_0041;
Returns
First, we train using basic gradient descent method apply weak line search conditions.
TrainingTester.java:480 executed in 32.99 seconds (0.140 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new ArmijoWolfeSearch());
iterativeTrainer.setOrientation(new GradientDescent());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 13214927035526
Reset training subject: 13215220741228
Constructing line search parameters: GD
th(0)=215.06479967941746;dx=-229.46204611604483
New Minimum: 215.06479967941746 > 4.818584490021626
WOLF (strong): th(2.154434690031884)=4.818584490021626; dx=34.28676750183555 evalInputDelta=210.24621518939583
END: th(1.077217345015942)=38.91298792219736; dx=-97.58764902901792 evalInputDelta=176.15181175722012
Fitness changed from 215.06479967941746 to 4.818584490021626
Iteration 1 complete. Error: 4.818584490021626 Total: 1.7653; Orientation: 0.0010; Line Search: 0.8854
th(0)=4.818584490021626;dx=-5.147405668333957
New Minimum: 4.818584490021626 > 0.27714840849351663
WOLF (strong): th(2.3207944168063896)=0.27714840849351663; dx=1.233714443129135 evalInputDelta=4.54143608152811
END: th(1.1603972084031948)=0.6967079829382152; dx=-1.9568456653626245 evalInputDelta=4.121876507083411
Fitness changed from 4.818584490021626 to 0.27714840849351663
Iteration 2 complete. Error: 0.27714840849351663 Total: 1.1691; Orientation: 0.0005; Line Search: 0.8803
th(0)=0.27714840849351663;dx=-0.2962908316047893
New Minimum: 0.27714840849351663 > 0.031387545228550265
WOLF (strong): th(2.5000000000000004)=0.031387545228550265; dx=0.09968215781927689 evalInputDelta=0.24576086326496638
New Minimum: 0.031387545228550265 > 0.030526416983047717
END: th(1.2500000000000002)=0.030526416983047717; dx=-0.09830435177658177 evalInputDelta=0.2466219915104689
Fitness changed from 0.27714840849351663 to 0.030526416983047717
Iteration 3 complete. Error: 0.030526416983047717 Total: 1.1676; Orientation: 0.0005; Line Search: 0.8768
th(0)=0.030526416983047717;dx=-0.03262528838560311
New Minimum: 0.030526416983047717 > 0.005890506823108953
WOLF (strong): th(2.6930433625398553)=0.005890506823108953; dx=0.014329326283042272 evalInputDelta=0.024635910159938764
New Minimum: 0.005890506823108953 > 0.002402108105264209
END: th(1.3465216812699277)=0.002402108105264209; dx=-0.009147977757064553 evalInputDelta=0.028124308877783506
Fitness changed from 0.030526416983047717 to 0.002402108105264209
Iteration 4 complete. Error: 0.002402108105264209 Total: 1.3015; Orientation: 0.1417; Line Search: 0.8697
th(0)=0.002402108105264209;dx=-0.002566290935546451
New Minimum: 0.002402108105264209 > 7.261116142397131E-4
WOLF (strong): th(2.9009930210079875)=7.261116142397131E-4; dx=0.0014108264658815144 evalInputDelta=0.0016759964910244957
New Minimum: 7.261116142397131E-4 > 1.2191110443372257E-4
END: th(1.4504965105039938)=1.2191110443372257E-4; dx=-5.777304291338955E-4 evalInputDelta=0.002280197000830486
Fitness changed from 0.002402108105264209 to 1.2191110443372257E-4
Iteration 5 complete. Error: 1.2191110443372257E-4 Total: 1.3028; Orientation: 0.0005; Line Search: 1.0075
th(0)=1.2191110443372257E-4;dx=-1.3017580599048096E-4
New Minimum: 1.2191110443372257E-4 > 5.4495083046723685E-5
WOLF (strong): th(3.125000000000001)=5.4495083046723685E-5; dx=8.702952415368836E-5 evalInputDelta=6.741602138699888E-5
New Minimum: 5.4495083046723685E-5 > 3.357407463568149E-6
END: th(1.5625000000000004)=3.357407463568149E-6; dx=-2.157339464591683E-5 evalInputDelta=1.1855369697015442E-4
Fitness changed from 1.2191110443372257E-4 to 3.357407463568149E-6
Iteration 6 complete. Error: 3.357407463568149E-6 Total: 1.2507; Orientation: 0.0007; Line Search: 0.9598
th(0)=3.357407463568149E-6;dx=-3.5822137654013556E-6
New Minimum: 3.357407463568149E-6 > 2.1274130361958794E-6
WOLF (strong): th(3.3663042031748196)=2.1274130361958794E-6; dx=2.85144662662618E-6 evalInputDelta=1.2299944273722696E-6
New Minimum: 2.1274130361958794E-6 > 3.5201557880190146E-8
END: th(1.6831521015874098)=3.5201557880190146E-8; dx=-3.6540328571599174E-7 evalInputDelta=3.3222059056879587E-6
Fitness changed from 3.357407463568149E-6 to 3.5201557880190146E-8
Iteration 7 complete. Error: 3.5201557880190146E-8 Total: 1.1992; Orientation: 0.0007; Line Search: 0.8788
th(0)=3.5201557880190146E-8;dx=-3.750135479177438E-8
New Minimum: 3.5201557880190146E-8 > 3.057976918038615E-8
WOLF (strong): th(3.626241276259985)=3.057976918038615E-8; dx=3.4952276374412143E-8 evalInputDelta=4.621788699803995E-9
New Minimum: 3.057976918038615E-8 > 4.7455397924030566E-11
END: th(1.8131206381299925)=4.7455397924030566E-11; dx=-1.2741648485917901E-9 evalInputDelta=3.5154102482266114E-8
Fitness changed from 3.5201557880190146E-8 to 4.7455397924030566E-11
Iteration 8 complete. Error: 4.7455397924030566E-11 Total: 1.3303; Orientation: 0.0007; Line Search: 1.0316
Low gradient: 6.7972202076529345E-6
th(0)=4.7455397924030566E-11;dx=-4.6202203124337154E-11
Armijo: th(3.9062500000000018)=5.411886228772006E-11; dx=4.955442919714224E-11 evalInputDelta=-6.663464363689494E-12
New Minimum: 4.7455397924030566E-11 > 9.25939195308501E-13
WOLF (strong): th(1.9531250000000009)=9.25939195308501E-13; dx=1.7889121874796847E-12 evalInputDelta=4.6529458728722064E-11
END: th(0.651041666666667)=2.2347641319232955E-11; dx=-3.0212487990969766E-11 evalInputDelta=2.510775660479761E-11
Fitness changed from 4.7455397924030566E-11 to 9.25939195308501E-13
Iteration 9 complete. Error: 9.25939195308501E-13 Total: 1.4462; Orientation: 0.0009; Line Search: 1.1540
Low gradient: 4.166733965071295E-7
th(0)=9.25939195308501E-13;dx=-1.7361671748838013E-13
New Minimum: 9.25939195308501E-13 > 1.153963652803564E-13
END: th(1.4026267513228416)=1.153963652803564E-13; dx=-2.5645461110934962E-15 evalInputDelta=8.105428300281447E-13
Fitness changed from 9.25939195308501E-13 to 1.153963652803564E-13
Iteration 10 complete. Error: 1.153963652803564E-13 Total: 0.8736; Orientation: 0.0008; Line Search: 0.5855
Low gradient: 1.0587027558936141E-7
th(0)=1.153963652803564E-13;dx=-1.120851428838485E-14
Armijo: th(3.0218677302166546)=1.1985635990126007E-13; dx=1.1010521171485502E-14 evalInputDelta=-4.459994620903661E-15
New Minimum: 1.153963652803564E-13 > 1.8920544448792826E-14
END: th(1.5109338651083273)=1.8920544448792826E-14; dx=-5.010955410040859E-17 evalInputDelta=9.647582083156358E-14
Fitness changed from 1.153963652803564E-13 to 1.8920544448792826E-14
Iteration 11 complete. Error: 1.8920544448792826E-14 Total: 1.1834; Orientation: 0.0007; Line Search: 0.8909
Low gradient: 3.195768309172855E-8
th(0)=1.8920544448792826E-14;dx=-1.0212938431932415E-15
New Minimum: 1.8920544448792826E-14 > 1.696124990519742E-14
WOLF (strong): th(3.2552083333333353)=1.696124990519742E-14; dx=9.853620255731095E-16 evalInputDelta=1.9592945435954066E-15
New Minimum: 1.696124990519742E-14 > 2.766826641632444E-15
END: th(1.6276041666666676)=2.766826641632444E-15; dx=-1.8615781786640654E-17 evalInputDelta=1.6153717807160382E-14
Fitness changed from 1.8920544448792826E-14 to 2.766826641632444E-15
Iteration 12 complete. Error: 2.766826641632444E-15 Total: 1.1873; Orientation: 0.0006; Line Search: 0.8892
Low gradient: 3.88406547720822E-9
th(0)=2.766826641632444E-15;dx=-1.5085963477207044E-17
New Minimum: 2.766826641632444E-15 > 1.768770106332271E-15
END: th(3.5065668783071047)=1.768770106332271E-15; dx=-9.587311748560913E-18 evalInputDelta=9.980565353001731E-16
Fitness changed from 2.766826641632444E-15 to 1.768770106332271E-15
Iteration 13 complete. Error: 1.768770106332271E-15 Total: 0.8946; Orientation: 0.0010; Line Search: 0.5948
Low gradient: 2.5390405111198275E-9
th(0)=1.768770106332271E-15;dx=-6.446725495855926E-18
New Minimum: 1.768770106332271E-15 > 6.435464552173833E-16
END: th(7.554669325541638)=6.435464552173833E-16; dx=-2.2503738816840287E-18 evalInputDelta=1.1252236511148878E-15
Fitness changed from 1.768770106332271E-15 to 6.435464552173833E-16
Iteration 14 complete. Error: 6.435464552173833E-16 Total: 0.8777; Orientation: 0.0006; Line Search: 0.5854
Low gradient: 9.41877521443643E-10
th(0)=6.435464552173833E-16;dx=-8.871332266395995E-19
New Minimum: 6.435464552173833E-16 > 1.851340028302809E-16
END: th(16.27604166666668)=1.851340028302809E-16; dx=-2.5762250044367145E-19 evalInputDelta=4.584124523871024E-16
Fitness changed from 6.435464552173833E-16 to 1.851340028302809E-16
Iteration 15 complete. Error: 1.851340028302809E-16 Total: 0.8731; Orientation: 0.0006; Line Search: 0.5821
Low gradient: 3.127874804917348E-10
th(0)=1.851340028302809E-16;dx=-9.783600696518903E-20
New Minimum: 1.851340028302809E-16 > 4.0301982317929045E-17
END: th(35.065668783071054)=4.0301982317929045E-17; dx=-1.9075281205153818E-20 evalInputDelta=1.4483202051235186E-16
Fitness changed from 1.851340028302809E-16 to 4.0301982317929045E-17
Iteration 16 complete. Error: 4.0301982317929045E-17 Total: 0.8742; Orientation: 0.0008; Line Search: 0.5835
Zero gradient: 8.757558296055375E-11
th(0)=4.0301982317929045E-17;dx=-7.669482688529967E-21
Armijo: th(75.54669325541639)=4.687531301413242E-16; dx=7.350602667503371E-21 evalInputDelta=-4.284511478233952E-16
New Minimum: 4.0301982317929045E-17 > 1.660170380321601E-17
END: th(37.77334662770819)=1.660170380321601E-17; dx=-3.0816151486612038E-21 evalInputDelta=2.3700278514713035E-17
Fitness changed from 4.0301982317929045E-17 to 1.660170380321601E-17
Iteration 17 complete. Error: 1.660170380321601E-17 Total: 1.1811; Orientation: 0.0008; Line Search: 0.8750
Zero gradient: 4.946585369048102E-11
th(0)=1.660170380321601E-17;dx=-2.4468706772306216E-21
New Minimum: 1.660170380321601E-17 > 9.361259873925653E-18
END: th(81.3802083333334)=9.361259873925653E-18; dx=-1.1801927124473958E-21 evalInputDelta=7.240443929290358E-18
Fitness changed from 1.660170380321601E-17 to 9.361259873925653E-18
Iteration 18 complete. Error: 9.361259873925653E-18 Total: 0.8767; Orientation: 0.0004; Line Search: 0.5826
Zero gradient: 3.186663641529408E-11
th(0)=9.361259873925653E-18;dx=-1.0154824952588652E-21
Armijo: th(175.32834391535528)=7.67042261053075E-15; dx=5.294466717512033E-20 evalInputDelta=-7.661061350656825E-15
Armijo: th(87.66417195767764)=5.281382358891601E-15; dx=3.163259650790743E-20 evalInputDelta=-5.2720210990176755E-15
New Minimum: 9.361259873925653E-18 > 8.125151711877276E-18
END: th(29.22139065255921)=8.125151711877276E-18; dx=-8.271875766217029E-22 evalInputDelta=1.236108162048377E-18
Fitness changed from 9.361259873925653E-18 to 8.125151711877276E-18
Iteration 19 complete. Error: 8.125151711877276E-18 Total: 1.5344; Orientation: 0.0007; Line Search: 1.1650
Zero gradient: 2.8473501123870275E-11
th(0)=8.125151711877276E-18;dx=-8.107402794653876E-22
Armijo: th(62.955577712846996)=5.281508985485472E-15; dx=2.632786254532517E-20 evalInputDelta=-5.273383833773595E-15
Armijo: th(31.477788856423498)=5.282018627372086E-15; dx=2.6286208893575863E-20 evalInputDelta=-5.273893475660208E-15
New Minimum: 8.125151711877276E-18 > 8.124998845731056E-18
WOLFE (weak): th(10.4925962854745)=8.124998845731056E-18; dx=-7.690780019487127E-22 evalInputDelta=1.5286614621953169E-22
Armijo: th(20.985192570949)=5.2823819059734466E-15; dx=2.6212419560092313E-20 evalInputDelta=-5.274256754261569E-15
Armijo: th(15.73889442821175)=5.282381975400135E-15; dx=2.6212232539317187E-20 evalInputDelta=-5.274256823688257E-15
Armijo: th(13.115745356843124)=8.140762381683316E-18; dx=-7.700627948765629E-22 evalInputDelta=-1.561066980604039E-20
New Minimum: 8.124998845731056E-18 > 8.124992710183198E-18
WOLFE (weak): th(11.804170821158813)=8.124992710183198E-18; dx=-7.6907752234076E-22 evalInputDelta=1.5900169407820894E-22
Armijo: th(12.459958089000969)=8.140781764385305E-18; dx=-7.701353051757333E-22 evalInputDelta=-1.5630052508029505E-20
WOLFE (weak): th(12.132064455079892)=8.124992710183198E-18; dx=-7.6907753032480535E-22 evalInputDelta=1.5900169407820894E-22
New Minimum: 8.124992710183198E-18 > 8.124991927148297E-18
WOLFE (weak): th(12.296011272040431)=8.124991927148297E-18; dx=-7.690739213680269E-22 evalInputDelta=1.597847289790962E-22
Armijo: th(12.3779846805207)=8.140781764385305E-18; dx=-7.701353214146171E-22 evalInputDelta=-1.5630052508029505E-20
mu ~= nu (12.296011272040431): th(12.296011272040431)=8.124991927148297E-18
Fitness changed from 8.125151711877276E-18 to 8.124991927148297E-18
Iteration 20 complete. Error: 8.124991927148297E-18 Total: 4.2397; Orientation: 0.0007; Line Search: 3.9487
Zero gradient: 2.789706923610262E-11
th(0)=8.124991927148297E-18;dx=-7.782464728885427E-22
Armijo: th(26.579256410952)=5.281746197440781E-15; dx=3.2024809397590525E-20 evalInputDelta=-5.2736212055136325E-15
Armijo: th(13.289628205476)=5.282287133119949E-15; dx=3.1976250403042345E-20 evalInputDelta=-5.2741621411928E-15
Armijo: th(4.429876068492)=5.282381971850107E-15; dx=3.1939004256946256E-20 evalInputDelta=-5.274256979922959E-15
Armijo: th(1.107469017123)=8.140758493409637E-18; dx=-7.808345521422405E-22 evalInputDelta=-1.57665662613406E-20
Armijo: th(0.22149380342459998)=8.140781764385305E-18; dx=-7.809312071451887E-22 evalInputDelta=-1.57898372370086E-20
Armijo: th(0.0369156339041)=8.140781765720744E-18; dx=-7.809312351890092E-22 evalInputDelta=-1.5789838572446883E-20
Armijo: th(0.0052736619863)=8.124991927148297E-18; dx=-7.782464678497943E-22 evalInputDelta=0.0
Armijo: th(6.592077482875E-4)=8.124991927148297E-18; dx=-7.782464828391553E-22 evalInputDelta=0.0
Armijo: th(7.324530536527778E-5)=8.124991927148297E-18; dx=-7.782464722503022E-22 evalInputDelta=0.0
Armijo: th(7.3245305365277775E-6)=8.124991927148297E-18; dx=-7.782464986928103E-22 evalInputDelta=0.0
WOLFE (weak): th(6.658664124116162E-7)=8.124991927148297E-18; dx=-7.782464797873205E-22 evalInputDelta=0.0
WOLFE (weak): th(3.995198474469697E-6)=8.124991927148297E-18; dx=-7.782464748746017E-22 evalInputDelta=0.0
Armijo: th(5.659864505498737E-6)=8.124991927148297E-18; dx=-7.782464653539413E-22 evalInputDelta=0.0
WOLFE (weak): th(4.827531489984217E-6)=8.124991927148297E-18; dx=-7.78246473006897E-22 evalInputDelta=0.0
Armijo: th(5.243697997741477E-6)=8.124991927148297E-18; dx=-7.78246465243262E-22 evalInputDelta=0.0
Armijo: th(5.0356147438628465E-6)=8.124991927148297E-18; dx=-7.782464862286789E-22 evalInputDelta=0.0
WOLFE (weak): th(4.931573116923532E-6)=8.124991927148297E-18; dx=-7.78246480640157E-22 evalInputDelta=0.0
Armijo: th(4.983593930393189E-6)=8.124991927148297E-18; dx=-7.78246461241519E-22 evalInputDelta=0.0
Armijo: th(4.95758352365836E-6)=8.124991927148297E-18; dx=-7.782464704990846E-22 evalInputDelta=0.0
mu ~= nu (4.931573116923532E-6): th(0.0)=8.124991927148297E-18
Fitness changed from 8.124991927148297E-18 to 8.124991927148297E-18
Static Iteration Total: 6.4614; Orientation: 0.0006; Line Search: 6.1733
Iteration 21 failed. Error: 8.124991927148297E-18
Previous Error: 0.0 -> 8.124991927148297E-18
Optimization terminated 21
Final threshold in iteration 21: 8.124991927148297E-18 (> 0.0) after 32.990s (< 30.000s)
Returns
8.124991927148297E-18
First, we use a conjugate gradient descent method, which converges the fastest for purely linear functions.
TrainingTester.java:452 executed in 34.37 seconds (0.121 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new QuadraticSearch());
iterativeTrainer.setOrientation(new GradientDescent());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 13247966035618
Reset training subject: 13248258196391
Constructing line search parameters: GD
F(0.0) = LineSearchPoint{point=PointSample{avg=215.06479967941746}, derivative=-229.46205432129358}
New Minimum: 215.06479967941746 > 215.06479967941704
F(1.0E-10) = LineSearchPoint{point=PointSample{avg=215.06479967941704}, derivative=-229.46205098181093}, evalInputDelta = -4.263256414560601E-13
New Minimum: 215.06479967941704 > 215.06479961657288
F(7.000000000000001E-10) = LineSearchPoint{point=PointSample{avg=215.06479961657288}, derivative=-229.4620561549077}, evalInputDelta = -6.284457754190953E-8
New Minimum: 215.06479961657288 > 215.06479872279704
F(4.900000000000001E-9) = LineSearchPoint{point=PointSample{avg=215.06479872279704}, derivative=-229.46205392573273}, evalInputDelta = -9.566204255406774E-7
New Minimum: 215.06479872279704 > 215.06479149788672
F(3.430000000000001E-8) = LineSearchPoint{point=PointSample{avg=215.06479149788672}, derivative=-229.4620532539873}, evalInputDelta = -8.181530745332566E-6
New Minimum: 215.06479149788672 > 215.06474425847676
F(2.4010000000000004E-7) = LineSearchPoint{point=PointSample{avg=215.06474425847676}, derivative=-229.4620230451539}, evalInputDelta = -5.5420940697104015E-5
New Minimum: 215.06474425847676 > 215.06441487227454
F(1.6807000000000003E-6) = LineSearchPoint{point=PointSample{avg=215.06441487227454}, derivative=-229.4618450935141}, evalInputDelta = -3.8480714292177254E-4
New Minimum: 215.06441487227454 > 215.06209859041866
F(1.1764900000000001E-5) = LineSearchPoint{point=PointSample{avg=215.06209859041866}, derivative=-229.46062176092562}, evalInputDelta = -0.0027010889988048348
New Minimum: 215.06209859041866 > 215.04590257574364
F(8.235430000000001E-5) = LineSearchPoint{point=PointSample{avg=215.04590257574364}, derivative=-229.45200184230836}, evalInputDelta = -0.018897103673822357
New Minimum: 215.04590257574364 > 214.93253991216747
F(5.764801000000001E-4) = LineSearchPoint{point=PointSample{avg=214.93253991216747}, derivative=-229.39148904361284}, evalInputDelta = -0.132259767249991
New Minimum: 214.93253991216747 > 214.13983386471102
F(0.004035360700000001) = LineSearchPoint{point=PointSample{avg=214.13983386471102}, derivative=-228.968036584419}, evalInputDelta = -0.9249658147064395
New Minimum: 214.13983386471102 > 208.63190502087738
F(0.028247524900000005) = LineSearchPoint{point=PointSample{avg=208.63190502087738}, derivative=-226.00394760870245}, evalInputDelta = -6.432894658540079
New Minimum: 208.63190502087738 > 172.0858795620341
F(0.19773267430000002) = LineSearchPoint{point=PointSample{avg=172.0858795620341}, derivative=-205.2553493320004}, evalInputDelta = -42.97892011738335
New Minimum: 172.0858795620341 > 14.727942108425749
F(1.3841287201) = LineSearchPoint{point=PointSample{avg=14.727942108425749}, derivative=-60.01513998270259}, evalInputDelta = -200.33685757099173
F(9.688901040700001) = LineSearchPoint{point=PointSample{avg=3737.9704074090414}, derivative=956.6664548353681}, evalInputDelta = 3522.905607729624
F(0.7453000800538463) = LineSearchPoint{point=PointSample{avg=78.04753518316751}, derivative=-138.22141613887345}, evalInputDelta = -137.01726449624994
F(5.217100560376924) = LineSearchPoint{point=PointSample{avg=683.9789627222535}, derivative=409.22253097563174}, evalInputDelta = 468.9141630428361
F(0.40131542772130185) = LineSearchPoint{point=PointSample{avg=132.8363612412943}, derivative=-180.33249151481718}, evalInputDelta = -82.22843843812316
F(2.809207994049113) = LineSearchPoint{point=PointSample{avg=53.51138775395107}, derivative=114.44501435321085}, evalInputDelta = -161.55341192546638
53.51138775395107 <= 215.06479967941746
New Minimum: 14.727942108425749 > 0.01720666910409742
F(1.874362861498513) = LineSearchPoint{point=PointSample{avg=0.01720666910409742}, derivative=-3.5408099343624266E-6}, evalInputDelta = -215.04759301031336
Left bracket at 1.874362861498513
Converged to left
Fitness changed from 215.06479967941746 to 0.01720666910409742
Iteration 1 complete. Error: 0.01720666910409742 Total: 7.8752; Orientation: 0.0008; Line Search: 7.0047
F(0.0) = LineSearchPoint{point=PointSample{avg=0.01720666910409742}, derivative=-0.018313048649028014}
New Minimum: 0.01720666910409742 > 2.7202216754968363E-6
F(1.874362861498513) = LineSearchPoint{point=PointSample{avg=2.7202216754968363E-6}, derivative=-4.4068705150897165E-5}, evalInputDelta = -0.017203948882421924
F(13.120540030489591) = LineSearchPoint{point=PointSample{avg=0.6158755901940518}, derivative=0.10956979048512795}, evalInputDelta = 0.5986689210899544
F(1.0092723100376608) = LineSearchPoint{point=PointSample{avg=0.0036879961069459016}, derivative=-0.008475906776411017}, evalInputDelta = -0.013518672997151517
F(7.064906170263626) = LineSearchPoint{point=PointSample{avg=0.13107141044831697}, derivative=0.050546948291315175}, evalInputDelta = 0.11386474134421955
F(0.5434543207895097) = LineSearchPoint{point=PointSample{avg=0.008693679467409773}, derivative=-0.01301612411243162}, evalInputDelta = -0.008512989636687646
F(3.804180245526568) = LineSearchPoint{point=PointSample{avg=0.018067107292583016}, derivative=0.018765412265193633}, evalInputDelta = 8.604381884855967E-4
F(0.2926292496558899) = LineSearchPoint{point=PointSample{avg=0.012265048276793113}, derivative=-0.015460855512854834}, evalInputDelta = -0.004941620827304306
F(2.048404747591229) = LineSearchPoint{point=PointSample{avg=1.426681420002624E-4}, derivative=0.0016522775670752927}, evalInputDelta = -0.017064000962097158
1.426681420002624E-4 <= 0.01720666910409742
New Minimum: 2.7202216754968363E-6 > 2.620497159093563E-6
F(1.8788841909971838) = LineSearchPoint{point=PointSample{avg=2.620497159093563E-6}, derivative=-2.788739287149376E-9}, evalInputDelta = -0.017204048606938326
Left bracket at 1.8788841909971838
Converged to left
Fitness changed from 0.01720666910409742 to 2.620497159093563E-6
Iteration 2 complete. Error: 2.620497159093563E-6 Total: 3.6798; Orientation: 0.0004; Line Search: 3.2773
F(0.0) = LineSearchPoint{point=PointSample{avg=2.620497159093563E-6}, derivative=-2.7928706832561195E-6}
New Minimum: 2.620497159093563E-6 > 5.135927824821215E-10
F(1.8788841909971838) = LineSearchPoint{point=PointSample{avg=5.135927824821215E-10}, derivative=3.919166431424559E-9}, evalInputDelta = -2.6199835663110807E-6
5.135927824821215E-10 <= 2.620497159093563E-6
Converged to right
Fitness changed from 2.620497159093563E-6 to 5.135927824821215E-10
Iteration 3 complete. Error: 5.135927824821215E-10 Total: 0.8874; Orientation: 0.0004; Line Search: 0.5897
F(0.0) = LineSearchPoint{point=PointSample{avg=5.135927824821215E-10}, derivative=-5.431845054571689E-10}
New Minimum: 5.135927824821215E-10 > 1.0842390478022503E-12
F(1.8788841909971838) = LineSearchPoint{point=PointSample{avg=1.0842390478022503E-12}, derivative=1.1342369034218835E-12}, evalInputDelta = -5.125085434343193E-10
1.0842390478022503E-12 <= 5.135927824821215E-10
Converged to right
Fitness changed from 5.135927824821215E-10 to 1.0842390478022503E-12
Iteration 4 complete. Error: 1.0842390478022503E-12 Total: 0.8811; Orientation: 0.0003; Line Search: 0.5884
Low gradient: 4.559311498703239E-7
F(0.0) = LineSearchPoint{point=PointSample{avg=1.0842390478022503E-12}, derivative=-2.0787321051908837E-13}
New Minimum: 1.0842390478022503E-12 > 1.2787790413690188E-13
F(1.8788841909971838) = LineSearchPoint{point=PointSample{avg=1.2787790413690188E-13}, derivative=1.3302559419580554E-14}, evalInputDelta = -9.563611436653483E-13
1.2787790413690188E-13 <= 1.0842390478022503E-12
New Minimum: 1.2787790413690188E-13 > 4.01655055435987E-14
F(1.765879187781048) = LineSearchPoint{point=PointSample{avg=4.01655055435987E-14}, derivative=-2.0103122615815566E-15}, evalInputDelta = -1.0440735422586516E-12
Left bracket at 1.765879187781048
Converged to left
Fitness changed from 1.0842390478022503E-12 to 4.01655055435987E-14
Iteration 5 complete. Error: 4.01655055435987E-14 Total: 1.4719; Orientation: 0.0006; Line Search: 1.1762
Low gradient: 4.618678166674104E-8
F(0.0) = LineSearchPoint{point=PointSample{avg=4.01655055435987E-14}, derivative=-2.133218463975584E-15}
New Minimum: 4.0165505
...skipping 1827 bytes...
le{avg=1.397143550935521E-13}, derivative=6.3050750675347485E-15}, evalInputDelta = 9.954884954995341E-14
F(0.559541711164101) = LineSearchPoint{point=PointSample{avg=1.1926358957252475E-14}, derivative=-1.6390114744481827E-16}, evalInputDelta = -2.8239146586346225E-14
F(3.916791978148707) = LineSearchPoint{point=PointSample{avg=8.309054437740555E-14}, derivative=3.1442515747924537E-15}, evalInputDelta = 4.292503883380685E-14
F(0.3012916906268236) = LineSearchPoint{point=PointSample{avg=1.2702777255222528E-14}, derivative=-1.755422863950482E-16}, evalInputDelta = -2.7462728288376174E-14
F(2.109041834387765) = LineSearchPoint{point=PointSample{avg=5.4218730840301423E-14}, derivative=1.957565013917524E-15}, evalInputDelta = 1.4053225296702723E-14
F(0.16223398726059732) = LineSearchPoint{point=PointSample{avg=1.372802673815901E-14}, derivative=-1.8488532836935054E-16}, evalInputDelta = -2.643747880543969E-14
F(1.1356379108241812) = LineSearchPoint{point=PointSample{avg=3.0731533317793796E-14}, derivative=-6.306038284254415E-17}, evalInputDelta = -9.433972225804904E-15
F(7.949465375769268) = LineSearchPoint{point=PointSample{avg=1.5796612264441975E-13}, derivative=7.384425384596946E-15}, evalInputDelta = 1.1780061710082104E-13
F(0.611497336597636) = LineSearchPoint{point=PointSample{avg=8.692150031527003E-15}, derivative=-9.120903121828863E-17}, evalInputDelta = -3.14733555120717E-14
F(4.2804813561834525) = LineSearchPoint{point=PointSample{avg=9.892160848396693E-14}, derivative=4.194598715279965E-15}, evalInputDelta = 5.875610294036823E-14
F(0.32926779662949635) = LineSearchPoint{point=PointSample{avg=1.244374932729023E-14}, derivative=-1.73309221641972E-16}, evalInputDelta = -2.772175621630847E-14
F(2.3048745764064744) = LineSearchPoint{point=PointSample{avg=5.830440979908324E-14}, derivative=2.0281141792404364E-15}, evalInputDelta = 1.813890425548454E-14
F(0.17729804433895957) = LineSearchPoint{point=PointSample{avg=1.3704716154606909E-14}, derivative=-1.8441170244187856E-16}, evalInputDelta = -2.646078938899179E-14
F(1.241086310372717) = LineSearchPoint{point=PointSample{avg=3.028909713165915E-14}, derivative=-5.746906962484294E-17}, evalInputDelta = -9.87640841193955E-15
F(8.687604172609019) = LineSearchPoint{point=PointSample{avg=1.7076874319689029E-13}, derivative=8.384882234912885E-15}, evalInputDelta = 1.3060323765329157E-13
F(0.6682772440468476) = LineSearchPoint{point=PointSample{avg=8.59804093289263E-15}, derivative=-8.94640545061407E-17}, evalInputDelta = -3.1567464610706073E-14
F(4.677940708327934) = LineSearchPoint{point=PointSample{avg=1.0193137913726224E-13}, derivative=4.259405753080191E-15}, evalInputDelta = 6.176587359366354E-14
F(0.3598415929483026) = LineSearchPoint{point=PointSample{avg=1.2390002089405224E-14}, derivative=-1.722989782891157E-16}, evalInputDelta = -2.7775503454193477E-14
F(2.518891150638118) = LineSearchPoint{point=PointSample{avg=6.651913436307061E-14}, derivative=2.0948426394453596E-15}, evalInputDelta = 2.6353628819471914E-14
F(0.19376085774139368) = LineSearchPoint{point=PointSample{avg=1.3676926583837855E-14}, derivative=-1.8389921134012276E-16}, evalInputDelta = -2.6488578959760845E-14
F(1.3563260041897558) = LineSearchPoint{point=PointSample{avg=3.073200834087175E-14}, derivative=-5.542201911915433E-17}, evalInputDelta = -9.433497202726952E-15
F(9.494282029328291) = LineSearchPoint{point=PointSample{avg=1.8954216847950435E-13}, derivative=9.449422390475483E-15}, evalInputDelta = 1.4937666293590566E-13
F(0.730329386871407) = LineSearchPoint{point=PointSample{avg=7.870213607110955E-15}, derivative=-8.402351153442732E-17}, evalInputDelta = -3.229529193648775E-14
F(5.112305708099849) = LineSearchPoint{point=PointSample{avg=1.0761254477881845E-13}, derivative=4.267636427639334E-15}, evalInputDelta = 6.744703923521974E-14
F(0.3932542852384499) = LineSearchPoint{point=PointSample{avg=1.2324591105780266E-14}, derivative=-1.7127068361635848E-16}, evalInputDelta = -2.7840914437818434E-14
F(2.7527799966691493) = LineSearchPoint{point=PointSample{avg=6.661075549333034E-14}, derivative=2.100131310977601E-15}, evalInputDelta = 2.6445249949731638E-14
F(0.21175230743608842) = LineSearchPoint{point=PointSample{avg=1.3649726234927949E-14}, derivative=-1.8335486268912689E-16}, evalInputDelta = -2.6515779308670752E-14
F(1.482266152052619) = LineSearchPoint{point=PointSample{avg=3.031482637107009E-14}, derivative=-5.1369682245845267E-17}, evalInputDelta = -9.850679172528608E-15
F(10.375863064368334) = LineSearchPoint{point=PointSample{avg=2.071109948165547E-13}, derivative=1.0476700864705927E-14}, evalInputDelta = 1.66945489272956E-13
F(0.798143312643718) = LineSearchPoint{point=PointSample{avg=7.507891425959682E-15}, derivative=-8.173078759110577E-17}, evalInputDelta = -3.265761411763902E-14
F(5.587003188506026) = LineSearchPoint{point=PointSample{avg=1.0791480763789084E-13}, derivative=4.2755372191800956E-15}, evalInputDelta = 6.774930209429214E-14
F(0.42976947603892507) = LineSearchPoint{point=PointSample{avg=1.2190751477076796E-14}, derivative=-1.6897861138585877E-16}, evalInputDelta = -2.7974754066521903E-14
F(3.0083863322724755) = LineSearchPoint{point=PointSample{avg=6.677725949392943E-14}, derivative=2.1064368368296123E-15}, evalInputDelta = 2.661175395033073E-14
F(0.2314143332517289) = LineSearchPoint{point=PointSample{avg=1.3607821658499917E-14}, derivative=-1.8278590206218723E-16}, evalInputDelta = -2.6557683885098783E-14
F(1.6199003327621022) = LineSearchPoint{point=PointSample{avg=3.0039240858491034E-14}, derivative=-4.876505300417517E-17}, evalInputDelta = -1.0126264685107667E-14
F(11.339302329334716) = LineSearchPoint{point=PointSample{avg=2.2617088338194306E-13}, derivative=1.157756143842152E-14}, evalInputDelta = 1.8600537783834434E-13
F(0.8722540253334397) = LineSearchPoint{point=PointSample{avg=7.3526426170487E-15}, derivative=-7.88684516322944E-17}, evalInputDelta = -3.2812862926550004E-14
F(6.105778177334077) = LineSearchPoint{point=PointSample{avg=1.3482443240743768E-13}, derivative=6.228668650196159E-15}, evalInputDelta = 9.465892686383898E-14
F(0.4696752444103136) = LineSearchPoint{point=PointSample{avg=1.2102279664385391E-14}, derivative=-1.6732882907715877E-16}, evalInputDelta = -2.806322587921331E-14
F(3.287726710872195) = LineSearchPoint{point=PointSample{avg=6.736092870447633E-14}, derivative=2.115188381562842E-15}, evalInputDelta = 2.7195423160877627E-14
F(0.25290205468247656) = LineSearchPoint{point=PointSample{avg=1.3565886589797174E-14}, derivative=-1.8205659720279117E-16}, evalInputDelta = -2.6599618953801526E-14
F(1.770314382777336) = LineSearchPoint{point=PointSample{avg=2.996292514219037E-14}, derivative=-4.7216947696893625E-17}, evalInputDelta = -1.020258040140833E-14
F(12.392200679441352) = LineSearchPoint{point=PointSample{avg=2.4535332560756725E-13}, derivative=1.2624023064686947E-14}, evalInputDelta = 2.0518782006396854E-13
Loops = 52
F(1.7913423214853994) = LineSearchPoint{point=PointSample{avg=2.99495589926732E-14}, derivative=-4.7063546295897995E-17}, evalInputDelta = -1.0215946550925503E-14
Left bracket at 1.7913423214853994
F(1.8307165285619633) = LineSearchPoint{point=PointSample{avg=2.973186347017958E-14}, derivative=-4.4882039968810206E-17}, evalInputDelta = -1.043364207341912E-14
Left bracket at 1.8307165285619633
F(1.868132623313159) = LineSearchPoint{point=PointSample{avg=2.970123058083E-14}, derivative=-4.453397433433496E-17}, evalInputDelta = -1.04642749627687E-14
Left bracket at 1.868132623313159
F(1.9051280423858112) = LineSearchPoint{point=PointSample{avg=2.967810159256776E-14}, derivative=-4.430777313639586E-17}, evalInputDelta = -1.0487403951030943E-14
Left bracket at 1.9051280423858112
F(1.9418068157156216) = LineSearchPoint{point=PointSample{avg=4.2736437860521333E-14}, derivative=9.551614588695724E-16}, evalInputDelta = 2.570932316922633E-15
Right bracket at 1.9418068157156216
Converged to left
Fitness changed from 4.01655055435987E-14 to 7.097573165140051E-15
Iteration 6 complete. Error: 7.097573165140051E-15 Total: 19.5705; Orientation: 0.0005; Line Search: 19.2760
Final threshold in iteration 6: 7.097573165140051E-15 (> 0.0) after 34.366s (< 30.000s)
Returns
7.097573165140051E-15
Next, we apply the same optimization using L-BFGS, which is nearly ideal for purely second-order or quadratic functions.
TrainingTester.java:509 executed in 33.87 seconds (0.063 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new ArmijoWolfeSearch());
iterativeTrainer.setOrientation(new LBFGS());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setIterationsPerSample(100);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 13282376564542
Reset training subject: 13282666617078
Adding measurement a99ecc8 to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD
Non-optimal measurement 215.06479967941746 < 215.06479967941746. Total: 1
th(0)=215.06479967941746;dx=-229.4620602688528
Adding measurement 747eff3e to history. Total: 1
New Minimum: 215.06479967941746 > 4.818585933522571
WOLF (strong): th(2.154434690031884)=4.818585933522571; dx=34.286773567024994 evalInputDelta=210.2462137458949
Non-optimal measurement 38.91298544036259 < 4.818585933522571. Total: 2
END: th(1.077217345015942)=38.91298544036259; dx=-97.58764427597178 evalInputDelta=176.1518142390549
Fitness changed from 215.06479967941746 to 4.818585933522571
Iteration 1 complete. Error: 4.818585933522571 Total: 1.7463; Orientation: 0.0012; Line Search: 0.8802
Non-optimal measurement 4.818585933522571 < 4.818585933522571. Total: 2
LBFGS Accumulation History: 2 points
Non-optimal measurement 4.818585933522571 < 4.818585933522571. Total: 2
th(0)=4.818585933522571;dx=-5.14740709758051
Adding measurement 5543e849 to history. Total: 2
New Minimum: 4.818585933522571 > 0.27714843181188215
WOLF (strong): th(2.3207944168063896)=0.27714843181188215; dx=1.2337147784883316 evalInputDelta=4.541437501710689
Non-optimal measurement 0.6967081880992423 < 0.27714843181188215. Total: 3
END: th(1.1603972084031948)=0.6967081880992423; dx=-1.9568462282456855 evalInputDelta=4.121877745423329
Fitness changed from 4.818585933522571 to 0.27714843181188215
Iteration 2 complete. Error: 0.27714843181188215 Total: 1.1890; Orientation: 0.0013; Line Search: 0.8961
Non-optimal measurement 0.27714843181188215 < 0.27714843181188215. Total: 3
LBFGS Accumulation History: 3 points
Non-optimal measurement 0.27714843181188215 < 0.27714843181188215. Total: 3
th(0)=0.27714843181188215;dx=-0.29629088463366665
Adding measurement 44073ef3 to history. Total: 3
New Minimum: 0.27714843181188215 > 0.03138757155207211
WOLF (strong): th(2.5000000000000004)=0.03138757155207211; dx=0.09968220486991236 evalInputDelta=0.24576086025981003
Adding measurement 344ee149 to history. Total: 4
New Minimum: 0.03138757155207211 > 0.030526404107874786
END: th(1.2500000000000002)=0.030526404107874786; dx=-0.09830433925054516 evalInputDelta=0.24662202770400737
Fitness changed from 0.27714843181188215 to 0.030526404107874786
Iteration 3 complete. Error: 0.030526404107874786 Total: 1.1667; Orientation: 0.0016; Line Search: 0.8752
Non-optimal measurement 0.030526404107874786 < 0.030526404107874786. Total: 5
Rejected: LBFGS Orientation magnitude: 3.380e-01, gradient 1.806e-01, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.030526404107874786, 0.03138757155207211, 0.27714843181188215, 4.818585933522571, 215.06479967941746
Rejected: LBFGS Orientation magnitude: 3.380e-01, gradient 1.806e-01, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.030526404107874786, 0.03138757155207211, 0.27714843181188215, 4.818585933522571
LBFGS Accumulation History: 3 points
Removed measurement 344ee149 to history. Total: 4
Removed measurement 44073ef3 to history. Total: 3
Adding measurement 3e2e3c2d to history. Total: 3
th(0)=0.030526404107874786;dx=-0.03262527335886124
Adding measurement 4b4716d5 to history. Total: 4
New Minimum: 0.030526404107874786 > 0.005890501328985009
WOLF (strong): th(2.6930433625398553)=0.005890501328985009; dx=0.014329316119754663 evalInputDelta=0.024635902778889777
Adding measurement 731acc3c to history. Total: 5
New Minimum: 0.005890501328985009 > 0.0024021086523462907
END: th(1.3465216812699277)=0.0024021086523462907; dx=-0.00914797679591191 evalInputDelta=0.028124295455528494
Fitness changed from 0.030526404107874786 to 0.0024021086523462907
Iteration 4 complete. Error: 0.0024021086523462907 Total: 1.3572; Orientation: 0.1979; Line Search: 0.8719
Non-optimal measurement 0.0024021086523462907 < 0.0024021086523462907. Total: 6
Rejected: LBFGS Orientation magnitude: 9.484e-02, gradient 5.066e-02, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.0024021086523462907, 0.005890501328985009, 0.030526404107874786, 0.27714843181188215, 4.818585933522571, 215.06479967941746
Rejected: LBFGS Orientation magnitude: 9.484e-02, gradient 5.066e-02, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.0024021086523462907, 0.005890501328985009, 0.030526404107874786, 0.27714843181188215, 4.818585933522571
Rejected: LBFGS Orientation magnitude: 9.484e-02, gradient 5.066e-02, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.0024021086523462907, 0.005890501328985009, 0.030526404107874786, 0.27714843181188215
LBFGS Accumulation History: 3 points
Removed measurement 731acc3c to history. Total: 5
Removed measurement 4b4716d5 to history. Total: 4
Removed measurement 3e2e3c2d to history. Total: 3
Adding measurement 45ab7388 to history. Total: 3
th(0)=0.0024021086523462907;dx=-0.0025662916360590735
Adding measurement 21d57bca to history. Total: 4
New Minimum: 0.0024021086523462907 > 7.261132260698287E-4
WOLF (strong): th(2.9009930210079875)=7.261132260698287E-4; dx=0.0014108282149454896 evalInputDelta=0.001675995426276462
Adding measurement 2007435c to history. Total: 5
New Minimum: 7.261132260698287E-4 > 1.2191136677586545E-4
END: th(1.4504965105039938)=1.2191136677586545E-4; dx=-5.777311248633191E-4 evalInputDelta=0.0022801972855704252
Fitness changed from 0.0024021086523462907 to 1.2191136677586545E-4
Iteration 5 complete. Error: 1.2191136677586545E-4 Total: 1.8037; Orientation: 0.6341; Line Search: 0.8820
Non-optimal measurement 1.2191136677586545E-4 < 1.2191136677586545E-4. Total: 6
Rejected: LBFGS Orientation magnitude: 2.137e-02, gradient 1.141e-02, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 1.2191136677586545E-4, 7.261132260698287E-4, 0.0024021086523462907, 0.27714843181188215, 4.818585933522571, 215.06479967941746
Rejected: LBFGS Orientation magnitude: 2.137e-02, gradient 1.141e-02, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 1.2191136677586545E-4, 7.261132260698287E-4, 0.0024021086523462907, 0.27714843181188215, 4.818585933522571
Rejected: LBFGS Orientation magnitude: 2.137e-02, gradient 1.141e-02, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 1.2191136677586545E-4, 7.261132260698287E-4, 0.0024021086523462907, 0.27714843181188215
LBFGS Accumulation History: 3 points
Removed measurement 2007435c to history. Total: 5
Removed measurement 21d57bca to history. Total: 4
Removed measurement 45ab7388 to history. Total: 3
Adding measurement 30452f43 to history. Total: 3
th(0)=1.2191136677586545E-4;dx=-1.301760962386862E-4
Adding measurement 7e809b85 to history. Total: 4
New Minimum: 1.2191136677586545E-4 > 5.449510024307755E-5
WOLF (strong): th(3.125000000000001)=5.449510024307755E-5; dx=8.702963097011848E-5 evalInputDelta=6.74162665327879E-5
Adding measurement 383b5cd to history. Total: 5
New Minimum: 5.449510024307755E-5 > 3.357341884323087E-6
END: th(1.5625000000000004)=3.357341884323087E-6; dx=-2.157320839142924E-5 evalInputDelta=1.1855402489154236E-4
Fitness changed from 1.2191136677586545E-4 to 3.357341884323087E-6
Iteration 6 complete. Error: 3.357341884323087E-6 Total: 1.7564; Orientation: 0.5829; Line Search: 0.8817
Non-optimal measurement 3.357341884323087E-6 < 3.357341884323087E-6. Total: 6
Rejected: LBFGS Orientation magnitude: 3.548e-03, gradient 1.893e-03, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 3.357341884323087E-6, 5.449510024307755E-5, 1.2191136677586545E-4, 0.27714843181188215, 4.818585933522571, 215.06479967941746
Rejected: LBFGS Orientation magnitude
...skipping 13690 bytes...
nputDelta=-1.918543703331451E-14
Non-optimal measurement 2.1439633790281225E-14 < 1.8475683891113187E-15. Total: 4
Armijo: th(2.034505208333335)=2.1439633790281225E-14; dx=-4.354429462071967E-18 evalInputDelta=-1.9592065401169908E-14
Non-optimal measurement 2.168794980818351E-14 < 1.8475683891113187E-15. Total: 4
Armijo: th(0.6781684027777782)=2.168794980818351E-14; dx=-5.289470094592219E-18 evalInputDelta=-1.984038141907219E-14
Adding measurement 3c8f0afe to history. Total: 4
New Minimum: 1.8475683891113187E-15 > 1.822615652703599E-15
WOLFE (weak): th(0.16954210069444456)=1.822615652703599E-15; dx=-6.8350034462612144E-18 evalInputDelta=2.4952736407719566E-17
Adding measurement 4346b7c6 to history. Total: 5
New Minimum: 1.822615652703599E-15 > 1.7770273941906296E-15
WOLFE (weak): th(0.4238552517361114)=1.7770273941906296E-15; dx=-6.6568847775004705E-18 evalInputDelta=7.054099492068908E-17
Non-optimal measurement 2.1709974446531994E-14 < 1.7770273941906296E-15. Total: 6
Armijo: th(0.5510118272569449)=2.1709974446531994E-14; dx=-5.376308916466533E-18 evalInputDelta=-1.9862406057420673E-14
Adding measurement 7038aeeb to history. Total: 6
New Minimum: 1.7770273941906296E-15 > 1.7686918023151993E-15
WOLFE (weak): th(0.4874335394965281)=1.7686918023151993E-15; dx=-6.618666257546106E-18 evalInputDelta=7.887658679611937E-17
Non-optimal measurement 2.1714200821301056E-14 < 1.7686918023151993E-15. Total: 7
Armijo: th(0.5192226833767365)=2.1714200821301056E-14; dx=-5.392947211136688E-18 evalInputDelta=-1.9866632432189736E-14
Non-optimal measurement 2.1714966532176496E-14 < 1.7686918023151993E-15. Total: 7
Armijo: th(0.5033281114366324)=2.1714966532176496E-14; dx=-5.39412080789246E-18 evalInputDelta=-1.986739814306518E-14
Non-optimal measurement 2.1717935964716726E-14 < 1.7686918023151993E-15. Total: 7
Armijo: th(0.49538082546658024)=2.1717935964716726E-14; dx=-5.399596786511553E-18 evalInputDelta=-1.987036757560541E-14
Adding measurement 4635a6a7 to history. Total: 7
New Minimum: 1.7686918023151993E-15 > 1.7686915165813802E-15
WOLFE (weak): th(0.4914071824815542)=1.7686915165813802E-15; dx=-6.618654876353406E-18 evalInputDelta=7.887687252993844E-17
Non-optimal measurement 1.7686915165813802E-15 < 1.7686915165813802E-15. Total: 8
mu ~= nu (0.4914071824815542): th(0.4914071824815542)=1.7686915165813802E-15
Fitness changed from 1.8475683891113187E-15 to 1.7686915165813802E-15
Iteration 15 complete. Error: 1.7686915165813802E-15 Total: 4.7585; Orientation: 0.6475; Line Search: 3.8187
Non-optimal measurement 1.7686915165813802E-15 < 1.7686915165813802E-15. Total: 8
Rejected: LBFGS Orientation magnitude: 3.935e-08, gradient 2.516e-09, dot -0.986; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 1.7686915165813802E-15, 1.7686918023151993E-15, 1.7770273941906296E-15, 1.822615652703599E-15, 1.8475683891113187E-15, 0.27714843181188215, 4.818585933522571, 215.06479967941746
Rejected: LBFGS Orientation magnitude: 3.938e-08, gradient 2.516e-09, dot -0.986; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 1.7686915165813802E-15, 1.7686918023151993E-15, 1.7770273941906296E-15, 1.822615652703599E-15, 1.8475683891113187E-15, 0.27714843181188215, 4.818585933522571
Rejected: LBFGS Orientation magnitude: 3.939e-08, gradient 2.516e-09, dot -0.987; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 1.7686915165813802E-15, 1.7686918023151993E-15, 1.7770273941906296E-15, 1.822615652703599E-15, 1.8475683891113187E-15, 0.27714843181188215
Rejected: LBFGS Orientation magnitude: 5.253e-08, gradient 2.516e-09, dot -0.965; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 1.7686915165813802E-15, 1.7686918023151993E-15, 1.7770273941906296E-15, 1.822615652703599E-15, 1.8475683891113187E-15
Rejected: LBFGS Orientation magnitude: 3.980e-08, gradient 2.516e-09, dot -0.956; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 1.7686915165813802E-15, 1.7686918023151993E-15, 1.7770273941906296E-15, 1.822615652703599E-15
LBFGS Accumulation History: 3 points
Removed measurement 4635a6a7 to history. Total: 7
Removed measurement 7038aeeb to history. Total: 6
Removed measurement 4346b7c6 to history. Total: 5
Removed measurement 3c8f0afe to history. Total: 4
Removed measurement 39fbe2a9 to history. Total: 3
Adding measurement 18ca68ba to history. Total: 3
th(0)=1.7686915165813802E-15;dx=-6.327946541465962E-18
Non-optimal measurement 2.1537569539298363E-14 < 1.7686915165813802E-15. Total: 4
Armijo: th(1.0629851580154595)=2.1537569539298363E-14; dx=-4.366152622748455E-18 evalInputDelta=-1.9768878022716983E-14
Non-optimal measurement 2.1623586454146442E-14 < 1.7686915165813802E-15. Total: 4
Armijo: th(0.5314925790077297)=2.1623586454146442E-14; dx=-4.683439606616336E-18 evalInputDelta=-1.9854894937565062E-14
Non-optimal measurement 2.1689578025549154E-14 < 1.7686915165813802E-15. Total: 4
Armijo: th(0.17716419300257658)=2.1689578025549154E-14; dx=-4.910353523674189E-18 evalInputDelta=-1.9920886508967774E-14
Non-optimal measurement 2.171061460210728E-14 < 1.7686915165813802E-15. Total: 4
Armijo: th(0.044291048250644144)=2.171061460210728E-14; dx=-4.98704962288744E-18 evalInputDelta=-1.99419230855259E-14
Non-optimal measurement 2.1717303793488828E-14 < 1.7686915165813802E-15. Total: 4
Armijo: th(0.008858209650128828)=2.1717303793488828E-14; dx=-5.003653220949595E-18 evalInputDelta=-1.9948612276907448E-14
Adding measurement 646d4006 to history. Total: 4
New Minimum: 1.7686915165813802E-15 > 1.7685693752852945E-15
WOLFE (weak): th(0.0014763682750214713)=1.7685693752852945E-15; dx=-6.322762210960109E-18 evalInputDelta=1.2214129608574616E-19
Non-optimal measurement 2.1717304334560183E-14 < 1.7685693752852945E-15. Total: 5
Armijo: th(0.00516728896257515)=2.1717304334560183E-14; dx=-5.003674774229484E-18 evalInputDelta=-1.9948612817978803E-14
Non-optimal measurement 2.1717935983109226E-14 < 1.7685693752852945E-15. Total: 5
Armijo: th(0.0033218286187983105)=2.1717935983109226E-14; dx=-5.0061069839737094E-18 evalInputDelta=-1.9949244466527846E-14
Non-optimal measurement 2.1717936008914734E-14 < 1.7685693752852945E-15. Total: 5
Armijo: th(0.0023990984469098907)=2.1717936008914734E-14; dx=-5.0061086898232626E-18 evalInputDelta=-1.9949244492333354E-14
Adding measurement 310429ff to history. Total: 5
New Minimum: 1.7685693752852945E-15 > 1.7685693749748925E-15
WOLFE (weak): th(0.001937733360965681)=1.7685693749748925E-15; dx=-6.322761755210151E-18 evalInputDelta=1.2214160648772122E-19
Non-optimal measurement 2.1717936008914734E-14 < 1.7685693749748925E-15. Total: 6
Armijo: th(0.0021684159039377857)=2.1717936008914734E-14; dx=-5.0061085361663485E-18 evalInputDelta=-1.9949244492333354E-14
Non-optimal measurement 1.7685693749748925E-15 < 1.7685693749748925E-15. Total: 6
WOLFE (weak): th(0.0020530746324517336)=1.7685693749748925E-15; dx=-6.322762449279115E-18 evalInputDelta=1.2214160648772122E-19
Non-optimal measurement 2.1717936008914734E-14 < 1.7685693749748925E-15. Total: 6
Armijo: th(0.0021107452681947596)=2.1717936008914734E-14; dx=-5.006107594641974E-18 evalInputDelta=-1.9949244492333354E-14
Non-optimal measurement 1.7685693749748925E-15 < 1.7685693749748925E-15. Total: 6
WOLFE (weak): th(0.0020819099503232466)=1.7685693749748925E-15; dx=-6.322762168388665E-18 evalInputDelta=1.2214160648772122E-19
Non-optimal measurement 2.1717936008914734E-14 < 1.7685693749748925E-15. Total: 6
Armijo: th(0.002096327609259003)=2.1717936008914734E-14; dx=-5.006109251664406E-18 evalInputDelta=-1.9949244492333354E-14
Non-optimal measurement 1.7685693749748925E-15 < 1.7685693749748925E-15. Total: 6
mu ~= nu (0.0020819099503232466): th(0.001937733360965681)=1.7685693749748925E-15
Fitness changed from 1.7686915165813802E-15 to 1.7685693749748925E-15
Iteration 16 complete. Error: 1.7685693749748925E-15 Total: 6.2749; Orientation: 0.9794; Line Search: 5.0023
Final threshold in iteration 16: 1.7685693749748925E-15 (> 0.0) after 33.867s (< 30.000s)
Returns
1.7685693749748925E-15
TrainingTester.java:432 executed in 0.01 seconds (0.000 gc):
return TestUtil.compare(title + " vs Iteration", runs);
Plotting range=[1.0, -17.090177061856373], [20.0, 0.6829196084941063]; valueStats=DoubleSummaryStatistics{count=42, sum=10.274784, min=0.000000, average=0.244638, max=4.818586}
Plotting 20 points for GD
Plotting 6 points for CjGD
Plotting 16 points for LBFGS
Returns
TrainingTester.java:435 executed in 0.01 seconds (0.000 gc):
return TestUtil.compareTime(title + " vs Time", runs);
Plotting range=[0.0, -17.090177061856373], [32.121, 0.6829196084941063]; valueStats=DoubleSummaryStatistics{count=42, sum=10.274784, min=0.000000, average=0.244638, max=4.818586}
Plotting 20 points for GD
Plotting 6 points for CjGD
Plotting 16 points for LBFGS
Returns
In this apply, attempt to train a network to emulate a randomized network given an example input/output. The target state is:
TrainingTester.java:279 executed in 0.00 seconds (0.000 gc):
RefList<double[]> temp_18_0037 = temp_18_0035.state();
assert temp_18_0037 != null;
String temp_18_0036 = temp_18_0037.stream().map(RefArrays::toString).reduce((a, b) -> a + "\n" + b).orElse("");
temp_18_0037.freeRef();
return temp_18_0036;
Returns
We simultaneously regress this target input:
TrainingTester.java:287 executed in 0.01 seconds (0.000 gc):
return RefArrays.stream(RefUtil.addRef(input_target)).flatMap(x -> {
RefStream<Tensor> temp_18_0006 = RefArrays.stream(RefUtil.addRef(x));
if (null != x)
RefUtil.freeRef(x);
return temp_18_0006;
}).map(x -> {
String temp_18_0007 = x.prettyPrint();
x.freeRef();
return temp_18_0007;
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
[ [ 0.74, 1.84, 1.472, -1.336, -1.868, 1.068, -1.588 ], [ 0.452, -1.148, 0.496, 0.524, 0.328, -0.376, -1.196 ], [ -1.68, 0.796, 0.788, 0.868, -0.1, 0.708, 1.5 ], [ -1.768, 0.972, 1.472, -1.276, -0.492, 1.024, 0.208 ], [ 1.272, -1.824, 0.304, 1.352, -1.504, -1.44, 1.616 ], [ 0.656, 1.044, 1.428, 1.668, 0.136, -1.228, -0.548 ], [ 1.052, -1.384, 1.348, 1.524, -1.276, -1.44, -1.676 ], [ -0.46, -1.6, -0.072, 1.368, -1.328, 1.304, -1.136 ], ... ],
[ [ -0.72, 1.824, 0.956, -0.248, 0.38, 1.376, -1.144 ], [ 1.548, -0.344, -0.184, -1.152, 1.284, -0.86, -1.924 ], [ 1.24, 1.036, -0.736, 1.964, 0.776, -1.76, -0.812 ], [ -0.04, 1.936, -0.256, -1.868, 1.552, -1.236, 1.06 ], [ 1.432, -1.496, 0.048, 1.504, 1.1, 0.02, 1.932 ], [ -0.008, 1.624, -0.24, 1.616, -1.584, 0.764, 0.896 ], [ -0.224, -0.012, 1.024, -0.244, -1.9, 1.136, 1.268 ], [ 1.616, 1.188, 0.092, 0.984, -0.944, -0.06, 0.984 ], ... ],
[ [ 0.58, 1.36, -0.648, -0.512, -1.052, 0.012, -1.044 ], [ 0.828, 0.456, 1.976, -1.488, 1.492, 0.32, -1.628 ], [ -1.732, 0.832, 1.416, -1.452, -1.224, 1.64, 0.756 ], [ -0.6, -1.528, 0.76, 1.196, 0.2, 1.948, -1.576 ], [ -1.508, 1.392, 0.516, -1.784, -0.132, 0.868, -0.636 ], [ 0.512, 0.932, -1.108, 0.892, 1.288, -0.156, 0.164 ], [ -0.328, 0.064, 0.264, -0.936, 1.932, -0.368, 0.744 ], [ -0.564, 0.068, -1.46, -0.4, -0.48, -1.924, 1.188 ], ... ],
[ [ -0.156, -1.112, 0.52, -1.36, -1.084, -1.968, 1.22 ], [ 1.48, -0.464, 1.64, 1.204, 0.204, 0.116, -1.552 ], [ 1.24, 0.38, -1.928, 0.868, -1.724, -0.228, -0.172 ], [ 0.52, 0.204, 0.232, -0.704, 1.504, -1.512, 1.004 ], [ -0.996, 0.264, 1.912, -0.368, 1.076, -2.0, 0.136 ], [ -0.268, 0.74, -1.952, 1.556, -1.812, -1.744, 0.212 ], [ -1.568, 1.368, -1.704, 0.02, -0.712, 1.984, -0.548 ], [ 0.356, -1.508, 0.176, -1.156, -1.428, -0.352, -1.376 ], ... ],
[ [ 1.444, -1.272, 1.004, 1.604, 0.816, -1.596, -0.396 ], [ 0.328, 1.288, -0.584, 1.16, -0.848, -0.324, 0.66 ], [ 0.92, 1.724, -1.224, 0.292, -1.848, 0.8, -0.504 ], [ 1.568, 0.288, -1.328, 1.988, -1.916, -1.376, 1.888 ], [ 0.352, 1.268, 0.688, 0.22, 0.636, -1.78, 0.384 ], [ -1.072, -1.864, 0.596, -1.552, 0.284, -0.048, 1.516 ], [ -0.388, -0.08, -1.152, 1.468, -0.624, 0.596, 0.2 ], [ 0.544, -1.228, 0.64, -0.44, 0.092, -0.868, 0.38 ], ... ],
[ [ -0.828, -0.196, 1.3, -0.576, -0.244, 1.156, -0.4 ], [ -0.088, 0.956, -0.492, 0.372, 1.9, 1.164, 0.716 ], [ 1.644, 0.176, -1.488, 1.064, 0.376, 1.436, 0.996 ], [ -0.544, -0.604, -1.02, -0.764, 1.848, 0.804, -1.94 ], [ 1.048, 1.1, 0.004, 0.872, 1.636, 0.604, -1.716 ], [ -0.652, 0.228, 1.6, -0.852, 1.744, -0.904, 0.6 ], [ 1.476, -1.476, 1.276, -0.384, -0.864, -0.276, 0.94 ], [ -1.376, -1.56, -1.792, 1.244, -0.732, 1.876, -1.316 ], ... ],
[ [ -0.552, 0.784, -0.764, 1.7, -1.684, -0.028, 0.092 ], [ 1.728, 1.632, 0.06, -1.224, -1.952, -1.488, 1.696 ], [ -0.336, 0.988, -0.476, -0.52, 0.968, 0.504, 0.424 ], [ 0.576, 1.084, -1.22, 0.848, 0.036, 0.476, 0.104 ], [ 0.72, -1.048, -0.4, 0.404, 0.268, -1.188, 1.644 ], [ 0.296, -0.648, 1.132, 1.88, -0.796, 1.96, 0.308 ], [ -0.212, -0.516, -1.468, 0.44, 0.468, 0.788, 0.648 ], [ -0.296, 0.424, 1.128, 0.692, 0.644, -0.288, -0.128 ], ... ],
[ [ 0.356, 1.332, 0.184, 0.58, 1.656, -1.556, -0.504 ], [ 0.792, -1.812, -1.556, 1.352, -0.672, 1.58, -1.976 ], [ -1.876, -1.672, 1.944, -1.208, -0.356, 0.672, 1.024 ], [ -1.304, -1.708, -0.232, 1.676, 1.344, -0.52, -1.156 ], [ 0.312, -0.536, 1.868, 1.032, 0.28, -1.92, 1.568 ], [ -1.468, 1.424, 0.716, -0.628, 1.948, 1.916, 0.376 ], [ 0.828, -1.144, 1.276, -0.396, 0.468, -1.324, -0.12 ], [ -1.112, 0.6, 0.824, -1.38, -1.796, -0.032, -0.948 ], ... ],
...
]
[
[ [ 0.16, -1.264, -0.48, -1.352, -0.656, 1.84, -0.52 ], [ -1.616, 1.868, -0.368, -1.272, -0.736, -1.396, -1.456 ], [ 0.652, -1.052, 0.036, -0.936, -0.928, 1.792, -1.068 ], [ 1.132, 1.432, 1.136, 1.216, -1.032, -1.656, 1.996 ], [ 0.2, 0.12, 0.456, -0.516, 0.68, 1.176, 1.388 ], [ -1.064, 0.344, 0.532, 1.752, 1.332, 1.628, 0.964 ], [ -1.548, 0.316, 1.296, 0.1, 1.04, -0.824, -0.956 ], [ 1.14, 0.492, -0.016, -0.372, -0.16, 0.8, 1.68 ], ... ],
[ [ 0.2, -1.928, -0.768, 1.952, -0.116, -0.324, -0.388 ], [ -0.308, -1.016, 0.76, -1.708, 1.956, 0.328, 1.504 ], [ 0.908, -1.324, 1.724, 1.836, -1.832, 1.696, -1.992 ], [ -1.008, 1.824, -1.3, 0.66, 0.824, -1.772, -0.836 ], [ 0.1, 0.088, 1.804, -0.62, -1.096, -0.516, 1.38 ], [ -0.06, 0.996, 1.448, 1.868, 1.932, 1.252, -0.8 ], [ 0.292, -1.204, 1.548, -0.304, -1.0, 0.284, 1.968 ], [ -1.768, -0.352, 0.52, -1.468, -0.568, 0.456, -1.692 ], ... ],
[ [ -0.516, 0.192, -0.708, -0.292, 0.0, -1.164, -1.616 ], [ 0.048, 0.472, 1.22, -0.044, -1.684, -1.588, -0.768 ], [ -1.732, -1.712, -0.704, 1.668, -0.46, 1.66, 1.5 ], [ 1.808, -1.792, -1.228, 1.364, 0.912, 1.064, -1.836 ], [ 0.912, 0.252, 0.22, 0.1, 1.016, 1.688, 1.88 ], [ 1.252, 0.484, 1.816, 0.48, -1.14, -1.5, -1.948 ], [ 0.828, -0.316, -0.204, 0.924, -1.18, 0.592, 0.024 ], [ 0.7, -0.16, 0.044, -1.176, -1.66, 1.904, -1.432 ], ... ],
[ [ -1.936, -0.2, -1.008, -0.456, -1.152, 1.74, -1.372 ], [ 0.02, -0.036, -1.996, -1.628, 0.6, -0.256, 0.8 ], [ 1.164, -1.472, -0.548, -0.268, 0.956, -0.588, -0.232 ], [ -0.992, 1.884, 0.536, -0.904, -0.248, 1.08, 0.112 ], [ -1.684, -0.252, -1.344, 1.632, 1.872, 1.216, -0.468 ], [ -1.7, -0.656, 1.76, 1.788, -0.036, 0.552, -1.056 ], [ -0.2, -1.376, -1.24, 1.42, -0.68, -0.388, -1.284 ], [ 0.356, -1.944, -1.192, -1.664, 1.28, -0.596, -0.668 ], ... ],
[ [ -0.712, -0.572, 1.98, 0.068, 0.2, 0.408, -0.472 ], [ -0.124, 0.68, 0.868, 0.096, 0.888, 0.272, 1.828 ], [ 0.792, 0.48, 1.348, -1.64, -0.716, 0.492, 0.316 ], [ -1.996, -0.636, 1.072, -1.796, -1.016, -1.004, -0.948 ], [ 0.148, 1.876, -0.392, 0.648, -1.516, -0.476, -1.864 ], [ 0.428, -0.816, -0.896, 0.452, 0.304, -1.64, 0.828 ], [ -1.424, 1.912, 0.488, 0.88, 1.728, 1.396, 1.264 ], [ 0.332, 0.076, 0.228, 1.596, -0.64, -0.816, -1.356 ], ... ],
[ [ 1.94, 0.164, -0.592, -0.448, 1.376, 0.568, -0.24 ], [ -1.92, -1.776, -0.024, -1.16, 0.82, -0.436, 0.108 ], [ -1.328, -0.748, -1.404, 0.5, -1.9, -0.236, 1.944 ], [ -0.1, -0.024, 0.424, 1.42, 0.02, -1.488, -0.828 ], [ -0.1, 1.464, 0.988, -0.632, -1.104, 1.604, -0.612 ], [ 0.688, 0.824, 0.924, 0.468, -1.684, 1.928, 1.192 ], [ -1.924, -0.984, -0.116, 1.468, 0.008, -1.932, -0.508 ], [ -0.608, 1.452, -1.612, 1.612, 0.172, 1.24, -0.624 ], ... ],
[ [ 0.788, 1.38, -1.192, -1.236, 0.056, 1.8, -0.436 ], [ -1.928, -0.26, 0.796, -1.484, 1.928, 1.684, -0.016 ], [ 0.492, -1.1, -0.628, 1.796, -0.568, -0.208, -0.08 ], [ 1.032, -0.076, 0.28, 0.0, 0.54, 1.78, -1.3 ], [ -0.376, 1.544, 0.256, -1.3, -0.448, -0.42, 1.316 ], [ -0.576, -0.36, 1.932, 1.108, 0.052, 0.76, -1.48 ], [ -0.6, -1.796, 1.016, 0.768, 0.388, 1.724, 0.756 ], [ 0.448, -0.724, 1.092, 1.688, 0.42, 0.44, 0.056 ], ... ],
[ [ -0.576, -0.824, -0.792, -1.328, 1.516, -1.096, 1.552 ], [ 0.1, -1.252, 0.812, 0.992, 0.26, 1.244, -0.064 ], [ -1.036, 0.812, -0.832, 0.264, 0.168, -0.728, -1.328 ], [ -1.62, -0.684, 0.588, -1.788, 0.296, 0.824, 0.532 ], [ -0.092, -1.472, -0.948, 0.768, 0.884, -1.456, 1.472 ], [ 0.092, -1.968, -1.964, -1.908, 1.38, -0.22, -0.912 ], [ 1.048, 1.116, 0.564, -1.696, -0.308, -0.784, -1.34 ], [ -0.6, -0.968, -0.204, 0.644, -0.016, -0.764, 0.776 ], ... ],
...
]
Which produces the following output:
TrainingTester.java:308 executed in 0.01 seconds (0.000 gc):
return RefStream.of(RefUtil.addRef(output_target)).map(x -> {
String temp_18_0008 = x.prettyPrint();
x.freeRef();
return temp_18_0008;
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
[ [ 0.7221439480781555, -8.054191589355469, 0.8430562615394592, -3.113086700439453, -2.5041284561157227 ], [ -6.965536117553711, 5.150351524353027, 7.291072368621826, 14.09681510925293, 14.730901718139648 ], [ -3.1501595973968506, 13.259231567382812, -9.180830955505371, 5.595775127410889, 7.347168445587158 ], [ 13.206209182739258, 2.2767670154571533, 5.667520523071289, -15.529295921325684, 4.383312225341797 ], [ -1.908287763595581, -2.6692311763763428, -14.921487808227539, 1.2319024801254272, 13.048508644104004 ], [ 4.458671569824219, -8.930048942565918, -0.0961586982011795, -11.78152084350586, -11.932304382324219 ], [ -0.40273618698120117, -11.635472297668457, 5.482944965362549, 1.351199746131897, -2.0953755378723145 ], [ 0.05513601005077362, -7.724399089813232, -6.189455986022949, -1.1783671379089355, 0.5107999444007874 ], ... ],
[ [ -0.5115044713020325, -7.968080520629883, -8.528766632080078, -14.868051528930664, 3.797327995300293 ], [ 6.144879341125488, -18.348066329956055, 3.7399039268493652, 17.914430618286133, 12.656189918518066 ], [ -15.575518608093262, 2.124863862991333, 11.692944526672363, 11.152894973754883, -1.5724619626998901 ], [ -3.9593753814697266, -15.640020370483398, 7.07955265045166, 1.235744833946228, -15.865630149841309 ], [ -5.606927394866943, 3.8518879413604736, 5.907808780670166, -7.8478899002075195, 4.537391185760498 ], [ -7.991775989532471, 2.570896625518799, -9.712641716003418, -7.724000930786133, 7.6933770179748535 ], [ 14.903010368347168, -6.861661434173584, -6.016191482543945, -13.93707275390625, 10.281904220581055 ], [ 4.622399806976318, 13.213621139526367, -6.82811164855957, -2.7724947929382324, 9.707039833068848 ], ... ],
[ [ -12.285344123840332, 4.111231803894043, 7.447552680969238, 2.0491838455200195, -3.8376479148864746 ], [ 8.773233413696289, 4.209216117858887, 11.870128631591797, 7.1118550300598145, 11.475614547729492 ], [ 3.2791526317596436, -2.4228782653808594, -11.435935974121094, 0.05051121115684509, 4.443440914154053 ], [ 10.452255249023438, 14.079041481018066, 12.416621208190918, 12.335103034973145, 9.54814338684082 ], [ 10.733583450317383, -7.910447120666504, -0.18507112562656403, 11.20972728729248, -4.9386396408081055 ], [ -6.236926078796387, 5.126399517059326, -19.374752044677734, 6.149183750152588, 10.167726516723633 ], [ 15.199420928955078, 6.796207427978516, 8.770222663879395, -3.3842074871063232, -13.979744911193848 ], [ -20.651315689086914, -8.440832138061523, 1.619856357574463, -8.089454650878906, -8.227313041687012 ], ... ],
[ [ -10.885248184204102, -2.4925270080566406, -4.602320194244385, 0.12892790138721466, 18.996862411499023 ], [ 1.8604792356491089, 3.88446307182312, 3.714495897293091, 5.902560234069824, 13.149439811706543 ], [ 5.147825717926025, -20.023900985717773, -27.388669967651367, -7.332799434661865, 12.764671325683594 ], [ 12.205584526062012, 5.400063514709473, 2.1729280948638916, 1.4760507345199585, -14.815635681152344 ], [ 10.729249000549316, 4.302223205566406, 12.812910079956055, -25.80457878112793, 7.90676736831665 ], [ -12.252687454223633, 9.35447883605957, 5.293600559234619, -5.797183513641357, 1.4259681701660156 ], [ 1.3435200452804565, -1.373216986656189, -1.6428635120391846, -0.44665709137916565, -25.884239196777344 ], [ 0.529599666595459, -24.900781631469727, 0.034624624997377396, 0.5868151187896729, -2.5267832279205322 ], ... ],
[ [ 1.0081437826156616, -3.554800271987915, 8.57147216796875, -5.596225261688232, 8.588032722473145 ], [ -3.5413267612457275, 10.15343952178955, -5.888640880584717, -9.682771682739258, 5.245120048522949 ], [ 8.116256713867188, -7.191888332366943, -18.574594497680664, 0.336208701133728, 11.409646987915039 ], [ -7.6114068031311035, -4.989887714385986, 14.371395111083984, 6.474544525146484, 5.337935447692871 ], [ 1.4384649991989136, -17.370410919189453, 14.049469947814941, -0.277952641248703, -16.15542221069336 ], [ -6.962399005889893, 3.910736083984375, 4.139936923980713, -10.381792068481445, 14.768847465515137 ], [ -20.676799774169922, 18.084659576416016, -5.91511869430542, 10.832174301147461, 2.5973761081695557 ], [ 8.237486839294434, -1.1650084257125854, -1.4984965324401855, -8.900272369384766, -18.64798355102539 ], ... ],
[ [ 4.023343086242676, -17.613426208496094, -5.417151927947998, -6.0411505699157715, 0.06776025891304016 ], [ 8.95220947265625, 5.601134777069092, -8.941777229309082, 8.290063858032227, 7.851790904998779 ], [ 7.331615447998047, 10.107696533203125, -8.339437484741211, 8.234559059143066, 0.03379647061228752 ], [ 9.319487571716309, -10.412960052490234, 0.15681594610214233, 4.980527400970459, -7.252767562866211 ], [ -3.3762569427490234, 8.182880401611328, 17.688814163208008, 23.129812240600586, 17.77166175842285 ], [ 19.464431762695312, -7.774112224578857, 10.532429695129395, 5.233920097351074, -10.84630298614502 ], [ 2.0680484771728516, -4.041743755340576, -8.52446460723877, -10.122209548950195, 2.549776077270508 ], [ -7.110816478729248, 14.697490692138672, 8.821040153503418, 8.000783920288086, -5.113471508026123 ], ... ],
[ [ -1.0687037706375122, 9.976496696472168, 6.329568862915039, 4.631022930145264, 8.780943870544434 ], [ 17.795915603637695, -21.295759201049805, -9.082928657531738, -11.228032112121582, -9.639360427856445 ], [ 1.669984221458435, 9.541216850280762, 10.009373664855957, -7.095907211303711, -12.602415084838867 ], [ -11.048784255981445, -8.179181098937988, -6.603647708892822, -10.284191131591797, 1.9799511432647705 ], [ 2.1045610904693604, -7.288303852081299, -0.6425121426582336, -1.0218875408172607, 5.1121602058410645 ], [ 16.2784481048584, -9.583280563354492, 7.178608417510986, -16.0406436920166, -3.217104911804199 ], [ 0.9701758623123169, -12.088399887084961, -10.800000190734863, 1.699328064918518, -1.0352016687393188 ], [ -0.816048264503479, 1.5312168598175049, 2.0056488513946533, 5.952830791473389, -11.211106300354004 ], ... ],
[ [ -3.711888074874878, 1.928224802017212, 2.68182373046875, 23.069103240966797, -4.749711990356445 ], [ -8.963968276977539, 17.689599990844727, 13.081425666809082, 15.976831436157227, 10.202528953552246 ], [ 13.699950218200684, 8.787856101989746, -2.6367366313934326, -4.735119819641113, -10.40519905090332 ], [ -21.528099060058594, 7.015548229217529, -9.755646705627441, -8.686816215515137, -4.990753173828125 ], [ 8.073232650756836, 1.5375196933746338, 3.7151193618774414, 6.962447166442871, 8.690385818481445 ], [ 8.078909873962402, 2.6040642261505127, 6.917825698852539, 10.097488403320312, -1.2742866277694702 ], [ -0.5312643647193909, 7.22422456741333, 4.2671027183532715, 5.537120342254639, 7.324426651000977 ], [ -6.532079696655273, -0.944176197052002, 13.712464332580566, -15.375823974609375, 11.084399223327637 ], ... ],
...
]
[
[ [ 4.628672122955322, 4.513360500335693, -10.882736206054688, -3.837792158126831, 3.464784622192383 ], [ -0.41284769773483276, -3.2407851219177246, 20.04017448425293, 2.6128950119018555, -17.418014526367188 ], [ -1.783503770828247, -9.029934883117676, -12.133934020996094, 12.464128494262695, 12.459792137145996 ], [ -10.118671417236328, 3.667631149291992, 1.2979668378829956, -10.616798400878906, -9.55099105834961 ], [ 13.05675220489502, 4.314448356628418, 14.038095474243164, 6.678193092346191, 7.228353023529053 ], [ 8.155263900756836, -0.15798456966876984, -2.2491533756256104, -10.206337928771973, 0.7808641791343689 ], [ 5.358063697814941, -11.942975044250488, 10.680655479431152, 1.9583839178085327, -11.732256889343262 ], [ -1.8765746355056763, 3.4140799045562744, -6.887392044067383, -7.258704662322998, 3.797344446182251 ], ... ],
[ [ -24.44295883178711, 2.447519063949585, 5.3766560554504395, 8.335041046142578, -13.478113174438477 ], [ 13.281185150146484, 16.5595703125, -3.747455596923828, 6.338944911956787, 8.985568046569824 ], [ -4.532095909118652, 19.54690170288086, -0.3922715187072754, -4.6944146156311035, -7.27070426940918 ], [ 7.357743740081787, -14.978157997131348, -6.256142616271973, -0.9463684558868408, -5.983424663543701 ], [ 4.896239757537842, -6.243453502655029, 14.331855773925781, 4.719088554382324, 4.823745250701904 ], [ 0.7276796102523804, -14.449630737304688, 5.918717861175537, 15.691072463989258, 2.8976635932922363 ], [ 7.695392608642578, 5.198575973510742, 1.4028640985488892, 8.339680671691895, 1.0079044103622437 ], [ 0.7995685935020447, -14.858719825744629, -4.093489170074463, -1.7860164642333984, -10.34972858428955 ], ... ],
[ [ -4.835088729858398, 4.398048400878906, -2.335584878921509, -3.0260162353515625, -7.990910053253174 ], [ -9.316463470458984, -4.889888286590576, 2.7341442108154297, -7.233439922332764, 7.475615978240967 ], [ -1.916224718093872, -13.743311882019043, -14.654848098754883, -5.442528247833252, -9.989103317260742 ], [ 2.9074718952178955, 8.153743743896484, -0.12299304455518723, 16.448143005371094, 9.457523345947266 ], [ 13.841326713562012, 4.576303005218506, 8.871149063110352, 10.779999732971191, -0.3837417960166931 ], [ 1.8638874292373657, -16.235614776611328, -1.490062952041626, 5.903825759887695, 1.6355687379837036 ], [ -9.643903732299805, 4.7938408851623535, -1.0143520832061768, -2.1238582134246826, -12.587346076965332 ], [ -0.9826717376708984, 7.40451192855835, -0.6940003037452698, 2.187551975250244, -9.73846435546875 ], ... ],
[ [ -10.241263389587402, -11.178207397460938, -3.596590995788574, -3.0657601356506348, 3.5104479789733887 ], [ 6.051087379455566, -11.738999366760254, -5.616608142852783, -12.789440155029297, 0.4627671539783478 ], [ 12.600878715515137, -7.457294940948486, 6.192384719848633, 5.208255290985107, -0.8285759687423706 ], [ -7.498319625854492, 6.295808792114258, 10.167008399963379, 6.002143383026123, 6.396417617797852 ], [ -4.766256332397461, 2.551327705383301, -16.903057098388672, 7.0513434410095215, 3.955167531967163 ], [ 11.374144554138184, -7.879201412200928, -10.382317543029785, -6.168032646179199, 8.320895195007324 ], [ 2.503680467605591, -1.1609927415847778, -13.540704727172852, 3.2564799785614014, 10.837630271911621 ], [ 2.5817925930023193, 6.128703594207764, 3.86476731300354, 10.822589874267578, 6.5043044090271 ], ... ],
[ [ 5.352128505706787, 11.188142776489258, 3.0219359397888184, -1.8509920835494995, -11.845855712890625 ], [ -3.928926706314087, 18.26837730407715, 3.8063528537750244, 0.9606563448905945, -3.3237593173980713 ], [ 3.176448345184326, 10.899519920349121, -3.949648857116699, 1.0876799821853638, -13.03345775604248 ], [ 0.8985589146614075, -7.8100810050964355, -7.6913275718688965, -10.306257247924805, 12.819660186767578 ], [ -14.314208030700684, -22.359920501708984, -10.745711326599121, -9.91889762878418, 6.945760250091553 ], [ 8.461983680725098, -6.846960067749023, 7.386272430419922, -4.294192314147949, -14.59801959991455 ], [ -1.0715841054916382, 17.829343795776367, 3.013248920440674, 2.244558095932007, 17.423458099365234 ], [ -5.4935832023620605, 0.10300793498754501, 8.984831809997559, 3.6876156330108643, -18.118610382080078 ], ... ],
[ [ 16.314224243164062, -4.905215263366699, 8.149200439453125, 8.904080390930176, -5.463232517242432 ], [ 4.0740966796875, -0.3548479974269867, 5.357471466064453, 8.118449211120605, 4.0808329582214355 ], [ -26.688636779785156, 2.6624810695648193, -25.25505256652832, -10.45588493347168, 3.850400447845459 ], [ 4.727135181427002, -8.837808609008789, 9.038064956665039, -2.1104018688201904, -21.33258819580078 ], [ -2.3090550899505615, 12.752559661865234, 5.027535915374756, 1.330031156539917, 0.43267229199409485 ], [ 13.33430290222168, -4.7036967277526855, 0.8684160709381104, 7.795120716094971, 12.46863842010498 ], [ -4.299023628234863, -10.061487197875977, 5.459936618804932, -11.619938850402832, -12.62321662902832 ], [ -7.655600547790527, -10.63748550415039, -8.31257438659668, 2.3641912937164307, 12.381359100341797 ], ... ],
[ [ -1.5586873292922974, 11.989263534545898, 7.223295211791992, 1.9922550916671753, 3.6605913639068604 ], [ 26.428993225097656, -11.793357849121094, -4.706033229827881, 14.398877143859863, -10.809809684753418 ], [ -16.169662475585938, -8.47755241394043, -7.1128973960876465, -6.93654727935791, -13.159037590026855 ], [ -1.339311957359314, 19.861074447631836, 18.433223724365234, 0.5242069959640503, -7.021249294281006 ], [ -1.8486071825027466, 19.348655700683594, -10.566847801208496, -1.0487339496612549, -7.67006254196167 ], [ -5.070319175720215, -12.145889282226562, 1.2016950845718384, -12.799901962280273, -16.72563362121582 ], [ -0.0378556065261364, 5.778512477874756, -5.0762248039245605, 7.875761032104492, 3.8630895614624023 ], [ -19.211408615112305, 21.997867584228516, -10.240894317626953, 2.6060802936553955, 2.4988811016082764 ], ... ],
[ [ -2.534626007080078, 10.400193214416504, -2.60479998588562, -1.9353598356246948, 6.3920464515686035 ], [ 4.03036642074585, -13.51607894897461, -16.414175033569336, 7.491456031799316, 15.55515193939209 ], [ 3.345442056655884, -14.485230445861816, -6.905358791351318, 4.001919746398926, -3.6367833614349365 ], [ 0.005072987172752619, -0.39956891536712646, 0.864719569683075, 15.800254821777344, 16.072063446044922 ], [ 0.2624482810497284, 3.5013749599456787, -10.511073112487793, -23.004819869995117, -2.6459827423095703 ], [ 0.4576142430305481, 3.301344871520996, -4.061761379241943, -7.01039981842041, 0.8658879995346069 ], [ 5.525360584259033, -6.424911022186279, -3.5343685150146484, -1.80022394657135, 16.813953399658203 ], [ 3.141265392303467, -12.480125427246094, 3.59543776512146, 2.633885622024536, -4.087022304534912 ], ... ],
...
]
First, we train using basic gradient descent method apply weak line search conditions.
TrainingTester.java:480 executed in 31.59 seconds (0.418 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new ArmijoWolfeSearch());
iterativeTrainer.setOrientation(new GradientDescent());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 13317095276969
Reset training subject: 13317525210570
Constructing line search parameters: GD
th(0)=215.321431391781;dx=-112.96711403810629
New Minimum: 215.321431391781 > 111.3921075347788
WOLF (strong): th(2.154434690031884)=111.3921075347788; dx=16.466686148152974 evalInputDelta=103.9293238570022
END: th(1.077217345015942)=128.49968384028006; dx=-48.234470039904615 evalInputDelta=86.82174755150095
Fitness changed from 215.321431391781 to 111.3921075347788
Iteration 1 complete. Error: 111.3921075347788 Total: 3.5879; Orientation: 0.1722; Line Search: 2.1543
th(0)=111.3921075347788;dx=-2.4138260798724063
New Minimum: 111.3921075347788 > 109.25110122015128
WOLF (strong): th(2.3207944168063896)=109.25110122015128; dx=0.5687515122474541 evalInputDelta=2.141006314627518
END: th(1.1603972084031948)=109.45636073691924; dx=-0.9225288742747115 evalInputDelta=1.935746797859565
Fitness changed from 111.3921075347788 to 109.25110122015128
Iteration 2 complete. Error: 109.25110122015128 Total: 2.2869; Orientation: 0.1815; Line Search: 1.6588
th(0)=109.25110122015128;dx=-0.13433627597638706
New Minimum: 109.25110122015128 > 109.1389699934802
WOLF (strong): th(2.5000000000000004)=109.1389699934802; dx=0.04463125856811253 evalInputDelta=0.11213122667108166
END: th(1.2500000000000002)=109.13910825088999; dx=-0.04485248155651918 evalInputDelta=0.1119929692612942
Fitness changed from 109.25110122015128 to 109.1389699934802
Iteration 3 complete. Error: 109.1389699934802 Total: 2.2546; Orientation: 0.1774; Line Search: 1.6605
th(0)=109.1389699934802;dx=-0.014850618829680064
New Minimum: 109.1389699934802 > 109.12769182695291
WOLF (strong): th(2.6930433625398553)=109.12769182695291; dx=0.0064748394325651335 evalInputDelta=0.011278166527290523
New Minimum: 109.12769182695291 > 109.12615211204313
END: th(1.3465216812699277)=109.12615211204313; dx=-0.004187889442889583 evalInputDelta=0.012817881437072742
Fitness changed from 109.1389699934802 to 109.12615211204313
Iteration 4 complete. Error: 109.12615211204313 Total: 2.4062; Orientation: 0.1778; Line Search: 1.8056
th(0)=109.12615211204313;dx=-0.0011822113933295886
New Minimum: 109.12615211204313 > 109.12537166093345
WOLF (strong): th(2.9009930210079875)=109.12537166093345; dx=6.441534647511063E-4 evalInputDelta=7.804511096765054E-4
New Minimum: 109.12537166093345 > 109.12509960274252
END: th(1.4504965105039938)=109.12509960274252; dx=-2.69028696190001E-4 evalInputDelta=0.00105250930060663
Fitness changed from 109.12615211204313 to 109.12509960274252
Iteration 5 complete. Error: 109.12509960274252 Total: 2.2818; Orientation: 0.1752; Line Search: 1.6784
th(0)=109.12509960274252;dx=-6.194789635624373E-5
New Minimum: 109.12509960274252 > 109.12506425161226
WOLF (strong): th(3.125000000000001)=109.12506425161226; dx=3.9323235825006654E-5 evalInputDelta=3.5351130264871244E-5
New Minimum: 109.12506425161226 > 109.12504236808354
END: th(1.5625000000000004)=109.12504236808354; dx=-1.1312348837056876E-5 evalInputDelta=5.72346589819972E-5
Fitness changed from 109.12509960274252 to 109.12504236808354
Iteration 6 complete. Error: 109.12504236808354 Total: 2.3770; Orientation: 0.1736; Line Search: 1.7847
th(0)=109.12504236808354;dx=-2.828555995608106E-6
New Minimum: 109.12504236808354 > 109.12503801160474
WOLF (strong): th(3.3663042031748196)=109.12503801160474; dx=2.401477173778449E-7 evalInputDelta=4.356478797262753E-6
END: th(1.6831521015874098)=109.12503889832591; dx=-1.2941968605880286E-6 evalInputDelta=3.469757629659398E-6
Fitness changed from 109.12504236808354 to 109.12503801160474
Iteration 7 complete. Error: 109.12503801160474 Total: 2.2498; Orientation: 0.1724; Line Search: 1.6547
th(0)=109.12503801160474;dx=-2.190511012833971E-6
New Minimum: 109.12503801160474 > 109.12503382838582
END: th(3.626241276259985)=109.12503382838582; dx=-1.1659441029063111E-7 evalInputDelta=4.183218919706633E-6
Fitness changed from 109.12503801160474 to 109.12503382838582
Iteration 8 complete. Error: 109.12503382838582 Total: 1.7522; Orientation: 0.1735; Line Search: 1.1486
th(0)=109.12503382838582;dx=-2.0480814543050625E-6
New Minimum: 109.12503382838582 > 109.12503296280352
WOLF (strong): th(7.8125000000000036)=109.12503296280352; dx=1.826465849852996E-6 evalInputDelta=8.655823080516711E-7
New Minimum: 109.12503296280352 > 109.125029611851
END: th(3.9062500000000018)=109.125029611851; dx=-1.1081181632847741E-7 evalInputDelta=4.216534819079243E-6
Fitness changed from 109.12503382838582 to 109.125029611851
Iteration 9 complete. Error: 109.125029611851 Total: 2.2676; Orientation: 0.1701; Line Search: 1.6797
th(0)=109.125029611851;dx=-2.205479835604004E-6
Armijo: th(8.41576050793705)=109.12503157740923; dx=2.672608442267291E-6 evalInputDelta=-1.9655582264022087E-6
New Minimum: 109.125029611851 > 109.12502546316183
WOLF (strong): th(4.207880253968525)=109.12502546316183; dx=2.335620859871794E-7 evalInputDelta=4.148689171756814E-6
END: th(1.4026267513228416)=109.12502708863141; dx=-1.3924666042485027E-6 evalInputDelta=2.5232195923763356E-6
Fitness changed from 109.125029611851 to 109.12502546316183
Iteration 10 complete. Error: 109.12502546316183 Total: 2.7920; Orientation: 0.1723; Line Search: 2.1951
th(0)=109.12502546316183;dx=-2.7973175581667772E-6
New Minimum: 109.12502546316183 > 109.12502109570207
END: th(3.0218677302166546)=109.12502109570207; dx=-9.303698615373554E-8 evalInputDelta=4.3674597662857195E-6
Fitness changed from 109.12502546316183 to 109.12502109570207
Iteration 11 complete. Error: 109.12502109570207 Total: 1.9099; Orientation: 0.1887; Line Search: 1.2843
th(0)=109.12502109570207;dx=-1.7452591584089868E-6
New Minimum: 109.12502109570207 > 109.12501681229858
WOLF (strong): th(6.5104166666666705)=109.12501681229858; dx=4.294277959551923E-7 evalInputDelta=4.283403484350856E-6
END: th(3.2552083333333353)=109.12501718433658; dx=-6.579152659514117E-7 evalInputDelta=3.911365482167639E-6
Fitness changed from 109.12502109570207 to 109.12501681229858
Iteration 12 complete. Error: 109.12501681229858 Total: 2.5953; Orientation: 0.1768; Line Search: 1.9503
th(0)=109.12501681229858;dx=-4.948146532897869E-6
Armijo: th(7.013133756614209)=109.12503232453008; dx=9.371821556919199E-6 evalInputDelta=-1.551223149931502E-5
New Minimum: 109.12501681229858 > 109.12501201477494
WOLF (strong): th(3.5065668783071047)=109.12501201477494; dx=2.2118377222322225E-6 evalInputDelta=4.797523644128887E-6
END: th(1.1688556261023682)=109.1250124235697; dx=-2.561486668413597E-6 evalInputDelta=4.388728882531723E-6
Fitness changed from 109.12501681229858 to 109.12501201477494
Iteration 13 complete. Error: 109.12501201477494 Total: 2.8310; Orientation: 0.1793; Line Search: 2.2189
Final threshold in iteration 13: 109.12501201477494 (> 0.0) after 31.592s (< 30.000s)
Returns
109.12501201477494
This training apply resulted in the following configuration:
TrainingTester.java:610 executed in 0.00 seconds (0.000 gc):
RefList<double[]> state = network.state();
assert state != null;
String description = state.stream().map(RefArrays::toString).reduce((a, b) -> a + "\n" + b)
.orElse("");
state.freeRef();
return description;
Returns
[0.0016639829860043975, 0.0017305885143357575, 0.002756534163700616, 0.009297448855320802, 0.002439688351543325, -0.01330478399225675, -0.00526319556019002, -4.97977659017307E-4, 0.003244167812776393, -0.00747937661580112, 0.004662592322992154, -0.0053367735583577675, -0.006347410103388712, 0.00985147883304842, -0.014889201182046518, 0.005451524901155676, 0.0070181039913363805, 0.00751309622197929, -0.0034786863671685065, 0.005983295026954185, -0.001755100019575225, 4.66847466226768E-4, 0.007043628949853599, 0.011862246784934999, 0.01440430937073095, 0.008373800313773012, -0.007995532405688486, 0.0032060429039279343, -0.0028686628702807803, 0.0043597597332318775, -0.008934397490864809, 2.5347042132315464E-4, -0.004056656026897144, 0.008624483684582962, 0.0026378142307434665, 0.0051915090433634166, -0.0020633363753497576, 0.01997504114292683, 1.0290052821057799E-4, -4.953980208248212E-4, -0.009438032742161418, -0.01151958572602457, -0.012888136392772712, 0.0020796463052896604, 0.01049996098817745, -6.012058334861323E-4, -0.0018422215527655102, 0.0029686385908753886, -0.006034085343832199, 8.04594107846281E-4, 0.024214250220242643, 0.0032548463486741313, 0.0035473149785420688, 0.006748278841714447, 0.01381039700669828, -5.086116602651367E-4, 0.010293410157892901, 0.0089332031839989, 0.015659178889738137, 0.009020267610714646, 0.0017286777091993816, -0.010288596547169722, 0.013365589144807684, 0.005494961247909572, 0.006158394660927885, 0.0065651755244857096, -0.01333217883338752, 0.0037733967121317256, 0.009155084060678241, -0.0021005278047633463, 0.0016898916175356327, -0.012994412880442922, -0.0011006413955555066, -2.5429614706232325E-4, 0.0015077511320523635, 0.022880360806790154, 0.004318142922191696, -0.005539364612028971, -0.01074547891691633, -0.013416488255626548, 5.525940543642E-4, 0.020813112841466246, -0.0075135787399443115, 0.012016146529217264, -0.00547691414386085, -0.002540743242489091, 0.0011924615566425913, 0.002570847020414209, 0.004014983016377485, 0.016149281071977876, 0.014377790184877082, -0.008682626504243597, -0.006821055083620224, -0.008704608723964781, 0.017274719471204646, -0.006316007007621509, -0.019444562373647757, 0.0029498705811633365, -0.0012407725641548812, 0.00815348884517996, -0.01773736777973458, 0.004245418191590985, -3.436535374070947E-4, 0.011841468074368177, -8.835970823907753E-4, 0.002616297287586013, -0.004643709418902418, -0.0046121633328680325, 8.012781047495208E-4, 0.00631117664399026, 0.007993489520628564, 0.001674167671769726, 0.010076150680485344, 0.010877049605476283, -0.010152128846673467, -0.0014534913645954167, -0.011720670888929145, -0.009594489917056352, 0.004248714016272608, 0.007952738259779109, -0.020048585699153316, 0.005994981832891878, -0.013380509243207458, 0.008561554454116353, -0.029919293637615505, -0.012642627839482322, 0.004326509298492535, -0.007671082947150474, 0.0043146486434014674, 0.0011205199085919779, -0.013855456217049958, -0.013656868309250935, -0.0031478825974401276, -0.00963203290238138, 0.006827564239721539, -0.009651612899934865, -0.011669135009422862, 0.01438577515529911, 0.005009584684876044, 0.0049129409658827455, -0.011303347441136138, 0.01320437816363102, -0.003518547089274492, 0.028923957943946817, 0.011256716413294721, -0.016021688008271827, 0.008710182104546717, -0.018145469924809112, 0.005058239475100487, 0.009003982793852285, 0.011333934182493835, 0.0011462714528142784, -0.0036790396528880694, 0.005664468264674788, 0.014696007756833118, 0.011571745901706886, 0.012884717174779396, -0.0065747050356957625, -0.01621631823704381, -0.011222058802281767, -0.0141438471826215, 0.0143024789063831, 0.004481020825414073, -0.006026731312921755, 4.1273463015936273E-4, -0.011345251668865988, -0.0011925836545134418, -0.007265589964621277, -0.009606541379799213, -0.006658604733049278, -5.418528766264346E-5, -0.003571302362332811, -0.0012784727740439072, -0.0028578853830608514, 0.011096166670169523, 0.008183118892951752, -0.001647584562323222, 4.4113259349782923E-4, -0.009592080871849446, -0.026326649943080822, 0.009943970808718087, 0.0017757182231675803, 2.9690255988057277E-4, 0.00887457798754823, 0.00878573334076482, -0.011742806897730084, -0.015259722297591363, -0.028350621746442678, -0.012333437914553913, 0.010551115988031604, -0.006872193773587171, -0.004352846052772955, 0.009111839865560594, 0.0034051006394606245, -0.015440165511561769, -0.0010693573646834023, -0.006451383690607439, 0.015356287891399187, -0.003704633163776261, -0.002906621762730559, 0.0202349961179171, 1.9047709117138198E-4, 7.541627866809371E-4, -0.008051842874223327, 0.02920002535335725, -0.005156740577934445, 0.0034699560778392985, 0.008054744036668159, -0.008811805162959336, 0.012564420919596392, -0.012992478760882524, 0.0046026236458806494, -0.009384029739552944, 0.00177589555554881, -0.007073006088900965, -4.7582322975829995E-4, 0.013913949664969156, 7.2269707991385E-5, -0.006609632866536338, 0.006488898279008008, 1.6704324368938445E-4, 0.005927245562157318, 0.015552485795963357, 0.010386606320804669, -0.01360895996216011, -0.007568122890570425, -0.011749486469196763, -0.022049044602127248, 0.0020804510522499505, 0.01748222524870006, -0.01307216132003184, 0.01193315077086342, -0.019485686309130622, -0.00417785042089466, -2.6563640172778795E-4, -0.007093918637102139, -0.02030635443089989, 0.008075575090991962, -0.005924034785254688, -0.00406190863295691, 0.0015024188416761348, -0.009287586133945714, -0.012370298837539123, 0.024653592634618936, 0.010039679646613108, -0.0028903619630814585, 0.014374179262065117, -0.004702530720737277, -0.0037241530333909935, 0.004224225902709512, -0.006015911563272978, 0.01045313422482899, -0.0012593907931356695, 0.01042309775383293, -0.004367402207122105, 0.002091627392512855, -0.0087429089121041, 0.013060692839994208, 0.0027616686275156797, 0.0022136894553708418, -0.016660120031711124, -0.015528613740951117, 0.008840678817734347, -0.0015341329257782842, -0.001116240671077549, -0.0018295735302073, 0.0036485700421816283, 0.009894569361860733, 0.016220894367209603, -0.019886088405868165, -0.010187548325463567, -0.015109289716903767, -0.01282503558875044, 0.002897289968643606, -0.004667191239675503, -0.017800625386671928, -0.016097579399211838, 0.0015013391333539461, 0.0026401783370078764, 0.006796112732982655, -0.005458399818987858, 0.01807695191504836, -4.673823636490638E-4, -4.494357290800565E-4, 0.01841967408306575, 0.005426249543898376, 0.003040142167969427, -0.004620263191862584, -0.003585569880710041, 0.0026816692383359827, -0.004057182526438598, 9.98104104423724E-4, 0.012345286646701504, -0.013324232698579484, 0.011325966326943264, 0.015006206799502191, -0.005371143358824611, -0.01717265241405795, -0.007483427686010803, 0.002204113511723074, -0.010927220892917023, -0.01633245031862226, 0.009086543641200498, 0.011607994128340501, -0.005802870656315361, -0.02133564017489925, -0.016761177311469623, 0.005152337326718508, -0.028684954794885337, -0.008328948173131828, -0.018529547606977538, 0.009801431546139635, 7.224836526777313E-4, 0.015886757265534537, -0.01577847695929806, -1.396, 0.996, -1.176, 0.66, 0.656, 1.88, 1.98, 1.244, 0.016, 0.66, -0.032, -0.924, -0.892, 1.22, 1.144, -0.384, 1.664, -1.476, 1.96, 1.352, -0.968, -0.968, 0.344, 1.048, -1.616, 1.656, 0.312, 0.788, -1.5, 1.536, 1.052, 0.132, 1.288, 0.356, -0.032, 1.44, -1.552, 0.56, 1.168, 1.324, 1.652, 0.972, 0.752, -0.028, -0.892, -1.44, -0.344, -1.104, 1.88, -0.02, 0.52, 1.912, -1.54, -1.808, -0.152, -0.636, -1.92, 0.8, 0.324, 0.012, -0.488, 1.524, -1.976, -1.228, 0.56, -1.256, 0.3, 0.7, 1.62, -1.176, 1.356, 1.836, 1.668, -0.636, -1.688, 0.636, 1.288, 0.0, 0.0, 1.26, -0.452, -1.42, 1.66, 1.144, -1.552, -0.212, -0.472, 1.948, 0.868, 1.628, -1.804, 1.704, -0.296, 0.0, 0.0, -1.408, -0.816, -0.628, 0.028, -1.052, 0.932, -0.26, 0.08, 0.98, -1.832, 0.184, -1.524, -1.432, 1.36, -1.656, -0.888, -0.124, 0.812, 1.764, -1.256, 1.144, 1.836, 1.368, 0.784, -0.892, 0.8, -1.044, 0.0, 1.196, -0.032, -1.248]
TrainingTester.java:622 executed in 0.00 seconds (0.000 gc):
return RefArrays.stream(RefUtil.addRef(data)).flatMap(x -> {
return RefArrays.stream(x);
}).limit(1).map(x -> {
String temp_18_0015 = x.prettyPrint();
x.freeRef();
return temp_18_0015;
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
[ [ -1.1280212557288978, -1.3759334975954767, 0.1599460293765919, -0.4638945936728415, 1.3559593060201642, 0.6518969963453227, -1.0279443997012614 ], [ -1.6238874312633527, 1.7118958520351713, 1.4919273159199455, 0.7959363596582777, 1.739938951091981, 1.363935399950491, 1.719798220337318 ], [ 1.8598144085671033, 0.8480224834711966, -0.9759334506347547, -0.3840393942815321, 0.9277779300888107, 0.46005094320241524, -1.5041037582138246 ], [ -0.6798013983308049, 1.0840338344577902, -0.49195378753280716, -1.8958617708851422, -0.36011931026141314, 1.5197149278906497, -1.3318393661072618 ], [ -1.3479428808464133, -0.30001284942754153, 0.6639278976560036, -1.1559702178602536, -0.5879615363627748, -0.1959828990957495, -0.8240396704114378 ], [ 1.340030448481441, 0.3561100443965949, -0.9720471490969708, 0.8439843077304686, -1.2839734968672538, 1.7279992633375096, 0.8319883318149356 ], [ 1.6359897612975887, 0.5880299653784516, -0.015965929687178047, 1.1838059713536173, -1.9757862018151195, -1.411882826030268, -1.34786799521083 ], [ 1.123978770526795, 0.07189771856218914, 1.6798858689639762, -1.879941395683562, 1.583920863966888, 0.6360147368940638, -1.4359459178814546 ], ... ],
[ [ 1.323953434144926, 0.7440322497378348, -1.4438707833107587, -1.7440747598061113, -0.2639489360355564, -1.8880245770756716, -0.34790430683240553 ], [ -0.8881645502866581, 1.2040845765084518, -0.9199596497520909, 1.011947363535565, -1.8958444218627806, -0.8839578753108227, 1.1919775070004122 ], [ -1.0639001368158227, -0.3161662671608165, -0.7677530531450902, -0.8798269567384938, 0.09177959698011695, -1.791812792843246, -1.512044168374199 ], [ 1.9798399807120577, -1.7997531803292253, -0.5879958784940755, -1.1880194943180795, -0.4598913461964431, -1.1400014632692201, -0.03586057199445156 ], [ 1.7038708108647362, -1.5480638207552917, -1.5558862034638326, -1.631901300478592, 1.0559628338881946, -1.8319839859411646, 1.4878868720137974 ], [ -0.6681204160171502, -0.46007530322198575, 0.7239844211117484, 0.45190347611538995, -1.1920860933803084, 1.563925825940557, 1.0597690302650367 ], [ 0.8919195294751432, 1.7041280614068637, -0.4720091977064262, -0.5040483432686705, 0.41191391503880204, 0.8759675878947972, 0.49986282708529456 ], [ 0.5001074165397106, 1.5518755777105893, -1.159844310196704, -1.467872619987481, 1.4557505249921836, -0.3399609476623777, -1.2198665052041189 ], ... ],
[ [ 1.9280267705909975, 1.4519371972678776, -0.5719152449878385, 0.2760099526805505, -1.1760303158936134, -1.4479546298146777, 1.671839615496428 ], [ 1.927763032491753, 0.456056760103559, 1.363952675643211, -0.4201319774167367, 0.16791215100871532, -1.175890148242045, 1.1800856561851145 ], [ -0.887978618048761, 1.8280037308667816, -1.2559094627161178, -1.291837191853003, -1.3520395195971027, -0.9399600207695181, 0.3757795920349849 ], [ 0.5677015236215688, 0.6881482727261491, -0.9237939677623508, -0.480128035341285, 0.23614894484241344, -1.6796270483220475, -1.2518479953756734 ], [ -0.9639725017674173, 1.8079297328260338, -0.8121784493636511, -0.6758900644906527, -0.8477244960700745, -1.1720448449149368, 0.23625696136179786 ], [ -1.9278097673676071, 1.5837827158535072, 0.9119283197724914, 1.5079482587553221, 0.37203221887109816, -1.5757340660853, 1.2196856620207324 ], [ 0.4958686286977652, -1.215896881175175, -0.35201457650822976, -0.06408775593722756, -0.855973844660843, -1.627820618399269, -1.7876226730870395 ], [ 0.28022452829383626, 0.10005466000328665, 0.4119509021680697, 1.4880999341315573, 0.33584472310283764, 0.9756127453060719, -0.15590388123818408 ], ... ],
[ [ -1.215987378970477, -1.7718361463223045, 0.12001659041213449, 0.5920601051627322, -1.8560441473075264, -0.8240121540649058, 1.2278088897361974 ], [ 1.5078831220431, -1.8359580490408116, -0.29191914279357556, 0.9920256445045208, 1.947995695372744, -0.8799379533326447, -1.5118087776036342 ], [ -0.619902024229733, -0.7679953711793994, -1.8159434651813957, -0.8479248018080674, -1.8597835077880127, -1.0080988625475837, 1.411906839185548 ], [ -1.3319498433148247, -0.7158743035288737, 1.1679199320734586, 1.367992266031586, 0.11615787735791505, 1.6201643282617477, 1.5197305214470487 ], [ -0.34417454998320546, 0.45619821540430966, 1.263831002323446, 0.919920114174249, 0.015991277654124305, -0.6439519714959446, -0.9360717353627932 ], [ -0.38799024313398134, 0.18782776996714026, 1.7398935475879087, 0.524053530503255, -1.280001703994861, 1.2118572916292825, 1.4758186770491681 ], [ -0.3038438734166592, -1.2440429366230812, -1.5159649064113918, -0.4080017791182976, -1.0559108468983158, -0.8639448979376412, -1.9159350086313485 ], [ 0.29993802300931965, -1.7476436628704888, 1.6958166372455128, -1.3920465631909407, -1.8556957776384586, 1.4599627109519113, 1.4360187472393398 ], ... ],
[ [ -1.207978589934252, 0.5919986934036617, 1.5199243077603006, 0.6721298760861845, 0.9518795233607341, 1.8877246402155603, -0.47193622254668416 ], [ -0.8757993146339156, 0.25195974598442616, -0.03976546918210486, 0.42811371343760474, -1.648078199032433, 1.1757235662561538, -0.36021236036304943 ], [ 1.6719228699680468, 0.17199090351637067, -1.6797150733494033, 1.0239514290382525, -0.42401340209776495, -1.3877290300139296, -1.3681478767593087 ], [ 1.0276866855563667, -1.0118795857580425, 0.5161779251028008, 0.9758382260563168, 0.17216099781873118, -1.187799969173209, 0.1039528604603626 ], [ 1.3796821347719188, 0.6957715154060706, -1.6358580268316703, 1.8397936131524701, -0.16397223446216522, -0.5198450446991257, 0.20019839532793868 ], [ 0.8079995633795891, 0.7558550406434308, 0.5120895403570108, 0.97211369910206, -0.7600282370239583, 0.7917346322936905, -1.2837283274647313 ], [ -0.33168162455550887, -0.4761672732767072, -0.03995749036879069, -0.29584587042139765, -0.4160404554198904, 0.40390728760409517, -1.8600989898920741 ], [ 0.14392313791325653, 1.0079247021695783, -0.9959595775113025, 1.2597971442068012, 0.5840809469706432, -1.5236727375966346, 1.0078663804973478 ], ... ],
[ [ 0.4400096463941087, -0.048008036008114624, 1.4079805224069724, -1.3759584849924056, 1.9639399262691173, -1.5600521842152255, -0.13996078614284588 ], [ 0.08399365998310736, -0.15179149225787655, 1.3120204384204284, -0.9838651393240221, -1.2240809555995362, -0.6320562500337507, -0.37602205910842906 ], [ 1.859862618148688, -1.9159573591870367, -1.387856891005048, 1.0440692627226864, -0.304040393072742, 0.712052654102916, 1.1519612997118114 ], [ -1.6319635056517627, -1.100003011715854, -1.0599955292862882, 1.472019467151376, -0.515931643025379, 0.015873512144018553, 0.6519427427195411 ], [ -1.7677700913711734, -1.3758898773781016, -1.7398761698701137, 1.61990550945624, 1.8318737019402191, 1.4920015201323438, -0.7719572755161583 ], [ -0.5001375617668796, -0.7118895323852434, -1.2280043824104832, 1.7237861980731022, -0.7959625028897367, -1.0436782099207336, -1.5356249629198682 ], [ 1.7597230693343064, 0.3718580036222117, -0.19212681574844248, 0.43599380453197706, -1.7237698230518854, -1.815899048685908, -1.02792107697241 ], [ -0.4039233957565665, 1.891685902914868, 0.8238896108583557, 1.0199149707550126, 0.7718632755317484, -0.6279165737958455, -0.1280353376787027 ], ... ],
[ [ -0.023873062194281383, -1.8640053118566935, 0.7641347009137107, -1.9399550784101844, 0.6358200829732381, 0.4918755185248636, 1.4079092925697467 ], [ 1.7278318236598895, -1.9677801952801883, 0.7239159749300245, 0.020069543767181838, 0.5159684322490022, 1.0878601743757237, -0.4478749974020246 ], [ -1.7356648088664124, -1.9159592009270345, -1.7237151316391341, -1.0118311582414126, -1.2277667488261965, 0.9637453602806304, 1.1720040396139342 ], [ -1.3158646481428256, 1.6518305374978592, 0.5160976731961625, -1.0520294910194985, -1.5279253141668512, -1.883866673897547, 0.4518425468544946 ], [ -1.1799066101259732, -1.4877493699230049, -1.8238230831084574, 1.5758384484424752, -0.07209931811602147, -1.6199893923608093, 0.9758351930313149 ], [ 0.5159611280882006, -1.095854755401112, -0.7119078982006933, 0.38004866377986896, 0.7038399027215169, -0.1238181783535081, -0.9040755111900006 ], [ 0.1280038261076607, 0.46801678786415846, -0.2799948268407404, -0.7919329170506881, -0.9838154056890843, -0.11995402863880773, 0.328106423977472 ], [ 0.36410408938245864, -1.3438971346514637, 1.1717796963979437, 0.3240346095014415, 0.9721796891400176, 0.9518492900561197, -0.39590230433481194 ], ... ],
[ [ -1.2558994290376435, -1.2759256218637816, 1.2918913872263156, -1.7398102165461735, -0.7118602023101783, -0.5840674785463009, 0.3599529690588026 ], [ -0.4159335432748775, -1.3319820688379937, 1.2760333002178663, -0.04007167125748347, 1.6518446662938122, -0.6999164511974886, -1.2160449214326565 ], [ 0.8758794243033977, -0.13585516145919263, -0.9279705401862819, 1.023808756740282, 0.35606946451713894, 0.09582222018929508, 1.4120383617344774 ], [ 1.103901549853846, -0.5479937552698058, -0.963974113282446, -1.3238404794256027, 0.3918899357630886, -1.9038185915095995, 0.44790835923908495 ], [ 1.30774263260983, 1.276013831752477, 0.8520771626763584, 1.3399976320458162, -0.7360170905093363, -1.3197544662866418, -0.6599745913160812 ], [ 0.6760416662052697, 0.5999387601197491, -0.46405429578879237, 0.032226883370508365, -1.5317650745430325, 1.9478815996342378, -1.39186649291132 ], [ -1.6357100840780578, 1.6160268600175984, 1.1999828257127572, -0.09603504209663424, -1.959818980358604, -0.4760738706903599, -0.42810838424321535 ], [ 1.7879138920829631, -1.1478310115128754, -1.3200347770208027, 0.3557413459853224, 0.22814096480734466, 0.1761297626999016, -0.1640738445798129 ], ... ],
...
]
To produce the following output:
TrainingTester.java:633 executed in 0.15 seconds (0.000 gc):
Result[] array = ConstantResult.batchResultArray(pop(RefUtil.addRef(data)));
@Nullable
Result eval = layer.eval(array);
assert eval != null;
TensorList tensorList = Result.getData(eval);
String temp_18_0016 = tensorList.stream().limit(1).map(x -> {
String temp_18_0017 = x.prettyPrint();
x.freeRef();
return temp_18_0017;
}).reduce((a, b) -> a + "\n" + b).orElse("");
tensorList.freeRef();
return temp_18_0016;
Returns
[
[ [ 0.047291163355112076, -0.05769770219922066, -0.04716409370303154, 0.03635771945118904, 0.03412790969014168 ], [ -0.007262136321514845, 0.12269169092178345, 0.12023091316223145, -0.10290073603391647, 0.03536438196897507 ], [ 0.032556191086769104, -0.03332327678799629, -0.16121388971805573, -0.049787167459726334, 0.16682150959968567 ], [ 0.05293300002813339, -0.07777321338653564, 0.054085634648799896, -0.04217197373509407, 0.007691083941608667 ], [ 0.018252551555633545, -0.0025830529630184174, 0.0703902468085289, -0.020524073392152786, -0.04395710304379463 ], [ -0.0827527865767479, 0.1120554506778717, 0.019629105925559998, -0.06239601597189903, -0.16434819996356964 ], [ 0.05337943881750107, -0.0674743577837944, -0.20677486062049866, -0.12160060554742813, -0.035599008202552795 ], [ -0.038503460586071014, 0.03020406886935234, -0.053333431482315063, 0.0738474503159523, -0.01663542166352272 ], ... ],
[ [ 0.03422505781054497, 0.03367418050765991, 0.1556309461593628, 0.13838057219982147, -0.08608181029558182 ], [ 0.07279403507709503, -0.15269872546195984, -0.1084805428981781, -0.10794594883918762, 0.059000708162784576 ], [ -0.11358480155467987, 0.058287590742111206, -0.09364429861307144, -0.02075641043484211, 0.09045692533254623 ], [ 0.011766361072659492, 0.029545942321419716, 0.09396624565124512, 0.07656329870223999, 0.0031818815041333437 ], [ -0.05430828779935837, 0.12721221148967743, 0.09072595834732056, 0.050049789249897, -0.12141284346580505 ], [ -0.0550205297768116, 0.045756321400403976, -0.03619515150785446, -0.022615354508161545, 0.2892089784145355 ], [ 0.04433785006403923, 0.007817457430064678, -0.11817558109760284, 0.057565297931432724, -0.04386759549379349 ], [ -0.07465320825576782, -0.009919018484652042, 0.08773107081651688, -0.10889396071434021, 0.06285874545574188 ], ... ],
[ [ 5.895073409192264E-4, -0.0322393923997879, -0.0069696614518761635, 0.012688031420111656, 0.048756521195173264 ], [ 0.01710902899503708, -0.22171637415885925, -0.1248839870095253, 0.1713736206293106, 0.1728607416152954 ], [ 0.005339545197784901, -0.07769333571195602, 0.07853332906961441, 0.022068209946155548, -0.041537344455718994 ], [ -0.12977497279644012, 0.06149601936340332, 0.007751130033284426, -0.016728173941373825, 0.08729476481676102 ], [ 0.014585199765861034, -0.0352751687169075, -0.0033118370920419693, 0.08873854577541351, -0.02155369333922863 ], [ 0.12160476297140121, -0.12124717980623245, 0.08223670721054077, 0.1057317703962326, 0.09721238166093826 ], [ 0.01286736037582159, -0.10939396172761917, -0.13146308064460754, -0.01798458956182003, 0.06001417338848114 ], [ 0.010096431709825993, 0.0702868178486824, 0.13041546940803528, 0.0021907135378569365, -0.11074168235063553 ], ... ],
[ [ -0.047341085970401764, -0.04606484994292259, -0.039222098886966705, -0.07138065248727798, -0.04592901095747948 ], [ -0.16167962551116943, -0.0063961041159927845, 0.06904226541519165, 0.3033752143383026, 0.04784843698143959 ], [ 0.019516626372933388, -0.03276434540748596, 0.16437816619873047, 0.1130165308713913, -0.016548367217183113 ], [ -0.10860133171081543, -0.11832676827907562, 0.061705462634563446, 0.1637519747018814, -0.04924369230866432 ], [ -0.09899760782718658, -0.01768551580607891, 0.06700479239225388, 0.14705237746238708, -0.015466916374862194 ], [ -0.05441233143210411, -0.04044149070978165, 0.08452808111906052, 0.05001183599233627, 0.05724082887172699 ], [ -0.06624376028776169, 0.012907193042337894, 0.05961604416370392, 0.0076876250095665455, 0.06064631789922714 ], [ -0.006578658241778612, -0.017663057893514633, 0.17901359498500824, 0.029921403154730797, -0.17974258959293365 ], ... ],
[ [ 0.03290511295199394, 0.020592911168932915, -0.007784419693052769, -0.027254469692707062, 0.06478086858987808 ], [ -0.009714506566524506, 0.06539420038461685, -0.05394358187913895, -0.03167083114385605, 0.05421867594122887 ], [ 0.08659887313842773, -0.10032424330711365, 0.09235817193984985, 0.08236710727214813, 0.014736358076334 ], [ 0.01533506065607071, -0.015216524712741375, -0.014621262438595295, 0.08311497420072556, 0.15019731223583221 ], [ -0.028424302116036415, 0.08118961751461029, -0.13243944942951202, -0.04609598219394684, -0.040171876549720764 ], [ -0.03518784046173096, -0.02758811227977276, -0.08143149316310883, -0.0038801408372819424, 0.23200596868991852 ], [ 0.0038323593325912952, 0.07257989794015884, -0.017317982390522957, 0.0493081696331501, -0.06252315640449524 ], [ 0.15996940433979034, 0.13556215167045593, 0.10715170949697495, 0.08932267129421234, -0.004200065042823553 ], ... ],
[ [ 0.07186757028102875, -0.024685654789209366, -0.03370685502886772, 0.07844658941030502, 0.026848869398236275 ], [ 0.07682068645954132, -0.1004256010055542, 0.019536757841706276, -0.12141884863376617, 0.10055220872163773 ], [ -0.13134917616844177, 0.015451708808541298, 0.03395036235451698, -0.02834993600845337, -0.07652673125267029 ], [ -0.027359245344996452, -0.020211508497595787, 0.07491851598024368, -0.11131837218999863, 0.09754515439271927 ], [ -0.15963038802146912, 0.020621228963136673, 0.10800032317638397, 0.1278245896100998, 0.17434066534042358 ], [ -0.0704716295003891, -0.01907920092344284, -0.07858987897634506, -0.006468980573117733, 0.09485930949449539 ], [ 0.021975647658109665, 0.0667617917060852, 0.08503730595111847, 0.04027735814452171, -0.0677889734506607 ], [ -0.10689345002174377, 0.06016775965690613, -0.036041680723428726, 0.039035338908433914, -0.03908679634332657 ], ... ],
[ [ -0.041827790439128876, 0.023469964042305946, 0.00955185852944851, -0.08646285533905029, -0.11134292185306549 ], [ -0.010325094684958458, 0.11074088513851166, 0.027949271723628044, -0.08359339088201523, -0.0823931023478508 ], [ -0.01744832843542099, -0.012827129103243351, -0.015161135233938694, -0.01857592910528183, 0.09691895544528961 ], [ 0.05419910326600075, -0.20258936285972595, -0.043809156864881516, 0.06112602725625038, 0.11621573567390442 ], [ -0.055467698723077774, -0.03216953203082085, -0.04985015466809273, -0.05772285908460617, 0.18966341018676758 ], [ -0.12330479174852371, -0.021821096539497375, -0.042948123067617416, 0.16587428748607635, 0.08186405897140503 ], [ -0.061609696596860886, 0.029343334957957268, 0.1401384472846985, -0.06869442015886307, 0.08496347069740295 ], [ 0.03442280367016792, -0.07409392297267914, 0.1451738327741623, 9.490313823334873E-4, -0.0937877967953682 ], ... ],
[ [ 0.1284841001033783, -0.09118347615003586, 0.02799164690077305, -0.1400197595357895, -0.0693981945514679 ], [ -0.07420311123132706, 0.1359531730413437, -0.17911066114902496, -0.04807717353105545, 0.14424842596054077 ], [ 0.11242438107728958, -9.552260744385421E-4, 0.014663603156805038, 0.13772054016590118, 0.06663160026073456 ], [ -0.0389808714389801, -0.1948787420988083, -0.18773230910301208, -0.06780911982059479, 0.0314021110534668 ], [ -0.12186753749847412, -0.07762952148914337, -0.06315474957227707, -0.08921743184328079, 0.14928610622882843 ], [ 0.02139604277908802, 0.1775377243757248, 0.04314054921269417, 0.06803032755851746, -0.09301582723855972 ], [ 0.04234003275632858, 0.06268072873353958, 0.2213853895664215, 0.028407065197825432, -0.031855493783950806 ], [ 0.11116339266300201, -0.11435946077108383, -0.04622018337249756, 0.06139673665165901, -0.03625776618719101 ], ... ],
...
]
First, we use a conjugate gradient descent method, which converges the fastest for purely linear functions.
TrainingTester.java:452 executed in 35.41 seconds (0.251 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new QuadraticSearch());
iterativeTrainer.setOrientation(new GradientDescent());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 13348891693161
Reset training subject: 13349306416520
Constructing line search parameters: GD
F(0.0) = LineSearchPoint{point=PointSample{avg=215.321431391781}, derivative=-112.9671174198888}
F(1.0E-10) = LineSearchPoint{point=PointSample{avg=215.321431391781}, derivative=-112.96711608111755}, evalInputDelta = 0.0
F(7.000000000000001E-10) = LineSearchPoint{point=PointSample{avg=215.321431391781}, derivative=-112.96711574416517}, evalInputDelta = 0.0
New Minimum: 215.321431391781 > 215.32143078240586
F(4.900000000000001E-9) = LineSearchPoint{point=PointSample{avg=215.32143078240586}, derivative=-112.96711480695278}, evalInputDelta = -6.093751494518074E-7
New Minimum: 215.32143078240586 > 215.32142674294843
F(3.430000000000001E-8) = LineSearchPoint{point=PointSample{avg=215.32142674294843}, derivative=-112.9671108769788}, evalInputDelta = -4.648832572229367E-6
New Minimum: 215.32142674294843 > 215.3214034890068
F(2.4010000000000004E-7) = LineSearchPoint{point=PointSample{avg=215.3214034890068}, derivative=-112.96710128290819}, evalInputDelta = -2.7902774206722825E-5
New Minimum: 215.3214034890068 > 215.32124082292074
F(1.6807000000000003E-6) = LineSearchPoint{point=PointSample{avg=215.32124082292074}, derivative=-112.96701512969688}, evalInputDelta = -1.9056886026191933E-4
New Minimum: 215.32124082292074 > 215.32010210719665
F(1.1764900000000001E-5) = LineSearchPoint{point=PointSample{avg=215.32010210719665}, derivative=-112.96641441805826}, evalInputDelta = -0.0013292845843579926
New Minimum: 215.32010210719665 > 215.31212815652134
F(8.235430000000001E-5) = LineSearchPoint{point=PointSample{avg=215.31212815652134}, derivative=-112.96217757978224}, evalInputDelta = -0.009303235259665144
New Minimum: 215.31212815652134 > 215.25631714758933
F(5.764801000000001E-4) = LineSearchPoint{point=PointSample{avg=215.25631714758933}, derivative=-112.93246958167971}, evalInputDelta = -0.06511424419167611
New Minimum: 215.25631714758933 > 214.8660575740014
F(0.004035360700000001) = LineSearchPoint{point=PointSample{avg=214.8660575740014}, derivative=-112.72457211100416}, evalInputDelta = -0.4553738177796163
New Minimum: 214.8660575740014 > 212.15436949927863
F(0.028247524900000005) = LineSearchPoint{point=PointSample{avg=212.15436949927863}, derivative=-111.26925322103683}, evalInputDelta = -3.1670618925023746
New Minimum: 212.15436949927863 > 194.15914378201694
F(0.19773267430000002) = LineSearchPoint{point=PointSample{avg=194.15914378201694}, derivative=-101.08251666769452}, evalInputDelta = -21.162287609764064
New Minimum: 194.15914378201694 > 116.52534984526125
F(1.3841287201) = LineSearchPoint{point=PointSample{avg=116.52534984526125}, derivative=-29.797171384427852}, evalInputDelta = -98.79608154651976
F(9.688901040700001) = LineSearchPoint{point=PointSample{avg=1937.951580125486}, derivative=468.1311820610015}, evalInputDelta = 1722.630148733705
F(0.7453000800538463) = LineSearchPoint{point=PointSample{avg=147.81906206036643}, derivative=-68.17684029290088}, evalInputDelta = -67.50236933141457
F(5.217100560376924) = LineSearchPoint{point=PointSample{avg=443.31982063296704}, derivative=200.24828367817562}, evalInputDelta = 227.99838924118603
F(0.40131542772130185) = LineSearchPoint{point=PointSample{avg=174.8259352586365}, derivative=-88.84740505121704}, evalInputDelta = -40.49549613314451
F(2.809207994049113) = LineSearchPoint{point=PointSample{avg=135.0450483288483}, derivative=55.779097666208024}, evalInputDelta = -80.2763830629327
135.0450483288483 <= 215.321431391781
New Minimum: 116.52534984526125 > 109.1344370031267
F(1.8806236878185425) = LineSearchPoint{point=PointSample{avg=109.1344370031267}, derivative=0.023698264955922813}, evalInputDelta = -106.1869943886543
Right bracket at 1.8806236878185425
Converged to right
Fitness changed from 215.321431391781 to 109.1344370031267
Iteration 1 complete. Error: 109.1344370031267 Total: 13.5820; Orientation: 0.1729; Line Search: 12.1539
F(0.0) = LineSearchPoint{point=PointSample{avg=109.1344370031267}, derivative=-0.009989613851390043}
New Minimum: 109.1344370031267 > 109.12505086851948
F(1.8806236878185425) = LineSearchPoint{point=PointSample{avg=109.12505086851948}, derivative=7.676226223216826E-6}, evalInputDelta = -0.009386134607225927
109.12505086851948 <= 109.1344370031267
Converged to right
Fitness changed from 109.1344370031267 to 109.12505086851948
Iteration 2 complete. Error: 109.12505086851948 Total: 1.7082; Orientation: 0.1722; Line Search: 1.1125
F(0.0) = LineSearchPoint{point=PointSample{avg=109.12505086851948}, derivative=-2.8890906154940823E-6}
New Minimum: 109.12505086851948 > 109.12504710602792
F(1.8806236878185425) = LineSearchPoint{point=PointSample{avg=109.12504710602792}, derivative=-1.1125567787689872E-6}, evalInputDelta = -3.762491559200498E-6
F(13.164365814729798) = LineSearchPoint{point=PointSample{avg=109.12509468967463}, derivative=9.546651348773204E-6}, evalInputDelta = 4.3821155145451485E-5
F(1.0126435242099845) = LineSearchPoint{point=PointSample{avg=109.12504842749249}, derivative=-1.9325004326140125E-6}, evalInputDelta = -2.4410269929830974E-6
F(7.088504669469891) = LineSearchPoint{point=PointSample{avg=109.12505412185692}, derivative=3.8070750979532976E-6}, evalInputDelta = 3.2533374394461134E-6
F(0.5452695899592224) = LineSearchPoint{point=PointSample{avg=109.12504943358707}, derivative=-2.3740026891151177E-6}, evalInputDelta = -1.4349324146678555E-6
New Minimum: 109.12504710602792 > 109.12504672254708
F(3.816887129714557) = LineSearchPoint{point=PointSample{avg=109.12504672254708}, derivative=7.165294494045927E-7}, evalInputDelta = -4.145972397395781E-6
109.12504672254708 <= 109.12505086851948
New Minimum: 109.12504672254708 > 109.12504645067571
F(3.0583734803928544) = LineSearchPoint{point=PointSample{avg=109.12504645067571}, derivative=4.267655726658754E-12}, evalInputDelta = -4.417843769033425E-6
Right bracket at 3.0583734803928544
Converged to right
Fitness changed from 109.12505086851948 to 109.12504645067571
Iteration 3 complete. Error: 109.12504645067571 Total: 6.0619; Orientation: 0.1729; Line Search: 5.4689
F(0.0) = LineSearchPoint{point=PointSample{avg=109.12504645067571}, derivative=-1.8162216508818749E-6}
New Minimum: 109.12504645067571 > 109.12504264375627
F(3.0583734803928544) = LineSearchPoint{point=PointSample{avg=109.12504264375627}, derivative=-6.734323805599263E-7}, evalInputDelta = -3.8069194374656945E-6
F(21.40861436274998) = LineSearchPoint{point=PointSample{avg=109.12509319790384}, derivative=6.183363481981686E-6}, evalInputDelta = 4.674722812580967E-5
F(1.646816489442306) = LineSearchPoint{point=PointSample{avg=109.12504396650515}, derivative=-1.200869452515763E-6}, evalInputDelta = -2.4841705652534074E-6
F(11.527715426096142) = LineSearchPoint{point=PointSample{avg=109.12505034124987}, derivative=2.491244778608069E-6}, evalInputDelta = 3.89057416327887E-6
F(0.886747340468934) = LineSearchPoint{point=PointSample{avg=109.12504498736996}, derivative=-1.48488184087177E-6}, evalInputDelta = -1.463305750348809E-6
New Minimum: 109.12504264375627 > 109.1250423756102
F(6.207231383282538) = LineSearchPoint{point=PointSample{avg=109.1250423756102}, derivative=5.031818984446064E-7}, evalInputDelta = -4.075065504594022E-6
109.1250423756102 <= 109.12504645067571
New Minimum: 109.1250423756102 > 109.12504203676757
F(4.860606526891323) = LineSearchPoint{point=PointSample{avg=109.12504203676757}, derivative=-2.2025382361217117E-12}, evalInputDelta = -4.413908143874323E-6
Left bracket at 4.860606526891323
Converged to left
Fitness changed from 109.12504645067571 to 109.12504203676757
Iteration 4 complete. Error: 109.12504203676757 Total: 5.6441; Orientation: 0.1755; Line Search: 5.0466
F(0.0) = LineSearchPoint{point=PointSample{avg=109.12504203676757}, derivative=-2.890817843316905E-6}
New Minimum: 109.12504203676757 > 109.12503916792664
F(4.860606526891323) = LineSearchPoint{point=PointSample{avg=109.12503916792664}, derivative=1.7103960170423498E-6}, evalInputDelta = -2.868840923042626E-6
109.12503916792664 <= 109.12504203676757
New Minimum: 109.12503916792664 > 109.12503762307496
F(3.053787218702101) = LineSearchPoint{point=PointSample{avg=109.12503762307496}, derivative=-2.4428613967905885E-12}, evalInputDelta = -4.413692607840858E-6
Left bracket at 3.053787218702101
Converged to left
Fitness changed from 109.12504203676757 to 109.12503762307496
Iteration 5 complete. Error: 109.12503762307496 Total: 2.8407; Orientation: 0.1757; Line Search: 2.2421
F(0.0) = LineSearchPoint{point=PointSample{avg=109.12503762307496}, derivative=-1.8189307768408614E-6}
New Minimum: 109.12503762307496 > 109.12503381703894
F(3.053787218702101) = LineSearchPoint{point=PointSample{avg=109.12503381703894}, derivative=-6.734744603982413E-7}, evalInputDelta = -3.806036019682324E-6
F(21.376510530914707) = LineSearchPoint{point=PointSample{avg=109.12508444124343}, derivative=6.199293152813813E-6}, evalInputDelta = 4.681816847096343E-5
F(1.644346963916516) = LineSearchPoint{point=PointSample{avg=109.12503513893503}, derivative=-1.2021429011325208E-6}, evalInputDelta = -2.4841399266506414E-6
F(11.510428747415613) = LineSearchPoint{point=PointSample{avg=109.1250415345882}, derivative=2.4985791128784766E-6}, evalInputDelta = 3.911513246634968E-6
F(0.8854175959550472) = LineSearchPoint{point=PointSample{avg=109.12503615923998}, derivative=-1.4868124052851722E-6}, evalInputDelta = -1.4638349767892578E-6
New Minimum: 109.12503381703894 > 109.12503355364305
F(6.19792317168533) = LineSearchPoint{point=PointSample{avg=109.12503355364305}, derivative=5.058819519042873E-7}, evalInputDelta = -4.069431909670129E-6
109.12503355364305 <= 109.12503762307496
New Minimum: 109.12503355364305 > 109.1250332122438
F(4.8492478856818115) = LineSearchPoint{point=PointSample{avg=109.1250332122438}, derivative=8.342379201806534E-13}, evalInputDelta = -4.410831152767969E-6
Right bracket at 4.8492478856818115
Converged to right
Fitness changed from 109.12503762307496 to 109.1250332122438
Iteration 6 complete. Error: 109.1250332122438 Total: 5.5756; Orientation: 0.1717; Line Search: 4.9719
Final threshold in iteration 6: 109.1250332122438 (> 0.0) after 35.413s (< 30.000s)
Returns
109.1250332122438
This training apply resulted in the following configuration:
TrainingTester.java:610 executed in 0.00 seconds (0.000 gc):
RefList<double[]> state = network.state();
assert state != null;
String description = state.stream().map(RefArrays::toString).reduce((a, b) -> a + "\n" + b)
.orElse("");
state.freeRef();
return description;
Returns
[0.0015259961975329825, 0.0016109981148917198, 0.0027256813272266375, 0.009343599056918696, 0.0027368103137058552, -0.01305383539139139, -0.005459202941658848, -5.35761363219998E-4, 0.0032768516773573884, -0.007571229510597111, 0.004569445981423489, -0.005154731843935805, -0.006467881802442228, 0.009693635881450809, -0.014929027718158133, 0.005391440254337387, 0.007027390918389864, 0.007434128750689893, -0.0034079804809316406, 0.006005794097369085, -0.0017024796393084326, 4.8379561403948546E-4, 0.007051296752974523, 0.011766913537525505, 0.014368346110202698, 0.008445836306977067, -0.008103613404398084, 0.003132307107464458, -0.002992784270870387, 0.004245648287565111, -0.008996759588697154, 2.293207584154117E-4, -0.004058935253278561, 0.008394924861054294, 0.0026561344325925613, 0.005353390486688917, -0.0021565480109683147, 0.01994231370028199, 2.6491865807072785E-4, -5.693059605829106E-4, -0.00946748870174566, -0.01138482669919178, -0.012906729830175438, 0.0021751625128170766, 0.010577993362543864, -5.309922464721073E-4, -0.0020619207949154074, 0.0028688764623058917, -0.006370004876048631, 7.426282058159578E-4, 0.024300901431357106, 0.0032654634160194577, 0.0035386821991651007, 0.006705810489806723, 0.013834719754473103, -5.310844363162443E-4, 0.010281939510092274, 0.008896958937882846, 0.015585854188040966, 0.008973113451624746, 0.0018437349665451322, -0.010145222355246373, 0.013212243792364835, 0.005367997013739714, 0.006387269524038863, 0.006472609045787686, -0.013309300661978492, 0.0037243308613228976, 0.008926878961909407, -0.002006715603231668, 0.0018486891639878634, -0.01314225706469357, -0.0011031417340367376, -2.1541457457524804E-4, 0.0012786795464184795, 0.022774398546658227, 0.0043499743364740495, -0.005337129989700466, -0.010772037855911814, -0.013375786928146317, 5.031569207779069E-4, 0.020966242865363496, -0.007529724966837574, 0.01186422395310352, -0.005486491607744972, -0.002547300587226688, 0.0010958495037644692, 0.002791664650336685, 0.003974870876733313, 0.01600555030360831, 0.014143074943886303, -0.008788912392204515, -0.006595185668981626, -0.00870667165332452, 0.017222835974248816, -0.006434389938895431, -0.019218093884640526, 0.0030368579456256793, -0.0014167367335054105, 0.008285903496915395, -0.01760318640047848, 0.004326151609047462, -4.16458229040513E-4, 0.011906903680325315, -8.068454026000214E-4, 0.0026667349038550204, -0.004632720027867339, -0.004652194342906066, 8.16486946653825E-4, 0.006226555348655594, 0.007944506488951392, 0.0018371617966760683, 0.009996507025275377, 0.010896116413417038, -0.00999944433453941, -0.001396796211641315, -0.01176700966669764, -0.009491584720989276, 0.004183476520979228, 0.007880390091600797, -0.02019808318233996, 0.005991321886678261, -0.013354244700933294, 0.008510682729848382, -0.02981116270285518, -0.01268586931028439, 0.00432726355885426, -0.007579830990008957, 0.004273373496992923, 0.001125382200204507, -0.013815160928809017, -0.013658914977333032, -0.0031911963062326897, -0.009609158960323246, 0.006707636512882813, -0.009767509489943458, -0.011662139505376956, 0.01444355257672968, 0.004970095992157307, 0.004851874920174335, -0.011403288908640043, 0.013202900143998048, -0.0036211341783273284, 0.029024996724486492, 0.011292015910633373, -0.015965155187686413, 0.008848479909169203, -0.018107814241699036, 0.005088644953576044, 0.008873341270350695, 0.011202547942799422, 0.0013072419553293506, -0.0038113520003438157, 0.005508102683176505, 0.014852455272904925, 0.011457549382292329, 0.012969173008125078, -0.006490462552216207, -0.016121269629121575, -0.011020128320778795, -0.014194415150330935, 0.014437605694238615, 0.004605118599707168, -0.005952393521896319, 5.284828407038787E-4, -0.011328866558441016, -0.0011925221508315871, -0.007158547574175062, -0.009550695013663832, -0.00658755542662536, -2.0425361077901623E-4, -0.0037379252207205703, -0.0012299859380503044, -0.0030713179446835246, 0.011177168433003653, 0.008105757705399364, -0.0014948256355122606, 3.620794922333511E-4, -0.009607161897575368, -0.026371252343731996, 0.009840448351390889, 0.0017003360554427114, 3.689774462191761E-4, 0.008875884165163607, 0.008824948505638827, -0.011947501815591552, -0.015253164936526419, -0.028291559829626466, -0.012310024431040838, 0.010594778162455158, -0.006703316482437621, -0.004493181155550963, 0.009354194330371218, 0.003409035585262099, -0.015436335668951893, -0.0013946469863586716, -0.006443687350332943, 0.01524394295179701, -0.0034723473102713314, -0.0029995328776881917, 0.02017862514049106, 7.604965037348187E-6, 5.637945587419538E-4, -0.007924861946080284, 0.029116119241497325, -0.0052999298046470375, 0.003502955518662732, 0.007810506607848821, -0.008861575431983158, 0.012594574362123854, -0.012821187521516059, 0.004429650350326939, -0.009433554016642165, 0.001983378708789659, -0.007125254441357601, -6.457819813849206E-4, 0.013905750277846705, 1.2792217340535029E-4, -0.006706394298803115, 0.00648474473111582, 1.2763056909571597E-4, 0.005939609463382473, 0.015389505249740176, 0.010287768467068546, -0.01376448788946686, -0.007958259804945633, -0.011816069000523089, -0.022056116743401903, 0.002069608595016675, 0.01746393131164896, -0.012906097360713454, 0.011949361623714634, -0.019615507432887258, -0.004052173919176678, -4.6051805694782036E-4, -0.007152099506581147, -0.020092643535159112, 0.00789085802419403, -0.0061204350047972, -0.0037810055527212273, 0.0016204848995023757, -0.00926582862199645, -0.012059540112135933, 0.024730278297849944, 0.010119117514299362, -0.0027546539408611517, 0.014514419420953877, -0.004764018330025511, -0.003668993515991679, 0.004346980566184414, -0.005999867617797722, 0.0104956043857818, -0.0012485136801143174, 0.010436220098202135, -0.004356005840301663, 0.0022135789532496575, -0.008584434221323546, 0.012847042286130431, 0.002706754482113172, 0.0021989105944118146, -0.016903080727719864, -0.015405923761727941, 0.008836111956384047, -0.001645249359727392, -0.0010233535806616861, -0.0020756357200053957, 0.003761857468111881, 0.009838456367633761, 0.016322713236483977, -0.019915499432622618, -0.01021065606288211, -0.015145169458850699, -0.012740507360887015, 0.0032631095439477646, -0.004489129297672321, -0.017834494605159547, -0.016138678528642644, 0.0013867078037912914, 0.002554533124311266, 0.006571101232248452, -0.005344180075650259, 0.018045883442345582, -4.2906079015064174E-4, -4.2451890130162614E-4, 0.018489455216889373, 0.005463863324332082, 0.002813414641147236, -0.004741682862650931, -0.003407715693980897, 0.002881630009468226, -0.0038595789858975826, 0.0012177912500973887, 0.012446121291222328, -0.013494238281785517, 0.011416806888156952, 0.015190226420228173, -0.005364189457214091, -0.016993880669818082, -0.0076031686000457765, 0.00197477563359882, -0.010807906338586132, -0.01628265827468205, 0.00884600444013808, 0.011420788757054521, -0.005862413327093618, -0.021030405224301975, -0.016746425750025593, 0.005266663166731622, -0.02866212110078671, -0.00851118036216836, -0.0181915114331272, 0.009882554336244135, 7.918142877974496E-4, 0.01606334942011302, -0.01594939557113273, -1.396, 0.996, -1.176, 0.66, 0.656, 1.88, 1.98, 1.244, 0.016, 0.66, -0.032, -0.924, -0.892, 1.22, 1.144, -0.384, 1.664, -1.476, 1.96, 1.352, -0.968, -0.968, 0.344, 1.048, -1.616, 1.656, 0.312, 0.788, -1.5, 1.536, 1.052, 0.132, 1.288, 0.356, -0.032, 1.44, -1.552, 0.56, 1.168, 1.324, 1.652, 0.972, 0.752, -0.028, -0.892, -1.44, -0.344, -1.104, 1.88, -0.02, 0.52, 1.912, -1.54, -1.808, -0.152, -0.636, -1.92, 0.8, 0.324, 0.012, -0.488, 1.524, -1.976, -1.228, 0.56, -1.256, 0.3, 0.7, 1.62, -1.176, 1.356, 1.836, 1.668, -0.636, -1.688, 0.636, 1.288, 0.0, 0.0, 1.26, -0.452, -1.42, 1.66, 1.144, -1.552, -0.212, -0.472, 1.948, 0.868, 1.628, -1.804, 1.704, -0.296, 0.0, 0.0, -1.408, -0.816, -0.628, 0.028, -1.052, 0.932, -0.26, 0.08, 0.98, -1.832, 0.184, -1.524, -1.432, 1.36, -1.656, -0.888, -0.124, 0.812, 1.764, -1.256, 1.144, 1.836, 1.368, 0.784, -0.892, 0.8, -1.044, 0.0, 1.196, -0.032, -1.248]
TrainingTester.java:622 executed in 0.00 seconds (0.000 gc):
return RefArrays.stream(RefUtil.addRef(data)).flatMap(x -> {
return RefArrays.stream(x);
}).limit(1).map(x -> {
String temp_18_0015 = x.prettyPrint();
x.freeRef();
return temp_18_0015;
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
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[ [ 1.3239755313399526, 0.744017152000623, -1.4438856074510285, -1.7440583570428003, -0.2639731033449126, -1.8880264119597114, -0.34792009961975373 ], [ -0.8881508814668676, 1.2040970672139184, -0.9199681552067234, 1.0119625346018128, -1.8958638790398021, -0.8839714913862268, 1.1919951198999978 ], [ -1.063911256741954, -0.31616958265297773, -0.7677754989865042, -0.8798522662345314, 0.09181513174329069, -1.791814062895327, -1.512042751450556 ], [ 1.9798524755684754, -1.7997909081747996, -0.5879910783766792, -1.1880221051535877, -0.4598979696835418, -1.140008673888975, -0.03587871713691919 ], [ 1.7039139951840059, -1.5480489641036308, -1.555901461193369, -1.6319022485936334, 1.0559630848342665, -1.8320064570076295, 1.4879071780130508 ], [ -0.6680999000010059, -0.460092869112084, 0.7239993526859333, 0.45189786305747154, -1.192089534066169, 1.5639426833919061, 1.0597702831632265 ], [ 0.8919243927336633, 1.7041394350031427, -0.472007558845776, -0.5040409830952481, 0.41193025426614527, 0.8759651577653799, 0.49987890480677605 ], [ 0.5001006168365137, 1.5518852439910122, -1.159873447446473, -1.4678662927346982, 1.4557501472661016, -0.3399566473913192, -1.219885067577868 ], ... ],
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...
]
To produce the following output:
TrainingTester.java:633 executed in 0.15 seconds (0.000 gc):
Result[] array = ConstantResult.batchResultArray(pop(RefUtil.addRef(data)));
@Nullable
Result eval = layer.eval(array);
assert eval != null;
TensorList tensorList = Result.getData(eval);
String temp_18_0016 = tensorList.stream().limit(1).map(x -> {
String temp_18_0017 = x.prettyPrint();
x.freeRef();
return temp_18_0017;
}).reduce((a, b) -> a + "\n" + b).orElse("");
tensorList.freeRef();
return temp_18_0016;
Returns
[
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[ [ 0.07202881574630737, -0.02420710027217865, -0.03381415829062462, 0.07905718684196472, 0.025864625349640846 ], [ 0.0775337815284729, -0.09987254440784454, 0.01948038674890995, -0.11945711821317673, 0.10292761027812958 ], [ -0.13067589700222015, 0.015451434068381786, 0.034943364560604095, -0.027699077501893044, -0.07634562999010086 ], [ -0.02602822333574295, -0.022069083526730537, 0.07481547445058823, -0.1114126443862915, 0.09567159414291382 ], [ -0.15855693817138672, 0.01843143254518509, 0.10767867416143417, 0.12747038900852203, 0.17160819470882416 ], [ -0.06938265264034271, -0.01947323977947235, -0.0774216428399086, -0.0052984654903411865, 0.09351504594087601 ], [ 0.022592928260564804, 0.06660974770784378, 0.08605673164129257, 0.038126569241285324, -0.06865961849689484 ], [ -0.10761355608701706, 0.05994575843214989, -0.0359807014465332, 0.03927356004714966, -0.037199944257736206 ], ... ],
[ [ -0.04125595837831497, 0.023759765550494194, 0.010332005098462105, -0.08722781389951706, -0.11066310107707977 ], [ -0.009350444190204144, 0.10959144681692123, 0.025686640292406082, -0.0824241042137146, -0.08100724965333939 ], [ -0.01775830052793026, -0.01260316837579012, -0.014942876063287258, -0.017323128879070282, 0.09562882035970688 ], [ 0.05384443700313568, -0.20269769430160522, -0.04463152214884758, 0.06310968846082687, 0.11541078239679337 ], [ -0.05493570864200592, -0.03226407989859581, -0.04874901473522186, -0.05633408948779106, 0.1910308450460434 ], [ -0.12330733239650726, -0.020947542041540146, -0.04265754669904709, 0.1653992384672165, 0.08293870836496353 ], [ -0.06113962084054947, 0.02844269759953022, 0.140701025724411, -0.07099812477827072, 0.08436743170022964 ], [ 0.0340091697871685, -0.07331138849258423, 0.14465364813804626, 6.919929292052984E-4, -0.09356451779603958 ], ... ],
[ [ 0.12887848913669586, -0.09074680507183075, 0.02767459861934185, -0.13976600766181946, -0.06946611404418945 ], [ -0.07482783496379852, 0.1344384402036667, -0.1789288967847824, -0.04669038578867912, 0.1436687558889389 ], [ 0.11425071954727173, -9.105850476771593E-4, 0.015341542661190033, 0.13843339681625366, 0.06748346984386444 ], [ -0.040174901485443115, -0.19089148938655853, -0.18823055922985077, -0.06784103065729141, 0.03334115073084831 ], [ -0.1226801648736, -0.07673878967761993, -0.06194648891687393, -0.08851470053195953, 0.14982612431049347 ], [ 0.02260497212409973, 0.1760716736316681, 0.04194589704275131, 0.06627332419157028, -0.09707828611135483 ], [ 0.04086679220199585, 0.06225639209151268, 0.2209043651819229, 0.028815263882279396, -0.03212445601820946 ], [ 0.11191263794898987, -0.11359453201293945, -0.04623980075120926, 0.06185198575258255, -0.03626416623592377 ], ... ],
...
]
Next, we apply the same optimization using L-BFGS, which is nearly ideal for purely second-order or quadratic functions.
TrainingTester.java:509 executed in 38.00 seconds (0.315 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new ArmijoWolfeSearch());
iterativeTrainer.setOrientation(new LBFGS());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setIterationsPerSample(100);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 13384515281524
Reset training subject: 13384929864093
Adding measurement 58727a60 to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD
Non-optimal measurement 215.321431391781 < 215.321431391781. Total: 1
th(0)=215.321431391781;dx=-112.96711476880921
Adding measurement 4433e3bf to history. Total: 1
New Minimum: 215.321431391781 > 111.39210763345568
WOLF (strong): th(2.154434690031884)=111.39210763345568; dx=16.466685415587733 evalInputDelta=103.92932375832532
Non-optimal measurement 128.49968364533646 < 111.39210763345568. Total: 2
END: th(1.077217345015942)=128.49968364533646; dx=-48.23447047436778 evalInputDelta=86.82174774644454
Fitness changed from 215.321431391781 to 111.39210763345568
Iteration 1 complete. Error: 111.39210763345568 Total: 3.3136; Orientation: 0.1997; Line Search: 1.8368
Non-optimal measurement 111.39210763345568 < 111.39210763345568. Total: 2
LBFGS Accumulation History: 2 points
Non-optimal measurement 111.39210763345568 < 111.39210763345568. Total: 2
th(0)=111.39210763345568;dx=-2.4138260553443462
Adding measurement 7fba255b to history. Total: 2
New Minimum: 111.39210763345568 > 109.25110120497416
WOLF (strong): th(2.3207944168063896)=109.25110120497416; dx=0.5687514593777319 evalInputDelta=2.141006428481518
Non-optimal measurement 109.45636076663054 < 109.25110120497416. Total: 3
END: th(1.1603972084031948)=109.45636076663054; dx=-0.9225289499307692 evalInputDelta=1.9357468668251414
Fitness changed from 111.39210763345568 to 109.25110120497416
Iteration 2 complete. Error: 109.25110120497416 Total: 2.4407; Orientation: 0.1607; Line Search: 1.8472
Non-optimal measurement 109.25110120497416 < 109.25110120497416. Total: 3
LBFGS Accumulation History: 3 points
Non-optimal measurement 109.25110120497416 < 109.25110120497416. Total: 3
th(0)=109.25110120497416;dx=-0.13433625700491095
Adding measurement 406bb920 to history. Total: 3
New Minimum: 109.25110120497416 > 109.13896999074088
WOLF (strong): th(2.5000000000000004)=109.13896999074088; dx=0.04463125408376016 evalInputDelta=0.11213121423328687
Non-optimal measurement 109.13910824969913 < 109.13896999074088. Total: 4
END: th(1.2500000000000002)=109.13910824969913; dx=-0.04485247537761454 evalInputDelta=0.11199295527502784
Fitness changed from 109.25110120497416 to 109.13896999074088
Iteration 3 complete. Error: 109.13896999074088 Total: 2.6449; Orientation: 0.3198; Line Search: 1.9004
Non-optimal measurement 109.13896999074088 < 109.13896999074088. Total: 4
Rejected: LBFGS Orientation magnitude: 2.285e-01, gradient 1.219e-01, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00, 6c8c563e-a7e1-4862-9723-53aa9fbbeed5 = 1.000/1.000e+00, 5cffe86a-e5e7-4209-90b7-c383e8b1bb8b = 1.000/1.000e+00]
Orientation rejected. Popping history element from 109.13896999074088, 109.25110120497416, 111.39210763345568, 215.321431391781
LBFGS Accumulation History: 3 points
Removed measurement 406bb920 to history. Total: 3
Adding measurement 793a8c0a to history. Total: 3
th(0)=109.13896999074088;dx=-0.014850615552285066
Adding measurement 13159955 to history. Total: 4
New Minimum: 109.13896999074088 > 109.12769182659368
WOLF (strong): th(2.6930433625398553)=109.12769182659368; dx=0.006474838452343571 evalInputDelta=0.011278164147199732
Adding measurement 3473a4a6 to history. Total: 5
New Minimum: 109.12769182659368 > 109.12615211181352
END: th(1.3465216812699277)=109.12615211181352; dx=-0.0041878883775679585 evalInputDelta=0.012817878927350534
Fitness changed from 109.13896999074088 to 109.12615211181352
Iteration 4 complete. Error: 109.12615211181352 Total: 7.7889; Orientation: 5.2828; Line Search: 2.0637
Non-optimal measurement 109.12615211181352 < 109.12615211181352. Total: 6
Rejected: LBFGS Orientation magnitude: 6.449e-02, gradient 3.438e-02, dot -1.000; [5cffe86a-e5e7-4209-90b7-c383e8b1bb8b = 1.000/1.000e+00, ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00, 6c8c563e-a7e1-4862-9723-53aa9fbbeed5 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 109.12615211181352, 109.12769182659368, 109.13896999074088, 109.25110120497416, 111.39210763345568, 215.321431391781
Rejected: LBFGS Orientation magnitude: 6.452e-02, gradient 3.438e-02, dot -1.000; [5cffe86a-e5e7-4209-90b7-c383e8b1bb8b = 1.000/1.000e+00, ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00, 6c8c563e-a7e1-4862-9723-53aa9fbbeed5 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 109.12615211181352, 109.12769182659368, 109.13896999074088, 109.25110120497416, 111.39210763345568
Rejected: LBFGS Orientation magnitude: 6.450e-02, gradient 3.438e-02, dot -1.000; [ed5c21e8-e89d-40d9-ad2c-850db94aad10 = 1.000/1.000e+00, 5cffe86a-e5e7-4209-90b7-c383e8b1bb8b = 1.000/1.000e+00, 6c8c563e-a7e1-4862-9723-53aa9fbbeed5 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 109.12615211181352, 109.12769182659368, 109.13896999074088, 109.25110120497416
LBFGS Accumulation History: 3 points
Removed measurement 3473a4a6 to history. Total: 5
Removed measurement 13159955 to history. Total: 4
Removed measurement 793a8c0a to history. Total: 3
Adding measurement 59a85c89 to history. Total: 3
th(0)=109.12615211181352;dx=-0.0011822109713624145
Adding measurement 715d23e1 to history. Total: 4
New Minimum: 109.12615211181352 > 109.12537166074674
WOLF (strong): th(2.9009930210079875)=109.12537166074674; dx=6.441531625697212E-4 evalInputDelta=7.804510667881459E-4
Adding measurement 4f896afa to history. Total: 5
New Minimum: 109.12537166074674 > 109.12509960279786
END: th(1.4504965105039938)=109.12509960279786; dx=-2.69028759836359E-4 evalInputDelta=0.001052509015664782
Fitness changed from 109.12615211181352 to 109.12509960279786
Iteration 5 complete. Error: 109.12509960279786 Total: 21.8102; Orientation: 19.4545; Line Search: 1.9404
Final threshold in iteration 5: 109.12509960279786 (> 0.0) after 37.999s (< 30.000s)
Returns
109.12509960279786
This training apply resulted in the following configuration:
TrainingTester.java:610 executed in 0.00 seconds (0.000 gc):
RefList<double[]> state = network.state();
assert state != null;
String description = state.stream().map(RefArrays::toString).reduce((a, b) -> a + "\n" + b)
.orElse("");
state.freeRef();
return description;
Returns
[0.0012599069011499336, 6.354531381142902E-5, 0.0036065339096853703, 0.008443083895603611, 0.0036211652742162365, -0.013018155222195385, -0.006621083207885176, -4.077039401662581E-4, 0.004295758862153894, -0.008260604830674508, 0.0046205286554162105, -0.003969574285324075, -0.007472884766132957, 0.008244030218874028, -0.015427528684715633, 0.005225522614710562, 0.006641046248172604, 0.007558862409244339, -0.004697295779772539, 0.006752963785855385, -0.002646692773875442, 8.076333950650437E-4, 0.0069278299515982055, 0.01047927765326944, 0.013138339408979674, 0.007702144227321669, -0.009205429807271157, 0.0023717130579718796, -0.003259164401403704, 0.0025598521685031633, -0.008938730911359336, -2.2477288965650258E-4, -0.003625626641789552, 0.007340392767188774, 0.0030876957585068265, 0.006307030592110741, -0.003226169472510722, 0.020427641540513637, 0.0017806061740443394, -9.823869639414072E-4, -0.009111916343183953, -0.010877291095178388, -0.012308105287699184, 0.0035068007817438632, 0.011971041957475396, 7.210461758295201E-4, -0.0018093826656276038, 0.002146659225814569, -0.00758850775731269, -9.234451256539848E-4, 0.02402638836538546, 0.0033957955254069155, 0.0033030083891170104, 0.0063837182920660936, 0.013881434891117825, -0.0021661816628595586, 0.00960480436931623, 0.007431653073937152, 0.014255163147546305, 0.007866930247896097, 0.0031319116244363974, -0.009157705936426707, 0.013104574651012049, 0.005062101016945055, 0.006421237310704235, 0.0065148336908756495, -0.013289545128377206, 0.003417103320685857, 0.007268352316975014, -6.265172473511656E-4, 0.002929445235711019, -0.014735427405410879, -5.599963621178809E-4, -0.0015636361549460982, 8.396521184613538E-4, 0.023242579267687274, 0.005044897830736544, -0.0044128623479633795, -0.010562334623982508, -0.01474907845996807, 6.805317307417424E-4, 0.02146293134473611, -0.007141989059501399, 0.011518307019220138, -0.0039037150047429286, -0.003937891780733948, 4.991784162616144E-4, 0.002805613408896939, 0.004675413959330259, 0.016812511171604615, 0.014327292427813942, -0.009072477207800725, -0.006962342765525856, -0.010092239634108865, 0.016278731427705626, -0.005697152176601886, -0.019206759173114055, 0.0036838229112426206, -0.0017479962341478332, 0.009072723552903861, -0.016243661000386694, 0.005558652425034663, -0.0012320962061464174, 0.013496200006097999, -1.2934411818728373E-4, 0.0034401984369640437, -0.00614230871166146, -0.0036297279278578306, 3.213415590115438E-4, 0.005655355209896641, 0.008818727688196805, 0.003184828676649918, 0.008914698986856632, 0.011048798401054565, -0.011557534129831074, -0.0017767260117036096, -0.010148737809873444, -0.008672268664808361, 0.0033824001197148576, 0.006713838249746087, -0.021699961178248926, 0.006753917542408875, -0.012987918052806793, 0.008001507955114917, -0.029797852263564052, -0.01263575500745444, 0.003264998570439838, -0.006301294213635804, 0.002876512277858478, 0.0016944047302975482, -0.01432073337935234, -0.013519397297014464, 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2.285602837766667E-6, 0.0067135519639436505, 0.014910975461350152, 0.009090421065438493, -0.014995436444497932, -0.00938992852298833, -0.012382721696655028, -0.022659499222411582, 7.694331049683785E-4, 0.01710407497784572, -0.012142034911833301, 0.013394813883299925, -0.01955982585070864, -0.003970410694446106, -0.0014797965403613583, -0.007016120958079021, -0.02184834292226541, 0.007874979093601558, -0.00700594925542242, -0.002432606640378499, 0.0030701119260022128, -0.00802771698905824, -0.011677747194217788, 0.025438876024154008, 0.010820692331407325, -0.001245270103119511, 0.016076757427064523, -0.00600553311078213, -0.003127086947963564, 0.004043191413773883, -0.006747423865856335, 0.010427932529480745, -0.0025532546245085937, 0.011783276904778515, -0.005409444226120459, 0.0032075972054614395, -0.007928301619366836, 0.012157201796499983, 0.004204641398149622, 7.064251143440977E-4, -0.01766900431724793, -0.015710905014986207, 0.009148978307132112, -0.0012710115152493174, -8.366890278035996E-4, -0.0035364215620044834, 0.004838893635387274, 0.009174698233180798, 0.016495181697355744, -0.02033781116712854, -0.010473520959693472, -0.015327577687430807, -0.012974842309783904, 0.004476012080859445, -0.0035592381891965215, -0.01803418903328314, -0.016545805646446563, 0.0022967765026603174, 7.911271222245282E-4, 0.006141704033906386, -0.005469694094207273, 0.018926644336664654, -0.0015424491494825292, -7.758534707195583E-5, 0.01918251688476723, 0.005578123354009106, 0.001830741052867701, -0.005369768193441989, -0.0021946064001837056, 0.004369468428158675, -0.00298956948329677, 0.001553767303846972, 0.013937308937457055, -0.015033800216509408, 0.010169283207023483, 0.01615262585105153, -0.0057972540102695005, -0.015488882457369985, -0.008355860547267228, 6.006956366999966E-4, -0.009705246608762994, -0.016624267267309135, 0.007564675275368922, 0.010206424884018076, -0.004251970838674617, -0.01990328873104565, -0.015823578648155506, 0.006687643975114757, -0.028348920459164508, -0.008685936928315333, -0.016917308890740907, 0.010306471103324279, 6.932627800829984E-4, 0.017188849347127003, -0.01735034173961694, -1.396, 0.996, -1.176, 0.66, 0.656, 1.88, 1.98, 1.244, 0.016, 0.66, -0.032, -0.924, -0.892, 1.22, 1.144, -0.384, 1.664, -1.476, 1.96, 1.352, -0.968, -0.968, 0.344, 1.048, -1.616, 1.656, 0.312, 0.788, -1.5, 1.536, 1.052, 0.132, 1.288, 0.356, -0.032, 1.44, -1.552, 0.56, 1.168, 1.324, 1.652, 0.972, 0.752, -0.028, -0.892, -1.44, -0.344, -1.104, 1.88, -0.02, 0.52, 1.912, -1.54, -1.808, -0.152, -0.636, -1.92, 0.8, 0.324, 0.012, -0.488, 1.524, -1.976, -1.228, 0.56, -1.256, 0.3, 0.7, 1.62, -1.176, 1.356, 1.836, 1.668, -0.636, -1.688, 0.636, 1.288, 0.0, 0.0, 1.26, -0.452, -1.42, 1.66, 1.144, -1.552, -0.212, -0.472, 1.948, 0.868, 1.628, -1.804, 1.704, -0.296, 0.0, 0.0, -1.408, -0.816, -0.628, 0.028, -1.052, 0.932, -0.26, 0.08, 0.98, -1.832, 0.184, -1.524, -1.432, 1.36, -1.656, -0.888, -0.124, 0.812, 1.764, -1.256, 1.144, 1.836, 1.368, 0.784, -0.892, 0.8, -1.044, 0.0, 1.196, -0.032, -1.248]
TrainingTester.java:622 executed in 0.00 seconds (0.000 gc):
return RefArrays.stream(RefUtil.addRef(data)).flatMap(x -> {
return RefArrays.stream(x);
}).limit(1).map(x -> {
String temp_18_0015 = x.prettyPrint();
x.freeRef();
return temp_18_0015;
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
[ [ -1.1280302635890591, -1.3759375117018597, 0.15995327612873475, -0.4638931382291313, 1.3559612778932049, 0.6519078597475447, -1.0279517848334552 ], [ -1.6238807786994938, 1.7119025127777143, 1.4919362956067372, 0.79592308708548, 1.7399342986639388, 1.3639444041339124, 1.7198069168063805 ], [ 1.8598078966474743, 0.8480066803823813, -0.9759173691387394, -0.38404690462940355, 0.9277794504791254, 0.4600641839912594, -1.5040930845170921 ], [ -0.6797940001074297, 1.0840167568179946, -0.49196293993637075, -1.8958580792931075, -0.36011251975794534, 1.5197279165073665, -1.3318489981001553 ], [ -1.3479443161759534, -0.3000075802890945, 0.6639241472746208, -1.1559632392938595, -0.5879715287883209, -0.19597896350609023, -0.8240321341371879 ], [ 1.3400238770852813, 0.356104544892451, -0.9720401537138761, 0.8439835021186021, -1.2839751100702326, 1.727992142872933, 0.8319800326149152 ], [ 1.6359968591214475, 0.5880384958197681, -0.015973790027863883, 1.1838049438671945, -1.9757916096183303, -1.4118939719440562, -1.3478709568276417 ], [ 1.12397535321626, 0.07191174390952568, 1.6798975954181647, -1.8799512837065315, 1.5839232190085641, 0.6360113694290095, -1.435924823603288 ], ... ],
[ [ 1.3239547351488226, 0.7440168826706643, -1.4438635270939904, -1.7440758385434145, -0.2639502402049837, -1.888005353561884, -0.3479040191415652 ], [ -0.888157420169358, 1.2040914817523, -0.919954538527369, 1.0119604944140979, -1.895844700348385, -0.8839559860191996, 1.1919837982435626 ], [ -1.0638953444021408, -0.31617041192793927, -0.7677538745971879, -0.8798347846478414, 0.09178314081992728, -1.7917905919846138, -1.5120356042533196 ], [ 1.9798397325111738, -1.7997405148724217, -0.5879826029441421, -1.1880188983648328, -0.45987620352935754, -1.140010919220519, -0.03586387637891368 ], [ 1.7038888081498178, -1.5480403703486971, -1.5559053320794312, -1.6318991236392137, 1.0559667865113658, -1.8319811447855947, 1.4878913512515493 ], [ -0.6681332798037861, -0.46009747916637617, 0.7239962168064203, 0.4518864349160515, -1.1920895848929223, 1.563927964173996, 1.0597633370921775 ], [ 0.8919214466128083, 1.70413341484251, -0.4720125418640776, -0.5040371574418939, 0.41192112590799745, 0.8759556267693271, 0.4998688971253085 ], [ 0.5001038312338858, 1.5518613639232206, -1.1598635463560931, -1.4678640582760325, 1.4557325572741704, -0.3399351960231184, -1.219869737645636 ], ... ],
[ [ 1.9280265795373146, 1.4519218017905553, -0.5719137568451689, 0.2759940373112777, -1.1760332500444284, -1.4479456565735338, 1.6718525091291068 ], [ 1.9277672927915313, 0.4560743493678018, 1.3639768126672875, -0.42013617475225873, 0.1679135897494892, -1.175905645358261, 1.180081664299795 ], [ -0.8879892481328869, 1.8279886116718669, -1.2558881206566812, -1.291867349245096, -1.3520265105054932, -0.9399558724898401, 0.37577312569033594 ], [ 0.5677154998390175, 0.6881608187029403, -0.9237937771250153, -0.4801377166547849, 0.23614115746779774, -1.6796323472622268, -1.2518417224697937 ], [ -0.9639781289026423, 1.807928625686466, -0.8121790650700381, -0.6758804514774646, -0.8477214121517417, -1.1720499661757626, 0.23623158964784188 ], [ -1.9278203933896678, 1.583789781840662, 0.9119290613763452, 1.5079377119973139, 0.3720108104459974, -1.5757440414507176, 1.219713995438679 ], [ 0.49586198602671544, -1.2158958924957797, -0.3520188796785476, -0.06406479661001382, -0.8559806673630355, -1.6278234018817384, -1.7876352666710202 ], [ 0.28023224417788545, 0.1000416757080873, 0.411948819392493, 1.4881078533180456, 0.33584178417611127, 0.975621753431084, -0.1559063236543167 ], ... ],
[ [ -1.2159744017994032, -1.7718409762300729, 0.12001719720323345, 0.5920561297863803, -1.8560459165018957, -0.8240107130573125, 1.2278256098781979 ], [ 1.5078691856111657, -1.8359645550847359, -0.29190638588905965, 0.9920136849203358, 1.9479761817446217, -0.879949922964468, -1.5118373449805742 ], [ -0.619914465292017, -0.7679923556068781, -1.815939115559427, -0.847932202120364, -1.8597767682604074, -1.0080813217993174, 1.4119169327950625 ], [ -1.3319615705453218, -0.715907158274155, 1.1679261880383593, 1.3679908488085983, 0.11614622569217556, 1.6201580561430806, 1.519733371741257 ], [ -0.34416113382153024, 0.45621326874458284, 1.2638196088774003, 0.9199108901747088, 0.01599116241509517, -0.6439387751161116, -0.9360750319868372 ], [ -0.38799257853718716, 0.18783503435245336, 1.7398779163306832, 0.5240618723738086, -1.2799919706160534, 1.211864881241781, 1.4758258283293655 ], [ -0.3038590396068002, -1.2440522035812853, -1.515940914175437, -0.4080102545575167, -1.0559050952539117, -0.8639623740985275, -1.9159408371176363 ], [ 0.2999536936553611, -1.747640209148551, 1.695789923151535, -1.3920354717886947, -1.855691082623485, 1.4599587863034629, 1.4360322239743093 ], ... ],
[ [ -1.207974711676435, 0.5919967335428847, 1.5199208274263107, 0.6721313388844583, 0.9518709874301012, 1.8877270449167523, -0.4719400223778893 ], [ -0.8758036660274316, 0.2519667788356723, -0.039739283054000214, 0.42808834314718497, -1.6480852033740148, 1.175715194989875, -0.36022360666132597 ], [ 1.671911365411512, 0.1720047376851578, -1.6797266097714367, 1.0239578929940998, -0.4240067427138755, -1.387711583736896, -1.3681450597457783 ], [ 1.0277013552179433, -1.0118796477343794, 0.5161832880535323, 0.9758756621274857, 0.17217639238428425, -1.1877766853056129, 0.10396851808707017 ], [ 1.3796820315757203, 0.6957646556117507, -1.6358481566988574, 1.8398009723394217, -0.1639585786611755, -0.5198434735858705, 0.20018158767290145 ], [ 0.8080340558261447, 0.7558714795971292, 0.5120758374737341, 0.9721063700581177, -0.7600161493208085, 0.7917417089245401, -1.2836961934669437 ], [ -0.33169341315549256, -0.47617913099903764, -0.03996111580193535, -0.295860484833593, -0.416048207240004, 0.4039047995430341, -1.8600910747424493 ], [ 0.1439198740366382, 1.0079321384107018, -0.9959626934775052, 1.2598000226282757, 0.584096056155339, -1.523693579388572, 1.0078470144004896 ], ... ],
[ [ 0.44000200823758473, -0.04799863763330516, 1.407993527560455, -1.375959305762884, 1.96394336990243, -1.5600647288148077, -0.13997143483559488 ], [ 0.0839979311432253, -0.15180463597871907, 1.3120089624226308, -0.9838834895160176, -1.2240973180267014, -0.6320528467312706, -0.3760123593086422 ], [ 1.8598620379705437, -1.915948643401267, -1.3878634866311683, 1.0440818437043677, -0.3040545942210376, 0.7120522176506922, 1.1519727798095425 ], [ -1.6319688118419933, -1.1000127760645297, -1.0599903542957017, 1.4720189808004887, -0.5159186531156013, 0.015882158188688055, 0.6519421164503022 ], [ -1.7677651335037574, -1.3758808481489897, -1.739863939778815, 1.6198916422777134, 1.8318559756080703, 1.4919951798797935, -0.7719576047471988 ], [ -0.500135761681702, -0.7118895282606822, -1.2279936478165934, 1.723801214888878, -0.7959619582406314, -1.0436890390948799, -1.5356611160380453 ], [ 1.7597310376392519, 0.37186665418944465, -0.19212424228318792, 0.4359844625481149, -1.7237698812050102, -1.8158935208472744, -1.0279009889468793 ], [ -0.40391693654456073, 1.891686319045249, 0.8238724116034665, 1.019918339041948, 0.7718493764098795, -0.6279123839412684, -0.12802961292444168 ], ... ],
[ [ -0.023867804421666486, -1.8640076125467935, 0.7641273376303941, -1.9399585455119916, 0.6358146807790952, 0.4918921699990109, 1.4079038848288703 ], [ 1.727832553363064, -1.9677867293700066, 0.7239224162168967, 0.02008821378791568, 0.5159965694478966, 1.0878675806896965, -0.4478709595439809 ], [ -1.7356595013174165, -1.9159697686534183, -1.7237477939245704, -1.0118326163703866, -1.227772598594869, 0.9637318330951876, 1.1720025327191168 ], [ -1.3158799352325548, 1.6518178251856568, 0.516099668573309, -1.0520328080864216, -1.527939631661902, -1.8838624342321642, 0.45183069509253315 ], [ -1.1799081987045745, -1.4877646990013156, -1.8238237593919966, 1.5758403532669174, -0.07209220840577721, -1.6199997792135394, 0.9758290596890826 ], [ 0.51595818405485, -1.0958409239754137, -0.711912433854956, 0.3800370384862197, 0.7038583027499011, -0.12381217218498464, -0.9041007135010537 ], [ 0.12800753301207293, 0.4680204208150916, -0.2800075414927, -0.7919315665921188, -0.9838127215681899, -0.11993722774842647, 0.3281169401635931 ], [ 0.36410340733315544, -1.3439032707277927, 1.1717817675782163, 0.3240402151522052, 0.9721820049727979, 0.9518463717562797, -0.3958895486111276 ], ... ],
[ [ -1.2559079001581397, -1.275917376993787, 1.2918949134272149, -1.7398176873395834, -0.7118524805591521, -0.5840709394002755, 0.35996245762624457 ], [ -0.4159423004210843, -1.3319665206419926, 1.2760371846113499, -0.040085790283462666, 1.6518347122065031, -0.6998968225064506, -1.216041783287919 ], [ 0.8758947287266874, -0.13584613976991608, -0.9279407321881245, 1.0238182080577463, 0.35609890497395486, 0.09581723448541288, 1.4120334745998542 ], [ 1.103898991881156, -0.5480010828179348, -0.9639812339454373, -1.3238532217427188, 0.39188452320696743, -1.9038142120029002, 0.44792391929040015 ], [ 1.3077492186616666, 1.276018765047986, 0.8520696055391754, 1.3400039871567857, -0.7359922932577819, -1.3197455999933854, -0.6599542111569591 ], [ 0.6760373915380221, 0.5999374874194843, -0.46403426766397776, 0.032207225573479686, -1.531764578124545, 1.9478908648457658, -1.3918617585636166 ], [ -1.6357018582178091, 1.6160288834841623, 1.1999837389626158, -0.09602755773877045, -1.9598280993784811, -0.4760580446446978, -0.4281049502483042 ], [ 1.7879222023711336, -1.1478361117051012, -1.3200148168438375, 0.3557410759281097, 0.22815788458661243, 0.17613185842049683, -0.16408626696221557 ], ... ],
...
]
To produce the following output:
TrainingTester.java:633 executed in 0.15 seconds (0.000 gc):
Result[] array = ConstantResult.batchResultArray(pop(RefUtil.addRef(data)));
@Nullable
Result eval = layer.eval(array);
assert eval != null;
TensorList tensorList = Result.getData(eval);
String temp_18_0016 = tensorList.stream().limit(1).map(x -> {
String temp_18_0017 = x.prettyPrint();
x.freeRef();
return temp_18_0017;
}).reduce((a, b) -> a + "\n" + b).orElse("");
tensorList.freeRef();
return temp_18_0016;
Returns
[
[ [ 0.05253462493419647, -0.060961391776800156, -0.04915355145931244, 0.044943127781152725, 0.034718725830316544 ], [ -0.016233671456575394, 0.12290003895759583, 0.127451092004776, -0.11302096396684647, 0.04020074009895325 ], [ 0.050113119184970856, -0.043301552534103394, -0.1614861935377121, -0.05539964884519577, 0.1644260436296463 ], [ 0.05835285782814026, -0.07726625353097916, 0.05017804354429245, -0.03869977593421936, -0.005193684250116348 ], [ 0.012580937705934048, -0.015963664278388023, 0.060809772461652756, -0.01035631075501442, -0.03590990602970123 ], [ -0.08878297358751297, 0.11309945583343506, 0.01671976037323475, -0.05650423467159271, -0.15828882157802582 ], [ 0.05483882129192352, -0.0675591230392456, -0.2047373652458191, -0.1157720610499382, -0.038732197135686874 ], [ -0.032793592661619186, 0.03692694380879402, -0.06472142040729523, 0.06214066967368126, -0.026722129434347153 ], ... ],
[ [ 0.03018764965236187, 0.03098188154399395, 0.16697467863559723, 0.1493927389383316, -0.09718886017799377 ], [ 0.07382169365882874, -0.13329929113388062, -0.10972513258457184, -0.10982441157102585, 0.05687632039189339 ], [ -0.11049531400203705, 0.07650627940893173, -0.09535069018602371, -0.023152193054556847, 0.0719057098031044 ], [ 0.023677203804254532, 0.02980288863182068, 0.10090191662311554, 0.0916050523519516, 0.00953651126474142 ], [ -0.06084195524454117, 0.1458895355463028, 0.08885325491428375, 0.05867011472582817, -0.11991757154464722 ], [ -0.06003643944859505, 0.030159328132867813, -0.030834197998046875, -0.02924160845577717, 0.2822554111480713 ], [ 0.05565180629491806, 0.011562099680304527, -0.11840685456991196, 0.046943243592977524, -0.04033660143613815 ], [ -0.07935434579849243, -0.014026215299963951, 0.10873118788003922, -0.12159132212400436, 0.0657888874411583 ], ... ],
[ [ -0.005042321514338255, -0.04131799936294556, -0.006712133530527353, 0.016819635406136513, 0.0508858896791935 ], [ 0.032834555953741074, -0.23088255524635315, -0.13121917843818665, 0.17670510709285736, 0.18516047298908234 ], [ 0.0056329285725951195, -0.0682222917675972, 0.07765109837055206, 0.02332589216530323, -0.047833360731601715 ], [ -0.11967754364013672, 0.04850293695926666, 0.005979724228382111, -0.010464884340763092, 0.08710838109254837 ], [ 0.014213461428880692, -0.048440124839544296, -0.01184352021664381, 0.08456968516111374, -0.03874742612242699 ], [ 0.11868594586849213, -0.12364843487739563, 0.08805715292692184, 0.10221821814775467, 0.08953509479761124 ], [ 0.03672085329890251, -0.11159510910511017, -0.13448466360569, -0.009948537684977055, 0.056183893233537674 ], [ 0.014656975865364075, 0.08876905590295792, 0.1351058930158615, 0.007295503746718168, -0.11032414436340332 ], ... ],
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...
]
TrainingTester.java:432 executed in 0.01 seconds (0.000 gc):
return TestUtil.compare(title + " vs Iteration", runs);
Plotting range=[1.0, 2.0379243045298936], [13.0, 2.046854421244683]; valueStats=DoubleSummaryStatistics{count=24, sum=2623.826727, min=109.125012, average=109.326114, max=111.392108}
Plotting 13 points for GD
Plotting 6 points for CjGD
Plotting 5 points for LBFGS
Returns
TrainingTester.java:435 executed in 0.01 seconds (0.000 gc):
return TestUtil.compareTime(title + " vs Time", runs);
Plotting range=[0.0, 2.0379243045298936], [34.684, 2.046854421244683]; valueStats=DoubleSummaryStatistics{count=24, sum=2623.826727, min=109.125012, average=109.326114, max=111.392108}
Plotting 13 points for GD
Plotting 6 points for CjGD
Plotting 5 points for LBFGS
Returns
TrainingTester.java:255 executed in 0.00 seconds (0.000 gc):
return grid(inputLearning, modelLearning, completeLearning);
Returns
TrainingTester.java:258 executed in 0.00 seconds (0.000 gc):
return new ComponentResult(null == inputLearning ? null : inputLearning.value,
null == modelLearning ? null : modelLearning.value, null == completeLearning ? null : completeLearning.value);
Returns
{"input":{ "LBFGS": { "type": "NonConverged", "value": 100.52900140451678 }, "CjGD": { "type": "NonConverged", "value": 5.845450932939826 }, "GD": { "type": "NonConverged", "value": 1.1603302883392659 } }, "model":{ "LBFGS": { "type": "Converged", "value": 1.7685693749748925E-15 }, "CjGD": { "type": "Converged", "value": 7.097573165140051E-15 }, "GD": { "type": "Converged", "value": 8.124991927148297E-18 } }, "complete":{ "LBFGS": { "type": "NonConverged", "value": 109.12509960279786 }, "CjGD": { "type": "NonConverged", "value": 109.1250332122438 }, "GD": { "type": "NonConverged", "value": 109.12501201477494 } }}
LayerTests.java:425 executed in 0.00 seconds (0.000 gc):
throwException(exceptions.addRef());
| details | result |
|---|---|
| {"input":{ "LBFGS": { "type": "NonConverged", "value": 100.52900140451678 }, "CjGD": { "type": "NonConverged", "value": 5.845450932939826 }, "GD": { "type": "NonConverged", "value": 1.1603302883392659 } }, "model":{ "LBFGS": { "type": "Converged", "value": 1.7685693749748925E-15 }, "CjGD": { "type": "Converged", "value": 7.097573165140051E-15 }, "GD": { "type": "Converged", "value": 8.124991927148297E-18 } }, "complete":{ "LBFGS": { "type": "NonConverged", "value": 109.12509960279786 }, "CjGD": { "type": "NonConverged", "value": 109.1250332122438 }, "GD": { "type": "NonConverged", "value": 109.12501201477494 } }} | OK |
{
"result": "OK",
"performance": {
"execution_time": "307.795",
"gc_time": "4.036"
},
"created_on": 1586747747249,
"file_name": "trainingTest",
"report": {
"simpleName": "IrregularTest_Float",
"canonicalName": "com.simiacryptus.mindseye.layers.cudnn.conv.ConvolutionLayerTest.IrregularTest_Float",
"link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/test/java/com/simiacryptus/mindseye/layers/cudnn/conv/ConvolutionLayerTest.java",
"javaDoc": ""
},
"training_analysis": {
"input": {
"LBFGS": {
"type": "NonConverged",
"value": 100.52900140451678
},
"CjGD": {
"type": "NonConverged",
"value": 5.845450932939826
},
"GD": {
"type": "NonConverged",
"value": 1.1603302883392659
}
},
"model": {
"LBFGS": {
"type": "Converged",
"value": 1.7685693749748925E-15
},
"CjGD": {
"type": "Converged",
"value": 7.097573165140051E-15
},
"GD": {
"type": "Converged",
"value": 8.124991927148297E-18
}
},
"complete": {
"LBFGS": {
"type": "NonConverged",
"value": 109.12509960279786
},
"CjGD": {
"type": "NonConverged",
"value": 109.1250332122438
},
"GD": {
"type": "NonConverged",
"value": 109.12501201477494
}
}
},
"archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/cudnn/conv/ConvolutionLayer/IrregularTest_Float/trainingTest/202004131547",
"id": "341c0c07-cb6f-43b2-9756-d48a2d558f0f",
"report_type": "Components",
"display_name": "Comparative Training",
"target": {
"simpleName": "ConvolutionLayer",
"canonicalName": "com.simiacryptus.mindseye.layers.cudnn.conv.ConvolutionLayer",
"link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/main/java/com/simiacryptus/mindseye/layers/cudnn/conv/ConvolutionLayer.java",
"javaDoc": ""
}
}