Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase
Using Seed 3788627499182801920
In this apply, we use a network to learn this target input, given it's pre-evaluated output:
TrainingTester.java:332 executed in 0.05 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
[
[ [ 1.804, 1.836, 0.024 ], [ -0.212, -0.904, 1.548 ], [ 0.516, -0.636, 1.668 ], [ 0.492, -1.972, -1.66 ], [ 1.26, -1.516, 0.584 ], [ -1.328, 0.264, -0.852 ], [ 0.544, -0.02, -0.76 ], [ 0.184, 1.62, -1.396 ], ... ],
[ [ 1.844, 1.38, 1.308 ], [ 1.916, 1.656, 1.212 ], [ -1.564, -1.612, -0.52 ], [ -1.496, 0.064, -0.484 ], [ 0.752, -1.984, 0.46 ], [ -0.948, -0.932, 0.6 ], [ -1.256, 1.244, 0.432 ], [ -0.032, -1.708, -0.784 ], ... ],
[ [ 1.164, 0.076, -0.336 ], [ 1.62, 0.768, 0.952 ], [ -1.312, 1.996, -0.988 ], [ 1.792, 0.804, -0.028 ], [ 1.036, 1.54, 1.196 ], [ -1.56, -0.732, 1.54 ], [ -0.584, 0.876, -0.252 ], [ 0.332, 1.58, -1.692 ], ... ],
[ [ 1.764, 1.656, 0.92 ], [ 1.064, -1.232, 1.708 ], [ -1.312, 0.332, 0.12 ], [ -1.616, -1.844, 1.564 ], [ -0.928, -1.352, -1.892 ], [ -1.412, -0.304, 0.012 ], [ 0.156, -0.876, -0.368 ], [ 0.632, -0.724, 1.152 ], ... ],
[ [ -0.952, -1.456, -0.268 ], [ 1.556, -1.74, -1.212 ], [ -0.02, 1.744, -0.556 ], [ 0.716, -1.008, 1.464 ], [ -0.736, 1.052, 0.244 ], [ 0.796, -0.684, -1.36 ], [ -0.376, 1.116, -0.928 ], [ -0.5, -1.576, -0.416 ], ... ],
[ [ -0.104, 0.308, -0.728 ], [ -1.808, -1.024, 1.652 ], [ 0.412, -1.24, 0.352 ], [ -1.288, -1.756, -0.9 ], [ 1.352, 0.048, -0.692 ], [ -1.452, 1.78, -1.504 ], [ 0.608, 0.448, 1.912 ], [ -1.04, 0.332, -0.608 ], ... ],
[ [ 1.2, 1.76, 0.4 ], [ 1.276, -1.104, -0.588 ], [ 0.82, 1.26, 0.924 ], [ 1.44, -1.36, 1.664 ], [ 1.424, 1.56, 0.996 ], [ 1.16, 0.008, -1.468 ], [ -0.604, 1.868, 0.952 ], [ -0.096, 1.388, 0.7 ], ... ],
[ [ 0.024, 1.88, -0.336 ], [ -0.192, 1.7, 0.924 ], [ -0.104, -0.7, 1.248 ], [ 0.324, -1.736, -1.168 ], [ -0.812, 0.172, -1.276 ], [ -0.936, 0.916, 0.448 ], [ -0.464, -0.48, 0.136 ], [ 0.784, -1.752, -0.456 ], ... ],
...
]
[
[ [ 0.56, 1.204, -1.1 ], [ 1.432, -1.976, -1.644 ], [ -1.352, -1.352, 0.348 ], [ -0.64, 1.524, 0.828 ], [ 1.964, 0.608, 1.464 ], [ -1.616, -1.68, 0.12 ], [ 1.22, 0.092, 1.548 ], [ -1.008, 0.776, 1.848 ], ... ],
[ [ 1.292, -1.164, -0.696 ], [ -1.772, 0.384, 1.72 ], [ 0.78, 1.656, 0.076 ], [ -0.152, 0.876, -1.536 ], [ -1.936, 1.42, 0.8 ], [ 1.244, 1.62, -0.784 ], [ -1.42, 1.08, -0.804 ], [ 0.672, 0.9, 1.628 ], ... ],
[ [ 0.452, 0.168, -0.736 ], [ -1.796, -1.208, 1.336 ], [ 1.668, -0.268, 1.996 ], [ 1.844, 0.108, 1.432 ], [ -1.452, -0.608, 0.168 ], [ 1.388, 1.912, 1.032 ], [ 0.428, 1.172, -1.476 ], [ -1.812, -0.288, 0.332 ], ... ],
[ [ 1.972, 0.656, 0.112 ], [ -0.348, 1.588, 0.752 ], [ 1.22, 0.028, -1.644 ], [ 1.112, 0.236, -1.64 ], [ -0.72, -0.4, 1.076 ], [ 1.884, 1.68, 1.804 ], [ -0.132, 0.932, 0.396 ], [ 1.24, 1.664, 0.844 ], ... ],
[ [ -1.352, -1.732, -0.724 ], [ 0.192, -1.296, -0.396 ], [ -0.676, 1.38, -1.412 ], [ 1.196, -0.32, -0.48 ], [ -0.34, -1.312, -1.476 ], [ -0.62, 0.056, 1.388 ], [ 0.092, 0.712, 0.94 ], [ 0.1, 1.272, -1.452 ], ... ],
[ [ -1.836, -1.484, 0.676 ], [ 1.632, -1.508, -0.828 ], [ -1.156, 0.16, -1.596 ], [ 0.324, 1.216, -0.124 ], [ 1.36, -1.604, 0.168 ], [ -0.404, -1.32, 0.22 ], [ -0.424, -1.524, -0.74 ], [ -1.636, 1.42, -0.456 ], ... ],
[ [ -1.984, 1.052, 1.144 ], [ -0.804, 0.164, -0.972 ], [ -0.452, -1.98, 0.264 ], [ -0.4, 0.84, 1.524 ], [ -0.996, -0.312, -0.384 ], [ -0.824, -1.544, -1.3 ], [ -0.916, -1.332, -1.308 ], [ 0.424, 1.804, 1.168 ], ... ],
[ [ 1.064, -0.016, 0.528 ], [ 0.688, -0.496, -0.924 ], [ -1.66, 0.312, -0.584 ], [ -1.74, -0.804, -0.896 ], [ -0.036, -1.5, -1.58 ], [ -1.248, 1.244, 1.928 ], [ 0.96, -1.156, 0.632 ], [ -1.24, 0.312, 0.08 ], ... ],
...
]
[
[ [ 0.02, 1.256, 1.568 ], [ -1.076, -1.548, -0.668 ], [ 1.276, -0.636, 1.636 ], [ -0.46, 1.36, 1.372 ], [ -0.176, -1.152, -1.456 ], [ -0.428, 1.656, 0.856 ], [ -1.36, 1.212, -1.44 ], [ 1.316, 0.844, -0.812 ], ... ],
[ [ 1.152, 0.564, 0.076 ], [ -1.164, -0.448, 1.616 ], [ -1.072, -1.452, 0.396 ], [ -0.648, 1.248, -1.796 ], [ 1.432, 0.232, 1.116 ], [ 1.744, -1.332, -0.584 ], [ 1.796, 0.528, -0.736 ], [ 1.248, 1.636, 1.836 ], ... ],
[ [ -1.352, 1.24, -1.384 ], [ -1.644, 1.86, -0.184 ], [ -1.58, -0.216, -0.696 ], [ 0.88, -1.516, -1.64 ], [ 1.912, 0.156, 0.264 ], [ -1.588, 1.036, -1.084 ], [ 1.936, -1.372, -1.94 ], [ -1.68, 1.264, 0.192 ], ... ],
[ [ -1.88, 0.444, 1.392 ], [ 0.92, 1.608, -0.856 ], [ -0.052, 0.932, 0.316 ], [ 0.1, 1.264, -1.86 ], [ 0.588, -0.408, 0.9 ], [ -1.784, 1.004, -1.232 ], [ 1.868, 1.54, 1.12 ], [ 1.828, 0.12, -1.088 ], ... ],
[ [ -0.544, 0.104, 1.228 ], [ -1.128, -1.184, -0.312 ], [ -0.064, -0.924, 0.608 ], [ 0.548, -1.04, 1.244 ], [ 0.764, 1.956, -1.484 ], [ -0.312, 1.712, 0.9 ], [ 1.452, 0.608, -1.696 ], [ -1.8, -0.872, 1.444 ], ... ],
[ [ -0.34, 1.2, -1.692 ], [ 0.308, 1.82, 1.316 ], [ -0.724, 0.404, -1.488 ], [ 1.128, -0.496, 0.432 ], [ 0.04, 0.356, 1.468 ], [ -0.86, -1.908, -1.044 ], [ -0.268, -1.908, 0.688 ], [ -0.732, 1.724, -0.764 ], ... ],
[ [ -1.98, -0.952, 1.384 ], [ 1.268, 1.204, -1.312 ], [ 1.872, -1.228, 1.212 ], [ 0.1, -0.828, -0.008 ], [ 0.932, 0.536, 1.368 ], [ 0.332, 0.868, -0.708 ], [ 0.256, -1.424, -0.948 ], [ 0.788, -1.808, 1.012 ], ... ],
[ [ -0.664, -1.76, -1.564 ], [ -0.272, -0.24, 0.004 ], [ -0.952, -0.836, 1.944 ], [ 0.624, -1.996, -1.388 ], [ -0.696, 1.256, 1.24 ], [ 0.532, 0.464, -1.396 ], [ -1.948, -1.176, 0.792 ], [ -1.492, -0.112, 0.204 ], ... ],
...
]
[
[ [ -1.612, 1.284, 0.908 ], [ 1.944, -0.544, 1.472 ], [ 0.032, 1.812, 1.772 ], [ -1.916, 0.4, -0.66 ], [ -0.256, -1.656, -0.98 ], [ 0.104, -1.28, 1.516 ], [ -1.004, 0.184, 1.444 ], [ 0.472, 0.668, -1.648 ], ... ],
[ [ 0.416, -0.028, -1.948 ], [ -0.016, -0.296, -1.54 ], [ 0.66, 0.444, 0.72 ], [ 0.344, 1.988, -0.804 ], [ 1.112, -0.584, -1.42 ], [ -1.368, -0.228, 0.828 ], [ -1.588, 0.116, 1.148 ], [ -0.16, 0.288, 0.26 ], ... ],
[ [ 0.48, -1.816, -0.184 ], [ 0.216, 1.032, -0.7 ], [ -1.044, 0.76, 1.148 ], [ -0.948, -0.448, -1.296 ], [ -0.812, 1.1, -1.8 ], [ -0.792, 1.06, -1.108 ], [ 0.844, 0.788, 1.964 ], [ 1.352, 1.02, 1.912 ], ... ],
[ [ 1.42, -1.624, 0.464 ], [ 0.612, 1.572, 0.588 ], [ -0.808, 0.868, -0.016 ], [ -0.28, 0.228, 1.276 ], [ -1.324, 1.804, -1.036 ], [ 0.292, -0.648, -1.728 ], [ -0.536, 0.892, 0.912 ], [ 0.364, -0.852, 0.62 ], ... ],
[ [ -1.312, -0.448, -1.552 ], [ -0.624, -1.696, 1.912 ], [ -0.416, 1.952, -1.232 ], [ -1.564, -1.908, 1.912 ], [ 0.844, 1.356, 1.248 ], [ 0.104, -0.864, 0.856 ], [ -0.66, 0.54, -1.36 ], [ 1.168, -0.444, -1.164 ], ... ],
[ [ -1.616, -1.06, -0.996 ], [ -1.556, 1.3, 1.7 ], [ -1.416, -1.16, -0.676 ], [ -0.348, -0.48, 0.804 ], [ 1.804, 0.148, -1.804 ], [ -1.668, -1.288, -1.732 ], [ 0.66, -0.312, -0.84 ], [ 1.656, -1.94, 1.288 ], ... ],
[ [ -0.032, -0.564, -0.72 ], [ 1.492, -1.784, 0.312 ], [ -0.104, -0.908, 1.572 ], [ 0.12, -0.264, 0.464 ], [ 0.54, 1.616, 0.716 ], [ -1.372, 0.48, -1.168 ], [ -0.548, 0.824, 0.624 ], [ -1.312, -1.132, 1.412 ], ... ],
[ [ 0.392, 0.32, 0.4 ], [ 1.448, -0.624, -0.468 ], [ -1.076, -1.104, 1.608 ], [ 1.444, -0.432, -1.648 ], [ -1.188, 1.628, -0.832 ], [ -0.156, 0.264, 0.8 ], [ -0.448, 0.092, 1.528 ], [ 1.616, 0.888, 0.732 ], ... ],
...
]
[
[ [ 1.88, 1.156, -0.216 ], [ -1.644, -1.46, 0.752 ], [ -0.592, -0.18, 0.056 ], [ -1.704, -0.268, -0.256 ], [ 1.016, -1.7, 1.952 ], [ -1.316, -1.372, -1.452 ], [ -0.728, -0.752, -1.5 ], [ 1.668, 1.98, 0.932 ], ... ],
[ [ 0.676, -0.556, 1.72 ], [ -1.376, -0.14, 0.224 ], [ -1.476, 1.844, -1.644 ], [ -0.992, -0.596, 0.024 ], [ 1.556, 1.284, 1.316 ], [ -0.916, 0.812, -1.932 ], [ 0.632, 0.932, 1.264 ], [ -1.32, -0.76, 1.7 ], ... ],
[ [ -1.72, 1.944, 0.74 ], [ 1.304, 0.936, -0.536 ], [ -1.144, -0.288, 1.012 ], [ 1.132, -0.728, 0.604 ], [ 0.268, -0.576, -0.396 ], [ 1.596, -1.112, 0.384 ], [ 1.084, 1.984, 0.988 ], [ -1.312, -0.716, 1.472 ], ... ],
[ [ -1.444, 1.308, -1.524 ], [ 0.544, 0.68, -1.028 ], [ 0.172, -0.956, 1.628 ], [ -0.104, -0.588, 1.22 ], [ 1.656, -0.604, -0.18 ], [ -0.724, -0.876, -1.144 ], [ 1.24, 1.744, -1.944 ], [ 1.1, 1.224, 0.012 ], ... ],
[ [ -0.464, 0.908, -1.84 ], [ 0.896, 1.992, -0.26 ], [ 0.288, -1.476, 0.8 ], [ -1.812, 1.092, -1.164 ], [ 0.132, 1.032, 1.168 ], [ 0.356, -0.1, -1.552 ], [ 0.76, -0.396, 1.964 ], [ 1.92, -1.704, -0.852 ], ... ],
[ [ 1.24, 0.016, -0.732 ], [ -0.04, 0.356, 1.964 ], [ -1.344, -1.536, -1.808 ], [ 0.276, 0.212, -0.312 ], [ 0.996, 1.368, -1.844 ], [ -1.692, -0.684, -0.96 ], [ -1.088, -1.908, 0.924 ], [ -0.916, 0.7, -1.14 ], ... ],
[ [ 0.116, 1.368, -1.788 ], [ -1.5, -0.84, 1.796 ], [ 1.692, -1.04, -0.62 ], [ 1.84, -1.668, -1.116 ], [ 0.172, 0.428, 1.368 ], [ 0.056, -1.108, 0.82 ], [ 1.448, -1.38, -0.956 ], [ -0.336, -0.36, 1.384 ], ... ],
[ [ 0.168, 0.912, -0.176 ], [ -0.796, 1.052, 1.82 ], [ 0.164, -1.232, -1.064 ], [ -1.112, -1.884, 1.68 ], [ 1.704, 1.58, 0.38 ], [ -1.444, -1.32, -1.176 ], [ 0.612, 1.512, -0.812 ], [ 0.624, 1.064, -1.592 ], ... ],
...
]
First, we train using basic gradient descent method apply weak line search conditions.
TrainingTester.java:480 executed in 2.35 seconds (0.000 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: 2212424087819
Reset training subject: 2212504359492
Constructing line search parameters: GD
th(0)=9.600000000000063E-4;dx=-0.006400000000000043
Armijo: th(2.154434690031884)=0.02654581585464764; dx=0.028572030779750825 evalInputDelta=-0.025585815854647635
Armijo: th(1.077217345015942)=0.004706884988513945; dx=0.011974904278764287 evalInputDelta=-0.0037468849885139385
New Minimum: 9.600000000000063E-4 > 5.768492580197477E-5
WOLF (strong): th(0.3590724483386473)=5.768492580197477E-5; dx=0.0010501768593537586 evalInputDelta=9.023150741980315E-4
END: th(0.08976811208466183)=4.7143943142877176E-4; dx=-0.004484946942193898 evalInputDelta=4.885605685712346E-4
Fitness changed from 9.600000000000063E-4 to 5.768492580197477E-5
Iteration 1 complete. Error: 5.768492580197477E-5 Total: 0.3873; Orientation: 0.0138; Line Search: 0.2341
th(0)=5.768492580197477E-5;dx=-3.845661720131651E-4
New Minimum: 5.768492580197477E-5 > 7.2834648611101475E-6
END: th(0.1933995347338658)=7.2834648611101475E-6; dx=-1.3664977620739155E-4 evalInputDelta=5.040146094086462E-5
Fitness changed from 5.768492580197477E-5 to 7.2834648611101475E-6
Iteration 2 complete. Error: 7.2834648611101475E-6 Total: 0.0864; Orientation: 0.0053; Line Search: 0.0558
th(0)=7.2834648611101475E-6;dx=-4.855643240740098E-5
New Minimum: 7.2834648611101475E-6 > 5.923033386856749E-7
WOLF (strong): th(0.41666666666666674)=5.923033386856749E-7; dx=1.015377152033015E-5 evalInputDelta=6.691161522424472E-6
END: th(0.20833333333333337)=6.800148520012414E-7; dx=-1.4836687680033135E-5 evalInputDelta=6.603450009108906E-6
Fitness changed from 7.2834648611101475E-6 to 5.923033386856749E-7
Iteration 3 complete. Error: 5.923033386856749E-7 Total: 0.1248; Orientation: 0.0034; Line Search: 0.1010
th(0)=5.923033386856749E-7;dx=-3.948688924571165E-6
New Minimum: 5.923033386856749E-7 > 1.4579554860220143E-7
WOLF (strong): th(0.4488405604233092)=1.4579554860220143E-7; dx=1.9590835749014382E-6 evalInputDelta=4.465077900834735E-7
New Minimum: 1.4579554860220143E-7 > 3.759345370445863E-8
END: th(0.2244202802116546)=3.759345370445863E-8; dx=-9.948026748361528E-7 evalInputDelta=5.547098849812163E-7
Fitness changed from 5.923033386856749E-7 to 3.759345370445863E-8
Iteration 4 complete. Error: 3.759345370445863E-8 Total: 0.3207; Orientation: 0.0047; Line Search: 0.2860
th(0)=3.759345370445863E-8;dx=-2.5062302469639085E-7
New Minimum: 3.759345370445863E-8 > 1.406489026218959E-8
WOLF (strong): th(0.4834988368346646)=1.406489026218959E-8; dx=1.5329677838608282E-7 evalInputDelta=2.3528563442269037E-8
New Minimum: 1.406489026218959E-8 > 1.417327612705842E-9
END: th(0.2417494184173323)=1.417327612705842E-9; dx=-4.866312315515401E-8 evalInputDelta=3.6176126091752786E-8
Fitness changed from 3.759345370445863E-8 to 1.417327612705842E-9
Iteration 5 complete. Error: 1.417327612705842E-9 Total: 0.1165; Orientation: 0.0084; Line Search: 0.0884
th(0)=1.417327612705842E-9;dx=-9.448850751372281E-9
New Minimum: 1.417327612705842E-9 > 7.679925277825127E-10
WOLF (strong): th(0.5208333333333335)=7.679925277825127E-10; dx=6.955404025257911E-9 evalInputDelta=6.493350849233293E-10
New Minimum: 7.679925277825127E-10 > 2.4674733226081573E-11
END: th(0.26041666666666674)=2.4674733226081573E-11; dx=-1.2467233630151516E-9 evalInputDelta=1.3926528794797604E-9
Fitness changed from 1.417327612705842E-9 to 2.4674733226081573E-11
Iteration 6 complete. Error: 2.4674733226081573E-11 Total: 0.2528; Orientation: 0.0043; Line Search: 0.2263
th(0)=2.4674733226081573E-11;dx=-1.6449822150721045E-10
New Minimum: 2.4674733226081573E-11 > 1.8683562209606066E-11
WOLF (strong): th(0.5610507005291365)=1.8683562209606066E-11; dx=1.4314125319416773E-10 evalInputDelta=5.991171016475506E-12
New Minimum: 1.8683562209606066E-11 > 1.039798694133332E-13
END: th(0.28052535026456826)=1.039798694133332E-13; dx=-1.0678484159294425E-11 evalInputDelta=2.4570753356668238E-11
Fitness changed from 2.4674733226081573E-11 to 1.039798694133332E-13
Iteration 7 complete. Error: 1.039798694133332E-13 Total: 0.0836; Orientation: 0.0039; Line Search: 0.0643
Low gradient: 8.325858090444619E-7
th(0)=1.039798694133332E-13;dx=-6.931991294222211E-13
Armijo: th(0.6043735460433307)=1.0703370668171378E-13; dx=7.033049233942907E-13 evalInputDelta=-3.053837268380584E-15
New Minimum: 1.039798694133332E-13 > 5.524768796285153E-18
WOLF (strong): th(0.30218677302166536)=5.524768796285153E-18; dx=5.052896806020351E-15 evalInputDelta=1.0397434464453691E-13
END: th(0.10072892434055512)=4.587702944268965E-14; dx=-4.604484543728362E-13 evalInputDelta=5.810283997064354E-14
Fitness changed from 1.039798694133332E-13 to 5.524768796285153E-18
Iteration 8 complete. Error: 5.524768796285153E-18 Total: 0.1100; Orientation: 0.0029; Line Search: 0.0898
Low gradient: 6.068920165501796E-9
th(0)=5.524768796285153E-18;dx=-3.6831791975234346E-17
New Minimum: 5.524768796285153E-18 > 4.227491376500088E-19
END: th(0.21701388888888895)=4.227491376500088E-19; dx=-1.0188427518720615E-17 evalInputDelta=5.102019658635144E-18
Fitness changed from 5.524768796285153E-18 to 4.227491376500088E-19
Iteration 9 complete. Error: 4.227491376500088E-19 Total: 0.0692; Orientation: 0.0037; Line Search: 0.0465
Low gradient: 1.6787875340058348E-9
th(0)=4.227491376500088E-19;dx=-2.818327584333392E-18
New Minimum: 4.227491376500088E-19 > 1.318526782836748E-19
WOLF (strong): th(0.46754225044094716)=1.318526782836748E-19; dx=1.573963236067921E-18 evalInputDelta=2.9089645936633397E-19
New Minimum: 1.318526782836748E-19 > 2.0603235317653304E-20
END: th(0.23377112522047358)=2.0603235317653304E-20; dx=-6.221825371055186E-19 evalInputDelta=4.021459023323555E-19
Fitness changed from 4.227491376500088E-19 to 2.0603235317653304E-20
Iteration 10 complete. Error: 2.0603235317653304E-20 Total: 0.0830; Orientation: 0.0033; Line Search: 0.0642
Low gradient: 3.7061422276767613E-10
th(0)=2.0603235317653304E-20;dx=-1.373549021176887E-19
New Minimum: 2.0603235317653304E-20 > 9.49380717891289E-21
WOLF (strong): th(0.5036446217027757)=9.49380717891289E-21; dx=9.3238795778276E-20 evalInputDelta=1.1109428138740413E-20
New Minimum: 9.49380717891289E-21 > 5.313625226688864E-22
END: th(0.25182231085138784)=5.313625226688864E-22; dx=-2.2058293561919526E-20 evalInputDelta=2.0071872794984418E-20
Fitness changed from 2.0603235317653304E-20 to 5.313625226688864E-22
Iteration 11 complete. Error: 5.313625226688864E-22 Total: 0.0648; Orientation: 0.0023; Line Search: 0.0526
Zero gradient: 5.95182057675849E-11
th(0)=5.313625226688864E-22;dx=-3.542416817792576E-21
New Minimum: 5.313625226688864E-22 > 3.4729866094074837E-22
WOLF (strong): th(0.5425347222222224)=3.4729866094074837E-22; dx=2.8638861895048112E-21 evalInputDelta=1.84063861728138E-22
New Minimum: 3.4729866094074837E-22 > 4.87457116776038E-24
END: th(0.2712673611111112)=4.87457116776038E-24; dx=-3.392910499420541E-22 evalInputDelta=5.264879515011259E-22
Fitness changed from 5.313625226688864E-22 to 4.87457116776038E-24
Iteration 12 complete. Error: 4.87457116776038E-24 Total: 0.0666; Orientation: 0.0020; Line Search: 0.0550
Zero gradient: 5.700626379478182E-12
th(0)=4.87457116776038E-24;dx=-3.249714111840253E-23
New Minimum: 4.87457116776038E-24 > 4.381860005956371E-24
WOLF (strong): th(0.584427813051184)=4.381860005956371E-24; dx=3.0811027715954054E-23 evalInputDelta=4.927111618040085E-25
New Minimum: 4.381860005956371E-24 > 3.2236012030951427E-27
END: th(0.292213906525592)=3.2236012030951427E-27; dx=-8.356610425865768E-25 evalInputDelta=4.871347566557284E-24
Fitness changed from 4.87457116776038E-24 to 3.2236012030951427E-27
Iteration 13 complete. Error: 3.2236012030951427E-27 Total: 0.0748; Orientation: 0.0039; Line Search: 0.0591
Zero gradient: 1.4659698048493685E-13
th(0)=3.2236012030951427E-27;dx=-2.149067468730095E-26
Armijo: th(0.6295557771284697)=3.8612111774217786E-27; dx=2.3519975540376157E-26 evalInputDelta=-6.376099743266359E-28
New Minimum: 3.2236012030951427E-27 > 6.3108872417680944E-30
WOLF (strong): th(0.31477788856423483)=6.3108872417680944E-30; dx=9.508403444263928E-28 evalInputDelta=3.2172903158533746E-27
END: th(0.10492596285474494)=1.4199496293978212E-27; dx=-1.4262605166395893E-26 evalInputDelta=1.8036515736973215E-27
Fitness changed from 3.2236012030951427E-27 to 6.3108872417680944E-30
Iteration 14 complete. Error: 6.3108872417680944E-30 Total: 0.0978; Orientation: 0.0034; Line Search: 0.0827
Zero gradient: 6.486338074120658E-15
th(0)=6.3108872417680944E-30;dx=-4.207258161178729E-29
New Minimum: 6.3108872417680944E-30 > 8.41451632235746E-31
END: th(0.22605613425925936)=8.41451632235746E-31; dx=-1.4024193870595766E-29 evalInputDelta=5.469435609532349E-30
Fitness changed from 6.3108872417680944E-30 to 8.41451632235746E-31
Iteration 15 complete. Error: 8.41451632235746E-31 Total: 0.0489; Orientation: 0.0027; Line Search: 0.0360
Zero gradient: 2.3684757858670005E-15
th(0)=8.41451632235746E-31;dx=-5.609677548238306E-30
New Minimum: 8.41451632235746E-31 > 6.310887241768095E-31
WOLF (strong): th(0.48702317754265334)=6.310887241768095E-31; dx=4.2072581611787294E-30 evalInputDelta=2.1036290805893643E-31
New Minimum: 6.310887241768095E-31 > 2.103629080589365E-31
END: th(0.24351158877132667)=2.103629080589365E-31; dx=-1.4024193870595765E-30 evalInputDelta=6.310887241768095E-31
Fitness changed from 8.41451632235746E-31 to 2.103629080589365E-31
Iteration 16 complete. Error: 2.103629080589365E-31 Total: 0.0783; Orientation: 0.0028; Line Search: 0.0574
Zero gradient: 1.1842378929335002E-15
th(0)=2.103629080589365E-31;dx=-1.4024193870595765E-30
Armijo: th(0.5246298142737247)=2.103629080589365E-31; dx=1.4024193870595765E-30 evalInputDelta=0.0
New Minimum: 2.103629080589365E-31 > 0.0
END: th(0.26231490713686234)=0.0; dx=0.0 evalInputDelta=2.103629080589365E-31
Fitness changed from 2.103629080589365E-31 to 0.0
Iteration 17 complete. Error: 0.0 Total: 0.2250; Orientation: 0.0029; Line Search: 0.2100
Zero gradient: 0.0
th(0)=0.0;dx=0.0 (ERROR: Starting derivative negative)
Fitness changed from 0.0 to 0.0
Static Iteration Total: 0.0425; Orientation: 0.0039; Line Search: 0.0267
Iteration 18 failed. Error: 0.0
Previous Error: 0.0 -> 0.0
Optimization terminated 18
Final threshold in iteration 18: 0.0 (> 0.0) after 2.334s (< 30.000s)
Returns
0.0
First, we use a conjugate gradient descent method, which converges the fastest for purely linear functions.
TrainingTester.java:452 executed in 1.14 seconds (0.039 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: 2214766564854
Reset training subject: 2214775883359
Constructing line search parameters: GD
F(0.0) = LineSearchPoint{point=PointSample{avg=9.600000000000063E-4}, derivative=-0.006400000000000043}
New Minimum: 9.600000000000063E-4 > 9.599999993599874E-4
F(1.0E-10) = LineSearchPoint{point=PointSample{avg=9.599999993599874E-4}, derivative=-0.006399999997866646}, evalInputDelta = -6.400189623070873E-13
New Minimum: 9.599999993599874E-4 > 9.59999995520006E-4
F(7.000000000000001E-10) = LineSearchPoint{point=PointSample{avg=9.59999995520006E-4}, derivative=-0.006399999985066708}, evalInputDelta = -4.480000355064351E-12
New Minimum: 9.59999995520006E-4 > 9.59999968640004E-4
F(4.900000000000001E-9) = LineSearchPoint{point=PointSample{avg=9.59999968640004E-4}, derivative=-0.006399999895466701}, evalInputDelta = -3.136000226861002E-11
New Minimum: 9.59999968640004E-4 > 9.599997804800103E-4
F(3.430000000000001E-8) = LineSearchPoint{point=PointSample{avg=9.599997804800103E-4}, derivative=-0.00639999926826668}, evalInputDelta = -2.195199960393704E-10
New Minimum: 9.599997804800103E-4 > 9.599984633606173E-4
F(2.4010000000000004E-7) = LineSearchPoint{point=PointSample{avg=9.599984633606173E-4}, derivative=-0.006399994877866696}, evalInputDelta = -1.536639388974824E-9
New Minimum: 9.599984633606173E-4 > 9.599892435501566E-4
F(1.6807000000000003E-6) = LineSearchPoint{point=PointSample{avg=9.599892435501566E-4}, derivative=-0.006399964145066774}, evalInputDelta = -1.0756449849748384E-8
New Minimum: 9.599892435501566E-4 > 9.599247061164047E-4
F(1.1764900000000001E-5) = LineSearchPoint{point=PointSample{avg=9.599247061164047E-4}, derivative=-0.00639974901546669}, evalInputDelta = -7.529388360157877E-8
New Minimum: 9.599247061164047E-4 > 9.59473004823809E-4
F(8.235430000000001E-5) = LineSearchPoint{point=PointSample{avg=9.59473004823809E-4}, derivative=-0.006398243108266736}, evalInputDelta = -5.269951761973507E-7
New Minimum: 9.59473004823809E-4 > 9.563140722059335E-4
F(5.764801000000001E-4) = LineSearchPoint{point=PointSample{avg=9.563140722059335E-4}, derivative=-0.006387701757866708}, evalInputDelta = -3.685927794072814E-6
New Minimum: 9.563140722059335E-4 > 9.343473889704297E-4
F(0.004035360700000001) = LineSearchPoint{point=PointSample{avg=9.343473889704297E-4}, derivative=-0.00631391230506664}, evalInputDelta = -2.5652611029576577E-5
New Minimum: 9.343473889704297E-4 > 7.877270157117582E-4
F(0.028247524900000005) = LineSearchPoint{point=PointSample{avg=7.877270157117582E-4}, derivative=-0.005797386135466733}, evalInputDelta = -1.7227298428824814E-4
New Minimum: 7.877270157117582E-4 > 1.2582974488490454E-4
F(0.19773267430000002) = LineSearchPoint{point=PointSample{avg=1.2582974488490454E-4}, derivative=-0.001939291509570384}, evalInputDelta = -8.341702551151018E-4
F(1.3841287201) = LineSearchPoint{point=PointSample{avg=0.009107766555670502}, derivative=0.016703612872652138}, evalInputDelta = 0.008147766555670496
F(0.10647144000769232) = LineSearchPoint{point=PointSample{avg=3.995019043487487E-4}, derivative=-0.0041286092798358525}, evalInputDelta = -5.604980956512576E-4
F(0.7453000800538463) = LineSearchPoint{point=PointSample{avg=0.0015809173907244726}, derivative=0.0068609197519408464}, evalInputDelta = 6.209173907244663E-4
F(0.05733077538875741) = LineSearchPoint{point=PointSample{avg=6.281424274498246E-4}, derivative=-0.005176943458373164}, evalInputDelta = -3.318575725501817E-4
New Minimum: 1.2582974488490454E-4 > 1.1790947461645535E-4
F(0.40131542772130185) = LineSearchPoint{point=PointSample{avg=1.1790947461645535E-4}, derivative=0.0018011631594899147}, evalInputDelta = -8.42090525383551E-4
1.1790947461645535E-4 <= 9.600000000000063E-4
New Minimum: 1.1790947461645535E-4 > 2.821016151728649E-5
F(0.3131773734368775) = LineSearchPoint{point=PointSample{avg=2.821016151728649E-5}, derivative=2.3426441665555699E-4}, evalInputDelta = -9.317898384827198E-4
Right bracket at 0.3131773734368775
New Minimum: 2.821016151728649E-5 > 2.670656705094757E-5
F(0.30211867723632807) = LineSearchPoint{point=PointSample{avg=2.670656705094757E-5}, derivative=3.76653730902556E-5}, evalInputDelta = -9.332934329490587E-4
Right bracket at 0.30211867723632807
Converged to right
Fitness changed from 9.600000000000063E-4 to 2.670656705094757E-5
Iteration 1 complete. Error: 2.670656705094757E-5 Total: 0.6542; Orientation: 0.0025; Line Search: 0.6240
F(0.0) = LineSearchPoint{point=PointSample{avg=2.670656705094757E-5}, derivative=-1.7804378033965044E-4}
New Minimum: 2.670656705094757E-5 > 1.990050831184008E-12
F(0.30211867723632807) = LineSearchPoint{point=PointSample{avg=1.990050831184008E-12}, derivative=1.87857857499922E-9}, evalInputDelta = -2.670656506089674E-5
1.990050831184008E-12 <= 2.670656705094757E-5
Converged to right
Fitness changed from 2.670656705094757E-5 to 1.990050831184008E-12
Iteration 2 complete. Error: 1.990050831184008E-12 Total: 0.0435; Orientation: 0.0031; Line Search: 0.0299
Low gradient: 3.6423900863618E-6
F(0.0) = LineSearchPoint{point=PointSample{avg=1.990050831184008E-12}, derivative=-1.326700554122672E-11}
New Minimum: 1.990050831184008E-12 > 9.925473171156611E-17
F(0.30211867723632807) = LineSearchPoint{point=PointSample{avg=9.925473171156611E-17}, derivative=9.369500433535446E-14}, evalInputDelta = -1.9899515764522962E-12
9.925473171156611E-17 <= 1.990050831184008E-12
Converged to right
Fitness changed from 1.990050831184008E-12 to 9.925473171156611E-17
Iteration 3 complete. Error: 9.925473171156611E-17 Total: 0.0405; Orientation: 0.0024; Line Search: 0.0288
Low gradient: 2.5723495318685615E-8
F(0.0) = LineSearchPoint{point=PointSample{avg=9.925473171156611E-17}, derivative=-6.616982114104407E-16}
New Minimum: 9.925473171156611E-17 > 4.950351175055795E-21
F(0.30211867723632807) = LineSearchPoint{point=PointSample{avg=4.950351175055795E-21}, derivative=4.673070737904278E-18}, evalInputDelta = -9.924978136039105E-17
4.950351175055795E-21 <= 9.925473171156611E-17
Converged to right
Fitness changed from 9.925473171156611E-17 to 4.950351175055795E-21
Iteration 4 complete. Error: 4.950351175055795E-21 Total: 0.0386; Orientation: 0.0021; Line Search: 0.0275
Low gradient: 1.816654649817588E-10
F(0.0) = LineSearchPoint{point=PointSample{avg=4.950351175055795E-21}, derivative=-3.3002341167038633E-20}
New Minimum: 4.950351175055795E-21 > 2.4724604709181786E-25
F(0.30211867723632807) = LineSearchPoint{point=PointSample{avg=2.4724604709181786E-25}, derivative=2.3323348348519893E-22}, evalInputDelta = -4.950103929008703E-21
2.4724604709181786E-25 <= 4.950351175055795E-21
Converged to right
Fitness changed from 4.950351175055795E-21 to 2.4724604709181786E-25
Iteration 5 complete. Error: 2.4724604709181786E-25 Total: 0.2467; Orientation: 0.0028; Line Search: 0.2327
Zero gradient: 1.2838640818295833E-12
F(0.0) = LineSearchPoint{point=PointSample{avg=2.4724604709181786E-25}, derivative=-1.648306980612119E-24}
New Minimum: 2.4724604709181786E-25 > 1.4935766472184488E-29
F(0.30211867723632807) = LineSearchPoint{point=PointSample{avg=1.4935766472184488E-29}, derivative=1.2770430938564503E-26}, evalInputDelta = -2.4723111132534566E-25
1.4935766472184488E-29 <= 2.4724604709181786E-25
Converged to right
Fitness changed from 2.4724604709181786E-25 to 1.4935766472184488E-29
Iteration 6 complete. Error: 1.4935766472184488E-29 Total: 0.0526; Orientation: 0.0033; Line Search: 0.0394
Zero gradient: 9.978565852928463E-15
F(0.0) = LineSearchPoint{point=PointSample{avg=1.4935766472184488E-29}, derivative=-9.957177648122994E-29}
New Minimum: 1.4935766472184488E-29 > 0.0
F(0.30211867723632807) = LineSearchPoint{point=PointSample{avg=0.0}, derivative=0.0}, evalInputDelta = -1.4935766472184488E-29
0.0 <= 1.4935766472184488E-29
Converged to right
Fitness changed from 1.4935766472184488E-29 to 0.0
Iteration 7 complete. Error: 0.0 Total: 0.0384; Orientation: 0.0027; Line Search: 0.0274
Zero gradient: 0.0
F(0.0) = LineSearchPoint{point=PointSample{avg=0.0}, derivative=0.0}
Fitness changed from 0.0 to 0.0
Static Iteration Total: 0.0231; Orientation: 0.0022; Line Search: 0.0122
Iteration 8 failed. Error: 0.0
Previous Error: 0.0 -> 0.0
Optimization terminated 8
Final threshold in iteration 8: 0.0 (> 0.0) after 1.138s (< 30.000s)
Returns
0.0
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 29.83 seconds (0.087 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: 2215910292229
Reset training subject: 2215919367546
Adding measurement 666cce0b to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD
Non-optimal measurement 9.600000000000063E-4 < 9.600000000000063E-4. Total: 1
th(0)=9.600000000000063E-4;dx=-0.006400000000000043
Non-optimal measurement 0.02654581585464764 < 9.600000000000063E-4. Total: 1
Armijo: th(2.154434690031884)=0.02654581585464764; dx=0.028572030779750825 evalInputDelta=-0.025585815854647635
Non-optimal measurement 0.004706884988513945 < 9.600000000000063E-4. Total: 1
Armijo: th(1.077217345015942)=0.004706884988513945; dx=0.011974904278764287 evalInputDelta=-0.0037468849885139385
Adding measurement eabdbfb to history. Total: 1
New Minimum: 9.600000000000063E-4 > 5.768492580197477E-5
WOLF (strong): th(0.3590724483386473)=5.768492580197477E-5; dx=0.0010501768593537588 evalInputDelta=9.023150741980315E-4
Non-optimal measurement 4.7143943142877176E-4 < 5.768492580197477E-5. Total: 2
END: th(0.08976811208466183)=4.7143943142877176E-4; dx=-0.004484946942193898 evalInputDelta=4.885605685712346E-4
Fitness changed from 9.600000000000063E-4 to 5.768492580197477E-5
Iteration 1 complete. Error: 5.768492580197477E-5 Total: 0.3937; Orientation: 0.1991; Line Search: 0.1693
Non-optimal measurement 5.768492580197477E-5 < 5.768492580197477E-5. Total: 2
LBFGS Accumulation History: 2 points
Non-optimal measurement 5.768492580197477E-5 < 5.768492580197477E-5. Total: 2
th(0)=5.768492580197477E-5;dx=-3.8456617201316503E-4
Adding measurement 7b4fab9c to history. Total: 2
New Minimum: 5.768492580197477E-5 > 7.2834648611101475E-6
END: th(0.1933995347338658)=7.2834648611101475E-6; dx=-1.3664977620739152E-4 evalInputDelta=5.040146094086462E-5
Fitness changed from 5.768492580197477E-5 to 7.2834648611101475E-6
Iteration 2 complete. Error: 7.2834648611101475E-6 Total: 0.0418; Orientation: 0.0050; Line Search: 0.0266
Non-optimal measurement 7.2834648611101475E-6 < 7.2834648611101475E-6. Total: 3
LBFGS Accumulation History: 3 points
Non-optimal measurement 7.2834648611101475E-6 < 7.2834648611101475E-6. Total: 3
th(0)=7.2834648611101475E-6;dx=-4.855643240740098E-5
Adding measurement ad64896 to history. Total: 3
New Minimum: 7.2834648611101475E-6 > 5.923033386856749E-7
WOLF (strong): th(0.41666666666666674)=5.923033386856749E-7; dx=1.015377152033015E-5 evalInputDelta=6.691161522424472E-6
Non-optimal measurement 6.800148520012414E-7 < 5.923033386856749E-7. Total: 4
END: th(0.20833333333333337)=6.800148520012414E-7; dx=-1.4836687680033135E-5 evalInputDelta=6.603450009108906E-6
Fitness changed from 7.2834648611101475E-6 to 5.923033386856749E-7
Iteration 3 complete. Error: 5.923033386856749E-7 Total: 0.0578; Orientation: 0.0036; Line Search: 0.0458
Non-optimal measurement 5.923033386856749E-7 < 5.923033386856749E-7. Total: 4
Rejected: LBFGS Orientation magnitude: 6.008e-04, gradient 1.987e-03, dot -0.990; [6d8e4188-5538-4eae-8439-1c74e885dde5 = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 1.000/1.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00]
Orientation rejected. Popping history element from 5.923033386856749E-7, 7.2834648611101475E-6, 5.768492580197477E-5, 9.600000000000063E-4
LBFGS Accumulation History: 3 points
Removed measurement ad64896 to history. Total: 3
Adding measurement 7768236a to history. Total: 3
th(0)=5.923033386856749E-7;dx=-3.948688924571165E-6
Adding measurement 1c0d429d to history. Total: 4
New Minimum: 5.923033386856749E-7 > 1.4579554860220143E-7
WOLF (strong): th(0.4488405604233092)=1.4579554860220143E-7; dx=1.9590835749014382E-6 evalInputDelta=4.465077900834735E-7
Adding measurement 310c9bd7 to history. Total: 5
New Minimum: 1.4579554860220143E-7 > 3.759345370445863E-8
END: th(0.2244202802116546)=3.759345370445863E-8; dx=-9.948026748361528E-7 evalInputDelta=5.547098849812163E-7
Fitness changed from 5.923033386856749E-7 to 3.759345370445863E-8
Iteration 4 complete. Error: 3.759345370445863E-8 Total: 0.7045; Orientation: 0.5412; Line Search: 0.1545
Non-optimal measurement 3.759345370445863E-8 < 3.759345370445863E-8. Total: 6
Rejected: LBFGS Orientation magnitude: 1.513e-04, gradient 5.006e-04, dot -0.990; [78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 1.000/1.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00]
Orientation rejected. Popping history element from 3.759345370445863E-8, 1.4579554860220143E-7, 5.923033386856749E-7, 7.2834648611101475E-6, 5.768492580197477E-5, 9.600000000000063E-4
Rejected: LBFGS Orientation magnitude: 1.502e-04, gradient 5.006e-04, dot -1.000; [6d8e4188-5538-4eae-8439-1c74e885dde5 = 1.000/1.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 1.000/1.000e+00]
Orientation rejected. Popping history element from 3.759345370445863E-8, 1.4579554860220143E-7, 5.923033386856749E-7, 7.2834648611101475E-6, 5.768492580197477E-5
Rejected: LBFGS Orientation magnitude: 1.437e-04, gradient 5.006e-04, dot -0.997; [e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 1.000/1.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 3.759345370445863E-8, 1.4579554860220143E-7, 5.923033386856749E-7, 7.2834648611101475E-6
LBFGS Accumulation History: 3 points
Removed measurement 310c9bd7 to history. Total: 5
Removed measurement 1c0d429d to history. Total: 4
Removed measurement 7768236a to history. Total: 3
Adding measurement 786ed07c to history. Total: 3
th(0)=3.759345370445863E-8;dx=-2.5062302469639085E-7
Adding measurement 1f5c92cd to history. Total: 4
New Minimum: 3.759345370445863E-8 > 1.406489026218959E-8
WOLF (strong): th(0.4834988368346646)=1.406489026218959E-8; dx=1.5329677838608282E-7 evalInputDelta=2.3528563442269037E-8
Adding measurement 6da15a2d to history. Total: 5
New Minimum: 1.406489026218959E-8 > 1.417327612705842E-9
END: th(0.2417494184173323)=1.417327612705842E-9; dx=-4.8663123155154E-8 evalInputDelta=3.6176126091752786E-8
Fitness changed from 3.759345370445863E-8 to 1.417327612705842E-9
Iteration 5 complete. Error: 1.417327612705842E-9 Total: 2.5790; Orientation: 2.5111; Line Search: 0.0588
Non-optimal measurement 1.417327612705842E-9 < 1.417327612705842E-9. Total: 6
Rejected: LBFGS Orientation magnitude: 2.945e-05, gradient 9.721e-05, dot -0.989; [e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 1.417327612705842E-9, 1.406489026218959E-8, 3.759345370445863E-8, 7.2834648611101475E-6, 5.768492580197477E-5, 9.600000000000063E-4
Rejected: LBFGS Orientation magnitude: 2.972e-05, gradient 9.721e-05, dot -1.000; [c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 1.417327612705842E-9, 1.406489026218959E-8, 3.759345370445863E-8, 7.2834648611101475E-6, 5.768492580197477E-5
Rejected: LBFGS Orientation magnitude: 2.801e-05, gradient 9.721e-05, dot -0.999; [3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 1.000/1.000e+00, e8eb88ef-
...skipping 20109 bytes...
09 to history. Total: 4
New Minimum: 3.2236012030951427E-27 > 6.3108872417680944E-30
WOLF (strong): th(0.31477788856423483)=6.3108872417680944E-30; dx=9.508403444263928E-28 evalInputDelta=3.2172903158533746E-27
Non-optimal measurement 1.4199496293978212E-27 < 6.3108872417680944E-30. Total: 5
END: th(0.10492596285474494)=1.4199496293978212E-27; dx=-1.4262605166395893E-26 evalInputDelta=1.8036515736973215E-27
Fitness changed from 3.2236012030951427E-27 to 6.3108872417680944E-30
Iteration 14 complete. Error: 6.3108872417680944E-30 Total: 2.8560; Orientation: 2.6447; Line Search: 0.1971
Non-optimal measurement 6.3108872417680944E-30 < 6.3108872417680944E-30. Total: 5
Rejected: LBFGS Orientation magnitude: 1.968e-15, gradient 6.486e-15, dot -0.989; [e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 1.000/1.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 1.000/1.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 6.3108872417680944E-30, 3.2236012030951427E-27, 7.2834648611101475E-6, 5.768492580197477E-5, 9.600000000000063E-4
Rejected: LBFGS Orientation magnitude: 2.005e-15, gradient 6.486e-15, dot -1.000; [e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 6.3108872417680944E-30, 3.2236012030951427E-27, 7.2834648611101475E-6, 5.768492580197477E-5
LBFGS Accumulation History: 3 points
Removed measurement 52cbc309 to history. Total: 4
Removed measurement 66319ab to history. Total: 3
Adding measurement 24a3f698 to history. Total: 3
th(0)=6.3108872417680944E-30;dx=-4.207258161178729E-29
Adding measurement 536e526f to history. Total: 4
New Minimum: 6.3108872417680944E-30 > 8.41451632235746E-31
END: th(0.22605613425925936)=8.41451632235746E-31; dx=-1.4024193870595766E-29 evalInputDelta=5.469435609532349E-30
Fitness changed from 6.3108872417680944E-30 to 8.41451632235746E-31
Iteration 15 complete. Error: 8.41451632235746E-31 Total: 1.2510; Orientation: 1.2023; Line Search: 0.0373
Non-optimal measurement 8.41451632235746E-31 < 8.41451632235746E-31. Total: 5
Rejected: LBFGS Orientation magnitude: 7.328e-16, gradient 2.368e-15, dot -0.985; [c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 0.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 8.41451632235746E-31, 6.3108872417680944E-30, 7.2834648611101475E-6, 5.768492580197477E-5, 9.600000000000063E-4
Rejected: LBFGS Orientation magnitude: 7.878e-16, gradient 2.368e-15, dot -0.995; [c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 0.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 1.000/1.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 8.41451632235746E-31, 6.3108872417680944E-30, 7.2834648611101475E-6, 5.768492580197477E-5
LBFGS Accumulation History: 3 points
Removed measurement 536e526f to history. Total: 4
Removed measurement 24a3f698 to history. Total: 3
Adding measurement 10fe546a to history. Total: 3
th(0)=8.41451632235746E-31;dx=-5.609677548238306E-30
Adding measurement 5310848d to history. Total: 4
New Minimum: 8.41451632235746E-31 > 6.310887241768095E-31
WOLF (strong): th(0.48702317754265334)=6.310887241768095E-31; dx=4.2072581611787294E-30 evalInputDelta=2.1036290805893643E-31
Adding measurement 72edb097 to history. Total: 5
New Minimum: 6.310887241768095E-31 > 2.103629080589365E-31
END: th(0.24351158877132667)=2.103629080589365E-31; dx=-1.4024193870595765E-30 evalInputDelta=6.310887241768095E-31
Fitness changed from 8.41451632235746E-31 to 2.103629080589365E-31
Iteration 16 complete. Error: 2.103629080589365E-31 Total: 1.4972; Orientation: 1.4388; Line Search: 0.0497
Non-optimal measurement 2.103629080589365E-31 < 2.103629080589365E-31. Total: 6
Rejected: LBFGS Orientation magnitude: 3.588e-16, gradient 1.184e-15, dot -0.990; [c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 0.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 0.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 0.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 0.000e+00]
Orientation rejected. Popping history element from 2.103629080589365E-31, 6.310887241768095E-31, 8.41451632235746E-31, 7.2834648611101475E-6, 5.768492580197477E-5, 9.600000000000063E-4
Rejected: LBFGS Orientation magnitude: 3.748e-16, gradient 1.184e-15, dot -0.997; [c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 0.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 0.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 0.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 0.000e+00]
Orientation rejected. Popping history element from 2.103629080589365E-31, 6.310887241768095E-31, 8.41451632235746E-31, 7.2834648611101475E-6, 5.768492580197477E-5
Rejected: LBFGS Orientation magnitude: 4.044e-16, gradient 1.184e-15, dot -0.997; [3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 0.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 0.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 1.000/1.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 0.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 0.000e+00]
Orientation rejected. Popping history element from 2.103629080589365E-31, 6.310887241768095E-31, 8.41451632235746E-31, 7.2834648611101475E-6
LBFGS Accumulation History: 3 points
Removed measurement 72edb097 to history. Total: 5
Removed measurement 5310848d to history. Total: 4
Removed measurement 10fe546a to history. Total: 3
Adding measurement a58c15b to history. Total: 3
th(0)=2.103629080589365E-31;dx=-1.4024193870595765E-30
Non-optimal measurement 2.103629080589365E-31 < 2.103629080589365E-31. Total: 4
Armijo: th(0.5246298142737247)=2.103629080589365E-31; dx=1.4024193870595765E-30 evalInputDelta=0.0
Adding measurement 2124c5e4 to history. Total: 4
New Minimum: 2.103629080589365E-31 > 0.0
END: th(0.26231490713686234)=0.0; dx=0.0 evalInputDelta=2.103629080589365E-31
Fitness changed from 2.103629080589365E-31 to 0.0
Iteration 17 complete. Error: 0.0 Total: 2.4387; Orientation: 2.3874; Line Search: 0.0435
Non-optimal measurement 0.0 < 0.0. Total: 5
Rejected: LBFGS Orientation magnitude: 0.000e+00, gradient 0.000e+00, dot NaN; [6d8e4188-5538-4eae-8439-1c74e885dde5 = 0.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 0.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 0.000e+00, 78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 0.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 0.000e+00]
Orientation rejected. Popping history element from 0.0, 2.103629080589365E-31, 7.2834648611101475E-6, 5.768492580197477E-5, 9.600000000000063E-4
Rejected: LBFGS Orientation magnitude: 0.000e+00, gradient 0.000e+00, dot NaN; [78e259cf-b338-4ff4-9228-3c82cee5b1e4 = 0.000e+00, 3d5ce83f-7c02-4d24-b8d3-db427819ab8e = 0.000e+00, c5007c40-2420-46eb-94e9-0532e614c7f5 = 0.000e+00, 6d8e4188-5538-4eae-8439-1c74e885dde5 = 0.000e+00, e8eb88ef-a084-4a95-b8f6-d9b3e62d7b9b = 0.000e+00]
Orientation rejected. Popping history element from 0.0, 2.103629080589365E-31, 7.2834648611101475E-6, 5.768492580197477E-5
LBFGS Accumulation History: 3 points
Removed measurement 2124c5e4 to history. Total: 4
Removed measurement a58c15b to history. Total: 3
Adding measurement 32c1acaf to history. Total: 3
th(0)=0.0;dx=0.0 (ERROR: Starting derivative negative)
Non-optimal measurement 0.0 < 0.0. Total: 4
Fitness changed from 0.0 to 0.0
Static Iteration Total: 1.2067; Orientation: 1.1406; Line Search: 0.0548
Iteration 18 failed. Error: 0.0
Previous Error: 0.0 -> 0.0
Optimization terminated 18
Final threshold in iteration 18: 0.0 (> 0.0) after 29.830s (< 30.000s)
Returns
0.0
TrainingTester.java:432 executed in 0.14 seconds (0.000 gc):
return TestUtil.compare(title + " vs Iteration", runs);
Plotting range=[1.0, -30.677030834125837], [17.0, -4.238937661650674]; valueStats=DoubleSummaryStatistics{count=38, sum=0.000158, min=0.000000, average=0.000004, max=0.000058}
Plotting 17 points for GD
Plotting 7 points for CjGD
Plotting 17 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, -30.677030834125837], [28.229, -4.238937661650674]; valueStats=DoubleSummaryStatistics{count=38, sum=0.000158, min=0.000000, average=0.000004, max=0.000058}
Plotting 17 points for GD
Plotting 7 points for CjGD
Plotting 17 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": "Converged", "value": 0.0 }, "CjGD": { "type": "Converged", "value": 0.0 }, "GD": { "type": "Converged", "value": 0.0 } }, "model":null, "complete":null}
LayerTests.java:425 executed in 0.00 seconds (0.000 gc):
throwException(exceptions.addRef());
| details | result |
|---|---|
| {"input":{ "LBFGS": { "type": "Converged", "value": 0.0 }, "CjGD": { "type": "Converged", "value": 0.0 }, "GD": { "type": "Converged", "value": 0.0 } }, "model":null, "complete":null} | OK |
{
"result": "OK",
"performance": {
"execution_time": "34.307",
"gc_time": "0.399"
},
"created_on": 1586736843982,
"file_name": "trainingTest",
"report": {
"simpleName": "Negative",
"canonicalName": "com.simiacryptus.mindseye.layers.cudnn.BandReducerLayerTest.Negative",
"link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/test/java/com/simiacryptus/mindseye/layers/cudnn/BandReducerLayerTest.java",
"javaDoc": ""
},
"training_analysis": {
"input": {
"LBFGS": {
"type": "Converged",
"value": 0.0
},
"CjGD": {
"type": "Converged",
"value": 0.0
},
"GD": {
"type": "Converged",
"value": 0.0
}
}
},
"archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/cudnn/BandReducerLayer/Negative/trainingTest/202004131403",
"id": "17a5308b-54de-409e-ba30-e8ad0007c1ab",
"report_type": "Components",
"display_name": "Comparative Training",
"target": {
"simpleName": "BandReducerLayer",
"canonicalName": "com.simiacryptus.mindseye.layers.cudnn.BandReducerLayer",
"link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/main/java/com/simiacryptus/mindseye/layers/cudnn/BandReducerLayer.java",
"javaDoc": ""
}
}