Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase
Using Seed 1824100359163567104
SingleDerivativeTester.java:101 executed in 0.01 seconds (0.000 gc):
log.info(RefString.format("Inputs: %s", prettyPrint(inputPrototype)));
log.info(RefString.format("Inputs Statistics: %s", printStats(inputPrototype)));
log.info(RefString.format("Output: %s", outputPrototype.prettyPrint()));
assert outputPrototype != null;
log.info(RefString.format("Outputs Statistics: %s", outputPrototype.getScalarStatistics()));
},
outputPrototype.addRef(),
RefUtil.addRef(inputPrototype)));
Inputs: [
[ [ 0.08 ], [ 1.208 ], [ 1.108 ], [ 1.032 ], [ 1.612 ], [ 1.552 ], [ -0.804 ], [ -1.832 ] ],
[ [ 0.7 ], [ -1.72 ], [ 0.028 ], [ 0.3 ], [ 1.64 ], [ 1.876 ], [ 0.148 ], [ 1.368 ] ],
[ [ -0.128 ], [ -1.028 ], [ -0.712 ], [ 0.636 ], [ 0.392 ], [ -0.408 ], [ -0.032 ], [ -1.54 ] ],
[ [ 0.496 ], [ -0.384 ], [ 1.048 ], [ -0.176 ], [ 0.092 ], [ -0.384 ], [ -0.892 ], [ -0.876 ] ],
[ [ -0.608 ], [ -0.852 ], [ -1.616 ], [ 1.556 ], [ -0.556 ], [ -1.572 ], [ 1.62 ], [ 1.652 ] ],
[ [ 1.764 ], [ 1.912 ], [ 1.356 ], [ 0.788 ], [ -1.476 ], [ -1.516 ], [ -1.856 ], [ -1.424 ] ],
[ [ 0.048 ], [ -1.688 ], [ 1.512 ], [ -0.768 ], [ 1.704 ], [ -0.636 ], [ 0.996 ], [ -0.464 ] ],
[ [ 1.524 ], [ -0.804 ], [ 1.556 ], [ -0.068 ], [ -1.228 ], [ -1.492 ], [ 0.048 ], [ -0.012 ] ]
],
[
[ [ -0.472 ], [ -0.316 ], [ -1.552 ], [ -1.484 ], [ -1.248 ], [ 0.56 ], [ -0.312 ], [ 0.812 ] ],
[ [ -0.504 ], [ 1.156 ], [ 0.016 ], [ 1.352 ], [ 1.324 ], [ -1.656 ], [ -0.968 ], [ -1.808 ] ],
[ [ -1.156 ], [ 0.972 ], [ 1.288 ], [ -0.888 ], [ 0.344 ], [ -0.856 ], [ -0.892 ], [ 0.644 ] ],
[ [ 0.184 ], [ -1.116 ], [ 1.628 ], [ -1.256 ], [ -1.34 ], [ -1.16 ], [ -0.808 ], [ 0.66 ] ],
[ [ 1.98 ], [ 0.52 ], [ -1.564 ], [ 1.916 ], [ 1.776 ], [ 0.688 ], [ -1.1 ], [ -1.76 ] ],
[ [ -0.628 ], [ -1.456 ], [ -1.764 ], [ -1.724 ], [ 0.52 ], [ -0.124 ], [ -0.968 ], [ 0.82 ] ],
[ [ -0.368 ], [ -2.0 ], [ 0.692 ], [ -1.664 ], [ 1.444 ], [ -1.176 ], [ -0.784 ], [ 1.24 ] ],
[ [ -1.16 ], [ 1.42 ], [ 1.628 ], [ 0.82 ], [ 1.956 ], [ -1.256 ], [ 0.012 ], [ -1.58 ] ]
]
Inputs Statistics: {meanExponent=-0.1923523558471011, negative=32, min=-1.856, max=1.912, mean=0.059375000000000025, count=64, sum=3.8000000000000016, positive=32, stdDev=1.1518728703181615, zeros=0},
{meanExponent=-0.06999649029273047, negative=36, min=-2.0, max=1.98, mean=-0.19524999999999998, count=64, sum=-12.495999999999999, positive=28, stdDev=1.186466998066107, zeros=0}
Output: [
[ [ 0.07999999821186066, -0.47200000286102295 ], [ 1.2079999446868896, -0.3160000145435333 ], [ 1.1080000400543213, -1.5520000457763672 ], [ 1.031999945640564, -1.4839999675750732 ], [ 1.6119999885559082, -1.2480000257492065 ], [ 1.5520000457763672, 0.5600000023841858 ], [ -0.8040000200271606, -0.31200000643730164 ], [ -1.8320000171661377, 0.8119999766349792 ] ],
[ [ 0.699999988079071, -0.5040000081062317 ], [ -1.7200000286102295, 1.156000018119812 ], [ 0.02800000086426735, 0.01600000075995922 ], [ 0.30000001192092896, 1.3519999980926514 ], [ 1.6399999856948853, 1.3240000009536743 ], [ 1.8760000467300415, -1.656000018119812 ], [ 0.14800000190734863, -0.9679999947547913 ], [ 1.3680000305175781, -1.8079999685287476 ] ],
[ [ -0.12800000607967377, -1.156000018119812 ], [ -1.027999997138977, 0.972000002861023 ], [ -0.7120000123977661, 1.2879999876022339 ], [ 0.6359999775886536, -0.8880000114440918 ], [ 0.3919999897480011, 0.3440000116825104 ], [ -0.40799999237060547, -0.8560000061988831 ], [ -0.03200000151991844, -0.8920000195503235 ], [ -1.5399999618530273, 0.6439999938011169 ] ],
[ [ 0.4959999918937683, 0.18400000035762787 ], [ -0.3840000033378601, -1.1160000562667847 ], [ 1.0479999780654907, 1.628000020980835 ], [ -0.17599999904632568, -1.25600004196167 ], [ 0.09200000017881393, -1.340000033378601 ], [ -0.3840000033378601, -1.159999966621399 ], [ -0.8920000195503235, -0.8080000281333923 ], [ -0.8759999871253967, 0.6600000262260437 ] ],
[ [ -0.6079999804496765, 1.9800000190734863 ], [ -0.8519999980926514, 0.5199999809265137 ], [ -1.6160000562667847, -1.5640000104904175 ], [ 1.555999994277954, 1.9160000085830688 ], [ -0.5559999942779541, 1.7760000228881836 ], [ -1.5720000267028809, 0.6880000233650208 ], [ 1.6200000047683716, -1.100000023841858 ], [ 1.6519999504089355, -1.7599999904632568 ] ],
[ [ 1.7640000581741333, -0.628000020980835 ], [ 1.9119999408721924, -1.4559999704360962 ], [ 1.3559999465942383, -1.7640000581741333 ], [ 0.7879999876022339, -1.7239999771118164 ], [ -1.4759999513626099, 0.5199999809265137 ], [ -1.5160000324249268, -0.12399999797344208 ], [ -1.8559999465942383, -0.9679999947547913 ], [ -1.4240000247955322, 0.8199999928474426 ] ],
[ [ 0.04800000041723251, -0.36800000071525574 ], [ -1.687999963760376, -2.0 ], [ 1.5119999647140503, 0.6919999718666077 ], [ -0.7680000066757202, -1.6640000343322754 ], [ 1.7039999961853027, 1.444000005722046 ], [ -0.6359999775886536, -1.1759999990463257 ], [ 0.9959999918937683, -0.7839999794960022 ], [ -0.46399998664855957, 1.2400000095367432 ] ],
[ [ 1.5240000486373901, -1.159999966621399 ], [ -0.8040000200271606, 1.4199999570846558 ], [ 1.555999994277954, 1.628000020980835 ], [ -0.06800000369548798, 0.8199999928474426 ], [ -1.2280000448226929, 1.9559999704360962 ], [ -1.4919999837875366, -1.25600004196167 ], [ 0.04800000041723251, 0.012000000104308128 ], [ -0.012000000104308128, -1.5800000429153442 ] ]
]
Outputs Statistics: {meanExponent=-0.13117442171955512, negative=68, min=-2.0, max=1.9800000190734863, mean=-0.06793750428187195, count=128, sum=-8.69600054807961, positive=60, stdDev=1.1762083152811893, zeros=0}
We validate the agreement between the implemented derivative of the inputs apply finite difference estimations:
SingleDerivativeTester.java:117 executed in 9.62 seconds (0.000 gc):
return testFeedback(
statistics,
component.addRef(),
RefUtil.addRef(inputPrototype),
outputPrototype.addRef());
},
outputPrototype.addRef(),
RefUtil.addRef(inputPrototype),
component.addRef()));
Feedback for input 0
Inputs Values: [
[ [ 0.08 ], [ 1.208 ], [ 1.108 ], [ 1.032 ], [ 1.612 ], [ 1.552 ], [ -0.804 ], [ -1.832 ] ],
[ [ 0.7 ], [ -1.72 ], [ 0.028 ], [ 0.3 ], [ 1.64 ], [ 1.876 ], [ 0.148 ], [ 1.368 ] ],
[ [ -0.128 ], [ -1.028 ], [ -0.712 ], [ 0.636 ], [ 0.392 ], [ -0.408 ], [ -0.032 ], [ -1.54 ] ],
[ [ 0.496 ], [ -0.384 ], [ 1.048 ], [ -0.176 ], [ 0.092 ], [ -0.384 ], [ -0.892 ], [ -0.876 ] ],
[ [ -0.608 ], [ -0.852 ], [ -1.616 ], [ 1.556 ], [ -0.556 ], [ -1.572 ], [ 1.62 ], [ 1.652 ] ],
[ [ 1.764 ], [ 1.912 ], [ 1.356 ], [ 0.788 ], [ -1.476 ], [ -1.516 ], [ -1.856 ], [ -1.424 ] ],
[ [ 0.048 ], [ -1.688 ], [ 1.512 ], [ -0.768 ], [ 1.704 ], [ -0.636 ], [ 0.996 ], [ -0.464 ] ],
[ [ 1.524 ], [ -0.804 ], [ 1.556 ], [ -0.068 ], [ -1.228 ], [ -1.492 ], [ 0.048 ], [ -0.012 ] ]
]
Value Statistics: {meanExponent=-0.1923523558471011, negative=32, min=-1.856, max=1.912, mean=0.059375000000000025, count=64, sum=3.8000000000000016, positive=32, stdDev=1.1518728703181615, zeros=0}
Implemented Feedback: [ [ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, ... ], ... ]
Implemented Statistics: {meanExponent=0.0, negative=0, min=0.0, max=1.0, mean=0.0078125, count=8192, sum=64.0, positive=64, stdDev=0.08804240366863003, zeros=8128}
Measured Feedback: [ [ 1.0000169277191162, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 1.0001659393310547, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 1.0000169277191162, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 1.0001659393310547, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.9995698928833008, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.9989738464355469, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9999796748161316, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9989738464355469, ... ], ... ]
Measured Statistics: {meanExponent=-2.5341161319175753E-6, negative=0, min=0.0, max=1.0001659393310547, mean=0.00781245489633875, count=8192, sum=63.99963051080704, positive=64, stdDev=0.08804190085112014, zeros=8128}
Feedback Error: [ [ 1.6927719116210938E-5, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 1.659393310546875E-4, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 1.6927719116210938E-5, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 1.659393310546875E-4, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, -4.3010711669921875E-4, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -0.001026153564453125, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -2.0325183868408203E-5, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.001026153564453125, ... ], ... ]
Error Statistics: {meanExponent=-3.896697545952671, negative=15, min=-0.001026153564453125, max=1.659393310546875E-4, mean=-4.510366125032306E-8, count=8192, sum=-3.694891929626465E-4, positive=49, stdDev=3.1053281036829444E-5, zeros=8128}
Feedback for input 1
Inputs Values: [
[ [ -0.472 ], [ -0.316 ], [ -1.552 ], [ -1.484 ], [ -1.248 ], [ 0.56 ], [ -0.312 ], [ 0.812 ] ],
[ [ -0.504 ], [ 1.156 ], [ 0.016 ], [ 1.352 ], [ 1.324 ], [ -1.656 ], [ -0.968 ], [ -1.808 ] ],
[ [ -1.156 ], [ 0.972 ], [ 1.288 ], [ -0.888 ], [ 0.344 ], [ -0.856 ], [ -0.892 ], [ 0.644 ] ],
[ [ 0.184 ], [ -1.116 ], [ 1.628 ], [ -1.256 ], [ -1.34 ], [ -1.16 ], [ -0.808 ], [ 0.66 ] ],
[ [ 1.98 ], [ 0.52 ], [ -1.564 ], [ 1.916 ], [ 1.776 ], [ 0.688 ], [ -1.1 ], [ -1.76 ] ],
[ [ -0.628 ], [ -1.456 ], [ -1.764 ], [ -1.724 ], [ 0.52 ], [ -0.124 ], [ -0.968 ], [ 0.82 ] ],
[ [ -0.368 ], [ -2.0 ], [ 0.692 ], [ -1.664 ], [ 1.444 ], [ -1.176 ], [ -0.784 ], [ 1.24 ] ],
[ [ -1.16 ], [ 1.42 ], [ 1.628 ], [ 0.82 ], [ 1.956 ], [ -1.256 ], [ 0.012 ], [ -1.58 ] ]
]
Value Statistics: {meanExponent=-0.06999649029273047, negative=36, min=-2.0, max=1.98, mean=-0.19524999999999998, count=64, sum=-12.495999999999999, positive=28, stdDev=1.186466998066107, zeros=0}
Implemented Feedback: [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], ... ]
Implemented Statistics: {meanExponent=0.0, negative=0, min=0.0, max=1.0, mean=0.0078125, count=8192, sum=64.0, positive=64, stdDev=0.08804240366863003, zeros=8128}
Measured Feedback: [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], ... ]
Measured Statistics: {meanExponent=5.1583188577981597E-5, negative=0, min=0.0, max=1.0001659393310547, mean=0.007813428055669647, count=8192, sum=64.00760263204575, positive=64, stdDev=0.08805286315791443, zeros=8128}
Feedback Error: [ [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], ... ]
Error Statistics: {meanExponent=-3.8569204711317275, negative=7, min=-4.3010711669921875E-4, max=1.659393310546875E-4, mean=9.280556696467102E-7, count=8192, sum=0.00760263204574585, positive=57, stdDev=1.600271695318757E-5, zeros=8128}
Returns
{
"absoluteTol" : {
"count" : 16384,
"sum" : 0.02526378631591797,
"min" : 0.0,
"max" : 0.001026153564453125,
"sumOfSquare" : 1.0004533532281812E-5,
"standardDeviation" : 2.4662736418872343E-5,
"average" : 1.541979145258665E-6
},
"relativeTol" : {
"count" : 128,
"sum" : 0.012633058429989876,
"min" : 8.493669094728505E-7,
"max" : 5.133401651466836E-4,
"sumOfSquare" : 2.50274700006974E-6,
"standardDeviation" : 9.905481372777064E-5,
"average" : 9.869576898429591E-5
}
}
We validate the agreement between the implemented derivative of the internal weights apply finite difference estimations:
SingleDerivativeTester.java:133 executed in 0.00 seconds (0.000 gc):
return testLearning(
statistics,
component.addRef(),
RefUtil.addRef(inputPrototype),
outputPrototype.addRef());
},
outputPrototype.addRef(),
RefUtil.addRef(inputPrototype),
component.addRef()));
Returns
{
"absoluteTol" : {
"count" : 16384,
"sum" : 0.02526378631591797,
"min" : 0.0,
"max" : 0.001026153564453125,
"sumOfSquare" : 1.0004533532281812E-5,
"standardDeviation" : 2.4662736418872343E-5,
"average" : 1.541979145258665E-6
},
"relativeTol" : {
"count" : 128,
"sum" : 0.012633058429989876,
"min" : 8.493669094728505E-7,
"max" : 5.133401651466836E-4,
"sumOfSquare" : 2.50274700006974E-6,
"standardDeviation" : 9.905481372777064E-5,
"average" : 9.869576898429591E-5
}
}
The overall agreement accuracy between the implemented derivative and the finite difference estimations:
SingleDerivativeTester.java:148 executed in 0.00 seconds (0.000 gc):
//log.info(String.format("Component: %s\nInputs: %s\noutput=%s", component, Arrays.toStream(inputPrototype), outputPrototype));
log.info(RefString.format("Finite-Difference Derivative Accuracy:"));
log.info(RefString.format("absoluteTol: %s", statistics.absoluteTol));
log.info(RefString.format("relativeTol: %s", statistics.relativeTol));
Finite-Difference Derivative Accuracy:
absoluteTol: 1.5420e-06 +- 2.4663e-05 [0.0000e+00 - 1.0262e-03] (16384#)
relativeTol: 9.8696e-05 +- 9.9055e-05 [8.4937e-07 - 5.1334e-04] (128#)
SingleDerivativeTester.java:156 executed in 0.01 seconds (0.000 gc):
testFrozen(component.addRef(), RefUtil.addRef(inputPrototype));
testUnFrozen(component.addRef(), RefUtil.addRef(inputPrototype));
LayerTests.java:425 executed in 0.00 seconds (0.000 gc):
throwException(exceptions.addRef());
| class | details | result |
|---|---|---|
| com.simiacryptus.mindseye.test.unit.SingleDerivativeTester | ToleranceStatistics{absoluteTol=1.5420e-06 +- 2.4663e-05 [0.0000e+00 - 1.0262e-03] (16384#), relativeTol=9.8696e-05 +- 9.9055e-05 [8.4937e-07 - 5.1334e-04] (128#)} | OK |
{
"result": "OK",
"performance": {
"execution_time": "10.883",
"gc_time": "1.197"
},
"created_on": 1586739503639,
"file_name": "derivativeTest",
"report": {
"simpleName": "Float",
"canonicalName": "com.simiacryptus.mindseye.layers.cudnn.ImgConcatLayerTest.Float",
"link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/test/java/com/simiacryptus/mindseye/layers/cudnn/ImgConcatLayerTest.java",
"javaDoc": ""
},
"archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/cudnn/ImgConcatLayer/Float/derivativeTest/202004135823",
"id": "0146f690-801e-4882-b782-304442546c8d",
"report_type": "Components",
"display_name": "Derivative Validation",
"target": {
"simpleName": "ImgConcatLayer",
"canonicalName": "com.simiacryptus.mindseye.layers.cudnn.ImgConcatLayer",
"link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/main/java/com/simiacryptus/mindseye/layers/cudnn/ImgConcatLayer.java",
"javaDoc": ""
}
}