Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase
Using Seed 1217544545040531456
SingleDerivativeTester.java:101 executed in 0.00 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 ], [ -0.128 ], [ -0.608 ] ],
[ [ 0.7 ], [ 0.496 ], [ 1.764 ] ]
]
Inputs Statistics: {meanExponent=-0.403119694464533, negative=2, min=-0.608, max=1.764, mean=0.38399999999999995, count=6, sum=2.304, positive=4, stdDev=0.747821725636086, zeros=0}
Output: [
[ [ 0.3976677055116089 ], [ 0.39568749504326983 ], [ 0.33161834545386687 ] ],
[ [ 0.31225393336676127 ], [ 0.35276733986812936 ], [ 0.08418095817883484 ] ]
]
Outputs Statistics: {meanExponent=-0.5525464417112985, negative=0, min=0.08418095817883484, max=0.3976677055116089, mean=0.3123626295704119, count=6, sum=1.8741757774224712, positive=6, stdDev=0.10668505000682163, zeros=0}
We validate the agreement between the implemented derivative of the inputs apply finite difference estimations:
SingleDerivativeTester.java:117 executed in 0.02 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 ], [ -0.128 ], [ -0.608 ] ],
[ [ 0.7 ], [ 0.496 ], [ 1.764 ] ]
]
Value Statistics: {meanExponent=-0.403119694464533, negative=2, min=-0.608, max=1.764, mean=0.38399999999999995, count=6, sum=2.304, positive=4, stdDev=0.747821725636086, zeros=0}
Implemented Feedback: [ [ -0.031813416440928714, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, -0.2185777533567329, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.050647999365538536, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, -0.17497260057459216, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.20162395403595104, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -0.14849521022746467 ] ]
Implemented Statistics: {meanExponent=-0.9556661361758314, negative=4, min=-0.2185777533567329, max=0.20162395403595104, mean=-0.008932972977728581, count=36, sum=-0.3215870271982289, positive=2, stdDev=0.06276040785694621, zeros=30}
Measured Feedback: [ [ -0.03183317241362005, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, -0.2185857149172854, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.05062853888626595, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, -0.1749858988181474, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.20161350160252667, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -0.1484863220253818 ] ]
Measured Statistics: {meanExponent=-0.9556489655000249, negative=4, min=-0.2185857149172854, max=0.20161350160252667, mean=-0.008934696324601168, count=36, sum=-0.32164906768564205, positive=2, stdDev=0.06276028788638831, zeros=30}
Feedback Error: [ [ -1.97559726913335E-5, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, -7.961560552494085E-6, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, -1.9460479272585818E-5, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, -1.3298243555254219E-5, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, -1.0452433424373853E-5, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 8.888202082862895E-6 ] ]
Error Statistics: {meanExponent=-4.903720705913417, negative=5, min=-1.97559726913335E-5, max=8.888202082862895E-6, mean=-1.7233468725882939E-6, count=36, sum=-6.204048741317858E-5, positive=1, stdDev=5.503974976184558E-6, zeros=30}
Returns
{
"absoluteTol" : {
"count" : 36,
"sum" : 7.981689157890437E-5,
"min" : 0.0,
"max" : 1.97559726913335E-5,
"sumOfSquare" : 1.1974919393421235E-9,
"standardDeviation" : 5.324281499300601E-6,
"average" : 2.217135877191788E-6
},
"relativeTol" : {
"count" : 6,
"sum" : 6.146141259686149E-4,
"min" : 1.821186153529119E-5,
"max" : 3.104011235618884E-4,
"sumOfSquare" : 1.3661446942741475E-7,
"standardDeviation" : 1.1079714856994842E-4,
"average" : 1.0243568766143581E-4
}
}
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" : 36,
"sum" : 7.981689157890437E-5,
"min" : 0.0,
"max" : 1.97559726913335E-5,
"sumOfSquare" : 1.1974919393421235E-9,
"standardDeviation" : 5.324281499300601E-6,
"average" : 2.217135877191788E-6
},
"relativeTol" : {
"count" : 6,
"sum" : 6.146141259686149E-4,
"min" : 1.821186153529119E-5,
"max" : 3.104011235618884E-4,
"sumOfSquare" : 1.3661446942741475E-7,
"standardDeviation" : 1.1079714856994842E-4,
"average" : 1.0243568766143581E-4
}
}
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: 2.2171e-06 +- 5.3243e-06 [0.0000e+00 - 1.9756e-05] (36#)
relativeTol: 1.0244e-04 +- 1.1080e-04 [1.8212e-05 - 3.1040e-04] (6#)
SingleDerivativeTester.java:156 executed in 0.00 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=2.2171e-06 +- 5.3243e-06 [0.0000e+00 - 1.9756e-05] (36#), relativeTol=1.0244e-04 +- 1.1080e-04 [1.8212e-05 - 3.1040e-04] (6#)} | OK |
{
"result": "OK",
"performance": {
"execution_time": "0.185",
"gc_time": "0.128"
},
"created_on": 1586738474825,
"file_name": "derivativeTest",
"report": {
"simpleName": "Basic",
"canonicalName": "com.simiacryptus.mindseye.layers.java.GaussianActivationLayerTest.Basic",
"link": "https://github.com/SimiaCryptus/mindseye-java/tree/93db34cedee48c0202777a2b25deddf1dfaf5731/src/test/java/com/simiacryptus/mindseye/layers/java/GaussianActivationLayerTest.java",
"javaDoc": ""
},
"archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/java/GaussianActivationLayer/Basic/derivativeTest/202004134114",
"id": "42881483-b5bf-4357-9892-b9d41f2e065e",
"report_type": "Components",
"display_name": "Derivative Validation",
"target": {
"simpleName": "GaussianActivationLayer",
"canonicalName": "com.simiacryptus.mindseye.layers.java.GaussianActivationLayer",
"link": "https://github.com/SimiaCryptus/mindseye-java/tree/93db34cedee48c0202777a2b25deddf1dfaf5731/src/main/java/com/simiacryptus/mindseye/layers/java/GaussianActivationLayer.java",
"javaDoc": ""
}
}