Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase
Using Seed 1984966934382303232
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, -0.608, 1.208 ], [ -0.128, 0.048, -1.028 ] ],
[ [ 0.7, 1.764, -1.72 ], [ 0.496, 1.524, -0.384 ] ]
]
Inputs Statistics: {meanExponent=-0.3033810201823816, negative=5, min=-1.72, max=1.764, mean=0.16266666666666665, count=12, sum=1.952, positive=7, stdDev=0.9945442283891763, zeros=0}
Output: [
[ [ 0.08, 1.208 ], [ -0.128, -1.028 ] ],
[ [ 0.7, -1.72 ], [ 0.496, -0.384 ] ]
]
Outputs Statistics: {meanExponent=-0.31690007582953555, negative=4, min=-1.72, max=1.208, mean=-0.09700000000000002, count=8, sum=-0.7760000000000001, positive=4, stdDev=0.8877944581940124, zeros=0}
We validate the agreement between the implemented derivative of the inputs apply finite difference estimations:
SingleDerivativeTester.java:117 executed in 0.03 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, -0.608, 1.208 ], [ -0.128, 0.048, -1.028 ] ],
[ [ 0.7, 1.764, -1.72 ], [ 0.496, 1.524, -0.384 ] ]
]
Value Statistics: {meanExponent=-0.3033810201823816, negative=5, min=-1.72, max=1.764, mean=0.16266666666666665, count=12, sum=1.952, positive=7, stdDev=0.9945442283891763, 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, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 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=0.08333333333333333, count=96, sum=8.0, positive=8, stdDev=0.2763853991962833, zeros=88}
Measured Feedback: [ [ 1.0000000000000286, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.9999999999998899, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.9999999999998899, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.9999999999998899, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 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=-4.029683400859781E-14, negative=0, min=0.0, max=1.0000000000000286, mean=0.0833333333333256, count=96, sum=7.9999999999992575, positive=8, stdDev=0.27638539919625765, zeros=88}
Feedback Error: [ [ 2.864375403532904E-14, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, -1.1013412404281553E-13, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, -1.1013412404281553E-13, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, -1.1013412404281553E-13, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0, 0.0, 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=-13.031189593810693, negative=7, min=-1.1013412404281553E-13, max=2.864375403532904E-14, mean=-7.732240773587288E-15, count=96, sum=-7.422951142643797E-13, positive=1, stdDev=2.8865264781580964E-14, zeros=88}
Returns
{
"absoluteTol" : {
"count" : 96,
"sum" : 7.995826223350377E-13,
"min" : 0.0,
"max" : 1.1013412404281553E-13,
"sumOfSquare" : 8.572714159598437E-26,
"standardDeviation" : 2.869876402120604E-14,
"average" : 8.32898564932331E-15
},
"relativeTol" : {
"count" : 8,
"sum" : 3.997913111675399E-13,
"min" : 1.4321877017664317E-14,
"max" : 5.50670620214108E-14,
"sumOfSquare" : 2.143178539899843E-26,
"standardDeviation" : 1.347520333040395E-14,
"average" : 4.997391389594249E-14
}
}
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" : 96,
"sum" : 7.995826223350377E-13,
"min" : 0.0,
"max" : 1.1013412404281553E-13,
"sumOfSquare" : 8.572714159598437E-26,
"standardDeviation" : 2.869876402120604E-14,
"average" : 8.32898564932331E-15
},
"relativeTol" : {
"count" : 8,
"sum" : 3.997913111675399E-13,
"min" : 1.4321877017664317E-14,
"max" : 5.50670620214108E-14,
"sumOfSquare" : 2.143178539899843E-26,
"standardDeviation" : 1.347520333040395E-14,
"average" : 4.997391389594249E-14
}
}
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: 8.3290e-15 +- 2.8699e-14 [0.0000e+00 - 1.1013e-13] (96#)
relativeTol: 4.9974e-14 +- 1.3475e-14 [1.4322e-14 - 5.5067e-14] (8#)
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=8.3290e-15 +- 2.8699e-14 [0.0000e+00 - 1.1013e-13] (96#), relativeTol=4.9974e-14 +- 1.3475e-14 [1.4322e-14 - 5.5067e-14] (8#)} | OK |
{
"result": "OK",
"performance": {
"execution_time": "0.176",
"gc_time": "0.104"
},
"created_on": 1586735418175,
"file_name": "derivativeTest",
"report": {
"simpleName": "Basic",
"canonicalName": "com.simiacryptus.mindseye.layers.java.ImgBandSelectLayerTest.Basic",
"link": "https://github.com/SimiaCryptus/mindseye-java/tree/93db34cedee48c0202777a2b25deddf1dfaf5731/src/test/java/com/simiacryptus/mindseye/layers/java/ImgBandSelectLayerTest.java",
"javaDoc": ""
},
"archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/java/ImgBandSelectLayer/Basic/derivativeTest/202004125018",
"id": "a6bf1a49-50fd-45fd-ade8-2d5fc91137c0",
"report_type": "Components",
"display_name": "Derivative Validation",
"target": {
"simpleName": "ImgBandSelectLayer",
"canonicalName": "com.simiacryptus.mindseye.layers.java.ImgBandSelectLayer",
"link": "https://github.com/SimiaCryptus/mindseye-java/tree/93db34cedee48c0202777a2b25deddf1dfaf5731/src/main/java/com/simiacryptus/mindseye/layers/java/ImgBandSelectLayer.java",
"javaDoc": ""
}
}