Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase
Using Seed 4372795770432974848
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, 0.7, -0.128 ]
Inputs Statistics: {meanExponent=-0.7148673344486438, negative=1, min=-0.128, max=0.7, mean=0.2173333333333333, count=3, sum=0.6519999999999999, positive=2, stdDev=0.3517018939701949, zeros=0}
Output: [ 0.08, 0.7, -0.128 ]
Outputs Statistics: {meanExponent=-0.7148673344486438, negative=1, min=-0.128, max=0.7, mean=0.2173333333333333, count=3, sum=0.6519999999999999, positive=2, stdDev=0.3517018939701949, 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, 0.7, -0.128 ]
Value Statistics: {meanExponent=-0.7148673344486438, negative=1, min=-0.128, max=0.7, mean=0.2173333333333333, count=3, sum=0.6519999999999999, positive=2, stdDev=0.3517018939701949, zeros=0}
Implemented Feedback: [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ]
Implemented Statistics: {meanExponent=0.0, negative=0, min=0.0, max=1.0, mean=0.3333333333333333, count=9, sum=3.0, positive=3, stdDev=0.4714045207910317, zeros=6}
Measured Feedback: [ [ 1.0000000000000286, 0.0, 0.0 ], [ 0.0, 0.9999999999998899, 0.0 ], [ 0.0, 0.0, 0.9999999999998899 ] ]
Measured Statistics: {meanExponent=-2.7740486787851373E-14, negative=0, min=0.0, max=1.0000000000000286, mean=0.333333333333312, count=9, sum=2.999999999999808, positive=3, stdDev=0.4714045207910016, zeros=6}
Feedback Error: [ [ 2.864375403532904E-14, 0.0, 0.0 ], [ 0.0, -1.1013412404281553E-13, 0.0 ], [ 0.0, 0.0, -1.1013412404281553E-13 ] ]
Error Statistics: {meanExponent=-13.153042086767142, negative=2, min=-1.1013412404281553E-13, max=2.864375403532904E-14, mean=-2.1291610450033557E-14, count=9, sum=-1.9162449405030202E-13, positive=1, stdDev=4.8304038389477654E-14, zeros=6}
Returns
{
"absoluteTol" : {
"count" : 9,
"sum" : 2.489120021209601E-13,
"min" : 0.0,
"max" : 1.1013412404281553E-13,
"sumOfSquare" : 2.5079515202592984E-26,
"standardDeviation" : 4.4963421625143194E-14,
"average" : 2.7656889124551122E-14
},
"relativeTol" : {
"count" : 3,
"sum" : 1.244560010604859E-13,
"min" : 1.4321877017664317E-14,
"max" : 5.50670620214108E-14,
"sumOfSquare" : 6.269878800648909E-27,
"standardDeviation" : 1.920746441123305E-14,
"average" : 4.1485333686828635E-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" : 9,
"sum" : 2.489120021209601E-13,
"min" : 0.0,
"max" : 1.1013412404281553E-13,
"sumOfSquare" : 2.5079515202592984E-26,
"standardDeviation" : 4.4963421625143194E-14,
"average" : 2.7656889124551122E-14
},
"relativeTol" : {
"count" : 3,
"sum" : 1.244560010604859E-13,
"min" : 1.4321877017664317E-14,
"max" : 5.50670620214108E-14,
"sumOfSquare" : 6.269878800648909E-27,
"standardDeviation" : 1.920746441123305E-14,
"average" : 4.1485333686828635E-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: 2.7657e-14 +- 4.4963e-14 [0.0000e+00 - 1.1013e-13] (9#)
relativeTol: 4.1485e-14 +- 1.9207e-14 [1.4322e-14 - 5.5067e-14] (3#)
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=2.7657e-14 +- 4.4963e-14 [0.0000e+00 - 1.1013e-13] (9#), relativeTol=4.1485e-14 +- 1.9207e-14 [1.4322e-14 - 5.5067e-14] (3#)} | OK |
{
"result": "OK",
"performance": {
"execution_time": "0.172",
"gc_time": "0.114"
},
"created_on": 1586738106452,
"file_name": "derivativeTest",
"report": {
"simpleName": "Basic",
"canonicalName": "com.simiacryptus.mindseye.layers.java.MonitoringSynapseTest.Basic",
"link": "https://github.com/SimiaCryptus/mindseye-java/tree/93db34cedee48c0202777a2b25deddf1dfaf5731/src/test/java/com/simiacryptus/mindseye/layers/java/MonitoringSynapseTest.java",
"javaDoc": ""
},
"archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/java/MonitoringSynapse/Basic/derivativeTest/202004133506",
"id": "164ca1d1-02ab-4d5f-aba4-83c694ddd859",
"report_type": "Components",
"display_name": "Derivative Validation",
"target": {
"simpleName": "MonitoringSynapse",
"canonicalName": "com.simiacryptus.mindseye.layers.java.MonitoringSynapse",
"link": "https://github.com/SimiaCryptus/mindseye-java/tree/93db34cedee48c0202777a2b25deddf1dfaf5731/src/main/java/com/simiacryptus/mindseye/layers/java/MonitoringSynapse.java",
"javaDoc": ""
}
}