Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase
Using Seed 1539306380352348160
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 ], [ 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 ] ]
]
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}
Output: [
[ [ -0.29687499999999994 ] ]
]
Outputs Statistics: {meanExponent=-0.5274263730310583, negative=1, min=-0.29687499999999994, max=-0.29687499999999994, mean=-0.29687499999999994, count=1, sum=-0.29687499999999994, positive=0, stdDev=0.0, zeros=0}
We validate the agreement between the implemented derivative of the inputs apply finite difference estimations:
SingleDerivativeTester.java:117 executed in 0.19 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: [ [ -0.078125 ], [ -0.078125 ], [ -0.078125 ], [ -0.078125 ], [ -0.078125 ], [ -0.078125 ], [ -0.078125 ], [ -0.078125 ], ... ]
Implemented Statistics: {meanExponent=-1.1072099696478686, negative=64, min=-0.078125, max=-0.078125, mean=-0.078125, count=64, sum=-5.0, positive=0, stdDev=0.0, zeros=0}
Measured Feedback: [ [ -0.07812500000037303 ], [ -0.07812499999981792 ], [ -0.07812500000037303 ], [ -0.07812500000037303 ], [ -0.07812500000037303 ], [ -0.07812499999981792 ], [ -0.07812499999981792 ], [ -0.07812500000037303 ], ... ]
Measured Statistics: {meanExponent=-1.1072099696473368, negative=64, min=-0.07812500000037303, max=-0.07812499999981792, mean=-0.07812500000009548, count=64, sum=-5.000000000006111, positive=0, stdDev=2.2812650937430355E-9, zeros=0}
Feedback Error: [ [ -3.730349362740526E-13 ], [ 1.8207657603852567E-13 ], [ -3.730349362740526E-13 ], [ -3.730349362740526E-13 ], [ -3.730349362740526E-13 ], [ 1.8207657603852567E-13 ], [ 1.8207657603852567E-13 ], [ -3.730349362740526E-13 ], ... ]
Error Statistics: {meanExponent=-12.583998207472236, negative=32, min=-3.730349362740526E-13, max=1.8207657603852567E-13, mean=-9.547918011776346E-14, count=64, sum=-6.110667527536862E-12, positive=32, stdDev=2.7755575615628914E-13, zeros=0}
Returns
{
"absoluteTol" : {
"count" : 64,
"sum" : 1.7763568394002505E-11,
"min" : 1.8207657603852567E-13,
"max" : 3.730349362740526E-13,
"sumOfSquare" : 5.513822183132784E-24,
"standardDeviation" : 9.547918011776346E-14,
"average" : 2.7755575615628914E-13
},
"relativeTol" : {
"count" : 64,
"sum" : 1.1368683772147709E-10,
"min" : 1.1652900866479222E-12,
"max" : 2.387423592148237E-12,
"sumOfSquare" : 2.258461566203492E-22,
"standardDeviation" : 6.110667527501574E-13,
"average" : 1.7763568393980795E-12
}
}
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" : 64,
"sum" : 1.7763568394002505E-11,
"min" : 1.8207657603852567E-13,
"max" : 3.730349362740526E-13,
"sumOfSquare" : 5.513822183132784E-24,
"standardDeviation" : 9.547918011776346E-14,
"average" : 2.7755575615628914E-13
},
"relativeTol" : {
"count" : 64,
"sum" : 1.1368683772147709E-10,
"min" : 1.1652900866479222E-12,
"max" : 2.387423592148237E-12,
"sumOfSquare" : 2.258461566203492E-22,
"standardDeviation" : 6.110667527501574E-13,
"average" : 1.7763568393980795E-12
}
}
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: 2.7756e-13 +- 9.5479e-14 [1.8208e-13 - 3.7303e-13] (64#)
relativeTol: 1.7764e-12 +- 6.1107e-13 [1.1653e-12 - 2.3874e-12] (64#)
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=2.7756e-13 +- 9.5479e-14 [1.8208e-13 - 3.7303e-13] (64#), relativeTol=1.7764e-12 +- 6.1107e-13 [1.1653e-12 - 2.3874e-12] (64#)} | OK |
{
"result": "OK",
"performance": {
"execution_time": "0.380",
"gc_time": "0.133"
},
"created_on": 1586744929879,
"file_name": "derivativeTest",
"report": {
"simpleName": "Negative",
"canonicalName": "com.simiacryptus.mindseye.layers.cudnn.BandAvgReducerLayerTest.Negative",
"link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/test/java/com/simiacryptus/mindseye/layers/cudnn/BandAvgReducerLayerTest.java",
"javaDoc": ""
},
"archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/cudnn/BandAvgReducerLayer/Negative/derivativeTest/202004132849",
"id": "dfd6a279-b6ff-4a9c-ad63-d529c75ba57d",
"report_type": "Components",
"display_name": "Derivative Validation",
"target": {
"simpleName": "BandAvgReducerLayer",
"canonicalName": "com.simiacryptus.mindseye.layers.cudnn.BandAvgReducerLayer",
"link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/main/java/com/simiacryptus/mindseye/layers/cudnn/BandAvgReducerLayer.java",
"javaDoc": ""
}
}