Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase
Using Seed 1813421203597677568
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 ] ],
[ [ 0.7 ], [ -1.72 ], [ 0.028 ], [ 0.3 ], [ 1.64 ], [ 1.876 ] ],
[ [ -0.128 ], [ -1.028 ], [ -0.712 ], [ 0.636 ], [ 0.392 ], [ -0.408 ] ],
[ [ 0.496 ], [ -0.384 ], [ 1.048 ], [ -0.176 ], [ 0.092 ], [ -0.384 ] ],
[ [ -0.608 ], [ -0.852 ], [ -1.616 ], [ 1.556 ], [ -0.556 ], [ -1.572 ] ],
[ [ 1.764 ], [ 1.912 ], [ 1.356 ], [ 0.788 ], [ -1.476 ], [ -1.516 ] ],
[ [ 0.048 ], [ -1.688 ], [ 1.512 ], [ -0.768 ], [ 1.704 ], [ -0.636 ] ],
[ [ 1.524 ], [ -0.804 ], [ 1.556 ], [ -0.068 ], [ -1.228 ], [ -1.492 ] ]
]
Inputs Statistics: {meanExponent=-0.15927984553930932, negative=22, min=-1.72, max=1.912, mean=0.1604166666666667, count=48, sum=7.700000000000002, positive=26, stdDev=1.1368718015042663, zeros=0}
Output: [
[ [ -0.608 ], [ -0.852 ], [ -1.616 ] ],
[ [ 1.764 ], [ 1.912 ], [ 1.356 ] ],
[ [ 0.048 ], [ -1.688 ], [ 1.512 ] ],
[ [ 1.524 ], [ -0.804 ], [ 1.556 ] ]
]
Outputs Statistics: {meanExponent=-0.004046102668246375, negative=5, min=-1.688, max=1.912, mean=0.3420000000000001, count=12, sum=4.104000000000001, positive=7, stdDev=1.336586198741655, zeros=0}
We validate the agreement between the implemented derivative of the inputs apply finite difference estimations:
SingleDerivativeTester.java:117 executed in 0.54 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 ] ],
[ [ 0.7 ], [ -1.72 ], [ 0.028 ], [ 0.3 ], [ 1.64 ], [ 1.876 ] ],
[ [ -0.128 ], [ -1.028 ], [ -0.712 ], [ 0.636 ], [ 0.392 ], [ -0.408 ] ],
[ [ 0.496 ], [ -0.384 ], [ 1.048 ], [ -0.176 ], [ 0.092 ], [ -0.384 ] ],
[ [ -0.608 ], [ -0.852 ], [ -1.616 ], [ 1.556 ], [ -0.556 ], [ -1.572 ] ],
[ [ 1.764 ], [ 1.912 ], [ 1.356 ], [ 0.788 ], [ -1.476 ], [ -1.516 ] ],
[ [ 0.048 ], [ -1.688 ], [ 1.512 ], [ -0.768 ], [ 1.704 ], [ -0.636 ] ],
[ [ 1.524 ], [ -0.804 ], [ 1.556 ], [ -0.068 ], [ -1.228 ], [ -1.492 ] ]
]
Value Statistics: {meanExponent=-0.15927984553930932, negative=22, min=-1.72, max=1.912, mean=0.1604166666666667, count=48, sum=7.700000000000002, positive=26, stdDev=1.1368718015042663, 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, ... ], [ 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, ... ], ... ]
Implemented Statistics: {meanExponent=0.0, negative=0, min=0.0, max=1.0, mean=0.020833333333333332, count=576, sum=12.0, positive=12, stdDev=0.1428261375083551, zeros=564}
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, ... ], [ 0.9999999999998899, 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, 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, ... ], ... ]
Measured Statistics: {meanExponent=-4.28081034527471E-14, negative=0, min=0.0, max=1.0000000000000286, mean=0.020833333333331278, count=576, sum=11.999999999998817, positive=12, stdDev=0.142826137508341, zeros=564}
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, ... ], [ -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, 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, ... ], ... ]
Error Statistics: {meanExponent=-13.006819095219404, negative=11, min=-1.1013412404281553E-13, max=2.864375403532904E-14, mean=-2.053527101450767E-15, count=576, sum=-1.1828316104356418E-12, positive=1, stdDev=1.5127712448597675E-14, zeros=564}
Returns
{
"absoluteTol" : {
"count" : 576,
"sum" : 1.2401191185062999E-12,
"min" : 0.0,
"max" : 1.1013412404281553E-13,
"sumOfSquare" : 1.3424524271069748E-25,
"standardDeviation" : 1.511387822099097E-14,
"average" : 2.152984580740104E-15
},
"relativeTol" : {
"count" : 12,
"sum" : 6.200595592531831E-13,
"min" : 1.4321877017664317E-14,
"max" : 5.50670620214108E-14,
"sumOfSquare" : 3.3561310677678044E-26,
"standardDeviation" : 1.1261374222586905E-14,
"average" : 5.167162993776526E-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" : 576,
"sum" : 1.2401191185062999E-12,
"min" : 0.0,
"max" : 1.1013412404281553E-13,
"sumOfSquare" : 1.3424524271069748E-25,
"standardDeviation" : 1.511387822099097E-14,
"average" : 2.152984580740104E-15
},
"relativeTol" : {
"count" : 12,
"sum" : 6.200595592531831E-13,
"min" : 1.4321877017664317E-14,
"max" : 5.50670620214108E-14,
"sumOfSquare" : 3.3561310677678044E-26,
"standardDeviation" : 1.1261374222586905E-14,
"average" : 5.167162993776526E-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: 2.1530e-15 +- 1.5114e-14 [0.0000e+00 - 1.1013e-13] (576#)
relativeTol: 5.1672e-14 +- 1.1261e-14 [1.4322e-14 - 5.5067e-14] (12#)
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=2.1530e-15 +- 1.5114e-14 [0.0000e+00 - 1.1013e-13] (576#), relativeTol=5.1672e-14 +- 1.1261e-14 [1.4322e-14 - 5.5067e-14] (12#)} | OK |
{
"result": "OK",
"performance": {
"execution_time": "0.765",
"gc_time": "0.144"
},
"created_on": 1586736502000,
"file_name": "derivativeTest",
"report": {
"simpleName": "LL",
"canonicalName": "com.simiacryptus.mindseye.layers.cudnn.ImgTileSelectLayerTest.LL",
"link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/test/java/com/simiacryptus/mindseye/layers/cudnn/ImgTileSelectLayerTest.java",
"javaDoc": ""
},
"archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/cudnn/ImgTileSelectLayer/LL/derivativeTest/202004130821",
"id": "01768efb-275b-4e32-b8f9-768acf408549",
"report_type": "Components",
"display_name": "Derivative Validation",
"target": {
"simpleName": "ImgTileSelectLayer",
"canonicalName": "com.simiacryptus.mindseye.layers.cudnn.ImgTileSelectLayer",
"link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/main/java/com/simiacryptus/mindseye/layers/cudnn/ImgTileSelectLayer.java",
"javaDoc": ""
}
}