1. Test Modules
  2. Differential Validation
    1. Feedback Validation
    2. Learning Validation
    3. Total Accuracy
    4. Frozen and Alive Status
  3. Results

Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase

Test Modules

Using Seed 1562023153226053632

Differential Validation

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)));
Logging 
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 ] ]
],
[
[ [ -0.472 ], [ -0.316 ], [ -1.552 ], [ -1.484 ], [ -1.248 ], [ 0.56 ], [ -0.312 ], [ 0.812 ] ],
[ [ -0.504 ], [ 1.156 ], [ 0.016 ], [ 1.352 ], [ 1.324 ], [ -1.656 ], [ -0.968 ], [ -1.808 ] ],
[ [ -1.156 ], [ 0.972 ], [ 1.288 ], [ -0.888 ], [ 0.344 ], [ -0.856 ], [ -0.892 ], [ 0.644 ] ],
[ [ 0.184 ], [ -1.116 ], [ 1.628 ], [ -1.256 ], [ -1.34 ], [ -1.16 ], [ -0.808 ], [ 0.66 ] ],
[ [ 1.98 ], [ 0.52 ], [ -1.564 ], [ 1.916 ], [ 1.776 ], [ 0.688 ], [ -1.1 ], [ -1.76 ] ],
[ [ -0.628 ], [ -1.456 ], [ -1.764 ], [ -1.724 ], [ 0.52 ], [ -0.124 ], [ -0.968 ], [ 0.82 ] ],
[ [ -0.368 ], [ -2.0 ], [ 0.692 ], [ -1.664 ], [ 1.444 ], [ -1.176 ], [ -0.784 ], [ 1.24 ] ],
[ [ -1.16 ], [ 1.42 ], [ 1.628 ], [ 0.82 ], [ 1.956 ], [ -1.256 ], [ 0.012 ], [ -1.58 ] ]
]
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},
{meanExponent=-0.06999649029273047, negative=36, min=-2.0, max=1.98, mean=-0.19524999999999998, count=64, sum=-12.495999999999999, positive=28, stdDev=1.186466998066107, zeros=0}
Output: [
[ [ -0.03776000067591667 ], [ -0.38172799348831177 ], [ -1.7196160554885864 ], [ -1.5314879417419434 ], [ -2.0117759704589844 ], [ 0.8691200017929077 ], [ 0.25084802508354187 ], [ -1.4875839948654175 ] ],
[ [ -0.35280001163482666 ], [ -1.9883201122283936 ], [ 4.480000352486968E-4 ], [ 0.40560001134872437 ], [ 2.1713600158691406 ], [ -3.106656074523926 ], [ -0.14326399564743042 ], [ -2.473344087600708 ] ],
[ [ 0.14796800911426544 ], [ -0.9992160201072693 ], [ -0.9170560240745544 ], [ -0.5647680163383484 ], [ 0.1348479986190796 ], [ 0.3492479920387268 ], [ 0.028544001281261444 ], [ -0.9917599558830261 ] ],
[ [ 0.09126400202512741 ], [ 0.4285440146923065 ], [ 1.7061439752578735 ], [ 0.2210559993982315 ], [ -0.12328000366687775 ], [ 0.44543999433517456 ], [ 0.720736026763916 ], [ -0.5781599879264832 ] ],
[ [ -1.2038400173187256 ], [ -0.44303998351097107 ], [ 2.5274240970611572 ], [ 2.9812960624694824 ], [ -0.9874560236930847 ], [ -1.081536054611206 ], [ -1.7820000648498535 ], [ -2.907519817352295 ] ],
[ [ -1.1077920198440552 ], [ -2.78387188911438 ], [ -2.391983985900879 ], [ -1.3585119247436523 ], [ -0.7675199508666992 ], [ 0.18798400461673737 ], [ 1.7966079711914062 ], [ -1.167680025100708 ] ],
[ [ -0.017664000391960144 ], [ 3.375999927520752 ], [ 1.0463039875030518 ], [ 1.2779520750045776 ], [ 2.460576057434082 ], [ 0.747935950756073 ], [ -0.7808640003204346 ], [ -0.5753600001335144 ] ],
[ [ -1.767840027809143 ], [ -1.1416800022125244 ], [ 2.533168077468872 ], [ -0.05576000362634659 ], [ -2.401968002319336 ], [ 1.873952031135559 ], [ 5.760000203736126E-4 ], [ 0.018960000947117805 ] ]
]
Outputs Statistics: {meanExponent=-0.26234884154316984, negative=36, min=-3.106656074523926, max=3.375999927520752, mean=-0.2395712457700938, count=64, sum=-15.332559729286004, positive=28, stdDev=1.4544719527005288, zeros=0}

Feedback Validation

We validate the agreement between the implemented derivative of the inputs apply finite difference estimations:

SingleDerivativeTester.java:117 executed in 3.94 seconds (0.000 gc):

        return testFeedback(
            statistics,
            component.addRef(),
            RefUtil.addRef(inputPrototype),
            outputPrototype.addRef());
      },
      outputPrototype.addRef(),
      RefUtil.addRef(inputPrototype),
      component.addRef()));
Logging 
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: [ [ -0.47200000286102295, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, -0.5040000081062317, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -1.156000018119812, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.18400000035762787, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 1.9800000190734863, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -0.628000020980835, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.36800000071525574, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.159999966621399, ... ], ... ]
Implemented Statistics: {meanExponent=-0.06999648780438449, negative=36, min=-2.0, max=1.9800000190734863, mean=-0.003050781334422936, count=4096, sum=-12.496000345796347, positive=28, stdDev=0.15027219307950793, zeros=4032}
Measured Feedback: [ [ -0.471998006105423, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, -0.5039870738983154, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -1.1560022830963135, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.18399953842163086, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 1.9800662994384766, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -0.6279945373535156, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.3679990768432617, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.1599063873291016, ... ], ... ]
Measured Statistics: {meanExponent=-0.06999518944814881, negative=36, min=-1.9998550415039062, max=1.9800662994384766, mean=-0.0030506483383874183, count=4096, sum=-12.495455594034865, positive=28, stdDev=0.15027163187700082, zeros=4032}
Feedback Error: [ [ 1.996755599975586E-6, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 1.2934207916259766E-5, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -2.2649765014648438E-6, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, -4.6193599700927734E-7, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 6.628036499023438E-5, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 5.4836273193359375E-6, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 9.238719940185547E-7, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 9.357929229736328E-5, ... ], ... ]
Error Statistics: {meanExponent=-4.836471682285403, negative=34, min=-2.4437904357910156E-4, max=3.103017807006836E-4, mean=1.3299603551786277E-7, count=4096, sum=5.447517614811659E-4, positive=30, stdDev=9.042126198565733E-6, zeros=4032}
Feedback for input 1
Inputs Values: [
[ [ -0.472 ], [ -0.316 ], [ -1.552 ], [ -1.484 ], [ -1.248 ], [ 0.56 ], [ -0.312 ], [ 0.812 ] ],
[ [ -0.504 ], [ 1.156 ], [ 0.016 ], [ 1.352 ], [ 1.324 ], [ -1.656 ], [ -0.968 ], [ -1.808 ] ],
[ [ -1.156 ], [ 0.972 ], [ 1.288 ], [ -0.888 ], [ 0.344 ], [ -0.856 ], [ -0.892 ], [ 0.644 ] ],
[ [ 0.184 ], [ -1.116 ], [ 1.628 ], [ -1.256 ], [ -1.34 ], [ -1.16 ], [ -0.808 ], [ 0.66 ] ],
[ [ 1.98 ], [ 0.52 ], [ -1.564 ], [ 1.916 ], [ 1.776 ], [ 0.688 ], [ -1.1 ], [ -1.76 ] ],
[ [ -0.628 ], [ -1.456 ], [ -1.764 ], [ -1.724 ], [ 0.52 ], [ -0.124 ], [ -0.968 ], [ 0.82 ] ],
[ [ -0.368 ], [ -2.0 ], [ 0.692 ], [ -1.664 ], [ 1.444 ], [ -1.176 ], [ -0.784 ], [ 1.24 ] ],
[ [ -1.16 ], [ 1.42 ], [ 1.628 ], [ 0.82 ], [ 1.956 ], [ -1.256 ], [ 0.012 ], [ -1.58 ] ]
]
Value Statistics: {meanExponent=-0.06999649029273047, negative=36, min=-2.0, max=1.98, mean=-0.19524999999999998, count=64, sum=-12.495999999999999, positive=28, stdDev=1.186466998066107, zeros=0}
Implemented Feedback: [ [ 0.07999999821186066, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.699999988079071, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -0.12800000607967377, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.4959999918937683, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, -0.6079999804496765, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 1.7640000581741333, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.04800000041723251, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.5240000486373901, ... ], ... ]
Implemented Statistics: {meanExponent=-0.19235235563472564, negative=32, min=-1.8559999465942383, max=1.9119999408721924, mean=9.277343256144377E-4, count=4096, sum=3.799999797716737, positive=32, stdDev=0.1441722826130822, zeros=4032}
Measured Feedback: [ [ 0.08000433444976807, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.6999969482421875, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -0.12800097465515137, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.4960000514984131, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, -0.6079673767089844, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 1.764059066772461, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.04800036549568176, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.5238523483276367, ... ], ... ]
Measured Statistics: {meanExponent=-0.1923504649580869, negative=32, min=-1.8559694290161133, max=1.9118785858154297, mean=9.276878714103987E-4, count=4096, sum=3.799809521296993, positive=32, stdDev=0.14417224840738088, zeros=4032}
Feedback Error: [ [ 4.336237907409668E-6, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, -3.039836883544922E-6, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -9.685754776000977E-7, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 5.9604644775390625E-8, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 3.260374069213867E-5, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 5.900859832763672E-5, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.650784492492676E-7, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.4770030975341797E-4, ... ], ... ]
Error Statistics: {meanExponent=-4.947006995393151, negative=35, min=-1.4770030975341797E-4, max=1.6760826110839844E-4, mean=-4.6454204039036995E-8, count=4096, sum=-1.9027641974389553E-4, positive=29, stdDev=6.862347153223654E-6, zeros=4032}

Returns

    {
      "absoluteTol" : {
        "count" : 8192,
        "sum" : 0.005091381724923849,
        "min" : 0.0,
        "max" : 3.103017807006836E-4,
        "sumOfSquare" : 5.278584855784732E-7,
        "standardDeviation" : 8.003098143121367E-6,
        "average" : 6.215065582182433E-7
      },
      "relativeTol" : {
        "count" : 128,
        "sum" : 0.0023970998136343073,
        "min" : 3.772445911707941E-8,
        "max" : 9.251678408027462E-5,
        "sumOfSquare" : 8.889951975926876E-8,
        "standardDeviation" : 1.8542226099418884E-5,
        "average" : 1.8727342294018025E-5
      }
    }

Learning Validation

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" : 8192,
        "sum" : 0.005091381724923849,
        "min" : 0.0,
        "max" : 3.103017807006836E-4,
        "sumOfSquare" : 5.278584855784732E-7,
        "standardDeviation" : 8.003098143121367E-6,
        "average" : 6.215065582182433E-7
      },
      "relativeTol" : {
        "count" : 128,
        "sum" : 0.0023970998136343073,
        "min" : 3.772445911707941E-8,
        "max" : 9.251678408027462E-5,
        "sumOfSquare" : 8.889951975926876E-8,
        "standardDeviation" : 1.8542226099418884E-5,
        "average" : 1.8727342294018025E-5
      }
    }

Total Accuracy

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));
Logging 
Finite-Difference Derivative Accuracy:
absoluteTol: 6.2151e-07 +- 8.0031e-06 [0.0000e+00 - 3.1030e-04] (8192#)
relativeTol: 1.8727e-05 +- 1.8542e-05 [3.7724e-08 - 9.2517e-05] (128#)

Frozen and Alive Status

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());

Results

classdetailsresult
com.simiacryptus.mindseye.test.unit.SingleDerivativeTesterToleranceStatistics{absoluteTol=6.2151e-07 +- 8.0031e-06 [0.0000e+00 - 3.1030e-04] (8192#), relativeTol=1.8727e-05 +- 1.8542e-05 [3.7724e-08 - 9.2517e-05] (128#)}OK
 
  {
    "result": "OK",
    "performance": {
      "execution_time": "4.494",
      "gc_time": "0.485"
    },
    "created_on": 1586737770774,
    "file_name": "derivativeTest",
    "report": {
      "simpleName": "Float",
      "canonicalName": "com.simiacryptus.mindseye.layers.cudnn.NProductLayerTest.Float",
      "link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/test/java/com/simiacryptus/mindseye/layers/cudnn/NProductLayerTest.java",
      "javaDoc": ""
    },
    "archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/cudnn/NProductLayer/Float/derivativeTest/202004132930",
    "id": "06020eb7-1e24-4afc-a313-8b788d6f45d6",
    "report_type": "Components",
    "display_name": "Derivative Validation",
    "target": {
      "simpleName": "NProductLayer",
      "canonicalName": "com.simiacryptus.mindseye.layers.cudnn.NProductLayer",
      "link": "https://github.com/SimiaCryptus/mindseye-cudnn/tree/59d5b3318556370acb2d83ee6ec123ce0fc6974f/src/main/java/com/simiacryptus/mindseye/layers/cudnn/NProductLayer.java",
      "javaDoc": ""
    }
  }