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 7673347839296751616

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: [
[ [ -0.03776 ], [ -0.381728 ], [ -1.7196160000000003 ], [ -1.531488 ], [ -2.0117760000000002 ], [ 0.8691200000000001 ], [ 0.250848 ], [ -1.4875840000000002 ] ],
[ [ -0.3528 ], [ -1.9883199999999999 ], [ 4.48E-4 ], [ 0.4056 ], [ 2.17136 ], [ -3.1066559999999996 ], [ -0.143264 ], [ -2.4733440000000004 ] ],
[ [ 0.147968 ], [ -0.999216 ], [ -0.917056 ], [ -0.564768 ], [ 0.134848 ], [ 0.34924799999999995 ], [ 0.028544 ], [ -0.9917600000000001 ] ],
[ [ 0.091264 ], [ 0.42854400000000004 ], [ 1.7061439999999999 ], [ 0.22105599999999997 ], [ -0.12328 ], [ 0.44544 ], [ 0.720736 ], [ -0.57816 ] ],
[ [ -1.20384 ], [ -0.44304 ], [ 2.5274240000000003 ], [ 2.981296 ], [ -0.9874560000000001 ], [ -1.081536 ], [ -1.7820000000000003 ], [ -2.90752 ] ],
[ [ -1.107792 ], [ -2.7838719999999997 ], [ -2.3919840000000003 ], [ -1.358512 ], [ -0.76752 ], [ 0.187984 ], [ 1.796608 ], [ -1.1676799999999998 ] ],
[ [ -0.017664 ], [ 3.376 ], [ 1.046304 ], [ 1.277952 ], [ 2.4605759999999997 ], [ 0.7479359999999999 ], [ -0.780864 ], [ -0.57536 ] ],
[ [ -1.7678399999999999 ], [ -1.14168 ], [ 2.533168 ], [ -0.055760000000000004 ], [ -2.401968 ], [ 1.873952 ], [ 5.76E-4 ], [ 0.01896 ] ]
]
Outputs Statistics: {meanExponent=-0.26234884613983145, negative=36, min=-3.1066559999999996, max=3.376, mean=-0.23957125, count=64, sum=-15.33256, positive=28, stdDev=1.454471946375535, zeros=0}

Feedback Validation

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

SingleDerivativeTester.java:117 executed in 2.70 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: [ [ -0.472, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, -0.504, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -1.156, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.184, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 1.98, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -0.628, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.368, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.16, ... ], ... ]
Implemented Statistics: {meanExponent=-0.06999649029273047, negative=36, min=-2.0, max=1.98, mean=-0.0030507812499999997, count=4096, sum=-12.495999999999999, positive=28, stdDev=0.15027219235861516, zeros=4032}
Measured Feedback: [ [ -0.47199999999997244, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, -0.5039999999995048, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -1.1559999999999349, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.18400000000001748, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 1.980000000001425, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, -0.6279999999980745, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.36800000000003497, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.1600000000000499, ... ], ... ]
Measured Statistics: {meanExponent=-0.06999649029271587, negative=36, min=-1.9999999999997797, max=1.980000000001425, mean=-0.0030507812499986214, count=4096, sum=-12.495999999994353, positive=28, stdDev=0.15027219235863803, zeros=4032}
Feedback Error: [ [ 2.7533531010703882E-14, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 4.951594689828198E-13, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 6.505906924303417E-14, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 1.7486012637846216E-14, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 1.425082274408851E-12, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 1.925459791607409E-12, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -3.497202527569243E-14, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -4.9960036108132044E-14, ... ], ... ]
Error Statistics: {meanExponent=-12.772773171329716, negative=28, min=-2.7853275241795927E-12, max=3.775646462145232E-12, mean=1.379176314169131E-15, count=4096, sum=5.6491061828367606E-12, positive=36, stdDev=1.0911305203330938E-13, 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: [ [ 0.08, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.7, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -0.128, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.496, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, -0.608, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 1.764, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.048, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.524, ... ], ... ]
Implemented Statistics: {meanExponent=-0.1923523558471011, negative=32, min=-1.856, max=1.912, mean=9.277343750000004E-4, count=4096, sum=3.8000000000000016, positive=32, stdDev=0.14417228277803418, zeros=4032}
Measured Feedback: [ [ 0.08000000000001062, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.700000000000145, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -0.1280000000000725, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.4959999999999687, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, -0.6079999999997199, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 1.7640000000018752, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.04799999999999249, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.5239999999994147, ... ], ... ]
Measured Statistics: {meanExponent=-0.19235235584721624, negative=32, min=-1.8560000000000798, max=1.9119999999972492, mean=9.277343749996917E-4, count=4096, sum=3.7999999999987373, positive=32, stdDev=0.14417228277799995, zeros=4032}
Feedback Error: [ [ 1.061650767297806E-14, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 1.4499512701604544E-13, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, -7.249756350802272E-14, 0.0, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, -3.1308289294429414E-14, 0.0, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 2.80109269112927E-13, 0.0, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 1.8751666885918894E-12, 0.0, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -7.507883204027621E-15, 0.0, ... ], [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -5.853095785823825E-13, ... ], ... ]
Error Statistics: {meanExponent=-12.668003119907267, negative=27, min=-2.750688565811288E-12, max=2.4356072714226684E-12, mean=-3.0870878092335505E-16, count=4096, sum=-1.2644711666620623E-12, positive=37, stdDev=1.16875705238222E-13, zeros=4032}

Returns

    {
      "absoluteTol" : {
        "count" : 8192,
        "sum" : 7.408979332823584E-11,
        "min" : 0.0,
        "max" : 3.775646462145232E-12,
        "sumOfSquare" : 1.0472483236811742E-22,
        "standardDeviation" : 1.1270313264130675E-13,
        "average" : 9.044164224638164E-15
      },
      "relativeTol" : {
        "count" : 128,
        "sum" : 3.527975177540854E-11,
        "min" : 6.251255769285792E-17,
        "max" : 1.5330093882248093E-12,
        "sumOfSquare" : 2.0122205734021203E-23,
        "standardDeviation" : 2.8502045660336323E-13,
        "average" : 2.756230607453792E-13
      }
    }

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" : 7.408979332823584E-11,
        "min" : 0.0,
        "max" : 3.775646462145232E-12,
        "sumOfSquare" : 1.0472483236811742E-22,
        "standardDeviation" : 1.1270313264130675E-13,
        "average" : 9.044164224638164E-15
      },
      "relativeTol" : {
        "count" : 128,
        "sum" : 3.527975177540854E-11,
        "min" : 6.251255769285792E-17,
        "max" : 1.5330093882248093E-12,
        "sumOfSquare" : 2.0122205734021203E-23,
        "standardDeviation" : 2.8502045660336323E-13,
        "average" : 2.756230607453792E-13
      }
    }

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: 9.0442e-15 +- 1.1270e-13 [0.0000e+00 - 3.7756e-12] (8192#)
relativeTol: 2.7562e-13 +- 2.8502e-13 [6.2513e-17 - 1.5330e-12] (128#)

Frozen and Alive Status

SingleDerivativeTester.java:156 executed in 0.02 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=9.0442e-15 +- 1.1270e-13 [0.0000e+00 - 3.7756e-12] (8192#), relativeTol=2.7562e-13 +- 2.8502e-13 [6.2513e-17 - 1.5330e-12] (128#)}OK
 
  {
    "result": "OK",
    "performance": {
      "execution_time": "3.198",
      "gc_time": "0.436"
    },
    "created_on": 1586737272834,
    "file_name": "derivativeTest",
    "report": {
      "simpleName": "Double",
      "canonicalName": "com.simiacryptus.mindseye.layers.cudnn.NProductLayerTest.Double",
      "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/Double/derivativeTest/202004132112",
    "id": "2a387312-d4bf-4b58-adea-d70c396f7ac0",
    "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": ""
    }
  }