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

Target Description: The type Assert dimensions layer.

Report Description: The type Basic.

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

Test Modules

Using Seed 5877875733883622400

Differential Validation

SingleDerivativeTester.java:153 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)));
Logging
Inputs: [ [ 0.08, -0.128 ], [ 0.7, 0.496 ] ]
Inputs Statistics: {meanExponent=-0.6122800817139336, negative=1, min=-0.128, max=0.7, mean=0.287, count=4, sum=1.148, positive=3, stdDev=0.3276141022605712, zeros=0}
Output: [ [ 0.08, -0.128 ], [ 0.7, 0.496 ] ]
Outputs Statistics: {meanExponent=-0.6122800817139336, negative=1, min=-0.128, max=0.7, mean=0.287, count=4, sum=1.148, positive=3, stdDev=0.3276141022605712, zeros=0}

Feedback Validation

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

SingleDerivativeTester.java:169 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()));
Logging
Feedback for input 0
Inputs Values: [ [ 0.08, -0.128 ], [ 0.7, 0.496 ] ]
Value Statistics: {meanExponent=-0.6122800817139336, negative=1, min=-0.128, max=0.7, mean=0.287, count=4, sum=1.148, positive=3, stdDev=0.3276141022605712, zeros=0}
Implemented Feedback: [ [ 1.0, 0.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0, 0.0 ], [ 0.0, 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 0.0, 1.0 ] ]
Implemented Statistics: {meanExponent=0.0, negative=0, min=0.0, max=1.0, mean=0.25, count=16, sum=4.0, positive=4, stdDev=0.4330127018922193, zeros=12}
Measured Feedback: [ [ 1.0000000000000286, 0.0, 0.0, 0.0 ], [ 0.0, 0.9999999999998899, 0.0, 0.0 ], [ 0.0, 0.0, 0.9999999999998899, 0.0 ], [ 0.0, 0.0, 0.0, 0.9999999999998899 ] ]
Measured Statistics: {meanExponent=-3.276302567614995E-14, negative=0, min=0.0, max=1.0000000000000286, mean=0.24999999999998113, count=16, sum=3.999999999999698, positive=4, stdDev=0.43301270189218666, zeros=12}
Feedback Error: [ [ 2.864375403532904E-14, 0.0, 0.0, 0.0 ], [ 0.0, -1.1013412404281553E-13, 0.0, 0.0 ], [ 0.0, 0.0, -1.1013412404281553E-13, 0.0 ], [ 0.0, 0.0, 0.0, -1.1013412404281553E-13 ] ]
Error Statistics: {meanExponent=-13.104301089584563, negative=3, min=-1.1013412404281553E-13, max=2.864375403532904E-14, mean=-1.8859913630819847E-14, count=16, sum=-3.0175861809311755E-13, positive=1, stdDev=4.4383202767685317E-14, zeros=12}

Returns

    {
      "absoluteTol" : {
        "count" : 16,
        "sum" : 3.590461261637756E-13,
        "min" : 0.0,
        "max" : 1.1013412404281553E-13,
        "sumOfSquare" : 3.720904048127126E-26,
        "standardDeviation" : 4.26848245403851E-14,
        "average" : 2.2440382885235977E-14
      },
      "relativeTol" : {
        "count" : 4,
        "sum" : 1.7952306308189672E-13,
        "min" : 1.4321877017664317E-14,
        "max" : 5.50670620214108E-14,
        "sumOfSquare" : 9.302260120318813E-27,
        "standardDeviation" : 1.7643182647570603E-14,
        "average" : 4.488076577047418E-14
      }
    }

Learning Validation

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

SingleDerivativeTester.java:185 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" : 16,
        "sum" : 3.590461261637756E-13,
        "min" : 0.0,
        "max" : 1.1013412404281553E-13,
        "sumOfSquare" : 3.720904048127126E-26,
        "standardDeviation" : 4.26848245403851E-14,
        "average" : 2.2440382885235977E-14
      },
      "relativeTol" : {
        "count" : 4,
        "sum" : 1.7952306308189672E-13,
        "min" : 1.4321877017664317E-14,
        "max" : 5.50670620214108E-14,
        "sumOfSquare" : 9.302260120318813E-27,
        "standardDeviation" : 1.7643182647570603E-14,
        "average" : 4.488076577047418E-14
      }
    }

Total Accuracy

The overall agreement accuracy between the implemented derivative and the finite difference estimations:

SingleDerivativeTester.java:200 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: 2.2440e-14 +- 4.2685e-14 [0.0000e+00 - 1.1013e-13] (16#)
relativeTol: 4.4881e-14 +- 1.7643e-14 [1.4322e-14 - 5.5067e-14] (4#)

Frozen and Alive Status

SingleDerivativeTester.java:208 executed in 0.00 seconds (0.000 gc):

    testFrozen(component.addRef(), RefUtil.addRef(inputPrototype));
    testUnFrozen(component.addRef(), RefUtil.addRef(inputPrototype));

LayerTests.java:605 executed in 0.00 seconds (0.000 gc):

    throwException(exceptions.addRef());

Results

classdetailsresult
com.simiacryptus.mindseye.test.unit.SingleDerivativeTesterToleranceStatistics{absoluteTol=2.2440e-14 +- 4.2685e-14 [0.0000e+00 - 1.1013e-13] (16#), relativeTol=4.4881e-14 +- 1.7643e-14 [1.4322e-14 - 5.5067e-14] (4#)}OK
  {
    "result": "OK",
    "performance": {
      "execution_time": "0.160",
      "gc_time": "0.099"
    },
    "created_on": 1587005910622,
    "file_name": "derivativeTest",
    "report": {
      "simpleName": "Basic",
      "canonicalName": "com.simiacryptus.mindseye.layers.java.AssertDimensionsLayerTest.Basic",
      "link": "https://github.com/SimiaCryptus/mindseye-java/tree/c9a1867488dc7e77a975f095285b5882c0486db6/src/test/java/com/simiacryptus/mindseye/layers/java/AssertDimensionsLayerTest.java",
      "javaDoc": "The type Basic."
    },
    "archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/java/AssertDimensionsLayer/Basic/derivativeTest/202004165830",
    "id": "44da2eb9-5e38-4910-bdd4-bf44c0163d90",
    "report_type": "Components",
    "display_name": "Derivative Validation",
    "target": {
      "simpleName": "AssertDimensionsLayer",
      "canonicalName": "com.simiacryptus.mindseye.layers.java.AssertDimensionsLayer",
      "link": "https://github.com/SimiaCryptus/mindseye-java/tree/c9a1867488dc7e77a975f095285b5882c0486db6/src/main/java/com/simiacryptus/mindseye/layers/java/AssertDimensionsLayer.java",
      "javaDoc": "The type Assert dimensions layer."
    }
  }