Test Modules

Using Seed 5448100106008833024

Performance

Now we execute larger-scale runs to benchmark performance:

PerformanceTester.java:120 executed in 0.15 seconds (0.000 gc):

    test(component == null ? null : component.addRef(), RefUtil.addRef(inputPrototype));

Logging

5 batch length, 5 trials
Input Dimensions:
[5]
Performance:
BACKPROP_AGG_SIZE = 3
THREADS = 64
SINGLE_THREADED = false
Initialized CoreSettings = {
"backpropAggregationSize" : 3,
"jvmThreads" : 64,
"singleThreaded" : false
}
Evaluation performance: 0.024605s +- 0.021061s [0.008490s - 0.065654s]
Learning performance: 0.001813s +- 0.001861s [0.000581s - 0.005521s]

LayerTests.java:425 executed in 0.00 seconds (0.000 gc):

    throwException(exceptions.addRef());

Results

class	result
com.simiacryptus.mindseye.test.unit.PerformanceTester	OK

  {
    "result": "OK",
    "performance": {
      "execution_time": "0.309",
      "gc_time": "0.143"
    },
    "created_on": 1586739399475,
    "file_name": "perfTest",
    "report": {
      "simpleName": "Basic",
      "canonicalName": "com.simiacryptus.mindseye.layers.java.BinaryNoiseLayerTest.Basic",
      "link": "https://github.com/SimiaCryptus/mindseye-java/tree/93db34cedee48c0202777a2b25deddf1dfaf5731/src/test/java/com/simiacryptus/mindseye/layers/java/BinaryNoiseLayerTest.java",
      "javaDoc": ""
    },
    "archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/java/StochasticSamplingSubnetLayer/Basic/perfTest/202004135639",
    "id": "dc066805-c146-4869-ae61-be719b7db77c",
    "report_type": "Components",
    "display_name": "Performance",
    "target": {
      "simpleName": "StochasticSamplingSubnetLayer",
      "canonicalName": "com.simiacryptus.mindseye.layers.java.StochasticSamplingSubnetLayer",
      "link": "https://github.com/SimiaCryptus/mindseye-java/tree/93db34cedee48c0202777a2b25deddf1dfaf5731/src/main/java/com/simiacryptus/mindseye/layers/java/StochasticSamplingSubnetLayer.java",
      "javaDoc": ""
    }
  }