Examples with ReferenceCountingBase com.simiacryptus.mindseye.lang.ReferenceCountingBase used on opensource projects

Example 1 with ReferenceCountingBase

use of com.simiacryptus.mindseye.lang.ReferenceCountingBase in project MindsEye by SimiaCryptus.

the class CudaLayerTester method testNonstandardBounds.

/**
 * Test nonstandard bounds tolerance statistics.
 *
 * @param log            the log
 * @param reference      the reference
 * @param inputPrototype the input prototype
 * @return the tolerance statistics
 */
@Nonnull
public ToleranceStatistics testNonstandardBounds(final NotebookOutput log, @Nullable final Layer reference, @Nonnull final Tensor[] inputPrototype) {
    log.h2("Irregular Input");
    log.p("This layer should be able to accept non-dense inputs.");
    return log.code(() -> {
        Tensor[] randomized = Arrays.stream(inputPrototype).map(x -> x.map(v -> getRandom())).toArray(i -> new Tensor[i]);
        logger.info("Input: " + Arrays.stream(randomized).map(Tensor::prettyPrint).collect(Collectors.toList()));
        Precision precision = Precision.Double;
        TensorList[] controlInput = CudaSystem.run(gpu -> {
            return Arrays.stream(randomized).map(original -> {
                TensorArray data = TensorArray.create(original);
                CudaTensorList wrap = CudaTensorList.wrap(gpu.getTensor(data, precision, MemoryType.Managed, false), 1, original.getDimensions(), precision);
                data.freeRef();
                return wrap;
            }).toArray(i -> new TensorList[i]);
        }, 0);
        @Nonnull final SimpleResult controlResult = CudaSystem.run(gpu -> {
            return SimpleGpuEval.run(reference, gpu, controlInput);
        }, 1);
        final TensorList[] irregularInput = CudaSystem.run(gpu -> {
            return Arrays.stream(randomized).map(original -> {
                return buildIrregularCudaTensor(gpu, precision, original);
            }).toArray(i -> new TensorList[i]);
        }, 0);
        @Nonnull final SimpleResult testResult = CudaSystem.run(gpu -> {
            return SimpleGpuEval.run(reference, gpu, irregularInput);
        }, 1);
        try {
            ToleranceStatistics compareOutput = compareOutput(controlResult, testResult);
            ToleranceStatistics compareDerivatives = compareDerivatives(controlResult, testResult);
            return compareDerivatives.combine(compareOutput);
        } finally {
            Arrays.stream(randomized).forEach(ReferenceCountingBase::freeRef);
            Arrays.stream(controlInput).forEach(ReferenceCounting::freeRef);
            Arrays.stream(irregularInput).forEach(x -> x.freeRef());
            controlResult.freeRef();
            testResult.freeRef();
        }
    });
}