public override void Test(string datasetFile)
{
var dataSource = CreateDataSource(datasetFile);
var testingResultResponse = new TestingResultResponse();
const int minibatchSize = 1;
var currentMinibatch = 0;
while (true)
{
var minibatchData = dataSource.MinibatchSource.GetNextMinibatch(minibatchSize, _device);
var inputDataMap = new Dictionary <Variable, Value>()
{
{ _modelWrapper.Input, minibatchData[dataSource.FeatureStreamInfo].data }
};
var outputDataMap = new Dictionary <Variable, Value>()
{
{ _modelWrapper.EvaluationOutput, null }
};
_modelWrapper.Model.Evaluate(inputDataMap, outputDataMap, _device);
var outputVal = outputDataMap[_modelWrapper.EvaluationOutput];
var actual = outputVal.GetDenseData <float>(_modelWrapper.EvaluationOutput);
var labelBatch = minibatchData[dataSource.LabelStreamInfo].data;
var expected = labelBatch.GetDenseData <float>(_modelWrapper.Model.Output);
Func <IEnumerable <IList <float> >, IEnumerable <int> > maxSelector =
(collection) => collection.Select(x => x.IndexOf(x.Max()));
var actualLabels = maxSelector(actual);
var expectedLabels = maxSelector(expected);
testingResultResponse.Correct += actualLabels.Zip(expectedLabels, (a, b) => a.Equals(b) ? 1 : 0).Sum();
testingResultResponse.Total += actualLabels.Count();
currentMinibatch++;
if (minibatchData.Values.Any(x => x.sweepEnd))
{
OnTestingFinished(testingResultResponse);
break;
}
}
}
protected void OnTestingFinished(TestingResultResponse testingResultResponse) => TestingFinished?.Invoke(this, testingResultResponse);
private static void TestingFinished(
object sender, TestingResultResponse testingResultResponse) =>
WriteLine(
$"Testing finished. " +
$"Correctly answered {testingResultResponse.Correct} of {testingResultResponse.Total}, " +
$"accuracy = {testingResultResponse.Accuracy * 100}%");