double validation_phase(CNTK.MinibatchSource reader)
{
var featuresStreamInfo = reader.StreamInfo("features");
var labelsStreamInfo = reader.StreamInfo("labels");
var num_samples = 0;
var num_minibatches = 0;
var score = 0.0;
while (num_samples < 2 * validation_set_size)
{
num_minibatches++;
var minibatchData = reader.GetNextMinibatch(minibatch_size, computeDevice);
var arguments = new test_feed_t {
{ features_tensor, minibatchData[featuresStreamInfo] }, { label_tensor, minibatchData[labelsStreamInfo] }
};
num_samples += (int)(minibatchData[featuresStreamInfo].numberOfSamples);
evaluator.TestMinibatch(arguments, computeDevice);
score += trainer.PreviousMinibatchEvaluationAverage();
}
var result = 1.0 - (score / num_minibatches);
return(result);
}
/// <summary>
/// Get a batch from the given image reader.
/// </summary>
/// <param name="reader">The image reader to use.</param>
/// <param name="batchSize">The size of the batch.</param>
/// <returns>A batch of values taken from the given image reader.</returns>
public static CNTK.UnorderedMapStreamInformationMinibatchData GetBatch(
this CNTK.MinibatchSource reader,
int batchSize)
{
return(reader.GetNextMinibatch((uint)batchSize, NetUtil.CurrentDevice));
}
