// Classify data using trained network parameters and count classification errors
public int Classify(ManagedArray test_input, ManagedArray test_output, int classes, int items, int batchsize, ManagedArray classification, bool pool = false)
{
var errors = 0;
var tempx = new ManagedArray(test_input.x, test_input.y, batchsize, false);
var tempy = new ManagedArray(batchsize, classes, false);
var tempclass = new ManagedArray(1, batchsize, false);
ManagedOps.Free(classification);
classification = new ManagedArray(1, items, false);
for (var i = 0; i < items; i += batchsize)
{
// generate batch
ManagedOps.Copy3D(tempx, test_input, 0, 0, i);
ManagedOps.Copy2D(tempy, test_output, i, 0);
// classify
FeedForward(tempx, pool);
// count classifcation errors
errors += Test(tempy, tempclass);
// save classification
ManagedOps.Copy2DOffset(classification, tempclass, i, 0);
}
ManagedOps.Free(tempx, tempy, tempclass);
return(errors);
}
public void Train(ManagedArray input, ManagedArray output, ConvolutionalNeuralNetworkOptions opts)
{
var temp_input = new ManagedArray(input.x, input.y, opts.BatchSize, false);
var temp_output = new ManagedArray(opts.BatchSize, output.y, false);
var index_list = new ManagedIntList(opts.Items);
for (var epoch = 0; epoch < opts.Epochs; epoch++)
{
var start = Profiler.now();
if (opts.Shuffle)
{
ManagedOps.Shuffle(index_list);
}
var rLVal = 0.0;
rL.Clear();
for (var i = 0; i < opts.Items; i += opts.BatchSize)
{
if (opts.Shuffle)
{
ManagedOps.Copy3D(temp_input, input, 0, 0, i, index_list);
ManagedOps.Copy2D(temp_output, output, i, 0, index_list);
}
else
{
ManagedOps.Copy3D(temp_input, input, 0, 0, i);
ManagedOps.Copy2D(temp_output, output, i, 0);
}
FeedForward(temp_input, opts.Pool);
BackPropagation(temp_output);
ApplyGradients(opts);
if (rL.Count == 0)
{
rL.Add(L);
}
rLVal = 0.99 * rL[rL.Count - 1] + 0.01 * L;
rL.Add(rLVal);
}
Console.WriteLine("epoch {0}/{1} elapsed time is {2} ms - Error: {3}", (epoch + 1).ToString("D", ManagedMatrix.ci), opts.Epochs.ToString("D", ManagedMatrix.ci), Profiler.Elapsed(start).ToString("D", ManagedMatrix.ci), rLVal.ToString("0.000000", ManagedMatrix.ci));
}
ManagedOps.Free(index_list);
ManagedOps.Free(temp_input, temp_output);
}
// Flip 3D Matrix along a dimension
public static void FlipAll(ManagedArray dst, ManagedArray src)
{
dst.Resize(src.x, src.y, src.z, false);
var tmp = new ManagedArray(src.x, src.y, src.z, false);
ManagedOps.Copy3D(tmp, src, 0, 0, 0);
for (int FlipDim = 0; FlipDim < 3; FlipDim++)
{
Flip(dst, tmp, FlipDim);
ManagedOps.Copy3D(tmp, dst, 0, 0, 0);
}
ManagedOps.Free(tmp);
}