public void ExecuteTest()
{
float max_err = 0;
foreach (int batch in new int[] { 1, 2 })
{
foreach (int channels in new int[] { 3, 5 })
{
foreach (int stride in new int[] { 2, 3, 4 })
{
foreach (int inwidth in new int[] { 5, 7, 11 })
{
foreach (int inheight in new int[] { 5, 7, 11 })
{
foreach (int indepth in new int[] { 5, 7, 11 })
{
int outwidth = inwidth / stride, outheight = inheight / stride, outdepth = indepth / stride;
float[] xval = (new float[inwidth * inheight * indepth * channels * batch]).Select((_, idx) => idx * 1e-3f).ToArray();
Map3D x = new Map3D(channels, inwidth, inheight, indepth, batch, xval);
Map3D y = Reference(x, stride);
OverflowCheckedTensor x_tensor = new OverflowCheckedTensor(Shape.Map3D(channels, inwidth, inheight, indepth, batch), xval);
OverflowCheckedTensor y_tensor = new OverflowCheckedTensor(Shape.Map3D(channels, outwidth, outheight, outdepth, batch));
AveragePooling ope = new AveragePooling(inwidth, inheight, indepth, channels, stride, batch);
ope.Execute(x_tensor, y_tensor);
float[] y_expect = y.ToArray();
float[] y_actual = y_tensor.State;
CollectionAssert.AreEqual(xval, x_tensor.State);
AssertError.Tolerance(y_expect, y_actual, 1e-7f, 1e-5f, ref max_err, $"mismatch value {channels},{stride},{inwidth},{inheight},{indepth},{batch}");
Console.WriteLine($"pass: {channels},{stride},{inwidth},{inheight},{indepth},{batch}");
}
}
}
}
}
}
Console.WriteLine($"maxerr:{max_err}");
}
public void SpeedTest()
{
int inwidth = 512, channels = 32, stride = 2;
int outwidth = inwidth / stride;
OverflowCheckedTensor x_tensor = new OverflowCheckedTensor(Shape.Map1D(channels, inwidth));
OverflowCheckedTensor y_tensor = new OverflowCheckedTensor(Shape.Map1D(channels, outwidth));
AveragePooling ope = new AveragePooling(inwidth, channels, stride);
Stopwatch sw = new Stopwatch();
sw.Start();
ope.Execute(x_tensor, y_tensor);
ope.Execute(x_tensor, y_tensor);
ope.Execute(x_tensor, y_tensor);
ope.Execute(x_tensor, y_tensor);
sw.Stop();
Console.WriteLine($"{sw.ElapsedMilliseconds / 4} msec");
}
public static void Run(bool verbose)
{
Stopwatch sw = new Stopwatch();
NdArray inputArrayCpu = new NdArray(BenchDataMaker.GetRealArray(INPUT_SIZE));
NdArray inputArrayGpu = new NdArray(BenchDataMaker.GetRealArray(INPUT_SIZE));
Ensure.Argument(inputArrayGpu).NotNull();
Ensure.Argument(inputArrayCpu).NotNull();
//Linear
Linear linear = new Linear(verbose, INPUT_SIZE, OUTPUT_SIZE);
if (verbose)
{
RILogManager.Default?.EnterMethod(linear.Name);
}
sw.Restart();
NdArray[] gradArrayCpu = linear.Forward(verbose, inputArrayCpu);
sw.Stop();
if (verbose)
{
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
}
Ensure.Argument(gradArrayCpu).NotNull();
gradArrayCpu[0].Grad = gradArrayCpu[0].Data; // Use Data as Grad
sw.Restart();
linear.Backward(verbose, gradArrayCpu);
sw.Stop();
if (verbose)
{
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
}
if (linear.SetGpuEnable(true))
{
sw.Restart();
NdArray[] gradArrayGpu = linear.Forward(verbose, inputArrayGpu);
sw.Stop();
if (verbose)
{
RILogManager.Default?.SendDebug("Forward [Gpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
}
gradArrayGpu[0].Grad = gradArrayGpu[0].Data;
sw.Restart();
linear.Backward(verbose, gradArrayGpu);
sw.Stop();
if (verbose)
{
RILogManager.Default?.SendDebug("Backward[Gpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
}
}
if (verbose)
{
RILogManager.Default?.ExitMethod(linear.Name);
}
//Tanh
Tanh tanh = new Tanh();
if (verbose)
{
RILogManager.Default?.EnterMethod(tanh.Name);
}
sw.Restart();
gradArrayCpu = tanh.Forward(verbose, inputArrayCpu);
sw.Stop();
if (verbose)
{
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
}
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
tanh.Backward(verbose, gradArrayCpu);
sw.Stop();
if (verbose)
{
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
}
if (tanh.SetGpuEnable(true))
{
HandleGPU(verbose, sw, tanh, inputArrayGpu);
}
if (verbose)
{
RILogManager.Default?.ExitMethod(tanh.Name);
}
//Sigmoid
Sigmoid sigmoid = new Sigmoid();
if (verbose)
{
RILogManager.Default?.EnterMethod(sigmoid.Name);
}
sw.Restart();
gradArrayCpu = sigmoid.Forward(verbose, inputArrayCpu);
sw.Stop();
if (verbose)
{
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
}
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
sigmoid.Backward(verbose, gradArrayCpu);
sw.Stop();
if (verbose)
{
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
}
if (sigmoid.SetGpuEnable(true))
{
HandleGPU(verbose, sw, sigmoid, inputArrayGpu);
}
if (verbose)
{
RILogManager.Default?.ExitMethod(tanh.Name);
}
//Softmax
Softmax sm = new Softmax();
RILogManager.Default?.EnterMethod(sm.Name);
sw.Restart();
gradArrayCpu = sm.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
sm.Backward(verbose, gradArrayCpu);
sw.Stop();
if (verbose)
{
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
}
if (verbose)
{
RILogManager.Default?.ExitMethod(sm.Name);
}
//Softplus
Softplus sp = new Softplus();
if (verbose)
{
RILogManager.Default?.EnterMethod(sp.Name);
}
sw.Restart();
gradArrayCpu = sp.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
sp.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
RILogManager.Default?.ExitMethod(sp.Name);
//ReLU
ReLU relu = new ReLU();
RILogManager.Default?.EnterMethod(relu.Name);
sw.Restart();
gradArrayCpu = relu.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
relu.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (relu.SetGpuEnable(true))
{
HandleGPU(verbose, sw, relu, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(relu.Name);
//LeakyReLU
LeakyReLU leakyRelu = new LeakyReLU();
RILogManager.Default?.EnterMethod(leakyRelu.Name);
sw.Restart();
gradArrayCpu = leakyRelu.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
leakyRelu.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (leakyRelu.SetGpuEnable(true))
{
HandleGPU(verbose, sw, leakyRelu, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(leakyRelu.Name);
//ReLuTanh
ReLuTanh rth = new ReLuTanh();
RILogManager.Default?.EnterMethod(rth.Name);
sw.Restart();
gradArrayCpu = rth.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
rth.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (rth.SetGpuEnable(true))
{
HandleGPU(verbose, sw, rth, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(rth.Name);
////Swish
//Swish swi = new Swish();
//RILogManager.Default?.SendDebug(swi.Name);
//sw.Restart();
//gradArrayCpu = swi.Forward(inputArrayCpu);
//sw.Stop();
//RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
//gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
//sw.Restart();
//swi.Backward(gradArrayCpu);
//sw.Stop();
//RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
NdArray inputImageArrayGpu = new NdArray(BenchDataMaker.GetRealArray(3 * 256 * 256 * 5), new[] { 3, 256, 256 }, 5);
NdArray inputImageArrayCpu = new NdArray(BenchDataMaker.GetRealArray(3 * 256 * 256 * 5), new[] { 3, 256, 256 }, 5);
//MaxPooling
MaxPooling maxPooling = new MaxPooling(3);
RILogManager.Default?.EnterMethod(maxPooling.Name);
sw.Restart();
NdArray[] gradImageArrayCpu = maxPooling.Forward(verbose, inputImageArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradImageArrayCpu[0].Grad = gradImageArrayCpu[0].Data;
sw.Restart();
maxPooling.Backward(verbose, gradImageArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (maxPooling.SetGpuEnable(true))
{
sw.Restart();
maxPooling.Forward(verbose, inputImageArrayGpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Gpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
// There is no implementation for memory transfer only
RILogManager.Default?.SendDebug("Backward[Gpu] : None");
}
RILogManager.Default?.ExitMethod(maxPooling.Name);
//AvgPooling
AveragePooling avgPooling = new AveragePooling(3);
RILogManager.Default?.EnterMethod(avgPooling.Name);
sw.Restart();
gradImageArrayCpu = avgPooling.Forward(verbose, inputImageArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradImageArrayCpu[0].Grad = gradImageArrayCpu[0].Data;
sw.Restart();
avgPooling.Backward(verbose, gradImageArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
RILogManager.Default?.ExitMethod(avgPooling.Name);
//Conv2D
Convolution2D conv2d = new Convolution2D(verbose, 3, 3, 3);
RILogManager.Default?.EnterMethod(conv2d.Name);
sw.Restart();
gradImageArrayCpu = conv2d.Forward(verbose, inputImageArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradImageArrayCpu[0].Grad = gradImageArrayCpu[0].Data;
sw.Restart();
conv2d.Backward(verbose, gradImageArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (conv2d.SetGpuEnable(true))
{
HandleGPU(verbose, sw, conv2d, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(conv2d.Name);
//Deconv2D
Deconvolution2D deconv2d = new Deconvolution2D(verbose, 3, 3, 3);
RILogManager.Default?.EnterMethod(deconv2d.Name);
sw.Restart();
gradImageArrayCpu = deconv2d.Forward(verbose, inputImageArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradImageArrayCpu[0].Grad = gradImageArrayCpu[0].Data;
sw.Restart();
deconv2d.Backward(verbose, gradImageArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (deconv2d.SetGpuEnable(true))
{
HandleGPU(verbose, sw, deconv2d, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(deconv2d.Name);
//Dropout
Dropout dropout = new Dropout();
RILogManager.Default?.EnterMethod(dropout.Name);
sw.Restart();
gradArrayCpu = dropout.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
dropout.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (dropout.SetGpuEnable(true))
{
sw.Restart();
NdArray[] gradArrayGpu = dropout.Forward(verbose, inputArrayGpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Gpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayGpu[0].Grad = gradArrayGpu[0].Data;
sw.Restart();
dropout.Backward(verbose, gradArrayGpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Gpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
}
RILogManager.Default?.ExitMethod(dropout.Name);
//ArcSinH
ArcSinH a = new ArcSinH();
RILogManager.Default?.EnterMethod(a.Name);
sw.Restart();
gradArrayCpu = a.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
a.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (a.SetGpuEnable(true))
{
HandleGPU(verbose, sw, a, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(a.Name);
//ELU
ELU e = new ELU();
RILogManager.Default?.EnterMethod(e.Name);
sw.Restart();
gradArrayCpu = e.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
e.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
RILogManager.Default?.ExitMethod(e.Name);
//LeakyReluShifted
LeakyReLUShifted lrs = new LeakyReLUShifted();
RILogManager.Default?.EnterMethod(lrs.Name);
sw.Restart();
gradArrayCpu = lrs.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
lrs.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (lrs.SetGpuEnable(true))
{
HandleGPU(verbose, sw, lrs, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(lrs.Name);
//Logistic
LogisticFunction lf = new LogisticFunction();
RILogManager.Default?.EnterMethod(lf.Name);
sw.Restart();
gradArrayCpu = lf.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
lf.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (lf.SetGpuEnable(true))
{
HandleGPU(verbose, sw, lf, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(lf.Name);
//MaxMinusOne
MaxMinusOne mmo = new MaxMinusOne();
RILogManager.Default?.EnterMethod(mmo.Name);
sw.Restart();
gradArrayCpu = mmo.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
mmo.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (mmo.SetGpuEnable(true))
{
HandleGPU(verbose, sw, mmo, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(mmo.Name);
//ScaledELU
ScaledELU se = new ScaledELU();
RILogManager.Default?.EnterMethod(se.Name);
sw.Restart();
gradArrayCpu = se.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
se.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (se.SetGpuEnable(true))
{
HandleGPU(verbose, sw, se, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(se.Name);
//Sine
Sine s = new Sine();
RILogManager.Default?.EnterMethod(s.Name);
sw.Restart();
gradArrayCpu = s.Forward(verbose, inputArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Forward [Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
gradArrayCpu[0].Grad = gradArrayCpu[0].Data;
sw.Restart();
s.Backward(verbose, gradArrayCpu);
sw.Stop();
RILogManager.Default?.SendDebug("Backward[Cpu] : " + (sw.ElapsedTicks / (Stopwatch.Frequency / (1000L * 1000L))).ToString("n0") + "μｓ");
if (s.SetGpuEnable(true))
{
HandleGPU(verbose, sw, s, inputArrayGpu);
}
RILogManager.Default?.ExitMethod(s.Name);
}
public bool CreateLayer(int nCount, ELayerType type, ActivationSettings activationSettings)
{
Layer.Utility.Layer layer;
switch (type)
{
case ELayerType.Invalid:
throw new ArgumentException("Invalid \"type\" argument.");
case ELayerType.AveragePooling:
layer = new AveragePooling(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
case ELayerType.AverageUnpooling:
layer = new AverageUnpooling(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
case ELayerType.Convolutional:
layer = new Convolutional(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
case ELayerType.Deconvolutional:
layer = new Deconvolutional(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
case ELayerType.Dropout:
layer = new Dropout(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
case ELayerType.FullyConnected:
layer = new FullyConnected(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
case ELayerType.GatedRecurrent:
layer = new GatedRecurrent(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
case ELayerType.LSTM:
layer = new LSTM(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
case ELayerType.MaxPooling:
layer = new MaxPooling(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
case ELayerType.MaxUnpooling:
layer = new MaxUnpooling(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
case ELayerType.Recurrent:
layer = new Recurrent(nCount, Layers.Count, activationSettings);
Layers.Add(layer);
return(true);
default:
throw new ArgumentException("Invalid \"type\" argument.");
}
}
