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."); } }