//後からActivationを追加する用
public void SetActivation(CompressibleActivation activation)
{
this.Activator = activation;
//Kernelの再構築が必要
CreateKernel();
}
protected CompressibleFunction(string functionName, CompressibleActivation activation = null, string name = FUNCTION_NAME, string[] inputNames = null, string[] outputNames = null, bool gpuEnable = false) : base(name, inputNames, outputNames)
{
string kernelNameBase = functionName.Replace(" ", "");
this.ForwardKernelName = kernelNameBase + "Forward";
this.BackwardgWKernelName = kernelNameBase + "gWBackward";
this.BackwardgXKernelName = kernelNameBase + "gXBackward";
this.Activator = activation;
this.SetGpuEnable(gpuEnable);
}
//後からActivationを追加する用
public void SetActivation(CompressibleActivation activation)
{
this.Activator = activation;
if (this.Activator != null)
{
foreach (var activationParameterer in this._activationParameters)
{
this.KernelString = this.KernelString.Replace(activationParameterer.Key, activationParameterer.Value);
}
}
//Kernelの再構築が必要
CreateKernel();
}
protected CompressibleFunction(string functionName, CompressibleActivation activation = null, KeyValuePair <string, string>[] activationParameters = null, string name = FUNCTION_NAME, string[] inputNames = null, string[] outputNames = null, bool gpuEnable = false) : base(name, inputNames, outputNames)
{
string kernelNameBase = functionName.Replace(" ", "");
this.ForwardKernelName = kernelNameBase + "Forward";
this.BackwardgWKernelName = kernelNameBase + "gWBackward";
this.BackwardgXKernelName = kernelNameBase + "gXBackward";
this.KernelString = Weaver.GetKernelSource(functionName);
this._activationParameters = activationParameters;
this.SetActivation(activation);
this.SetGpuEnable(gpuEnable);
}
public Deconvolution2D(int inputChannels, int outputChannels, int[] kSize, int[] subSample = null, int[] trim = null, bool noBias = false, Array initialW = null, Array initialb = null, CompressibleActivation activation = null, string name = FUNCTION_NAME, string[] inputNames = null, string[] outputNames = null, bool gpuEnable = false) : base(FUNCTION_NAME, activation, name, inputNames, outputNames, gpuEnable)
{
if (subSample == null)
{
subSample = new[] { 1, 1 }
}
;
if (trim == null)
{
trim = new[] { 0, 0 }
}
;
this._kWidth = kSize[0];
this._kHeight = kSize[1];
this._padX = trim[0];
this._padY = trim[1];
this.NoBias = noBias;
this._strideX = subSample[0];
this._strideY = subSample[1];
this.Parameters = new NdArray[noBias ? 1 : 2];
this.OutputCount = outputChannels;
this.InputCount = inputChannels;
this.Initialize(initialW, initialb);
}
void Initialize(Array initialW = null, Array initialb = null)
{
this.Weight = new NdArray(InputCount, OutputCount, this._kHeight, this._kWidth);
this.Weight.Name = this.Name + " Weight";
if (initialW == null)
{
Initializer.InitWeight(this.Weight);
}
else
{
this.Weight.Data = Real.ToRealArray(initialW);
}
this.Parameters[0] = this.Weight;
if (!NoBias)
{
this.Bias = new NdArray(OutputCount);
this.Bias.Name = this.Name + " Bias";
if (initialb != null)
{
this.Bias.Data = Real.ToRealArray(initialb);
}
this.Parameters[1] = this.Bias;
}
}
public Deconvolution2D(int inputChannels, int outputChannels, int kSize, int stride = 1, int pad = 0, bool noBias = false, Array initialW = null, Array initialb = null, CompressibleActivation activation = null, string name = FUNCTION_NAME, string[] inputNames = null, string[] outputNames = null, bool gpuEnable = false) : base(FUNCTION_NAME, activation, name, inputNames, outputNames, gpuEnable)
{
this._kWidth = kSize;
this._kHeight = kSize;
this._padX = pad;
this._padY = pad;
this._strideX = stride;
this._strideY = stride;
this.NoBias = noBias;
this.Parameters = new NdArray[noBias ? 1 : 2];
this.OutputCount = outputChannels;
this.InputCount = inputChannels;
this.Initialize(initialW, initialb);
}
public Convolution2D(int inputChannels, int outputChannels, int[] kSize, int[] stride = null, int[] pad = null, bool noBias = false, Array initialW = null, Array initialb = null, CompressibleActivation activation = null, string name = FUNCTION_NAME, string[] inputNames = null, string[] outputNames = null, bool gpuEnable = false) : base(FUNCTION_NAME, activation, name, inputNames, outputNames, gpuEnable)
{
if (pad == null)
{
pad = new[] { 0, 0 }
}
;
if (stride == null)
{
stride = new[] { 1, 1 }
}
;
this._kWidth = kSize[0];
this._kHeight = kSize[1];
this._strideX = stride[0];
this._strideY = stride[1];
this._padX = pad[0];
this._padY = pad[1];
this.NoBias = noBias;
this.Parameters = new NdArray[noBias ? 1 : 2];
this.OutputCount = outputChannels;
this.InputCount = inputChannels;
this.Initialize(initialW, initialb);
}
public Convolution2D(int inputChannels, int outputChannels, Size kSize, Size stride = new Size(), Size pad = new Size(), bool noBias = false, Array initialW = null, Array initialb = null, CompressibleActivation activation = null, string name = FUNCTION_NAME, string[] inputNames = null, string[] outputNames = null, bool gpuEnable = false) : base(FUNCTION_NAME, activation, new[] { new KeyValuePair <string, string>(PARAM_NAME, PARAM_VALUE) }, name, inputNames, outputNames, gpuEnable)
{
if (pad == Size.Empty)
{
pad = new Size(0, 0);
}
if (stride == Size.Empty)
{
stride = new Size(1, 1);
}
this._kWidth = kSize.Width;
this._kHeight = kSize.Height;
this._strideX = stride.Width;
this._strideY = stride.Height;
this._padX = pad.Width;
this._padY = pad.Height;
this.NoBias = noBias;
this.Parameters = new NdArray[noBias ? 1 : 2];
this.OutputCount = outputChannels;
this.InputCount = inputChannels;
this.Initialize(initialW, initialb);
}
public Linear(int inputCount, int outputCount, bool noBias = false, Array initialW = null, Array initialb = null, CompressibleActivation activation = null, string name = FUNCTION_NAME, string[] inputNames = null, string[] outputNames = null, bool gpuEnable = false) : base(FUNCTION_NAME, activation, name, inputNames, outputNames, gpuEnable)
{
this.OutputCount = outputCount;
this.InputCount = inputCount;
this.Weight = new NdArray(outputCount, inputCount);
this.Weight.Name = this.Name + " Weight";
this.NoBias = noBias;
this.Parameters = new NdArray[noBias ? 1 : 2];
if (initialW == null)
{
Initializer.InitWeight(this.Weight);
}
else
{
this.Weight.Data = Real.ToRealArray(initialW);
}
this.Parameters[0] = this.Weight;
if (!noBias)
{
this.Bias = new NdArray(outputCount);
this.Bias.Name = this.Name + " Bias";
if (initialb != null)
{
this.Bias.Data = Real.ToRealArray(initialb);
}
this.Parameters[1] = this.Bias;
}
}
public Deconvolution2D(int inputChannels, int outputChannels, int kSize, int subSample = 1, int trim = 0, bool noBias = false, Array initialW = null, Array initialb = null, CompressibleActivation activation = null, string name = FUNCTION_NAME, string[] inputNames = null, string[] outputNames = null, bool gpuEnable = false) : base(FUNCTION_NAME, activation, new [] { new KeyValuePair <string, string>(PARAM_NAME, PARAM_VALUE) }, name, inputNames, outputNames, gpuEnable)
{
this._kWidth = kSize;
this._kHeight = kSize;
this._trimX = trim;
this._trimY = trim;
this._subSampleX = subSample;
this._subSampleY = subSample;
this.NoBias = noBias;
this.Parameters = new NdArray[noBias ? 1 : 2];
this.OutputCount = outputChannels;
this.InputCount = inputChannels;
this.Initialize(initialW, initialb);
}
