public Convolution2D(Linear <T> linear) : base(linear)
{
this.SetParallel(linear.IsParallel);
this.InitFunc(new StreamingContext());
}
public void RandomTest(bool gpuEnable)
{
Python.Initialize();
Chainer.Initialize();
int inputCount = Mother.Dice.Next(1, 50);
int outputCount = Mother.Dice.Next(1, 50);
int batchCount = Mother.Dice.Next(1, 5);
Real[,] input = (Real[, ])Initializer.GetRealNdArray(new[] { batchCount, inputCount });
Real[,] dummyGy = (Real[, ])Initializer.GetRealNdArray(new[] { batchCount, outputCount });
Real[,] w = (Real[, ])Initializer.GetRealNdArray(new[] { outputCount, inputCount });
Real[] b = Initializer.GetRealArray(outputCount);
//Chainer
NChainer.Linear <Real> cLinear = new NChainer.Linear <Real>(inputCount, outputCount, false, Real.ToBaseNdArray(w), Real.ToBaseArray(b));
Variable <Real> cX = new Variable <Real>(Real.ToBaseNdArray(input));
Variable <Real> cY = cLinear.Forward(cX);
cY.Grad = Real.ToBaseNdArray(dummyGy);
cY.Backward();
//KelpNet
KelpNet.CL.Linear linear = new KelpNet.CL.Linear(inputCount, outputCount, false, w, b, gpuEnable: gpuEnable);
NdArray x = new NdArray(Real.ToRealArray(input), new[] { inputCount }, batchCount);
NdArray y = linear.Forward(x)[0];
y.Grad = Real.ToRealArray(dummyGy);
y.Backward();
Real[] cYdata = Real.ToRealArray((Real[, ])cY.Data);
Real[] cXgrad = Real.ToRealArray((Real[, ])cX.Grad);
Real[] cWgrad = Real.ToRealArray((Real[, ])cLinear.W.Grad);
Real[] cbgrad = (Real[])cLinear.b.Grad;
//許容範囲を算出
double delta = 0.00001;
//y
Assert.AreEqual(cYdata.Length, y.Data.Length);
for (int i = 0; i < y.Data.Length; i++)
{
Assert.AreEqual(cYdata[i], y.Data[i], delta);
}
//x.grad
Assert.AreEqual(cXgrad.Length, x.Grad.Length);
for (int i = 0; i < x.Grad.Length; i++)
{
Assert.AreEqual(cXgrad[i], x.Grad[i], delta);
}
//W.grad
Assert.AreEqual(cWgrad.Length, linear.Weight.Grad.Length);
for (int i = 0; i < linear.Weight.Grad.Length; i++)
{
Assert.AreEqual(cWgrad[i], linear.Weight.Grad[i], delta);
}
//b.grad
Assert.AreEqual(cbgrad.Length, linear.Bias.Grad.Length);
for (int i = 0; i < linear.Bias.Grad.Length; i++)
{
Assert.AreEqual(cbgrad[i], linear.Bias.Grad[i], delta);
}
}
public Convolution2D(Linear linear) : base(linear)
{
this.SetParallel(linear.IsParallel);
}
