public void LRNRandomTest()
{
Python.Initialize();
Chainer.Initialize();
int n = Mother.Dice.Next(2, 7);
float k = (float)Mother.Dice.NextDouble() * 3;
int batchCount = Mother.Dice.Next(1, 5);
int ch = Mother.Dice.Next(1, 5);
int width = Mother.Dice.Next(1, 16);
int height = Mother.Dice.Next(1, 16);
Real[,,,] input = (Real[, , , ])Initializer.GetRealNdArray(new[] { batchCount, ch, height, width });
Real[,,,] dummyGy = (Real[, , , ])Initializer.GetRealNdArray(new[] { batchCount, ch, height, width });
//chainer
NChainer.LocalResponseNormalization <Real> cLocalResponseNormalization = new NChainer.LocalResponseNormalization <Real>(n, k);
Variable <Real> cX = new Variable <Real>(Real.ToBaseNdArray(input));
Variable <Real> cY = cLocalResponseNormalization.Forward(cX);
cY.Grad = Real.ToBaseNdArray(dummyGy);
cY.Backward();
//kelpnet
KelpNet.LRN lrn = new LRN(n, k);
NdArray x = new NdArray(Real.ToRealArray(input), new[] { ch, height, width }, batchCount);
NdArray y = lrn.Forward(x)[0];
y.Grad = Real.ToRealArray(dummyGy);
y.Backward();
Real[] cYdata = Real.ToRealArray((Real[, , , ])cY.Data);
Real[] cXgrad = Real.ToRealArray((Real[, , , ])cX.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);
}
}
public void LRNRandomTest()
{
Python.Initialize();
Chainer.Initialize();
int n = Mother.Dice.Next(2, 7);
float k = (float)Mother.Dice.NextDouble() * 3;
int batchCount = Mother.Dice.Next(1, 5);
int ch = Mother.Dice.Next(1, 5);
int width = Mother.Dice.Next(1, 16);
int height = Mother.Dice.Next(1, 16);
Real[,,,] input = Initializer.GetRandomValues <Real[, , , ]>(batchCount, ch, height, width);
Real[,,,] dummyGy = Initializer.GetRandomValues <Real[, , , ]>(batchCount, ch, height, width);
//chainer
LocalResponseNormalization <Real> cLocalResponseNormalization = new LocalResponseNormalization <Real>(n, k);
Variable <Real> cX = new Variable <Real>(input);
Variable <Real> cY = cLocalResponseNormalization.Forward(cX);
cY.Grad = dummyGy;
cY.Backward();
//kelpnet
LRN <Real> lrn = new LRN <Real>(n, k);
NdArray <Real> x = new NdArray <Real>(input, asBatch: true);
NdArray <Real> y = lrn.Forward(x)[0];
y.Grad = dummyGy.Flatten();
y.Backward();
Real[] cYdata = ((Real[, , , ])cY.Data).Flatten();
Real[] cXgrad = ((Real[, , , ])cX.Grad).Flatten();
//許容範囲を算出
Real delta = 0.00001f;
//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);
}
}
