public void EmbedIDRandomTest()
{
Python.Initialize();
Chainer.Initialize();
int inputCount = Mother.Dice.Next(2, 30);
int outputCount = Mother.Dice.Next(1, 30);
int batchCount = Mother.Dice.Next(1, 5);
int[,] input = (int[, ])Enumerable.Repeat(0, batchCount * inputCount).ToNdArray(batchCount, inputCount);
input[0, 0] = 1;
Real[,,] dummyGy = Initializer.GetRandomValues <Real[, , ]>(batchCount, inputCount, outputCount);
Real[,] w = Initializer.GetRandomValues <Real[, ]>(inputCount, outputCount);
//Chainer
NChainer.EmbedID <Real> cEmbedId = new NChainer.EmbedID <Real>(inputCount, outputCount, w);
Variable <int> cX = new Variable <int>(input);
Variable <Real> cY = cEmbedId.Forward(cX);
cY.Grad = dummyGy;
cY.Backward();
//KelpNet
EmbedID <Real> embedId = new EmbedID <Real>(inputCount, outputCount, w);
NdArray <Real> x = new NdArray <Real>(input, asBatch: true);
NdArray <Real> y = embedId.Forward(x)[0];
y.Grad = dummyGy.Flatten();
y.Backward();
Real[] cYdata = ((Real[, , ])cY.Data).Flatten();
Real[] cWgrad = ((Real[, ])cEmbedId.W.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);
}
//W.grad
Assert.AreEqual(cWgrad.Length, embedId.Weight.Grad.Length);
for (int i = 0; i < embedId.Weight.Grad.Length; i++)
{
Assert.AreEqual(cWgrad[i], embedId.Weight.Grad[i], delta);
}
}
