Here are the examples of the java api cn.centipede.numpy.NDArray.subtract() taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.
3 Examples
17
Source : LossFunction.java
with MIT License
from DRL-CASIA
with MIT License
from DRL-CASIA
public static NDArray MES_loss(NDArray y_pre, NDArray y) {
// loss = np.sum((y_pre - y) ** 2)
NDArray loss = np.abs(y_pre.subtract(y));
return loss;
}
17
Source : LossFunction.java
with MIT License
from DRL-CASIA
with MIT License
from DRL-CASIA
public static NDArray Softmax_cross_loss(NDArray y_pre, NDArray y) {
NDArray softmax = np.exp(y_pre).divide(np.sum(np.exp(y_pre), 0));
// loss = - np.sum(y * np.log(softmax))
NDArray loss = softmax.subtract(y);
return loss;
}
14
Source : Softmax.java
with MIT License
from DRL-CASIA
with MIT License
from DRL-CASIA
public NDArray loss(NDArray predict, NDArray label) {
int[] pdimens = predict.shape();
int batchsize = pdimens[0];
predict(predict);
NDArray delta = np.zeros(pdimens);
double loss = 0;
for (int i = 0; i < batchsize; i++) {
NDArray label_i = label.row(i);
NDArray softmanx_i = this.softmax.row(i);
delta.set(softmanx_i.subtract(label_i), i);
loss -= np.sum(np.log(softmanx_i).multiply(label_i));
}
loss /= batchsize;
System.out.printf("Softmax: loss=%f\n", loss);
return delta;
}