问Keras自定义损失(chi2)线性回归

EN

from keras.models import Sequential
from keras.layers import Dense
from keras import optimizers
from keras import backend as K
import numpy as np

def custom_loss(y_true, y_pred):
    return K.mean(K.square(y_pred-y_true)/K.clip(K.square(0.01*y_pred), K.epsilon(), None), axis=-1)

def build_model():
    model = Sequential()
    model.add(Dense(1, input_dim=1, activation='linear'))

    sgd = optimizers.SGD(lr=0.01, momentum=0.01, nesterov=False)
    model.compile(optimizer=sgd, loss=custom_loss, metrics=['mape', 'mse', custom_loss])
    return model

if __name__ == '__main__':

    model = build_model()

    x_train = np.linspace(0.0, 1.0, 500)
    y_train = np.array(map(lambda x: x + 0.01*x*np.random.randn(1), x_train))

    model.fit(x_train, y_train, shuffle=True, epochs=1000, batch_size=10)