keras_utils.py 文件源码

def weighted_binary_crossentropy(feature_weights):
    def loss(y_true, y_pred):
        # try:
        #     x = K.binary_crossentropy(y_pred, y_true)
        #     # y = tf.Variable(feature_weights.astype('float32'))
        #     # z = K.dot(x, y)
        #     y_true = tf.pow(y_true + 1e-5, .75)
        #     y2 = tf.div(y_true, tf.reshape(K.sum(y_true, 1), [-1, 1]))
        #     z = K.sum(tf.mul(x, y2), 1)
        # except Exception as e:
        #     print e
        #     import pdb;pdb.set_trace()
        # return z
        return K.dot(K.binary_crossentropy(y_pred, y_true), K.variable(feature_weights.astype('float32')))
    return loss