MSE−均方误差MSE-均方误差MSE−均方误差
补充：reduce操作是用来减维度
一 TF2.0
1.1 类实现
class MeanSquaredError(tf.keras.losses.Loss):def call(self, y_true, y_pred):return tf.reduce_mean(tf.square(y_pred - y_true))
a = tf.constant([0., 0., 1., 1.])b = tf.constant([1., 1., 1., 0.])
mse = MeanSquaredError()
mse(a,b)
1.2 函数式实现
def MeanSquaredError( y_true, y_pred):return tf.reduce_mean(tf.square(y_pred - y_true))
mse = MeanSquaredError(a,b)mse
1.3 tf2.0的keras高阶API
mse = tf.keras.losses.MeanSquaredError()loss = mse([0., 0., 1., 1.], [1., 1., 1., 0.])print('Loss: ', loss.numpy()) # Loss: 0.75
