import numpy as np
import tensorflow as tf
y_pred = np.array([[1],
[2],
[3]],dtype=np.float32)
y_real = np.array([[1],
[1],
[1]])
bias = np.array([1,2,3,4],dtype=np.float32)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
Input = tf.reduce_mean(tf.square(y_pred-y_real))
# =============================================================================
# tf.square(y_pred-y_real)
# [[0]
# [1]
# [4]]
# =============================================================================
result = sess.run(Input)
print(result)
#返回1.6666666666666667,如果不加轴的话,返回的是一个数