如何定义在构建tensorflow图时需要输入numpy数组(而不是张量)的损失函数？

import tensorflow as tf
import numpy as np

input_placeholder = tf.placeholder(tf.float32, shape=(None, input_shape))
target_placeholder = tf.placeholder(tf.float32, shape=(None, target_shape))

input_tensor = tf.convert_to_tensor(input_numpy_array)
target_tensor = tf.convert_to_tensor(target_numpy_array)

loss = tf.reduce_mean(tf.square(input_placeholder - target_tensor))

with tf.Session() as sess:
    loss_value = sess.run(loss, feed_dict={input_placeholder: input_numpy_array, target_placeholder: target_numpy_array})
    print("损失函数值：", loss_value)