ValueError: setting an array element with a sequence.????

Question

在只使用Tensorflow内置库的情况下，完成线性回归，结果出现ValueError: setting an array element with a sequence错误。之前找的相关回答，都是有其它库介入的情况的错误，比如numpy。而我现在遇到的错误Queue一直不能修正。这个技术难度应该不大，但是我一直没能找到合适解决办法，希望大家可以帮忙看一下！

import tensorflow as tf

x_data = tf.Variable(tf.random_normal([2000, 3]))  # random test data
noise = tf.Variable(tf.random_normal([2000, 1]))  # random noise
w_real = tf.constant([[3.0, 5.1, 1.7]])  # weight
b_real = tf.constant(-0.2)  # bias
y_data = tf.Variable(tf.matmul(x_data, tf.transpose(w_real)) + b_real + noise)

NUM_STEPS = 10

x = tf.placeholder(dtype=tf.float32, shape=[None, 3], name="x_train")
y_true = tf.placeholder(dtype=tf.float32, shape=None, name="y_true")

with tf.name_scope("inference") as scope:
    w = tf.Variable(tf.zeros([3, 1]))
    b = tf.Variable(0.0)
    y_pred = tf.matmul(x, w) + b

with tf.name_scope("loss") as scope:
    loss = tf.reduce_mean(1 / 2 * tf.square(y_pred - y_true))

with tf.name_scope("train") as scope:
    learning_rate = 0.1
    optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)
    train = optimizer.minimize(loss)

init = tf.global_variables_initializer()
with tf.Session() as sess:
    sess.run(init)
    for step in range(NUM_STEPS):
        sess.run(train, feed_dict={x: x_data, y_true: y_data})
        print(step, sess.run([w, b]))
    tf.summary.FileWriter("./graph", sess.graph)

Answer 1

tensorflow的输入必须array必须是n*n（2*2或者3*3），即行和列数必须一致。