搭了一个神经网络，但是placeholder总是报错，说shape或者dtype不匹配，但是我输出了一下dtype和shape都是一样的啊，，有大神能解决我的问题吗？？重谢！！代码和错误说明贴在下面
出错核心部分代码：
feat_int_feature = tf.placeholder(tf.int32,shape=[1,12],name="feat_int_feature")
feat_cate_feature = tf.placeholder(tf.int32,shape=[26,8],name="feat_cate_feature")
feat_label = tf.placeholder(tf.int32,name="feat_label")
-----------------此处省略许多行-----------------------------
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
batch = 50
accurate = 0
print(np.array(int_input[0]).shape)
for i in range(2000):
print(cate_input[i])
print(np.array(cate_input[i]).shape)
print(np.array(cate_input[i].dtype))
print(np.array(y_label[i]).dtype) #检查类型和维度是否匹配
merged = tf.summary.merge_all()
sess.run(optimizer,feed_dict={'feat_int_feature:0': int_input[i],
'feat_cate_feature:0': cate_input[i],
'feat_label:0': y_label[i]})
temp = 0
if sess.run(model_output) - 0.5 >0:
temp = 1
if temp == y_label[i]:
accurate += 1
if i%50 == 0:
print(" Accuracy = \n")
print(accurate/batch)