tf.concat()

转载自：https://blog.csdn.net/appleml/article/details/71023039

https://www.cnblogs.com/mdumpling/p/8053474.html

tf.concat(concat_dim, values, name='concat')

t1 = [[1, 2, 3], [4, 5, 6]]
t2 = [[7, 8, 9], [10, 11, 12]]
tf.concat(0, [t1, t2]) == > [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]
tf.concat(1, [t1, t2]) ==> [[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]]
tf.shape(tf.concat(0, [t3, t4])) ==> [4, 3]
tf.shape(tf.concat(1, [t3, t4])) ==> [2, 6] 

一维拼接：

t1=tf.constant([1,2,3])
t2=tf.constant([4,5,6])
#concated = tf.concat(1, [t1,t2])这样会报错
t1=tf.expand_dims(tf.constant([1,2,3]),1)
t2=tf.expand_dims(tf.constant([4,5,6]),1)
concated = tf.concat(1, [t1,t2])#这样就是正确的

如果想沿着tensor新轴连接打包，则tf.concat(axis, [tf.expand_dims(t, axis) for t in tensors])，等价于tf.pack(tensors, axis=axis)，tf.pack改名为tf.stack了