tf.concat(values, axis, name=‘concat’)：按照指定的已经存在的轴进行拼接
t1 = [[1, 2, 3], [4, 5, 6]]
t2 = [[7, 8, 9], [10, 11, 12]]
tf.concat([t1, t2], 0)
==>
[
[1, 2, 3]
[4, 5, 6]
[7, 8, 9]
[10, 11, 12]
]
按照行拼接，多了两行
tf.concat([t1, t2], 1)
==>
[
[1, 2, 3, 7, 8, 9]
[4, 5, 6, 10, 11, 12]
]
按照接拼接，多了三列
类似的函数还有一个tf.stack
tf.stack(values, axis=0, name=‘stack’)：按照指定的新建的轴进行拼接
tf.concat([t1, t2], 1)
==>
[
[1, 2, 3, 7, 8, 9]
[4, 5, 6, 10, 11, 12]
]
tf.stack([t1, t2], 0)
==>
[
[[1, 2, 3], [4, 5, 6]]
[[7, 8, 9], [10, 11, 12]]
]
结果是三维矩阵，就0维和1维像堆叠在一起一样
tf.stack([t1, t2], 1) ==> [[[1, 2, 3], [7, 8, 9]], [[4, 5, 6], [10, 11, 12]]]
tf.stack([t1, t2], 2) ==> [[[1, 7], [2, 8], [3, 9]], [[4, 10], [5, 11], [6, 12]]]
例子参见：
https://colab.research.google.com/drive/1MWUJKxqbXHeVmzh3JctTRTNDtBf7WF-4