TensorFlow提供两种类型的拼接:
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tf.concat(values, axis, name = 'concat' ):按照指定的已经存在的轴进行拼接 tf.stack(values, axis = 0 , name = 'stack' ):按照指定的新建的轴进行拼接 |
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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 ]] 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 ]]] 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 ]]] |
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t1 = [[ 1 , 2 , 3 ], [ 4 , 5 , 6 ]] t2 = [[ 7 , 8 , 9 ], [ 10 , 11 , 12 ]] tf.concat([t1, t2], 0 ) # [2,3] + [2,3] ==> [4, 3] tf.concat([t1, t2], 1 ) # [2,3] + [2,3] ==> [2, 6] tf.stack([t1, t2], 0 ) # [2,3] + [2,3] ==> [2*,2,3] tf.stack([t1, t2], 1 ) # [2,3] + [2,3] ==> [2,2*,3] tf.stack([t1, t2], 2 ) # [2,3] + [2,3] ==> [2,3,2*] |
以上这篇TensorFlow tensor的拼接实例就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持服务器之家。
原文链接:https://blog.csdn.net/Eric_LH/article/details/82631299