tf.transpose()的用法
一、tensorflow官方文档内容
transpose(
a,
perm = None ,
name = 'transpose'
)
|
Defined in tensorflow/python/ops/array_ops.py
.
See the guides: Math > Matrix Math Functions, Tensor Transformations > Slicing and Joining
Transposes a
. Permutes the dimensions according to perm
.
The returned tensor's dimension i will correspond to the input dimension perm[i]
. If perm
is not given, it is set to (n-1...0), where n is the rank of the input tensor. Hence by default, this operation performs a regular matrix transpose on 2-D input Tensors.
For example:
# 'x' is [[1 2 3]
# [4 5 6]]
tf.transpose(x) = = > [[ 1 4 ]
[ 2 5 ]
[ 3 6 ]]
# Equivalently
tf.transpose(x, perm = [ 1 , 0 ]) = = > [[ 1 4 ]
[ 2 5 ]
[ 3 6 ]]
# 'perm' is more useful for n-dimensional tensors, for n > 2
# 'x' is [[[1 2 3]
# [4 5 6]]
# [[7 8 9]
# [10 11 12]]]
# Take the transpose of the matrices in dimension-0
tf.transpose(x, perm = [ 0 , 2 , 1 ]) = = > [[[ 1 4 ]
[ 2 5 ]
[ 3 6 ]]
[[ 7 10 ]
[ 8 11 ]
[ 9 12 ]]]
|
Args:
-
a
: ATensor
. -
perm
: A permutation of the dimensions ofa
. -
name
: A name for the operation (optional).
Returns:
A transposed Tensor
.
二、中文翻译
transpose(
a,
perm = None ,
name = 'transpose'
)
|
Defined in tensorflow/python/ops/array_ops.py
.
See the guides: Math > Matrix Math Functions, Tensor Transformations > Slicing and Joining
a的转置是根据 perm 的设定值来进行的。
返回数组的 dimension(尺寸、维度) i与输入的 perm[i]的维度相一致。如果未给定perm,默认设置为 (n-1...0),这里的 n 值是输入变量的 rank 。因此默认情况下,这个操作执行了一个正规(regular)的2维矩形的转置。
例子:
# 'x' is [[1 2 3]
# [4 5 6]]
tf.transpose(x) = = > [[ 1 4 ]
[ 2 5 ]
[ 3 6 ]]
# Equivalently(等价于)
tf.transpose(x, perm = [ 1 , 0 ]) = = > [[ 1 4 ]
[ 2 5 ]
[ 3 6 ]]
# 'perm' is more useful for n-dimensional tensors, for n > 2
# 'x' is [[[1 2 3]
# [4 5 6]]
# [[7 8 9]
# [10 11 12]]]
# Take the transpose of the matrices in dimension-0
tf.transpose(x, perm = [ 0 , 2 , 1 ]) = = > [[[ 1 4 ]
[ 2 5 ]
[ 3 6 ]]
[[ 7 10 ]
[ 8 11 ]
[ 9 12 ]]]
|
参数:
-
a
: a 是一个张量(Tensor) -
perm
: perm 是 a 维度的置换 -
name
:操作的名称(可选).
返回值:
返回的是一个转置的张量。
三、解释
tf.transpose(input, [dimension_1, dimenaion_2,..,dimension_n]):这个函数主要适用于交换输入张量的不同维度用的,如果输入张量是二维,就相当是转置。dimension_n是整数,如果张量是三维,就是用0,1,2来表示。这个列表里的每个数对应相应的维度。如果是[2,1,0],就把输入张量的第三维度和第一维度交换。
---------------------------------- 参考链接: 1、 tf.transpose函数的用法: https://i.cnblogs.com/EditPosts.aspx?opt=1 2、 tensorflow中的不懂得知识点——转置函数 transpose : http://blog.****.net/u010417185/article/details/51900441 3、tensorflow官方文档: https://www.tensorflow.org/versions/r1.3/api_docs/python/tf/transpose 转自:https://www.cnblogs.com/hezhiyao/p/8476160.html