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。