如何在某个轴上用张量填充零(Python) [英] How to pad with zeros a tensor along some axis (Python)

问题描述

我想在选定的轴上用0填充一个numpy张量. 例如，我有形状为(4,3,2)的张量r，但是我只对仅填充最后两个轴(即仅填充矩阵)感兴趣.可以使用单行python代码来做到这一点吗?

I would like to pad a numpy tensor with 0 along the chosen axis. For instance, I have tensor r with shape (4,3,2) but I am only interested in padding only the last two axis (that is, pad only the matrix). Is it possible to do it with the one-line python code?

推荐答案

您可以使用 np.pad() :

You can use np.pad():

a = np.ones((4, 3, 2))

# npad is a tuple of (n_before, n_after) for each dimension
npad = ((0, 0), (1, 2), (2, 1))
b = np.pad(a, pad_width=npad, mode='constant', constant_values=0)

print(b.shape)
# (4, 6, 5)

print(b)
# [[[ 0.  0.  0.  0.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  0.  0.  0.]
#   [ 0.  0.  0.  0.  0.]]

#  [[ 0.  0.  0.  0.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  0.  0.  0.]
#   [ 0.  0.  0.  0.  0.]]

#  [[ 0.  0.  0.  0.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  0.  0.  0.]
#   [ 0.  0.  0.  0.  0.]]

#  [[ 0.  0.  0.  0.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  1.  1.  0.]
#   [ 0.  0.  0.  0.  0.]
#   [ 0.  0.  0.  0.  0.]]]

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