np.pad(array，pad_width，mode，**kwargs) # 返回填充后的numpy数组
array：要填充的numpy数组【要对谁进行填充】
pad_width：每个轴要填充的数据的数目【每个维度前、后各要填充多少个数据】
mode：填充的方式【采用哪种方式填充】
import numpy as np
# 一维
a = np.array([1, 2, 3, 4, 5])
print("a.shape", a.shape)
b = np.pad(a, 1, 'constant')
print("b = ", b)
c = np.pad(a, (1, 2), 'constant')
print("c.shape", c.shape)
print("c = ", c)
print("----------------------------------")
# 二维
d = np.array([[1, 2], [3, 4]])
print("d.shape", d.shape)
e = np.pad(d, (1, 2), 'constant')
print("e = ")
print(e)
f = np.pad(d, ((1, 2), (3, 4)), 'constant')
print("f = ")
print(f)
print("----------------------------------")
# 三维
arr = np.array([[[1, 2, 3], [4, 5, 6], [7, 8, 9]]])
arr_pad = np.pad(arr, ((1, 1), (1, 2), (3, 4)), 'constant')
print("arr.shape", arr.shape)
print(arr_pad)
print("----------------------------------")
# 四维
img = np.array([[[[1, 2],
[5, 6],
[9, 10],
[13,14]]]])
pad = 1
print("img.shape", img.shape)
img_pad = np.pad(img, [(1,1), (1,1), (pad, pad), (pad, pad)], "constant")
print(img_pad)
a.shape (5,) b = [0 1 2 3 4 5 0] c.shape (8,) c = [0 1 2 3 4 5 0 0] ---------------------------------- d.shape (2, 2) e = [[0 0 0 0 0] [0 1 2 0 0] [0 3 4 0 0] [0 0 0 0 0] [0 0 0 0 0]] f = [[0 0 0 0 0 0 0 0 0] [0 0 0 1 2 0 0 0 0] [0 0 0 3 4 0 0 0 0] [0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0]] ---------------------------------- arr.shape (1, 3, 3) [[[0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0]] [[0 0 0 0 0 0 0 0 0 0] [0 0 0 1 2 3 0 0 0 0] [0 0 0 4 5 6 0 0 0 0] [0 0 0 7 8 9 0 0 0 0] [0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0]] [[0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0]]] ---------------------------------- img.shape (1, 1, 4, 2) [[[[ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0]] [[ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0]] [[ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0]]] [[[ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0]] [[ 0 0 0 0] [ 0 1 2 0] [ 0 5 6 0] [ 0 9 10 0] [ 0 13 14 0] [ 0 0 0 0]] [[ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0]]] [[[ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0]] [[ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0]] [[ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0] [ 0 0 0 0]]]]