python - 从 block 对角线 PyTorch 张量中提取 block

Question

我有一个形状为 (m*n, m*n) 的张量，我想提取一个大小为 (n, m*n) 的张量，其中包含对角线上大小为 n*n 的 m 个块。例如:

>>> a
tensor([[1, 2, 0, 0],
        [3, 4, 0, 0],
        [0, 0, 5, 6],
        [0, 0, 7, 8]])

我想要一个函数 extract(a, m, n)这将输出:

>>> extract(a, 2, 2)
tensor([[1, 2, 5, 6],
        [3, 4, 7, 8]])

我想过使用某种切片，因为块可以表示为:

>>> for i in range(m):
...     print(a[i*m: i*m + n, i*m: i*m + n])
tensor([[1, 2],
        [3, 4]])
tensor([[5, 6],
        [7, 8]])

Answer 1

您可以利用 reshape和切片:

import torch
import numpy as np

def extract(a, m, n):
  s=(range(m), np.s_[:], range(m), np.s_[:])  # the slices of the blocks
  a.reshape(m, n, m, n)[s]  # reshaping according to blocks and slicing
  return a.reshape(m*n, n).T  # reshape to desired output format

例子:

a = torch.arange(36).reshape(6,6)
extract(a, 3, 2)

tensor([[ 0,  6, 14, 20, 28, 34],
        [ 1,  7, 15, 21, 29, 35]])

extract(a, 2, 3)

tensor([[ 0,  6, 12, 21, 27, 33],
        [ 1,  7, 13, 22, 28, 34],
        [ 2,  8, 14, 23, 29, 35]])