numpy 和 torch 的维度调整

1、numpy

import numpy as np

a = np.random.random((1, 2, 3))
print(a.shape)

# 转为一维
b = a.ravel()
print(b.shape)

# 或则用以下方法转为一维
b_ = a.flatten()
print(b_.shape)

# reshape(n1,n2,...，ni)将数组转换成特定维度
# n1*n2*...*ni = 转换前数组元素的总数
c = a.reshape((2, 3))
print(c.shape)


# transpose转换坐标系,transpose(1, 2, 0)括号里的值表示坐标系的索引号
# 原始的坐标系为[c,h,w]  0-c,1-h,2-w
# 变换后的坐标系统[h,w,c]
d = a.transpose((1, 2, 0))
print(d.shape)

2、torch

import torch

a = torch.rand(1, 2, 3)
print(a.shape)

# 用 transpose
# 但是改方法只能进行2D tensor的转置
b = a.transpose(0, 1)
print(b.shape)

# 用 permute 推荐用它
# 对任意高维矩阵进行转置
b_ = a.permute(1, 2, 0)
print(b_.shape)