PyTorch torch.flipud 函数
Pytorch torch 参考手册torch.flipud 是 PyTorch 中用于上下翻转（垂直翻转）张量的函数。
函数定义
torch.flipud(input)
使用示例
实例
import torch
# 二维张量上下翻转
x = torch.arange(12).reshape(3, 4)
print("原始张量:")
print(x)
result = torch.flipud(x)
print("上下翻转:")
print(result)
# 方阵上下翻转
y = torch.tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print("n3x3 方阵:")
print(y)
result = torch.flipud(y)
print("上下翻转:")
print(result)
# 一维张量上下翻转
z = torch.tensor([1, 2, 3, 4])
result = torch.flipud(z)
print("n一维张量 [1, 2, 3, 4]:")
print("上下翻转:", result)
# 二维张量上下翻转
x = torch.arange(12).reshape(3, 4)
print("原始张量:")
print(x)
result = torch.flipud(x)
print("上下翻转:")
print(result)
# 方阵上下翻转
y = torch.tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print("n3x3 方阵:")
print(y)
result = torch.flipud(y)
print("上下翻转:")
print(result)
# 一维张量上下翻转
z = torch.tensor([1, 2, 3, 4])
result = torch.flipud(z)
print("n一维张量 [1, 2, 3, 4]:")
print("上下翻转:", result)
输出结果为：
原始张量:
tensor([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
上下翻转:
tensor([[ 8, 9, 10, 11],
[ 4, 5, 6, 7],
[ 0, 1, 2, 3]])
3x3 方阵:
tensor([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
上下翻转:
tensor([[7, 8, 9],
[4, 5, 6],
[1, 2, 3]])
一维张量 [1, 2, 3, 4]:
上下翻转: tensor([4, 3, 2, 1])