PyTorch torch.flipud Function
PyTorch torch Reference Manual
torch.flipudA function in PyTorch used to flip a tensor upside down (vertically flip).
Function Definition
torch.flipud(input)
Usage Examples
Example
import torch
# Flip a 2D tensor upside down
x = torch.arange(12).reshape(3, 4)
print("Original tensor:")
print(x)
result = torch.flipud(x)
print("Flipped upside down:")
print(result)
# Flip a square matrix upside down
y = torch.tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print("3x3 square matrix:")
print(y)
result = torch.flipud(y)
print("Flipped upside down:")
print(result)
# Flip a 1D tensor upside down
z = torch.tensor([1, 2, 3, 4])
result = torch.flipud(z)
print("1D tensor [1, 2, 3, 4]:")
print("Flipped upside down:", result)
# Flip a 2D tensor upside down
x = torch.arange(12).reshape(3, 4)
print("Original tensor:")
print(x)
result = torch.flipud(x)
print("Flipped upside down:")
print(result)
# Flip a square matrix upside down
y = torch.tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print("3x3 square matrix:")
print(y)
result = torch.flipud(y)
print("Flipped upside down:")
print(result)
# Flip a 1D tensor upside down
z = torch.tensor([1, 2, 3, 4])
result = torch.flipud(z)
print("1D tensor [1, 2, 3, 4]:")
print("Flipped upside down:", result)
The output is:
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])
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