PyTorch torch.column_stack Function
Pytorch torch Reference Manual
torch.column_stackis a function in PyTorch used to stack tensors column-wise.
Function Definition
torch.column_stack(tensors, *, out=None)
Usage Example
Example
import torch
# Stack 1D tensors column-wise
x1 = torch.tensor([1, 2, 3])
x2 = torch.tensor([4, 5, 6])
result = torch.column_stack([x1, x2])
print("1D tensor column stacking:")
print(f" x1: {x1}")
print(f" x2: {x2}")
print(f" column_stack:n{result}")
# Stack 2D tensors column-wise
y1 = torch.tensor([[1], [2], [3]])
y2 = torch.tensor([[4], [5], [6]])
result = torch.column_stack([y1, y2])
print("n2D tensor column stacking:")
print(f" y1:n{y1}")
print(f" y2:n{y2}")
print(f" column_stack:n{result}")
# Stack multiple tensors column-wise
z1 = torch.tensor([1, 2, 3])
z2 = torch.tensor([4, 5, 6])
z3 = torch.tensor([7, 8, 9])
result = torch.column_stack([z1, z2, z3])
print("nMultiple 1D tensors column stacking:")
print(f" result:n{result}")
# Stack 1D tensors column-wise
x1 = torch.tensor([1, 2, 3])
x2 = torch.tensor([4, 5, 6])
result = torch.column_stack([x1, x2])
print("1D tensor column stacking:")
print(f" x1: {x1}")
print(f" x2: {x2}")
print(f" column_stack:n{result}")
# Stack 2D tensors column-wise
y1 = torch.tensor([[1], [2], [3]])
y2 = torch.tensor([[4], [5], [6]])
result = torch.column_stack([y1, y2])
print("n2D tensor column stacking:")
print(f" y1:n{y1}")
print(f" y2:n{y2}")
print(f" column_stack:n{result}")
# Stack multiple tensors column-wise
z1 = torch.tensor([1, 2, 3])
z2 = torch.tensor([4, 5, 6])
z3 = torch.tensor([7, 8, 9])
result = torch.column_stack([z1, z2, z3])
print("nMultiple 1D tensors column stacking:")
print(f" result:n{result}")
The output result is:
一维张量列堆叠:
x1: tensor([1, 2, 3])
x2: tensor([4, 5, 6])
column_stack:
tensor([[1, 4],
[2, 5],
[3, 6]])
二维张量列堆叠:
y1:
tensor([[1],
[2],
[3]])
y2:
tensor([[4],
[5],
[6]])
column_stack:
tensor([[1, 4],
[2, 5],
[3, 6]])
多个一维张量列堆叠:
result:
tensor([[1, 4, 7],
[2, 5, 8],
[3, 6, 9]])
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