PyTorch torch.hsplit function
Pytorch torch reference manual
torch.hsplitIt is a function in PyTorch used to split tensors horizontally (along columns).
Function definition
torch.hsplit(input, indices_or_sections)
Usage example
Example
import torch
# Horizontal split of a 1D tensor
x = torch.arange(10)
print("Original 1D tensor:")
print(x)
result = torch.hsplit(x, 2)
print("Split into 2 equal parts:")
for i, t in enumerate(result):
print(f" Block {i}: {t}")
# Horizontal split of a 2D tensor
y = torch.arange(12).reshape(3, 4)
print("\nOriginal 2D tensor:")
print(y)
result = torch.hsplit(y, 2)
print("Split into 2 parts along columns:")
for i, t in enumerate(result):
print(f" Block {i}:\n{t}")
# Split by indices
result = torch.hsplit(y, [1, 3])
print("\nSplit by indices [1, 3]:")
for i, t in enumerate(result):
print(f" Block {i}:\n{t}")
# Horizontal split of a 1D tensor
x = torch.arange(10)
print("Original 1D tensor:")
print(x)
result = torch.hsplit(x, 2)
print("Split into 2 equal parts:")
for i, t in enumerate(result):
print(f" Block {i}: {t}")
# Horizontal split of a 2D tensor
y = torch.arange(12).reshape(3, 4)
print("\nOriginal 2D tensor:")
print(y)
result = torch.hsplit(y, 2)
print("Split into 2 parts along columns:")
for i, t in enumerate(result):
print(f" Block {i}:\n{t}")
# Split by indices
result = torch.hsplit(y, [1, 3])
print("\nSplit by indices [1, 3]:")
for i, t in enumerate(result):
print(f" Block {i}:\n{t}")
The output result is:
原始一维张量:
tensor([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
平均分为 2 份:
块 0: tensor([0, 1, 2, 3, 4])
Chunk 1: tensor([5, 6, 7, 8, 9])
原始二维张量:
tensor([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
沿列分为 2 份:
块 0:
tensor([[0, 1],
[4, 5],
[8, 9]])
Chunk 1:
tensor([[ 2, 3],
[ 6, 7],
[10, 11]])
按索引 [1, 3] 分割:
块 0:
tensor([[0],
[4],
[8]])
Chunk 1:
tensor([[ 1, 2],
[ 5, 6],
[ 9, 10]])
Chunk 2:
tensor([[ 3],
[ 7],
[11]])
Other extensions