PyTorch torch.slice_scatter Function

Pytorch torch 参考手册 Pytorch torch Reference Manual

torch.slice_scatterIt is a function in PyTorch used to scatter the values of a source tensor into the slice positions of the input tensor.

Its effect is equivalent toinput[dim][start:end:step] = src, but it does not modify the original tensor; instead, it returns a new tensor.

Function Definition

torch.slice_scatterThe complete function definition is as follows:

torch.slice_scatter(input, src, dim=0, start=None, end=None, step=1)

Parameter Description

The following table liststorch.slice_scatterits various parameters:

Parameter	Type	Required	Default Value	Description
`input`	`Tensor`	Required	—	Input tensor, the tensor to be modified.
`src`	`Tensor`	Required	—	Source tensor, the values to be scattered into the input slice,its size must match the size of the slice.。
`dim`	`int`	Optional	`0`	The dimension for scattering.
`start`	`int`	Optional	`None`	Starting index (inclusiveof that index), defaults to 0.
`end`	`int`	Optional	`None`	Ending index (exclusiveof that index), defaults to the end.
`step`	`int`	Optional	`1`	Step size, with the same meaning as step in Python slicing.

Return Value

Returns the scattered new tensor (torch.Tensor), the originalinputwill not be modified.

Usage Examples

The following examples demonstratetorch.slice_scatterits common usage.

Example

import torch

# Create input tensor and source tensor
input = torch.zeros(8, 4)
src = torch.ones(2, 4)

# Scatter src into the first two rows of input
output = torch.slice_scatter(input, src, dim=0, end=2)

print("Input tensor:")
print(input)
print("\nSource tensor:")
print(src)
print("\nScatter result:")
print(output)

The output is:

输入张量:
tensor([[0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.]])

源张量:
tensor([[1., 1., 1., 1.],
        [1., 1., 1., 1.]])

散布结果:
tensor([[1., 1., 1., 1.],
        [1., 1., 1., 1.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.],
        [0., 0., 0., 0.]])

Example

import torch

# Use start and end to specify the range
input = torch.zeros(10)
src = torch.tensor([1, 2, 3])

# Scatter src to positions at indices 2-4 of input
output = torch.slice_scatter(input, src, dim=0, start=2, end=5)

print("Input:", input)
print("Source:", src)
print("Result:", output)

The output is:

输入: tensor([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
源: tensor([1., 2., 3.])
结果: tensor([0., 0., 1., 2., 3., 0., 0., 0., 0., 0.])

Example

import torch

# Use the step parameter
input = torch.zeros(10)
src = torch.tensor([1, 2])

# Step size is 2, from index 0 to 4 (exclusive), actually writes indices 0 and 2
output = torch.slice_scatter(input, src, dim=0, start=0, end=4, step=2)

print("Input:", input)
print("Source:", src)
print("Result with step 2:", output)

The output is:

输入: tensor([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
源: tensor([1., 2.])
步长为2的结果: tensor([1., 0., 2., 0., 0., 0., 0., 0., 0., 0.])

Note:torch.slice_scatterdoes not modify the original input tensor, but returns a new tensor.

This function istorch.slicethe inverse operation of.

Pytorch torch 参考手册 Pytorch torch Reference Manual

Other Extensions