# How to perform an expand operation in PyTorch?

Tensor.expand() attribute is used to perform expand operation. It expands the Tensor to new dimensions along the singleton dimension.

• Expanding a tensor only creates a new view of the original tensor; it doesn't make a copy of the original tensor.

• If you set a particular dimension as -1, the tensor will not be expanded along this dimension.

• For example, if we have a tensor of size (3,1), we can expand this tensor along the dimension of size 1.

## Steps

To expand a tensor, one could follow the steps given below −

• Import the torch library. Make sure you have already installed it.

import torch
• Define a tensor having at least one dimension as singleton.

t = torch.tensor([,,])

• Expand the tensor along the singleton dimension. Expanding along a non-singleton dimension will throw a Runtime Error (see Example 3).

t_exp = t.expand(3,2)
• Display the expanded tensor.

print("Tensor after expand:", t_exp)


## Example 1

The following Python program shows how to expand a tensor of size (3,1) to a tensor of size (3,2). It expands the tensor along the dimension size of 1. The other dimension of size 3 remains unchanged.

# import required libraries
import torch

# create a tensor
t = torch.tensor([,,])

# display the tensor
print("Tensor:", t)
print("Size of Tensor:", t.size())

# expand the tensor
exp = t.expand(3,2)
print("Tensor after expansion:", exp)

## Output

Tensor:
tensor([,
,
])
Size of Tensor:
torch.Size([3, 1])
Tensor after expansion:
tensor([[1, 1],
[2, 2],
[3, 3]])

## Example 2

The following Python program expands a tensor of size (1,3) to a tensor of size (3,3). It expands the tensor along the dimension size of 1.

# import required libraries
import torch

# create a tensor
t = torch.tensor([[1,2,3]])

# display the tensor
print("Tensor:", t)

# size of tensor is [1,3]
print("Size of Tensor:", t.size())

# expand the tensor
expandedTensor = t.expand(3,-1)

print("Expanded Tensor:", expandedTensor)
print("Size of expanded tensor:", expandedTensor.size())

## Output

Tensor:
tensor([[1, 2, 3]])
Size of Tensor:
torch.Size([1, 3])
Expanded Tensor:
tensor([[1, 2, 3],
[1, 2, 3],
[1, 2, 3]])
Size of expanded tensor:
torch.Size([3, 3])

## Example 3

In the following Python program, we tried to expand the tensor along a nonsingleton dimension, hence it throws a Runtime Error.

# import required libraries
import torch

# create a tensor
t = torch.tensor([[1,2,3]])

# display the tensor
print("Tensor:", t)

# size of tensor is [1,3]
print("Size of Tensor:", t.size())
t.expand(3,4)

## Output

Tensor:
tensor([[1, 2, 3]])
Size of Tensor:
torch.Size([1, 3])

RuntimeError: The expanded size of the tensor (4) must match the existing size (3) at non-singleton dimension 1. Target sizes: [3, 4]. Tensor sizes: [1, 3]