PyTorch Transpose

Introduction

In PyTorch, the torch.transpose() function is used to reverse or permute the dimensions of a tensor. It provides a way to manipulate the order of the tensor's dimensions, thereby achieving different layouts for the data.

Syntax

The syntax for torch.transpose() is as follows:

torch.transpose(input, dim0, dim1) → Tensor

• input (Tensor): The input tensor whose dimensions are to be reversed.
• dim0 (int): The first dimension to be swapped.
• dim1 (int): The second dimension to be swapped.

Example

Let's understand how torch.transpose() works with an example:

import torch

# Create a 2D tensor
x = torch.tensor([[1, 2, 3],
                  [4, 5, 6]])

# Transpose the tensor
y = torch.transpose(x, 0, 1)

The transposed tensor y will be:

tensor([[1, 4],
        [2, 5],
        [3, 6]])

Here, the original tensor x has dimensions (2, 3). After transposing, the dimensions become (3, 2) as the first dimension (0-indexed) '0' is swapped with the second dimension '1'.

Markdown Format - Code

The code snippet that demonstrates the usage of torch.transpose() in markdown format is as below:

```python
import torch

# Create a 2D tensor
x = torch.tensor([[1, 2, 3],
                  [4, 5, 6]])

# Transpose the tensor
y = torch.transpose(x, 0, 1)

The transposed tensor y will be:

tensor([[1, 4],
        [2, 5],
        [3, 6]])

Hope this helps you understand the PyTorch `torch.transpose()` function!