**Tensors**are the essential data structure in PyTorch that can have N-dimensional data. Sometimes, users may want to find a transpose of 2D or 3D tensors due to various reasons, such as changing data layout from row to column or vice versa. PyTorch provides a “transpose()” method to compute the transpose of any desired matrix by converting columns to rows and rows to columns.

This article will exemplify the method to find/compute the transpose of various tensors in PyTorch.

## How to Transpose a Tensor in PyTorch?

To transpose a particular tensor in PyTorch, first, import the PyTorch library. Then, create a desired 2D or 3D tensor. After that, find/compute the transpose of the tensor using the **“transpose()” **method. Lastly, display transposed tensor.

The basic syntax of “transpose()” method is:

Here, “0” is the first dimension, and “1” is the second dimension to be transposed.

Go through the next provided examples for a better understanding.

## Example 1: Find Transpose of 2D Tensor

In the first example, we will create a 2D tensor and find its transpose. Let’s follow the below step-by-step procedure:

**Step 1: Import PyTorch Library**

First, import the “**torch**” library to compute the transpose of the tensor:

**Step 2: Create 2D Tensor **

Then, create a 2D tensor using the **“torch.tensor()”** function and print its elements. Here, we are creating the following **“Tens1”** 2D tensor:

print(Tens1)

The tensor has been created successfully:

**Step 3: Find Transpose of Tensor **

Now, use the “transpose()” method to find the transpose of the above-created tensor:

**Step 4: Display Transposed Tensor**

Finally, print the transposed tensor and view its elements:

The below output shows the transpose of the “**Tens1**” tensor:

## Example 2: Find Transpose of 3D Tensor

In the second example, we will create a 3D tensor and find out its transpose. Let’s follow the provided steps:

**Step 1: Define 3D Tensor **

First, utilize the **“torch.tensor()”** function to create a 3D tensor and print its elements. Here, we are creating the following “**Tens2**” 3D tensor:

print(Tens2)

This has created a 3D tensor as seen below:

**Step 2: Find Transpose of Tensor **

Then, find the transpose of the above-created 3D tensor using the “transpose()” method:

**Step 3: Display Transposed Tensor**

Lastly, print the transposed tensor and view its elements:

According to the below output, the transpose of the “**Tens2**” tensor has been computed:

We have efficiently explained the method to compute a transpose of 2D or 3D tensors in PyTorch.

**Note**: You can access our Google Colab Notebook at this link.

## Conclusion

To transpose a tensor in PyTorch, first, import the “torch” library. Then, create the desired 2D or 3D tensor and view its elements. Next, use the** “transpose()”** method to find/compute the transpose of the input tensor. Lastly, print the transposed tensor and view its elements. This blog has exemplified the method to find/compute the transpose of different tensors in PyTorch.