This article will illustrate different methods to narrow down tensors in PyTorch.

## Method 1: Narrow Down Tensors Using “torch.narrow()” Method in PyTorch

The basic syntax of the “torch.narrow()” method is given below:

Here:

- “
**input_tensor**” is the desired tensor that is required to narrow down. - “
**dim**” is the dimension along which the tensor will be narrowed down. - “
**start**” is the starting index along the specified dimension. - “
**length**” is the number of elements to include along the specified dimension.

To narrow down a specific tensor using the “torch.narrow()” method in PyTorch, follow the below-provided steps:

**Step 1: Import PyTorch Library**

First, import the “**torch**” library to narrow down a PyTorch tensor:

**Step 2: Create a Tensor **

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

print(tens)

This has created the tensor as seen below:

**Step 3: View Tensor Size**

Next, use the **“size()”** attribute to view the size of the above-created “**tens**” tensor:

The size/shape of the “**tens**” tensor is 3×3:

**Step 4: Narrow Down Tensor**

Now, narrow down the tensor using the “**torch.narrow(<tensor>, <dim>, <start>, <length>)**” method. It is required to specify the input tensor, specific dimension, starting dimension, and ending length. Here, we are narrowing the “**tens**” tensor with the following arguments:

Here:

- “
**tens**” is the input tensor to narrow. - “
**0**” is the dimension to narrow down the tensor along the first row. - “
**1**” is the starting dimension to start the tensor from the second row. - “
**2**” is the length which indicates that the 2 rows will be included from the original tensor:

**Step 5: Display Narrowed Tensor and Its Size**

Finally, display the elements of the narrowed tensor and its size:

print(nar_tens.size())

According to the below output, the tensor has been narrowed successfully:

Similarly, users can also narrow down the tensor in other dimensions, such as “1”:

## Method 2: Narrow Down Tensor Using “Tensor.narrow()” Method in PyTorch

The basic syntax of the “Tensor.narrow()” method is given below:

Here, “**Tensor**” is the input tensor to narrow. The remaining arguments are the same as in the above method.

To narrow down a particular tensor using the “Tensor.narrow()” method in PyTorch, check out the below-listed steps:

**Step 1: Import PyTorch Library**

First, import the “**torch**” library to narrow down a tensor:

**Step 2: Create a Tensor **

Then, use the “**torch.tensor()**” function to create a desired tensor and print its elements. Here, we are creating the following “**T1**” 2D tensor:

print(T1)

The below output shows that the ‘**T1**” tensor has been created successfully:

**Step 3: View Tensor Size**

Next, view the size of the above-created “**T1**” tensor using the **“size()”** attribute:

It can be observed that the size of the “**T1**” tensor is 4×3:

**Step 4: Narrow Down Tensor**

Now, use the **“Tensor.narrow(<dim>, <start>, <length>)”** method to narrow down the “**T1**” tensor. It is required to specify the input tensor, specific dimension, starting dimension, and ending length. Here, we are narrowing the “**T1**” tensor with the following arguments:

**Step 5: Display Narrowed Tensor and Its Size**

Lastly, display the elements of the narrowed tensor and its size:

print(N_tens.size())

In the below output, the elements of the tensor and its size indicate that the tensor has been narrowed successfully:

Similarly, users can also narrow down the tensor in other dimensions and starting index as seen below:

We have efficiently explained the methods to narrow down tensors in PyTorch.

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

## Conclusion

To narrow down a tensor in PyTorch, first, import “**torch**” library. Then, create the desired tensor and view its elements and size. After that, use the **“torch.narrow(<tensor>, <dim>, <start>, <length>)”** or **“Tensor.narrow(<dim>, <start>, <length>)”** method to narrow down the input tensor. Lastly, display the elements of the narrowed tensor and its size. This article has illustrated different methods to narrow down tensors in PyTorch.