# .sum()

In PyTorch, the ** .sum()** function is used to compute the sum of all elements in the input tensor. This function is part of the

`torch`

package.## Syntax

To calculate the sum of all elements, the following syntax is used:

```
torch.sum(input, *, dtype=None)
```

`input`

: The input tensor.`dtype`

(Optional): The data type of the output tensor.

To calculate the sum along specific dimensions, the following syntax is used:

```
torch.sum(input, *, dim=None, keepdim=False, out=None)
```

`input`

: The input tensor.`dim`

(Optional): Specifies the dimension(s) along which the sum is computed. If not specified, the sum is computed over all elements.`keepdim`

(Optional): If set to`True`

, the output tensor retains dimensions of size*1*for the reduced dimensions. The default is`False`

.`out`

(Optional): A tensor to store the output into. If not provided, a new tensor is created.

## Example 1

In this example, the sum of all elements in the input tensor `[[1, 2], [3, 4]]`

is computed, resulting in a tensor with a single element `10`

. The sum is calculated as `1 + 2 + 3 + 4 = 10`

:

import torch# Create a tensortensor = torch.tensor([[1, 2], [3, 4]])# Compute the sum of all elements in the tensorsum_tensor = torch.sum(tensor)print(sum_tensor)

Here is the output for the above example:

tensor(10)

## Example 2

In this example, the sum is computed along the columns of the input tensor `[[1, 2], [3, 4]]`

, resulting in a tensor with two elements `[4, 6]`

. The sum along the columns is calculated as `[1 + 3, 2 + 4] = [4, 6]`

:

import torch# Create a tensortensor = torch.tensor([[1, 2], [3, 4]])# Compute the sum along the rows of the tensorsum_rows = torch.sum(tensor, dim=0)print(sum_rows)

Here is the output for the above example:

tensor([4, 6])

Specifying the `dim`

parameter customizes the dimension along which the sum is computed, providing flexibility in handling multi-dimensional tensors.

### Contribute to Docs

- Learn more about how to get involved.
- Edit this page on GitHub to fix an error or make an improvement.
- Submit feedback to let us know how we can improve Docs.