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Original file line number Diff line number Diff line change
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---
Title: '.index_select()'
Description: 'Extract specific elements from a tensor and return a new tensor.'
Subjects:
- 'AI'
- 'Data Science'
Tags:
- 'AI'
- 'Arrays'
- 'Data Structures'
- 'Deep Learning'
CatalogContent:
- 'intro-to-py-torch-and-neural-networks'
- 'paths/computer-science'
---

**`Index_select()`** is used to extract specific elements (rows, columns) from the tensor to return a new tensor.

## Syntax

```pseudo
torch.index_select(input, dim, index, out)
```

- `input`: The input tensor.
- `dim`: The dimension to index (0 for rows, 1 for columns).
- `index`: The 1-D tensor containing the indices to select.
- `out` (optional): The output tensor (optional).

Note: If the result is to be stored in an existing tensor, the output tensor can be specified using the optional out argument.

## Example

The following example demonstrates the use of `.index_select()`:

```py
import torch

#Define a tensor
ten = torch.tensor([[1, 2, 3, -8],
[4, 3, 8, 0],
[-1, 7, 6, 3],
[5, 6, 9, 0]])

indices = torch.tensor([0, 2])

#Define a new tensor using index_select
r = torch.index_select(ten, 0, indices)
print(r)

#Define a new tensor using index_select
c = torch.index_select(ten, 1, indices)
print(c)
```

```shell
tensor([[1, 2, 3, -8],
[-1, 7, 6, 3]])
tensor([[1, 3],
[4, 8],
[-1, 6],
[5, 9]])
```
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