# Differences with torchtext.data.functional.simple_space_split

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## torchtext.data.functional.simple_space_split

```python
torchtext.data.functional.simple_space_split(iterator)
```

For more information, see [torchtext.data.functional.simple_space_split](https://pytorch.org/text/0.9.0/data_functional.html#torchtext.data.functional.simple_space_split).

## mindspore.dataset.text.WhitespaceTokenizer

```python
class mindspore.dataset.text.WhitespaceTokenizer(with_offsets=False)
```

For more information, see [mindspore.dataset.text.WhitespaceTokenizer](https://www.mindspore.cn/docs/en/r2.3.0rc1/api_python/dataset_text/mindspore.dataset.text.WhitespaceTokenizer.html#mindspore.dataset.text.WhitespaceTokenizer).

## Differences

PyTorch: Tokenize a string on with whitespaces.

MindSpore: Tokenize a string on with whitespaces.

| Categories | Subcategories |PyTorch | MindSpore | Difference |
| --- | ---   | ---   | ---        |---  |
|Parameter | Parameter1 | -    | with_offsets     | Whether to output offsets of tokens |

## Code Example

```python
# PyTorch
from torchtext.data.functional import simple_space_split

list_a = "sentencepiece encode as pieces"
result = simple_space_split([list_a])
print(list(result))
# Out: [['sentencepiece', 'encode', 'as', 'pieces']]

# MindSpore
import mindspore.dataset.text as text

result = text.WhitespaceTokenizer()(list_a)
print(list(result))
# Out: ['sentencepiece', 'encode', 'as', 'pieces']
```