# tensorplay.functional.as_strided_scatter

Source: https://www.tensorplay.cn/docs/generated/tensorplay.functional.as_strided_scatter.html

```python
tensorplay.functional.as_strided_scatter(input, src, size, stride, storage_offset=None) → Tensor
```

Embeds the values of the src tensor into input along
the elements corresponding to the result of calling
input.as_strided(size, stride, storage_offset).

This function returns a tensor with fresh storage; it does not
return a view.

Parameters:

- input ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – the input tensor.

- size ([tuple](https://docs.python.org/3/builtins/stdtypes.html#tuple) or ints) – the shape of the output tensor

- stride ([tuple](https://docs.python.org/3/builtins/stdtypes.html#tuple) or ints) – the stride of the output tensor

- storage_offset ([int](https://docs.python.org/3/builtins/functions.html#int), optional) – the offset in the underlying storage of the output tensor

> **Note**
>
> src must be of the proper size in order to be embedded into input. Specifically, it should have the same shape as tensorplay.as_strided(input, size, stride, storage_offset)

Example:

```
>>> a = tensorplay.arange(4).reshape(2, 2) + 1
>>> a
tensor([[1, 2],
        [3, 4]])
>>> b = tensorplay.zeros(3, 3)
>>> b
tensor([[0., 0., 0.],
        [0., 0., 0.],
        [0., 0., 0.]])
>>> tensorplay.as_strided_scatter(b, a, (2, 2), (1, 2))
tensor([[1., 3., 2.],
        [4., 0., 0.],
        [0., 0., 0.]])
```