# tensorplay.functional.diagonal_scatter

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

```python
tensorplay.functional.diagonal_scatter(input, src, offset=0, dim1=0, dim2=1) → Tensor
```

Embeds the values of the src tensor into input along
the diagonal elements of input, with respect to dim1
and dim2.

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

The argument offset controls which diagonal to consider:

- If offset = 0, it is the main diagonal.

- If offset > 0, it is above the main diagonal.

- If offset 
Parameters:

- input ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – the input tensor. Must be at least 2-dimensional.

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

- offset ([int](https://docs.python.org/3/builtins/functions.html#int), optional) – which diagonal to consider. Default: 0 (main diagonal).

- dim1 ([int](https://docs.python.org/3/builtins/functions.html#int), optional) – first dimension with respect to which to take diagonal. Default: 0.

- dim2 ([int](https://docs.python.org/3/builtins/functions.html#int), optional) – second dimension with respect to which to take diagonal. Default: 1.

> **Note**
>
> src must be of the proper size in order to be embedded into input. Specifically, it should have the same shape as tensorplay.diagonal(input, offset, dim1, dim2)

Examples:

```
>>> a = tensorplay.zeros(3, 3)
>>> a
tensor([[0., 0., 0.],
        [0., 0., 0.],
        [0., 0., 0.]])

>>> tensorplay.diagonal_scatter(a, tensorplay.ones(3), 0)
tensor([[1., 0., 0.],
        [0., 1., 0.],
        [0., 0., 1.]])

>>> tensorplay.diagonal_scatter(a, tensorplay.ones(2), 1)
tensor([[0., 1., 0.],
        [0., 0., 1.],
        [0., 0., 0.]])
```