# tensorplay.functional.diagflat

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

```python
tensorplay.functional.diagflat(input, offset=0) → Tensor
```

- If input is a vector (1-D tensor), then returns a 2-D square tensor with the elements of input as the diagonal.

- If input is a tensor with more than one dimension, then returns a 2-D tensor with diagonal elements equal to a flattened input.

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.

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

Examples:

```
>>> a = tensorplay.randn(3)
>>> a
tensor([-0.2956, -0.9068,  0.1695])
>>> tensorplay.diagflat(a)
tensor([[-0.2956,  0.0000,  0.0000],
        [ 0.0000, -0.9068,  0.0000],
        [ 0.0000,  0.0000,  0.1695]])
>>> tensorplay.diagflat(a, 1)
tensor([[ 0.0000, -0.2956,  0.0000,  0.0000],
        [ 0.0000,  0.0000, -0.9068,  0.0000],
        [ 0.0000,  0.0000,  0.0000,  0.1695],
        [ 0.0000,  0.0000,  0.0000,  0.0000]])

>>> a = tensorplay.randn(2, 2)
>>> a
tensor([[ 0.2094, -0.3018],
        [-0.1516,  1.9342]])
>>> tensorplay.diagflat(a)
tensor([[ 0.2094,  0.0000,  0.0000,  0.0000],
        [ 0.0000, -0.3018,  0.0000,  0.0000],
        [ 0.0000,  0.0000, -0.1516,  0.0000],
        [ 0.0000,  0.0000,  0.0000,  1.9342]])
```