# tensorplay.functional.vdot

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

```python
tensorplay.functional.vdot(input, other, *, out=None) → Tensor
```

Computes the dot product of two 1D vectors along a dimension.

In symbols, this function computes

$$\sum_{i=1}^n \overline{x_i}y_i.$$

where $\overline{x_i}$ denotes the conjugate for complex
vectors, and it is the identity for real vectors.

> **Note**
>
> Unlike NumPy’s vdot, tensorplay.vdot intentionally only supports computing the dot product of two 1D tensors with the same number of elements.

> **See also**
>
> tensorplay.linalg.vecdot() computes the dot product of two batches of vectors along a dimension.

Parameters:

- input ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – first tensor in the dot product, must be 1D. Its conjugate is used if it’s complex.

- other ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – second tensor in the dot product, must be 1D.

Keyword args:

> **Note**
>
> out (Tensor, optional): the output tensor.

Example:

```
>>> tensorplay.vdot(tensorplay.tensor([2, 3]), tensorplay.tensor([2, 1]))
tensor(7)
>>> a = tensorplay.tensor((1 +2j, 3 - 1j))
>>> b = tensorplay.tensor((2 +1j, 4 - 0j))
>>> tensorplay.vdot(a, b)
tensor([16.+1.j])
>>> tensorplay.vdot(b, a)
tensor([16.-1.j])
```