torch.vdot
torch.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, torch.vdot intentionally only supports
 computing the dot product of two 1D tensors with the same number
 of elements.

See also:
 "torch.linalg.vecdot()" computes the dot product of two batches
 of vectors along a dimension.

Parameters:
      * input (Tensor) -- first tensor in the dot product, must
        be 1D. Its conjugate is used if it's complex.
  * **other** (*Tensor*) -- second tensor in the dot product, must
    be 1D.

Keyword args:
Note:
 out (Tensor, optional): the output tensor.

Example:
  >>> torch.vdot(torch.tensor([2, 3]), torch.tensor([2, 1]))
  tensor(7)
