torch.linalg.vecdot#

torch.linalg.vecdot(x,y,*,dim=-1,out=None)→Tensor#

Computes the dot product of two batches of vectors along a dimension.

In symbols, this function computes

$$\sum _{i=1}^n\overline{x_i}{y}_i\mathrm{.}$$i=1∑n​xi​​yi​.

over the dimensiondim where$\overline{x_i}$xi​​ denotes the conjugate for complexvectors, and it is the identity for real vectors.

Supports input of half, bfloat16, float, double, cfloat, cdouble and integral dtypes.It also supports broadcasting.

Parameters

• x (Tensor) – first batch of vectors of shape(*, n).

• y (Tensor) – second batch of vectors of shape(*, n).

Keyword Arguments

• dim (int) – Dimension along which to compute the dot product. Default:-1.

• out (Tensor,optional) – output tensor. Ignored ifNone. Default:None.

Examples:

>>>v1=torch.randn(3,2)>>>v2=torch.randn(3,2)>>>linalg.vecdot(v1,v2)tensor([ 0.3223,  0.2815, -0.1944])>>>torch.vdot(v1[0],v2[0])tensor(0.3223)