dpnp.vecdot

dpnp.vecdot(x1, x2, /, out=None, *, casting='same_kind', order='K', dtype=None, subok=True, signature=None, axes=None, axis=None)

Computes the vector dot product.

Let $a$ be a vector in x1 and $b$ be a corresponding vector in x2. The dot product is defined as:

a \cdot b = \sum_{i = 0}^{n - 1} \overset{―}{a_{i}} b_{i}

where the sum is over the last dimension (unless axis is specified) and where $\overset{―}{a_{i}}$ denotes the complex conjugate if $a_{i}$ is complex and the identity otherwise.

For full documentation refer to numpy.vecdot.

Parameters:

x1 ({dpnp.ndarray, usm_ndarray}) -- First input array.
x2 ({dpnp.ndarray, usm_ndarray}) -- Second input array.
out ({None, dpnp.ndarray, usm_ndarray}, optional) --
A location into which the result is stored. If provided, it must have the broadcasted shape of x1 and x2 with the last axis removed. If not provided or None, a freshly-allocated array is used.

Default: None.
casting ({"no", "equiv", "safe", "same_kind", "unsafe"}, optional) --
Controls what kind of data casting may occur.

Default: "same_kind".
order ({"C", "F", "A", "K", None}, optional) --
Memory layout of the newly output array, if parameter out is None.

Default: "K".
dtype ({None, str, dtype object}, optional) --
Type to use in computing the vector dot product. By default, the returned array will have data type that is determined by considering Promotion Type Rule and device capabilities.

Default: None.
axes ({None, list of tuples}, optional) --
A list of tuples with indices of axes the dot product should operate on. For instance, for the signature of (i),(i)->(), the base elements are vectors and these are taken to be stored in the last axes of each argument. The corresponding axes keyword would be [(-1,), (-1,), ()].

Default: None.
axis ({None, int}, optional) --
Axis over which to compute the dot product. This is a short-cut for passing in axes with entries of (axis,) for each single-core-dimension argument and () for all others. For instance, for a signature (i),(i)->(), it is equivalent to passing in axes=[(axis,), (axis,), ()].

Default: None.

Returns:

out -- The vector dot product of the inputs. This is a 0-d array only when both x1, x2 are 1-d vectors.

Return type:

dpnp.ndarray

Limitations

Keyword arguments subok, and signature are only supported with their default values. Otherwise NotImplementedError exception will be raised.