{{alias}}( x, y[, dim] )
    Computes the dot product of two single-precision floating-point vectors.

    If provided at least one input array having more than one dimension, the
    input arrays are broadcasted to a common shape.

    For multi-dimensional input arrays, the function performs batched
    computation, such that the function computes the dot product for each pair
    of vectors in `x` and `y` according to the specified dimension index.

    The size of the contracted dimension must be the same for both input arrays.

    The function resolves the dimension index for which to compute the dot
    product *before* broadcasting.

    If provided empty vectors, the dot product is `0`.

    Parameters
    ----------
    x: ndarray
        First input array. Must have a 'float32' data type. Must have at least
        one dimension and be broadcast-compatible with the second input array.

    y: ndarray
        Second input array. Must have a 'float32' data type. Must have at least
        one dimension and be broadcast-compatible with the first input array.

    dim: integer (optional)
        Dimension index for which to compute the dot product. Must be a negative
        integer. Negative indices are resolved relative to the last array
        dimension, with the last dimension corresponding to `-1`. Default: -1.

    Returns
    -------
    out: ndarray
        The dot product. The output array has the same data type as the input
        arrays and has a shape which is determined by broadcasting and excludes
        the contracted dimension.

    Examples
    --------
    > var xbuf = new {{alias:@stdlib/array/float32}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
    > var x = {{alias:@stdlib/ndarray/array}}( xbuf );
    > var ybuf = new {{alias:@stdlib/array/float32}}( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
    > var y = {{alias:@stdlib/ndarray/array}}( ybuf );
    > var z = {{alias}}( x, y )
    <ndarray>
    > z.get()
    -5.0

    See Also
    --------