diff --git a/spec/API_specification/array_api/linear_algebra_functions.py b/spec/API_specification/array_api/linear_algebra_functions.py index f8f15e5b0..321c66668 100644 --- a/spec/API_specification/array_api/linear_algebra_functions.py +++ b/spec/API_specification/array_api/linear_algebra_functions.py @@ -86,13 +86,20 @@ def tensordot(x1: array, x2: array, /, *, axes: Union[int, Tuple[Sequence[int], def vecdot(x1: array, x2: array, /, *, axis: int = -1) -> array: """ Computes the (vector) dot product of two arrays. + + Let :math:`\mathbf{a}` be a vector in ``x1`` and :math:`\mathbf{b}` be a corresponding vector in ``x2``. The dot product is defined as + + .. math:: + \mathbf{a} \cdot \mathbf{b} = \sum_{i=0}^{n-1} a_i\overline{b_i} + + over the dimension specified by ``axis`` and where :math:`n` is the dimension size and :math:`\overline{b_i}` denotes the complex conjugate if :math:`b_i` is complex and the identity if :math:`b_i` is real-valued. Parameters ---------- x1: array - first input array. Should have a real-valued data type. + first input array. Should have a floating-point data type. x2: array - second input array. Must be compatible with ``x1`` for all non-contracted axes (see :ref:`broadcasting`). The size of the axis over which to compute the dot product must be the same size as the respective axis in ``x1``. Should have a real-valued data type. + second input array. Must be compatible with ``x1`` for all non-contracted axes (see :ref:`broadcasting`). The size of the axis over which to compute the dot product must be the same size as the respective axis in ``x1``. Should have a floating-point data type. .. note:: The contracted axis (dimension) must not be broadcasted. pFad - Phonifier reborn

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