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Add complex number support to linalg.matrix_rank #563

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Dec 14, 2022
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4 changes: 3 additions & 1 deletion spec/API_specification/array_api/linalg.py
Original file line number Diff line number Diff line change
Expand Up @@ -262,10 +262,12 @@ def matrix_rank(x: array, /, *, rtol: Optional[Union[float, array]] = None) -> a
"""
Returns the rank (i.e., number of non-zero singular values) of a matrix (or a stack of matrices).

When ``x`` is a stack of matrices, the function must compute the number of non-zero singular values for each matrix in the stack.

Parameters
----------
x: array
input array having shape ``(..., M, N)`` and whose innermost two dimensions form ``MxN`` matrices. Should have a real-valued floating-point data type.
input array having shape ``(..., M, N)`` and whose innermost two dimensions form ``MxN`` matrices. Should have a floating-point data type.
rtol: Optional[Union[float, array]]
relative tolerance for small singular values. Singular values approximately less than or equal to ``rtol * largest_singular_value`` are set to zero. If a ``float``, the value is equivalent to a zero-dimensional array having a real-valued floating-point data type determined by :ref:`type-promotion` (as applied to ``x``) and must be broadcast against each matrix. If an ``array``, must have a real-valued floating-point data type and must be compatible with ``shape(x)[:-2]`` (see :ref:`broadcasting`). If ``None``, the default value is ``max(M, N) * eps``, where ``eps`` must be the machine epsilon associated with the real-valued floating-point data type determined by :ref:`type-promotion` (as applied to ``x``). Default: ``None``.

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