12 from ._normalizations import ArrayLike, KeepDims, normalizer
51 def matrix_power(a: ArrayLike, n):  argument
58 def multi_dot(inputs: Sequence[ArrayLike], *, out=None):  argument
67 def solve(a: ArrayLike, b: ArrayLike):  argument
74 def lstsq(a: ArrayLike, b: ArrayLike, rcond=None):  argument
84 def inv(a: ArrayLike):  argument
92 def pinv(a: ArrayLike, rcond=1e-15, hermitian=False):  argument
99 def tensorsolve(a: ArrayLike, b: ArrayLike, axes=None):  argument
106 def tensorinv(a: ArrayLike, ind=2):  argument
116 def det(a: ArrayLike):  argument
123 def slogdet(a: ArrayLike):  argument
130 def cond(x: ArrayLike, p=None):  argument
148 def matrix_rank(a: ArrayLike, tol=None, hermitian=False):  argument
165 def norm(x: ArrayLike, ord=None, axis=None, keepdims: KeepDims = False):  argument
175 def cholesky(a: ArrayLike):  argument
182 def qr(a: ArrayLike, mode="reduced"):  argument
193 def svd(a: ArrayLike, full_matrices=True, compute_uv=True, hermitian=False):  argument
208 def eig(a: ArrayLike):  argument
220 def eigh(a: ArrayLike, UPLO="L"):  argument
227 def eigvals(a: ArrayLike):  argument
237 def eigvalsh(a: ArrayLike, UPLO="L"):  argument