address more feedback

Author: lithomas1

array_api_compat/common/_linalg.py

@@ -77,10 +77,7 @@ def matrix_rank(x: ndarray,
     # dimensional arrays.
     if x.ndim < 2:
         raise xp.linalg.LinAlgError("1-dimensional array given. Array must be at least two-dimensional")
-    if hasattr(xp.linalg, "svdvals"):
-        S = xp.linalg.svdvals(x, **kwargs)
-    else:
-        S = xp.linalg.svd(x, compute_uv=False, **kwargs)
+    S = get_xp(xp).linalg.svdvals(x, **kwargs)
     if rtol is None:
         tol = S.max(axis=-1, keepdims=True) * max(x.shape[-2:]) * xp.finfo(S.dtype).eps
     else:

array_api_compat/dask/array/linalg.py

@@ -10,8 +10,17 @@
 
 from typing import TYPE_CHECKING
 if TYPE_CHECKING:
-    from typing import Optional, Union, Tuple
-    from ...common._typing import ndarray, Device, Dtype
+    from typing import Union, Tuple
+    from ...common._typing import ndarray
+
+# cupy.linalg doesn't have __all__. If it is added, replace this with
+#
+# from cupy.linalg import __all__ as linalg_all
+_n = {}
+exec('from dask.array.linalg import *', _n)
+del _n['__builtins__']
+linalg_all = list(_n)
+del _n
 
 EighResult = _linalg.EighResult
 QRResult = _linalg.QRResult
@@ -30,6 +39,10 @@ def svdvals(x: ndarray) -> Union[ndarray, Tuple[ndarray, ...]]:
 vector_norm = get_xp(da)(_linalg.vector_norm)
 diagonal = get_xp(da)(_linalg.diagonal)
 
+__all__ = linalg_all + ["EighResult", "QRResult", "SlogdetResult",
+                        "SVDResult", "qr", "cholesky", "matrix_rank", "matrix_norm",
+                        "svdvals", "vector_norm", "diagonal"]
+
 del get_xp
 del da
 del _linalg