Merge pull request #260 from crusaderky/torch_import

MAINT: torch: tweak imports

Author: ev-br

array_api_compat/torch/_aliases.py

@@ -3,13 +3,7 @@
 from functools import wraps as _wraps
 from builtins import all as _builtin_all, any as _builtin_any
 
-from ..common._aliases import (matrix_transpose as _aliases_matrix_transpose,
-                               vecdot as _aliases_vecdot,
-                               clip as _aliases_clip,
-                               unstack as _aliases_unstack,
-                               cumulative_sum as _aliases_cumulative_sum,
-                               cumulative_prod as _aliases_cumulative_prod,
-                               )
+from ..common import _aliases
 from .._internal import get_xp
 
 from ._info import __array_namespace_info__
@@ -215,10 +209,10 @@ def min(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None, keep
         return torch.clone(x)
     return torch.amin(x, axis, keepdims=keepdims)
 
-clip = get_xp(torch)(_aliases_clip)
-unstack = get_xp(torch)(_aliases_unstack)
-cumulative_sum = get_xp(torch)(_aliases_cumulative_sum)
-cumulative_prod = get_xp(torch)(_aliases_cumulative_prod)
+clip = get_xp(torch)(_aliases.clip)
+unstack = get_xp(torch)(_aliases.unstack)
+cumulative_sum = get_xp(torch)(_aliases.cumulative_sum)
+cumulative_prod = get_xp(torch)(_aliases.cumulative_prod)
 
 # torch.sort also returns a tuple
 # https://github.com/pytorch/pytorch/issues/70921
@@ -710,8 +704,8 @@ def matmul(x1: array, x2: array, /, **kwargs) -> array:
     x1, x2 = _fix_promotion(x1, x2, only_scalar=False)
     return torch.matmul(x1, x2, **kwargs)
 
-matrix_transpose = get_xp(torch)(_aliases_matrix_transpose)
-_vecdot = get_xp(torch)(_aliases_vecdot)
+matrix_transpose = get_xp(torch)(_aliases.matrix_transpose)
+_vecdot = get_xp(torch)(_aliases.vecdot)
 
 def vecdot(x1: array, x2: array, /, *, axis: int = -1) -> array:
     x1, x2 = _fix_promotion(x1, x2, only_scalar=False)