BUG: torch: meshgrid defaults to indexing="xy"

As of version 2.6, torch defaults to indexing='ij', and is planning
to transition to 'xy' at some point. When it does, we'll be able to drop
our wrapper.

Author: ev-br

array_api_compat/torch/_aliases.py

@@ -2,7 +2,7 @@
 
 from functools import reduce as _reduce, wraps as _wraps
 from builtins import all as _builtin_all, any as _builtin_any
-from typing import Any, List, Optional, Sequence, Tuple, Union
+from typing import Any, List, Optional, Sequence, Tuple, Union, Literal
 
 import torch
 
@@ -828,6 +828,12 @@ def sign(x: Array, /) -> Array:
         return out
 
 
+def meshgrid(*arrays: Array, indexing: Literal['xy', 'ij'] = 'xy') -> List[Array]:
+    # enforce the default of 'xy'
+    # TODO: is the return type a list or a tuple
+    return list(torch.meshgrid(*arrays, indexing='xy'))
+
+
 __all__ = ['__array_namespace_info__', 'asarray', 'result_type', 'can_cast',
            'permute_dims', 'bitwise_invert', 'newaxis', 'conj', 'add',
            'atan2', 'bitwise_and', 'bitwise_left_shift', 'bitwise_or',
@@ -844,6 +850,6 @@ def sign(x: Array, /) -> Array:
            'UniqueAllResult', 'UniqueCountsResult', 'UniqueInverseResult',
            'unique_all', 'unique_counts', 'unique_inverse', 'unique_values',
            'matmul', 'matrix_transpose', 'vecdot', 'tensordot', 'isdtype',
-           'take', 'take_along_axis', 'sign', 'finfo', 'iinfo', 'repeat']
+           'take', 'take_along_axis', 'sign', 'finfo', 'iinfo', 'repeat', 'meshgrid']
 
 _all_ignore = ['torch', 'get_xp']

tests/test_torch.py

@@ -100,3 +100,20 @@ def test_gh_273(self, default_dt, dtype_a, dtype_b):
             assert dtype_1 == dtype_2
         finally:
             torch.set_default_dtype(prev_default)
+
+
+def test_meshgrid():
+    """Verify that array_api_compat.torch.meshgrid defaults to indexing='xy'."""
+
+    x, y = xp.asarray([1, 2]), xp.asarray([4])
+
+    X, Y = xp.meshgrid(x, y)
+
+    # output of torch.meshgrid(x, y, indexing='xy') -- indexing='ij' is different
+    X_xy, Y_xy = xp.asarray([[1, 2]]), xp.asarray([[4, 4]])
+
+    assert X.shape == X_xy.shape
+    assert xp.all(X == X_xy)
+
+    assert Y.shape == Y_xy.shape
+    assert xp.all(Y == Y_xy)