TST: NumPy 1.x support (data-apis#169)

* TST: NumPy 1.x support

* Downgrade to  oldest SPEC0

Author: crusaderky

Diff for: .github/workflows/ci.yml

@@ -48,7 +48,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        environment: [tests-py310, tests-py313, tests-backends]
+        environment: [tests-py310, tests-py313, tests-numpy1, tests-backends]
         runs-on: [ubuntu-latest]
 
     steps:

Diff for: pixi.lock

@@ -126,6 +126,10 @@ python = "~=3.10.0"
 [tool.pixi.feature.py313.dependencies]
 python = "~=3.13.0"
 
+[tool.pixi.feature.numpy1.dependencies]
+# Oldest SPEC 0 NumPy at the moment of writing
+numpy = "=1.25.0"
+
 # Backends that can run on CPU-only hosts
 [tool.pixi.feature.backends.dependencies]
 pytorch = "*"
@@ -167,6 +171,8 @@ tests = { features = ["tests"], solve-group = "default" }
 docs = { features = ["docs"], solve-group = "default" }
 dev = { features = ["lint", "tests", "docs", "dev", "backends"], solve-group = "default" }
 dev-cuda = { features = ["lint", "tests", "docs", "dev", "backends", "cuda-backends"] }
+dev-numpy1 = { features = ["lint", "tests", "dev", "numpy1"] }
+tests-numpy1 = ["py310", "tests", "numpy1"]
 tests-py310 = ["py310", "tests"]
 tests-py313 = ["py313", "tests"]
 # CUDA not available on free github actions and on some developers' PCs

Diff for: pyproject.toml

@@ -565,12 +565,11 @@ def isclose(
     if rtol == 0:
         return xp.abs(a - b) <= atol
 
-    try:
-        nrtol = xp.asarray(int(1.0 / rtol), dtype=b.dtype)
-    except OverflowError:
-        # rtol * max_int(dtype) < 1, so it's inconsequential
+    # Don't rely on OverflowError, as it is not guaranteed by the Array API.
+    nrtol = int(1.0 / rtol)
+    if nrtol > xp.iinfo(b.dtype).max:
+        # rtol * max_int < 1, so it's inconsequential
         return xp.abs(a - b) <= atol
-
     return xp.abs(a - b) <= (atol + xp.abs(b) // nrtol)
 
 

Diff for: src/array_api_extra/_lib/_funcs.py

@@ -245,8 +245,7 @@ def eager_shape(x: Array, /) -> tuple[int, ...]:
 
 
 def meta_namespace(
-    *arrays: Array | int | float | complex | bool | None,
-    xp: ModuleType | None = None,
+    *arrays: Array | complex | None, xp: ModuleType | None = None
 ) -> ModuleType:
     """
     Get the namespace of Dask chunks.

Diff for: src/array_api_extra/_lib/_utils/_helpers.py

@@ -48,6 +48,9 @@
 lazy_xp_function(sinc, static_argnames="xp")
 
 
+NUMPY_GE2 = int(np.__version__.split(".")[0]) >= 2
+
+
 @pytest.mark.skip_xp_backend(
     Backend.SPARSE, reason="read-only backend without .at support"
 )
@@ -213,6 +216,13 @@ def test_hypothesis(  # type: ignore[explicit-any,decorated-any]
         xp: ModuleType,
         library: Backend,
     ):
+        if (
+            library in (Backend.NUMPY, Backend.NUMPY_READONLY)
+            and not NUMPY_GE2
+            and dtype is np.float32
+        ):
+            pytest.xfail(reason="NumPy 1.x dtype promotion for scalars")
+
         mbs = npst.mutually_broadcastable_shapes(num_shapes=n_arrays + 1, min_side=0)
         input_shapes, _ = data.draw(mbs)
         cond_shape, *shapes = input_shapes

Diff for: tests/test_funcs.py

@@ -18,9 +18,9 @@
 from array_api_extra._lib._utils._typing import Array, Device, DType
 from array_api_extra.testing import lazy_xp_function
 
-# mypy: disable-error-code=no-untyped-usage
+from .conftest import np_compat
 
-np_compat = array_namespace(np.empty(0))  # type: ignore[arg-type]  # pyright: ignore[reportArgumentType]
+# mypy: disable-error-code=no-untyped-usage
 
 # FIXME calls xp.unique_values without size
 lazy_xp_function(in1d, jax_jit=False, static_argnames=("assume_unique", "invert", "xp"))
@@ -149,7 +149,7 @@ def test_numpy_generics(self, dtype: DType):
         which are subclasses of float and complex.
         """
         a = cast(Array, dtype(0))  # type: ignore[operator]  # pyright: ignore[reportCallIssue]
-        xa, xb = asarrays(a, 0, xp=np)
+        xa, xb = asarrays(a, 0, xp=np_compat)
         assert xa.dtype == dtype
         assert xb.dtype == dtype
 

Diff for: tests/test_helpers.py

@@ -94,12 +94,7 @@ def f(x: Array) -> tuple[Array, Array]:
 @pytest.mark.parametrize(
     "as_numpy",
     [
-        pytest.param(
-            False,
-            marks=pytest.mark.xfail_xp_backend(
-                Backend.TORCH, reason="illegal dtype promotion"
-            ),
-        ),
+        False,
         pytest.param(
             True,
             marks=[
@@ -119,7 +114,7 @@ def f(x: Array, y: Array) -> tuple[Array, Array]:
         return x + y, x - y
 
     x = xp.asarray([1, 2], dtype=xp.float32)
-    y = xp.asarray(3, dtype=xp.float64)
+    y = xp.asarray([3], dtype=xp.float64)
     expect = (
         xp.asarray([4, 5], dtype=xp.float64),
         xp.asarray([-2, -1], dtype=xp.float64),