Cover everything in test_all

Author: honno

array_api_tests/test_set_functions.py

@@ -1,4 +1,4 @@
-# TODO: disable if opted out
+# TODO: disable if opted out, refactor things
 import math
 from collections import Counter, defaultdict
 

array_api_tests/test_utility_functions.py

@@ -1,19 +1,48 @@
 from hypothesis import given
+from hypothesis import strategies as st
 
 from . import _array_module as xp
+from . import array_helpers as ah
+from . import dtype_helpers as dh
 from . import hypothesis_helpers as hh
+from . import pytest_helpers as ph
 from . import xps
+from .test_statistical_functions import (
+    assert_equals,
+    assert_keepdimable_shape,
+    axes,
+    axes_ndindex,
+    normalise_axis,
+)
 
 
-# TODO: generate kwargs
-@given(xps.arrays(dtype=xps.scalar_dtypes(), shape=hh.shapes()))
-def test_any(x):
-    xp.any(x)
-    # TODO
+@given(
+    x=xps.arrays(dtype=xps.scalar_dtypes(), shape=hh.shapes(min_side=1)),
+    data=st.data(),
+)
+def test_all(x, data):
+    kw = data.draw(hh.kwargs(axis=axes(x.ndim), keepdims=st.booleans()), label="kw")
+
+    out = xp.all(x, **kw)
+
+    ph.assert_dtype("all", x.dtype, out.dtype, xp.bool)
+    _axes = normalise_axis(kw.get("axis", None), x.ndim)
+    assert_keepdimable_shape(
+        "all", out.shape, x.shape, _axes, kw.get("keepdims", False), **kw
+    )
+    scalar_type = dh.get_scalar_type(x.dtype)
+    for indices, out_idx in zip(axes_ndindex(x.shape, _axes), ah.ndindex(out.shape)):
+        result = bool(out[out_idx])
+        elements = []
+        for idx in indices:
+            s = scalar_type(x[idx])
+            elements.append(s)
+        expected = all(elements)
+        assert_equals("all", scalar_type, out_idx, result, expected)
 
 
 # TODO: generate kwargs
 @given(xps.arrays(dtype=xps.scalar_dtypes(), shape=hh.shapes()))
-def test_all(x):
-    xp.all(x)
+def test_any(x):
+    xp.any(x)
     # TODO