Remove redundant dtype strategies in hypothesis_helpers.py

Author: honno

array_api_tests/hypothesis_helpers.py

@@ -22,16 +22,6 @@
 from .pytest_helpers import nargs
 from .typing import Array, DataType, Shape
 
-integer_dtypes = xps.integer_dtypes() | xps.unsigned_integer_dtypes()
-floating_dtypes = xps.floating_dtypes()
-numeric_dtypes = xps.numeric_dtypes()
-integer_or_boolean_dtypes = xps.boolean_dtypes() | integer_dtypes
-boolean_dtypes = xps.boolean_dtypes()
-dtypes = xps.scalar_dtypes()
-
-shared_dtypes = shared(dtypes, key="dtype")
-shared_floating_dtypes = shared(floating_dtypes, key="dtype")
-
 _dtype_categories = [(xp.bool,), dh.uint_dtypes, dh.int_dtypes, dh.real_float_dtypes, dh.complex_dtypes]
 _sorted_dtypes = [d for category in _dtype_categories for d in category]
 
@@ -337,7 +327,7 @@ def python_integer_indices(draw, sizes):
 def integer_indices(draw, sizes):
     # Return either a Python integer or a 0-D array with some integer dtype
     idx = draw(python_integer_indices(sizes))
-    dtype = draw(integer_dtypes)
+    dtype = draw(xps.integer_dtypes() | xps.unsigned_integer_dtypes())
     m, M = dh.dtype_ranges[dtype]
     if m <= idx <= M:
         return draw(one_of(just(idx),

array_api_tests/meta/test_hypothesis_helpers.py

@@ -128,20 +128,20 @@ def run(n, d, data):
     assert any("d" in kw.keys() and kw["d"] is xp.float64 for kw in results)
 
 
-
 @given(finite=st.booleans(), dtype=xps.floating_dtypes(), data=st.data())
 def test_symmetric_matrices(finite, dtype, data):
-    m = data.draw(hh.symmetric_matrices(st.just(dtype), finite=finite))
+    m = data.draw(hh.symmetric_matrices(st.just(dtype), finite=finite), label="m")
     assert m.dtype == dtype
     # TODO: This part of this test should be part of the .mT test
     ah.assert_exactly_equal(m, m.mT)
 
     if finite:
         ah.assert_finite(m)
 
-@given(m=hh.positive_definite_matrices(hh.shared_floating_dtypes),
-       dtype=hh.shared_floating_dtypes)
-def test_positive_definite_matrices(m, dtype):
+
+@given(dtype=xps.floating_dtypes(), data=st.data())
+def test_positive_definite_matrices(dtype, data):
+    m = data.draw(hh.positive_definite_matrices(st.just(dtype)), label="m")
     assert m.dtype == dtype
     # TODO: Test that it actually is positive definite
 

array_api_tests/test_creation_functions.py

@@ -427,21 +427,11 @@ def test_full(shape, fill_value, kw):
     ph.assert_fill("full", fill_value=fill_value, dtype=dtype, out=out, kw=dict(fill_value=fill_value))
 
 
-@st.composite
-def full_like_fill_values(draw):
-    kw = draw(
-        st.shared(hh.kwargs(dtype=st.none() | xps.scalar_dtypes()), key="full_like_kw")
-    )
-    dtype = kw.get("dtype", None) or draw(hh.shared_dtypes)
-    return draw(xps.from_dtype(dtype))
-
-
-@given(
-    x=xps.arrays(dtype=hh.shared_dtypes, shape=hh.shapes()),
-    fill_value=full_like_fill_values(),
-    kw=st.shared(hh.kwargs(dtype=st.none() | xps.scalar_dtypes()), key="full_like_kw"),
-)
-def test_full_like(x, fill_value, kw):
+@given(kw=hh.kwargs(dtype=st.none() | xps.scalar_dtypes()), data=st.data())
+def test_full_like(kw, data):
+    dtype = kw.get("dtype", None) or data.draw(xps.scalar_dtypes(), label="dtype")
+    x = data.draw(xps.arrays(dtype=dtype, shape=hh.shapes()), label="x")
+    fill_value = data.draw(xps.from_dtype(dtype), label="fill_value")
     out = xp.full_like(x, fill_value, **kw)
     dtype = kw.get("dtype", None) or x.dtype
     if kw.get("dtype", None) is None:
@@ -551,7 +541,7 @@ def test_ones(shape, kw):
 
 
 @given(
-    x=xps.arrays(dtype=hh.dtypes, shape=hh.shapes()),
+    x=xps.arrays(dtype=xps.scalar_dtypes(), shape=hh.shapes()),
     kw=hh.kwargs(dtype=st.none() | xps.scalar_dtypes()),
 )
 def test_ones_like(x, kw):
@@ -589,7 +579,7 @@ def test_zeros(shape, kw):
 
 
 @given(
-    x=xps.arrays(dtype=hh.dtypes, shape=hh.shapes()),
+    x=xps.arrays(dtype=xps.scalar_dtypes(), shape=hh.shapes()),
     kw=hh.kwargs(dtype=st.none() | xps.scalar_dtypes()),
 )
 def test_zeros_like(x, kw):