Update erf tests after migration

Author: vlad-perevezentsev

dpnp/tests/test_special.py

@@ -25,7 +25,7 @@ def test_basic(self, func, dt):
         a = generate_random_numpy_array((2, 5), dtype=dt)
         ia = dpnp.array(a)
 
-        result = getattr(dpnp.special, func)(ia)
+        result = getattr(dpnp.scipy.special, func)(ia)
         expected = getattr(scipy.special, func)(a)
 
         # scipy >= 0.16.0 returns float64, but dpnp returns float32
@@ -41,7 +41,7 @@ def test_nan_inf(self, func):
         a = numpy.array([numpy.nan, -numpy.inf, numpy.inf])
         ia = dpnp.array(a)
 
-        result = getattr(dpnp.special, func)(ia)
+        result = getattr(dpnp.scipy.special, func)(ia)
         expected = getattr(scipy.special, func)(a)
         assert_allclose(result, expected)
 
@@ -51,7 +51,7 @@ def test_zeros(self, func):
         a = numpy.array([0.0, -0.0])
         ia = dpnp.array(a)
 
-        result = getattr(dpnp.special, func)(ia)
+        result = getattr(dpnp.scipy.special, func)(ia)
         expected = getattr(scipy.special, func)(a)
         assert_allclose(result, expected)
         assert_equal(dpnp.signbit(result), numpy.signbit(expected))
@@ -60,7 +60,7 @@ def test_zeros(self, func):
     def test_complex(self, func, dt):
         x = dpnp.empty(5, dtype=dt)
         with pytest.raises(ValueError):
-            getattr(dpnp.special, func)(x)
+            getattr(dpnp.scipy.special, func)(x)
 
 
 class TestConsistency:
@@ -72,11 +72,11 @@ def test_erfc(self):
         a = rng.pareto(0.02, n) * (2 * rng.randint(0, 2, n) - 1)
         a = dpnp.array(a)
 
-        res = 1 - dpnp.special.erf(a)
+        res = 1 - dpnp.scipy.special.erf(a)
         mask = dpnp.isfinite(res)
         a = a[mask]
 
         tol = 8 * dpnp.finfo(a).resolution
         assert dpnp.allclose(
-            dpnp.special.erfc(a), res[mask], rtol=tol, atol=tol
+            dpnp.scipy.special.erfc(a), res[mask], rtol=tol, atol=tol
         )

dpnp/tests/test_strides.py

@@ -175,7 +175,7 @@ def test_erf_funcs(func, stride):
     x = generate_random_numpy_array(10)
     a, ia = x[::stride], dpnp.array(x)[::stride]
 
-    result = getattr(dpnp.special, func)(ia)
+    result = getattr(dpnp.scipy.special, func)(ia)
     expected = getattr(scipy.special, func)(a)
     assert_dtype_allclose(result, expected)
 

dpnp/tests/test_sycl_queue.py

@@ -1493,7 +1493,7 @@ def test_interp(device, left, right, period):
 def test_erf_funcs(func, device):
     x = dpnp.linspace(-3, 3, num=5, device=device)
 
-    result = getattr(dpnp.special, func)(x)
+    result = getattr(dpnp.scipy.special, func)(x)
     assert_sycl_queue_equal(result.sycl_queue, x.sycl_queue)
 
 

dpnp/tests/test_usm_type.py

@@ -1300,7 +1300,7 @@ def test_choose(usm_type_x, usm_type_ind):
 @pytest.mark.parametrize("usm_type", list_of_usm_types)
 def test_erf_funcs(func, usm_type):
     x = dpnp.linspace(-3, 3, num=5, usm_type=usm_type)
-    y = getattr(dpnp.special, func)(x)
+    y = getattr(dpnp.scipy.special, func)(x)
     assert x.usm_type == y.usm_type == usm_type
 
 

dpnp/tests/third_party/cupyx/scipy_tests/special_tests/test_erf.py

@@ -1,12 +1,13 @@
 from __future__ import annotations
 
 import unittest
+from functools import wraps
 
 import numpy
 import pytest
 
 import dpnp as cupy
-import dpnp.special
+import dpnp.scipy.special
 from dpnp.tests.third_party.cupy import testing
 
 
@@ -16,6 +17,19 @@ def _boundary_inputs(boundary, rtol, atol):
     return [left, boundary, right]
 
 
+# Ensure `scp` exposes `.special` submodule:
+# use `dpnp.scipy` for DPNP, `scipy` for SciPy
+def resolve_special_scp(func):
+    @wraps(func)
+    def wrapper(*args, **kwargs):
+        scp = kwargs.get("scp")
+        if scp is not None and not hasattr(scp, "special"):
+            kwargs["scp"] = getattr(scp, "scipy", scp)  # dpnp -> dpnp.scipy
+        return func(*args, **kwargs)
+
+    return wrapper
+
+
 @testing.with_requires("scipy")
 class _TestBase:
 
@@ -53,14 +67,18 @@ class TestSpecial(unittest.TestCase, _TestBase):
     # scipy>=1.16: 'e -> d', which causes type_check=False
     @testing.for_dtypes(["e", "f", "d"])
     @testing.numpy_cupy_allclose(atol=1e-5, scipy_name="scp", type_check=False)
+    @resolve_special_scp
     def check_unary(self, name, xp, scp, dtype):
         import scipy.special
 
         a = testing.shaped_arange((2, 3), xp, dtype)
+        # _scp = getattr(scp, "scipy", scp)
+        # return getattr(_scp.special, name)(a)
         return getattr(scp.special, name)(a)
 
     @testing.for_dtypes(["f", "d"])
     @testing.numpy_cupy_allclose(atol=1e-5, scipy_name="scp")
+    @resolve_special_scp
     def check_unary_random(self, name, xp, scp, dtype, scale, offset):
         import scipy.special
 
@@ -69,6 +87,7 @@ def check_unary_random(self, name, xp, scp, dtype, scale, offset):
 
     @testing.for_dtypes(["f", "d"])
     @testing.numpy_cupy_allclose(atol=1e-5, scipy_name="scp")
+    @resolve_special_scp
     def check_unary_boundary(self, name, xp, scp, dtype, boundary):
         import scipy.special