define a new helper function for tests called get_integer_float_dtypes (#2402)

A new helper function is defined for tests, to get integer and float
dtypes.

Author: vtavana

dpnp/tests/helper.py

@@ -325,6 +325,36 @@ def get_integer_dtypes(all_int_types=False, no_unsigned=False):
     return dtypes
 
 
+def get_integer_float_dtypes(
+    all_int_types=False,
+    no_unsigned=False,
+    no_float16=True,
+    device=None,
+    xfail_dtypes=None,
+    exclude=None,
+):
+    """
+    Build a list of integer and float types supported by DPNP.
+    """
+    dtypes = get_integer_dtypes(
+        all_int_types=all_int_types, no_unsigned=no_unsigned
+    )
+    dtypes += get_float_dtypes(no_float16=no_float16, device=device)
+
+    def mark_xfail(dtype):
+        if xfail_dtypes is not None and dtype in xfail_dtypes:
+            return pytest.param(dtype, marks=pytest.mark.xfail)
+        return dtype
+
+    def not_excluded(dtype):
+        if exclude is None:
+            return True
+        return dtype not in exclude
+
+    dtypes = [mark_xfail(dtype) for dtype in dtypes if not_excluded(dtype)]
+    return dtypes
+
+
 def has_support_aspect16(device=None):
     """
     Return True if the device supports 16-bit precision floating point operations,

dpnp/tests/test_binary_ufuncs.py

@@ -20,6 +20,7 @@
     get_float_complex_dtypes,
     get_float_dtypes,
     get_integer_dtypes,
+    get_integer_float_dtypes,
     has_support_aspect16,
     numpy_version,
 )
@@ -141,7 +142,7 @@ def test_invalid_out(self, xp, out):
 @pytest.mark.parametrize("func", ["fmax", "fmin", "maximum", "minimum"])
 class TestBoundFuncs:
     @pytest.mark.parametrize("dtype", get_all_dtypes(no_none=True))
-    def test_out(self, func, dtype):
+    def test_basic(self, func, dtype):
         a = generate_random_numpy_array(10, dtype)
         b = generate_random_numpy_array(10, dtype)
         expected = getattr(numpy, func)(a, b)
@@ -278,7 +279,7 @@ def test_invalid_out(self, xp, out):
 
 @pytest.mark.parametrize("func", ["floor_divide", "remainder"])
 class TestFloorDivideRemainder:
-    ALL_DTYPES = get_all_dtypes(no_none=True, no_bool=True, no_complex=True)
+    ALL_DTYPES = get_integer_float_dtypes()
 
     def do_inplace_op(self, base, other, func):
         if func == "floor_divide":

dpnp/tests/test_histogram.py

@@ -19,15 +19,14 @@
     get_float_complex_dtypes,
     get_float_dtypes,
     get_integer_dtypes,
+    get_integer_float_dtypes,
     has_support_aspect64,
     numpy_version,
 )
 
 
 class TestDigitize:
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
+    @pytest.mark.parametrize("dtype", get_integer_float_dtypes())
     @pytest.mark.parametrize("right", [True, False])
     @pytest.mark.parametrize(
         "x, bins",
@@ -73,12 +72,8 @@ def test_digitize_inf(self, dtype, right):
         expected = numpy.digitize(x, bins, right=right)
         assert_dtype_allclose(result, expected)
 
-    @pytest.mark.parametrize(
-        "dtype_x", get_all_dtypes(no_bool=True, no_complex=True)
-    )
-    @pytest.mark.parametrize(
-        "dtype_bins", get_all_dtypes(no_bool=True, no_complex=True)
-    )
+    @pytest.mark.parametrize("dtype_x", get_integer_float_dtypes())
+    @pytest.mark.parametrize("dtype_bins", get_integer_float_dtypes())
     @pytest.mark.parametrize("right", [True, False])
     def test_digitize_diff_types(self, dtype_x, dtype_bins, right):
         x = numpy.array([1, 2, 3, 4, 5], dtype=dtype_x)
@@ -90,9 +85,7 @@ def test_digitize_diff_types(self, dtype_x, dtype_bins, right):
         expected = numpy.digitize(x, bins, right=right)
         assert_dtype_allclose(result, expected)
 
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True)
-    )
+    @pytest.mark.parametrize("dtype", get_integer_float_dtypes())
     @pytest.mark.parametrize(
         "x, bins",
         [

dpnp/tests/test_linalg.py

@@ -22,6 +22,7 @@
     get_all_dtypes,
     get_complex_dtypes,
     get_float_complex_dtypes,
+    get_integer_float_dtypes,
     has_support_aspect64,
     is_cpu_device,
     is_cuda_device,
@@ -1409,9 +1410,7 @@ def test_einsum_tensor(self):
         result = dpnp.einsum("ijij->", tensor_dp)
         assert_dtype_allclose(result, expected)
 
-    @pytest.mark.parametrize(
-        "dtype", get_all_dtypes(no_bool=True, no_complex=True, no_none=True)
-    )
+    @pytest.mark.parametrize("dtype", get_integer_float_dtypes())
     def test_different_paths(self, dtype):
         # Simple test, designed to exercise most specialized code paths,
         # note the +0.5 for floats.  This makes sure we use a float value

dpnp/tests/test_logic.py

@@ -8,6 +8,7 @@
     get_all_dtypes,
     get_float_complex_dtypes,
     get_float_dtypes,
+    get_integer_float_dtypes,
 )
 
 
@@ -83,7 +84,7 @@ def check_raises(func_name, exception, *args, **kwargs):
         check_raises(func, TypeError, [0, 1, 2, 3])
 
 
-@pytest.mark.parametrize("dtype", get_all_dtypes(no_bool=True, no_complex=True))
+@pytest.mark.parametrize("dtype", get_integer_float_dtypes())
 def test_allclose(dtype):
     a = numpy.random.rand(10)
     b = a + numpy.random.rand(10) * 1e-8
@@ -508,7 +509,7 @@ def test_infinity_sign_errors(func):
         getattr(dpnp, func)(x, out=out)
 
 
-@pytest.mark.parametrize("dtype", get_all_dtypes(no_bool=True, no_complex=True))
+@pytest.mark.parametrize("dtype", get_integer_float_dtypes())
 @pytest.mark.parametrize(
     "rtol", [1e-05, dpnp.array(1e-05), dpnp.full(10, 1e-05)]
 )
@@ -549,7 +550,7 @@ def test_array_equiv(a, b):
     assert_equal(result, expected)
 
 
-@pytest.mark.parametrize("dtype", get_all_dtypes(no_bool=True, no_complex=True))
+@pytest.mark.parametrize("dtype", get_integer_float_dtypes())
 def test_array_equiv_dtype(dtype):
     a = numpy.array([1, 2], dtype=dtype)
     b = numpy.array([1, 2], dtype=dtype)
@@ -575,7 +576,7 @@ def test_array_equiv_scalar(a):
     assert_equal(result, expected)
 
 
-@pytest.mark.parametrize("dtype", get_all_dtypes(no_bool=True, no_complex=True))
+@pytest.mark.parametrize("dtype", get_integer_float_dtypes())
 @pytest.mark.parametrize("equal_nan", [True, False])
 def test_array_equal_dtype(dtype, equal_nan):
     a = numpy.array([1, 2], dtype=dtype)

dpnp/tests/test_manipulation.py

@@ -20,6 +20,7 @@
     get_float_complex_dtypes,
     get_float_dtypes,
     get_integer_dtypes,
+    get_integer_float_dtypes,
     has_support_aspect64,
     numpy_version,
 )
@@ -325,9 +326,7 @@ class TestCopyTo:
     ]
     testdata += [
         ([1, -1, 0], dtype)
-        for dtype in get_all_dtypes(
-            no_none=True, no_bool=True, no_complex=True, no_unsigned=True
-        )
+        for dtype in get_integer_float_dtypes(no_unsigned=True)
     ]
     testdata += [([0.1, 0.0, -0.1], dtype) for dtype in get_float_dtypes()]
     testdata += [([1j, -1j, 1 - 2j], dtype) for dtype in get_complex_dtypes()]