update third party tests for newly added integr dtypes (int8, int16, uint8-uint64) (#2239)

In this PR, third party tests are update to pass with newly added
integer dtypes (int8, int16, uint8, uint16, uint32, uint64).
This PR is in continuation of
#2233.

Author: vtavana

.github/workflows/conda-package.yml

@@ -529,7 +529,7 @@ jobs:
         env:
           DPNP_TEST_ALL_INT_TYPES: 1
         run: |
-          pytest -n auto -ra --pyargs ${{ env.PACKAGE_NAME }}.tests
+          pytest -ra --pyargs ${{ env.PACKAGE_NAME }}.tests
 
   upload:
     name: Upload ['${{ matrix.os }}', python='${{ matrix.python }}']

dpnp/dpnp_algo/dpnp_elementwise_common.py

@@ -590,12 +590,13 @@ def __init__(
     def __call__(self, x, decimals=0, out=None, dtype=None):
         if decimals != 0:
             x_usm = dpnp.get_usm_ndarray(x)
-            if dpnp.issubdtype(x_usm.dtype, dpnp.integer) and dtype is None:
-                dtype = x_usm.dtype
-
             out_usm = None if out is None else dpnp.get_usm_ndarray(out)
-            x_usm = dpt.round(x_usm * 10**decimals, out=out_usm)
-            res_usm = dpt.divide(x_usm, 10**decimals, out=out_usm)
+
+            if dpnp.issubdtype(x_usm.dtype, dpnp.integer):
+                res_usm = dpt.round(x_usm, out=out_usm)
+            else:
+                x_usm = dpt.round(x_usm * 10**decimals, out=out_usm)
+                res_usm = dpt.divide(x_usm, 10**decimals, out=out_usm)
 
             if dtype is not None:
                 res_usm = dpt.astype(res_usm, dtype, copy=False)

dpnp/dpnp_iface_manipulation.py

@@ -1469,7 +1469,20 @@ def copyto(dst, src, casting="same_kind", where=True):
             f"but got {type(dst)}"
         )
     if not dpnp.is_supported_array_type(src):
+        no_dtype_attr = not hasattr(src, "dtype")
         src = dpnp.array(src, sycl_queue=dst.sycl_queue)
+        if no_dtype_attr:
+            # This case (scalar, list, etc) needs special handling to
+            # behave similar to NumPy
+            if dpnp.issubdtype(src, dpnp.integer) and dpnp.issubdtype(
+                dst, dpnp.unsignedinteger
+            ):
+                if dpnp.any(src < 0):
+                    raise OverflowError(
+                        "Cannot copy negative values to an unsigned int array"
+                    )
+
+                src = src.astype(dst.dtype)
 
     if not dpnp.can_cast(src.dtype, dst.dtype, casting=casting):
         raise TypeError(

dpnp/tests/test_sycl_queue.py

@@ -810,6 +810,7 @@ def test_reduce_hypot(device):
             [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0],
             [5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0],
         ),
+        pytest.param("round", [1.234, 2.567], 2),
         pytest.param("searchsorted", [11, 12, 13, 14, 15], [-10, 20, 12, 13]),
         pytest.param(
             "subtract",

dpnp/tests/test_usm_type.py

@@ -740,6 +740,7 @@ def test_1in_1out(func, data, usm_type):
         pytest.param("maximum", [0.0, 1.0, 2.0], [3.0, 4.0, 5.0]),
         pytest.param("minimum", [0.0, 1.0, 2.0], [3.0, 4.0, 5.0]),
         pytest.param("nextafter", [1, 2], [2, 1]),
+        pytest.param("round", [1.234, 2.567], 2),
         pytest.param("searchsorted", [11, 12, 13, 14, 15], [-10, 20, 12, 13]),
         pytest.param(
             "tensordot",

dpnp/tests/third_party/cupy/core_tests/test_elementwise.py

@@ -4,7 +4,11 @@
 import pytest
 
 import dpnp as cupy
-from dpnp.tests.helper import has_support_aspect64
+from dpnp.tests.helper import (
+    has_support_aspect64,
+    is_win_platform,
+    numpy_version,
+)
 from dpnp.tests.third_party.cupy import testing
 
 
@@ -94,20 +98,22 @@ class TestElementwiseType(unittest.TestCase):
     @testing.for_int_dtypes(no_bool=True)
     @testing.numpy_cupy_array_equal(accept_error=OverflowError)
     def test_large_int_upper_1(self, xp, dtype):
-        a = xp.array([0], dtype=numpy.int8)
+        a = xp.array([0], dtype=xp.int8)
         b = xp.iinfo(dtype).max
         return a + b
 
     @testing.for_int_dtypes(no_bool=True)
     @testing.numpy_cupy_array_equal(accept_error=OverflowError)
     def test_large_int_upper_2(self, xp, dtype):
-        if (
-            numpy.issubdtype(dtype, numpy.unsignedinteger)
-            and numpy.lib.NumpyVersion(numpy.__version__) < "2.0.0"
-        ):
-            pytest.skip("numpy promotes dtype differently")
+        if numpy_version() < "2.0.0":
+            flag = dtype in [xp.int16, xp.int32, xp.int64, xp.longlong]
+            if xp.issubdtype(dtype, xp.unsignedinteger) or flag:
+                pytest.skip("numpy doesn't raise OverflowError")
+
+            if dtype in [xp.int8, xp.intc] and is_win_platform():
+                pytest.skip("numpy promotes dtype differently")
 
-        a = xp.array([1], dtype=numpy.int8)
+        a = xp.array([1], dtype=xp.int8)
         b = xp.iinfo(dtype).max - 1
         return a + b
 
@@ -116,7 +122,7 @@ def test_large_int_upper_2(self, xp, dtype):
     def test_large_int_upper_3(self, xp, dtype):
         if (
             numpy.issubdtype(dtype, numpy.unsignedinteger)
-            and numpy.lib.NumpyVersion(numpy.__version__) < "2.0.0"
+            and numpy_version() < "2.0.0"
         ):
             pytest.skip("numpy promotes dtype differently")
         elif (
@@ -134,7 +140,7 @@ def test_large_int_upper_3(self, xp, dtype):
     def test_large_int_upper_4(self, xp, dtype):
         if (
             numpy.issubdtype(dtype, numpy.unsignedinteger)
-            and numpy.lib.NumpyVersion(numpy.__version__) < "2.0.0"
+            and numpy_version() < "2.0.0"
         ):
             pytest.skip("numpy promotes dtype differently")
         elif (
@@ -150,14 +156,28 @@ def test_large_int_upper_4(self, xp, dtype):
     @testing.for_int_dtypes(no_bool=True)
     @testing.numpy_cupy_array_equal(accept_error=OverflowError)
     def test_large_int_lower_1(self, xp, dtype):
-        a = xp.array([0], dtype=numpy.int8)
+        if numpy_version() < "2.0.0":
+            if dtype in [xp.int16, xp.int32, xp.int64, xp.longlong]:
+                pytest.skip("numpy doesn't raise OverflowError")
+
+            if dtype in [xp.int8, xp.intc] and is_win_platform():
+                pytest.skip("numpy promotes dtype differently")
+
+        a = xp.array([0], dtype=xp.int8)
         b = xp.iinfo(dtype).min
         return a + b
 
     @testing.for_int_dtypes(no_bool=True)
     @testing.numpy_cupy_array_equal(accept_error=OverflowError)
     def test_large_int_lower_2(self, xp, dtype):
-        a = xp.array([-1], dtype=numpy.int8)
+        if numpy_version() < "2.0.0":
+            if dtype in [xp.int16, xp.int32, xp.int64, xp.longlong]:
+                pytest.skip("numpy doesn't raise OverflowError")
+
+            if dtype in [xp.int8, xp.intc] and is_win_platform():
+                pytest.skip("numpy promotes dtype differently")
+
+        a = xp.array([-1], dtype=xp.int8)
         b = xp.iinfo(dtype).min + 1
         return a + b
 
@@ -166,7 +186,7 @@ def test_large_int_lower_2(self, xp, dtype):
     def test_large_int_lower_3(self, xp, dtype):
         if (
             numpy.issubdtype(dtype, numpy.unsignedinteger)
-            and numpy.lib.NumpyVersion(numpy.__version__) < "2.0.0"
+            and numpy_version() < "2.0.0"
         ):
             pytest.skip("numpy promotes dtype differently")
         elif (

dpnp/tests/third_party/cupy/core_tests/test_ndarray_complex_ops.py

@@ -4,7 +4,6 @@
 import pytest
 
 import dpnp as cupy
-from dpnp.tests.helper import has_support_aspect64
 from dpnp.tests.third_party.cupy import testing
 
 
@@ -41,8 +40,10 @@ def test_conjugate_pass(self, xp, dtype):
 
 class TestAngle(unittest.TestCase):
 
+    # For dtype=int8, uint8, NumPy returns float16, but dpnp returns float32
+    # so type_check=False
     @testing.for_all_dtypes()
-    @testing.numpy_cupy_array_almost_equal(type_check=has_support_aspect64())
+    @testing.numpy_cupy_array_almost_equal(type_check=False)
     def test_angle(self, xp, dtype):
         x = testing.shaped_arange((2, 3), xp, dtype)
         return xp.angle(x)

dpnp/tests/third_party/cupy/core_tests/test_ndarray_copy_and_view.py

@@ -338,7 +338,7 @@ def test_astype_type(self, src_dtype, dst_dtype, order):
         b = astype_without_warning(a, dst_dtype, order=order)
         a_cpu = testing.shaped_arange((2, 3, 4), numpy, src_dtype)
         b_cpu = astype_without_warning(a_cpu, dst_dtype, order=order)
-        assert b.dtype.type == b_cpu.dtype.type
+        assert b.dtype == b_cpu.dtype
 
     @testing.for_orders("CAK")
     @testing.for_all_dtypes()

dpnp/tests/third_party/cupy/creation_tests/test_ranges.py

@@ -227,7 +227,13 @@ def test_linspace_mixed_start_stop2(self, xp, dtype_range, dtype_out):
         # TODO (ev-br): np 2.0: had to bump the default rtol on Windows
         #               and numpy 1.26+weak promotion from 0 to 5e-6
         if xp.dtype(dtype_range).kind in "u":
-            start = xp.array([160, 120], dtype=dtype_range)
+            # to avoid overflow, limit `val` to be smaller
+            # than xp.iinfo(dtype).max
+            if dtype_range == xp.uint8 or dtype_out == xp.uint8:
+                val = 125
+            else:
+                val = 160
+            start = xp.array([val, 120], dtype=dtype_range)
         else:
             start = xp.array([-120, 120], dtype=dtype_range)
         stop = 0

dpnp/tests/third_party/cupy/indexing_tests/test_indexing.py

@@ -204,6 +204,10 @@ class TestChoose(unittest.TestCase):
     @testing.for_all_dtypes()
     @testing.numpy_cupy_array_equal()
     def test_choose(self, xp, dtype):
+        # TODO: include additional dtype when dpnp#2201 is merged
+        dtype_list = [xp.int8, xp.int16]
+        if dtype in dtype_list or xp.issubdtype(dtype, xp.unsignedinteger):
+            pytest.skip("dpnp.choose() does not support new integer dtypes.")
         a = xp.array([0, 2, 1, 2])
         c = testing.shaped_arange((3, 4), xp, dtype)
         return a.choose(c)