fix TestKron, TestTake, and avoid warnings

Author: vtavana

dpnp/tests/test_indexing.py

@@ -703,8 +703,8 @@ def test_1d(self, a_dt, ind_dt, indices, mode):
         elif numpy.issubdtype(ind_dt, numpy.uint64):
             # For this special case, although casting `ind_dt` to numpy.intp
             # is not safe, both NumPy and dpnp work properly
-            # NumPy < "2.2.0" raises an error on Windows
-            if numpy_version() < "2.2.0" and is_win_platform():
+            # NumPy < "2.2.0" raises an error
+            if numpy_version() < "2.2.0":
                 ind = ind.astype(numpy.int64)
             result = dpnp.take(ia, iind, mode=mode)
             expected = numpy.take(a, ind, mode=mode)

dpnp/tests/test_nanfunctions.py

@@ -15,6 +15,7 @@
 
 from .helper import (
     assert_dtype_allclose,
+    get_abs_array,
     get_all_dtypes,
     get_complex_dtypes,
     get_float_complex_dtypes,
@@ -648,7 +649,7 @@ class TestNanStd:
     )
     def test_nanstd(self, array, dtype):
         try:
-            a = numpy.array(array, dtype=dtype)
+            a = get_abs_array(array, dtype=dtype)
         except:
             pytest.skip("floating datat type is needed to store NaN")
         ia = dpnp.array(a)
@@ -835,9 +836,9 @@ class TestNanVar:
     )
     def test_nanvar(self, array, dtype):
         try:
-            a = numpy.array(array, dtype=dtype)
+            a = get_abs_array(array, dtype=dtype)
         except:
-            pytest.skip("floating datat type is needed to store NaN")
+            pytest.skip("floating data type is needed to store NaN")
         ia = dpnp.array(a)
         for ddof in range(a.ndim):
             expected = numpy.nanvar(a, ddof=ddof)

dpnp/tests/test_product.py

@@ -510,8 +510,9 @@ def test_scalar(self, dtype):
 
         result = dpnp.kron(ib, a)
         expected = numpy.kron(b, a)
-        # NumPy returns incorrect dtype on Windows
-        flag = not is_win_platform() if numpy_version() < "2.0.0" else True
+        # NumPy returns incorrect dtype for numpy_version() < "2.0.0"
+        flag = dtype in [numpy.int64, numpy.float64, numpy.complex128]
+        flag = flag or numpy_version() >= "2.0.0"
         assert_dtype_allclose(result, expected, check_type=flag)
 
     @pytest.mark.parametrize("dtype", get_all_dtypes(no_none=True))