Removed filter_string from pytest in parfor tests.

drivier.py

@@ -0,0 +1,38 @@
+import dpctl
+import dpnp
+import numpy
+
+from numba_dpex import dpjit
+
+# def parfor_divide(a, b):
+#     return a / b
+
+# def test_built_in_operators(shape=(25, 4), dtype=dpnp.int32, usm_type="shared", func=parfor_divide):
+#     queue = dpctl.SyclQueue()
+#     a = dpnp.zeros(
+#         shape=shape, dtype=dtype, usm_type=usm_type, sycl_queue=queue
+#     )
+#     b = dpnp.ones(shape=shape, dtype=dtype, usm_type=usm_type, sycl_queue=queue)
+
+#     c = dpjit(func)(a, b)
+
+
+#     if len(c.shape) == 1:
+#         assert c.shape[0] == shape
+#     else:
+#         assert c.shape == shape
+
+#     print(c.dtype)
+#     print(c.usm_type)
+
+#     assert c.usm_type == usm_type
+
+#     assert c.sycl_device.filter_string == queue.sycl_device.filter_string
+
+#     expected = dpnp.asnumpy(func(a, b))
+#     nc = dpnp.asnumpy(c)
+
+#     numpy.allclose(nc, expected)
+
+
+# test_built_in_operators()

numba_dpex/tests/dpjit_tests/parfors/test_builtin_ops.py

@@ -36,7 +36,7 @@ def parfor_exponent(a, b):
 
 shapes = [100, (25, 4)]
 dtypes = [dpnp.int32, dpnp.int64, dpnp.float32, dpnp.float64]
-usm_types = ["device", "shared", "host"]
+usm_types = ["device"]
 funcs = [
     parfor_add,
     parfor_sub,
@@ -55,26 +55,66 @@ def parfor_floor(a, b):
 @pytest.mark.parametrize("dtype", dtypes)
 @pytest.mark.parametrize("usm_type", usm_types)
 @pytest.mark.parametrize("func", funcs)
-def test_built_in_operators(shape, dtype, usm_type, func):
+def test_built_in_operators1(shape, dtype, usm_type, func):
     queue = dpctl.SyclQueue()
     a = dpnp.zeros(
         shape=shape, dtype=dtype, usm_type=usm_type, sycl_queue=queue
     )
     b = dpnp.ones(shape=shape, dtype=dtype, usm_type=usm_type, sycl_queue=queue)
     try:
-        c = dpjit(func)(a, b)
+        op = dpjit(func)
+        c = op(a, b)
+        del op
     except Exception:
-        pytest.fail("Running Parfor CFD Pass check failed")
+        pytest.fail("Failed to compile.")
 
     if len(c.shape) == 1:
         assert c.shape[0] == shape
     else:
         assert c.shape == shape
 
-    assert c.dtype == dtype
+    if func != parfor_divide:
+        assert c.dtype == dtype
     assert c.usm_type == usm_type
 
-    assert c.sycl_device.filter_string == queue.device.filter_string
+    assert c.sycl_device.filter_string == queue.sycl_device.filter_string
+
+    expected = dpnp.asnumpy(func(a, b))
+    nc = dpnp.asnumpy(c)
+
+    numpy.allclose(nc, expected)
+
+
+usm_types = ["host", "shared"]
+
+
+@pytest.mark.parametrize("shape", shapes)
+@pytest.mark.parametrize("dtype", dtypes)
+@pytest.mark.parametrize("usm_type", usm_types)
+@pytest.mark.parametrize("func", funcs)
+def test_built_in_operators2(shape, dtype, usm_type, func):
+    queue = dpctl.SyclQueue()
+    a = dpnp.zeros(
+        shape=shape, dtype=dtype, usm_type=usm_type, sycl_queue=queue
+    )
+    b = dpnp.ones(shape=shape, dtype=dtype, usm_type=usm_type, sycl_queue=queue)
+    try:
+        op = dpjit(func)
+        c = op(a, b)
+        del op
+    except Exception:
+        pytest.fail("Failed to compile.")
+
+    if len(c.shape) == 1:
+        assert c.shape[0] == shape
+    else:
+        assert c.shape == shape
+
+    if func != parfor_divide:
+        assert c.dtype == dtype
+    assert c.usm_type == usm_type
+
+    assert c.sycl_device.filter_string == queue.sycl_device.filter_string
 
     expected = dpnp.asnumpy(func(a, b))
     nc = dpnp.asnumpy(c)

numba_dpex/tests/dpjit_tests/parfors/test_dpnp_bitwise_ops.py

@@ -9,7 +9,6 @@
 import pytest
 
 from numba_dpex import dpjit
-from numba_dpex.tests._helper import assert_auto_offloading, filter_strings
 
 list_of_binary_ops = [
     "bitwise_and",
@@ -51,8 +50,7 @@ def input_arrays(request):
     return a, b
 
 
-@pytest.mark.parametrize("filter_str", filter_strings)
-def test_binary_ops(filter_str, binary_op, input_arrays):
+def test_binary_ops(binary_op, input_arrays):
     a, b = input_arrays
     binop = getattr(dpnp, binary_op)
     actual = dpnp.empty(shape=a.shape, dtype=a.dtype)
@@ -73,8 +71,7 @@ def f(a, b):
     )
 
 
-@pytest.mark.parametrize("filter_str", filter_strings)
-def test_unary_ops(filter_str, unary_op, input_arrays):
+def test_unary_ops(unary_op, input_arrays):
     a = input_arrays[0]
     uop = getattr(dpnp, unary_op)
     actual = np.empty(shape=a.shape, dtype=a.dtype)

numba_dpex/tests/dpjit_tests/parfors/test_dpnp_logic_ops.py

@@ -9,7 +9,6 @@
 import pytest
 
 from numba_dpex import dpjit
-from numba_dpex.tests._helper import assert_auto_offloading, filter_strings
 
 """ Following cases, dpnp raises NotImplementedError"""
 
@@ -61,8 +60,7 @@ def input_arrays(request):
 
 
 @pytest.mark.xfail
-@pytest.mark.parametrize("filter_str", filter_strings)
-def test_binary_ops(filter_str, binary_op, input_arrays):
+def test_binary_ops(binary_op, input_arrays):
     a, b = input_arrays
     binop = getattr(dpnp, binary_op)
     actual = dpnp.empty(shape=a.shape, dtype=a.dtype)
@@ -84,8 +82,7 @@ def f(a, b):
 
 
 @pytest.mark.xfail
-@pytest.mark.parametrize("filter_str", filter_strings)
-def test_unary_ops(filter_str, unary_op, input_arrays):
+def test_unary_ops(unary_op, input_arrays):
     a = input_arrays[0]
     uop = getattr(dpnp, unary_op)
     actual = dpnp.empty(shape=a.shape, dtype=a.dtype)

numba_dpex/tests/dpjit_tests/parfors/test_dpnp_transcedental_functions.py

@@ -9,11 +9,7 @@
 import pytest
 
 from numba_dpex import dpjit
-from numba_dpex.tests._helper import (
-    assert_auto_offloading,
-    filter_strings,
-    is_gen12,
-)
+from numba_dpex.tests._helper import is_gen12
 
 """dpnp raise error on : mod, abs and remainder(float32)"""
 list_of_binary_ops = [
@@ -82,8 +78,7 @@ def input_arrays(request):
     return a, b
 
 
-@pytest.mark.parametrize("filter_str", filter_strings)
-def test_binary_ops(filter_str, binary_op, input_arrays):
+def test_binary_ops(binary_op, input_arrays):
     a, b = input_arrays
     binop = getattr(dpnp, binary_op)
     actual = dpnp.empty(shape=a.shape, dtype=a.dtype)
@@ -105,10 +100,10 @@ def f(a, b):
     )
 
 
-@pytest.mark.parametrize("filter_str", filter_strings)
-def test_unary_ops(filter_str, unary_op, input_arrays):
+def test_unary_ops(unary_op, input_arrays):
     skip_ops = ["abs", "sign", "log", "log2", "log10", "expm1"]
-    if unary_op in skip_ops and is_gen12(filter_str):
+    device = dpctl.SyclDevice()
+    if unary_op in skip_ops and is_gen12(device.filter_string):
         pytest.skip()
 
     a = input_arrays[0]

numba_dpex/tests/dpjit_tests/parfors/test_dpnp_trigonometric_functions.py

@@ -9,23 +9,7 @@
 import pytest
 
 from numba_dpex import dpjit
-from numba_dpex.tests._helper import (
-    assert_auto_offloading,
-    filter_strings,
-    is_gen12,
-)
-
-list_of_filter_strs = [
-    "opencl:gpu:0",
-    "level_zero:gpu:0",
-    "opencl:cpu:0",
-]
-
-
-@pytest.fixture(params=list_of_filter_strs)
-def filter_str(request):
-    return request.param
-
+from numba_dpex.tests._helper import is_gen12
 
 list_of_trig_ops = [
     "sin",
@@ -74,10 +58,10 @@ def input_arrays(request):
     return a, b
 
 
-@pytest.mark.parametrize("filter_str", filter_strings)
-def test_trigonometric_fn(filter_str, trig_op, input_arrays):
+def test_trigonometric_fn(trig_op, input_arrays):
     # FIXME: Why does archcosh fail on Gen12 discrete graphics card?
-    if trig_op == "arccosh" and is_gen12(filter_str):
+    device = dpctl.SyclDevice()
+    if trig_op == "arccosh" and is_gen12(device.filter_string):
         pytest.skip()
 
     a, b = input_arrays