Merge pull request #1150 from IntelPython/main

Merge main into GOLD

Author: ZzEeKkAa

CHANGELOG.md

@@ -4,17 +4,21 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [0.21.3] - 2023-09-21
+## [0.21.3] - 2023-09-28
 
 ### Fixed
+* Pin CI conda channels (#1133)
 * Mangled kernel name generation (#1112)
 
 ### Added
+* Support tests on single point precision GPUs (#1143)
+* Initial work on Coverity scan CI (#1128)
 * Python 3.11 support (#1123)
 * Security policy (#1117)
-* scikit-build to build native extensions (#1107, #1127)
+* scikit-build to build native extensions (#1107, #1116, #1127, #1139, #1140)
 
 ### Changed
+* Rename helper function to clearly indicate its usage (#1145)
 * The data model used by the DpnpNdArray type for kernel functions(#1118)
 
 ### Removed

numba_dpex/core/typing/typeof.py

@@ -5,7 +5,6 @@
 from dpctl import SyclQueue
 from dpctl.tensor import usm_ndarray
 from dpnp import ndarray
-from numba.core import types
 from numba.extending import typeof_impl
 from numba.np import numpy_support
 
@@ -16,7 +15,7 @@
 from ..types.usm_ndarray_type import USMNdArray
 
 
-def _typeof_helper(val, array_class_type):
+def _array_typeof_helper(val, array_class_type):
     """Creates a Numba type of the specified ``array_class_type`` for ``val``."""
     try:
         dtype = numpy_support.from_dtype(val.dtype)
@@ -74,7 +73,7 @@ def typeof_usm_ndarray(val, c):
 
     Returns: The Numba type corresponding to dpctl.tensor.usm_ndarray
     """
-    return _typeof_helper(val, USMNdArray)
+    return _array_typeof_helper(val, USMNdArray)
 
 
 @typeof_impl.register(ndarray)
@@ -92,7 +91,7 @@ def typeof_dpnp_ndarray(val, c):
 
     Returns: The Numba type corresponding to dpnp.ndarray
     """
-    return _typeof_helper(val, DpnpNdArray)
+    return _array_typeof_helper(val, DpnpNdArray)
 
 
 @typeof_impl.register(SyclQueue)

numba_dpex/tests/_helper.py

@@ -8,6 +8,7 @@
 import shutil
 
 import dpctl
+import dpnp
 import pytest
 
 from numba_dpex import config, numba_sem_version
@@ -138,3 +139,116 @@ def override_config(name, value, config=config):
 
 def _id(obj):
     return obj
+
+
+def get_complex_dtypes(device=None):
+    """
+    Build a list of complex types supported by DPNP based on device capabilities.
+    """
+
+    dev = dpctl.select_default_device() if device is None else device
+
+    # add complex types
+    dtypes = [dpnp.complex64]
+    if dev.has_aspect_fp64:
+        dtypes.append(dpnp.complex128)
+    return dtypes
+
+
+def get_float_dtypes(no_float16=True, device=None):
+    """
+    Build a list of floating types supported by DPNP based on device capabilities.
+    """
+
+    dev = dpctl.select_default_device() if device is None else device
+
+    # add floating types
+    dtypes = []
+    if not no_float16 and dev.has_aspect_fp16:
+        dtypes.append(dpnp.float16)
+
+    dtypes.append(dpnp.float32)
+    if dev.has_aspect_fp64:
+        dtypes.append(dpnp.float64)
+    return dtypes
+
+
+def get_float_complex_dtypes(no_float16=True, device=None):
+    """
+    Build a list of floating and complex types supported by DPNP based on device capabilities.
+    """
+
+    dtypes = get_float_dtypes(no_float16, device)
+    dtypes.extend(get_complex_dtypes(device))
+    return dtypes
+
+
+def get_all_dtypes(
+    no_bool=False,
+    no_int=False,
+    no_float16=True,
+    no_float=False,
+    no_complex=False,
+    no_none=False,
+    device=None,
+):
+    """
+    Build a list of types supported by DPNP based on input flags and device capabilities.
+    """
+
+    dev = dpctl.select_default_device() if device is None else device
+
+    # add boolean type
+    dtypes = [dpnp.bool] if not no_bool else []
+
+    # add integer types
+    if not no_int:
+        dtypes.extend([dpnp.int32, dpnp.int64])
+
+    # add floating types
+    if not no_float:
+        dtypes.extend(get_float_dtypes(no_float16=no_float16, device=dev))
+
+    # add complex types
+    if not no_complex:
+        dtypes.extend(get_complex_dtypes(device=dev))
+
+    # add None value to validate a default dtype
+    if not no_none:
+        dtypes.append(None)
+    return dtypes
+
+
+def get_queue_or_skip(args=tuple()):
+    try:
+        q = dpctl.SyclQueue(*args)
+    except dpctl.SyclQueueCreationError:
+        pytest.skip(f"Queue could not be created from {args}")
+    return q
+
+
+def skip_if_dtype_not_supported(dt, q_or_dev):
+    import dpctl.tensor as dpt
+
+    dt = dpt.dtype(dt)
+    if type(q_or_dev) is dpctl.SyclQueue:
+        dev = q_or_dev.sycl_device
+    elif type(q_or_dev) is dpctl.SyclDevice:
+        dev = q_or_dev
+    else:
+        raise TypeError(
+            "Expected dpctl.SyclQueue or dpctl.SyclDevice, "
+            f"got {type(q_or_dev)}"
+        )
+    dev_has_dp = dev.has_aspect_fp64
+    if dev_has_dp is False and dt in [dpt.float64, dpt.complex128]:
+        pytest.skip(
+            f"{dev.name} does not support double precision floating point types"
+        )
+    dev_has_hp = dev.has_aspect_fp16
+    if dev_has_hp is False and dt in [
+        dpt.float16,
+    ]:
+        pytest.skip(
+            f"{dev.name} does not support half precision floating point type"
+        )

numba_dpex/tests/core/passes/test_parfor_legalize_cfd_pass.py

@@ -14,10 +14,13 @@
 
 from numba_dpex import dpjit
 from numba_dpex.core.exceptions import ExecutionQueueInferenceError
-from numba_dpex.tests._helper import skip_no_opencl_cpu, skip_no_opencl_gpu
+from numba_dpex.tests._helper import (
+    get_all_dtypes,
+    skip_no_opencl_cpu,
+    skip_no_opencl_gpu,
+)
 
 shapes = [10, (2, 5)]
-dtypes = [dpnp.int32, dpnp.int64, dpnp.float32, dpnp.float64]
 usm_types = ["device"]
 devices = ["gpu"]
 
@@ -30,7 +33,12 @@ def func1(a, b):
 
 @skip_no_opencl_gpu
 @pytest.mark.parametrize("shape", shapes)
-@pytest.mark.parametrize("dtype", dtypes)
+@pytest.mark.parametrize(
+    "dtype",
+    get_all_dtypes(
+        no_bool=True, no_float16=True, no_none=True, no_complex=True
+    ),
+)
 @pytest.mark.parametrize("usm_type", usm_types)
 @pytest.mark.parametrize("device", devices)
 def test_parfor_legalize_cfd_pass(shape, dtype, usm_type, device):

numba_dpex/tests/core/types/DpnpNdArray/test_boxing_unboxing.py

@@ -22,7 +22,7 @@ def test_boxing_unboxing():
     def func(a):
         return a
 
-    a = dpnp.empty(10)
+    a = dpnp.empty(10, dtype=dpnp.float32)
     try:
         b = func(a)
     except:
@@ -40,8 +40,8 @@ def test_stride_calc_at_unboxing():
     def _tester(a):
         return a.strides
 
-    b = dpnp.empty((4, 16, 4))
+    b = dpnp.empty((4, 16, 4), dtype=dpnp.float32)
     strides = dpjit(_tester)(b)
 
     # Numba computes strides as bytes
-    assert list(strides) == [512, 32, 8]
+    assert list(strides) == [256, 16, 4]

numba_dpex/tests/core/types/USMNdArray/test_array_creation_errors.py

@@ -1,23 +1,23 @@
 import dpctl
 import pytest
 
-from numba_dpex.core.types import USMNdArray, dpctl_types
+from numba_dpex.core.types import USMNdArray, dpctl_types, float32
 
 
 def test_usmndarray_negative_tests():
     default_device = dpctl.SyclDevice().filter_string
 
-    usmarr1 = USMNdArray(1, device=None, queue=None)
-    assert usmarr1.dtype.name == "float64"
+    usmarr1 = USMNdArray(1, device=None, queue=None, dtype=float32)
+    assert usmarr1.dtype.name == "float32"
     assert usmarr1.ndim == 1
     assert usmarr1.layout == "C"
     assert usmarr1.addrspace == 1
     assert usmarr1.usm_type == "device"
 
     assert usmarr1.queue.sycl_device == default_device
 
-    usmarr2 = USMNdArray(1, device=default_device, queue=None)
-    assert usmarr2.dtype.name == "float64"
+    usmarr2 = USMNdArray(1, device=default_device, queue=None, dtype=float32)
+    assert usmarr2.dtype.name == "float32"
     assert usmarr2.ndim == 1
     assert usmarr2.layout == "C"
     assert usmarr2.addrspace == 1
@@ -26,18 +26,18 @@ def test_usmndarray_negative_tests():
 
     queue = dpctl_types.DpctlSyclQueue(dpctl.SyclQueue())
 
-    usmarr3 = USMNdArray(1, device=None, queue=queue)
-    assert usmarr3.dtype.name == "float64"
+    usmarr3 = USMNdArray(1, device=None, queue=queue, dtype=float32)
+    assert usmarr3.dtype.name == "float32"
     assert usmarr3.ndim == 1
     assert usmarr3.layout == "C"
     assert usmarr3.addrspace == 1
     assert usmarr3.usm_type == "device"
 
     with pytest.raises(TypeError):
-        USMNdArray(1, device=default_device, queue=queue)
+        USMNdArray(1, device=default_device, queue=queue, dtype=float32)
 
     with pytest.raises(TypeError):
-        USMNdArray(1, queue=0)
+        USMNdArray(1, queue=0, dtype=float32)
 
     with pytest.raises(TypeError):
-        USMNdArray(1, device=0)
+        USMNdArray(1, device=0, dtype=float32)

numba_dpex/tests/core/types/USMNdArray/test_usm_ndarray_type.py

@@ -2,12 +2,17 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
+import dpctl
 import dpctl.tensor as dpt
 import numpy as np
 import pytest
 from numba.misc.special import typeof
 
 from numba_dpex.core.types import USMNdArray
+from numba_dpex.tests._helper import (
+    get_queue_or_skip,
+    skip_if_dtype_not_supported,
+)
 
 list_of_dtypes = [
     np.int32,
@@ -35,6 +40,9 @@ def usm_type(request):
 
 
 def test_usm_ndarray_type(dtype, usm_type):
+    q = get_queue_or_skip()
+    skip_if_dtype_not_supported(dtype, q)
+
     a = np.array(np.random.random(10), dtype)
     da = dpt.usm_ndarray(a.shape, dtype=a.dtype, buffer=usm_type)
 

numba_dpex/tests/dpjit_tests/dpnp/test_dpnp_empty.py

@@ -10,9 +10,9 @@
 from numba import errors
 
 from numba_dpex import dpjit
+from numba_dpex.tests._helper import get_all_dtypes
 
 shapes = [11, (2, 5)]
-dtypes = [dpnp.int32, dpnp.int64, dpnp.float32, dpnp.float64]
 usm_types = ["device", "shared", "host"]
 
 
@@ -51,7 +51,12 @@ def func(shape):
 
 
 @pytest.mark.parametrize("shape", shapes)
-@pytest.mark.parametrize("dtype", dtypes)
+@pytest.mark.parametrize(
+    "dtype",
+    get_all_dtypes(
+        no_bool=True, no_float16=True, no_none=True, no_complex=True
+    ),
+)
 @pytest.mark.parametrize("usm_type", usm_types)
 def test_dpnp_empty_from_device(shape, dtype, usm_type):
     """ "Use device only in dpnp.emtpy() inside dpjit."""
@@ -84,7 +89,12 @@ def func(shape):
 
 
 @pytest.mark.parametrize("shape", shapes)
-@pytest.mark.parametrize("dtype", dtypes)
+@pytest.mark.parametrize(
+    "dtype",
+    get_all_dtypes(
+        no_bool=True, no_float16=True, no_none=True, no_complex=True
+    ),
+)
 @pytest.mark.parametrize("usm_type", usm_types)
 def test_dpnp_empty_from_queue(shape, dtype, usm_type):
     """ "Use queue only in dpnp.emtpy() inside dpjit."""
@@ -121,7 +131,9 @@ def test_dpnp_empty_exceptions():
 
     @dpjit
     def func(shape, queue):
-        c = dpnp.empty(shape, sycl_queue=queue, device=device)
+        c = dpnp.empty(
+            shape, sycl_queue=queue, device=device, dtype=dpnp.float32
+        )
         return c
 
     with pytest.raises(errors.TypingError):