cleaning up some of the guards, removing some of the standalone_numba_cuda reasons (not needed), cleaning up some imports

Author: atmnp

numba_cuda/numba/cuda/__init__.py

@@ -7,10 +7,8 @@
 import warnings
 import sys
 
-# Import version from the parent package
 from numba_cuda._version import __version__
 
-# Generate version_info early to avoid circular import issues
 from numba_cuda._version import generate_version_info
 
 version_info = generate_version_info(__version__)
@@ -22,14 +20,7 @@
 # Re-export all type names
 from numba.cuda.types import *
 
-# Check if upstream numba is available - needs to be defined early to avoid circular imports
-try:
-    import numba
-
-    _HAS_NUMBA = True
-except ImportError:
-    _HAS_NUMBA = False
-
+_HAS_NUMBA = importlib.util.find_spec("numba") is not None
 
 # Require NVIDIA CUDA bindings at import time
 if not (

numba_cuda/numba/cuda/core/errors.py

@@ -15,7 +15,7 @@
 from functools import wraps
 from abc import abstractmethod
 
-from numba_cuda._version import __version__
+import numba_cuda
 
 # Filled at the end
 __all__ = []
@@ -456,7 +456,7 @@ def termcolor():
 This should not have happened, a problem has occurred in Numba's internals.
 You are currently using Numba version %s.
 %s
-""" % (__version__, feedback_details)
+""" % (numba_cuda.__version__, feedback_details)
 
 error_extras = dict()
 error_extras["unsupported_error"] = unsupported_error_info

numba_cuda/numba/cuda/lowering.py

@@ -1880,14 +1880,14 @@ def _lit_or_omitted(value):
     """Returns a Literal instance if the type of value is supported;
     otherwise, return `Omitted(value)`.
     """
-    excepts = LiteralTypingError
+    typing_errors = LiteralTypingError
     if _HAS_NUMBA:
         from numba.core.errors import (
             LiteralTypingError as CoreLiteralTypingError,
         )
 
-        excepts = (LiteralTypingError, CoreLiteralTypingError)
+        typing_errors = (LiteralTypingError, CoreLiteralTypingError)
     try:
         return types.literal(value)
-    except excepts:
+    except typing_errors:
         return types.Omitted(value)

numba_cuda/numba/cuda/tests/core/serialize_usecases.py

@@ -11,10 +11,8 @@
 import numpy as np
 import numpy.random as nprand
 
-from numba.cuda import _HAS_NUMBA
-
-if _HAS_NUMBA:
-    from numba import jit
+# This does not need a guard, it's already guarded at the import site
+from numba import jit
 
 
 @jit("int32(int32, int32)")

numba_cuda/numba/cuda/tests/cudapy/test_datetime.py

@@ -3,8 +3,7 @@
 
 import numpy as np
 
-from numba.cuda import vectorize, guvectorize
-from numba import cuda
+from numba import cuda, vectorize, guvectorize
 from numba.cuda.np.numpy_support import from_dtype
 from numba.cuda.testing import CUDATestCase, skip_on_cudasim
 import unittest

numba_cuda/numba/cuda/tests/cudapy/test_enums.py

@@ -8,8 +8,7 @@
 import numpy as np
 
 from numba.cuda import int16, int32
-from numba.cuda import vectorize
-from numba.cuda import _HAS_NUMBA
+from numba.cuda import vectorize, _HAS_NUMBA
 
 if _HAS_NUMBA:
     from numba import njit
@@ -67,9 +66,7 @@ def f(out):
         f(expected)
         self.assertPreciseEqual(expected, got)
 
-    @skip_on_standalone_numba_cuda(
-        "Test not supported in standalone numba_cuda"
-    )
+    @skip_on_standalone_numba_cuda
     def test_return_from_device_func(self):
         @njit
         def inner(pred):

numba_cuda/numba/cuda/tests/cudapy/test_gufunc_scalar.py

@@ -8,8 +8,7 @@
 """
 
 import numpy as np
-from numba.cuda import guvectorize
-from numba import cuda
+from numba import cuda, guvectorize
 from numba.cuda.testing import skip_on_cudasim, CUDATestCase
 import unittest
 

numba_cuda/numba/cuda/tests/cudapy/test_math.py

@@ -10,8 +10,7 @@
     skip_on_cudasim,
 )
 from numba.cuda.np import numpy_support
-from numba import vectorize
-import numba.cuda as cuda
+from numba import cuda, vectorize
 from numba.cuda import float32, float64, int32, void, int64
 import math
 

numba_cuda/numba/cuda/tests/cudapy/test_overload.py

@@ -237,9 +237,7 @@ def check_overload(self, kernel, expected):
         cuda.jit(kernel)[1, 1](x)
         self.assertEqual(x[0], expected)
 
-    @skip_on_standalone_numba_cuda(
-        "Test not supported in standalone numba_cuda"
-    )
+    @skip_on_standalone_numba_cuda
     def check_overload_cpu(self, kernel, expected):
         x = np.ones(1, dtype=np.int32)
         njit(kernel)(x)
@@ -344,9 +342,7 @@ def kernel(x):
         expected = GENERIC_TARGET_OL_CALLS_TARGET_OL * GENERIC_TARGET_OL
         self.check_overload_cpu(kernel, expected)
 
-    @skip_on_standalone_numba_cuda(
-        "Test not supported in standalone numba_cuda"
-    )
+    @skip_on_standalone_numba_cuda
     def test_overload_attribute_target(self):
         MyDummy, MyDummyType = self.make_dummy_type()
         mydummy_type_cpu = cpu_typeof(MyDummy())  # For @njit (cpu)

numba_cuda/numba/cuda/tests/cudapy/test_serialize.py

@@ -3,8 +3,7 @@
 
 import pickle
 import numpy as np
-from numba.cuda import vectorize
-from numba import cuda
+from numba import cuda, vectorize
 from numba.cuda import types
 from numba.cuda.testing import skip_on_cudasim, CUDATestCase
 import unittest