address more review comments

Author: atmnp

numba_cuda/numba/cuda/__init__.py

@@ -7,7 +7,6 @@
 import warnings
 import sys
 
-from numba_cuda._version import __version__
 
 # Re-export types itself
 import numba.cuda.types as types
@@ -69,6 +68,3 @@
     )
 
 from numba.cuda.np.ufunc import vectorize, guvectorize
-from numba.cuda.misc import quicksort, mergesort
-from numba.cuda.misc.special import literal_unroll
-from numba.cuda.np.numpy_support import *

numba_cuda/numba/cuda/core/ir.py

@@ -28,7 +28,6 @@
     ConstantInferenceError,
 )
 from numba.cuda.core import consts
-from numba.cuda import HAS_NUMBA
 
 # terminal color markup
 _termcolor = errors.termcolor()
@@ -783,7 +782,7 @@ def __init__(self, value, loc):
         if HAS_NUMBA:
             assert isinstance(loc, (Loc, numba.core.ir.Loc))
         else:
-            assert isinstance(loc)
+            assert isinstance(loc, (Loc))
         self.value = value
         self.loc = loc
 

numba_cuda/numba/cuda/core/untyped_passes.py

@@ -12,6 +12,7 @@
     SSACompliantMixin,
     register_pass,
 )
+from numba import cuda
 from numba.cuda.core import postproc, bytecode, transforms, inline_closurecall
 from numba.cuda.core import (
     errors,
@@ -632,8 +633,6 @@ def __init__(self):
         FunctionPass.__init__(self)
 
     def run_pass(self, state):
-        from numba import njit
-
         func_ir = state.func_ir
         mutated = False
         for idx, blk in func_ir.blocks.items():
@@ -669,7 +668,7 @@ def run_pass(self, state):
                                 continue
 
                             pyfunc = convert_code_obj_to_function(node, func_ir)
-                            func = njit()(pyfunc)
+                            func = cuda.jit()(pyfunc)
                             new_node = ir.Global(
                                 node.code.co_name, func, stmt.loc
                             )

numba_cuda/numba/cuda/cpython/listobj.py

@@ -19,9 +19,8 @@
     RefType,
 )
 from numba.cuda.extending import overload_method, overload
-from numba.cuda.misc import quicksort
 from numba.cuda.cpython import slicing
-from numba.cuda import literal_unroll
+from numba.cuda.misc.special import literal_unroll
 
 registry = Registry("listobj")
 lower = registry.lower
@@ -1132,17 +1131,6 @@ def gt(a, b):
     return a > b
 
 
-sort_forwards = quicksort.make_jit_quicksort().run_quicksort
-sort_backwards = quicksort.make_jit_quicksort(lt=gt).run_quicksort
-
-arg_sort_forwards = quicksort.make_jit_quicksort(
-    is_argsort=True, is_list=True
-).run_quicksort
-arg_sort_backwards = quicksort.make_jit_quicksort(
-    is_argsort=True, lt=gt, is_list=True
-).run_quicksort
-
-
 def _sort_check_reverse(reverse):
     if isinstance(reverse, types.Omitted):
         rty = reverse.value
@@ -1168,35 +1156,6 @@ def _sort_check_key(key):
         raise errors.TypingError(msg)
 
 
-@overload_method(types.List, "sort")
-def ol_list_sort(lst, key=None, reverse=False):
-    _sort_check_key(key)
-    _sort_check_reverse(reverse)
-
-    if cgutils.is_nonelike(key):
-        KEY = False
-        sort_f = sort_forwards
-        sort_b = sort_backwards
-    elif isinstance(key, types.Dispatcher):
-        KEY = True
-        sort_f = arg_sort_forwards
-        sort_b = arg_sort_backwards
-
-    def impl(lst, key=None, reverse=False):
-        if KEY is True:
-            _lst = [key(x) for x in lst]
-        else:
-            _lst = lst
-        if reverse is False or reverse == 0:
-            tmp = sort_f(_lst)
-        else:
-            tmp = sort_b(_lst)
-        if KEY is True:
-            lst[:] = [lst[i] for i in tmp]
-
-    return impl
-
-
 @overload(sorted)
 def ol_sorted(iterable, key=None, reverse=False):
     if not isinstance(iterable, types.IterableType):