class NumbaContext(miniast.LLVMContext):
# debug = True
# debug_elements = True
# Accept dynamic arguments
astbuilder_cls = miniast.DynamicArgumentASTBuilder
shape_type = minitypes.npy_intp.pointer()
strides_type = shape_type
def init(self):
self.astbuilder = self.astbuilder_cls(self)
self.typemapper = NumbaTypeMapper(self)
def is_object(self, type):
return super(NumbaContext, self).is_object(type) or type.is_array
def promote_types(self, *args, **kwargs):
return self.typemapper.promote_types(*args, **kwargs)
class NumbaContext(miniast.LLVMContext):
# debug = True
# debug_elements = True
# Accept dynamic arguments
astbuilder_cls = miniast.DynamicArgumentASTBuilder
shape_type = minitypes.npy_intp.pointer()
strides_type = shape_type
optimize_broadcasting = False
def init(self):
self.astbuilder = self.astbuilder_cls(self)
self.typemapper = NumbaTypeMapper(self)
def is_object(self, type):
return super(NumbaContext, self).is_object(type) or type.is_array
def promote_types(self, *args, **kwargs):
return self.typemapper.promote_types(*args, **kwargs)
def init(self):
self.astbuilder = self.astbuilder_cls(self)
self.typemapper = NumbaTypeMapper(self)
def init(self):
self.astbuilder = self.astbuilder_cls(self)
self.typemapper = NumbaTypeMapper(self)
