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)