from llvmlite.ir import Constant, IRBuilder import llvmlite.ir from numba.core import types, config, cgutils class _ArgManager(object): """ A utility class to handle argument unboxing and cleanup """ def __init__(self, context, builder, api, env_manager, endblk, nargs): self.context = context self.builder = builder self.api = api self.env_manager = env_manager self.arg_count = 0 # how many function arguments have been processed self.cleanups = [] self.nextblk = endblk def add_arg(self, obj, ty): """ Unbox argument and emit code that handles any error during unboxing. Args are cleaned up in reverse order of the parameter list, and cleanup begins as soon as unboxing of any argument fails. E.g. failure on arg2 will result in control flow going through: arg2.err -> arg1.err -> arg0.err -> arg.end (returns) """ # Unbox argument native = self.api.to_native_value(ty, obj) # If an error occurred, go to the cleanup block for # the previous argument with cgutils.if_unlikely(self.builder, native.is_error): self.builder.branch(self.nextblk) # Define the cleanup function for the argument def cleanup_arg(): # Native value reflection self.api.reflect_native_value(ty, native.value, self.env_manager) # Native value cleanup if native.cleanup is not None: native.cleanup() # NRT cleanup # (happens after the native value cleanup as the latter # may need the native value) if self.context.enable_nrt: self.context.nrt.decref(self.builder, ty, native.value) self.cleanups.append(cleanup_arg) # Write the on-error cleanup block for this argument cleanupblk = self.builder.append_basic_block( "arg%d.err" % self.arg_count) with self.builder.goto_block(cleanupblk): cleanup_arg() # Go to next cleanup block self.builder.branch(self.nextblk) self.nextblk = cleanupblk self.arg_count += 1 return native.value def emit_cleanup(self): """ Emit the cleanup code after returning from the wrapped function. """ for dtor in self.cleanups: dtor() class _GilManager(object): """ A utility class to handle releasing the GIL and then re-acquiring it again. """ def __init__(self, builder, api, argman): self.builder = builder self.api = api self.argman = argman self.thread_state = api.save_thread() def emit_cleanup(self): self.api.restore_thread(self.thread_state) self.argman.emit_cleanup() class PyCallWrapper(object): def __init__(self, context, module, func, fndesc, env, call_helper, release_gil): self.context = context self.module = module self.func = func self.fndesc = fndesc self.env = env self.release_gil = release_gil def build(self): wrapname = self.fndesc.llvm_cpython_wrapper_name # This is the signature of PyCFunctionWithKeywords # (see CPython's methodobject.h) pyobj = self.context.get_argument_type(types.pyobject) wrapty = llvmlite.ir.FunctionType(pyobj, [pyobj, pyobj, pyobj]) wrapper = llvmlite.ir.Function(self.module, wrapty, name=wrapname) builder = IRBuilder(wrapper.append_basic_block('entry')) # - `closure` will receive the `self` pointer stored in the # PyCFunction object (see _dynfunc.c) # - `args` and `kws` will receive the tuple and dict objects # of positional and keyword arguments, respectively. closure, args, kws = wrapper.args closure.name = 'py_closure' args.name = 'py_args' kws.name = 'py_kws' api = self.context.get_python_api(builder) self.build_wrapper(api, builder, closure, args, kws) return wrapper, api def build_wrapper(self, api, builder, closure, args, kws): nargs = len(self.fndesc.argtypes) objs = [api.alloca_obj() for _ in range(nargs)] parseok = api.unpack_tuple(args, self.fndesc.qualname, nargs, nargs, *objs) pred = builder.icmp_unsigned( '==', parseok, Constant(parseok.type, None)) with cgutils.if_unlikely(builder, pred): builder.ret(api.get_null_object()) # Block that returns after erroneous argument unboxing/cleanup endblk = builder.append_basic_block("arg.end") with builder.goto_block(endblk): builder.ret(api.get_null_object()) # Get the Environment object env_manager = self.get_env(api, builder) cleanup_manager = _ArgManager(self.context, builder, api, env_manager, endblk, nargs) # Compute the arguments to the compiled Numba function. innerargs = [] for obj, ty in zip(objs, self.fndesc.argtypes): if isinstance(ty, types.Omitted): # It's an omitted value => ignore dummy Python object innerargs.append(None) else: val = cleanup_manager.add_arg(builder.load(obj), ty) innerargs.append(val) if self.release_gil: cleanup_manager = _GilManager(builder, api, cleanup_manager) # We elect to not inline the top level user function into the call # wrapper, this incurs an overhead of a function call, however, it # increases optimisation stability in that the optimised user function # is what will actually be run and it is this function that all the # inspection tools "see". Further, this makes optimisation "stable" in # that calling the user function from e.g. C or from this wrapper will # result in the same code executing, were inlining permitted this may # not be the case as the inline could trigger additional optimisation # as the function goes into the wrapper, this resulting in the executing # instruction stream being different from that of the instruction stream # present in the user function. status, retval = self.context.call_conv.call_function( builder, self.func, self.fndesc.restype, self.fndesc.argtypes, innerargs, attrs=('noinline',)) # Do clean up self.debug_print(builder, "# callwrapper: emit_cleanup") cleanup_manager.emit_cleanup() self.debug_print(builder, "# callwrapper: emit_cleanup end") # Determine return status with builder.if_then(status.is_ok, likely=True): # Ok => return boxed Python value with builder.if_then(status.is_none): api.return_none() retty = self._simplified_return_type() obj = api.from_native_return(retty, retval, env_manager) builder.ret(obj) # Error out self.context.call_conv.raise_error(builder, api, status) builder.ret(api.get_null_object()) def get_env(self, api, builder): """Get the Environment object which is declared as a global in the module of the wrapped function. """ envname = self.context.get_env_name(self.fndesc) gvptr = self.context.declare_env_global(builder.module, envname) envptr = builder.load(gvptr) env_body = self.context.get_env_body(builder, envptr) api.emit_environment_sentry(envptr, return_pyobject=True, debug_msg=self.fndesc.env_name) env_manager = api.get_env_manager(self.env, env_body, envptr) return env_manager def _simplified_return_type(self): """ The NPM callconv has already converted simplified optional types. We can simply use the value type from it. """ restype = self.fndesc.restype # Optional type if isinstance(restype, types.Optional): return restype.type else: return restype def debug_print(self, builder, msg): if config.DEBUG_JIT: self.context.debug_print(builder, "DEBUGJIT: {0}".format(msg))