def _backend(self, lowerfn, objectmode): """ Back-end: Generate LLVM IR from Numba IR, compile to machine code """ if self.library is None: codegen = self.targetctx.codegen() self.library = codegen.create_library(self.func_id.func_qualname) # Enable object caching upfront, so that the library can # be later serialized. self.library.enable_object_caching() lowered = lowerfn() signature = typing.signature(self.return_type, *self.args) self.cr = compile_result( typing_context=self.typingctx, target_context=self.targetctx, entry_point=lowered.cfunc, typing_error=self.status.fail_reason, type_annotation=self.type_annotation, library=self.library, call_helper=lowered.call_helper, signature=signature, objectmode=objectmode, interpmode=False, lifted=self.lifted, fndesc=lowered.fndesc, environment=lowered.env, metadata=self.metadata, )
def run_pass(self, state): """ Back-end: Generate LLVM IR from Numba IR, compile to machine code """ if state.library is None: codegen = state.targetctx.codegen() state.library = codegen.create_library(state.func_id.func_qualname) # Enable object caching upfront, so that the library can # be later serialized. state.library.enable_object_caching() # TODO: Pull this out into the pipeline NativeLowering().run_pass(state) lowered = state['cr'] signature = typing.signature(state.return_type, *state.args) from numba.compiler import compile_result state.cr = compile_result( typing_context=state.typingctx, target_context=state.targetctx, entry_point=lowered.cfunc, typing_error=state.status.fail_reason, type_annotation=state.type_annotation, library=state.library, call_helper=lowered.call_helper, signature=signature, objectmode=False, interpmode=False, lifted=state.lifted, fndesc=lowered.fndesc, environment=lowered.env, metadata=state.metadata, reload_init=state.reload_init, ) return True
def run_pass(self, state): """ Just create a compile result for interpreter mode """ args = [types.pyobject] * len(state.args) signature = typing.signature(types.pyobject, *args) from numba.compiler import compile_result state.cr = compile_result( typing_context=state.typingctx, target_context=state.targetctx, entry_point=state.func_id.func, typing_error=state.status.fail_reason, type_annotation="<Interpreter mode function>", signature=signature, objectmode=False, interpmode=True, lifted=(), fndesc=None, ) return True
def run_pass(self, state): """ Lowering for object mode """ if state.library is None: codegen = state.targetctx.codegen() state.library = codegen.create_library(state.func_id.func_qualname) # Enable object caching upfront, so that the library can # be later serialized. state.library.enable_object_caching() def backend_object_mode(): """ Object mode compilation """ with giveup_context( state, "Function %s failed at object mode lowering" % (state.func_id.func_name, )): if len(state.args) != state.nargs: # append missing # BUG?: What's going on with nargs here? # check state.nargs vs self.nargs on original code state.args = (tuple(state.args) + (types.pyobject, ) * (state.nargs - len(state.args))) return self._py_lowering_stage(state.targetctx, state.library, state.func_ir, state.flags) lowered = backend_object_mode() signature = typing.signature(state.return_type, *state.args) from numba.compiler import compile_result state.cr = compile_result( typing_context=state.typingctx, target_context=state.targetctx, entry_point=lowered.cfunc, typing_error=state.status.fail_reason, type_annotation=state.type_annotation, library=state.library, call_helper=lowered.call_helper, signature=signature, objectmode=True, interpmode=False, lifted=state.lifted, fndesc=lowered.fndesc, environment=lowered.env, metadata=state.metadata, reload_init=state.reload_init, ) # Warn, deprecated behaviour, code compiled in objmode without # force_pyobject indicates fallback from nopython mode if not state.flags.force_pyobject: # first warn about object mode and yes/no to lifted loops if len(state.lifted) > 0: warn_msg = ('Function "%s" was compiled in object mode without' ' forceobj=True, but has lifted loops.' % (state.func_id.func_name, )) else: warn_msg = ('Function "%s" was compiled in object mode without' ' forceobj=True.' % (state.func_id.func_name, )) warnings.warn(errors.NumbaWarning(warn_msg, state.func_ir.loc)) url = ("http://numba.pydata.org/numba-doc/latest/reference/" "deprecation.html#deprecation-of-object-mode-fall-" "back-behaviour-when-using-jit") msg = ("\nFall-back from the nopython compilation path to the " "object mode compilation path has been detected, this is " "deprecated behaviour.\n\nFor more information visit %s" % url) warnings.warn( errors.NumbaDeprecationWarning(msg, state.func_ir.loc)) if state.flags.release_gil: warn_msg = ("Code running in object mode won't allow parallel" " execution despite nogil=True.") warnings.warn_explicit(warn_msg, errors.NumbaWarning, state.func_id.filename, state.func_id.firstlineno) return True