def run_pass(self, state):
"""
Back-end: Generate LLVM IR from Numba IR, compile to machine code
"""
lowered = state['cr']
signature = typing.signature(state.return_type, *state.args)
from numba.core.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,
lifted=state.lifted,
fndesc=lowered.fndesc,
environment=lowered.env,
metadata=state.metadata,
reload_init=state.reload_init,
)
return True
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.core.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):
"""
Back-end: Packages lowering output in a compile result
"""
lowered = state['cr']
signature = typing.signature(state.return_type, *state.args)
state.cr = compile_result(
typing_context=state.typingctx,
target_context=state.targetctx,
typing_error=state.status.fail_reason,
type_annotation=state.type_annotation,
library=state.library,
call_helper=lowered.call_helper,
signature=signature,
fndesc=lowered.fndesc,
)
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.core.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.core.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
