def run_pass(self, state):
targetctx = state.targetctx
library = state.library
interp = state.func_ir # why is it called this?!
typemap = state.typemap
restype = state.return_type
calltypes = state.calltypes
flags = state.flags
metadata = state.metadata
msg = ("Function %s failed at nopython "
"mode lowering" % (state.func_id.func_name,))
with fallback_context(state, msg):
# Lowering
fndesc = \
funcdesc.PythonFunctionDescriptor.from_specialized_function(
interp, typemap, restype, calltypes,
mangler=targetctx.mangler, inline=flags.forceinline,
noalias=flags.noalias)
with targetctx.push_code_library(library):
lower = lowering.Lower(targetctx, library, fndesc, interp,
metadata=metadata)
lower.lower()
if not flags.no_cpython_wrapper:
lower.create_cpython_wrapper(flags.release_gil)
if not flags.no_cfunc_wrapper:
# skip cfunc wrapper generation if unsupported
# argument or return types are used
for t in state.args:
if isinstance(t, (types.Omitted, types.Generator)):
break
else:
if isinstance(restype,
(types.Optional, types.Generator)):
pass
else:
lower.create_cfunc_wrapper()
env = lower.env
call_helper = lower.call_helper
del lower
from numba.core.compiler import _LowerResult # TODO: move this
if flags.no_compile:
state['cr'] = _LowerResult(fndesc, call_helper,
cfunc=None, env=env)
else:
# Prepare for execution
cfunc = targetctx.get_executable(library, fndesc, env)
# Insert native function for use by other jitted-functions.
# We also register its library to allow for inlining.
targetctx.insert_user_function(cfunc, fndesc, [library])
state['cr'] = _LowerResult(fndesc, call_helper,
cfunc=cfunc, env=env)
return True
def run_pass(self, state):
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()
library = state.library
targetctx = state.targetctx
interp = state.func_ir # why is it called this?!
typemap = state.typemap
restype = state.return_type
calltypes = state.calltypes
flags = state.flags
metadata = state.metadata
pre_stats = llvm.passmanagers.dump_refprune_stats()
msg = ("Function %s failed at nopython "
"mode lowering" % (state.func_id.func_name, ))
with fallback_context(state, msg):
# Lowering
fndesc = \
funcdesc.PythonFunctionDescriptor.from_specialized_function(
interp, typemap, restype, calltypes,
mangler=targetctx.mangler, inline=flags.forceinline,
noalias=flags.noalias)
with targetctx.push_code_library(library):
lower = lowering.Lower(targetctx,
library,
fndesc,
interp,
metadata=metadata)
lower.lower()
if not flags.no_cpython_wrapper:
lower.create_cpython_wrapper(flags.release_gil)
if not flags.no_cfunc_wrapper:
# skip cfunc wrapper generation if unsupported
# argument or return types are used
for t in state.args:
if isinstance(t, (types.Omitted, types.Generator)):
break
else:
if isinstance(restype,
(types.Optional, types.Generator)):
pass
else:
lower.create_cfunc_wrapper()
env = lower.env
call_helper = lower.call_helper
del lower
from numba.core.compiler import _LowerResult # TODO: move this
if flags.no_compile:
state['cr'] = _LowerResult(fndesc,
call_helper,
cfunc=None,
env=env)
else:
# Prepare for execution
cfunc = targetctx.get_executable(library, fndesc, env)
# Insert native function for use by other jitted-functions.
# We also register its library to allow for inlining.
targetctx.insert_user_function(cfunc, fndesc, [library])
state['cr'] = _LowerResult(fndesc,
call_helper,
cfunc=cfunc,
env=env)
# capture pruning stats
post_stats = llvm.passmanagers.dump_refprune_stats()
metadata['prune_stats'] = post_stats - pre_stats
# Save the LLVM pass timings
metadata['llvm_pass_timings'] = library.recorded_timings
return True
