class Flags(utils.ConfigOptions):
# These options are all false by default, but the defaults are
# different with the @jit decorator (see targets.options.TargetOptions).
OPTIONS = {
# Enable loop-lifting
'enable_looplift': False,
# Enable pyobject mode (in general)
'enable_pyobject': False,
# Enable pyobject mode inside lifted loops
'enable_pyobject_looplift': False,
# Enable SSA:
'enable_ssa': True,
# Force pyobject mode inside the whole function
'force_pyobject': False,
# Release GIL inside the native function
'release_gil': False,
'no_compile': False,
'debuginfo': False,
'boundscheck': False,
'forceinline': False,
'no_cpython_wrapper': False,
'no_cfunc_wrapper': False,
# Enable automatic parallel optimization, can be fine-tuned by taking
# a dictionary of sub-options instead of a boolean, see parfor.py for
# detail.
'auto_parallel': cpu.ParallelOptions(False),
'nrt': False,
'no_rewrites': False,
'error_model': 'python',
'fastmath': cpu.FastMathOptions(False),
'noalias': False,
'inline': cpu.InlineOptions('never'),
}
def autogenerate(cls):
test_flags = [
'fastmath',
] # TODO: add 'auto_parallel' ?
# generate all the combinations of the flags
test_flags = sum([list(combinations(test_flags, x)) for x in range( \
len(test_flags)+1)], [])
flag_list = [] # create Flag class instances
for ft in test_flags:
flags = Flags()
flags.set('nrt')
flags.set('error_model', 'numpy')
flags.__name__ = '_'.join(ft + ('usecase', ))
for f in ft:
flags.set(f, {'fastmath':
cpu.FastMathOptions(True)}.get(f, True))
flag_list.append(flags)
# main loop covering all the modes and use-cases
for dtype in (
'complex64',
'float64',
'float32',
'int32',
):
for vlen in vlen2cpu:
for flags in flag_list:
for mode in "scalar", "range", "prange", "numpy":
cls._inject_test(dtype, mode, vlen, flags)
# mark important
for n in (
"test_int32_range4_usecase", # issue #3016
):
setattr(cls, n, tag("important")(getattr(cls, n)))
def __init__(self, *args):
self.flags = Flags()
self.flags.nrt = True
# flags for njit(fastmath=True)
self.fastflags = Flags()
self.fastflags.nrt = True
self.fastflags.fastmath = cpu.FastMathOptions(True)
super(TestSVML, self).__init__(*args)
def __init__(self, *args):
self.flags = Flags()
self.flags.set('nrt')
# flags for njit(fastmath=True)
self.fastflags = Flags()
self.fastflags.set('nrt')
self.fastflags.set('fastmath', cpu.FastMathOptions(True))
super(TestSVML, self).__init__(*args)
def compile_parallel(self, func, arg_types):
fast_pflags = Flags()
fast_pflags.set('auto_parallel', cpu.ParallelOptions(True))
fast_pflags.set('nrt')
fast_pflags.set('fastmath', cpu.FastMathOptions(True))
return compile_isolated(func, arg_types, flags=fast_pflags).entry_point
def compile_parallel(self, func, arg_types):
fast_pflags = Flags()
fast_pflags.auto_parallel = cpu.ParallelOptions(True)
fast_pflags.nrt = True
fast_pflags.fastmath = cpu.FastMathOptions(True)
return compile_isolated(func, arg_types, flags=fast_pflags).entry_point
class Flags(TargetConfig):
enable_looplift = Option(
type=bool,
default=False,
doc="Enable loop-lifting",
)
enable_pyobject = Option(
type=bool,
default=False,
doc="Enable pyobject mode (in general)",
)
enable_pyobject_looplift = Option(
type=bool,
default=False,
doc="Enable pyobject mode inside lifted loops",
)
enable_ssa = Option(
type=bool,
default=True,
doc="Enable SSA",
)
force_pyobject = Option(
type=bool,
default=False,
doc="Force pyobject mode inside the whole function",
)
release_gil = Option(
type=bool,
default=False,
doc="Release GIL inside the native function",
)
no_compile = Option(
type=bool,
default=False,
doc="TODO",
)
debuginfo = Option(
type=bool,
default=False,
doc="TODO",
)
boundscheck = Option(
type=bool,
default=False,
doc="TODO",
)
forceinline = Option(
type=bool,
default=False,
doc="Force inlining of the function. Overrides _dbg_optnone.",
)
no_cpython_wrapper = Option(
type=bool,
default=False,
doc="TODO",
)
no_cfunc_wrapper = Option(
type=bool,
default=False,
doc="TODO",
)
auto_parallel = Option(
type=cpu.ParallelOptions,
default=cpu.ParallelOptions(False),
doc="""Enable automatic parallel optimization, can be fine-tuned by
taking a dictionary of sub-options instead of a boolean, see parfor.py for
detail""",
)
nrt = Option(
type=bool,
default=False,
doc="TODO",
)
no_rewrites = Option(
type=bool,
default=False,
doc="TODO",
)
error_model = Option(
type=str,
default="python",
doc="TODO",
)
fastmath = Option(
type=cpu.FastMathOptions,
default=cpu.FastMathOptions(False),
doc="TODO",
)
noalias = Option(
type=bool,
default=False,
doc="TODO",
)
inline = Option(
type=cpu.InlineOptions,
default=cpu.InlineOptions("never"),
doc="TODO",
)
# Defines a new target option for tracking the "target backend".
# This will be the XYZ in @jit(_target=XYZ).
target_backend = Option(
type=str,
default="cpu", # if not set, default to CPU
doc="backend")
dbg_extend_lifetimes = Option(
type=bool,
default=False,
doc=("Extend variable lifetime for debugging. "
"This automatically turns on with debug=True."),
)
dbg_optnone = Option(
type=bool,
default=False,
doc=("Disable optimization for debug. "
"Equivalent to adding optnone attribute in the LLVM Function."))
class Flags(TargetConfig):
enable_looplift = Option(
type=bool,
default=False,
doc="Enable loop-lifting",
)
enable_pyobject = Option(
type=bool,
default=False,
doc="Enable pyobject mode (in general)",
)
enable_pyobject_looplift = Option(
type=bool,
default=False,
doc="Enable pyobject mode inside lifted loops",
)
enable_ssa = Option(
type=bool,
default=True,
doc="Enable SSA",
)
force_pyobject = Option(
type=bool,
default=False,
doc="Force pyobject mode inside the whole function",
)
release_gil = Option(
type=bool,
default=False,
doc="Release GIL inside the native function",
)
no_compile = Option(
type=bool,
default=False,
doc="TODO",
)
debuginfo = Option(
type=bool,
default=False,
doc="TODO",
)
boundscheck = Option(
type=bool,
default=False,
doc="TODO",
)
forceinline = Option(
type=bool,
default=False,
doc="TODO",
)
no_cpython_wrapper = Option(
type=bool,
default=False,
doc="TODO",
)
no_cfunc_wrapper = Option(
type=bool,
default=False,
doc="TODO",
)
auto_parallel = Option(
type=cpu.ParallelOptions,
default=cpu.ParallelOptions(False),
doc="""Enable automatic parallel optimization, can be fine-tuned by
taking a dictionary of sub-options instead of a boolean, see parfor.py for
detail""",
)
nrt = Option(
type=bool,
default=False,
doc="TODO",
)
no_rewrites = Option(
type=bool,
default=False,
doc="TODO",
)
error_model = Option(
type=str,
default="python",
doc="TODO",
)
fastmath = Option(
type=cpu.FastMathOptions,
default=cpu.FastMathOptions(False),
doc="TODO",
)
noalias = Option(
type=bool,
default=False,
doc="TODO",
)
inline = Option(
type=cpu.InlineOptions,
default=cpu.InlineOptions("never"),
doc="TODO",
)
