def __init__(self,
arg_template,
precision=ML_Binary32,
abs_accuracy=S2**-24,
libm_compliant=True,
debug_flag=False,
fuse_fma=True,
fast_path_extract=True,
target=FixedPointBackend(),
output_file="ut_static_vectorization.c",
function_name="ut_static_vectorization"):
# precision argument extraction
precision = ArgDefault.select_value(
[arg_template.precision, precision])
io_precisions = [precision] * 2
# initializing base class
ML_FunctionBasis.__init__(self,
base_name="ut_static_vectorization",
function_name=function_name,
output_file=output_file,
io_precisions=io_precisions,
abs_accuracy=None,
libm_compliant=libm_compliant,
processor=target,
fuse_fma=fuse_fma,
fast_path_extract=fast_path_extract,
debug_flag=debug_flag,
arg_template=arg_template)
self.precision = precision
def __init__(self,
precision=ML_Binary32,
abs_accuracy=S2**-24,
libm_compliant=True,
debug_flag=False,
fuse_fma=True,
fast_path_extract=True,
target=FixedPointBackend(),
output_file="ut_call_externalization.c",
function_name="ut_call_externalization"):
io_precisions = [precision] * 2
# initializing base class
ML_FunctionBasis.__init__(self,
base_name="ut_call_externalization",
function_name=function_name,
output_file=output_file,
io_precisions=io_precisions,
abs_accuracy=None,
libm_compliant=libm_compliant,
processor=target,
fuse_fma=fuse_fma,
fast_path_extract=fast_path_extract,
debug_flag=debug_flag)
self.precision = precision
def __init__(self,
precision=ML_Binary32,
abs_accuracy=S2**-24,
libm_compliant=True,
debug_flag=False,
fuse_fma=True,
fast_path_extract=True,
target=FixedPointBackend(),
output_file="ut_opencl_code.c",
function_name="ut_opencl_code",
vector_size=2,
language=C_Code):
io_precisions = [precision] * 2
# initializing base class
ML_FunctionBasis.__init__(self,
base_name="ut_opencl_code",
function_name=function_name,
output_file=output_file,
io_precisions=io_precisions,
abs_accuracy=None,
libm_compliant=libm_compliant,
processor=target,
fuse_fma=fuse_fma,
fast_path_extract=fast_path_extract,
debug_flag=debug_flag,
vector_size=vector_size,
language=language)
self.precision = precision
def get_default_args(**kw):
""" Return a structure containing the arguments for ML_SinCos,
builtin from a default argument mapping overloaded with @p kw """
default_args_sincos = {
"output_file": "my_sincos.c",
"function_name": "new_fastsincos",
"precision": ML_Binary32,
"accuracy": ML_Faithful,
"target": FixedPointBackend.get_target_instance(),
"cos_output": True,
}
default_args_sincos.update(kw)
return DefaultArgTemplate(**default_args_sincos)
def get_default_args(**kw):
""" Return a structure containing the arguments for current class,
builtin from a default argument mapping overloaded with @p kw """
default_args = {
"output_file": "ut_vector_code.c",
"function_name": "ut_vector_code",
"precision": ML_Binary32,
"target": FixedPointBackend(),
"fast_path_extract": True,
"fuse_fma": True,
"libm_compliant": True
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
def get_default_args(**kw):
""" generate default argument structure for BipartiteApprox """
default_dict = {
"target": FixedPointBackend(),
"output_file": "my_bipartite_approx.c",
"entity_name": "my_bipartie_approx",
"language": C_Code,
"function": lambda x: 1.0 / x,
"interval": Interval(1, 2),
"pipelined": False,
"precision": fixed_point(1, 15, signed=False),
"disable_sub_testing": False,
"disable_sv_testing": False,
"alpha": 6,
"beta": 5,
"gamma": 5,
"guard_bits": 3,
"passes": ["start:size_datapath"],
}
default_dict.update(kw)
return DefaultArgTemplate(**default_dict)