def get_default_args(**args):
""" Generate a default argument structure set specifically for
the Hyperbolic Cosine """
default_div_args = {
"precision":
ML_Binary32,
"accuracy":
ML_CorrectlyRounded,
"target":
GenericProcessor.get_target_instance(),
"output_file":
"my_div.c",
"function_name":
"my_div",
"input_intervals": [DefaultArgTemplate.input_intervals[0]] * 2,
"auto_test_range":
DefaultArgTemplate.auto_test_range * 2,
"bench_test_range":
DefaultArgTemplate.bench_test_range * 2,
"language":
C_Code,
"num_iter":
3,
"passes": [
"typing:basic_legalization",
"beforecodegen:expand_multi_precision"
],
"vector_size":
1,
}
default_div_args.update(args)
return DefaultArgTemplate(**default_div_args)
def get_default_args(**kw):
""" Return a structure containing the arguments for MetaAtan,
builtin from a default argument mapping overloaded with @p kw
"""
default_args_rootn = {
"output_file":
"rootn.c",
"function_name":
"rootn",
"input_precisions": [ML_Binary32, ML_Int32],
"accuracy":
ML_Faithful,
"input_intervals": [
sollya.Interval(-2.0**126, 2.0**126),
sollya.Interval(-2**24, 2**24)
],
"auto_test_range": [
sollya.Interval(-2.0**126, 2.0**126),
sollya.Interval(-2**24, 2**24)
],
"target":
GenericProcessor.get_target_instance(),
"expand_div":
False,
}
default_args_rootn.update(kw)
return DefaultArgTemplate(**default_args_rootn)
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_new_arg_template.c",
"function_name": "ut_new_arg_template",
"precision": ML_Binary32,
"accuracy": ML_Faithful,
"target": MPFRProcessor()
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
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 MetalibmSqrt,
builtin from a default argument mapping overloaded with @p kw """
default_args_fast_exp2i = {
"output_file": "fast_expi.c",
"function_name": "fast_expi",
"input_precisions": [ML_Int32],
"precision": ML_Binary32,
"accuracy": ML_Faithful,
"target": GenericProcessor.get_target_instance()
}
default_args_fast_exp2i.update(kw)
return DefaultArgTemplate(**default_args_fast_exp2i)
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_machine_insn_generation.S",
"function_name": "ut_machine_insn_generation",
"precision": ML_Binary32,
"passes": [
# default pass for dummy asm target are enough
],
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
def get_default_args(**kw):
""" Return a structure containing the arguments for FunctionExpression,
builtin from a default argument mapping overloaded with @p kw """
default_args_log = {
"output_file": "func_expr.c",
"function_name": "func_expr",
"function_expr_str": "exp(x)",
"precision": ML_Binary32,
"accuracy": ML_Faithful,
"expand_div": False,
"target": GenericProcessor.get_target_instance(),
}
default_args_log.update(kw)
return DefaultArgTemplate(**default_args_log)
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_gappa_code.c",
"function_name": "ut_gappa_code",
"precision": ML_Binary32,
"target": MPFRProcessor(),
"fast_path_extract": True,
"fuse_fma": True,
"libm_compliant": True
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
def get_default_args(**kw):
""" Return a structure containing the arguments for ML_Exponential,
builtin from a default argument mapping overloaded with @p kw """
default_args_mmk = {
"output_file": "mm_kernel.c",
"function_name": "mm_kernel",
"test_index_range": [[16, 32], [16, 32], [16, 32]],
"auto_test_range": [Interval(-1, 1), Interval(-1, 1)],
"vectorize": False,
"precision": ML_Binary32,
"target": GenericProcessor.get_target_instance()
}
default_args_mmk.update(kw)
return DefaultArgTemplate(**default_args_mmk)
def get_default_args(**kw):
""" Return a structure containing the arguments for MetaAtan,
builtin from a default argument mapping overloaded with @p kw
"""
default_args_pow = {
"output_file": "ml_pow.c",
"function_name": "ml_pow",
"input_precisions": [ML_Binary32, ML_Binary32],
"accuracy": ML_Faithful,
"input_intervals": [None, Interval(-2**24, 2**24)], # sollya.Interval(-2.0**126, 2.0**126), sollya.Interval(0, 2**31-1)],
"auto_test_range": [None, Interval(-2**24, 2**24)], # sollya.Interval(-2.0**126, 2.0**126), sollya.Interval(0, 47)],
"target": GenericProcessor.get_target_instance()
}
default_args_pow.update(kw)
return DefaultArgTemplate(**default_args_pow)
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_llvm_code.ll",
"function_name": "ut_llvm_code",
"precision": ML_Int32,
"target": LLVMBackend(),
"language": LLVM_IR_Code,
"fast_path_extract": True,
"fuse_fma": False,
"libm_compliant": True
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
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_m128_conversion.c",
"function_name": "ut_m128_conversion",
"precision": ML_Binary32,
"target": X86_AVX2_Processor(),
"fast_path_extract": True,
"fuse_fma": True,
"debug": True,
"libm_compliant": True,
"pre_gen_passes": ["m128_promotion"],
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
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_mp_vectorization.c",
"function_name": "ut_mp_vectorization",
"precision": ML_DoubleDouble,
"target": GenericProcessor.get_target_instance(),
"fast_path_extract": True,
"fuse_fma": True,
"passes": ["start:basic_legalization", "start:expand_multi_precision"],
"libm_compliant": True
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
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_legalize_sqrt.c",
"function_name": "ut_legalize_sqrt",
"precision": ML_Binary32,
"target": GenericProcessor(),
"fast_path_extract": True,
"fuse_fma": True,
"debug": True,
"libm_compliant": True,
"test_range": Interval(S2**-8, S2**8),
"accuracy": dar(S2**-7),
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
def get_default_args(**args):
""" Generate a default argument structure set specifically for
the Hyperbolic Cosine """
default_div_args = {
"precision": ML_Binary32,
"accuracy": ML_CorrectlyRounded,
"target": GenericProcessor(),
"output_file": "my_div.c",
"function_name": "my_div",
"language": C_Code,
"num_iter": 3,
"passes": ["beforecodegen:expand_multi_precision"],
"vector_size": 1,
"arity": ML_Division.arity,
}
default_div_args.update(args)
return DefaultArgTemplate(**default_div_args)
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_multi_precision.c",
"function_name": "ut_multi_precision",
"precision": ML_Binary32,
"target": GenericProcessor(),
"language": C_Code,
"arity": 2,
"input_precisions": [ML_Binary32, ML_Binary32],
"fast_path_extract": True,
"fuse_fma": False,
"libm_compliant": True
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
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_eval_error.c",
"function_name": "ut_eval_error",
"precision": FIXED_FORMAT,
"target": GenericProcessor.get_target_instance(),
"fast_path_extract": True,
"fuse_fma": True,
"debug": True,
"libm_compliant": True,
"test_range": Interval(S2**-8, S2**8),
"accuracy": dar(S2**-6),
}
default_args.update(kw)
return DefaultArgTemplate(**default_args)
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_bfloat16.c",
"function_name": "ut_bfloat16",
"precision": ML_Binary32,
"input_precisions": [ML_UInt32],
"target": GenericProcessor.get_target_instance(),
"fast_path_extract": True,
"fuse_fma": True,
"debug": True,
"libm_compliant": True,
"table_size": 16,
"auto_test_range": Interval(0, 16),
"accuracy": dar(S2**-7),
}
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)