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)