def test_cast_str(): assert Option(name='str_option', type=str).cast_value("abc") == "abc" assert Option(name='str_option', type=str).cast_value(1.5) == "1.5" assert Option(name='str_option', type=str).cast_value('123') == "123" assert Option(name='str_option', type=str).cast_value('off') == 'off' with pytest.raises(VergeMLError): Option(name='str_option', type=str).cast_value({}) == {}
def test_command_usage5(): cmd = Command('train', options=[ Option(name='optimizer', type=str), Option(name='learning-rate', default=0.0001, short='l') ]) assert cmd.usage() == USAGE_5
def test_command_usage6(): cmd = Command('train', options=[ Option(name='a', type=str, default="A"), Option(name='b', type=str, default="B"), Option(name='c', type=str, default="C"), ]) assert cmd.usage() == USAGE_6
def test_cast_none(): assert Option(name='none_option', type=type(None)).cast_value(None) == None assert Option(name='none_option', type=type(None)).cast_value("NULL") == None with pytest.raises(VergeMLError): assert Option(name='none_option', type=type(None)).cast_value("Nichts") == None
def test_command_2(): cmd = Command('run', options=[Option('<args>', type=list), Option('@AIs', type=list)]) assert cmd.parse(["run", "tensorboard"]) == {'@AIs': [], '<args>': ["tensorboard"]} assert cmd.parse(["@funky-terminator", "run", "tensorboard"]) == \ {'@AIs': ['funky-terminator'], '<args>': ["tensorboard"]} assert cmd.parse(["@funky-terminator", "@touchy-brobot", "run", "tensorboard", "--port=2204"]) == \ {'@AIs': ['funky-terminator', 'touchy-brobot'], '<args>': ["tensorboard", "--port=2204"]}
def test_cast_float(): assert Option(name='float_option', type=float).cast_value(1) == 1. assert Option(name='float_option', type=float).cast_value(1.5) == 1.5 assert Option(name='float_option', type=float).cast_value('123') == 123. assert Option(name='float_option', type=float).cast_value('123.5') == 123.5 with pytest.raises(VergeMLError): Option(name='float_option', type=float).cast_value('x123.5') == 123.5
def test_command_usage9(): cmd = Command('predict', options=[ Option(name='<file>', type='Optional[str]', descr="The file to use when predicting."), Option(name='a', type=str, default="A"), Option(name='b', type=str, default="B"), Option(name='c', type=str, default="C"), ]) assert cmd.usage() == USAGE_9
def test_command_usage8(): cmd = Command('predict', options=[ Option(name='<file>', type='Optional[str]'), Option(name='a', type=str, default="A"), Option(name='b', type=str, default="B"), Option(name='c', type=str, default="C"), ]) assert cmd.usage() == USAGE_8
def test_command_7(): cmd = Command('help', options=[Option(name='<topic>'), Option(name="@AI", type='Optional[@]')], free_form=True) assert cmd.parse(["@funky-robot", "help", "--option=xyz", "something"]) == \ ('funky-robot', ["--option=xyz", "something"]) assert cmd.parse(["help", "--option=xyz", "something"]) == \ (None, ["--option=xyz", "something"])
def test_validate_in(): Option(name='in_option', type=int, validate=(1,2,3,4,5)).validate_value(5) with pytest.raises(VergeMLError, match=r'Invalid value for option in_option\.'): Option(name='in_option', type=int, validate=(1,2,3,4,5)).validate_value(6) Option(name='in_option', type=int, validate=("adam", "sgd")).validate_value("adam") with pytest.raises(VergeMLError, match=r'Invalid value for option in_option\.'): Option(name='in_option', type=int, validate=("adam", "sgd")).validate_value("sgf")
def test_cast_list_int(): assert Option(name='list_option', type='List[int]').cast_value(["1", "2", "3"]) == [1, 2, 3] assert Option(name='list_option', type='List[int]').cast_value([]) == [] assert Option(name='list_option', type='List[int]').cast_value([1, 2, 3]) == [1, 2, 3] with pytest.raises(VergeMLError): assert Option(name='list_option', type='List[int]').cast_value(["1.0", "2.0"]) == [1, 2]
def test_command_usage4(): cmd = Command('predict', options=[ Option(name='@AI'), Option(name='threshold', default=0.2, descr="Prediction Threshold.") ]) assert cmd.usage() == USAGE_4
def test_command_usage11(): cmd = Command('predict', options=[ Option(name='@AIs', type="List[AI]"), Option(name='threshold', default=0.2, descr="Prediction Threshold.") ]) assert cmd.usage() == USAGE_11
def test_cast_union(): assert Option(name='union_option', type='Union[int,str]').cast_value("abc") == "abc" assert Option(name='union_option', type='Union[int,str]').cast_value(1) == 1 assert Option(name='union_option', type='Union[int,str]').cast_value("1") == 1 with pytest.raises(VergeMLError): assert Option(name='union_option', type='Union[int,str]').cast_value(True) == True
def test_command_5(): options = [ Option('threshold', type=float, validate=">0", short='t'), Option('id', default=False, type=bool, flag=True, short='i') ] cmd = Command('predict', options=options) assert cmd.parse(["predict", "--threshold=0.2"]) == {'threshold': 0.2, 'id': False} assert cmd.parse(["predict", "-t0.2"]) == {'threshold': 0.2, 'id': False} assert cmd.parse(["predict", "-t0.2", "--id"]) == {'threshold': 0.2, 'id': True} assert cmd.parse(["predict", "-t0.2", "-i"]) == {'threshold': 0.2, 'id': True}
def test_command_usage13(): cmd = Command('predict', long_descr="Make a prediction.", examples="ml @skynet predict", options=[ Option(name='@AIs', type="List[AI]"), Option(name='threshold', default=0.2, descr="Prediction Threshold.") ]) assert cmd.usage() == USAGE_13
def test_cast_list_str(): assert Option(name='list_option', type='List[str]').cast_value(["a", "b", "c"]) == ["a", "b", "c"] assert Option(name='list_option', type='List[str]').cast_value([]) == [] assert Option(name='list_option', type='List[str]').cast_value([1, 2, 3]) == ["1", "2", "3"] with pytest.raises(VergeMLError): assert Option(name='list_option', type='List[str]').cast_value([True, False ]) == ["True", "False"]
def test_command_3(): cmd = Command('predict', options=[Option(name="@AI")]) assert cmd.parse(["@stubborn-dishwasher", "predict"]) == { '@AI': 'stubborn-dishwasher' } with pytest.raises(VergeMLError): cmd.parse(["predict"])
def decorator(o): assert getattr(o, _MODEL_META_KEY, None) is None options = Option.discover(o) cmd = Model(name, descr=descr, long_descr=long_descr, options=options) setattr(o, _MODEL_META_KEY, cmd) return o
def decorator(obj): # make sure that a command is not defined more than once assert getattr(obj, _CMD_META_KEY, None) is None # name defaults to the functions name _name = name or getattr(obj, '__name__', None) # construct the command with options and attach it to obj options = list(reversed(Option.discover(obj))) cmd = Command(_name, descr=descr, long_descr=long_descr, examples=examples, options=options, free_form=free_form, type=type) if inspect.isclass(obj): setattr(obj, _CMD_META_KEY, cmd) _wrapper = _CommandCallProxy.class_wrapper(obj, cmd) else: _wrapper = _CommandCallProxy.function_wrapper(obj, cmd) setattr(_wrapper, _CMD_META_KEY, cmd) return _wrapper
def __init__(self, name=None, plugins=PLUGINS): self._values = {} self._options = Option.discover(self, plugins=plugins) self.plugins = plugins self.name = name for option in self._options: if option.alias is None: dict_set_path(self._values, option.name, option.default)
def decorator(o): # if getattr(o, _SOURCE_META_KEY, None): # print(getattr(o, _SOURCE_META_KEY, None).name, name) # assert getattr(o, _SOURCE_META_KEY, None) is None options = Option.discover(o) if input_patterns: assert isinstance(input_patterns, (str, list)) input_patterns_option = Option('input-patterns', input_patterns, type='Union[str, List[str]]', descr="Controls which files are loaded.", transform=lambda v: v if isinstance(v, list) else v.split(",")) options.append(input_patterns_option) cmd = Source(name, descr=descr, long_descr=long_descr, options=options) setattr(o, _SOURCE_META_KEY, cmd) return o
def test_validate_float(): Option(name='float_option_1', validate='>=0').validate_value(0.1) Option(name='float_option_2', validate='>=0').validate_value(0.0) Option(name='float_option_3', validate='<=0').validate_value(0.0) Option(name='float_option_4', validate='<=0').validate_value(-0.) Option(name='float_option_5', validate='<0').validate_value(-0.1) Option(name='float_option_6', validate='>0').validate_value(0.1) with pytest.raises(VergeMLError): Option(name='float_option_7', validate='>=0').validate_value(-0.1) with pytest.raises(VergeMLError): Option(name='float_option_8', validate='<=0').validate_value(0.1) with pytest.raises(VergeMLError): Option(name='float_option_9', validate='<0').validate_value(0.1) with pytest.raises(VergeMLError): Option(name='float_option_10', validate='>0').validate_value(-0.1)
def decorator(o): assert getattr(o, _OPERATION_META_KEY, None) is None options = Option.discover(o) cmd = Operation(name, descr=descr, long_descr=long_descr, apply=apply, options=options, topic=topic) setattr(o, _OPERATION_META_KEY, cmd) return o
def test_command_1(): cmd = Command('train', options=[Option('epochs', 20, int, validate='>=1')]) assert cmd.parse(["train", "--epochs=14"]) == {'epochs': 14} with pytest.raises(VergeMLError): cmd.parse(["train", "--epochs=abc"]) with pytest.raises(VergeMLError): cmd.parse(["train", "--epochz=14"]) with pytest.raises(VergeMLError): cmd.parse(["train", "--epochs=-1"])
def decorator(o): assert(getattr(o, _CMD_META_KEY, None) is None) _name = name or getattr(o, '__name__', None) options = list(reversed(Option.discover(o))) cmd = Command(_name, descr=descr, long_descr=long_descr, examples=examples, options=options, free_form=free_form, kind=kind) setattr(o, _CMD_META_KEY, cmd) return o
def test_cast_list_float(): assert Option(name='list_option', type='List[float]').cast_value(["1", "2", "3"]) == [1., 2., 3.] assert Option(name='list_option', type='List[float]').cast_value([]) == [] assert Option(name='list_option', type='List[float]').cast_value([1., 2., 3.]) == [1., 2., 3.] assert Option(name='list_option', type='List[float]').cast_value([1, 2, 3]) == [1., 2., 3.] assert Option(name='list_option', type='List[float]').cast_value(["1.0", "2.0"]) == [1, 2] with pytest.raises(VergeMLError): assert Option(name='list_option', type='List[float]').cast_value(["one", "two"]) == [1., 2.]
def test_cast_bool(): assert Option(name='bool_option', type=bool).cast_value(True) == True assert Option(name='bool_option', type=bool).cast_value(False) == False assert Option(name='bool_option', type=bool).cast_value('on') == True assert Option(name='bool_option', type=bool).cast_value('off') == False with pytest.raises(VergeMLError): Option(name='bool_option', type=bool).cast_value('falsch') == False with pytest.raises(VergeMLError): Option(name='bool_option', type=bool).cast_value(1) == True
def _normalize(raw, validators): raw = deepcopy(raw) res = {} for _, conf in validators.items(): options = Option.discover(conf) aliases = [opt for opt in options if opt.alias] for alias in aliases: if dict_has_path(raw, alias.name): v = dict_get_path(raw, alias.name) if not alias.type or isinstance(v, alias.type): dict_set_path(res, alias.alias, v) dict_del_path(raw, alias.name) for k, v in deepcopy(raw).items(): if "." in k: dict_set_path(res, k, v) del raw[k] return dict_merge(res, raw)
def options(self): return Option.discover(self)