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)
