class dummy_factory(object):
def __init__(self):
self.count = 0
self.app = App('dummy_cascade_set', '', '1.0')
self.fail_node_list = []
def add_node(self, inputs, outputs, has_fallback=False):
assert len(
inputs
) <= 10, 'Only supports generating node with less then 10 inputs'
self.count += 1
name = 'node' + str(self.count)
def func_base(df, valid_input):
if name in self.fail_node_list:
raise ValueError
if not valid_input:
val = 1000
else:
val = df.sum().sum()
return tuple(pd.Series(val * (i + 1)) for i in range(len(outputs)))
def func_no_default(df):
return func_base(df, True)
func = func_base
if not has_fallback:
func = func_no_default
setattr(func, '__name__', name)
self.app.add_metric(func, '', inputs, outputs)
class dummy_factory(object):
def __init__(self):
self.count = 0
self.app = App('dummy_cascade_set', '', '1.0')
self.fail_node_list = []
def add_node(self, inputs, outputs, has_fallback=False):
assert len(inputs) <= 10, 'Only supports generating node with less then 10 inputs'
self.count += 1
name = 'node' + str(self.count)
def func_base(arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10, valid_input):
if name in self.fail_node_list:
raise ValueError
if not valid_input:
val = name + ' default'
else:
arg_list = [arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10]
val = name + str([arg for arg in arg_list if arg is not None]).replace("'","")
return tuple( val + str(i) for i in range(len(outputs)) )
def func_no_default(arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10):
return func_base(arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10, True)
func = func_base
if not has_fallback:
func = func_no_default
args = [None] * (10 - len(inputs))
partial_func = partial(func, *args)
setattr(partial_func, '__name__', name)
self.app.add_metric(partial_func, '', inputs, outputs)