def eval_error(output):
if isinstance(output, dict):
return optimbox(output).error()
elif isinstance(output, (float, int)):
return float(abs(output))
elif isinstance(output, tuple):
return average([ eval_error(elt) for elt in output ])
elif hasattr(output, '__iter__'):
return mae(output)
else:
raise Exception('output must be based on optimbox, float, tuple or list/array')
def eval_error(output):
if isinstance(output, dict):
return optimbox(output).error()
elif isinstance(output, (float, int)):
return float(abs(output))
elif isinstance(output, tuple):
return average([eval_error(elt) for elt in output])
elif hasattr(output, '__iter__'):
return mae(output)
else:
raise Exception(
'output must be based on optimbox, float, tuple or list/array'
)
def mean(self, x):
return mae(x)
def mean(self, x):
return mae(x)
