
Traceback (most recent call last):

 "test2.py", line 17, in <module>
row[caso.c.id](caso.c.id)
TypeError: expected string or Unicode object, Column found
Traceback (most recent call last):


 "//anaconda3/lib/python3.7/threading.py", line 917, in _bootstrap_inner

self.run()


 "//anaconda3/lib/python3.7/threading.py", line 865, in run

self._target(*self._args, **self._kwargs)


 "/Users/hzaws/git/AutoGluon/autogluon/scheduler/fifo.py", line 266, in _run_reporter

reward=last_result[self._reward_attr], **last_result)


 "/Users/hzaws/git/AutoGluon/autogluon/searcher/skopt_searcher.py", line 172, in update

-reward)
# provide negative reward since skopt performs minimization


 "//anaconda3/lib/python3.7/site-packages/scikit_optimize-0.5.2-py3.7.egg/skopt/optimizer/optimizer.py", line 443, in tell

return self._tell(x, y, fit=fit)


 "//anaconda3/lib/python3.7/site-packages/scikit_optimize-0.5.2-py3.7.egg/skopt/optimizer/optimizer.py", line 486, in _tell

est.fit(self.space.transform(self.Xi), self.yi)


 "//anaconda3/lib/python3.7/site-packages/scikit_optimize-0.5.2-py3.7.egg/skopt/learning/gaussian_process/gpr.py", line 195, in fit

super(GaussianProcessRegressor, self).fit(X, y)


 "//anaconda3/lib/python3.7/site-packages/sklearn/gaussian_process/gpr.py", line 221, in fit

self.kernel_.bounds))]


 "//anaconda3/lib/python3.7/site-packages/sklearn/gaussian_process/gpr.py", line 465, in _constrained_optimization

fmin_l_bfgs_b(obj_func, initial_theta, bounds=bounds)


 "//anaconda3/lib/python3.7/site-packages/scipy/optimize/lbfgsb.py", line 199, in fmin_l_bfgs_b

**opts)


 "//anaconda3/lib/python3.7/site-packages/scipy/optimize/lbfgsb.py", line 335, in _minimize_lbfgsb

f, g = func_and_grad(x)


 "//anaconda3/lib/python3.7/site-packages/scipy/optimize/lbfgsb.py", line 285, in func_and_grad

f = fun(x, *args)


 "//anaconda3/lib/python3.7/site-packages/scipy/optimize/optimize.py", line 326, in function_wrapper

return function(*(wrapper_args + args))


 "//anaconda3/lib/python3.7/site-packages/scipy/optimize/optimize.py", line 64, in __call__

fg = self.fun(x, *args)


 "//anaconda3/lib/python3.7/site-packages/sklearn/gaussian_process/gpr.py", line 213, in obj_func

theta, eval_gradient=True)


 "//anaconda3/lib/python3.7/site-packages/sklearn/gaussian_process/gpr.py", line 423, in log_marginal_likelihood

K, K_gradient = kernel(self.X_train_, eval_gradient=True)


 "//anaconda3/lib/python3.7/site-packages/sklearn/gaussian_process/kernels.py", line 685, in __call__

K1, K1_gradient = self.k1(X, Y, eval_gradient=True)


 "//anaconda3/lib/python3.7/site-packages/sklearn/gaussian_process/kernels.py", line 760, in __call__

K2, K2_gradient = self.k2(X, Y, eval_gradient=True)


 "//anaconda3/lib/python3.7/site-packages/scikit_optimize-0.5.2-py3.7.egg/skopt/learning/gaussian_process/kernels.py", line 391, in __call__

(X.shape, len(length_scale)))
TypeError: %d format: a number is required, not tuple
