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sherpa-ai / sherpa

Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
http://parameter-sherpa.readthedocs.io/
GNU General Public License v3.0
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ValueError: `f0` passed has more than 1 dimension. #111

Closed jing-2020 closed 3 years ago

jing-2020 commented 3 years ago

algorithm=GPyOpt(max_num_trials=10)

INFO:GP:initializing Y INFO:GP:initializing inference method INFO:GP:adding kernel and likelihood as parameters Traceback (most recent call last): File "E:/my_python/瞎写/数据分析.py", line 23, in for trial in study: File "D:\program files(x86)\python\lib\site-packages\sherpa\core.py", line 376, in next t = self.get_suggestion() File "D:\program files(x86)\python\lib\site-packages\sherpa\core.py", line 215, in get_suggestion self.lower_is_better) File "D:\program files(x86)\python\lib\site-packages\sherpa\algorithms\bayesian_optimization.py", line 110, in get_suggestion lower_is_better) File "D:\program files(x86)\python\lib\site-packages\sherpa\algorithms\bayesian_optimization.py", line 149, in _generate_bayesopt_batch return bo_step.suggest_next_locations() File "D:\program files(x86)\python\lib\site-packages\GPyOpt\core\bo.py", line 69, in suggest_next_locations suggested_locations = self._compute_next_evaluations(pending_zipped_X = pending_X, ignored_zipped_X = ignored_X) File "D:\program files(x86)\python\lib\site-packages\GPyOpt\core\bo.py", line 236, in _compute_next_evaluations return self.space.zip_inputs(self.evaluator.compute_batch(duplicate_manager=duplicate_manager, context_manager= self.acquisition.optimizer.context_manager)) File "D:\program files(x86)\python\lib\site-packages\GPyOpt\core\evaluators\batch_local_penalization.py", line 37, in compute_batch L = estimate_L(self.acquisition.model.model,self.acquisition.space.get_bounds()) File "D:\program files(x86)\python\lib\site-packages\GPyOpt\core\evaluators\batch_local_penalization.py", line 66, in estimate_L res = scipy.optimize.minimize(df,x0, method='L-BFGS-B',bounds=bounds, args = (model,x0), options = {'maxiter': 200}) File "D:\program files(x86)\python\lib\site-packages\scipy\optimize_minimize.py", line 618, in minimize callback=callback, options) File "D:\program files(x86)\python\lib\site-packages\scipy\optimize\lbfgsb.py", line 308, in _minimize_lbfgsb finite_diff_rel_step=finite_diff_rel_step) File "D:\program files(x86)\python\lib\site-packages\scipy\optimize\optimize.py", line 262, in _prepare_scalar_function finite_diff_rel_step, bounds, epsilon=epsilon) File "D:\program files(x86)\python\lib\site-packages\scipy\optimize_differentiable_functions.py", line 95, in init self._update_grad() File "D:\program files(x86)\python\lib\site-packages\scipy\optimize_differentiable_functions.py", line 171, in _update_grad self._update_grad_impl() File "D:\program files(x86)\python\lib\site-packages\scipy\optimize_differentiable_functions.py", line 92, in update_grad finite_diff_options) File "D:\program files(x86)\python\lib\site-packages\scipy\optimize_numdiff.py", line 388, in approx_derivative raise ValueError("f0 passed has more than 1 dimension.") ValueError: f0 passed has more than 1 dimension.