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Hi @jaberg, Thanks for the package! This extension on hyperopt can be very handy.
I was trying to run fmin with algo=ei.suggest and got the error message above. The full error message is as follows:
AttributeError Traceback (most recent call last) ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hp_gpsmbo/hpsuggest_ei.py in init_fns(self) 18 try: ---> 19 self._cost_deriv 20 except AttributeError: AttributeError: 'DomainGP_EI' object has no attribute '_cost_deriv' During handling of the above exception, another exception occurred: TypeError Traceback (most recent call last) <ipython-input-146-b79d81f8328e> in <module>() 5 #algo=ucb.suggest, 6 max_evals = 30, ----> 7 trials=trials) 8 rf_best ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hyperopt/fmin.py in fmin(fn, space, algo, max_evals, trials, rstate, allow_trials_fmin, pass_expr_memo_ctrl, catch_eval_exceptions, verbose, return_argmin) 305 verbose=verbose, 306 catch_eval_exceptions=catch_eval_exceptions, --> 307 return_argmin=return_argmin, 308 ) 309 ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hyperopt/base.py in fmin(self, fn, space, algo, max_evals, rstate, verbose, pass_expr_memo_ctrl, catch_eval_exceptions, return_argmin) 633 pass_expr_memo_ctrl=pass_expr_memo_ctrl, 634 catch_eval_exceptions=catch_eval_exceptions, --> 635 return_argmin=return_argmin) 636 637 ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hyperopt/fmin.py in fmin(fn, space, algo, max_evals, trials, rstate, allow_trials_fmin, pass_expr_memo_ctrl, catch_eval_exceptions, verbose, return_argmin) 318 verbose=verbose) 319 rval.catch_eval_exceptions = catch_eval_exceptions --> 320 rval.exhaust() 321 if return_argmin: 322 return trials.argmin ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hyperopt/fmin.py in exhaust(self) 197 def exhaust(self): 198 n_done = len(self.trials) --> 199 self.run(self.max_evals - n_done, block_until_done=self.async) 200 self.trials.refresh() 201 return self ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hyperopt/fmin.py in run(self, N, block_until_done) 155 d['result'].get('status'))) 156 new_trials = algo(new_ids, self.domain, trials, --> 157 self.rstate.randint(2 ** 31 - 1)) 158 assert len(new_ids) >= len(new_trials) 159 if len(new_trials): ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hp_gpsmbo/hpsuggest_ei.py in suggest(new_ids, domain, trials, seed, warmup_cutoff, n_buckshots, n_finetunes, stop_at, plot_contours, gp_fit_method, failure_loss, max_ei_thresh) 200 n_buckshots=n_buckshots, 201 n_finetunes=n_finetunes, --> 202 rng=rng, 203 ) 204 t1 = time.time() ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hp_gpsmbo/hpsuggest_ei.py in optimize_over_X(self, n_buckshots, n_finetunes, rng) 137 n_finetunes, 138 rng, --> 139 ret_raw=True) 140 if len(self.gpr._params_list) == 1: 141 Ks = self._K_new(np.atleast_2d(rval_raw), ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hp_gpsmbo/hpsuggest.py in optimize_over_X(self, n_buckshots, n_finetunes, rng, ret_raw, ret_results) 360 # -- sample a bunch of points 361 buckshot = self.draw_n_feature_vecs(n_buckshots, rng) --> 362 buckshot_crit = self.crit(buckshot) 363 best_first = np.argsort(buckshot_crit) 364 #print 'buckshot stats', buckshot_crit.min(), buckshot_crit.max() ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hp_gpsmbo/hpsuggest_ei.py in crit(self, X) 95 96 def crit(self, X): ---> 97 self.init_fns() 98 #return -self.gpr.logEI(X, 99 #self._EI_thresh, ~/anaconda/envs/ldsa/lib/python3.6/site-packages/hp_gpsmbo/hpsuggest_ei.py in init_fns(self) 53 on_unused_input='ignore', 54 allow_input_downcast=True, ---> 55 profile=0) 56 op_Kcond.use_lazy_cholesky = None 57 op_Kcond.use_lazy_cholesky_idx = None ~/anaconda/envs/ldsa/lib/python3.6/site-packages/theano/compile/function.py in function(inputs, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input) 315 on_unused_input=on_unused_input, 316 profile=profile, --> 317 output_keys=output_keys) 318 return fn ~/anaconda/envs/ldsa/lib/python3.6/site-packages/theano/compile/pfunc.py in pfunc(params, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input, output_keys) 484 accept_inplace=accept_inplace, name=name, 485 profile=profile, on_unused_input=on_unused_input, --> 486 output_keys=output_keys) 487 488 ~/anaconda/envs/ldsa/lib/python3.6/site-packages/theano/compile/function_module.py in orig_function(inputs, outputs, mode, accept_inplace, name, profile, on_unused_input, output_keys) 1839 name=name) 1840 with theano.change_flags(compute_test_value="off"): -> 1841 fn = m.create(defaults) 1842 finally: 1843 t2 = time.time() ~/anaconda/envs/ldsa/lib/python3.6/site-packages/theano/compile/function_module.py in create(self, input_storage, trustme, storage_map) 1713 theano.config.traceback.limit = theano.config.traceback.compile_limit 1714 _fn, _i, _o = self.linker.make_thunk( -> 1715 input_storage=input_storage_lists, storage_map=storage_map) 1716 finally: 1717 theano.config.traceback.limit = limit_orig ~/anaconda/envs/ldsa/lib/python3.6/site-packages/theano/gof/link.py in make_thunk(self, input_storage, output_storage, storage_map) 697 return self.make_all(input_storage=input_storage, 698 output_storage=output_storage, --> 699 storage_map=storage_map)[:3] 700 701 def make_all(self, input_storage, output_storage): ~/anaconda/envs/ldsa/lib/python3.6/site-packages/theano/gof/vm.py in make_all(self, profiler, input_storage, output_storage, storage_map) 1089 compute_map, 1090 [], -> 1091 impl=impl)) 1092 linker_make_thunk_time[node] = time.time() - thunk_start 1093 if not hasattr(thunks[-1], 'lazy'): TypeError: ('The following error happened while compiling the node', <hp_gpsmbo.op_Kcond.LazyCholesky object at 0x1364166d8>(Elemwise{Composite{((i0 * exp((((-maximum(((i1 + i2) - i3), i4)) / i5) + (i6 * maximum(((i7 + i8) - i9), i4)) + log(i10)))) + (i11 * i12))}}[(0, 3)].0, reuse_cholesky, reuse_cholesky_idx), '\n', "make_thunk() got an unexpected keyword argument 'impl'")
Any suggestions on what could be going wrong?
Much appreciated! Miguel
The text was updated successfully, but these errors were encountered:
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Hi @jaberg,
Thanks for the package! This extension on hyperopt can be very handy.
I was trying to run fmin with algo=ei.suggest and got the error message above. The full error message is as follows:
Any suggestions on what could be going wrong?
Much appreciated!
Miguel
The text was updated successfully, but these errors were encountered: