spiralulam
commented
9 months ago Thanks, Robert. I will look into it. Best, Nathan
Am Do., 23. Nov. 2023 um 10:03 Uhr schrieb Robert Lee < @.***>:
Hi Nathan @spiralulam https://github.com/spiralulam
I cloned the master branch and did pip install . then installed glpk and scip via conda as written in the docs. Then I realized I still did not have pyomo or gurobipy, so I did pip install -r requirements.txt and everything seemed good to go. But when I run multi_obj_with_constraints.ipynb (the first one I tried) I got errors with both the Gurobi and pyomo versions at the lines res_gur = opt_gur.solve(enting, model_core=model_gur) and / or res_pyo = opt_pyo.solve(enting, model_core=model_pyo)
The error (for the pyomo version) is:
AttributeError Traceback (most recent call last) Untitled-1 in line 1 ----> 88 res_pyo = opt_pyo.solve(enting, model_core=model_pyo)
File c:\Users\myuser\dev\entmoot_test\entmoot\entmoot\optimizers\pyomo_opt.py:96, in PyomoOptimizer.solve(self, tree_model, model_core, weights) 93 opt.options[k] = v 95 # build pyomo model using information from tree model ---> 96 tree_model.add_to_pyomo_model(opt_model) 98 # Solve optimization model 99 opt.solve(opt_model, tee=True)
File c:\Users\myuser\dev\entmoot_test\entmoot\entmoot\models\enting.py:209, in Enting.add_to_pyomo_model(self, core_model, weights) 204 core_model.constraint_link_mu_auxmu = pyo.Constraint( 205 expr=core_model._aux_mu[obj_name] == core_model._mu 206 ) 207 else: 208 # multi-objective case --> 209 self.mean_model.add_to_pyomo_model( 210 core_model, add_mu_var=True, normalize_mean=True 211 ) 212 if weights is not None: 213 moo_weights = weights
File c:\Users\myuser\dev\entmoot_test\entmoot\entmoot\models\mean_models\tree_ensemble.py:402, in TreeEnsemble.add_to_pyomo_model(self, model, add_mu_var, normalize_mean) 397 def add_to_pyomo_model( 398 self, model, add_mu_var: bool = True, normalize_mean: bool = False 399 ): 400 import pyomo.environ as pyo --> 402 self._update_meta_tree_dict() 404 # attach tree info 405 model._num_trees = lambda obj_name: self._meta_tree_dict[obj_name].num_trees
File c:\Users\myuser\dev\entmoot_test\entmoot\entmoot\models\mean_models\tree_ensemble.py:132, in TreeEnsemble._update_meta_tree_dict(self) 126 raise IOError( 127 "Parameter 'train_lib' for tree ensembles needs to be " 128 "in '('lgbm')'." 129 ) 131 # order tree_model_dict --> 132 ordered_tree_model_dict = read_lgbm_tree_model_dict( 133 lib_out, cat_idx=self._problem_config.cat_idx 134 ) 136 # populate meta_tree_model 137 self._meta_tree_dict[obj.name] = MetaTreeModel(ordered_tree_model_dict)
File c:\Users\myuser\dev\entmoot_test\entmoot\entmoot\models\mean_models\lgbm_utils.py:11, in read_lgbm_tree_model_dict(tree_model_dict, cat_idx) 8 node_list = [] 10 # populate node_list and add to ordered_tree_list if non-empty ---> 11 add_next_nodes(node_list=node_list, node=root_node, cat_idx=cat_idx) 13 if node_list: 14 ordered_tree_list.append(node_list)
File c:\Users\myuser\dev\entmoot_test\entmoot\entmoot\models\mean_models\lgbm_utils.py:56, in add_next_nodes(node_list, node, cat_idx) 53 except KeyError: 54 pass ---> 56 add_next_nodes(node_list, node, cat_idx=cat_idx)
File c:\Users\myuser\dev\entmoot_test\entmoot\entmoot\models\mean_models\lgbm_utils.py:56, in add_next_nodes(node_list, node, cat_idx) 53 except KeyError: 54 pass ---> 56 add_next_nodes(node_list, node, cat_idx=cat_idx)
[... skipping similar frames: add_next_nodes at line 56 (3 times)]File c:\Users\myuser\dev\entmoot_test\entmoot\entmoot\models\mean_models\lgbm_utils.py:56, in add_next_nodes(node_list, node, cat_idx) 53 except KeyError: 54 pass ---> 56 add_next_nodes(node_list, node, cat_idx=cat_idx)
File c:\Users\myuser\dev\entmoot_test\entmoot\entmoot\models\mean_models\lgbm_utils.py:32, in add_next_nodes(node_list, node, cat_idx) 29 new_node["split_code_pred"] = temp_node_val 30 else: 31 # read categorical variables ---> 32 cat_set = node[-1]["threshold"].split("||") 33 temp_node_val = [int(cat) for cat in cat_set] 34 new_node["split_code_pred"] = temp_node_val
AttributeError: 'float' object has no attribute 'split'`
Any idea what is missing here?
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R-M-Lee
Hi Nathan @spiralulam
I cloned the master branch and did
pip install .then installed glpk and scip via conda as written in the docs. Then I realized I still did not have pyomo or gurobipy, so I didpip install -r requirements.txtand everything seemed good to go. But when I run multi_obj_with_constraints.ipynb (the first one I tried) I got errors with both the Gurobi and pyomo versions at the linesres_gur = opt_gur.solve(enting, model_core=model_gur)and / orres_pyo = opt_pyo.solve(enting, model_core=model_pyo)The error (for the pyomo version) is:
Any idea what is missing here?