Merge pull request #38 from jgh9094/tutorial-fixes

Tutorial fixes
EpistasisLab · Aug 16, 2023 · e6a2647 · e6a2647
2 parents b069841 + e7209b6
commit e6a2647
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Showing 2 changed files with 11 additions and 2 deletions.
diff --git a/tpot2/evolvers/base_evolver.py b/tpot2/evolvers/base_evolver.py
@@ -645,7 +645,7 @@ def get_unevaluated_individuals(self, column_names, budget=None, individual_list
     def evaluate_population_selection_early_stop(self,survival_counts, thresholds=None, budget=None):
 
 
-        survival_selector = tpot2.parent_selectors.survival_select_NSGA2
+        survival_selector = tpot2.selectors.survival_select_NSGA2
 
         ################
 

diff --git a/tpot2/tpot_estimator/templates/tpottemplates.py b/tpot2/tpot_estimator/templates/tpottemplates.py
@@ -32,6 +32,8 @@ def __init__(       self,
                         warm_start = False,
                         periodic_checkpoint_folder = None, 
                         verbose = 0,
+                        memory_limit = "4GB",
+                        client = None
         ):
         """
         See TPOTEstimator for documentation
@@ -64,6 +66,8 @@ def __init__(       self,
                         periodic_checkpoint_folder = periodic_checkpoint_folder, 
                         verbose = verbose,
                         classification=False,
+                        memory_limit = memory_limit,
+                        client = client
 )
 
 
@@ -94,6 +98,9 @@ def __init__(       self,
                         warm_start = False,
                         periodic_checkpoint_folder = None, 
                         verbose = 0,
+                        memory_limit = "4GB",
+                        client = None
+
         ):
         """
         See TPOTEstimator for documentation
@@ -126,10 +133,12 @@ def __init__(       self,
                         periodic_checkpoint_folder = periodic_checkpoint_folder, 
                         verbose = verbose,
                         classification=True,
+                        memory_limit = memory_limit,
+                        client = client
         )
 
 
     def predict(self, X, **predict_params):
         check_is_fitted(self)
         #X=check_array(X)
-        return self.fitted_pipeline_.predict(X,**predict_params)
+        return self.fitted_pipeline_.predict(X,**predict_params)