Adding missing copy function calls in Optimization (#172)

dssg · Feb 20, 2024 · 37bf697 · 37bf697
1 parent 5d48298
commit 37bf697
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Showing 2 changed files with 14 additions and 14 deletions.
diff --git a/src/aequitas/flow/experiment/experiment.py b/src/aequitas/flow/experiment/experiment.py
@@ -231,15 +231,15 @@ def run(self) -> None:
                         f"'{method_name}' in '{dataset_name}'."
                     )
                     objective = ObjectiveFunction(
-                        X_train=dataset["train"]["X"],
-                        y_train=dataset["train"]["y"],
-                        s_train=dataset["train"]["s"],
-                        X_val=dataset["validation"]["X"],
-                        y_val=dataset["validation"]["y"],
-                        s_val=dataset["validation"]["s"],
-                        X_test=dataset["test"]["X"],
-                        y_test=dataset["test"]["y"],
-                        s_test=dataset["test"]["s"],
+                        X_train=dataset["train"]["X"].copy(deep=True),
+                        y_train=dataset["train"]["y"].copy(deep=True),
+                        s_train=dataset["train"]["s"].copy(deep=True),
+                        X_val=dataset["validation"]["X"].copy(deep=True),
+                        y_val=dataset["validation"]["y"].copy(deep=True),
+                        s_val=dataset["validation"]["s"].copy(deep=True),
+                        X_test=dataset["test"]["X"].copy(deep=True),
+                        y_test=dataset["test"]["y"].copy(deep=True),
+                        s_test=dataset["test"]["s"].copy(deep=True),
                         threshold=threshold,
                         preprocessing_method=pre,  # type: ignore
                         preprocessing_configs=pre_configs.args,
@@ -295,4 +295,4 @@ def plot_pareto(
         self.plot = Plot(
             results, dataset, fairness_metric, performance_metric, split=split
         )
-        return self.plot.visualize()
+        return self.plot.visualize()
diff --git a/src/aequitas/flow/optimization/__init__.py b/src/aequitas/flow/optimization/__init__.py
@@ -166,9 +166,9 @@ def __call__(self, trial: BaseTrial) -> float:
         start_time = time.process_time()
         preprocessing.fit(self.X_train, self.y_train, self.s_train)
         preprocessing_output = preprocessing.transform(
-            self.X_train,
-            self.y_train,
-            self.s_train,
+            self.X_train.copy(),
+            self.y_train.copy(),
+            self.s_train.copy(),
         )
         inprocessing.fit(*preprocessing_output)
 
@@ -292,4 +292,4 @@ def omegaconf_to_dict(config: Optional[DictConfig]) -> Union[dict, None]:
         if config is not None:
             return OmegaConf.to_container(config)
         else:
-            return None
+            return None