Merge branch 'main' into fix_auth_ci_test

YuanTingHsieh · Nov 27, 2024 · 5610731 · 5610731
2 parents ca4cbfc + 60d292e
commit 5610731
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diff --git a/examples/advanced/xgboost/histogram-based/requirements.txt b/examples/advanced/xgboost/histogram-based/requirements.txt
@@ -3,5 +3,7 @@ pandas
 scikit-learn
 torch
 tensorboard
+matplotlib
+shap
 # require xgboost 2.2 version, for now need to install a nightly build
 https://s3-us-west-2.amazonaws.com/xgboost-nightly-builds/federated-secure/xgboost-2.2.0.dev0%2B4601688195708f7c31fcceeb0e0ac735e7311e61-py3-none-manylinux_2_28_x86_64.whl
diff --git a/examples/advanced/xgboost/tree-based/requirements.txt b/examples/advanced/xgboost/tree-based/requirements.txt
@@ -3,5 +3,7 @@ pandas
 scikit-learn
 torch
 tensorboard
+matplotlib
+shap
 # require xgboost 2.2 version, for now need to install a nightly build
 https://s3-us-west-2.amazonaws.com/xgboost-nightly-builds/federated-secure/xgboost-2.2.0.dev0%2B4601688195708f7c31fcceeb0e0ac735e7311e61-py3-none-manylinux_2_28_x86_64.whl
diff --git a/nvflare/app_opt/xgboost/histogram_based_v2/runners/xgb_client_runner.py b/nvflare/app_opt/xgboost/histogram_based_v2/runners/xgb_client_runner.py
@@ -224,15 +224,16 @@ def run(self, ctx: dict):
             bst.save_model(os.path.join(self._model_dir, self.model_file_name))
             xgb.collective.communicator_print("Finished training\n")
 
-            # Save explanability outputs based on val_data
-            explainer = shap.TreeExplainer(bst)
-            explanation = explainer(val_data)
-
-            # save the beeswarm plot to png file
-            shap.plots.beeswarm(explanation, show=False)
-            img = plt.gcf()
-            img.subplots_adjust(left=0.3, right=0.9, bottom=0.3, top=0.9)
-            img.savefig(os.path.join(self._model_dir, "shap_beeswarm.png"), bbox_inches="tight")
+            if self._data_split_mode == 0:
+                # Save explainability outputs based on val_data
+                explainer = shap.TreeExplainer(bst)
+                explanation = explainer(val_data)
+
+                # save the beeswarm plot to png file
+                shap.plots.beeswarm(explanation, show=False)
+                img = plt.gcf()
+                img.subplots_adjust(left=0.3, right=0.9, bottom=0.3, top=0.9)
+                img.savefig(os.path.join(self._model_dir, "shap_beeswarm.png"), bbox_inches="tight")
 
         self._stopped = True