disable invalid-name

sudhcha · Nov 27, 2021 · 05c098b · 05c098b
1 parent 017d0b6
commit 05c098b
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Showing 4 changed files with 12 additions and 12 deletions.
diff --git a/notebooks/kubeflow_pipelines/pipelines/labs/trainer_image/train.py b/notebooks/kubeflow_pipelines/pipelines/labs/trainer_image/train.py
@@ -77,18 +77,16 @@ def train_evaluate(
     df_validation = df_validation.astype(num_features_type_map)
 
     print(f"Starting training: alpha={alpha}, max_iter={max_iter}")
-    X_train = df_train.drop(  # pylint: disable=invalid-name
-        "Cover_Type", axis=1
-    )
+    # pylint: disable-next=invalid-name
+    X_train = df_train.drop("Cover_Type", axis=1)
     y_train = df_train["Cover_Type"]
 
     pipeline.set_params(classifier__alpha=alpha, classifier__max_iter=max_iter)
     pipeline.fit(X_train, y_train)
 
     if hptune:
-        X_validation = df_validation.drop(  # pylint: disable=invalid-name
-            "Cover_Type", axis=1
-        )
+        # pylint: disable-next=invalid-name
+        X_validation = df_validation.drop("Cover_Type", axis=1)
         y_validation = df_validation["Cover_Type"]
         accuracy = pipeline.score(X_validation, y_validation)
         print(f"Model accuracy: {accuracy}")

diff --git a/notebooks/kubeflow_pipelines/pipelines/labs/trainer_image_vertex/train.py b/notebooks/kubeflow_pipelines/pipelines/labs/trainer_image_vertex/train.py
@@ -74,13 +74,15 @@ def train_evaluate(
     df_validation = df_validation.astype(num_features_type_map)
 
     print(f"Starting training: alpha={alpha}, max_iter={max_iter}")
+    # pylint: disable-next=invalid-name
     X_train = df_train.drop("Cover_Type", axis=1)
     y_train = df_train["Cover_Type"]
 
     pipeline.set_params(classifier__alpha=alpha, classifier__max_iter=max_iter)
     pipeline.fit(X_train, y_train)
 
     if hptune:
+        # pylint: disable-next=invalid-name
         X_validation = df_validation.drop("Cover_Type", axis=1)
         y_validation = df_validation["Cover_Type"]
         accuracy = pipeline.score(X_validation, y_validation)

diff --git a/notebooks/kubeflow_pipelines/pipelines/solutions/trainer_image/train.py b/notebooks/kubeflow_pipelines/pipelines/solutions/trainer_image/train.py
@@ -77,18 +77,16 @@ def train_evaluate(
     df_validation = df_validation.astype(num_features_type_map)
 
     print(f"Starting training: alpha={alpha}, max_iter={max_iter}")
-    X_train = df_train.drop(  # pylint: disable=invalid-name
-        "Cover_Type", axis=1
-    )
+    # pylint: disable-next=invalid-name
+    X_train = df_train.drop("Cover_Type", axis=1)
     y_train = df_train["Cover_Type"]
 
     pipeline.set_params(classifier__alpha=alpha, classifier__max_iter=max_iter)
     pipeline.fit(X_train, y_train)
 
     if hptune:
-        X_validation = df_validation.drop(  # pylint: disable=invalid-name
-            "Cover_Type", axis=1
-        )
+        # pylint: disable-next=invalid-name
+        X_validation = df_validation.drop("Cover_Type", axis=1)
         y_validation = df_validation["Cover_Type"]
         accuracy = pipeline.score(X_validation, y_validation)
         print(f"Model accuracy: {accuracy}")

diff --git a/notebooks/kubeflow_pipelines/pipelines/solutions/trainer_image_vertex/train.py b/notebooks/kubeflow_pipelines/pipelines/solutions/trainer_image_vertex/train.py
@@ -74,13 +74,15 @@ def train_evaluate(
     df_validation = df_validation.astype(num_features_type_map)
 
     print(f"Starting training: alpha={alpha}, max_iter={max_iter}")
+    # pylint: disable-next=invalid-name
     X_train = df_train.drop("Cover_Type", axis=1)
     y_train = df_train["Cover_Type"]
 
     pipeline.set_params(classifier__alpha=alpha, classifier__max_iter=max_iter)
     pipeline.fit(X_train, y_train)
 
     if hptune:
+        # pylint: disable-next=invalid-name
         X_validation = df_validation.drop("Cover_Type", axis=1)
         y_validation = df_validation["Cover_Type"]
         accuracy = pipeline.score(X_validation, y_validation)