Fix MWE for multithreading

Author: dwoiwode

examples/basics/image_classification.py

@@ -9,20 +9,25 @@
 # Note: You can write your own datamanager! Call fit with respective train, valid data (numpy matrices) 
 csv_dir = os.path.abspath("../../datasets/example.csv")
 
-X_train = np.array([csv_dir])
-Y_train = np.array([0])
-
-# Note: every parameter has a default value, you do not have to specify anything. The given parameter allow a fast test.
-autonet = AutoNetImageClassification(config_preset="tiny_cs", result_logger_dir="logs/")
-
-res = autonet.fit(X_train=X_train,
-                  Y_train=Y_train,
-                  images_shape=[3, 32, 32],
-                  min_budget=600,
-                  max_budget=900,
-                  max_runtime=1800,
-                  save_checkpoints=True,
-                  images_root_folders=[os.path.abspath("../../datasets/example_images")])
-
-print(res)
-print("Score:", autonet.score(X_test=X_train, Y_test=Y_train))
+def main():
+    X_train = np.array([csv_dir])
+    Y_train = np.array([0])
+
+    # Note: every parameter has a default value, you do not have to specify anything. The given parameter allow a fast test.
+    autonet = AutoNetImageClassification(config_preset="full_cs", result_logger_dir="logs/")
+
+    res = autonet.fit(X_train=X_train,
+                      Y_train=Y_train,
+                      images_shape=[3, 32, 32],
+                      min_budget=600,
+                      max_budget=900,
+                      max_runtime=1800,
+                      save_checkpoints=True,
+                      images_root_folders=[os.path.abspath("../../datasets/example_images")])
+
+    print(res)
+    print("Score:", autonet.score(X_test=X_train, Y_test=Y_train))
+
+
+if __name__ == '__main__':
+    main()