also returning accuracy score from test data from the api

app.py

@@ -45,4 +45,4 @@ def neural_net():
 
 
 if __name__ == "__main__":
-    app.run(debug=False)
+    app.run()

ml-vis

@@ -1 +1 @@
-Subproject commit 25374f53029979b4d35a79596baaf2f68174bc34
+Subproject commit 63131debee222b78f47a847e8cf8e3ab1f94526b

nn/train.py

@@ -88,6 +88,7 @@ def train(nn: NN) -> dict:
         "log_loss": log_loss(y_true=y_test, y_pred=y_hat),
         "accuracy": accuracy_score(y_true=y_test, y_pred=y_hat),
         "accuracy_scores": accuracy_scores,
+        "test_accuracy": accuracy_score(y_true=y_test, y_pred=y_hat)
     }