having some issues with backprop when trying to use the iris dataset

app.py

@@ -41,13 +41,11 @@ def index():
     # in the future instead of a random data set
     # we should do a more real one like palmer penguins
 
-    X_train, X_test, y_train, y_test = iris()
+    X, y = iris()
     return jsonify(
         algorithm(
-            X_train=X_train,
-            y_train=y_train,
-            X_test=X_test,
-            y_test=y_test,
+            X=X,
+            y=y,
             args=args,
         )
     )

neural_network/backprop.py

@@ -22,8 +22,8 @@ def bp(
     X_train: np.array,
     y_train: np.array,
     wb: dict,
-    args: dict
-):
+    args: dict,
+) -> NeuralNetwork:
     model = NeuralNetwork.from_dict(args | wb)
     loss_history = []
     for _ in range(model.epochs):

neural_network/main.py

@@ -37,7 +37,12 @@ def main(
         random_state=8675309,
     )
 
-    model = bp(X_train, y_train, wb, args)
+    model = bp(
+        X_train=X_train,
+        y_train=y_train,
+        wb=wb,
+        args=args,
+    )
 
     # evaluate the model and return final results
     model.eval(