Don't warn about autoboxing.

Author: khatchad

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testModel/in/A.py

@@ -0,0 +1,41 @@
+import tensorflow as tf
+
+# Create an override model to classify pictures
+
+class SequentialModel(tf.keras.Model):
+  def __init__(self, **kwargs):
+    super(SequentialModel, self).__init__(**kwargs)
+
+    self.flatten = tf.keras.layers.Flatten(input_shape=(28, 28))
+
+    # Add a lot of small layers
+    num_layers = 100
+    self.my_layers = [tf.keras.layers.Dense(64, activation="relu")
+                      for n in range(num_layers)]
+
+    self.dropout = tf.keras.layers.Dropout(0.2)
+    self.dense_2 = tf.keras.layers.Dense(10)
+
+  def call(self, x):
+    x = self.flatten(x)
+
+    for layer in self.my_layers:
+      x = layer(x)
+
+    x = self.dropout(x)
+    x = self.dense_2(x)
+
+    return x
+
+if __name__ == '__main__':
+    input_data = tf.random.uniform([20, 28, 28])
+    print("Input:")
+    print(type(input_data))
+    print(input_data)
+
+    model = SequentialModel()
+    result = model(input_data)
+
+    print("Output:")
+    print(type(input_data))
+    print(result)

edu.cuny.hunter.hybridize.tests/resources/HybridizeFunction/testModel/in/requirements.txt

@@ -0,0 +1 @@
+tensorflow==2.9.3

pom.xml

@@ -156,6 +156,7 @@
                         <arg>-err:-super</arg>
                         <arg>-err:-discouraged</arg>
                         <arg>-err:-emptyBlock</arg>
+                        <arg>-err:-boxing</arg>
                     </compilerArgs>
                 </configuration>
             </plugin>