Fix compiled crossentropy (#18975)

* Fix compiled crossentropy

* Update test case naming

keras/trainers/compile_utils.py

@@ -468,6 +468,8 @@ def build(self, y_true, y_pred):
                     "must be a callable. "
                     f"Received instead:\nloss={loss} of type {type(loss)}"
                 )
+            if isinstance(y_pred, list) and len(y_pred) == 1:
+                y_pred = y_pred[0]
 
         if is_function_like(loss) and tree.is_nested(y_pred):
             # The model has multiple outputs but only one loss fn

keras/trainers/compile_utils_test.py

@@ -251,6 +251,21 @@ def test_single_output_case(self):
         value = compile_loss(y_true, y_pred)
         self.assertAllClose(value, 0.068333, atol=1e-5)
 
+    def test_single_output_case_with_crossentropy_loss(self):
+        compile_loss = CompileLoss(loss="crossentropy")
+
+        # Test symbolic build
+        y_true, y_pred = backend.KerasTensor((3, 4)), backend.KerasTensor(
+            (3, 4)
+        )
+        compile_loss.build(y_true, y_pred)
+        # Test eager build
+        y_true = np.array([[0.1, 0.2], [0.3, 0.4], [0.5, 0.6]])
+        y_pred = np.array([[0.4, 0.1], [0.2, 0.6], [0.6, 0.1]])
+        compile_loss.build(y_true, y_pred)
+        value = compile_loss(y_true, y_pred)
+        self.assertAllClose(value, 0.706595, atol=1e-5)
+
     @parameterized.parameters(True, False)
     def test_list_output_case(self, broadcast):
         if broadcast: