Ensures consistent serialization for Functional model (#21341)

* Fixes inconsitent serialization for nested inputs

* Adds test case to validate input shape

* renames methods

Author: JyotinderSingh

keras/src/models/functional.py

@@ -453,8 +453,6 @@ def get_tensor_config(tensor):
             return [operation.name, new_node_index, tensor_index]
 
         def map_tensors(tensors):
-            if isinstance(tensors, backend.KerasTensor):
-                return [get_tensor_config(tensors)]
             return tree.map_structure(get_tensor_config, tensors)
 
         config["input_layers"] = map_tensors(self._inputs_struct)
@@ -621,10 +619,6 @@ def map_tensors(tensors):
 
     input_tensors = map_tensors(functional_config["input_layers"])
     output_tensors = map_tensors(functional_config["output_layers"])
-    if isinstance(input_tensors, list) and len(input_tensors) == 1:
-        input_tensors = input_tensors[0]
-    if isinstance(output_tensors, list) and len(output_tensors) == 1:
-        output_tensors = output_tensors[0]
 
     return cls(
         inputs=input_tensors,

keras/src/models/functional_test.py

@@ -11,12 +11,14 @@
 from keras.src import ops
 from keras.src import saving
 from keras.src import testing
+from keras.src.backend.common.keras_tensor import KerasTensor
 from keras.src.dtype_policies import dtype_policy
 from keras.src.layers.core.input_layer import Input
 from keras.src.layers.input_spec import InputSpec
 from keras.src.models import Functional
 from keras.src.models import Model
 from keras.src.models import Sequential
+from keras.src.models.model import model_from_json
 
 
 class FunctionalTest(testing.TestCase):
@@ -273,6 +275,27 @@ def test_restored_multi_output_type(self, out_type):
         out_val = model_restored(Input(shape=(3,), batch_size=2))
         self.assertIsInstance(out_val, out_type)
 
+    def test_restored_nested_input(self):
+        input_a = Input(shape=(3,), batch_size=2, name="input_a")
+        x = layers.Dense(5)(input_a)
+        outputs = layers.Dense(4)(x)
+        model = Functional([[input_a]], outputs)
+
+        # Serialize and deserialize the model
+        json_config = model.to_json()
+        restored_json_config = model_from_json(json_config).to_json()
+
+        # Check that the serialized model is the same as the original
+        self.assertEqual(json_config, restored_json_config)
+
+    def test_functional_input_shape_and_type(self):
+        input = layers.Input((1024, 4))
+        conv = layers.Conv1D(32, 3)(input)
+        model = Functional(input, conv)
+
+        self.assertIsInstance(model.input, KerasTensor)
+        self.assertEqual(model.input_shape, (None, 1024, 4))
+
     @pytest.mark.requires_trainable_backend
     def test_layer_getters(self):
         # Test mixing ops and layers