Fixes inconsistent serialization logic for inputs (#20993)

* Removes unnesting logic for input tensors in functional model deserialization flow

* Adds test case for verifying nested input restoration after deserialization

removes unnecessary imports

* fixes imports

Author: JyotinderSingh

keras/src/models/functional.py

@@ -618,8 +618,6 @@ 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]
 

keras/src/models/functional_test.py

@@ -16,6 +16,7 @@
 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):
@@ -272,6 +273,19 @@ 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)
+
     @pytest.mark.requires_trainable_backend
     def test_layer_getters(self):
         # Test mixing ops and layers