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Ensures consistent serialization for Functional model #21341

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Merged
merged 3 commits into from
Jun 2, 2025
Merged

Ensures consistent serialization for Functional model #21341

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b36d717
Fixes inconsitent serialization for nested inputs
JyotinderSingh Jun 2, 2025
1ab48b8
Adds test case to validate input shape
JyotinderSingh Jun 2, 2025
de15418
renames methods
JyotinderSingh Jun 2, 2025
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6 changes: 0 additions & 6 deletions keras/src/models/functional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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)
Expand Down Expand Up @@ -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,
Expand Down
23 changes: 23 additions & 0 deletions keras/src/models/functional_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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):
Expand Down Expand Up @@ -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
Expand Down