add serialization tests for Sequential and Residual

Author: vpratz

tests/test_networks/test_residual/__init__.py

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+import pytest
+
+from bayesflow.networks.residual import Residual
+
+
+@pytest.fixture()
+def residual():
+    import keras
+
+    return Residual(keras.layers.Flatten(), keras.layers.Dense(2))
+
+
+@pytest.fixture()
+def build_shapes():
+    return {"input_shape": (32, 2)}

tests/test_networks/test_residual/conftest.py

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+import keras
+
+from bayesflow.utils.serialization import deserialize, serialize
+
+from ...utils import assert_layers_equal
+
+
+def test_serialize_deserialize(residual, build_shapes):
+    residual.build(**build_shapes)
+
+    serialized = serialize(residual)
+    deserialized = deserialize(serialized)
+    reserialized = serialize(deserialized)
+
+    assert reserialized == serialized
+
+
+def test_save_and_load(tmp_path, residual, build_shapes):
+    residual.build(**build_shapes)
+
+    keras.saving.save_model(residual, tmp_path / "model.keras")
+    loaded = keras.saving.load_model(tmp_path / "model.keras")
+
+    assert_layers_equal(residual, loaded)

tests/test_networks/test_residual/test_residual.py

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+import pytest
+
+from bayesflow.networks import Sequential
+
+
+@pytest.fixture()
+def sequential():
+    import keras
+
+    return Sequential(keras.layers.Flatten(), keras.layers.Dense(2))
+
+
+@pytest.fixture()
+def build_shapes():
+    return {"input_shape": (32, 2)}

tests/test_networks/test_sequential/__init__.py

@@ -0,0 +1,24 @@
+import keras
+
+from bayesflow.utils.serialization import deserialize, serialize
+
+from ...utils import assert_layers_equal
+
+
+def test_serialize_deserialize(sequential, build_shapes):
+    sequential.build(**build_shapes)
+
+    serialized = serialize(sequential)
+    deserialized = deserialize(serialized)
+    reserialized = serialize(deserialized)
+
+    assert reserialized == serialized
+
+
+def test_save_and_load(tmp_path, sequential, build_shapes):
+    sequential.build(**build_shapes)
+
+    keras.saving.save_model(sequential, tmp_path / "model.keras")
+    loaded = keras.saving.load_model(tmp_path / "model.keras")
+
+    assert_layers_equal(sequential, loaded)