rename (de)serialize_val_or_type to (de)serialize_value_or_type

bayesflow/networks/consistency_models/consistency_model.py

@@ -7,7 +7,7 @@
 import numpy as np
 
 from bayesflow.types import Tensor
-from bayesflow.utils import find_network, keras_kwargs, serialize_val_or_type, deserialize_val_or_type
+from bayesflow.utils import find_network, keras_kwargs, serialize_value_or_type, deserialize_value_or_type
 
 
 from ..inference_network import InferenceNetwork
@@ -98,15 +98,15 @@ def __init__(
             "s1": s1,
             **kwargs,
         }
-        self.config = serialize_val_or_type(self.config, "subnet", subnet)
+        self.config = serialize_value_or_type(self.config, "subnet", subnet)
 
     def get_config(self):
         base_config = super().get_config()
         return base_config | self.config
 
     @classmethod
     def from_config(cls, config):
-        config = deserialize_val_or_type(config, "subnet")
+        config = deserialize_value_or_type(config, "subnet")
         return cls(**config)
 
     def _schedule_discretization(self, step) -> float:

bayesflow/networks/consistency_models/continuous_consistency_model.py

@@ -14,8 +14,8 @@
     keras_kwargs,
     expand_right_as,
     expand_right_to,
-    serialize_val_or_type,
-    deserialize_val_or_type,
+    serialize_value_or_type,
+    deserialize_value_or_type,
 )
 
 
@@ -76,15 +76,15 @@ def __init__(
             "sigma_data": sigma_data,
             **kwargs,
         }
-        self.config = serialize_val_or_type(self.config, "subnet", subnet)
+        self.config = serialize_value_or_type(self.config, "subnet", subnet)
 
     def get_config(self):
         base_config = super().get_config()
         return base_config | self.config
 
     @classmethod
     def from_config(cls, config):
-        config = deserialize_val_or_type(config, "subnet")
+        config = deserialize_value_or_type(config, "subnet")
         return cls(**config)
 
     def _discretize_time(self, num_steps: int, rho: float = 3.5, **kwargs):

bayesflow/networks/coupling_flow/coupling_flow.py

@@ -2,7 +2,7 @@
 from keras.saving import register_keras_serializable as serializable
 
 from bayesflow.types import Tensor
-from bayesflow.utils import find_permutation, keras_kwargs, serialize_val_or_type, deserialize_val_or_type
+from bayesflow.utils import find_permutation, keras_kwargs, serialize_value_or_type, deserialize_value_or_type
 
 from .actnorm import ActNorm
 from .couplings import DualCoupling
@@ -67,7 +67,7 @@ def __init__(
             "base_distribution": base_distribution,
             **kwargs,
         }
-        self.config = serialize_val_or_type(self.config, "subnet", subnet)
+        self.config = serialize_value_or_type(self.config, "subnet", subnet)
 
     # noinspection PyMethodOverriding
     def build(self, xz_shape, conditions_shape=None):
@@ -82,7 +82,7 @@ def get_config(self):
 
     @classmethod
     def from_config(cls, config):
-        config = deserialize_val_or_type(config, "subnet")
+        config = deserialize_value_or_type(config, "subnet")
         return cls(**config)
 
     def _forward(

bayesflow/networks/coupling_flow/couplings/dual_coupling.py

@@ -1,7 +1,7 @@
 import keras
 from keras.saving import register_keras_serializable as serializable
 
-from bayesflow.utils import keras_kwargs, serialize_val_or_type, deserialize_val_or_type
+from bayesflow.utils import keras_kwargs, serialize_value_or_type, deserialize_value_or_type
 from bayesflow.types import Tensor
 from .single_coupling import SingleCoupling
 from ..invertible_layer import InvertibleLayer
@@ -20,15 +20,15 @@ def __init__(self, subnet: str | type = "mlp", transform: str = "affine", **kwar
             "transform": transform,
             **kwargs,
         }
-        self.config = serialize_val_or_type(self.config, "subnet", subnet)
+        self.config = serialize_value_or_type(self.config, "subnet", subnet)
 
     def get_config(self):
         base_config = super().get_config()
         return base_config | self.config
 
     @classmethod
     def from_config(cls, config):
-        config = deserialize_val_or_type(config, "subnet")
+        config = deserialize_value_or_type(config, "subnet")
         return cls(**config)
 
     # noinspection PyMethodOverriding

bayesflow/networks/coupling_flow/couplings/single_coupling.py

@@ -3,7 +3,7 @@
 from keras.saving import register_keras_serializable as serializable
 
 from bayesflow.types import Tensor
-from bayesflow.utils import find_network, keras_kwargs, serialize_val_or_type, deserialize_val_or_type
+from bayesflow.utils import find_network, keras_kwargs, serialize_value_or_type, deserialize_value_or_type
 from ..invertible_layer import InvertibleLayer
 from ..transforms import find_transform
 
@@ -31,15 +31,15 @@ def __init__(self, subnet: str | type = "mlp", transform: str = "affine", **kwar
             "transform": transform,
             **kwargs,
         }
-        self.config = serialize_val_or_type(self.config, "subnet", subnet)
+        self.config = serialize_value_or_type(self.config, "subnet", subnet)
 
     def get_config(self):
         base_config = super().get_config()
         return base_config | self.config
 
     @classmethod
     def from_config(cls, config):
-        config = deserialize_val_or_type(config, "subnet")
+        config = deserialize_value_or_type(config, "subnet")
         return cls(**config)
 
     # noinspection PyMethodOverriding

bayesflow/networks/flow_matching/flow_matching.py

@@ -7,8 +7,8 @@
     expand_right_as,
     keras_kwargs,
     optimal_transport,
-    serialize_val_or_type,
-    deserialize_val_or_type,
+    serialize_value_or_type,
+    deserialize_value_or_type,
 )
 from ..inference_network import InferenceNetwork
 from .integrators import EulerIntegrator
@@ -66,7 +66,7 @@ def __init__(
             "optimal_transport_kwargs": optimal_transport_kwargs,
             **kwargs,
         }
-        self.config = serialize_val_or_type(self.config, "subnet", subnet)
+        self.config = serialize_value_or_type(self.config, "subnet", subnet)
 
     def build(self, xz_shape: Shape, conditions_shape: Shape = None) -> None:
         super().build(xz_shape)
@@ -78,7 +78,7 @@ def get_config(self):
 
     @classmethod
     def from_config(cls, config):
-        config = deserialize_val_or_type(config, "subnet")
+        config = deserialize_value_or_type(config, "subnet")
         return cls(**config)
 
     def _forward(

bayesflow/networks/free_form_flow/free_form_flow.py

@@ -10,8 +10,8 @@
     log_jacobian_determinant,
     jvp,
     vjp,
-    serialize_val_or_type,
-    deserialize_val_or_type,
+    serialize_value_or_type,
+    deserialize_value_or_type,
 )
 
 from ..inference_network import InferenceNetwork
@@ -79,17 +79,17 @@ def __init__(
             "hutchinson_sampling": hutchinson_sampling,
             **kwargs,
         }
-        self.config = serialize_val_or_type(self.config, "encoder_subnet", encoder_subnet)
-        self.config = serialize_val_or_type(self.config, "decoder_subnet", decoder_subnet)
+        self.config = serialize_value_or_type(self.config, "encoder_subnet", encoder_subnet)
+        self.config = serialize_value_or_type(self.config, "decoder_subnet", decoder_subnet)
 
     def get_config(self):
         base_config = super().get_config()
         return base_config | self.config
 
     @classmethod
     def from_config(cls, config):
-        config = deserialize_val_or_type(config, "encoder_subnet")
-        config = deserialize_val_or_type(config, "decoder_subnet")
+        config = deserialize_value_or_type(config, "encoder_subnet")
+        config = deserialize_value_or_type(config, "decoder_subnet")
         return cls(**config)
 
     # noinspection PyMethodOverriding

bayesflow/utils/__init__.py

@@ -18,7 +18,7 @@
     format_bytes,
     parse_bytes,
 )
-from .serialization import serialize_val_or_type, deserialize_val_or_type
+from .serialization import serialize_value_or_type, deserialize_value_or_type
 from .jacobian_trace import jacobian_trace
 from .jacobian import compute_jacobian, log_jacobian_determinant
 from .jvp import jvp

bayesflow/utils/serialization.py

@@ -4,7 +4,7 @@
 PREFIX = "_bayesflow_"
 
 
-def serialize_val_or_type(config, name, obj):
+def serialize_value_or_type(config, name, obj):
     """Serialize an object that can be either a value or a type
     and add it to a copy of the supplied dictionary.
 
@@ -43,7 +43,7 @@ def serialize_val_or_type(config, name, obj):
     return updated_config
 
 
-def deserialize_val_or_type(config, name):
+def deserialize_value_or_type(config, name):
     """Deserialize an object that can be either a value or a type and add
     it to the supplied dictionary.
 
@@ -66,7 +66,7 @@ def deserialize_val_or_type(config, name):
 
     See Also
     --------
-    `serialize_val_or_type`
+    `serialize_value_or_type`
     """
     updated_config = config.copy()
     if f"{PREFIX}{name}_type" in config: