Move DiffusionModel from experimental to networks module

bayesflow/experimental/__init__.py

@@ -9,4 +9,4 @@
 
 from ..utils._docs import _add_imports_to_all
 
-_add_imports_to_all(include_modules=["diffusion_model"])
+_add_imports_to_all()

bayesflow/experimental/diffusion_model/__init__.py

@@ -1,9 +1,13 @@
-from .diffusion_model import DiffusionModel
-from bayesflow.experimental.diffusion_model.schedules import CosineNoiseSchedule
-from bayesflow.experimental.diffusion_model.schedules import EDMNoiseSchedule
-from bayesflow.experimental.diffusion_model.schedules import NoiseSchedule
-from .dispatch import find_noise_schedule
+from bayesflow.networks import DiffusionModel as StabilizedDiffusionModel
 
-from ...utils._docs import _add_imports_to_all
 
-_add_imports_to_all(include_modules=[])
+def DiffusionModel(*args, **kwargs):
+    from warnings import warn
+
+    warn(
+        "DiffusionModel has been stabilized and moved to bayesflow.networks. "
+        "Please switch your imports to the new location. This reference will be "
+        "removed in a future version.",
+        FutureWarning,
+    )
+    return StabilizedDiffusionModel(*args, **kwargs)

bayesflow/networks/__init__.py

@@ -7,6 +7,7 @@
 from .consistency_models import ConsistencyModel
 from .coupling_flow import CouplingFlow
 from .deep_set import DeepSet
+from .diffusion_model import DiffusionModel
 from .flow_matching import FlowMatching
 from .inference_network import InferenceNetwork
 from .point_inference_network import PointInferenceNetwork
@@ -19,4 +20,4 @@
 
 from ..utils._docs import _add_imports_to_all
 
-_add_imports_to_all(include_modules=[])
+_add_imports_to_all(include_modules=["diffusion_model"])

bayesflow/networks/diffusion_model/__init__.py

@@ -0,0 +1,9 @@
+from .diffusion_model import DiffusionModel
+from .schedules import CosineNoiseSchedule
+from .schedules import EDMNoiseSchedule
+from .schedules import NoiseSchedule
+from .dispatch import find_noise_schedule
+
+from ...utils._docs import _add_imports_to_all
+
+_add_imports_to_all(include_modules=[])

bayesflow/experimental/diffusion_model/diffusion_model.py → bayesflow/networks/diffusion_model/diffusion_model.py

@@ -4,7 +4,7 @@
 import keras
 from keras import ops
 
-from bayesflow.networks import InferenceNetwork
+from ..inference_network import InferenceNetwork
 from bayesflow.types import Tensor, Shape
 from bayesflow.utils import (
     expand_right_as,

examples/Likelihood_Estimation.ipynb

@@ -200,7 +200,7 @@
    "source": [
     "workflow = bf.BasicWorkflow(\n",
     "    simulator=simulator,\n",
-    "    inference_network=bf.experimental.DiffusionModel(),\n",
+    "    inference_network=bf.networks.DiffusionModel(),\n",
     "    inference_variables=\"x\",\n",
     "    inference_conditions=\"theta\",\n",
     "    initial_learning_rate=1e-3,\n",

tests/test_networks/conftest.py

@@ -5,7 +5,7 @@
 
 @pytest.fixture()
 def diffusion_model_edm_F():
-    from bayesflow.experimental import DiffusionModel
+    from bayesflow.networks import DiffusionModel
 
     return DiffusionModel(
         subnet=MLP([8, 8]),
@@ -17,7 +17,7 @@ def diffusion_model_edm_F():
 
 @pytest.fixture()
 def diffusion_model_edm_velocity():
-    from bayesflow.experimental import DiffusionModel
+    from bayesflow.networks import DiffusionModel
 
     return DiffusionModel(
         subnet=MLP([8, 8]),
@@ -29,7 +29,7 @@ def diffusion_model_edm_velocity():
 
 @pytest.fixture()
 def diffusion_model_edm_noise():
-    from bayesflow.experimental import DiffusionModel
+    from bayesflow.networks import DiffusionModel
 
     return DiffusionModel(
         subnet=MLP([8, 8]),
@@ -41,7 +41,7 @@ def diffusion_model_edm_noise():
 
 @pytest.fixture()
 def diffusion_model_cosine_F():
-    from bayesflow.experimental import DiffusionModel
+    from bayesflow.networks import DiffusionModel
 
     return DiffusionModel(
         subnet=MLP([8, 8]),
@@ -53,7 +53,7 @@ def diffusion_model_cosine_F():
 
 @pytest.fixture()
 def diffusion_model_cosine_velocity():
-    from bayesflow.experimental import DiffusionModel
+    from bayesflow.networks import DiffusionModel
 
     return DiffusionModel(
         subnet=MLP([8, 8]),
@@ -65,7 +65,7 @@ def diffusion_model_cosine_velocity():
 
 @pytest.fixture()
 def diffusion_model_cosine_noise():
-    from bayesflow.experimental import DiffusionModel
+    from bayesflow.networks import DiffusionModel
 
     return DiffusionModel(
         subnet=MLP([8, 8]),

tests/test_networks/test_diffusion_model/conftest.py

@@ -3,14 +3,14 @@
 
 @pytest.fixture()
 def cosine_noise_schedule():
-    from bayesflow.experimental.diffusion_model.schedules import CosineNoiseSchedule
+    from bayesflow.networks.diffusion_model.schedules import CosineNoiseSchedule
 
     return CosineNoiseSchedule(min_log_snr=-12, max_log_snr=12, shift=0.1, weighting="likelihood_weighting")
 
 
 @pytest.fixture()
 def edm_noise_schedule():
-    from bayesflow.experimental.diffusion_model.schedules import EDMNoiseSchedule
+    from bayesflow.networks.diffusion_model.schedules import EDMNoiseSchedule
 
     return EDMNoiseSchedule(sigma_data=10.0, sigma_min=1e-5, sigma_max=85.0)
 

tests/test_networks/test_inference_networks.py

@@ -88,7 +88,7 @@ def test_cycle_consistency(generative_inference_network, random_samples, random_
     # cycle-consistency means the forward and inverse methods are inverses of each other
     import bayesflow as bf
 
-    if isinstance(generative_inference_network, bf.experimental.DiffusionModel):
+    if isinstance(generative_inference_network, bf.networks.DiffusionModel):
         pytest.skip(reason="test unstable for untrained diffusion models")
     try:
         forward_output, forward_log_density = generative_inference_network(

tests/test_utils/test_dispatch.py

@@ -2,7 +2,7 @@
 import pytest
 
 from bayesflow.utils import find_inference_network, find_distribution, find_network, find_summary_network
-from bayesflow.experimental.diffusion_model import find_noise_schedule
+from bayesflow.networks.diffusion_model import find_noise_schedule
 
 # --- Tests for find__network.py ---
 
@@ -247,7 +247,7 @@ def test_find_summary_network_invalid_type():
 
 
 def test_find_noise_schedule_by_name():
-    from bayesflow.experimental.diffusion_model.schedules import CosineNoiseSchedule, EDMNoiseSchedule
+    from bayesflow.networks.diffusion_model.schedules import CosineNoiseSchedule, EDMNoiseSchedule
 
     schedule = find_noise_schedule("cosine")
     assert isinstance(schedule, CosineNoiseSchedule)
@@ -262,7 +262,7 @@ def test_find_noise_schedule_unknown_name():
 
 
 def test_pass_noise_schedule():
-    from bayesflow.experimental.diffusion_model.schedules.noise_schedule import NoiseSchedule
+    from bayesflow.networks.diffusion_model.schedules.noise_schedule import NoiseSchedule
 
     class CustomNoiseSchedule(NoiseSchedule):
         def __init__(self):
@@ -282,7 +282,7 @@ def derivative_log_snr(self, log_snr_t, training):
 
 
 def test_pass_noise_schedule_type():
-    from bayesflow.experimental.diffusion_model.schedules import EDMNoiseSchedule
+    from bayesflow.networks.diffusion_model.schedules import EDMNoiseSchedule
 
     schedule = find_noise_schedule(EDMNoiseSchedule, sigma_data=10.0)
     assert isinstance(schedule, EDMNoiseSchedule)