as_model wraps function arguments in Data if they support it.

pymc_extras/model/model_api.py

@@ -1,6 +1,9 @@
 from functools import wraps
+from inspect import signature
 
-from pymc import Model
+import pytensor.tensor as pt
+
+from pymc import Data, Model
 
 
 def as_model(*model_args, **model_kwargs):
@@ -9,6 +12,8 @@ def as_model(*model_args, **model_kwargs):
     This removes all need to think about context managers and lets you separate creating a generative model from using the model.
     Additionally, a coords argument is added to the function so coords can be changed during function invocation
 
+    All parameters are wrapped with a `pm.Data` object if the underlying type of the data supports it.
+
     Adapted from `Rob Zinkov's blog post <https://www.zinkov.com/posts/2023-alternative-frontends-pymc/>`_ and inspired by the `sampled <https://github.com/colcarroll/sampled>`_ decorator for PyMC3.
 
     Examples
@@ -47,8 +52,19 @@ def decorator(f):
         @wraps(f)
         def make_model(*args, **kwargs):
             coords = model_kwargs.pop("coords", {}) | kwargs.pop("coords", {})
+            sig = signature(f)
+            ba = sig.bind(*args, **kwargs)
+            ba.apply_defaults()
+
             with Model(*model_args, coords=coords, **model_kwargs) as m:
-                f(*args, **kwargs)
+                for name, v in ba.arguments.items():
+                    # Only wrap pm.Data around values pytensor can process
+                    try:
+                        _ = pt.as_tensor_variable(v)
+                        ba.arguments[name] = Data(name, v)
+                    except (NotImplementedError, TypeError, ValueError):
+                        pass
+                f(*ba.args, **ba.kwargs)
             return m
 
         return make_model

tests/model/test_model_api.py

@@ -25,5 +25,14 @@ def model_wrapped2():
 
     mw2 = model_wrapped2(coords=coords)
 
+    @pmx.as_model()
+    def model_wrapped3(mu):
+        pm.Normal("x", mu, 1.0, dims="obs")
+
+    mw3 = model_wrapped3(0.0, coords=coords)
+    mw4 = model_wrapped3(np.array([np.nan]), coords=coords)
+
     np.testing.assert_equal(model.point_logps(), mw.point_logps())
     np.testing.assert_equal(mw.point_logps(), mw2.point_logps())
+    assert mw3["mu"] in mw3.data_vars
+    assert "mu" not in mw4