Avoid unclear TypeError when using theano.shared variables as input to distribution parameters

RELEASE-NOTES.md

@@ -8,6 +8,7 @@
 
 ### Maintenance
 - `math.log1mexp_numpy` no longer raises RuntimeWarning when given very small inputs. These were commonly observed during NUTS sampling (see [#4428](https://github.com/pymc-devs/pymc3/pull/4428)).
+- `ScalarSharedVariable` can now be used as an input to other RVs directly (see [#4445](https://github.com/pymc-devs/pymc3/pull/4445)).
 
 ## PyMC3 3.11.0 (21 January 2021)
 

pymc3/distributions/distribution.py

@@ -148,17 +148,17 @@ def default(self):
     def get_test_val(self, val, defaults):
         if val is None:
             for v in defaults:
-                if hasattr(self, v) and np.all(np.isfinite(self.getattr_value(v))):
-                    return self.getattr_value(v)
-        else:
-            return self.getattr_value(val)
-
-        if val is None:
+                if hasattr(self, v):
+                    attr_val = self.getattr_value(v)
+                    if np.all(np.isfinite(attr_val)):
+                        return attr_val
             raise AttributeError(
                 "%s has no finite default value to use, "
                 "checked: %s. Pass testval argument or "
                 "adjust so value is finite." % (self, str(defaults))
             )
+        else:
+            return self.getattr_value(val)
 
     def getattr_value(self, val):
         if isinstance(val, string_types):
@@ -167,7 +167,7 @@ def getattr_value(self, val):
         if isinstance(val, tt.TensorVariable):
             return val.tag.test_value
 
-        if isinstance(val, tt.sharedvar.TensorSharedVariable):
+        if isinstance(val, tt.sharedvar.SharedVariable):
             return val.get_value()
 
         if isinstance(val, theano_constant):

pymc3/tests/test_data_container.py

@@ -16,6 +16,8 @@
 import pandas as pd
 import pytest
 
+from theano import shared
+
 import pymc3 as pm
 
 from pymc3.tests.helpers import SeededTest
@@ -156,6 +158,26 @@ def test_shared_data_as_rv_input(self):
         np.testing.assert_allclose(np.array([2.0, 4.0, 6.0]), x.get_value(), atol=1e-1)
         np.testing.assert_allclose(np.array([2.0, 4.0, 6.0]), trace["y"].mean(0), atol=1e-1)
 
+    def test_shared_scalar_as_rv_input(self):
+        # See https://github.com/pymc-devs/pymc3/issues/3139
+        with pm.Model() as m:
+            shared_var = shared(5.0)
+            v = pm.Normal("v", mu=shared_var, shape=1)
+
+        np.testing.assert_allclose(
+            v.logp({"v": [5.0]}),
+            -0.91893853,
+            rtol=1e-5,
+        )
+
+        shared_var.set_value(10.0)
+
+        np.testing.assert_allclose(
+            v.logp({"v": [10.0]}),
+            -0.91893853,
+            rtol=1e-5,
+        )
+
     def test_creation_of_data_outside_model_context(self):
         with pytest.raises((IndexError, TypeError)) as error:
             pm.Data("data", [1.1, 2.2, 3.3])