Make nested models share coords with parents

RELEASE-NOTES.md

@@ -120,6 +120,7 @@ This includes API changes we did not warn about since at least `3.11.0` (2021-01
   - New named dimensions can be introduced to the model via `pm.Data(..., dims=...)`. For mutable data variables (see above) the lengths of these dimensions are symbolic, so they can be re-sized via `pm.set_data()`.
   - `pm.Data` now passes additional kwargs to `aesara.shared`/`at.as_tensor`. [#5098](https://github.com/pymc-devs/pymc/pull/5098).
 - Univariate censored distributions are now available via `pm.Censored`. [#5169](https://github.com/pymc-devs/pymc/pull/5169)
+- Nested models now inherit the parent model's coordinates. [#5344](https://github.com/pymc-devs/pymc/pull/5344)
 - ...
 
 

pymc/model.py

@@ -628,10 +628,6 @@ def __init__(
         rng_seeder: Optional[Union[int, np.random.RandomState]] = None,
     ):
         self.name = name
-        self._coords = {}
-        self._RV_dims = {}
-        self._dim_lengths = {}
-        self.add_coords(coords)
         self.check_bounds = check_bounds
 
         if rng_seeder is None:
@@ -654,6 +650,9 @@ def __init__(
             self.auto_deterministics = treelist(parent=self.parent.auto_deterministics)
             self.deterministics = treelist(parent=self.parent.deterministics)
             self.potentials = treelist(parent=self.parent.potentials)
+            self._coords = self.parent._coords
+            self._RV_dims = treedict(parent=self.parent._RV_dims)
+            self._dim_lengths = self.parent._dim_lengths
         else:
             self.named_vars = treedict()
             self.values_to_rvs = treedict()
@@ -663,6 +662,10 @@ def __init__(
             self.auto_deterministics = treelist()
             self.deterministics = treelist()
             self.potentials = treelist()
+            self._coords = {}
+            self._RV_dims = treedict()
+            self._dim_lengths = {}
+        self.add_coords(coords)
 
         from pymc.printing import str_for_model
 

pymc/tests/test_model.py

@@ -651,3 +651,17 @@ def test_datalogpt_multiple_shapes():
     # This would raise a TypeError, see #4803 and #4804
     x_val = m.rvs_to_values[x]
     m.datalogpt.eval({x_val: 0})
+
+
+def test_nested_model_coords():
+    COORDS = {"dim": range(10)}
+    with pm.Model(name="m1", coords=COORDS) as m1:
+        a = pm.Normal("a")
+        with pm.Model(name="m2") as m2:
+            b = pm.Normal("b")
+            c = pm.HalfNormal("c")
+            d = pm.Normal("d", b, c, dims="dim")
+        e = pm.Normal("e", a + d, dims="dim")
+    assert m1.coords is m2.coords
+    assert m1.dim_lengths is m2.dim_lengths
+    assert set(m2.RV_dims) < set(m1.RV_dims)