Lift constraint on dim lengths being constant in R2D2M2CP

A constraint can be introduced by using `freeze_data_and_dims`

Author: ricardoV94

pymc_experimental/distributions/multivariate/r2d2m2cp.py

@@ -418,9 +418,7 @@ def R2D2M2CP(
     *broadcast_dims, dim = dims
     input_sigma = pt.as_tensor(input_sigma)
     output_sigma = pt.as_tensor(output_sigma)
-    with pm.Model(name) as model:
-        if not all(isinstance(model.dim_lengths[d], pt.TensorConstant) for d in dims):
-            raise ValueError(f"{dims!r} should be constant length immutable dims")
+    with pm.Model(name):
         if r2_std is not None:
             r2 = pm.Beta("r2", mu=r2, sigma=r2_std, dims=broadcast_dims)
         phi = _phi(

pymc_experimental/tests/distributions/test_multivariate.py

@@ -302,27 +302,3 @@ def test_zero_length_rvs_not_created(self, model: pm.Model):
             "b2", 1, [1, 1], r2=0.5, positive_probs=[1, 1], positive_probs_std=[0, 0], dims="a"
         )
         assert not model.free_RVs, model.free_RVs
-
-    def test_immutable_dims(self, model: pm.Model):
-        model.add_coord("a", range(2), mutable=True)
-        model.add_coord("b", range(2), mutable=False)
-        with pytest.raises(ValueError, match="should be constant length immutable dims"):
-            pmx.distributions.R2D2M2CP(
-                "beta0",
-                1,
-                [1, 1],
-                dims="a",
-                r2=0.8,
-                positive_probs=[0.5, 1],
-                positive_probs_std=[0.3, 0],
-            )
-        with pytest.raises(ValueError, match="should be constant length immutable dims"):
-            pmx.distributions.R2D2M2CP(
-                "beta0",
-                1,
-                [1, 1],
-                dims=("a", "b"),
-                r2=0.8,
-                positive_probs=[0.5, 1],
-                positive_probs_std=[0.3, 0],
-            )