raise when sampling a multinomial

Author: Rishab87

pymc/distributions/multivariate.py

@@ -619,6 +619,12 @@ def dist(cls, n, p, *args, **kwargs):
         return super().dist([n, p], *args, **kwargs)
 
     def support_point(rv, size, n, p):
+        observed = getattr(rv.tag, "observed", None)
+        if observed is None:
+            raise ValueError(
+                "Latent Multinomial variables are not supported for sampling. "
+                "Use a Categorical variable instead."
+            )
         n = pt.shape_padright(n)
         mean = n * p
         mode = pt.round(mean)

tests/distributions/test_distribution.py

@@ -82,7 +82,14 @@ def test_issue_4499(self):
         with pm.Model(check_bounds=False) as m:
             x = pm.DiracDelta("x", 1, size=10)
         npt.assert_almost_equal(m.compile_logp()({"x": np.ones(10)}), 0 * 10)
-
+    def test_issue_7548(self):
+        #Test for bug in Multinomial, it should raise when trying to sample a Multinomial variable
+        with pm.Model() as model:
+            p = [0.3, 0.4, 0.3]
+            n = 10
+            x = pm.Multinomial("x", n=n, p=p)
+            with pytest.raises(ValueError, match="Latent Multinomial variables are not supported"):
+                pm.sample(draws=100, chains=1)
 
 def test_all_distributions_have_support_points():
     import pymc.distributions as dist_module