Fix PyTorch 2.5 compatibility issues with arg_constraints

funsor/distribution.py

@@ -306,7 +306,10 @@ def _infer_value_domain(cls, **domains):
     @classmethod
     @functools.lru_cache(maxsize=5000)
     def _infer_param_domain(cls, name, raw_shape):
-        support = cls.dist_class.arg_constraints.get(name, None)
+        constraints = getattr(cls.dist_class, "arg_constraints", {})
+        if isinstance(constraints, property):
+            constraints = {}
+        support = constraints.get(name, None)
         # XXX: if the backend does not have the same definition of constraints, we should
         # define backend-specific distributions and overide these `infer_value_domain`,
         # `infer_param_domain` methods.
@@ -326,9 +329,12 @@ def _infer_param_domain(cls, name, raw_shape):
         # resolve the issue: logits's constraints are real (instead of real_vector)
         # for discrete multivariate distributions in Pyro
         elif support_name == "Real":
+            constraints = getattr(cls.dist_class, "arg_constraints", {})
+            if isinstance(constraints, property):
+                constraints = {}
             if name == "logits" and (
-                "probs" in cls.dist_class.arg_constraints
-                and type(cls.dist_class.arg_constraints["probs"]).__name__.lstrip("_")
+                "probs" in constraints
+                and type(constraints.get("probs")).__name__.lstrip("_")
                 == "Simplex"
             ):
                 output = Reals[raw_shape[-1 - event_dim :]]
@@ -374,10 +380,13 @@ def make_dist(
     backend_dist_class, param_names=(), generate_eager=True, generate_to_funsor=True
 ):
     if not param_names:
+        constraints = getattr(backend_dist_class, "arg_constraints", {})
+        if isinstance(constraints, property):
+            constraints = {}
         param_names = tuple(
             name
             for name in inspect.getfullargspec(backend_dist_class.__init__)[0][1:]
-            if name in backend_dist_class.arg_constraints
+            if name in constraints
         )
 
     @makefun.with_signature(
@@ -437,7 +446,7 @@ def dist_init(self, **kwargs):
     ("Pareto", ()),
     ("Poisson", ()),
     ("StudentT", ()),
-    ("Uniform", ()),
+    ("Uniform", ("low", "high")),
     ("VonMises", ()),
 ]
 
@@ -587,7 +596,7 @@ def module(self):
     def __call__(self, cls, args, kwargs):
         # Check whether distribution class takes any tensor inputs.
         arg_constraints = getattr(cls, "arg_constraints", None)
-        if not arg_constraints:
+        if not arg_constraints or isinstance(arg_constraints, property):
             return
 
         # Check whether any tensor inputs are actually funsors.