refactor: Use infer_static_shape from pytensor

Author: ferrine

pymc_experimental/model/transforms/autoreparam.py

@@ -21,6 +21,7 @@
 )
 from pymc.pytensorf import toposort_replace
 from pytensor.graph.basic import Apply, Variable
+from pytensor.tensor.basic import infer_static_shape
 from pytensor.tensor.random.op import RandomVariable
 
 _log = logging.getLogger("pmx")
@@ -176,12 +177,9 @@ def vip_reparam_node(
 ) -> Tuple[ModelDeterministic, ModelNamed]:
     if not isinstance(node.op, RandomVariable | SymbolicRandomVariable):
         raise TypeError("Op should be RandomVariable type")
-    _, size, *_ = node.inputs
-    eval_size = size.eval(mode="FAST_COMPILE")
-    if eval_size is not None:
-        rv_shape = tuple(eval_size)
-    else:
-        rv_shape = ()
+    rv = node.default_output()
+    rv_shape_t, _ = infer_static_shape(rv.shape)
+    rv_shape = pt.as_tensor(rv_shape_t).eval(mode="FAST_COMPILE")
     lam_name = f"{name}::lam_logit__"
     _log.debug(f"Creating {lam_name} with shape of {rv_shape}")
     logit_lam_ = pytensor.shared(