Add type hints for default_shape_from_params

aesara/tensor/random/op.py

@@ -26,8 +26,11 @@ from aesara.tensor.var import TensorVariable
 
 
 def default_shape_from_params(
-    ndim_supp, dist_params, rep_param_idx=0, param_shapes=None
-):
+    ndim_supp: int,
+    dist_params: Sequence[Variable],
+    rep_param_idx: Optional[int] = 0,
+    param_shapes: Optional[Sequence[Tuple[ScalarVariable]]] = None,
+) -> Tuple[int, ...]:
     """Infer the dimensions for the output of a `RandomVariable`.
 
     This is a function that derives a random variable's support
@@ -50,14 +53,14 @@ def default_shape_from_params(
         (e.g. a multivariate normal draw is 1D, so `ndim_supp = 1`).
     dist_params: list of `aesara.graph.basic.Variable`
         The distribution parameters.
-    param_shapes: list of tuple of `ScalarVariable` (optional)
-        Symbolic shapes for each distribution parameter.  These will
-        be used in place of distribution parameter-generated shapes.
     rep_param_idx: int (optional)
         The index of the distribution parameter to use as a reference
         In other words, a parameter in `dist_param` with a shape corresponding
         to the support's shape.
         The default is the first parameter (i.e. the value 0).
+    param_shapes: list of tuple of `ScalarVariable` (optional)
+        Symbolic shapes for each distribution parameter.  These will
+        be used in place of distribution parameter-generated shapes.
 
     Results
     -------