Rename `*shape_from_params` to `*supp_shape_from_params` for clarity

aesara/tensor/random/basic.py

@@ -6,7 +6,7 @@ import scipy.stats as stats
 
 import aesara
 from aesara.tensor.basic import as_tensor_variable
-from aesara.tensor.random.op import RandomVariable, default_shape_from_params
+from aesara.tensor.random.op import RandomVariable, default_supp_shape_from_params
 from aesara.tensor.random.type import RandomGeneratorType, RandomStateType
 from aesara.tensor.random.utils import broadcast_params
 from aesara.tensor.random.var import (
@@ -591,8 +591,8 @@ class MultinomialRV(RandomVariable):
     dtype = "int64"
     _print_name = ("MN", "\\operatorname{MN}")
 
-    def _shape_from_params(self, dist_params, rep_param_idx=1, param_shapes=None):
-        return default_shape_from_params(
+    def _supp_shape_from_params(self, dist_params, rep_param_idx=1, param_shapes=None):
+        return default_supp_shape_from_params(
             self.ndim_supp, dist_params, rep_param_idx, param_shapes
         )
 
@@ -713,7 +713,7 @@ class ChoiceRV(RandomVariable):
     def rng_fn(cls, rng, a, p, replace, size):
         return rng.choice(a, size, replace, p)
 
-    def _shape_from_params(self, *args, **kwargs):
+    def _supp_shape_from_params(self, *args, **kwargs):
         raise NotImplementedError()
 
     def _infer_shape(self, size, dist_params, param_shapes=None):

aesara/tensor/random/op.py

@@ -24,7 +24,7 @@ from aesara.tensor.type_other import NoneConst
 from aesara.tensor.var import TensorVariable
 
 
-def default_shape_from_params(
+def default_supp_shape_from_params(
     ndim_supp: int,
     dist_params: Sequence[Variable],
     rep_param_idx: Optional[int] = 0,
@@ -151,14 +151,15 @@ class RandomVariable(Op):
         if self.inplace:
             self.destroy_map = {0: [0]}
 
-    def _shape_from_params(self, dist_params, **kwargs):
-        """Determine the shape of a `RandomVariable`'s output given its parameters.
+    def _supp_shape_from_params(self, dist_params, **kwargs):
+        """Determine the support shape of a `RandomVariable`'s output given its parameters.
 
-        This does *not* consider the extra dimensions added by the `size` parameter.
+        This does *not* consider the extra dimensions added by the `size` parameter
+        or independent (batched) parameters.
 
         Defaults to `param_supp_shape_fn`.
         """
-        return default_shape_from_params(self.ndim_supp, dist_params, **kwargs)
+        return default_supp_shape_from_params(self.ndim_supp, dist_params, **kwargs)
 
     def rng_fn(self, rng, *args, **kwargs):
         """Sample a numeric random variate."""
@@ -196,7 +197,7 @@ class RandomVariable(Op):
             if self.ndim_supp == 0:
                 return size
             else:
-                supp_shape = self._shape_from_params(
+                supp_shape = self._supp_shape_from_params(
                     dist_params, param_shapes=param_shapes
                 )
                 return tuple(size) + tuple(supp_shape)
@@ -256,7 +257,7 @@ class RandomVariable(Op):
 
             ndim_reps = len(shape_reps)
         else:
-            shape_supp = self._shape_from_params(
+            shape_supp = self._supp_shape_from_params(
                 dist_params,
                 param_shapes=param_shapes,
             )

tests/tensor/random/test_basic.py

@@ -1227,7 +1227,7 @@ def test_integers_samples():
 
 def test_choice_samples():
     with pytest.raises(NotImplementedError):
-        choice._shape_from_params(np.asarray(5))
+        choice._supp_shape_from_params(np.asarray(5))
 
     rv_numpy_tester(choice, np.asarray([5]))
     rv_numpy_tester(choice, np.array([1.0, 5.0], dtype=config.floatX))

tests/tensor/random/test_op.py

@@ -10,7 +10,7 @@ from aesara.tensor.random.op import (
     RandomState,
     RandomVariable,
     default_rng,
-    default_shape_from_params,
+    default_supp_shape_from_params,
 )
 from aesara.tensor.shape import specify_shape
 from aesara.tensor.type import all_dtypes, iscalar, tensor
@@ -22,20 +22,24 @@ def set_aesara_flags():
         yield
 
 
-def test_default_shape_from_params():
+def test_default_supp_shape_from_params():
     with pytest.raises(ValueError, match="^ndim_supp*"):
-        default_shape_from_params(0, (np.array([1, 2]), 0))
+        default_supp_shape_from_params(0, (np.array([1, 2]), 0))
 
-    res = default_shape_from_params(1, (np.array([1, 2]), np.eye(2)), rep_param_idx=0)
+    res = default_supp_shape_from_params(
+        1, (np.array([1, 2]), np.eye(2)), rep_param_idx=0
+    )
     assert res == (2,)
 
-    res = default_shape_from_params(1, (np.array([1, 2]), 0), param_shapes=((2,), ()))
+    res = default_supp_shape_from_params(
+        1, (np.array([1, 2]), 0), param_shapes=((2,), ())
+    )
     assert res == (2,)
 
     with pytest.raises(ValueError, match="^Reference parameter*"):
-        default_shape_from_params(1, (np.array(1),), rep_param_idx=0)
+        default_supp_shape_from_params(1, (np.array(1),), rep_param_idx=0)
 
-    res = default_shape_from_params(
+    res = default_supp_shape_from_params(
         2, (np.array([1, 2]), np.ones((2, 3, 4))), rep_param_idx=1
     )
     assert res == (3, 4)