Cosmetic improvements to dynamic broadcast checks

pytensor/tensor/extra_ops.py

@@ -1434,6 +1434,13 @@ def ravel_multi_index(multi_index, dims, mode="raise", order="C"):
     return RavelMultiIndex(mode=mode, order=order)(*args)
 
 
+_broadcast_assert = Assert(
+    "Could not broadcast dimensions. Broadcasting is only allowed along "
+    "axes that have a statically known length 1. Use `specify_shape` to "
+    "inform PyTensor of a known shape."
+)
+
+
 def broadcast_shape(*arrays, **kwargs) -> Tuple[aes.ScalarVariable, ...]:
     """Compute the shape resulting from broadcasting arrays.
 
@@ -1510,20 +1517,19 @@ def broadcast_shape_iter(
     for dim_shapes in zip(*array_shapes):
         # Get the shapes in this dimension that are not broadcastable
         # (i.e. not symbolically known to be broadcastable)
-        maybe_non_bcast_shapes = [shape for shape in dim_shapes if shape != one_at]
+        non_bcast_shapes = [shape for shape in dim_shapes if shape != one_at]
 
-        if len(maybe_non_bcast_shapes) == 0:
+        if len(non_bcast_shapes) == 0:
             # Every shape was broadcastable in this dimension
             result_dims.append(one_at)
-        elif len(maybe_non_bcast_shapes) == 1:
+        elif len(non_bcast_shapes) == 1:
             # Only one shape might not be broadcastable in this dimension
-            result_dims.extend(maybe_non_bcast_shapes)
+            result_dims.extend(non_bcast_shapes)
         else:
             # More than one shape might not be broadcastable in this dimension
-
             nonconst_nb_shapes: Set[int] = set()
             const_nb_shapes: Set[Variable] = set()
-            for shape in maybe_non_bcast_shapes:
+            for shape in non_bcast_shapes:
                 if isinstance(shape, Constant):
                     const_nb_shapes.add(shape.value.item())
                 else:
@@ -1534,7 +1540,6 @@ def broadcast_shape_iter(
                     f"Could not broadcast dimensions. Incompatible shapes were {array_shapes}."
                 )
 
-            assert_op = Assert("Could not dynamically broadcast dimensions.")
             if len(const_nb_shapes) == 1:
                 (first_length,) = const_nb_shapes
                 other_lengths = nonconst_nb_shapes
@@ -1547,23 +1552,8 @@ def broadcast_shape_iter(
                 continue
 
             # Add assert that all remaining shapes are equal
-            use_scalars = False
-            if use_scalars:
-                condition = None
-                for other in other_lengths:
-                    cond = aes.eq(first_length, other)
-                    if condition is None:
-                        condition = cond
-                    else:
-                        condition = aes.and_(condition, cond)
-            else:
-                condition = pt_all(
-                    [pt_eq(first_length, other) for other in other_lengths]
-                )
-            if condition is None:
-                result_dims.append(first_length)
-            else:
-                result_dims.append(assert_op(first_length, condition))
+            condition = pt_all([pt_eq(first_length, other) for other in other_lengths])
+            result_dims.append(_broadcast_assert(first_length, condition))
 
     return tuple(result_dims)