refactor: added vectorize=True to all jacobians

Author: Michal-Novomestsky

pytensor/tensor/optimize.py

@@ -820,7 +820,7 @@ def __init__(
         self.fgraph = FunctionGraph([variables, *args], [equations])
 
         if jac:
-            jac_wrt_x = jacobian(self.fgraph.outputs[0], self.fgraph.inputs[0])
+            jac_wrt_x = jacobian(self.fgraph.outputs[0], self.fgraph.inputs[0], vectorize=True)
             self.fgraph.add_output(atleast_2d(jac_wrt_x))
 
         self.jac = jac
@@ -900,8 +900,8 @@ def L_op(
         inner_x, *inner_args = self.fgraph.inputs
         inner_fx = self.fgraph.outputs[0]
 
-        df_dx = jacobian(inner_fx, inner_x) if not self.jac else self.fgraph.outputs[1]
-        df_dtheta_columns = jacobian(inner_fx, inner_args, disconnected_inputs="ignore")
+        df_dx = jacobian(inner_fx, inner_x, vectorize=True) if not self.jac else self.fgraph.outputs[1]
+        df_dtheta_columns = jacobian(inner_fx, inner_args, disconnected_inputs="ignore", vectorize=True)
 
         grad_wrt_args = implict_optimization_grads(
             df_dx=df_dx,