refactor: jacobian should use tensorize

Michal-Novomestsky · jessegrabowski · commit d31af6e8aa84 · 2025-09-20T13:21:31.000-04:00
diff --git a/pytensor/tensor/optimize.py b/pytensor/tensor/optimize.py
@@ -561,7 +561,7 @@ def L_op(self, inputs, outputs, output_grads):
         implicit_f = grad(inner_fx, inner_x)
 
         df_dx, *df_dtheta_columns = jacobian(
-            implicit_f, [inner_x, *inner_args], disconnected_inputs="ignore"
+            implicit_f, [inner_x, *inner_args], disconnected_inputs="ignore", vectorize=True
         )
         grad_wrt_args = implict_optimization_grads(
             df_dx=df_dx,

Original file line number	Diff line number	Diff line change
`@@ -561,7 +561,7 @@ def L_op(self, inputs, outputs, output_grads):`
`561`	`561`	`implicit_f = grad(inner_fx, inner_x)`
`562`	`562`
`563`	`563`	`df_dx, *df_dtheta_columns = jacobian(`
`564`		`- implicit_f, [inner_x, *inner_args], disconnected_inputs="ignore"`
	`564`	`+ implicit_f, [inner_x, *inner_args], disconnected_inputs="ignore", vectorize=True`
`565`	`565`	`)`
`566`	`566`	`grad_wrt_args = implict_optimization_grads(`
`567`	`567`	`df_dx=df_dx,`