remove _optimized_guard in dygrahpe_mode (#22143)

* remove _optimized_guard in dygrahpe_mode test=develop

* remove comment code test=develop

* remove list append test=develop

* remove list append test=develop

python/paddle/fluid/optimizer.py

@@ -441,17 +441,12 @@ class Optimizer(object):
             [p[0] for p in parameters_and_grads if p[0].trainable])
         self._create_global_learning_rate()
 
-        optimize_ops = []
         if framework.in_dygraph_mode():
             for param_and_grad in parameters_and_grads:
                 if param_and_grad[1] is None:
                     continue
-                with param_and_grad[0].block.program._optimized_guard(
-                        param_and_grad):
-                    if param_and_grad[0].trainable is True:
-                        optimize_op = self._append_optimize_op(target_block,
-                                                               param_and_grad)
-                        optimize_ops.append(optimize_op)
+                if param_and_grad[0].trainable is True:
+                    self._append_optimize_op(target_block, param_and_grad)
         else:
             for param_and_grad in parameters_and_grads:
                 if param_and_grad[1] is None:
@@ -459,9 +454,7 @@ class Optimizer(object):
                 with param_and_grad[0].block.program._optimized_guard(
                         param_and_grad), name_scope("optimizer"):
                     if param_and_grad[0].trainable is True:
-                        optimize_op = self._append_optimize_op(target_block,
-                                                               param_and_grad)
-                        optimize_ops.append(optimize_op)
+                        self._append_optimize_op(target_block, param_and_grad)
 
         # Get custom finish ops for subclasses
         # FIXME: Need to fix this once we figure out how to handle dependencies