Fix random op dependency and lr_shedule bugs for standalone executor (#45265)

* Fix random op depenency and lr_shedule bugs for standalone executor

* Fix CI errors

* Fix CI errors

* Fix CI errors

paddle/fluid/framework/new_executor/interpreter/dependency_builder.cc

@@ -273,20 +273,18 @@ void DependencyBuilder::AddDependencyForCommunicationOp() {
 
 // make sure that the random op is scheduled sequentially
 void DependencyBuilder::AddDependencyForRandomOp() {
-  const std::set<std::string> random_op_set = {
-      "bernoulli",
-      "poisson",
-      "multinomial",
-      "gaussian_random",
-      "truncated_gaussian_random",
-      "uniform_random",
-      "randint",
-      "randperm",
-      "exponential",
-      "sampling_id"
-      "dropout",
-      "class_center_sample",
-  };
+  const std::set<std::string> random_op_set = {"bernoulli",
+                                               "poisson",
+                                               "multinomial",
+                                               "gaussian_random",
+                                               "truncated_gaussian_random",
+                                               "uniform_random",
+                                               "randint",
+                                               "randperm",
+                                               "exponential",
+                                               "sampling_id",
+                                               "dropout",
+                                               "class_center_sample"};
 
   int dependence_op_idx = -1;
   for (size_t op_idx = 0; op_idx < op_num_; ++op_idx) {

python/paddle/fluid/executor.py

@@ -1516,6 +1516,8 @@ class Executor(object):
                         program._compile(scope, self.place)
                         ir_graph = framework.IrGraph(program._graph)
                         inner_program = ir_graph.to_program()
+                        if hasattr(program._program, 'lr_sheduler'):
+                            inner_program.lr_sheduler = program._program.lr_sheduler
                         # print(f"Program after convert:\n {inner_program}", flush=True)
                         logging.warning(
                             "FLAGS_USE_STANDALONE_EXECUTOR and FLAGS_CONVERT_GRAPH_TO_PROGRAM is set to 1. Graph will be converted to Program and executed using new executor."