delete new executor log (#45917)

paddle/fluid/framework/new_executor/interpretercore_util.cc

@@ -418,7 +418,6 @@ void build_op_func_list(const platform::Place& place,
                                        : var_scope->GetMutableScope();
   std::vector<std::unique_ptr<OperatorBase>>
       ops_unique;  // its elements will be moved to vec_func_list
-  bool flag_log_is_printed = false;
   // Step 1: create all ops for current block.
   create_all_ops(block, &ops_unique);
 
@@ -449,13 +448,6 @@ void build_op_func_list(const platform::Place& place,
 
     VLOG(6) << "Build OpFuncNode from : " << op_type;
 
-    // Print new executor log if grad op is used.
-    // It's only for test and will be removed later.
-    if (!flag_log_is_printed && op_type.find("_grad") != std::string::npos) {
-      VLOG(0) << "Standalone Executor is Used.";
-      flag_log_is_printed = true;
-    }
-
     // Hot fix for variables used in dataloader, like
     // 'lod_tensor_blocking_queue_0'. These variables may be created in scope,
     // and it is not existed as variable in program.

python/paddle/fluid/executor.py

@@ -771,9 +771,6 @@ class _ExecutorCache(object):
 
             inner_program = converted_program
             # print(f"Program after convert:\n {inner_program}", flush=True)
-            warnings.warn(
-                "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."
-            )
         else:
             build_strategy = None
             from paddle.incubate.autograd import prim_enabled, prim2orig
@@ -789,9 +786,16 @@ class _ExecutorCache(object):
                                       fetch_var_name=fetch_var_name,
                                       use_fetch_v2=True)
 
-        # If there are multiple blocks in the program, subblock will not be executed with the new executor in temporary
+        if os.environ.get('FLAGS_CONVERT_GRAPH_TO_PROGRAM', None) in [
+                1, '1', True, 'True', 'true'
+        ] and not program._is_start_up_program_:
             if program.num_blocks > 1:
-            warnings.warn("There are more than 1 block in program.")
+                # If there are multiple blocks in the program, subblock will not be executed with the new executor in temporary
+                logging.warning("There are more than 1 block in program.")
+            elif program.num_blocks == 1:
+                logging.warning("There are 1 block in program.")
+            else:
+                logging.warning("There are no block in program.")
 
         # standalone executor will apply buffer_shared_inplace_pass and
         # inplace_addto_op_pass to program according to build_strategy
@@ -1654,10 +1658,6 @@ class Executor(object):
                 else:
                     tensor._copy_from(cpu_tensor, self.place)
 
-            warnings.warn(
-                "FLAGS_USE_STANDALONE_EXECUTOR is set to 1. New executor is used to execute Program."
-            )
-
             return new_exe.run(scope, list(feed.keys()), fetch_list,
                                return_numpy)