Add maxiter and profiler for padding models (#3947)

* add profiler and max_iter for paddingrnn

* add profiler for paddingrnn

PaddleNLP/language_model/args.py

@@ -80,5 +80,8 @@ def parse_args():
     parser.add_argument('--enable_ce', action='store_true')
     parser.add_argument('--batch_size', type=int, default=0, help='batch size')
     parser.add_argument('--max_epoch', type=int, default=0, help='max epoch')
+    
+    # NOTE: args for profiler, used for benchmark
+    parser.add_argument('--profiler_path', type=str, default='/tmp/paddingrnn.profile', help='the profiler output file path. used for benchmark')
     args = parser.parse_args()
     return args

PaddleNLP/language_model/train.py

@@ -25,6 +25,7 @@ import contextlib
 from distutils.dir_util import mkpath
 import paddle
 import paddle.fluid as fluid
+from paddle.fluid import profiler
 import paddle.fluid.framework as framework
 import paddle.fluid.profiler as profiler
 from paddle.fluid.executor import Executor
@@ -50,9 +51,9 @@ SEED = 123
 
 
 @contextlib.contextmanager
-def profile_context(profile=True):
+def profile_context(profile=True, profiler_path='/tmp/paddingrnn.profile'):
     if profile:
-        with profiler.profiler('All', 'total', '/tmp/paddingrnn.profile'):
+        with profiler.profiler('All', 'total', profiler_path):
             yield
     else:
         yield
@@ -318,6 +319,12 @@ def main():
                 print(
                     "-- Epoch:[%d]; Batch:[%d]; Time: %.5f s; ppl: %.5f, lr: %.5f"
                     % (epoch_id, batch_id, batch_time, ppl[0], lr[0]))
+            
+            # profiler tools for benchmark
+            if args.profile and batch_id == log_interval:
+                profiler.reset_profiler()
+            elif args.profile and batch_id == (log_interval + 5):
+                break
         ppl = np.exp(total_loss / iters)
         return ppl
 
@@ -371,6 +378,11 @@ def main():
                         % (epoch_id, batch_id, batch_time, ppl[0], lr[0]))
 
                 batch_id += 1
+                # profiler tools for benchmark
+                if args.profile and batch_id == log_interval:
+                    profiler.reset_profiler()
+                elif args.profile and batch_id == (log_interval + 5):
+                    break
         except fluid.core.EOFException:
             dataloader.reset()
 
@@ -455,7 +467,7 @@ def main():
             fluid.save(main_program, save_model_dir)
             print("Saved model to: %s.\n" % save_model_dir)
 
-    with profile_context(args.profile):
+    with profile_context(args.profile, args.profiler_path):
         train()
 
     test_ppl = eval(test_data)