add ce for PaddleDetection (#4078)

* add ce for PaddleDetection

PaddleCV/PaddleDetection/tools/train.py

@@ -19,6 +19,7 @@ from __future__ import print_function
 import os
 import time
 import numpy as np
+import random
 import datetime
 from collections import deque
 
@@ -62,10 +63,13 @@ def main():
     FLAGS.dist = 'PADDLE_TRAINER_ID' in env and 'PADDLE_TRAINERS_NUM' in env
     if FLAGS.dist:
         trainer_id = int(env['PADDLE_TRAINER_ID'])
-        import random
         local_seed = (99 + trainer_id)
         random.seed(local_seed)
         np.random.seed(local_seed)
+    
+    if FLAGS.enable_ce:
+        random.seed(0)
+        np.random.seed(0)
 
     cfg = load_config(FLAGS.config)
     if 'architecture' in cfg:
@@ -112,6 +116,9 @@ def main():
     # build program
     startup_prog = fluid.Program()
     train_prog = fluid.Program()
+    if FLAGS.enable_ce:
+        startup_prog.random_seed = 1000
+        train_prog.random_seed = 1000
     with fluid.program_guard(train_prog, startup_prog):
         with fluid.unique_name.guard():
             model = create(main_arch)
@@ -258,6 +265,11 @@ def main():
             strs = 'iter: {}, lr: {:.6f}, {}, time: {:.3f}, eta: {}'.format(
                 it, np.mean(outs[-1]), logs, time_cost, eta)
             logger.info(strs)
+        
+        #only for continuous evaluation
+        if FLAGS.enable_ce and it == cfg.max_iters - 1:
+            print("kpis\t{}_train_loss\t{}".format(cfg.architecture, stats['loss']))
+            print("kpis\t{}_train_time\t{}".format(cfg.architecture, time_cost))
 
         # profiler tools, used for benchmark
         if FLAGS.is_profiler and it == 5:
@@ -342,6 +354,12 @@ if __name__ == '__main__':
         type=str,
         default="tb_log_dir/scalar",
         help='Tensorboard logging directory for scalar.')
+    parser.add_argument(
+        '--enable_ce',
+        type=bool,
+        default=False,
+        help="If set True, enable continuous evaluation job."
+        "This flag is only used for internal test.")
 
     #NOTE:args for profiler tools, used for benchmark
     parser.add_argument(