fix train.py

ppcls/utils/logger.py

@@ -23,7 +23,7 @@ logging.basicConfig(
 
 
 def time_zone(sec, fmt):
-    real_time = datetime.datetime.now() + datetime.timedelta(hours=8)
+    real_time = datetime.datetime.now()
     return real_time.timetuple()
 
 

tools/train.py

@@ -13,12 +13,13 @@
 # limitations under the License.
 
 from __future__ import absolute_import
-import program
-from ppcls.utils import logger
-from ppcls.utils.save_load import init_model, save_model
-from ppcls.utils.config import get_config
+from paddle.distributed import ParallelEnv
+import paddle
 from ppcls.data import Reader
-import paddle.fluid as fluid
+from ppcls.utils.config import get_config
+from ppcls.utils.save_load import init_model, save_model
+from ppcls.utils import logger
+import program
 from __future__ import division
 from __future__ import print_function
 
@@ -53,23 +54,24 @@ def main(args):
     # assign the place
     use_gpu = config.get("use_gpu", True)
     if use_gpu:
-        gpu_id = fluid.dygraph.ParallelEnv().dev_id
-        place = fluid.CUDAPlace(gpu_id)
+        gpu_id = ParallelEnv().dev_id
+        place = paddle.CUDAPlace(gpu_id)
     else:
-        place = fluid.CPUPlace()
+        place = paddle.CPUPlace()
 
     use_data_parallel = int(os.getenv("PADDLE_TRAINERS_NUM", 1)) != 1
     config["use_data_parallel"] = use_data_parallel
 
-    with fluid.dygraph.guard(place):
+    paddle.disable_static(place)
+
     net = program.create_model(config.ARCHITECTURE, config.classes_num)
 
     optimizer = program.create_optimizer(
         config, parameter_list=net.parameters())
 
     if config["use_data_parallel"]:
-            strategy = fluid.dygraph.parallel.prepare_context()
-            net = fluid.dygraph.parallel.DataParallel(net, strategy)
+        strategy = paddle.distributed.init_parallel_env()
+        net = paddle.DataParallel(net, strategy)
 
     # load model from checkpoint or pretrained model
     init_model(config, net, optimizer)
@@ -90,8 +92,7 @@ def main(args):
         program.run(train_dataloader, config, net, optimizer, epoch_id,
                     'train')
 
-            if not config["use_data_parallel"] or fluid.dygraph.parallel.Env(
-            ).local_rank == 0:
+        if not config["use_data_parallel"] or ParallelEnv().local_rank == 0:
             # 2. validate with validate dataset
             if config.validate and epoch_id % config.valid_interval == 0:
                 net.eval()
@@ -101,15 +102,12 @@ def main(args):
                     best_top1_acc = top1_acc
                     message = "The best top1 acc {:.5f}, in epoch: {:d}".format(
                         best_top1_acc, epoch_id)
-                        logger.info("{:s}".format(
-                            logger.coloring(message, "RED")))
+                    logger.info("{:s}".format(logger.coloring(message, "RED")))
                     if epoch_id % config.save_interval == 0:
 
-                            model_path = os.path.join(
-                                config.model_save_dir,
+                        model_path = os.path.join(config.model_save_dir,
                                                   config.ARCHITECTURE["name"])
-                            save_model(net, optimizer, model_path,
-                                       "best_model")
+                        save_model(net, optimizer, model_path, "best_model")
 
             # 3. save the persistable model
             if epoch_id % config.save_interval == 0: