update according comments

ppcls/engine/engine.py

@@ -13,21 +13,13 @@
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
-import os
-import sys
-import numpy as np
-
-__dir__ = os.path.dirname(os.path.abspath(__file__))
-sys.path.append(os.path.abspath(os.path.join(__dir__, '../../')))
 
-import time
+import os
 import platform
-import datetime
-import argparse
 import paddle
-import paddle.nn as nn
 import paddle.distributed as dist
 from visualdl import LogWriter
+from paddle import nn
 
 from ppcls.utils.check import check_gpu
 from ppcls.utils.misc import AverageMeter
@@ -67,7 +59,8 @@ class Engine(object):
         print_config(config)
 
         # init train_func and eval_func
-        assert self.eval_mode in ["classification", "retrieval"], logger.error("Invalid eval mode: {}".format(self.eval_mode))
+        assert self.eval_mode in ["classification", "retrieval"], logger.error(
+            "Invalid eval mode: {}".format(self.eval_mode))
         self.train_epoch_func = train_epoch
         self.eval_func = getattr(evaluation, self.eval_mode + "_eval")
 

ppcls/engine/evaluation/classification.py

@@ -14,14 +14,10 @@
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
-import os
-import sys
 import time
 import platform
 import paddle
 
-__dir__ = os.path.dirname(os.path.abspath(__file__))
-sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
 from ppcls.utils.misc import AverageMeter
 from ppcls.utils import logger
 
@@ -61,14 +57,14 @@ def classification_eval(evaler, epoch_id=0):
         out = evaler.model(batch[0])
         # calc loss
         if evaler.eval_loss_func is not None:
-            loss_dict = evaler.eval_loss_func(out, batch[-1])
+            loss_dict = evaler.eval_loss_func(out, batch[1])
             for key in loss_dict:
                 if key not in output_info:
                     output_info[key] = AverageMeter(key, '7.5f')
                 output_info[key].update(loss_dict[key].numpy()[0], batch_size)
         # calc metric
         if evaler.eval_metric_func is not None:
-            metric_dict = evaler.eval_metric_func(out, batch[-1])
+            metric_dict = evaler.eval_metric_func(out, batch[1])
             if paddle.distributed.get_world_size() > 1:
                 for key in metric_dict:
                     paddle.distributed.all_reduce(

ppcls/engine/evaluation/retrieval.py

@@ -14,15 +14,9 @@
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
-import os
-import sys
-import time
+
 import platform
 import paddle
-
-__dir__ = os.path.dirname(os.path.abspath(__file__))
-sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
-from ppcls.utils.misc import AverageMeter
 from ppcls.utils import logger
 
 

ppcls/engine/train/train.py

@@ -13,19 +13,8 @@
 # limitations under the License.
 from __future__ import absolute_import, division, print_function
 
-import datetime
-import os
-import platform
-import sys
 import time
-
-import numpy as np
 import paddle
-
-__dir__ = os.path.dirname(os.path.abspath(__file__))
-sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
-from ppcls.utils import logger
-from ppcls.utils.misc import AverageMeter
 from ppcls.engine.train.utils import update_loss, update_metric, log_info
 
 
@@ -88,6 +77,7 @@ def train_epoch(trainer, epoch_id, print_batch_step):
             log_info(trainer, batch_size, epoch_id, iter_id)
         tic = time.time()
 
+
 def forward(trainer, batch):
     if trainer.eval_mode == "classification":
         return trainer.model(batch[0])

ppcls/engine/train/utils.py

@@ -14,16 +14,6 @@
 from __future__ import absolute_import, division, print_function
 
 import datetime
-import os
-import platform
-import sys
-import time
-
-import numpy as np
-import paddle
-
-__dir__ = os.path.dirname(os.path.abspath(__file__))
-sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
 from ppcls.utils import logger
 from ppcls.utils.misc import AverageMeter