update benchmark network.

official/cv/resnet/config/resnet50_imagenet2012_Boost_config.yaml

@@ -23,7 +23,7 @@ batch_size: 256
 loss_scale: 1024
 momentum: 0.85
 weight_decay: 5.0e-5
-epoch_size: 38
+epoch_size: 45 
 pretrain_epoch_size: 0
 save_checkpoint: False
 save_checkpoint_epochs: 5
@@ -33,7 +33,7 @@ lr_decay_mode: "poly"
 use_label_smooth: True
 label_smooth_factor: 0.1
 lr_init: 0
-lr_max: 13.96
+lr_max: 13.01
 lr_end: 0.0
 lars_epsilon: 0.0
 lars_coefficient: 0.001

official/nlp/bert/src/dataset.py

@@ -41,7 +41,7 @@ class BucketDatasetGenerator:
         bucket_size = len(bucket_list)
         self.random_list = np.random.binomial(n=(bucket_size - 1), p=0.5, size=self.__len__())
         self.random_list = (self.random_list + 2) % bucket_size
-        self.random_list = (self.random_list + 1) * bucket_list[0]
+        self.random_list = [bucket_list[i] for i in self.random_list]
         self.iter = 0
 
     def __next__(self):