migrate BERTFinetune to AdamWeightDecay

demo/ernie-classification/README.md

@@ -95,7 +95,7 @@ with fluid.program_guard(program): # NOTE: 必须使用fluid.program_guard接口
 ### Step4：选择优化策略并开始Finetune
 
 ```python
-strategy = hub.BERTFinetuneStrategy(
+strategy = hub.AdamWeightDecayStrategy(
     weight_decay=0.01,
     learning_rate=5e-5,
     warmup_strategy="linear_warmup_decay",

demo/ernie-classification/ernie_tiny_demo.py

@@ -21,7 +21,7 @@ with fluid.program_guard(program):
         feature=pooled_output, label=label, num_classes=reader.get_num_labels())
 
 # Step4
-strategy = hub.BERTFinetuneStrategy(
+strategy = hub.AdamWeightDecayStrategy(
     learning_rate=5e-5,
     warmup_proportion=0.1,
     warmup_strategy="linear_warmup_decay",

demo/ernie-classification/question_answering.py

@@ -62,7 +62,7 @@ if __name__ == '__main__':
             pooled_output, label, num_classes=num_labels)
 
         # Step4: Select finetune strategy, setup config and finetune
-        strategy = hub.BERTFinetuneStrategy(
+        strategy = hub.AdamWeightDecayStrategy(
             weight_decay=args.weight_decay,
             learning_rate=args.learning_rate,
             warmup_strategy="linear_warmup_decay",

demo/ernie-classification/question_matching.py

@@ -62,7 +62,7 @@ if __name__ == '__main__':
             pooled_output, label, num_classes=num_labels)
 
         # Step4: Select finetune strategy, setup config and finetune
-        strategy = hub.BERTFinetuneStrategy(
+        strategy = hub.AdamWeightDecayStrategy(
             weight_decay=args.weight_decay,
             learning_rate=args.learning_rate,
             warmup_strategy="linear_warmup_decay",

demo/ernie-classification/sentiment_cls.py

@@ -61,7 +61,7 @@ if __name__ == '__main__':
             pooled_output, label, num_classes=reader.get_num_labels())
 
         # Step4: Select finetune strategy, setup config and finetune
-        strategy = hub.BERTFinetuneStrategy(
+        strategy = hub.AdamWeightDecayStrategy(
             weight_decay=args.weight_decay,
             learning_rate=args.learning_rate,
             warmup_strategy="linear_warmup_decay",

demo/ernie-seq-labeling/sequence_labeling.py

@@ -69,7 +69,7 @@ if __name__ == '__main__':
             num_classes=num_labels)
 
         # Select a finetune strategy
-        strategy = hub.BERTFinetuneStrategy(
+        strategy = hub.AdamWeightDecayStrategy(
             weight_decay=args.weight_decay,
             learning_rate=args.learning_rate,
             warmup_strategy="linear_warmup_decay",

paddlehub/__init__.py

@@ -39,5 +39,5 @@ from .finetune.task import create_text_classification_task
 from .finetune.task import create_img_classification_task
 from .finetune.finetune import finetune_and_eval
 from .finetune.config import RunConfig
-from .finetune.strategy import BERTFinetuneStrategy
+from .finetune.strategy import AdamWeightDecayStrategy
 from .finetune.strategy import DefaultStrategy

paddlehub/finetune/finetune.py

@@ -25,7 +25,7 @@ import numpy as np
 from visualdl import LogWriter
 
 from paddlehub.common.logger import logger
-from paddlehub.finetune.strategy import BERTFinetuneStrategy, DefaultStrategy
+from paddlehub.finetune.strategy import AdamWeightDecayStrategy, DefaultStrategy
 from paddlehub.finetune.checkpoint import load_checkpoint, save_checkpoint
 from paddlehub.finetune.evaluate import evaluate_cls_task, evaluate_seq_labeling_task
 import paddlehub as hub
@@ -74,7 +74,7 @@ def _finetune_seq_label_task(task,
         data_feeder = fluid.DataFeeder(feed_list=feed_list, place=place)
 
         # Select strategy
-        if isinstance(config.strategy, hub.BERTFinetuneStrategy):
+        if isinstance(config.strategy, hub.AdamWeightDecayStrategy):
             scheduled_lr = config.strategy.execute(loss, main_program,
                                                    data_reader, config)
         elif isinstance(config.strategy, hub.DefaultStrategy):
@@ -173,7 +173,7 @@ def _finetune_cls_task(task, data_reader, feed_list, config=None,
         data_feeder = fluid.DataFeeder(feed_list=feed_list, place=place)
 
         # select strategy
-        if isinstance(config.strategy, hub.BERTFinetuneStrategy):
+        if isinstance(config.strategy, hub.AdamWeightDecayStrategy):
             scheduled_lr = config.strategy.execute(loss, main_program,
                                                    data_reader, config)
         elif isinstance(config.strategy, hub.DefaultStrategy):

paddlehub/finetune/strategy.py

@@ -61,7 +61,7 @@ class DefaultStrategy(object):
         return "DefaultStrategy"
 
 
-class BERTFinetuneStrategy(DefaultStrategy):
+class AdamWeightDecayStrategy(DefaultStrategy):
     def __init__(self,
                  learning_rate=1e-4,
                  warmup_strategy="linear_warmup_decay",
@@ -114,7 +114,7 @@ class BERTFinetuneStrategy(DefaultStrategy):
 
     # TODO complete __str__()
     def __str__(self):
-        return "BERTFintuneStrategy"
+        return "AdamWeightDecayStrategy"
 
 
 class DefaultFinetuneStrategy(DefaultStrategy):