Merge branch 'xlnet'

examples/lm_finetuning/finetune_on_pregenerated.py

@@ -13,10 +13,10 @@ from torch.utils.data import DataLoader, Dataset, RandomSampler
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm
 
-from pytorch_pretrained_bert import WEIGHTS_NAME, CONFIG_NAME
-from pytorch_pretrained_bert.modeling import BertForPreTraining
-from pytorch_pretrained_bert.tokenization import BertTokenizer
-from pytorch_pretrained_bert.optimization import BertAdam, WarmupLinearSchedule
+from pytorch_transformers import WEIGHTS_NAME, CONFIG_NAME
+from pytorch_transformers.modeling_bert import BertForPreTraining
+from pytorch_transformers.tokenization_bert import BertTokenizer
+from pytorch_transformers.optimization import AdamW, WarmupLinearSchedule
 
 InputFeatures = namedtuple("InputFeatures", "input_ids input_mask segment_ids lm_label_ids is_next")
 
@@ -273,7 +273,7 @@ def main():
         warmup_linear = WarmupLinearSchedule(warmup=args.warmup_proportion,
                                              t_total=num_train_optimization_steps)
     else:
-        optimizer = BertAdam(optimizer_grouped_parameters,
+        optimizer = AdamW(optimizer_grouped_parameters,
                              lr=args.learning_rate,
                              warmup=args.warmup_proportion,
                              t_total=num_train_optimization_steps)

examples/lm_finetuning/pregenerate_training_data.py

@@ -6,7 +6,7 @@ import shelve
 from multiprocessing import Pool
 
 from random import random, randrange, randint, shuffle, choice
-from pytorch_pretrained_bert.tokenization import BertTokenizer
+from pytorch_transformers.tokenization_bert import BertTokenizer
 import numpy as np
 import json
 import collections

examples/lm_finetuning/simple_lm_finetuning.py

@@ -29,10 +29,10 @@ from torch.utils.data import DataLoader, Dataset, RandomSampler
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm, trange
 
-from pytorch_pretrained_bert import WEIGHTS_NAME, CONFIG_NAME
-from pytorch_pretrained_bert.modeling import BertForPreTraining
-from pytorch_pretrained_bert.tokenization import BertTokenizer
-from pytorch_pretrained_bert.optimization import BertAdam, WarmupLinearSchedule
+from pytorch_transformers import WEIGHTS_NAME, CONFIG_NAME
+from pytorch_transformers.modeling_bert import BertForPreTraining
+from pytorch_transformers.tokenization_bert import BertTokenizer
+from pytorch_transformers.optimization import BertAdam, WarmupLinearSchedule
 
 logging.basicConfig(format='%(asctime)s - %(levelname)s - %(name)s -   %(message)s',
                     datefmt='%m/%d/%Y %H:%M:%S',