make examples work without apex

examples/run_classifier.py

@@ -36,13 +36,6 @@ from pytorch_pretrained_bert.modeling import BertForSequenceClassification
 from pytorch_pretrained_bert.optimization import BertAdam
 from pytorch_pretrained_bert.file_utils import PYTORCH_PRETRAINED_BERT_CACHE
 
-try:
-    from apex.optimizers import FP16_Optimizer
-    from apex.optimizers import FusedAdam
-    from apex.parallel import DistributedDataParallel as DDP
-except ImportError:
-    raise ImportError("Please install apex from https://www.github.com/nvidia/apex to run this.")
-
 logging.basicConfig(format = '%(asctime)s - %(levelname)s - %(name)s -   %(message)s',
                     datefmt = '%m/%d/%Y %H:%M:%S',
                     level = logging.INFO)
@@ -467,6 +460,11 @@ def main():
         model.half()
     model.to(device)
     if args.local_rank != -1:
+        try:
+            from apex.parallel import DistributedDataParallel as DDP
+        except ImportError:
+            raise ImportError("Please install apex from https://www.github.com/nvidia/apex to use distributed and fp16 training.")
+
         model = DDP(model)
     elif n_gpu > 1:
         model = torch.nn.DataParallel(model)
@@ -482,6 +480,12 @@ def main():
     if args.local_rank != -1:
         t_total = t_total // torch.distributed.get_world_size()
     if args.fp16:
+        try:
+            from apex.optimizers import FP16_Optimizer
+            from apex.optimizers import FusedAdam
+        except ImportError:
+            raise ImportError("Please install apex from https://www.github.com/nvidia/apex to use distributed and fp16 training.")
+
         optimizer = FusedAdam(optimizer_grouped_parameters,
                               lr=args.learning_rate,
                               bias_correction=False,

examples/run_squad.py

@@ -39,13 +39,6 @@ from pytorch_pretrained_bert.modeling import BertForQuestionAnswering
 from pytorch_pretrained_bert.optimization import BertAdam
 from pytorch_pretrained_bert.file_utils import PYTORCH_PRETRAINED_BERT_CACHE
 
-try:
-    from apex.optimizers import FP16_Optimizer
-    from apex.optimizers import FusedAdam
-    from apex.parallel import DistributedDataParallel as DDP
-except ImportError:
-    raise ImportError("Please install apex from https://www.github.com/nvidia/apex to run this.")
-
 logging.basicConfig(format = '%(asctime)s - %(levelname)s - %(name)s -   %(message)s',
                     datefmt = '%m/%d/%Y %H:%M:%S',
                     level = logging.INFO)
@@ -813,6 +806,11 @@ def main():
         model.half()
     model.to(device)
     if args.local_rank != -1:
+        try:
+            from apex.parallel import DistributedDataParallel as DDP
+        except ImportError:
+            raise ImportError("Please install apex from https://www.github.com/nvidia/apex to use distributed and fp16 training.")
+
         model = DDP(model)
     elif n_gpu > 1:
         model = torch.nn.DataParallel(model)
@@ -834,6 +832,12 @@ def main():
     if args.local_rank != -1:
         t_total = t_total // torch.distributed.get_world_size()
     if args.fp16:
+        try:
+            from apex.optimizers import FP16_Optimizer
+            from apex.optimizers import FusedAdam
+        except ImportError:
+            raise ImportError("Please install apex from https://www.github.com/nvidia/apex to use distributed and fp16 training.")
+
         optimizer = FusedAdam(optimizer_grouped_parameters,
                               lr=args.learning_rate,
                               bias_correction=False,