fixed alignment

megatron/arguments.py

@@ -644,14 +644,18 @@ def _add_biencoder_args(parser):
 
     # network size
     group.add_argument('--ict-head-size', type=int, default=None,
-                       help='Size of block embeddings to be used in ICT and REALM (paper default: 128)')
+                       help='Size of block embeddings to be used in ICT and '
+                        'REALM (paper default: 128)')
     group.add_argument('--projection-dim', type=int, default=0,
-                       help='Size of projection head used in biencoder (paper default: 128)')
+                       help='Size of projection head used in biencoder (paper'
+                        ' default: 128)')
     group.add_argument('--shared-query-context-model', action='store_true',
-                        help='Whether to share the parameters of the query and context models or not')
+                        help='Whether to share the parameters of the query '
+                        'and context models or not')
     group.add_argument('--pool-type', type=str, default='cls-token',
                        choices=['avg', 'cls-token', 'max'],
-                       help='different options are: avg | cls-token | max, default=cls-token')
+                       help='different options are: avg | cls-token | max, '
+                        'default=cls-token')
 
     # checkpointing
     group.add_argument('--ict-load', type=str, default=None,
@@ -670,10 +674,12 @@ def _add_biencoder_args(parser):
                        help='Whether to use one sentence documents in ICT')
 
     # training
-    group.add_argument('--report-topk-accuracies', nargs='+', type=int, default=[],
-                       help="Which top-k accuracies to report (e.g. '1 5 20')")
+    group.add_argument('--report-topk-accuracies', nargs='+', type=int, 
+                        default=[], help="Which top-k accuracies to report '
+                        '(e.g. '1 5 20')")
     group.add_argument('--retriever-score-scaling', action='store_true',
-                       help="Whether to scale retriever scores by inverse square root of hidden size")
+                       help="Whether to scale retriever scores by inverse '
+                        'square root of hidden size")
 
     # faiss index
     group.add_argument('--faiss-use-gpu', action='store_true',

pretrain_ict.py

@@ -34,9 +34,11 @@ from megatron.data.biencoder_dataset_utils import get_ict_batch
 
 def pretrain_ict_model_provider():
     args = get_args()
-    model = biencoder_model_provider(only_context_model=False,
-                                     only_query_model=False,
-                                     shared_query_context_model=args.shared_query_context_model)
+    model = biencoder_model_provider(
+                only_context_model=False,
+                only_query_model=False,
+                shared_query_context_model=args.shared_query_context_model
+                )
     return model
 
 def get_group_world_size_rank():