rm dependency on .git; multi-gpu WIP; fine-grained time

arguments.py

@@ -71,9 +71,10 @@ def parse():
     parser.add_argument('--resume', action='store_true', help='whether to resume training with past optimizers')
 
     parser.add_argument('--seed', default=123, type=int, help='Random seed.')
-    parser.add_argument('--gpus', nargs='+', type=int, help='gpus to use')
+    parser.add_argument('--gpus', nargs='+', type=int, help='a list of gpus that can be used for training (multi-gpu currently WIP)')
     parser.add_argument('--backend', default='gloo', type=str, help='backend for distributed training')
 
+    parser.add_argument('--no_commit', action='store_false', dest='commit', help='do not track the git commit associated with this training run') 
     parser.add_argument('--exist_ok', action='store_true', help='Ok if the save directory already exists, i.e. overwrite is ok') 
     parser.add_argument('--token_testing', action='store_true', help='if true, sorts all iterators') 
     parser.add_argument('--reverse', action='store_true', help='if token_testing and true, sorts all iterators in reverse') 
@@ -86,7 +87,10 @@ def parse():
     if 'imdb' in args.val_tasks:
         args.val_tasks.remove('imdb')
     args.world_size = len(args.gpus) if args.gpus[0] > -1 else -1
-    args.timestamp = '-'.join(datetime.datetime.now(tz=tz.tzoffset(None, -8*60*60)).strftime("%y/%m/%d/%H/%M").split())
+    if args.world_size > 1:
+        print('multi-gpu training is currently a work in progress')
+        return
+    args.timestamp = '-'.join(datetime.datetime.now(tz=tz.tzoffset(None, -8*60*60)).strftime("%y/%m/%d/%H/%M/%S.%f").split())
 
     if len(args.train_tasks) > 1:
         if args.train_iterations is  None:
@@ -99,7 +103,10 @@ def parse():
         args.val_batch_size = len(args.val_tasks) * args.val_batch_size
         
     # postprocess arguments
-    args.commit = get_commit()
+    if args.commit:
+        args.commit = get_commit()
+    else:
+        args.commit = ''
     train_out = f'{",".join(args.train_tasks)}'
     if len(args.train_tasks) > 1:
         train_out += f'{"-".join([str(x) for x in args.train_iterations])}'

train.py

@@ -336,8 +336,10 @@ def init_opt(args, model):
     return opt
 
 
-if __name__ == '__main__':
+def main():
     args = arguments.parse()
+    if args is None:
+        return
     set_seed(args)
     logger = initialize_logger(args)
     logger.info(f'Arguments:\n{pformat(vars(args))}')
@@ -357,3 +359,8 @@ if __name__ == '__main__':
     else:
         logger.info(f'Processing')
         run(args, run_args, world_size=args.world_size)
+
+
+if __name__ == '__main__':
+    main()
+