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API: Change --batch-size argument to be across all nodes, not one 

Changed the behaviour of main_lincls.py to be consistent with the
behaviour of main_moco.py.
https://github.com/facebookresearch/moco-v3/blob/878544a/main_moco.py#L206
pull/17/head
Scott Lowe 2021-11-24 21:47:12 -04:00
parent 7074f47f0d
commit a29021ab3e
1 changed files with 2 additions and 2 deletions
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main_lincls.py
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@ -53,7 +53,7 @@ parser.add_argument('--start-epoch', default=0, type=int, metavar='N',
parser.add_argument('-b', '--batch-size', default=1024, type=int,
metavar='N',
help='mini-batch size (default: 1024), this is the total '
'batch size of all GPUs on the current node when '
'batch size of all GPUs on all nodes when '
'using Data Parallel or Distributed Data Parallel')
parser.add_argument('--lr', '--learning-rate', default=0.1, type=float,
metavar='LR', help='initial (base) learning rate', dest='lr')
@ -207,7 +207,7 @@ def main_worker(gpu, ngpus_per_node, args):
# When using a single GPU per process and per
# DistributedDataParallel, we need to divide the batch size
# ourselves based on the total number of GPUs we have
args.batch_size = int(args.batch_size / ngpus_per_node)
args.batch_size = int(args.batch_size / args.world_size)
args.workers = int((args.workers + ngpus_per_node - 1) / ngpus_per_node)
model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.gpu])
else: