Related lr_scheduler to gradient batch accumulation

Fixed updates_per_epoch in training script

train.py

@@ -325,7 +325,7 @@ group.add_argument('--amp-dtype', default='float16', type=str,
                     help='lower precision AMP dtype (default: float16)')
 group.add_argument('--amp-impl', default='native', type=str,
                     help='AMP impl to use, "native" or "apex" (default: native)')
-group.add_argument('--iters_to_accumulate', default='1', type=int,
+group.add_argument('--iters-to-accumulate', default='1', type=int,
                    help='number of batches evaluated before performing an optimizer step. Used for Gradient accumulation')
 group.add_argument('--no-ddp-bb', action='store_true', default=False,
                     help='Force broadcast buffers for native DDP to off.')
@@ -715,7 +715,7 @@ def main():
             f.write(args_text)
 
     # setup learning rate schedule and starting epoch
-    updates_per_epoch = len(loader_train)
+    updates_per_epoch = len(loader_train) // args.iters_to_accumulate
     lr_scheduler, num_epochs = create_scheduler_v2(
         optimizer,
         **scheduler_kwargs(args),