Add auto layout to classification, detection and segmentation scripts

Signed-off-by: Serge Panev <spanev@nvidia.com>

Author: Kh4L

scripts/classification/imagenet/train_imagenet.py

@@ -108,6 +108,8 @@ def parse_args():
                         help='whether to use group norm.')
     parser.add_argument('--amp', action='store_true',
                     help='Use MXNet AMP for mixed precision training.')
+    parser.add_argument('--auto-layout', action='store_true',
+                        help='Add layout optimization to AMP. Must be used in addition of `--amp`.')
     opt = parser.parse_args()
     return opt
 
@@ -125,8 +127,10 @@ def main():
 
     logger.info(opt)
 
+    assert not opt.auto_layout or opt.amp, "--auto-layout needs to be used with --amp"
+
     if opt.amp:
-        amp.init()
+        amp.init(layout_optimization=opt.auto_layout)
 
     batch_size = opt.batch_size
     classes = 1000

scripts/detection/faster_rcnn/train_faster_rcnn.py

@@ -121,6 +121,8 @@ def parse_args():
                         help='Whether to use static memory allocation. Memory usage will increase.')
     parser.add_argument('--amp', action='store_true',
                         help='Use MXNet AMP for mixed precision training.')
+    parser.add_argument('--auto-layout', action='store_true',
+                        help='Add layout optimization to AMP. Must be used in addition of `--amp`.')
     parser.add_argument('--horovod', action='store_true',
                         help='Use MXNet Horovod for distributed training. Must be run with OpenMPI. '
                              '--gpus is ignored when using --horovod.')
@@ -622,8 +624,10 @@ def train(net, train_data, val_data, eval_metric, batch_size, ctx, args):
     # fix seed for mxnet, numpy and python builtin random generator.
     gutils.random.seed(args.seed)
 
+    assert not args.auto_layout or args.amp, "--auto-layout needs to be used with --amp"
+
     if args.amp:
-        amp.init()
+        amp.init(layout_optimization=args.auto_layout)
 
     # training contexts
     if args.horovod:

scripts/detection/ssd/train_ssd.py

@@ -89,6 +89,8 @@ def parse_args():
                         'Currently supports only COCO.')
     parser.add_argument('--amp', action='store_true',
                         help='Use MXNet AMP for mixed precision training.')
+    parser.add_argument('--auto-layout', action='store_true',
+                        help='Add layout optimization to AMP. Must be used in addition of `--amp`.')
     parser.add_argument('--horovod', action='store_true',
                         help='Use MXNet Horovod for distributed training. Must be run with OpenMPI. '
                         '--gpus is ignored when using --horovod.')
@@ -360,8 +362,10 @@ def train(net, train_data, val_data, eval_metric, ctx, args):
 if __name__ == '__main__':
     args = parse_args()
 
+    assert not args.auto_layout or args.amp, "--auto-layout needs to be used with --amp"
+
     if args.amp:
-        amp.init()
+        amp.init(layout_optimization=args.auto_layout)
 
     if args.horovod:
         hvd.init()

scripts/detection/yolo/train_yolo3.py

@@ -97,6 +97,8 @@ def parse_args():
     parser.add_argument('--label-smooth', action='store_true', help='Use label smoothing.')
     parser.add_argument('--amp', action='store_true',
                         help='Use MXNet AMP for mixed precision training.')
+    parser.add_argument('--auto-layout', action='store_true',
+                        help='Add layout optimization to AMP. Must be used in addition of `--amp`.')
     parser.add_argument('--horovod', action='store_true',
                         help='Use MXNet Horovod for distributed training. Must be run with OpenMPI. '
                         '--gpus is ignored when using --horovod.')
@@ -325,8 +327,10 @@ def train(net, train_data, val_data, eval_metric, ctx, args):
 if __name__ == '__main__':
     args = parse_args()
 
+    assert not args.auto_layout or args.amp, "--auto-layout needs to be used with --amp"
+
     if args.amp:
-        amp.init()
+        amp.init(layout_optimization=args.auto_layout)
 
     if args.horovod:
         if hvd is None:

scripts/instance/mask_rcnn/train_mask_rcnn.py

@@ -124,6 +124,8 @@ def parse_args():
                         help='Whether to use static memory allocation. Memory usage will increase.')
     parser.add_argument('--amp', action='store_true',
                         help='Use MXNet AMP for mixed precision training.')
+    parser.add_argument('--auto-layout', action='store_true',
+                        help='Add layout optimization to AMP. Must be used in addition of `--amp`.')
     parser.add_argument('--horovod', action='store_true',
                         help='Use MXNet Horovod for distributed training. Must be run with OpenMPI. '
                              '--gpus is ignored when using --horovod.')
@@ -700,8 +702,10 @@ def train(net, train_data, val_data, eval_metric, batch_size, ctx, logger, args)
     # fix seed for mxnet, numpy and python builtin random generator.
     gutils.random.seed(args.seed)
 
+    assert not args.auto_layout or args.amp, "--auto-layout needs to be used with --amp"
+
     if args.amp:
-        amp.init()
+        amp.init(layout_optimization=args.auto_layout)
 
     # training contexts
     if args.horovod:

scripts/segmentation/train.py

@@ -8,6 +8,7 @@
 import mxnet as mx
 from mxnet import gluon, autograd
 from mxnet.gluon.data.vision import transforms
+from mxnet.contrib import amp
 
 import gluoncv
 gluoncv.utils.check_version('0.6.0')
@@ -93,6 +94,11 @@ def parse_args():
     # synchronized Batch Normalization
     parser.add_argument('--syncbn', action='store_true', default=False,
                         help='using Synchronized Cross-GPU BatchNorm')
+    # performance related
+    parser.add_argument('--amp', action='store_true',
+                        help='Use MXNet AMP for mixed precision training.')
+    parser.add_argument('--auto-layout', action='store_true',
+                        help='Add layout optimization to AMP. Must be used in addition of `--amp`.')
     # the parser
     args = parser.parse_args()
 
@@ -200,7 +206,11 @@ def __init__(self, args, logger):
                 v.wd_mult = 0.0
 
         self.optimizer = gluon.Trainer(self.net.module.collect_params(), 'sgd',
-                                       optimizer_params, kvstore=kv)
+                                       optimizer_params, kvstore=(False if args.amp else None))
+
+
+        if args.amp:
+            amp.init_trainer(trainer)
         # evaluation metrics
         self.metric = gluoncv.utils.metrics.SegmentationMetric(trainset.num_class)
 
@@ -212,7 +222,11 @@ def training(self, epoch):
                 outputs = self.net(data.astype(args.dtype, copy=False))
                 losses = self.criterion(outputs, target)
                 mx.nd.waitall()
-                autograd.backward(losses)
+                if args.amp:
+                    with amp.scale_loss(losses, self.optimizer) as scaled_losses:
+                        autograd.backward(scaled_losses)
+                else:
+                    autograd.backward(losses)
             self.optimizer.step(self.args.batch_size)
             for loss in losses:
                 train_loss += np.mean(loss.asnumpy()) / len(losses)
@@ -252,7 +266,10 @@ def save_checkpoint(net, args, epoch, mIoU, is_best=False):
 
 if __name__ == "__main__":
     args = parse_args()
+    assert not args.auto_layout or args.amp, "--auto-layout needs to be used with --amp"
 
+    if args.amp:
+        amp.init(layout_optimization=args.auto_layout)
     # build logger
     filehandler = logging.FileHandler(os.path.join(args.save_dir, args.logging_file))
     streamhandler = logging.StreamHandler()