update benchmark

dygraph/benchmark/deeplabv3p.py

@@ -19,7 +19,8 @@ from paddle.fluid.dygraph.parallel import ParallelEnv
 
 from dygraph.datasets import DATASETS
 import dygraph.transforms as T
-from dygraph.models import MODELS
+#from dygraph.models import MODELS
+from dygraph.cvlibs import manager
 from dygraph.utils import get_environ_info
 from dygraph.utils import logger
 from dygraph.core import train
@@ -33,7 +34,7 @@ def parse_args():
         '--model_name',
         dest='model_name',
         help='Model type for training, which is one of {}'.format(
-            str(list(MODELS.keys()))),
+            str(list(manager.MODELS.components_dict.keys()))),
         type=str,
         default='UNet')
 
@@ -161,18 +162,15 @@ def main(args):
         eval_dataset = None
         if args.do_eval:
             eval_transforms = T.Compose(
-                [T.Resize(args.input_size),
+                [T.Padding((2049, 1025)),
                  T.Normalize()])
             eval_dataset = dataset(
                 dataset_root=args.dataset_root,
                 transforms=eval_transforms,
                 mode='val')
 
-        if args.model_name not in MODELS:
-            raise Exception(
-                '`--model_name` is invalid. it should be one of {}'.format(
-                    str(list(MODELS.keys()))))
-        model = MODELS[args.model_name](num_classes=train_dataset.num_classes)
+        model = manager.MODELS[args.model_name](
+            num_classes=train_dataset.num_classes)
 
         # Creat optimizer
         # todo, may less one than len(loader)
@@ -195,7 +193,6 @@ def main(args):
             save_dir=args.save_dir,
             iters=args.iters,
             batch_size=args.batch_size,
-            pretrained_model=args.pretrained_model,
             resume_model=args.resume_model,
             save_interval_iters=args.save_interval_iters,
             log_iters=args.log_iters,

dygraph/benchmark/hrnet.py

@@ -19,7 +19,8 @@ from paddle.fluid.dygraph.parallel import ParallelEnv
 
 from dygraph.datasets import DATASETS
 import dygraph.transforms as T
-from dygraph.models import MODELS
+#from dygraph.models import MODELS
+from dygraph.cvlibs import manager
 from dygraph.utils import get_environ_info
 from dygraph.utils import logger
 from dygraph.core import train
@@ -33,7 +34,7 @@ def parse_args():
         '--model_name',
         dest='model_name',
         help='Model type for training, which is one of {}'.format(
-            str(list(MODELS.keys()))),
+            str(list(manager.MODELS.components_dict.keys()))),
         type=str,
         default='UNet')
 
@@ -166,11 +167,9 @@ def main(args):
                 transforms=eval_transforms,
                 mode='val')
 
-        if args.model_name not in MODELS:
-            raise Exception(
-                '`--model_name` is invalid. it should be one of {}'.format(
-                    str(list(MODELS.keys()))))
-        model = MODELS[args.model_name](num_classes=train_dataset.num_classes)
+        model = manager.MODELS[args.model_name](
+            num_classes=train_dataset.num_classes,
+            pretrained_model=args.pretrained_model)
 
         # Creat optimizer
         # todo, may less one than len(loader)
@@ -193,7 +192,6 @@ def main(args):
             save_dir=args.save_dir,
             iters=args.iters,
             batch_size=args.batch_size,
-            pretrained_model=args.pretrained_model,
             resume_model=args.resume_model,
             save_interval_iters=args.save_interval_iters,
             log_iters=args.log_iters,

dygraph/models/__init__.py

@@ -14,38 +14,5 @@
 
 from .architectures import *
 from .unet import UNet
-from .hrnet import *
 from .deeplab import *
 from .fcn import *
-
-# MODELS = {
-#     "UNet": UNet,
-#     "HRNet_W18_Small_V1": HRNet_W18_Small_V1,
-#     "HRNet_W18_Small_V2": HRNet_W18_Small_V2,
-#     "HRNet_W18": HRNet_W18,
-#     "HRNet_W30": HRNet_W30,
-#     "HRNet_W32": HRNet_W32,
-#     "HRNet_W40": HRNet_W40,
-#     "HRNet_W44": HRNet_W44,
-#     "HRNet_W48": HRNet_W48,
-#     "HRNet_W60": HRNet_W48,
-#     "HRNet_W64": HRNet_W64,
-#     "SE_HRNet_W18_Small_V1": SE_HRNet_W18_Small_V1,
-#     "SE_HRNet_W18_Small_V2": SE_HRNet_W18_Small_V2,
-#     "SE_HRNet_W18": SE_HRNet_W18,
-#     "SE_HRNet_W30": SE_HRNet_W30,
-#     "SE_HRNet_W32": SE_HRNet_W30,
-#     "SE_HRNet_W40": SE_HRNet_W40,
-#     "SE_HRNet_W44": SE_HRNet_W44,
-#     "SE_HRNet_W48": SE_HRNet_W48,
-#     "SE_HRNet_W60": SE_HRNet_W60,
-#     "SE_HRNet_W64": SE_HRNet_W64,
-#     "DeepLabV3P": DeepLabV3P,
-#     "deeplabv3p_resnet101_vd": deeplabv3p_resnet101_vd,
-#     "deeplabv3p_resnet101_vd_os8": deeplabv3p_resnet101_vd_os8,
-#     "deeplabv3p_resnet50_vd": deeplabv3p_resnet50_vd,
-#     "deeplabv3p_resnet50_vd_os8": deeplabv3p_resnet50_vd_os8,
-#     "deeplabv3p_xception65_deeplab": deeplabv3p_xception65_deeplab,
-#     "deeplabv3p_mobilenetv3_large": deeplabv3p_mobilenetv3_large,
-#     "deeplabv3p_mobilenetv3_small": deeplabv3p_mobilenetv3_small
-# }

dygraph/train.py

@@ -19,7 +19,6 @@ from paddle.fluid.dygraph.parallel import ParallelEnv
 
 from dygraph.datasets import DATASETS
 import dygraph.transforms as T
-#from dygraph.models import MODELS
 from dygraph.cvlibs import manager
 from dygraph.utils import get_environ_info
 from dygraph.utils import logger