Add depth for ResNetC5 in some configs (#2655)

configs/faster_rcnn_r101_1x.yml

@@ -25,6 +25,7 @@ ResNet:
   freeze_at: 2
 
 ResNetC5:
+  depth: 101
   norm_type: affine_channel
 
 RPNHead:

configs/faster_rcnn_r50_1x.yml

@@ -25,6 +25,7 @@ ResNet:
   freeze_at: 2
 
 ResNetC5:
+  depth: 50
   norm_type: affine_channel
 
 RPNHead:

configs/faster_rcnn_r50_2x.yml

@@ -25,6 +25,7 @@ ResNet:
   freeze_at: 2
 
 ResNetC5:
+  depth: 50
   norm_type: affine_channel
 
 RPNHead:

configs/faster_rcnn_r50_vd_1x.yml

@@ -26,6 +26,7 @@ ResNet:
   variant: d
 
 ResNetC5:
+  depth: 50
   norm_type: affine_channel
   variant: d
 

configs/mask_rcnn_r50_1x.yml

@@ -28,6 +28,7 @@ ResNet:
   freeze_at: 2
 
 ResNetC5:
+  depth: 50
   norm_type: affine_channel
 
 RPNHead:

configs/mask_rcnn_r50_2x.yml

@@ -29,6 +29,7 @@ ResNet:
   freeze_at: 2
 
 ResNetC5:
+  depth: 50
   norm_type: affine_channel
 
 RPNHead:

ppdet/utils/checkpoint.py

@@ -183,7 +183,8 @@ def load_and_fusebn(exe, prog, path):
                         [scale_name, bias_name, mean_name, variance_name])
 
     if not bn_in_path:
-        raise ValueError("The model in path {} has not params of batch norm.")
+        raise ValueError("There is no params of batch norm in model {}.".format(
+            path))
 
     # load running mean and running variance on cpu place into global scope.
     place = fluid.CPUPlace()