change Normally to Default in the docstring of backbones (#2937)

mmdet/models/backbones/hrnet.py

@@ -200,7 +200,7 @@ class HRNet(nn.Module):
 
     Args:
         extra (dict): detailed configuration for each stage of HRNet.
-        in_channels (int): Number of input image channels. Normally 3.
+        in_channels (int): Number of input image channels. Default: 3.
         conv_cfg (dict): dictionary to construct and config conv layer.
         norm_cfg (dict): dictionary to construct and config norm layer.
         norm_eval (bool): Whether to set norm layers to eval mode, namely,

mmdet/models/backbones/regnet.py

@@ -23,7 +23,7 @@ class RegNet(ResNet):
             - bot_mul (float): bottleneck ratio, i.e. expansion of bottlneck.
         strides (Sequence[int]): Strides of the first block of each stage.
         base_channels (int): Base channels after stem layer.
-        in_channels (int): Number of input image channels. Normally 3.
+        in_channels (int): Number of input image channels. Default: 3.
         dilations (Sequence[int]): Dilation of each stage.
         out_indices (Sequence[int]): Output from which stages.
         style (str): `pytorch` or `caffe`. If set to "pytorch", the stride-two

mmdet/models/backbones/res2net.py

@@ -243,8 +243,8 @@ class Res2Net(ResNet):
         scales (int): Scales used in Res2Net. Default: 4
         base_width (int): Basic width of each scale. Default: 26
         depth (int): Depth of res2net, from {50, 101, 152}.
-        in_channels (int): Number of input image channels. Normally 3.
-        num_stages (int): Res2net stages, normally 4.
+        in_channels (int): Number of input image channels. Default: 3.
+        num_stages (int): Res2net stages. Default: 4.
         strides (Sequence[int]): Strides of the first block of each stage.
         dilations (Sequence[int]): Dilation of each stage.
         out_indices (Sequence[int]): Output from which stages.

mmdet/models/backbones/resnet.py

@@ -290,8 +290,8 @@ class ResNet(nn.Module):
 
     Args:
         depth (int): Depth of resnet, from {18, 34, 50, 101, 152}.
-        in_channels (int): Number of input image channels. Normally 3.
-        num_stages (int): Resnet stages, normally 4.
+        in_channels (int): Number of input image channels. Default: 3.
+        num_stages (int): Resnet stages. Default: 4.
         strides (Sequence[int]): Strides of the first block of each stage.
         dilations (Sequence[int]): Dilation of each stage.
         out_indices (Sequence[int]): Output from which stages.

mmdet/models/backbones/resnext.py

@@ -89,8 +89,8 @@ class ResNeXt(ResNet):
 
     Args:
         depth (int): Depth of resnet, from {18, 34, 50, 101, 152}.
-        in_channels (int): Number of input image channels. Normally 3.
-        num_stages (int): Resnet stages, normally 4.
+        in_channels (int): Number of input image channels. Default: 3.
+        num_stages (int): Resnet stages. Default: 4.
         groups (int): Group of resnext.
         base_width (int): Base width of resnext.
         strides (Sequence[int]): Strides of the first block of each stage.