Protect against dangerous default value. (#268)

* Protect against dangerous default value.

* Added comments.

mmpose/models/backbones/cpm.py

@@ -1,3 +1,5 @@
+import copy
+
 import torch
 import torch.nn as nn
 from mmcv.cnn import ConvModule, constant_init, normal_init
@@ -75,6 +77,8 @@ def __init__(self,
                  middle_channels=32,
                  num_stages=6,
                  norm_cfg=dict(type='BN', requires_grad=True)):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super().__init__()
 
         assert in_channels == 3

mmpose/models/backbones/hourglass.py

@@ -1,3 +1,5 @@
+import copy
+
 import torch.nn as nn
 from mmcv.cnn import ConvModule, constant_init, normal_init
 from torch.nn.modules.batchnorm import _BatchNorm
@@ -28,6 +30,8 @@ def __init__(self,
                  stage_channels,
                  stage_blocks,
                  norm_cfg=dict(type='BN', requires_grad=True)):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super().__init__()
 
         self.depth = depth
@@ -119,6 +123,8 @@ def __init__(self,
                  stage_blocks=(2, 2, 2, 2, 2, 4),
                  feat_channel=256,
                  norm_cfg=dict(type='BN', requires_grad=True)):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super().__init__()
 
         self.num_stacks = num_stacks

mmpose/models/backbones/hrnet.py

@@ -1,3 +1,5 @@
+import copy
+
 import torch.nn as nn
 from mmcv.cnn import (build_conv_layer, build_norm_layer, constant_init,
                       normal_init)
@@ -26,6 +28,9 @@ def __init__(self,
                  with_cp=False,
                  conv_cfg=None,
                  norm_cfg=dict(type='BN')):
+
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super().__init__()
         self._check_branches(num_branches, num_blocks, in_channels,
                              num_channels)
@@ -269,6 +274,8 @@ def __init__(self,
                  norm_eval=False,
                  with_cp=False,
                  zero_init_residual=False):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super().__init__()
         self.extra = extra
         self.conv_cfg = conv_cfg

mmpose/models/backbones/mobilenet_v2.py

@@ -1,3 +1,4 @@
+import copy
 import logging
 
 import torch.nn as nn
@@ -38,6 +39,9 @@ def __init__(self,
                  norm_cfg=dict(type='BN'),
                  act_cfg=dict(type='ReLU6'),
                  with_cp=False):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
+        act_cfg = copy.deepcopy(act_cfg)
         super().__init__()
         self.stride = stride
         assert stride in [1, 2], f'stride must in [1, 2]. ' \
@@ -131,6 +135,9 @@ def __init__(self,
                  act_cfg=dict(type='ReLU6'),
                  norm_eval=False,
                  with_cp=False):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
+        act_cfg = copy.deepcopy(act_cfg)
         super().__init__()
         self.widen_factor = widen_factor
         self.out_indices = out_indices

mmpose/models/backbones/mobilenet_v3.py

@@ -1,3 +1,4 @@
+import copy
 import logging
 
 import torch.nn as nn
@@ -70,6 +71,8 @@ def __init__(self,
                  frozen_stages=-1,
                  norm_eval=False,
                  with_cp=False):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super().__init__()
         assert arch in self.arch_settings
         for index in out_indices:

mmpose/models/backbones/regnet.py

@@ -1,3 +1,5 @@
+import copy
+
 import numpy as np
 import torch.nn as nn
 from mmcv.cnn import build_conv_layer, build_norm_layer
@@ -98,6 +100,8 @@ def __init__(self,
                  norm_eval=False,
                  with_cp=False,
                  zero_init_residual=True):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super(ResNet, self).__init__()
 
         # Generate RegNet parameters first

mmpose/models/backbones/resnet.py

@@ -1,3 +1,5 @@
+import copy
+
 import torch.nn as nn
 import torch.utils.checkpoint as cp
 from mmcv.cnn import (ConvModule, build_conv_layer, build_norm_layer,
@@ -42,6 +44,8 @@ def __init__(self,
                  with_cp=False,
                  conv_cfg=None,
                  norm_cfg=dict(type='BN')):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super().__init__()
         self.in_channels = in_channels
         self.out_channels = out_channels
@@ -157,6 +161,8 @@ def __init__(self,
                  with_cp=False,
                  conv_cfg=None,
                  norm_cfg=dict(type='BN')):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super().__init__()
         assert style in ['pytorch', 'caffe']
 
@@ -336,6 +342,8 @@ def __init__(self,
                  norm_cfg=dict(type='BN'),
                  downsample_first=True,
                  **kwargs):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         self.block = block
         self.expansion = get_expansion(block, expansion)
 
@@ -493,6 +501,8 @@ def __init__(self,
                  norm_eval=False,
                  with_cp=False,
                  zero_init_residual=True):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super().__init__()
         if depth not in self.arch_settings:
             raise KeyError(f'invalid depth {depth} for resnet')

mmpose/models/backbones/scnet.py

@@ -1,3 +1,5 @@
+import copy
+
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -29,6 +31,8 @@ def __init__(self,
                  pooling_r,
                  conv_cfg=None,
                  norm_cfg=dict(type='BN', momentum=0.1)):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
         super().__init__()
 
         assert in_channels == out_channels

mmpose/models/backbones/shufflenet_v1.py

@@ -1,3 +1,4 @@
+import copy
 import logging
 
 import torch
@@ -52,6 +53,9 @@ def __init__(self,
                  norm_cfg=dict(type='BN'),
                  act_cfg=dict(type='ReLU'),
                  with_cp=False):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
+        act_cfg = copy.deepcopy(act_cfg)
         super().__init__()
         self.in_channels = in_channels
         self.out_channels = out_channels
@@ -184,6 +188,9 @@ def __init__(self,
                  act_cfg=dict(type='ReLU'),
                  norm_eval=False,
                  with_cp=False):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
+        act_cfg = copy.deepcopy(act_cfg)
         super().__init__()
         self.stage_blocks = [4, 8, 4]
         self.groups = groups

mmpose/models/backbones/shufflenet_v2.py

@@ -1,3 +1,4 @@
+import copy
 import logging
 
 import torch
@@ -36,6 +37,9 @@ def __init__(self,
                  norm_cfg=dict(type='BN'),
                  act_cfg=dict(type='ReLU'),
                  with_cp=False):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
+        act_cfg = copy.deepcopy(act_cfg)
         super().__init__()
         self.stride = stride
         self.with_cp = with_cp
@@ -159,6 +163,9 @@ def __init__(self,
                  act_cfg=dict(type='ReLU'),
                  norm_eval=False,
                  with_cp=False):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
+        act_cfg = copy.deepcopy(act_cfg)
         super().__init__()
         self.stage_blocks = [4, 8, 4]
         for index in out_indices:

mmpose/models/backbones/utils/inverted_residual.py

@@ -1,3 +1,5 @@
+import copy
+
 import torch.nn as nn
 import torch.utils.checkpoint as cp
 from mmcv.cnn import ConvModule
@@ -45,6 +47,9 @@ def __init__(self,
                  norm_cfg=dict(type='BN'),
                  act_cfg=dict(type='ReLU'),
                  with_cp=False):
+        # Protect mutable default arguments
+        norm_cfg = copy.deepcopy(norm_cfg)
+        act_cfg = copy.deepcopy(act_cfg)
         super().__init__()
         self.with_res_shortcut = (stride == 1 and in_channels == out_channels)
         assert stride in [1, 2]