Inheritance diagram for fastreid.modeling.backbones.resnest.Bottleneck:
Public Member Functions | |
| __init__ (self, inplanes, planes, bn_norm, with_ibn=False, stride=1, downsample=None, radix=1, cardinality=1, bottleneck_width=64, avd=False, avd_first=False, dilation=1, is_first=False, rectified_conv=False, rectify_avg=False, dropblock_prob=0.0, last_gamma=False) | |
| forward (self, x) | |
Public Attributes | |
| conv1 | |
| bn1 | |
| dropblock_prob | |
| radix | |
| avd | |
| avd_first | |
| avd_layer | |
| conv2 | |
| bn2 | |
| conv3 | |
| bn3 | |
| relu | |
| downsample | |
| dilation | |
| stride | |
Static Public Attributes | |
| int | expansion = 4 |
Detailed Description
ResNet Bottleneck
Definition at line 43 of file resnest.py.
Constructor & Destructor Documentation
◆ __init__()
| fastreid.modeling.backbones.resnest.Bottleneck.__init__ | ( | self, | |
| inplanes, | |||
| planes, | |||
| bn_norm, | |||
| with_ibn = False, | |||
| stride = 1, | |||
| downsample = None, | |||
| radix = 1, | |||
| cardinality = 1, | |||
| bottleneck_width = 64, | |||
| avd = False, | |||
| avd_first = False, | |||
| dilation = 1, | |||
| is_first = False, | |||
| rectified_conv = False, | |||
| rectify_avg = False, | |||
| dropblock_prob = 0.0, | |||
| last_gamma = False ) |
Definition at line 49 of file resnest.py.
53 dropblock_prob=0.0, last_gamma=False):
54 super(Bottleneck, self).__init__()
55 group_width = int(planes * (bottleneck_width / 64.)) * cardinality
56 self.conv1 = nn.Conv2d(inplanes, group_width, kernel_size=1, bias=False)
57 if with_ibn:
58 self.bn1 = IBN(group_width, bn_norm)
59 else:
60 self.bn1 = get_norm(bn_norm, group_width)
61 self.dropblock_prob = dropblock_prob
62 self.radix = radix
63 self.avd = avd and (stride > 1 or is_first)
64 self.avd_first = avd_first
65
66 if self.avd:
67 self.avd_layer = nn.AvgPool2d(3, stride, padding=1)
68 stride = 1
69
70 if radix > 1:
71 self.conv2 = SplAtConv2d(
72 group_width, group_width, kernel_size=3,
73 stride=stride, padding=dilation,
74 dilation=dilation, groups=cardinality, bias=False,
75 radix=radix, rectify=rectified_conv,
76 rectify_avg=rectify_avg,
77 norm_layer=bn_norm,
78 dropblock_prob=dropblock_prob)
79 elif rectified_conv:
80 from rfconv import RFConv2d
81 self.conv2 = RFConv2d(
82 group_width, group_width, kernel_size=3, stride=stride,
83 padding=dilation, dilation=dilation,
84 groups=cardinality, bias=False,
85 average_mode=rectify_avg)
86 self.bn2 = get_norm(bn_norm, group_width)
87 else:
88 self.conv2 = nn.Conv2d(
89 group_width, group_width, kernel_size=3, stride=stride,
90 padding=dilation, dilation=dilation,
91 groups=cardinality, bias=False)
92 self.bn2 = get_norm(bn_norm, group_width)
93
94 self.conv3 = nn.Conv2d(
95 group_width, planes * 4, kernel_size=1, bias=False)
96 self.bn3 = get_norm(bn_norm, planes * 4)
97
98 if last_gamma:
99 from torch.nn.init import zeros_
100 zeros_(self.bn3.weight)
101 self.relu = nn.ReLU(inplace=True)
102 self.downsample = downsample
103 self.dilation = dilation
104 self.stride = stride
105
Member Function Documentation
◆ forward()
| fastreid.modeling.backbones.resnest.Bottleneck.forward | ( | self, | |
| x ) |
Definition at line 106 of file resnest.py.
106 def forward(self, x):
107 residual = x
108
109 out = self.conv1(x)
110 out = self.bn1(out)
111 if self.dropblock_prob > 0.0:
112 out = self.dropblock1(out)
113 out = self.relu(out)
114
115 if self.avd and self.avd_first:
116 out = self.avd_layer(out)
117
118 out = self.conv2(out)
119 if self.radix == 1:
120 out = self.bn2(out)
121 if self.dropblock_prob > 0.0:
122 out = self.dropblock2(out)
123 out = self.relu(out)
124
125 if self.avd and not self.avd_first:
126 out = self.avd_layer(out)
127
128 out = self.conv3(out)
129 out = self.bn3(out)
130 if self.dropblock_prob > 0.0:
131 out = self.dropblock3(out)
132
133 if self.downsample is not None:
134 residual = self.downsample(x)
135
136 out += residual
137 out = self.relu(out)
138
139 return out
140
141
Member Data Documentation
◆ avd
| fastreid.modeling.backbones.resnest.Bottleneck.avd |
Definition at line 63 of file resnest.py.
◆ avd_first
| fastreid.modeling.backbones.resnest.Bottleneck.avd_first |
Definition at line 64 of file resnest.py.
◆ avd_layer
| fastreid.modeling.backbones.resnest.Bottleneck.avd_layer |
Definition at line 67 of file resnest.py.
◆ bn1
| fastreid.modeling.backbones.resnest.Bottleneck.bn1 |
Definition at line 58 of file resnest.py.
◆ bn2
| fastreid.modeling.backbones.resnest.Bottleneck.bn2 |
Definition at line 86 of file resnest.py.
◆ bn3
| fastreid.modeling.backbones.resnest.Bottleneck.bn3 |
Definition at line 96 of file resnest.py.
◆ conv1
| fastreid.modeling.backbones.resnest.Bottleneck.conv1 |
Definition at line 56 of file resnest.py.
◆ conv2
| fastreid.modeling.backbones.resnest.Bottleneck.conv2 |
Definition at line 71 of file resnest.py.
◆ conv3
| fastreid.modeling.backbones.resnest.Bottleneck.conv3 |
Definition at line 94 of file resnest.py.
◆ dilation
| fastreid.modeling.backbones.resnest.Bottleneck.dilation |
Definition at line 103 of file resnest.py.
◆ downsample
| fastreid.modeling.backbones.resnest.Bottleneck.downsample |
Definition at line 102 of file resnest.py.
◆ dropblock_prob
| fastreid.modeling.backbones.resnest.Bottleneck.dropblock_prob |
Definition at line 61 of file resnest.py.
◆ expansion
|
static |
Definition at line 47 of file resnest.py.
◆ radix
| fastreid.modeling.backbones.resnest.Bottleneck.radix |
Definition at line 62 of file resnest.py.
◆ relu
| fastreid.modeling.backbones.resnest.Bottleneck.relu |
Definition at line 101 of file resnest.py.
◆ stride
| fastreid.modeling.backbones.resnest.Bottleneck.stride |
Definition at line 104 of file resnest.py.
The documentation for this class was generated from the following file:
- smreid/fastreid/modeling/backbones/resnest.py
