1x1 convolution with padding
(in_channels, out_channels, module_name, postfix, stride=1, groups=1, kernel_size=1, padding=0)
| 134 | |
| 135 | |
| 136 | def conv1x1(in_channels, out_channels, module_name, postfix, stride=1, groups=1, kernel_size=1, padding=0): |
| 137 | """1x1 convolution with padding""" |
| 138 | return [ |
| 139 | ( |
| 140 | f"{module_name}_{postfix}/conv", |
| 141 | nn.Conv2d( |
| 142 | in_channels, |
| 143 | out_channels, |
| 144 | kernel_size=kernel_size, |
| 145 | stride=stride, |
| 146 | padding=padding, |
| 147 | groups=groups, |
| 148 | bias=False, |
| 149 | ), |
| 150 | ), |
| 151 | (f"{module_name}_{postfix}/norm", nn.BatchNorm2d(out_channels)), |
| 152 | (f"{module_name}_{postfix}/relu", nn.ReLU(inplace=True)), |
| 153 | ] |
| 154 | |
| 155 | |
| 156 | class Hsigmoid(nn.Module): |