| 22 | |
| 23 | |
| 24 | class BasicBlock(nn.Module): |
| 25 | expansion = 1 |
| 26 | |
| 27 | def __init__(self, inplanes, planes, stride=1, downsample=None, dilation=1): |
| 28 | super(BasicBlock, self).__init__() |
| 29 | self.conv1 = conv3x3(inplanes, planes, stride, dilation) |
| 30 | self.bn1 = nn.BatchNorm2d(planes) |
| 31 | self.relu = nn.ReLU(inplace=True) |
| 32 | self.conv2 = conv3x3(planes, planes) |
| 33 | self.bn2 = nn.BatchNorm2d(planes) |
| 34 | self.downsample = downsample |
| 35 | self.stride = stride |
| 36 | |
| 37 | def forward(self, x): |
| 38 | residual = x |
| 39 | |
| 40 | out = self.conv1(x) |
| 41 | out = self.bn1(out) |
| 42 | out = self.relu(out) |
| 43 | |
| 44 | out = self.conv2(out) |
| 45 | out = self.bn2(out) |
| 46 | |
| 47 | if self.downsample is not None: |
| 48 | residual = self.downsample(x) |
| 49 | |
| 50 | out += residual |
| 51 | out = self.relu(out) |
| 52 | |
| 53 | return out |
| 54 | |
| 55 | |
| 56 | class Bottleneck(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected