| 30 | |
| 31 | |
| 32 | class BasicBlock(nn.Module): |
| 33 | expansion = 1 |
| 34 | |
| 35 | def __init__(self, inplanes, planes, stride=1, downsample=None): |
| 36 | super(BasicBlock, self).__init__() |
| 37 | self.conv1 = conv3x3(inplanes, planes, stride) |
| 38 | self.bn1 = nn.BatchNorm2d(planes) |
| 39 | self.relu = nn.ReLU(inplace=True) |
| 40 | self.conv2 = conv3x3(planes, planes) |
| 41 | self.bn2 = nn.BatchNorm2d(planes) |
| 42 | self.downsample = downsample |
| 43 | self.stride = stride |
| 44 | |
| 45 | def forward(self, x): |
| 46 | residual = x |
| 47 | |
| 48 | out = self.conv1(x) |
| 49 | out = self.bn1(out) |
| 50 | out = self.relu(out) |
| 51 | |
| 52 | out = self.conv2(out) |
| 53 | out = self.bn2(out) |
| 54 | |
| 55 | if self.downsample is not None: |
| 56 | residual = self.downsample(x) |
| 57 | |
| 58 | out += residual |
| 59 | out = self.relu(out) |
| 60 | |
| 61 | return out |
| 62 | |
| 63 | |
| 64 | class Bottleneck(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected