Resnet Basic Block

class BasicBlock(nn.Module):
  # see https://pytorch.org/docs/0.4.0/_modules/torchvision/models/resnet.html
  def __init__(self, inplanes, planes, stride=1):
    super(BasicBlock, self).__init__()
    self.conv1 = nn.Conv2d(inplanes, planes, kernel_size=3, stride=stride, padding=1, bias=False)
    self.bn1 = nn.BatchNorm2d(planes)
    self.relu = nn.ReLU(inplace=True)
    self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, padding=1, bias=False)
    self.bn2 = nn.BatchNorm2d(planes)

  def forward(self, x):
    residual = x
    out = self.conv1(x)
    out = self.bn1(out)
    out = self.relu(out)
    out = self.conv2(out)
    out = self.bn2(out)
    out += residual
    out = self.relu(out)
    return out