Hello! I’m training a ResNet and i get this error:
out += residual
RuntimeError: The size of tensor a (16) must match the size of tensor b (32) at non-singleton dimension 3
this is my code:
class ResidualBlock(nn.Module):
expansion = 1
def __init__(self, in_channels, out_channels, stride=1, downsample=None):
super(ResidualBlock, self).__init__()
self.conv1 = conv3x3(in_channels, out_channels, stride)
self.bn1 = nn.BatchNorm2d(out_channels)
self.relu = nn.ReLU(inplace=True)
self.conv2 = conv3x3(out_channels, out_channels)
self.bn2 = nn.BatchNorm2d(out_channels)
self.downsample = downsample
self.shortcut = nn.Sequential()
if stride != 1 or in_channels != self.expansion * out_channels:
self.shortcut = nn.Sequential(conv3x3(in_channels, out_channels, stride),
nn.BatchNorm2d(self.expansion * out_channels))
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)
if self.downsample:
residual = self.downsample(x)
out += residual
out = self.relu(out)
return out
I don’t understand what’s wrong.