activation after each FC layer in TopNet

[CuiRuikai]

class MLP(nn.Module):
    def __init__(self, dims,  bn=None):
        super().__init__()
        self.model = nn.Sequential()
        for i, num_channels in enumerate(dims[:-2]):
            self.model.add_module('fc_%d' % (i+1), nn.Linear(num_channels, dims[i+1]))
        self.bn = bn
        if self.bn:
            self.batch_norm = nn.BatchNorm1d(dims[-2])
        self.output_layer = nn.Linear(dims[-2], dims[-1])

    def forward(self, features):
        features = self.model(features)
        if self.bn:
            features = self.batch_norm(features)
        features = F.relu(features)
        outputs = self.output_layer(features)
        return outputs

for this implementation, it looks that there's no activation function after each fc layer. There is only one activation at the end