The in_features used in the tutorial represent the number of input features to the last linear layer.
Based on your code snippet it seems that the last activations are calculated in:
        bbox_regressions = torch.cat([self.BboxHead[i](feature) for i, feature in enumerate(features)], dim=1)
        classifications = torch.cat([self.ClassHead[i](feature) for i, feature in enumerate(features)],dim=1)
        ldm_regressions = torch.cat([self.LandmarkHead[i](feature) for i, feature in enumerate(features)], dim=1)

so you would most likely want to either replace these modules or the last layer(s) inside each of these modules.