code: def forward_momentum(self, x):
      features = self.backbone_momentum(x).flatten(start_dim=1)
      encoded = self.projection_head_momentum(features)
      return encoded
  
file_path: lightly/examples/pytorch/smog.py
imports: import copy
  import torch
  import torchvision
  from sklearn.cluster import KMeans
  from torch import nn
  from lightly.models import utils
  from lightly.models.modules.heads import SMoGPredictionHead, SMoGProjectionHead, SMoGPrototypes
  from lightly.models.modules.memory_bank import MemoryBankModule
  from lightly.transforms.smog_transform import SMoGTransform
label_desc: Use image node_id 6 for calling the SMoGModel obj's underlying member method code with example usage: obj.forward_momentum(x) and returns: encoded