class_docstr: MobileNet v1 implementation. This model
  can be instantiated from a pretrained network.
code: def forward(self, x, latent_input=None, return_lat_acts=False):
      if latent_input is not None:
          with torch.no_grad():
              orig_acts = self.lat_features(x)
          lat_acts = torch.cat((orig_acts, latent_input), 0)
      else:
          orig_acts = self.lat_features(x)
          lat_acts = orig_acts
  
      x = self.end_features(lat_acts)
      x = x.view(x.size(0), -1)
      logits = self.output(x)
  
      if return_lat_acts:
          return logits, orig_acts
      else:
          return logits
  
file_path: avalanche/avalanche/models/mobilenetv1.py
imports: from typing import List
  import torch.nn
  import torch
  from pytorchcv.models.mobilenet import mobilenet_w1
label_desc: Use image node_id 2 for calling the MobilenetV1 obj's underlying member method code with example usage: obj.forward(x, latent_input, return_lat_acts) and returns: logits,  orig_acts, logits