class_docstr: Fine-tuning wrapper for action segmentation.
code: def forward(
      self, caps, cmasks, vfeats, vmasks, attention_mask=None, **kwargs
  ):
      # ActionLocalization assume of batch_size=1, squeeze it.
      caps = caps.view(-1, caps.size(-1))
      cmasks = cmasks.view(-1, cmasks.size(-1))
      vfeats = vfeats.view(-1, vfeats.size(2), vfeats.size(3))
      vmasks = vmasks.view(-1, vmasks.size(-1))
      logits = self.forward_video(
          vfeats, vmasks, caps, cmasks, output_hidden_states=True
      )
      return {"logits": logits[:, 1 : vmasks.size(1) + 1]}
  
imports: import torch
  from torch import nn
  from .None import transformermodel
label_desc: Use image node_id 1 for calling the MMFusionSeparateActionSegmentation obj's underlying member method code with example usage: obj.forward(caps, cmasks, vfeats, vmasks, attention_mask) and returns: dict