class_docstr: a MMPT wrapper class for MMBert style models.
  TODO: move isolated mask to a subclass.
code: def _make_iso_mask(self, batch_size, cmasks, vmasks):
      cls_self_mask = torch.cat(
          [
              torch.ones(
                  (batch_size, 1),
                  dtype=torch.bool,
                  device=cmasks.device,
              ),
              torch.zeros(
                  (batch_size, cmasks.size(1) + vmasks.size(1) - 1),
                  dtype=torch.bool,
                  device=cmasks.device,
              ),
          ],
          dim=1,
      )
  
      iso_video_mask = torch.cat(
          [
              # [CLS] is not used.
              torch.zeros(
                  (batch_size, 1),
                  dtype=torch.bool,
                  device=cmasks.device,
              ),
              vmasks,
              # assume to be 1.
              cmasks[:, 1:2],
              # 2 means [CLS] + [SEP]
              torch.zeros(
                  (batch_size, cmasks.size(1) - 2),
                  dtype=torch.bool,
                  device=cmasks.device,
              ),
          ],
          dim=1,
      )
      iso_text_mask = torch.cat(
          [
              torch.zeros(
                  (batch_size, 2 + vmasks.size(1)),
                  dtype=torch.bool,
                  device=cmasks.device,
              ),  # [CLS] is not used.
              cmasks[:, 2:],  # assume to be 1.
          ],
          dim=1,
      )
      cls_self_mask = cls_self_mask[:, None, :]
      iso_video_mask = iso_video_mask[:, None, :].repeat(
          1, vmasks.size(1) + 1, 1
      )
      iso_text_mask = iso_text_mask[:, None, :].repeat(
          1, cmasks.size(1) - 2, 1
      )
      return torch.cat(
          [cls_self_mask, iso_video_mask, iso_text_mask], dim=1
      )
  
imports: import torch
  from torch import nn
  from .None import transformermodel
label_desc: Use image node_id 5 for calling the MMFusion obj's underlying member method code with example usage: obj._make_iso_mask(batch_size, cmasks, vmasks) and returns: torch