class_docstr: MaskedLinearSeq, but with more outputs than inputs and in a different order.
class_docstr_tok: ["MaskedLinearSeq",",","but","with","more","outputs","than","inputs","and","in","a","different","order","."]
code: def forward(self, x, mask):
      dup = x.clone().detach() * 1.38  # just an arbitrary scaling
      x, mask = super().forward(x, mask)
      return dup, x, mask
  
imports: import pytest
  import torch
  import deepspeed
  from deepspeed.accelerator import get_accelerator
  from copy import deepcopy
  from unit.common import DistributedTest
label_desc: Use image node_id 1 for calling the MaskedLinearSeqDup obj's underlying member method code with example usage: obj.forward(x, mask) and returns: dup,  x,  mask