code: def replicate_first_beam(self, tensor, mask, beam_size: int):
      tensor = tensor.view(-1, beam_size, tensor.size(-1))
      tensor[mask] = tensor[mask][:, :1, :]
      return tensor.view(-1, tensor.size(-1))
  
imports: import math
  from typing import Dict, List, Optional
  from omegaconf.listconfig import ListConfig
  from omegaconf.dictconfig import DictConfig
  import torch
  import torch.nn
  from fairseq.models import FairseqIncrementalDecoder
  from torch import Tensor
  from fairseq.ngram_repeat_block import NGramRepeatBlock
  from .multichannel_search import ContiguousMultichannelBeamSearch
  from fairseq.models.speech_dlm import SpeechDLM
label_desc: Use image node_id 7 for calling the MultichannelSequenceGenerator obj's underlying member method code with example usage: obj.replicate_first_beam(tensor, mask, beam_size) and returns: tensor