docstr: Computation pipeline based on a LLAMA2.
          
docstr_tok: ["Computation","pipeline","based","on","a","LLAMA2","."]
code: def compute_forward(self, batch, stage):
      """Computation pipeline based on a LLAMA2."""
      # Get required data from batch
      batch = batch.to(self.device)
      input_ids, _ = batch.input_ids
  
      # Forward Pass
      padding_mask = ~self.hparams.padding_mask(
          input_ids, pad_idx=tokenizer.pad_token_id
      )
      outputs = self.modules.llama2_model(
          input_ids, padding_mask
      ).logits
  
      return outputs
  
file_path: speechbrain/recipes/MultiWOZ/response_generation/llama2/train_with_llama2.py
imports: import sys
  import speechbrain
  import torch
  from itertools import chain
  from hyperpyyaml import load_hyperpyyaml
  from speechbrain.utils.distributed import run_on_main
  import math
  from speechbrain.dataio.batch import PaddedBatch
label_desc: Use image node_id 1 for calling the ResGenBrain obj's underlying member method code with example usage: obj.compute_forward(batch, stage) and returns: outputs