code: def generator(self, src_tokens, src_seq_len, first):
      batch_size = src_tokens.size(0)
      past_key_values = (
          self.get_prompt(batch_size) if self.use_prompt else None
      )
      attention_mask = seq_to_mask(
          src_seq_len, max_len=src_tokens.size(1)
      )
      encoder_outputs, hidden_states = self.prompt_encoder(
          src_tokens,
          attention_mask=attention_mask,
          past_key_values=past_key_values,
      )
      prompt_state = PromptBartState(
          encoder_outputs,
          attention_mask,
          past_key_values,
          src_tokens,
          first,
          hidden_states[0],
          self.bart_config.preseqlen,
      )
  
      return prompt_state
  
imports: import torch
  from torch import nn
  from torch.nn import functional
  from transformers.models.bart.configuration_bart import BartConfig
  from .modeling_bart import BartModel
  from ..utils.util import avg_token_embeddings, seq_to_mask, get_model_device
  from functools import partial
  from typing import Union
label_desc: Use image node_id 3 for calling the PromptBartModel obj's underlying member method code with example usage: obj.generator(src_tokens, src_seq_len, first) and returns: prompt_state