code: def decode_text(self, out_embeds):
      out_text = self.tokenizer.batch_decode(
          out_embeds, skip_special_tokens=True
      )[0]
      out_text = out_text.split(self.eoa)[0]
      return out_text
  
imports: import copy
  import os
  import sys
  import contextlib
  import torch.utils.checkpoint
  from torch.nn import LayerNorm
  from torchvision import transforms
  from torchvision.transforms.functional import InterpolationMode
  from PIL import Image
  from .modeling_perceive_sampler import BertConfig, BertLMHeadModel
  from .modeling_vit import *
  from .modeling_InternLM import *
  from .modeling_utils import *
  from transformers.utils import logging
label_desc: Use image node_id 8 for calling the InternLMXComposerForCausalLM obj's underlying member method code with example usage: obj.decode_text(out_embeds) and returns: out_text