code: def encode_text(self, text, add_special_tokens=False):
      text_token_ids = self.tokenizer(
          text,
          return_tensors="pt",
          add_special_tokens=add_special_tokens,
      ).input_ids.to(self.device)
      text_embeds = self.internlm_model.model.embed_tokens(
          text_token_ids
      )
      return text_embeds
  
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 7 for calling the InternLMXComposerForCausalLM obj's underlying member method code with example usage: obj.encode_text(text, add_special_tokens) and returns: text_embeds